Hansen, Hans R. Man-Machine Communication and ... UR-83-33 Mo, Olav. Stochastic Time Domain Analysis of ...... Finn-Idar Grøtta Giske. Long-Term Extreme ...
Minjoo Choi
Modular Adaptable Ship Design for Handling Uncertainty in the Future Operating Context
Thesis for the degree of Philosophiae Doctor
Trondheim, September 2018 Norwegian University of Science and Technology Faculty of Engineering Department of MarineTechnology
NTNU Norwegian University of Science and Technology Thesis for the degree of Philosophiae Doctor Faculty of Engineering Department of MarineTechnology
© Minjoo Choi ISBN 978-82-326-3318-0 (printed version) ISBN 978-82-326-3319-7 (electronic version) ISSN 1503-8181
Doctoral theses at NTNU, 2018:264 Printed by Skipnes Kommunikasjon as
Abstract A ship's value is dependent on its context as well as its design features. Ship designers therefore need to consider future operating context scenarios for designing a value-robust ship. The context of a ship comprises a variety of factors and their complex behavior makes the prediction difficult. For handling such contextual uncertainty, ship designers often consider extra functions and capabilities. However, the increased CAPEX and OPEX due to the extra capabilities can be a significant threat to stakeholders if the need is not realized in the future operating context. The design of modular adaptable ships is an alternative approach that aims to mitigate the risk of the conventional robust approach. In fact, modularization is not a new concept in the field of ship design. It has received attention for efficient ship design and manufacturing. However, the modules of modular adaptable ships are used for fast and affordable ship conversion in the operation phase. The prime benefit is that the relative independence of modules allows decision makers to postpone investment in the extra capabilities until more information is available. There are available approaches to module based synthesis and lifecycle evaluation for ships. However, the approaches to module based synthesis are based on a given fixed set of functional requirements. This underestimates the value of operational flexibility of modular designs. On the other hand, the approaches to lifecycle evaluation are based on a given set of design alternatives. To bridge the gap, this thesis presents optimization methods that support decision makers in determining the best modular solution considering the value of operational flexibility in the uncertain future operating context. The case studies that demonstrate the methods show that operational flexibility can mitigate risks in early design decisions and the value of flexible designs is highly dependent on how to use their flexibility. This configuration change of a modular adaptable ship is based on its operation platform, which i
is a set of common modules that are shared by multiple configurations. The design of an operation platform is challenging due to the conflicting requirements of multiple missions and the interface decisions that affect the level of flexibility of the operation platform. For the operation platform design problem, this thesis presents an optimization model that determines the optimal platform design that best meets the desired capabilities of multiple missions while considering its expected lifecycle cost. The presented model is implemented in a case study that shows that the design results provide insights into the design problem, so that designer can improve the design further.
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Preface This thesis is submitted to the Norwegian University of Science and Technology (NTNU) for partial fulfillment of the requirements for the degree of philosophiae doctor. The work has been performed at the Department of Marine Technology, NTNU, Trondheim with Professor Stein Ove Erikstad as the main supervisor and Professor Bjørn Egil Asbjørnslett as the co-supervisor. The research was supported by the by the Research Council of Norway and industrial partners, Ulstein and DNV GL, through the Research Council of Norway (RCN) 233996, “SIMOSYS”. This thesis is divided into two parts: a main thesis and a compilation of papers. The first part of the thesis provides the context of this thesis work, which includes the research motivation, objective, questions, scope, and limitations. The first part presents methods that deal with the research questions, and provides the main results. The second part comprises the publications as the results of the research.
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Acknowledgements (English) There are people who helped me finish this PhD work successfully. I would like to thank my main supervisor, Professor Stein Ove Erikstad, and co-supervisor Professor Bjørn Egil Asbjørnslett. Their guidance enabled me to have more insights into the research problems and develop the research ideas further to be more concrete and realistic. I would like to thank my colleagues and friends. I was happy to have Carl, Sigurd, and Jose who have conducted PhD research in a same project. In my new workplace, SINTEF digital, the daily conversation with Daniel was a great help when I was struggling to write this thesis. I really appreciate the emotional support of Amalie. One of the most grateful things which I gained during my PhD period is that I could meet her. The special thank is given to my family. The dedication of my parents enables me to focus on this PhD work and their cheerful messages are the energy for me to keep moving forward.
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Acknowledgements (Korean) 박사과정도 이제 끝이 보입니다. 뒤돌아 보니 힘들었던 순간도 많았지만 그보단 즐거웠던 순간이 더 많았던 것 같습니다. 제가 이렇게 학위과정에 몰두하고 스스 로의 발전에만 집중 할 수 있었던 건, 부모님의 정신적 물질적 지원과 힘들 때 옆에서 힘을 주었던 친구들 및 지인들 덕일 것입니다. 너무나 신세진 사람들이 많아 일일이 감사를 표현 할 수 없지만, 그 분들 모두에게 감사드립니다. 특히,박 사과정 동안 저와 많은 시간을 함께했던 성필이 형, 웅식이, 대성이, 구섭이 형, 태 환이 형, 영민이, 또한 새로운 환경 오슬로에 적응하는데 큰 도움이 된 주송이, 병 규, 윤성이 모두 고맙습니다. 그리고 이런 좋은 자리에, 저라는 사람을 믿고 기회 를 주신 Erikstad 교수님 Asbjørnslett 교수님, 그리고 석사졸업 후에도 항상 좋은 말 씀 주시는 정현 교수님께도 감사의 말을 드립니다.
박사과정을 시작할 때, 논문을 위한 연구가 아닌 세상에 도움이 될 수 있는 실용 적인 연구를 하자고 다짐하였습니다. 따라서, 연구방향에 대해 끊임없이 고민하고 동료들과 의견을 나눴습니다. 그 결과물로 세 편의 논문을 저널에 게재하였습니 다. 앞으로 개선해야 하는 부분이 아직 많이 남았지만 제 연구 결과가 누군가에 게 도움이 될 수 있기를 희망합니다. 저 또한 역시, 이번 연구에서 부족했던 부분 들을 계속 발전시켜 나갈 계획입니다.
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정말 연구가 너무나도 좋았던 시간들이 있었습니다. 새로운 배움을 위해 노력하 는 스스로의 모습이 자랑스러웠고 그 배움의 과정이 너무나도 즐거웠습니다. 하 지만, 요즘은 점점 연구를 ‘하고 싶은 일’ 보다는 ‘해야만 하는 일’ 로 여기고 있 는 것은 아닌지 생각이 듭니다. 그리고 가슴 뛰는 설렘이 아닌 현실적인 조건을 우선순위로 의사결정을 하는 일이 잦아졌습니다. 하지만, 이번을 계기로 초심을 되찾고 본능에 충실한 연구자가 될 수 있도록 노력하겠습니다. 박사라는 호칭은 사회적 책임을 동반한다고 생각합니다. 부와 명예를 좇아 양심을 저버리는 행동 을 하지 않고, 더 나은 세상을 만드는 것에 힘쓰는 연구자가 되겠습니다.
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Abbreviations AIMS
architectures, interfaces and modular systems
CAPEX
capital expenditures
CBL
cable laying
CFD
computational fluid dynamics
CTO
configure-to-order
DBB
design building blocks
DCF
discounted-cash-flow
DP
dynamic positioning
DS
diving support
DWT
deadweight tonnage
FEM
finite element method
GA
genetic algorithm
GM
metacentric height
GP
goal programming
IMR
inspection, maintenance, and repair
LPP
longest path problem
LWI
light well intervention
MAS
modular adaptable ship
NPV
net present value
NPVI
net present value index
OBS
optimization based simulation
OCI
offshore construction and installation
OPEX
operating expenses
OSV
offshore support vessel ix
PS
platform supply
ROA
real options analysis
ROV
remotely operated vehicle
RQ
research question
SBO
simulation based optimization
SEAMOD
sea systems modification and modernization by modularity
S-O
simulation-optimization
UML
unified modeling language
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List of figures Figure 1: Oil prices predicted by IMF in 2011 and the real oil prices. ............................ 2 Figure 2: History of modular adaptable ship development (Abbott et al. 2008). ............ 3 Figure 3(a): Swiss army knife. ....................................................................................... 7 Figure 3(b): Inflexible multi-purpose ship. .................................................................... 7 Figure 4(a): Evolutionary acquisition. ...........................................................................
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Figure 4(b): Conventional ship acquisition. ..................................................................
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Figure 5: Mission flexibility by modularity. ..................................................................
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Figure 6: Four types of modularity defined by Salvador et al. (2002). ........................... 11 Figure 7: Design as mapping between the functional domain and physical domain. ..... 12 Figure 8: Ship design projects in the configure-to-order strategy. .................................. 13 Figure 9: Illustration of the rolling horizon process. ...................................................... 18 Figure 10: Simulation based optimization and optimization based simulation. ............. 19 Figure 11: Relationship between the RQs and journal papers in the MAS design process. ........................................................................................................................... 21 Figure 12: Graph representation of a single contract scenario. ........................................ 23 Figure 13: Conceptual illustration of the proposed hybrid simulation-optimization method. ........................................................................................................................... 28 Figure 14: Main bodies and modules used in this case study. .......................................... 29 Figure 15: Chromosome representation scheme of main body 2. .................................... 29 Figure 16: Identified design alternatives during the optimization process. ..................... 30 Figure 17: Design alternatives without considering vessel reconfiguration. ................... 31 Figure 18: Comparison results with different scheduling horizon sizes. ......................... 32 Figure 19: Description of ship modules, slots, and task-related modules using a class diagram in the unified modeling language. ..................................................................... 33 Figure 20: Comparison between the inflexible design and flexible design in multiple missions. ......................................................................................................................... 37 xi
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List of tables Table 1: Common types of options (Perlitz et al., 1999). ................................................. 15 Table 2: Description of module capabilities. ................................................................... 23
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Contents Abstract.......................................................................................................................
ⅰ
Preface......................................................................................................................... ⅲ Acknowledgements.....................................................................................................
ⅴ
Abbreviations..............................................................................................................
ⅸ
List of figures............................................................................................................... ⅹⅰ List of tables................................................................................................................
ⅹⅲ
1.
1
2.
Introduction........................................................................................................ 1.1.
Research motivation.................................................................................. 1
1.2.
Research objective and questions.............................................................. 4
1.3.
Research scope and limitations.................................................................. 5
Background........................................................................................................ 2.1.
Modularity for handling contextual uncertainty......................................... 7
2.1.1.
Passive approach vs. active approach............................................... 7
2.1.2.
The effect of modularity on ship lifecycle......................................... 8
2.1.3.
Modularity type................................................................................
2.2.
10
Modular adaptable ship design.................................................................. 12
2.2.1.
Design synthesis and analysis........................................................... 12
2.2.2.
Module based design process: configure-to-order process............... 13
2.2.3.
Product platform vs. operation platform........................................... 14
2.2.4.
Real options analysis for lifecycle evaluation of flexible designs..... 15
2.3.
3.
7
Optimization and simulation in ship design............................................... 16
2.3.1.
Optimization for design synthesis in ship design.............................. 16
2.3.2.
Goal programming for multi-objective optimization problems........ 17
2.3.3.
Rolling horizon process in ship operation simulation....................... 17
2.3.4.
Hybrid simulation optimization........................................................ 18
Summary of work............................................................................................... 21 3.1.
Research contributions..............................................................................
3.2.
Summary of papers.................................................................................... 22
3.2.1.
Summary of paper 1: A module configuration and valuation model xv
21
for operational flexibility in ship design using contract scenarios.... 22 3.2.2.
Summary of paper 2: A hybrid method for a module configuration problem in modular adaptable ship design....................................... 27
3.2.3.
Summary of paper 3: Operation platform design for modular adaptable ships: Towards the configure-to-order strategy................ 32
4.
Conclusions........................................................................................................
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References...................................................................................................................
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Appendix A: Papers..................................................................................................... 45 Paper 1: A module configuration and valuation model for operational flexibility in ship design using contract scenarios.................................................. 47 Paper 2: A hybrid method for a module configuration problem in modular adaptable ship design............................................................................................. 59 Paper 3: Operation platform design for modular adaptable ships: Towards the configure-to-order strategy.....................................................................................
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Appendix B: Previous PhD theses............................................................................... 85
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1. Introduction
1.1 Research motivation As Simon (1969) addresses, the value of an artificial system is determined by its context as well as its design characteristics. The value of a car, for instance, is dependent on its contextual factors (e.g. market trend, fuel price, and regulations) as well as its design characteristics (e.g. as size, speed, fuel efficiency, power, and color). Therefore, to design a value-robust system, which can maintain its value over the lifecycle, both design characteristics and contextual factors should be considered together in the design process. The context of ships can be defined by economic, technological, regulatory, and physical factors (Erikstad and Rehn 2015). These factors are highly uncertain and the prediction is challenging. For instance, the sharp drop in oil prices in 2014 was an example of the uncertainty. The low oil prices made the demand of offshore activities decreased, which in turn had a negative effect on the market rate significantly. Experts had predicted oil prices based on various quantitative and qualitative analyses, but most failed in predicting the low oil price scenario. Figure 1 illustrates an example of the failure of the prediction. This compares the real oil prices with the prediction by IMF in 2011 (Benes et al. 2015), where even an increased oil price scenario was predicted.
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Figure 1. Oil prices predicted by IMF in 2011 and the real oil prices. Modular adaptable ship (MAS) design is an approach to handling such contextual uncertainty in ship design. This considers modularity in operation, which enables a ship to be changeable; thus, equipment can be retrofitted and different missions can be taken to maximize the value throughout the lifecycle. This active approach differs from the traditional passive and inflexible approaches, which do not consider ship reconfiguration in operation. There have been various projects for MAS development in the maritime industry since the German shipyard Blohm+Voss developed the first MAS in the late 1970s. The Royal Danish Navy developed MASs at Standard Flex concept in the 1980’s. In this concept, the weapons, sensors, and other mission systems were containerized for flexible configuration, and the ship configuration was determined based on the given tasks (Bertram 2005). The U.S. Navy has developed MAS technology since 1975 through a series of programs from the SEAMOD (Sea Systems Modification and Modernization by Modularity) program to the AIMS (Architectures, Interfaces and Modular Systems) program. The history of MAS development is well illustrated in Figure 2 (Abbott et al. 2008).
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Figure 2. History of modular adaptable ship development (Abbott et al. 2008). Several technical papers (Marcantonio et al. 2007; Abbott et al. 2008; Doerry 2014) were recently published through the U.S navy's programs. In these papers, the authors discuss important issues on MAS development, such as designing an interface standard and determining the proper degree of modularity. Doerry (2014) investigates state-of-the-art technology related to MAS development and finds that there is lack of design method to consider the potential effect of modularity on the lifecycle value of MASs, although hardware and software technologies are already sufficiently mature based on the previous programs. For modular ships, there are available design synthesis approaches using a given static context, and lifecycle evaluation approaches for a given design towards a dynamic operating context. For instance, the design building blocks (DBB) (Andrews 2011) and the packing approach (Van Oers 2011) create design alternatives based on independent chunks, which are referred to as ‘blocks’ or ‘objects’. Such bottom-up approaches can be applied to the design of modular ships, allowing for fast validation and visualization from the early stages of design; thus, rework can be avoided and ship designers and stakeholders gain more insight into the design results. Real options analysis (ROA) has often been applied to the lifecycle evaluation of flexible ships. For instance, Gregor (2003) and Page (2011) apply ROA to a naval vessel design and acquisition process, and Bendall and Stent (2005) use ROA to evaluate vessel investment strategies. Sødal 3
et al. (2007) use ROA to determine the economic value of the flexibility provided by an orebulk-oil carrier as opposed to using a specialized bulk carrier and an oil tanker. However, to investigate a large number of modular designs and evaluate them without underestimating their value, the two different problems, 1) module configuration and 2) lifecycle evaluation, should be combined into one design problem, where design alternatives are created through module configuration and the best design is selected based on lifecycle evaluation.
1.2 Research objective and questions The prime objective of this thesis is to develop quantitative design methods for MASs. The methods support ship designers in identifying design alternatives and selecting the best design based on lifecycle evaluation. The lifecycle evaluation takes into account the economic value of operational flexibility of modular designs under uncertain future operating contexts. The research objective is achieved by answering the following research questions (RQs): RQ1
How can we integrate module based design synthesis and lifecycle evaluation into a design problem?
RQ2
How can we consider contextual uncertainty in evaluating the lifecycle value of MAS designs?
RQ3
How can we design modules for MASs in a systematic and efficient way?
In this thesis, the design process of MASs is broken down into two tasks: 1) module design and 2) module configuration. RQ 3 is related to the module design and RQ 1 and 2 are related to the module configuration.
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1.3 Research scope and limitations - This thesis work focuses on developing design methods for MASs. The design methods comprise optimization models for making design and operational decisions and simulation methods for evaluating flexible designs in a detailed manner. - In module design, this thesis work focuses on designing platform modules on which a variety of task-related modules operate, assuming that the task-related modules are provided by thirdparty vendors. - In module configuration, it is assumed that there is a static list of task-related modules. Future modules that will be available in the future operating context are not considered. - In scenario generation, it is assumed that the stochastic property of contextual uncertainty is known.
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2. Background
2.1. Modularity for handling contextual uncertainty
2.1.1. Passive approach vs. active approach In engineering systems design, there are various approaches to handling contextual uncertainty. According to Ross and Rhodes (2008), the approaches can be categorized as ‘passive’ or ‘active’ approaches. The ‘versatile design’ is an example of the passive approach, in which extra capabilities and functions are considered for future opportunities. The ‘Swiss army knife’ in Figure 3(a) is an example. It is a pocketknife having multiple tools, such as a can opener, small screwdriver, scissor, and blade. In many cases, the customers do not know if they need all the tools, but they believe that the tools will create value in the future.
Figure 3(a). Swiss army knife.
Figure 3(b). Inflexible multi-purpose ship.
In a maritime case, inflexible multi-purpose ships can be examples of versatile design. Figure 3(b) describes an offshore support vessel (OSV) that can be used for light well intervention 7
(LWI) and diving support (DS) missions, using a variety of task-related systems, such as a multi-purpose tower, saturated system, cranes, and remotely operated vehicles (ROVs). This multifunctional ship enables its owner to have wider options in contract selection, and its value is less sensitive to the market condition compared with that of dedicated ships for the individual mission. In active approaches, design changeability is investigated for handling contextual uncertainty. For instance, ‘changeable design’, ‘flexible design’, ‘adaptable design’, and ‘scalable design’ are active approaches. The ability can be implemented by modularization and standardization, and enables designers to delay investment decisions on the extra capabilities and functions until more information is available in the operation phase. One can ask “which approach is more appropriate for handling contextual uncertainty?” The answer can differ depending on the case, because both passive and active approaches have their own advantages and disadvantages. Although the active approaches can mitigate risks in initial design decisions, the design change of flexible systems requires a certain amount of time to have the extra capabilities and functions. Therefore, there can be a time gap between the demand and supply. On the other hand, the versatile systems are always ready for serving all functions. Thus, their response to new demands can be faster than that of flexible systems. However, some of the extra functions may not be used throughout the lifetime. In the maritime sector, this can be a significant threat to stakeholders, because the acquisition cost of marine systems are relatively expensive than that of daily products. Thus, the extra systems can only increase the capital expenditures (CAPEX) significantly. Moreover, the extra systems increase the operating expenses (OPEX) as well, such as increased fuel consumption and reduced deck area.
2.1.2. The effect of modularity on ship lifecycle Modularity is a particular design structure, in which parameters and tasks are interdependent within modules and independent across them (Baldwin and Clark 2000). A module is an 8
independent subsystem that can be combinable and separable with/from other modules through standard interfaces. This independence allows for potential benefits throughout the lifecycle of modular ships. Modularity in design enables ship designers to reuse earlier designs and makes structural complexity manageable with simplified representation due to the hidden interactions within modules. This simplification is necessary for holistic approaches to ship design because ship designers have to deal with a large number of subsystems and the conflicting requirements of multiple stakeholders (Papanikolaou, 2010). Modularity in production allows for shorter production time due to the parallel manufacturing and testing of modules. It also improves the efficiency of dry dock operations, which is a shipyard’s most valuable resource, and allows for wider outsourcing options due to the standard interfaces. Modularity in operation allows for ‘evolutionary acquisition’ and ‘mission flexibility’ which are briefly described in Section 2.1.1. Evolutionary acquisition is addressed by Abbott et al. (2003). It is an investment strategy in which decision makers postpone investment decisions for modules waiting for more information available. Evolutionary acquisition can be compared with the conventional ship acquisition process. While all investment decisions are made at the design phase in the conventional acquisition process, the decisions are made over the lifetime in the evolutionary acquisition process. Figure 4(a) and (b) illustrate the difference between the evolutionary acquisition and conventional ship acquisition process.
Figure 4(a). Evolutionary acquisition.
Figure 4(b). Conventional ship acquisition.
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Mission flexibility (or referred to as market flexibility) is an ability to switch the mission. This enables one ship to be used for different missions at different times, and makes the value of the ship insensitive to the change of the operating context. An example of mission flexibility of a modular ship is illustrated in Figure 5.
Figure 5. Mission flexibility by modularity.
2.1.3. Modularity type According to Ulrich (1995), the different interface types of modularity are sectional, bus, and slot modularity. Salvador et al. (2002) further divide slot-type modularity into combinatorial modularity and component-swapping modularity. The four types of modularity can be differentiated from each other based on interface diversity and the use of a main body. Figure 6 illustrates the differences.
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Figure 6. Four types of modularity defined by Salvador et al. (2002). In sectional modularity, modules interface with each other through identical interfaces, whereas in bus modularity, modules interface with a main body using identical interfaces in what is known as a bus interface. In both combinatorial modularity and component-swapping modularity, there is no identical interface that all modules share globally. However, some modules share a common interface locally, which is called a slot. Each module in combinatorial modularity has its own slots and can be connected to other modules that have the same type of slot. Alternatively, in component-swapping modularity, modules interface with a main body through slots. In the design of MASs, component-swapping modularity can be an appropriate type, because the hull serves as the main body on which different module configurations can exist. Component-swapping modularity does not require identical interfaces. Thus, this is a more general case of bus modularity.
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2.2. Modular adaptable ship design
2.2.1. Design synthesis and analysis In engineering systems design, design tasks have been considered as mapping between the functional domain and physical domain. The mapping is an iterative process of design synthesis and analysis as Figure 7 describes.
Figure 7. Design as mapping between the functional domain and physical domain. The dictionary definition of synthesis is “the act of combining different ideas or things to make a whole that is new and different from the items considered separately”. In engineering systems design, the input of design synthesis, ‘the different ideas or things’, can be the functional requirements, alternatives for each design decision, synthesis rules, experience of designers, etc. Based on the input, design synthesis creates a design alternative or a set of design alternatives. In analysis, the design alternative is evaluated from multiple perspectives. In ship design, for instance, the perspectives include economic, operability, capacity, and capability perspectives (Rehn et al. 2018). During the iterative process, designers gain more insight and knowledge, which enables them to do better synthesis. The iterative process is continued until the process meets the termination criteria. The criteria can be, for instance, design quality, a given design time, and the number of design iterations.
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2.2.2. Module based design process: configure-to-order strategy In the conventional ship design process is a top-down process, in which ship designers explore the design space by repeatedly improving options for a benchmark ship, and they determine a design at the end of the process. This process fits to the ‘build-to-order’ strategy, in which a design project begins from A to Z to provide a high-end customized product to each customer. On the other hand, module based design process is a bottom-up process. In this process, design alternatives are created by configuring predeveloped modules and the design characteristics are indirectly determined by the module configuration. This enables the ‘configure-to-order (CTO)’ strategy, in which multiple ship design projects share standard modules that are developed before confirmed orders based on demand forecasting. The CTO process enables a design team to reduce development time and cost, and improve design reliability with proven and tested technologies. Moreover, the rapid prototyping allows for better communication with customers. This is essential to define the ‘right’ key performance indicators of design projects. Figure 8 illustrates ship design projects based on the CTO process.
Figure 8. Ship design projects in the configure-to-order strategy. For instance, ship modules include the main hull, deckhouse, bridge, and tanks and voids, which serve basic functions for ship operation, such as buoyancy, transition, storage, and accommodation. Examples of task-related modules include weapons and sensor systems in navy ship design, as well as topside modules such as well intervention towers, cranes, ROVs, 13
and saturated systems in OSV design. In the CTO strategy, ship design projects can be defined by module configuration, evaluation, and selection to best meet individual customers’ needs.
2.2.3. Product platform vs. operation platform As it is discussed in Section 2.1.3, an MAS can be defined by component-swapping modularity, in which a main body interfaces with add-on modules through slots. In this sense, the ship modules of an MAS serve as the main body, which is referred to as an operation platform in this thesis. In a general context of engineering systems design, the term ‘platform or product platform’ indicates common parts, components, and modules, from which a stream of derivative products can be created efficiently (Meyer and Lehnerd 1997). By using common elements across multiple products, a product platform enables product development to increase its diversity, while maintaining economies of scale. Moreover, a product platform allows for reduced development time and system complexity, reduced development and production costs, and improved ability to upgrade products (Simpson 2004). Because of these advantages, product platform design has received attention in diverse fields of product design and manufacturing (Jiao et al. 2007). However, as Rehn et al. (2018) state, the term product platform and operation platform should be distinguished carefully. While a product platform is a common basis for multiple products for mass customization, an operation platform is a common basis for multiple configurations of a flexible product. In product platform design, one important issue is to determine the level of commonality. In a modular approach, determining the level of commonality is associated with defining platform modules, which are commonly shared by multiple products. Similarly, defining platform modules is an important issue in operation platform design. Although the basic assumption is that ship modules are platform modules, task-related modules also can be platform modules according to their interface. More specifically, if an interface of a task-related module is designed for configuration flexibility in the operation phase, the module is a dedicated module for a specific mission. Otherwise, the module is a platform module as one of the members of the operation platform. In this sense, if all the task-related modules are defined 14
as platform modules (shared by all the module configurations), the ship is versatile ship (or inflexible multi-purpose ship).
2.2.4. Real options analysis for lifecycle evaluation for flexible designs ROA is an evaluation approach, which applies the option pricing models in capital budgeting to real assets. ROA has been used in high-risk investment projects. Discounted-cash-flow (DCF) analysis, typically used for project evaluation, has shown limitations, because it cannot take into account the response of decision makers to new circumstances. Moreover, DCF analysis requires the use of risk-adjusted discount rate, which is determined by adding an expected risk premium to a risk-free discount rate. Thus, it is normally higher than the risk-free discount rate and it is the main source of underestimation of project value (Ho and Liao 2011). ROA makes up for the limitation of DCF analysis. ROA enables the evaluation to consider the value of flexible decision-making in response to the new circumstances, and it does not require the use of risk-adjusted discount rate. Instead, ROA uses a risk-free discount rate which can be determined easily in a project. In ROA, flexibility is represented as a collection of options. This allows for explicit definition of flexibility and quantitative evaluation. In diverse fields, the successful applications of ROA have been reported (Triantis and Borison 2001) and several common types of options have been identified (Perlitz et al. 1999). Table 1 presents the common options. Table 1. Common types of options (Perlitz et al., 1999) Option to wait (or defer)
the right to wait until conditions are favorable to decide to exercise the option
Option to expand
the right to increase the scale of the project
Option to contract
the right to reduce the scale of the project
Option to switch
the right to switch the input or output of the project
Option to abandon
the right to abandon the project before its expected lifetime ends 15
An option can be classified as an independent option or compound option based on its dependence on other options. The value of the independent option is not affected by other options. Thus, each independent option can be evaluated individually. On the other hand, the value of the compound option is dependent on other options. Therefore, compound options should be evaluated together as a group of options. In particular, some compound options are referred to as path-dependent options that are dependent on the history of option exercise of other options. An option can also be categorized as ‘an American option’ or ‘European option’. The option holders of American options can exercise the options at any time before the option expires. On the other hand, the option holders of European options can exercise the options only once at its expiration.
2.3. Optimization and simulation in ship design
2.3.1. Optimization for design synthesis in ship design In engineering systems design, a design can be represented by a set of design variables. The number, type, and range of these variables determine possible design alternatives, which are referred to as 'design space'. In ship design, there are a large number of design alternatives even in the early design stage. The number can increase as the design stage proceeds. This makes it difficult for ship designers to determine the best design. Thus, ship designers are often satisfied with a feasible solution that meets the given requirements rather than the best solution. Optimization enables ship designers to identify promising design alternatives efficiently, so they can determine the best design (or a ‘good enough design’) with less effort. For instance, a genetic algorithm (GA), which is one of the most used algorithms in ship design optimization, creates promising design alternatives by using the information of design alternatives that are created in previous iterations. This certainly improves the efficiency of design space exploration compared with that of exhaustive methods, which investigate all design alternatives.
16
2.3.2. Goal programming for multi-objective optimization problems A goal programming (GP) is an application of linear programming and often used for solving multi-objective problems. Each objective of a GP is represented by a specific goal value and the objective is to minimize the deviation between the goal value and achieved value. The basic formulation of a GP is described in Equations (1) - (4). Here, 𝐱 is the set of decision variables that determine the achieved goal values. A goal is defined by 𝑖 and the set is defined by 𝑆. The negative and positive deviations of 𝑖-th goal are defined by 𝑑𝑖− and 𝑑𝑖+ respectively. These deviations are penalized by weight 𝑊𝑖− and weight 𝑊𝑖+ . According to the weight values, the goal can be defined as a one-sided goal (lower or upper) or two-sided goal (Romero 2004). For instance, if the value of negative weight 𝑊𝑖− or positive weight 𝑊𝑖+ is 0, the 𝑖-th goal is a onesided goal. Equations (2) and (3) define the deviations. The optimal solution satisfies 𝑑𝑖− ∙ 𝑑𝑖+ = 0, which means at least one of the deviations is 0. Equation (4) defines the decision variables. Min
(1)
∑(𝑤𝑖− ∙ 𝑑𝑖− + 𝑤𝑖+ ∙ 𝑑𝑖+ ) 𝑖𝜖𝑆
s.t.
𝑓𝑖 (𝐱) − 𝑑𝑖+ + 𝑑𝑖− = 𝑔𝑖
𝑖𝜖𝑆
(2)
𝑑𝑖− , 𝑑𝑖+
𝑖𝜖𝑆
(3)
𝐅 is a feasible set
(4)
≥0
𝐱𝜖𝐅
2.3.3. Rolling horizon process in ship operation simulation Ship schedules are often made in a rolling horizon manner (Fagerholt et al. 2010). The rolling horizon is an iterative process in which the operating context scenario is gradually revealed and a new schedule is made in response to the new information. This process resembles the actual scheduling situation of ship operators, who often make only short-term schedules because there is high uncertainty in the long-term operating context. An example of the rolling horizon process is illustrated in Figure 9. Each scenario includes a full horizon that comprises 17
a ‘past horizon’, ‘scheduling horizon’, and ‘future horizon’. In an each iteration, the simulation updates these horizons and makes a schedule for the current scheduling horizon. The schedule is made by operational decisions optimization, which determines whether to exercise given options based on the past and scheduling horizon information.
Figure 9. Illustration of the rolling horizon process.
2.3.4. Hybrid simulation optimization A hybrid simulation-optimization (S-O) is a method which literally uses both optimization and simulation together. An S-O can be categorized as simulation based optimization (SBO) or optimization based simulation (OBS) based on the hierarchical structure between the simulation and optimization (Juan et al. 2015). In the case of SBO, optimization is the key driver and simulation acts as an evaluation function in optimization. In comparison to simple calculation, simulation improves the accuracy of the evaluation by mimicking stochastic phenomena in a natural way (Nance and Sargent 2002). Moreover, it allows for accommodating the various distributional properties of uncertain parameters in modeling scenarios (Jung et al. 2004). In the case of OBS, simulation is the key driver and optimization is used to determine the simulation parameters. In contrast to a simple sequential procedure, optimization allows for complex operational and managerial decision support during simulation execution. Figure 10 is an example of SBO and OBS in a design problem.
18
Figure 10. Simulation based optimization and optimization based simulation
19
20
3. Summary of work
3.1. Research contributions The main body of this thesis comprises three journal papers. In this section, the contribution of each paper is presented relating to the RQs. Figure 11 illustrates the relationships in the MAS design process.
Figure 11. Relationship between the RQs and journal papers in the MAS design process. The prime contribution of paper 1 is that this research work integrates the module based design synthesis and lifecycle evaluation into an optimization problem. The proposed model 21
determines the optimal initial module configuration based on the economic value of operational flexibilities. This is associated with RQ 1. The research work of paper 2 is an extended work of paper 1. Paper 2 presents a hybrid method that considers contextual uncertainty in module configuration. This is the prime contribution of paper 2 and associated with RQ 2. In paper 3, the CTO strategy and standard modules are discussed for efficient MAS development, and an optimization model is presented for the design of a standard operation platform for MASs. This is associated with RQ 3.
3.2. Summary of papers
3.2.1. Summary of paper 1: A module configuration and valuation model for operational flexibility in ship design using contract scenarios (Minjoo Choi and Stein Ove Erikstad, 2017, Published in Ship and offshore structures) This paper presents an optimization model for determining the initial module configuration of an MAS. An MAS design is represented by component-swapping modularity and the value of the design is defined by the net present value (NPV), which is expected to be maximized. The capabilities of design alternatives are determined by linear summation of the configured modules’ capabilities. Table 2 provides an example of module capabilities, in which ten types of capabilities are considered and the capability levels are represented on a normalized scale of 0 to 10.
22
Table 2. Description of module capabilities. Capability index (𝑝)
Name
Range (from-to)
Unit
Scaled range (from-to)
1
Crane lifting
0-500
Metric ton
0-10
2
Accommodation
0-250
Person on board
0-10
3
ROV operation
0-3000
Meter
0-10
4
Moonpool size
0-150
Square meter
0-10
5
Power generation
0-18000
kilowatt
0-10
6
Deck space
0-3000
Square meter
0-10
7
DP level
1-3
Level
0-10
8
Light well intervention
0-3000
Meter
0-10
9
Diving support
0-30
Person in saturation
0-10
10
Cable laying
0-10000
Metric ton
0-10
In evaluation, the operational flexibility of MASs is represented as measurable options. More specifically, the economic value of additional module acquisition, ship reconfiguration, and mission switching in the operation phase are taken into account. The market scenario is represented as a set of contracts in the model. The NPV maximization problem using contract scenarios can be considered as the longest path problem (LPP). In the LPP, the contract scenario can be represented as a graph in which each node indicates a contract and each edge indicates a possible contract transition (Erikstad et al. 2011). The length of edges indicates revenue from contracts and it is dependent on predetermined decisions in module investment and configuration. Figure 12 describes an example of a graph of a contract scenario.
Figure 12. Graph representation of a single contract scenario. 𝑛1 and 𝑛2 indicate the starting node and terminating node of the graph, respectively. 23
The optimization model is presented with the sets, parameters, and variables as follows. Sets: 𝐹
Main bodies, indexed by 𝑓
𝑆𝑓
Slots of main body 𝑓, indexed by 𝑠
𝑀𝑓𝑠
Modules of slot 𝑠 of main body 𝑓, indexed by 𝑚 Nodes comprising a starting node (𝑛 = 1), terminating node (𝑛 =
𝑁
2), and other nodes related to contracts (𝑛 = 3, … , |𝑁|), indexed by 𝑛
𝑃
Capabilities, indexed by 𝑝
𝑇
Time periods, indexed by 𝑡
𝑅𝑓𝑛
Revenue of main body 𝑓 from contract 𝑛 operation
𝐶𝑓𝑃𝐴
Acquisition cost of main body 𝑓
Parameters:
𝑀𝐴 𝐶𝑓𝑠𝑚𝑡
𝑀𝑂 𝐶𝑓𝑠𝑚𝑡
𝑀𝐶 𝐶𝑓𝑠𝑚𝑡 𝑀𝑅 𝐶𝑓𝑠𝑚𝑡 𝑅𝐶 𝐶𝑓𝑠𝑖𝑗𝑡
Acquisition cost of module 𝑚 of slot 𝑠 of main body 𝑓 in time period 𝑡 Operation cost of module 𝑚 of slot 𝑠 of main body 𝑓 in time period 𝑡 Configuration cost of module 𝑚 of slot 𝑠 of main body 𝑓 in time period 𝑡 Removal cost of module 𝑚 of slot 𝑠 of main body 𝑓 in time period 𝑡 Reconfiguration cost of module 𝑖 to 𝑗 of slot 𝑠 of main body 𝑓 in time period 𝑡
𝑅 𝑉𝑝𝑛
Required capability 𝑝 for contract 𝑛
𝐴 𝑉𝑓𝑠𝑚𝑝
Achieved capability 𝑝 by module 𝑚 of slot 𝑠 of main body 𝑓
𝐴 𝑉𝑓𝑝
Achieved capability 𝑝 by main body 𝑓
𝑆𝑇𝑛
Starting time period of contract 𝑛
𝑇𝑀𝑛
Terminating time period of contract 𝑛
𝐴𝑖𝑗
1 if node transition from node 𝑖 to 𝑗 is available from a time perspective, 0 otherwise
Variables: 24
1 if main body 𝑓 is used, 0 otherwise
𝑏𝑓
1 if module 𝑚 is assigned to slot 𝑠 of main body 𝑓 in time period 𝑡,
𝑥𝑓𝑠𝑚𝑡
0 otherwise 1 if main body 𝑓 changes its operation from contract 𝑖 to 𝑗, 0
𝑦𝑓𝑖𝑗
otherwise 1 if module 𝑖 of slot 𝑠 of main body 𝑓 is replaced by module 𝑗 in
𝑧𝑓𝑠𝑖𝑗𝑡
time period 𝑡, 0 otherwise 1 if module 𝑚 of slot 𝑠 of main body 𝑓 is invested in in time
𝑘𝑓𝑠𝑚𝑡
period 𝑡, 0 otherwise
Model: max
𝑀𝐴 ∑ ∑ ∑ 𝑅𝑓𝑗 ∙ 𝑦𝑓𝑖𝑗 − ∑ 𝐶𝑓𝑃𝐴 ∙ 𝑏𝑓 − ∑ ∑ ∑ ∑ 𝐶𝑓𝑠𝑚𝑡 ∙ 𝑘𝑓𝑠𝑚𝑡 𝑓𝜖𝐹 𝑖𝜖𝑁 𝑗𝜖𝑁
𝑓𝜖𝐹
(5)
𝑓𝜖𝐹 𝑠𝜖𝑆𝑓 𝑚𝜖𝑀𝑓𝑠 𝑡𝜖𝑇
𝑀𝐶 𝑀𝑂 − ∑ ∑ ∑ 𝐶𝑓𝑠𝑚0 ∙ 𝑥𝑓𝑠𝑚0 − ∑ ∑ ∑ ∑ 𝐶𝑓𝑠𝑚𝑡 ∙ 𝑥𝑓𝑠𝑚𝑡 𝑓𝜖𝐹 𝑠𝜖𝑆𝑓 𝑚𝜖𝑀𝑓𝑠
−∑∑ ∑ ∑
𝑓𝜖𝐹 𝑠𝜖𝑆𝑓 𝑚𝜖𝑀𝑓𝑠 𝑡𝜖𝑇 𝑅𝐶 ∑ 𝐶𝑓𝑠𝑖𝑗𝑡 ∙ 𝑧𝑓𝑠𝑖𝑗𝑡
𝑓𝜖𝐹 𝑠𝜖𝑆𝑓 𝑖𝜖𝑀𝑓𝑠 𝑗𝜖𝑀𝑓𝑠 𝑡𝜖𝑇|𝑡≥1
s.t.
∑ 𝑏𝑓 = 1
(6)
𝑓𝜖𝐹
∑ 𝑥𝑓𝑠𝑚𝑡 = 𝑏𝑓 𝑚𝜖𝑀𝑓𝑠
𝑓𝜖𝐹, 𝑠𝜖𝑆𝑓 , 𝑡𝜖𝑇
(7)
𝑓𝜖𝐹, 𝑠𝜖𝑆𝑓 , 𝑚𝜖𝑀𝑓𝑠 , 𝑡𝜖𝑇
(8)
𝑓𝜖𝐹, 𝑠𝜖𝑆𝑓 , 𝑚𝜖𝑀𝑓𝑠
(9)
𝑡
𝑥𝑓𝑠𝑚𝑡 ≤ ∑ 𝑘𝑓𝑠𝑚𝑖 𝑖=0
∑ 𝑘𝑓𝑠𝑚𝑡 ≤ 𝑏𝑓 𝑡𝜖𝑇
∑ ∑ 𝑦𝑓1𝑗 = 1
(10)
𝑓𝜖𝐹 𝑗𝜖𝑁
∑ ∑ 𝑦𝑓𝑖2 = 1
(11)
𝑓𝜖𝐹 𝑖𝜖𝑁
∑
∑
𝑓𝜖𝐹 𝑖𝜖𝑁|𝑖≠1,2
𝑦𝑓𝑖𝑗 − ∑
∑
𝑦𝑓𝑗𝑖 = 0
𝑗𝜖𝑁
(12)
𝑓𝜖𝐹 𝑖𝜖𝑁|𝑖≠1,2
𝑅 𝐴 𝐴 𝑉𝑝𝑗 ∙ 𝑦𝑓𝑖𝑗 ≤ 𝑉𝑓𝑝 ∙ 𝑏𝑓 + ∑ ∑ 𝑉𝑓𝑠𝑚𝑝 ∙ 𝑥𝑓𝑠𝑚𝑡
𝑓𝜖𝐹, 𝑝𝜖𝑃, 𝑖, 𝑗𝜖𝑁, 𝑡𝜖𝑇|𝑆𝑇𝑗 ≤ 𝑡 ≤ 𝑇𝑀𝑗
𝑠𝜖𝑆𝑓 𝑚𝜖𝑀𝑠𝑓
𝑦𝑓𝑖𝑗 ≤ 𝐴𝑖𝑗
𝑓𝜖𝐹, 𝑖, 𝑗𝜖𝑁
25
(13) (14)
𝑓𝜖𝐹, 𝑠𝜖𝑆, 𝑖, 𝑗𝜖𝑀𝑓𝑠 |𝑖
𝑧𝑓𝑠𝑖𝑗𝑡 ≥ 𝑥𝑓𝑠𝑖(𝑡−1) + 𝑥𝑓𝑠𝑗𝑡 − 1
≠ 𝑗, 𝑡𝜖𝑇|𝑡 > 1 𝑓𝜖𝐹, 𝑠𝜖𝑆𝑓 , 𝑖, 𝑗𝜖𝑀𝑓𝑠 |𝑖
2𝑧𝑓𝑠𝑖𝑗𝑡 ≤ 𝑥𝑓𝑠𝑖(𝑡−1) + 𝑥𝑓𝑠𝑗𝑡
≠ 𝑗, 𝑡𝜖𝑇|𝑡 > 1
(15)
(16)
𝑏𝑓 𝜖{0,1}
𝑓𝜖𝐹
(17)
𝑥𝑓𝑠𝑚𝑡 𝜖{0,1}
𝑓𝜖𝐹, 𝑠𝜖𝑆𝑓 , 𝑚𝜖𝑀𝑓𝑠 , 𝑡𝜖𝑇
(18)
𝑦𝑓𝑖𝑗 𝜖{0,1}
𝑓𝜖𝐹, 𝑖, 𝑗𝜖𝑁
(19)
𝑧𝑓𝑠𝑖𝑗𝑡 𝜖{0,1}
𝑓𝜖𝐹, 𝑠𝜖𝑆𝑓 , 𝑖, 𝑗𝜖𝑀𝑓𝑠 , 𝑡𝜖𝑇
(20)
𝑘𝑓𝑠𝑚𝑡 𝜖{0,1}
𝑓𝜖𝐹, 𝑠𝜖𝑆𝑓 , 𝑚𝜖𝑀𝑓𝑠 , 𝑡𝜖𝑇
(21)
Equation (5) is the objective function. The first term, the aggregation of 𝑅𝑓𝑗 ∙ 𝑦𝑓𝑖𝑗 , indicates revenue from the operation in the contract scenario. The decision variables 𝑦𝑓𝑖𝑗 represent the selected contract. For example, 𝑦𝑓𝑖𝑗 = 1 indicates that contract 𝑖 and contract 𝑗 are selected for operation, and the sequence is from contract 𝑖 to contract 𝑗. The revenue 𝑅𝑓,𝑛 is an adjusted revenue with regard to the operation cost and time value of the selected main body. The revenue 𝑅𝑓2 of the terminating node is zero. The second term, the aggregation of 𝐶𝑓𝑃𝐴 ∙ 𝑏𝑓 , indicates the 𝑀𝐴 main body’s acquisition cost, and the third term, the aggregation of 𝐶𝑓𝑠𝑚𝑡 ∙ 𝑘𝑓𝑠𝑚𝑡 , indicates the 𝑀𝐶 modules’ acquisition cost during the lifetime. The fourth term, the aggregation of 𝐶𝑓𝑠𝑚0 ∙
𝑥𝑓𝑠𝑚0 , indicates the module configuration cost in the initial time period (𝑡 = 0), and the fifth 𝑀𝑂 term, the aggregation of 𝐶𝑓𝑠𝑚𝑡 ∙ 𝑥𝑓𝑠𝑚𝑡 , indicates the module operation cost during the lifetime. 𝑅𝐶 The final term, the aggregation of 𝐶𝑓𝑠𝑖𝑗𝑡 ∙ 𝑧𝑓𝑠𝑖𝑗𝑡 , indicates the ship reconfiguration cost during
the operation time (𝑡 > 0). Equation (6) ensures that only one main body is selected. In the design of multiple ships, the constraint is removed. Equation (7) ensures that every slot of the main body is assigned one module. Empty slots are represented by assigning an empty dummy module to the slots. Equation (8) allows only pre-invested modules to be configured. These constraints are based on the assumption that the module acquisition time is short enough to be neglected. Equation (9) allows modules to be acquired only when their main body is selected. Equation (10) ensures that every solution includes the starting node in the LPP. Equation (11) ensures that every solution includes the terminating node in the LPP. Equation (12) ensures continuity in the LPP. Equation (13) constrains ships to operate during the full contract period when the ships can satisfy the required capabilities of the contracts. Equation (14) allows for 26
only feasible node transition from a time perspective. 𝐴𝑖𝑗 indicates the feasibility of node transition from node 𝑖 to 𝑗 and is defined as 𝐴𝑖𝑗 = 1 if 𝑆𝑇𝑗 > 𝑇𝑀𝑖 , or 0 otherwise. The feasible node transition constraints ensure that a node can be visited only once. Like other nodes, the starting node and terminating node have a starting time period and terminating time period that satisfy 𝑆𝑇𝑛|𝑛≠1 > 𝑇𝑀1 and 𝑇𝑀𝑛|𝑛≠2 < 𝑆𝑇2 . Equations (15) and (16) ensure consistency in the reconfiguration variables. Equations (17) - (21) define the decision variables as binary variables.
3.2.2. Summary of paper 2: A hybrid method for a module configuration problem in modular adaptable ship design (Minjoo Choi, Carl Fredrik Rhen, Stein Ove Erikstad, 2018, Published in Ship and offshore structures) This paper presents an S-O that considers contextual uncertainty in module configuration. The presented method comprises three models that form a hierarchical structure including both SBO and OBS. Figure 13 illustrates the hierarchical structure. The first model is a design optimization model. This is the key driver of the hybrid method and creates promising design alternatives (initial module configurations) by configuring predesigned modules based on the lifecycle value. The second model evaluates the lifecycle value of the design alternatives. This evaluation is carried out by ship operation simulation using a set of given future operating context scenarios. During the simulation run, the third model determines operational decisions to maximize the lifecycle value in a given context.
27
Figure 13. Conceptual illustration of the proposed hybrid simulation-optimization method. The presented method was implemented in a case study, in which we designed a modular adaptable OSV. The objective was to maximize the expected net present value index (NPVI). NPVI was calculated by dividing net present value by lifecycle cost. We considered two main bodies in creating design alternatives. Each main body has slots, and each slot has module alternatives. We assumed that the functional capabilities of design alternatives are determined by aggregating the functional capabilities of the main body and add-on modules. This can be reasonable in the early design stages because a module is a subsystem that performs an independent function. Figure 14 illustrates the main bodies and module alternatives. Each module is either grey or black, which represents whether the module has configuration flexibility in the operation phase. The black modules are combinable and separable in both the design and operation phases, while the grey modules have these options in only the design phase.
28
Figure 14. Main bodies and modules used in this case study. Module E indicates an empty slot.
In the case study, we used a GA for design optimization due to its demonstrated effectiveness in combinatorial optimization problems (Juan et al. 2015). Design alternatives are represented by a vector of genes, which is referred to as a chromosome. Each gene indicates a slot, and its value indicates a selected module for the slot. Figure 15 illustrates the representation scheme for main body 2 and an example design.
Figure 15. Chromosome representation scheme of main body 2. Each operating context scenario is represented as a set of contracts. The stochastic simulation created multiple sets of contracts through Monte Carlo sampling based on the given probability distributions of markets. We considered LWI, DS, cable laying (CBL), and inspection, maintenance, and repair (IMR) markets, with the contract value and time window defined as uncertain factors. We assumed a vessel lifetime of 20 years and that all contracts exist in a discrete time domain of 20 periods. The simulation generated a common set of 30 contract 29
scenarios for evaluation, and each scenario includes an average of 60 contracts. As an optimization model for making operational decisions, we used the optimization model, which is presented in paper 1. Although the model is for the design of an MAS, it was used for scheduling in the rolling horizon process in this paper. The prime difference is the decisionmaking scope. Although the original model makes both design and operational decisions, the model was used for making only operational decisions. That is contract selection, additional module acquisition, and vessel reconfiguration. In the case study, the GA created and evaluates 147 design alternatives (without repetition) during the optimization process. Figure 16 shows the design alternatives, which are sorted in descending order and each assigned a design number. The design number indicates the rank according to the objective value. For instance, design number 5 has the fifth highest objective value. We describe the designs using different marks based on the main body. The green squares indicate the designs created based on main body 1, and the red triangles indicate the designs created based on main body 2. In Figure 16, one interesting observation is that the objective values of the flexible designs are highly dependent on the selected main body. The worst design of main body 2 has a better objective value than even the best design of main body 1.
Figure 16. Identified design alternatives during the optimization process. We investigated the designs in more detail by conducting two ‘what-if question’ analyses. The 30
first question is ‘what if the designs do not have reconfiguration options?’ In this analysis, the designs have a 15% cost reduction in vessel development instead of reconfiguration options. This advantage is given because enabling an option often has a price. Figure 17 shows the results of the analysis, where the line is the initial objective value shown in Figure 16. In spite of the reduced development cost, the objective value of most of the designs dramatically decreases. Surprisingly, this happens more clearly to the designs of main body 2, which are considered as ‘good designs’ with the reconfiguration options. If we consider designs with a negative value as ‘infeasible designs’, more infeasible designs can be created based on main body 2. This occurs because main body 2 is a multi-purpose platform that leverages the vessel reconfiguration options actively but has higher acquisition and operation costs. Hence, the fixed design constraints can be more influential on the designs of main body 2.
Figure 17. Design alternatives without considering vessel reconfiguration. Another question is ‘what if the scheduling horizon size becomes bigger or smaller?’ For the analysis, we evaluated the designs with different scheduling horizon sizes. Additionally, we considered sizes 2, 4, and 20 and compare them with the initial size of 3. Figure 18 illustrates the comparison results. Size 20 is the condition where all contract information is fully known in scheduling. The comparison shows a relatively big difference in the designs of main body 2. On the other hand, the designs of main body 1 are insensitive to the change of the scheduling horizon size. This may occur because the more options of main body 2 enable leveraging the 31
horizon information more effectively.
Figure 18. Comparison results with different scheduling horizon sizes.
3.2.3. Summary of paper 3: Operation platform design for modular adaptable ships: Towards the configure-to-order strategy (Minjoo Choi, Stein Ove Erikstad, Hyun Chung, 2018, Published in Ocean Engineering) In this paper, we present an optimization model for the design of a standard operation platform for MASs. It is assumed that ship modules are used as platform modules and task-related modules can be defined as platform modules or add-on modules according to their slot. The property of a slot, which indicates the different level of support for task-related modules and their configuration flexibility in the operation phase, is determined based on the selection of its alternative. Figure 19 illustrates the relationship between ship modules, slots, and task related modules using a class diagram described by the unified modeling language (UML).
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Figure 19. Description of ship modules, slots, and task-related modules using a class diagram in the unified modeling language. Based on the assumption, we model the platform design problem as a goal programming model. The objective is to minimize the deviation between the desired capabilities of multiple missions and the achieved capabilities of the platform. The model calculates the platform’s capabilities based on its best derivative designs. The best derivative designs indicate ship designs that can be derived from the operation platform with the optimal module configurations for individual missions. The optimal configurations are determined based on both the lifecycle cost and the achieved capabilities. The lifecycle cost includes the platform acquisition cost and expected costs of module acquisition and platform reconfiguration. We use the term ‘expected’ in this case because these costs are dependent on the operation scenario. The model is described as follows. Sets: 𝑵
Set of missions, indexed by 𝑛
𝑺
Set of slots, indexed by 𝑠
𝑴𝑠
Set of modules of slot 𝑠, indexed by 𝑚
𝑨𝑠
Set of slot alternatives of slot 𝑠, indexed by 𝑎
𝑷
Set of Capabilities, indexed by 𝑝
𝐱
Set of basic variables, indexed by 𝑥𝑖
𝐲
Set of slot variables, indexed by 𝑦𝑠𝑎
𝐳
Set of configuration variables, indexed by 𝑧𝑛𝑠𝑚
33
Parameters: 𝐵𝑛𝑝 − 𝑊𝑛𝑝
Goal value of capability 𝑝 of mission 𝑛 Weight that penalizes negative deviation of capability 𝑝 in mission 𝑛
+ 𝑊𝑛𝑝
Weight that penalizes positive deviation of capability 𝑝 in mission 𝑛
𝑅𝑝
Normalization factor of capability 𝑝
𝐿𝑋𝑖
Lower boundary of basic variable 𝑥𝑖
𝑈𝑖𝑋
Upper boundary of basic variable 𝑥𝑖
𝑁 𝐸𝐶
Number of equality constraints
𝑁 𝐼𝐶
Number of inequality constraints 1 if slot alternative 𝑎 of slot 𝑠 allows for flexible module
𝐹𝑠𝑎
configuration, 0 otherwise 1 if slot alternative 𝑎 of slot 𝑠 allows for configuration of
𝐻𝑠𝑎𝑚
module 𝑚, 0 otherwise
Variables: 𝑥𝑖
𝑖-th basic variable
𝑦𝑠𝑎
1 if slot alternative 𝑎 is selected for slot 𝑠, 0 otherwise 1 if module alternative 𝑚 is configured to slot 𝑠 in mission 𝑛, 0
𝑧𝑛𝑠𝑚
− 𝑑𝑛𝑝
+ 𝑑𝑛𝑝
otherwise Negative deviation between goal and achieved capability 𝑝 in mission 𝑛 Positive deviation between goal and achieved capability 𝑝 in mission 𝑛
34
Model: Minimize
∑∑ 𝑛∈𝑵 𝑝∈𝑷
s.t.
− + 𝑊𝑛𝑝 𝑊𝑛𝑝 − + ∙ 𝑑𝑛𝑝 +∑∑ ∙ 𝑑𝑛𝑝 𝑅𝑝 𝑅𝑝
(22)
𝑛∈𝑵 𝑝∈𝑷
𝑈 (𝐱, − + 𝑓𝑛𝑝 𝐲, 𝐳) + 𝑑𝑛𝑝 − 𝑑𝑛𝑝 = 𝐵𝑛𝑝
𝑛 ∈ 𝑵, 𝑝 ∈ 𝑷
(23)
− + 𝑑𝑛𝑝 , 𝑑𝑛𝑝 ≥0
𝑛 ∈ 𝑵, 𝑝 ∈ 𝑷
(24)
𝑦𝑠𝑎 ∙ 𝑧𝑛𝑠𝑚 ≤ 𝐻𝑠𝑎𝑚
𝑛 ∈ 𝑵, 𝑠 ∈ 𝑺, 𝑚 ∈ 𝑴𝑠 , 𝑎 ∈ 𝑨𝑠
(25)
(1 − 𝐹𝑠𝑎 ) ∙ 𝑦𝑠𝑎 ∙ 𝑧𝑛1𝑠𝑚 = (1 − 𝐹𝑠𝑎 ) ∙ 𝑦𝑠𝑎 ∙ 𝑧𝑛2𝑠𝑚
𝑛1 , 𝑛2 ∈ 𝑵, 𝑠 ∈ 𝑺, 𝑚 ∈ 𝑴𝑠 , 𝑎 ∈ 𝑨𝑠
(26)
∑ 𝑦𝑠𝑎 = 1
𝑠∈𝑺
(27)
𝑛 ∈ 𝑵, 𝑠 ∈ 𝑺
(28)
𝑔𝑛𝑗 (𝐱, 𝐲, 𝐳) = 0
𝑛 ∈ 𝑵, 𝑗 ∈ {1, … , 𝑁 𝐸𝐶 }
(29)
𝑘𝑛𝑘 (𝐱, 𝐲, 𝐳) ≤ 0
𝑛 ∈ 𝑵, 𝑘 ∈ {1, … , 𝑁 𝐼𝐶 }
(30)
𝑖 ∈ {1, … , |𝐱|}
(31)
𝑦𝑠𝑎 ∈ {0, 1}.
𝑠 ∈ 𝑺, 𝑎 ∈ 𝑨𝑠
(32)
𝑧𝑛𝑠𝑚 ∈ {0, 1}.
𝑛 ∈ 𝑵, 𝑠 ∈ 𝑺, 𝑚 ∈ 𝑴𝑠
(33)
𝑎∈𝑨𝑠
∑ 𝑧𝑛𝑠𝑚 = 1 𝑚∈𝑴𝑠
𝑥𝑖 ∈ {0, 1}
if 𝑥𝑖 is a binary variable,
𝐿𝑋𝑖 ≤ 𝑥𝑖 ≤ 𝑈𝑖𝑋
otherwise,
Equation (22) is the objective function. It minimizes the deviation between goal and achieved − + capabilities in multiple missions. Here, negative deviation 𝑑𝑛𝑝 and positive deviation 𝑑𝑛𝑝 are − + penalized by weight 𝑊𝑛𝑝 and weight 𝑊𝑛𝑝 respectively. The deviations are normalized by 𝑅𝑝 ,
due to the different scale of each capability. Equation (23) - (24) define the deviations. Here, 𝑈 (𝐱, the achieved capability 𝑝 in mission 𝑛 is calculated by function 𝑓𝑛𝑝 𝐲, 𝐳). Equation (25)
allows only for feasible module configurations, which are dependent on slot variables 𝐲. Here, matrix 𝐻𝑠𝑎𝑚 has 1 if the configuration of module 𝑚 is feasible when alternative 𝑎 is selected for slot 𝑠. Otherwise, it has 0. Equation (26) allows only flexible slots to change its module configuration. This is also dependent on slot variables 𝐲. Equation (27) ensures that only one 35
slot alternative is selected for a slot. Equation (28) ensures that every slot is assigned one module. Equation (29) and (30) are equality and inequality constraints that ensure that the designs derived from the operation platform meet given physical and economic constraints. That is, for instance, the constraint of metacentric height (GM) for intact stability and the constraint of expected lifecycle cost. The economic constraint makes sure that the derivative ships have a competitive price compared with its competing ships. The costs include option exercise costs, such as additional module acquisition and ship reconfiguration costs. The lifecycle costs are evaluated based on a set of scenarios because they are dependent on the operation scenario. Equation (31) - (33) define the basic, slot, and configuration variables. We applied the model to the design of a standard operation platform for modular adaptable OSVs. The derivative designs of the platform would compete with inflexible multi-purpose OSVs. The mission set is defined by platform supply (PS), DS, offshore construction and installation (OCI), and IMR missions. The key capabilities are defined by deadweight tonnage (DWT), deck area, maximum speed, crane capability, the number of divers, moonpool size, the number of ROVs, and dynamic positioning (DP) class. Figure 20 compares the capabilities of the inflexible design and flexible design that were created based on the given setting of the case study. Both the designs have the same module configurations in DS, OCI, and IMR missions. This occurs because platform reconfiguration cost of the flexible design can be reduced if it has the same module configuration in the missions. However, in a PS mission, the flexible platform removes the ROV, DS, and crane modules for additional DWT and deck area. Thus, the flexible design can have more DWT compared with the inflexible design, although it has a shorter breadth.
36
Inflexible design vs. flexible design
Inflexible design vs. flexible design
Inflexible design vs. flexible design
Inflexible design vs. flexible design
Figure 20. Comparison between the inflexible design and flexible design in multiple missions. Most of the deviations of the flexible design are small, but there are also some large deviations, such as in the moonpool size in the PS mission and the DWT in the OCI mission. These large deviations occur because the moonpool size and DWT cannot be adjusted by a flexible module configuration. The deviation of the number of divers in OCI and IMR missions occurs because the penalty weights on the positive deviations are relatively small. The identified problems involving large deviations could also be opportunities for developing the design further. For instance, the deviation of the moonpool size in the PS mission could be reduced by considering a moonpool-ready system. The system has doors on the top and bottom, so it can serve as a moonpool or storage space according to the demand. This may increase the acquisition cost of the operation platform, but it would be valuable for further investigating the benefits and costs. The target mission list could also be redefined based on the design results. For instance, the OCI mission requires a relatively high DWT and deck area compared to other missions. Thus, 37
it is difficult to meet the requirements of the OCI mission because the increased DWT and deck area have negative effects on other missions. Instead, we can consider excluding the OCI mission from the target mission list and including another mission that better fits the other missions.
38
4. Conclusions The motivation of this thesis is to develop methods for the design of value-robust ships that can maintain their value throughout their lifecycle, although there are contextual changes in the operation phase. The contextual changes indicate, for instance, changes in market rates, demands and supplies, regulations, stakeholders’ preference, and physical operating conditions. This thesis work was initiated from a comprehensive literature survey based on the following keywords: modular adaptable ship, flexible system or product, lifecycle evaluation, real options, modularization, design optimization, simulation, hybrid simulation optimization, product platform, mass customization, etc. Based on the literature survey, ‘modular adaptable ship design for handling uncertainty in the future operating context’ was determined as this PhD research topic, and three research questions were defined. Because mature methods for each keyword are existing, the research focus was on combining the methods in a ‘smart’ way to achieve the research goal. The results of the thesis work have been published in international journals, and each journal paper deals with one of the research questions, respectively. The prime contribution of this thesis is the integration of module based design synthesis and lifecycle evaluation for flexible designs. This serves as a bridge connecting two different domains, and can be a starting point from which a variety of extended models can be derived. By combining the design synthesis and lifecycle evaluation, the proposed methods enable ship designers to understand the logical chain between physical design decisions and the economic results, describing how the invested flexibilities have a value in different operating contexts. This also can be a useful communication tool between designers and customers, because the proposed designs can be well explained to the customers relating to their business scenarios. There is room for further improvement. The presented methods are based on the assumption that the functional capabilities of modular ships can be determined by linear aggregation of the 39
functional capabilities of configured modules. Although this can be reasonable in the early design stages, ships have functional capabilities that should be analyzed in more detail using high-fidelity methods, such as computational fluid dynamics (CFD) or finite element method (FEM). The computation time of these methods is often hours or days, which is too slow to use in optimization. In paper 1, this issue is concluded that such functional capabilities must be analyzed further in the later design stages as the number of design alternatives decreases. However, as the research fields of modeling surrogate models or meta-models have developed rapidly, in the near future such high-fidelity analyses can be available even in the early design stages. For instance, Prebeg et al. (2014) show the potential, applying a surrogate modeling to the design of thin-walled ship structures. The performance and cost of surrogate modeling is dependent on its parameter selection and pre- and post-processes. These require the domain knowledge, which can be achieved by trials and errors. In this thesis, it is assumed that there is a known static module list. However, the list will evolve over the lifecycle of ships. When it comes to open architecture design, there is high uncertainty in the future module list. So, how can we consider the value of future modules in the design of MASs? This issue is related to decision-making in unknowable uncertainty (Chow and Sarin 2012), in which it is assumed that decision makers even do not know the stochastic properties of uncertainties. I believe that this can be an interesting topic for future study.
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Doerry NH. 2014. Institutionalizing Modular Adaptable Ship Technologies. Journal of Ship Production and Design. 30(3):126-141. Erikstad SO, Fagerholt K., Solem S. 2011. A Ship Design and Deployment Model for NonCargo Vessels Using Contract Scenarios. Ship Technology Research. 58(3):132-141. Erikstad SO, Rehn CF. 2015. Handling Uncertainty in Marine Systems Design-State-of-theArt and Need for Research. IMDC 2015. Fagerholt K, Christiansen M, Hvattum LM, Johnsen TA, Vabø TJ. 2010. A decision support methodology for strategic planning in maritime transportation. Omega. 38(6): 465-474. Gregor JA. 2003. Real options for naval ship design and acquisition: a method for valuing flexibility under uncertainty. Master’s Thesis, Massachusetts Institute of Technology. Ho SH, Liao SH. 2011. A fuzzy real option approach for investment project valuation. Expert Systems with Applications, 38(12), 15296-15302. Jiao JR, Simpson TW, Siddique Z. 2007. Product family design and platform-based product development: a state-of-the-art review. Journal of intelligent Manufacturing. 18(1): 5-29. Juan AA, Faulin J, Grasman SE, Rabe M, Figueira G. 2015. A review of simheuristics: Extending metaheuristics to deal with stochastic combinatorial optimization problems. Operations Research Perspectives. 2: 62-72. Jung JY, Blau G, Pekny JF, Reklaitis GV, Eversdyk D. 2004. A simulation based optimization approach to supply chain management under demand uncertainty. Computers & chemical engineering. 28(10): 2087-2106. Marcantonio RT, Sanford EG, Levine DSTAJ. 2007. Addressing The Design Challenges Of Open System Architecture Systems On US Navy Ships–Building Out Of The Box. MAST 2007 42
Conference. Meyer MH, Lehnerd AP, 1997. The power of product platforms. The Free Press, New York. Nance RE, Sargent RG. 2002. Perspectives on the evolution of simulation. Operations Research. 50(1): 161-172. Page J. 2012. Flexibility in early stage design of US Navy ships: An analysis of options. Journal of Ship Production and Design. 28(3):128-133. Papanikolaou A. 2010. Holistic ship design optimization. Computer-Aided Design, 42(11): 1028-1044. Perlitz M, Peske T, Schrank R. 1999. Real options valuation: the new frontier in R&D project evaluation?
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Prebeg P, Zanic V, Vazic B. 2014. Application of a surrogate modeling to the ship structural design. Ocean engineering, 84, 259-272. Rehn CF, Pettersen SS, Erikstad SO, Asbjørnslett BE. 2018. Investigating tradeoffs between performance, cost and flexibility for reconfigurable offshore ships. Ocean Engineering. 147, 546-555. Romero C. 2004. A general structure of achievement function for a goal programming model. European Journal of Operational Research, 153(3), 675-686. Ross AM, Rhodes DH, Hastings DE. 2008. Defining changeability: Reconciling flexibility, adaptability, scalability, modifiability, and robustness for maintaining system lifecycle value. Systems Engineering. 11(3): 246-262. Salvador F, Forza C, Rungtusanatham M. 2002. Modularity, product variety, production 43
volume, and component sourcing: theorizing beyond generic prescriptions. Journal of Operations Management. 20(5):549-575. Simon HA, 1969. The sciences of the artificial. Cambridge, MA. Simpson TW, Marion T, de Weck O, Hölttä-Otto K, Kokkolaras M, Shooter SB. 2006. Platform-based design and development: current trends and needs in industry. American Society of Mechanical Engineers (ASME). 801-810. Sødal S, Koekebakker S, Aadland R. 2008. Market switching in shipping - A real option model applied to the valuation of combination carriers. Review of Financial Economics. 17(3):183203. Triantis A, Borison A. 2001. Real options: state of the practice. Journal of Applied Corporate Finance, 14(2), 8-24. Ulrich K. 1995. The role of product architecture in the manufacturing firm. Research policy. 24(3):419-440. Van Oers BJ. 2011. A packing approach for the early stage design of service vessels. PhD Thesis, TU Delft.
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Appendix A: Papers
Paper 1 Choi, M., Erikstad, S.O., 2017. A module configuration and valuation model for operational flexibility in ship design using contract scenarios. Ships and Offshore Structures. 12(8), 11271135. Paper 2 Choi, M., Rehn, C. F., Erikstad, S.O., 2018. A hybrid method for a module configuration problem in modular adaptable ship design. Ships and Offshore Structures. 13(4), 343-351. Paper 3 Choi, M., Erikstad, S.O., Chung, H., 2018, Operation Platform Design for Modular Adaptable Ships: Towards the Configure-To-Order Strategy. Ocean Engineering. 163, 85-93.
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Paper 1 Choi, M., Erikstad, S.O., 2017. A module configuration and valuation model for operational flexibility in ship design using contract scenarios. Ships and Offshore Structures. 12(8), 11271135.
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Paper 2 Choi, M., Rehn, C. F., Erikstad, S.O., 2018. A hybrid method for a module configuration problem in modular adaptable ship design. Ships and Offshore Structures. 13(4), 343-351.
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Paper 3 Choi, M., Erikstad, S.O., Chung, H., 2018, Operation Platform Design for Modular Adaptable Ships: Towards the Configure-To-Order Strategy. Ocean Engineering. 163, 85-93.
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Appendix B: Previous PhD theses
Previous PhD theses published at the Departement of Marine Technology (earlier: Faculty of Marine Technology) NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY
Report No.
Author
Title
Kavlie, Dag
Optimization of Plane Elastic Grillages, 1967
Hansen, Hans R.
Man-Machine Communication and Data-Storage Methods in Ship Structural Design, 1971
Gisvold, Kaare M.
A Method for non-linear mixed -integer programming and its Application to Design Problems, 1971
Lund, Sverre
Tanker Frame Optimalization by means of SUMTTransformation and Behaviour Models, 1971
Vinje, Tor
On Vibration of Spherical Shells Interacting with Fluid, 1972
Lorentz, Jan D.
Tank Arrangement for Crude Oil Carriers in Accordance with the new Anti-Pollution Regulations, 1975
Carlsen, Carl A.
Computer-Aided Design of Tanker Structures, 1975
Larsen, Carl M.
Static and Dynamic Analysis of Offshore Pipelines during Installation, 1976
UR-79-01
Brigt Hatlestad, MK
The finite element method used in a fatigue evaluation of fixed offshore platforms. (Dr.Ing. Thesis)
UR-79-02
Erik Pettersen, MK
Analysis and design of cellular structures. (Dr.Ing. Thesis)
UR-79-03
Sverre Valsgård, MK
Finite difference and finite element methods applied to nonlinear analysis of plated structures. (Dr.Ing. Thesis)
85
UR-79-04
Nils T. Nordsve, MK
Finite element collapse analysis of structural members considering imperfections and stresses due to fabrication. (Dr.Ing. Thesis)
UR-79-05
Ivar J. Fylling, MK
Analysis of towline forces in ocean towing systems. (Dr.Ing. Thesis)
UR-80-06
Nils Sandsmark, MM
Analysis of Stationary and Transient Heat Conduction by the Use of the Finite Element Method. (Dr.Ing. Thesis)
UR-80-09
Sverre Haver, MK
Analysis of uncertainties related to the stochastic modeling of ocean waves. (Dr.Ing. Thesis)
UR-81-15
Odland, Jonas
On the Strength of welded Ring stiffened cylindrical Shells primarily subjected to axial Compression
UR-82-17
Engesvik, Knut
Analysis of Uncertainties in the fatigue Capacity of Welded Joints
UR-82-18
Rye, Henrik
Ocean wave groups
UR-83-30
Eide, Oddvar Inge
On Cumulative Fatigue Damage in Steel Welded Joints
UR-83-33
Mo, Olav
Stochastic Time Domain Analysis of Slender Offshore Structures
UR-83-34
Amdahl, Jørgen
Energy absorption in Ship-platform impacts
UR-84-37
Mørch, Morten
Motions and mooring forces of semi submersibles as determined by full-scale measurements and theoretical analysis
UR-84-38
Soares, C. Guedes
Probabilistic models for load effects in ship structures
UR-84-39
Aarsnes, Jan V.
Current forces on ships
UR-84-40
Czujko, Jerzy
Collapse Analysis of Plates subjected to Biaxial Compression and Lateral Load
UR-85-46
Alf G. Engseth, MK
Finite element collapse analysis of tubular steel offshore structures. (Dr.Ing. Thesis)
UR-86-47
Dengody Sheshappa, MP
A Computer Design Model for Optimizing Fishing Vessel Designs Based on Techno-Economic Analysis. (Dr.Ing. Thesis)
UR-86-48
Vidar Aanesland, MH
A Theoretical and Numerical Study of Ship Wave Resistance. (Dr.Ing. Thesis)
UR-86-49
Heinz-Joachim Wessel, MK
Fracture Mechanics Analysis of Crack Growth in Plate Girders. (Dr.Ing. Thesis)
86
UR-86-50
Jon Taby, MK
Ultimate and Post-ultimate Strength of Dented Tubular Members. (Dr.Ing. Thesis)
UR-86-51
Walter Lian, MH
A Numerical Study of Two-Dimensional Separated Flow Past Bluff Bodies at Moderate KC-Numbers. (Dr.Ing. Thesis)
UR-86-52
Bjørn Sortland, MH
Force Measurements in Oscillating Flow on Ship Sections and Circular Cylinders in a U-Tube Water Tank. (Dr.Ing. Thesis)
UR-86-53
Kurt Strand, MM
A System Dynamic Approach to One-dimensional Fluid Flow. (Dr.Ing. Thesis)
UR-86-54
Arne Edvin Løken, MH
Three Dimensional Second Order Hydrodynamic Effects on Ocean Structures in Waves. (Dr.Ing. Thesis)
UR-86-55
Sigurd Falch, MH
A Numerical Study of Slamming of TwoDimensional Bodies. (Dr.Ing. Thesis)
UR-87-56
Arne Braathen, MH
Application of a Vortex Tracking Method to the Prediction of Roll Damping of a Two-Dimension Floating Body. (Dr.Ing. Thesis)
UR-87-57
Bernt Leira, MK
Gaussian Vector Processes for Reliability Analysis involving Wave-Induced Load Effects. (Dr.Ing. Thesis)
UR-87-58
Magnus Småvik, MM
Thermal Load and Process Characteristics in a TwoStroke Diesel Engine with Thermal Barriers (in Norwegian). (Dr.Ing. Thesis)
MTA-8859
Bernt Arild Bremdal, MP
An Investigation of Marine Installation Processes – A Knowledge - Based Planning Approach. (Dr.Ing. Thesis)
MTA-8860
Xu Jun, MK
Non-linear Dynamic Analysis of Space-framed Offshore Structures. (Dr.Ing. Thesis)
MTA-8961
Gang Miao, MH
Hydrodynamic Forces and Dynamic Responses of Circular Cylinders in Wave Zones. (Dr.Ing. Thesis)
MTA-8962
Martin Greenhow, MH
Linear and Non-Linear Studies of Waves and Floating Bodies. Part I and Part II. (Dr.Techn. Thesis)
MTA-8963
Chang Li, MH
Force Coefficients of Spheres and Cubes in Oscillatory Flow with and without Current. (Dr.Ing. Thesis
MTA-8964
Hu Ying, MP
A Study of Marketing and Design in Development of Marine Transport Systems. (Dr.Ing. Thesis)
MTA-8965
Arild Jæ ger, MH
Seakeeping, Dynamic Stability and Performance of a Wedge Shaped Planing Hull. (Dr.Ing. Thesis)
87
MTA-8966
Chan Siu Hung, MM
The dynamic characteristics of tilting-pad bearings
MTA-8967
Kim Wikstrøm, MP
Analysis av projekteringen for ett offshore projekt. (Licenciat-avhandling)
MTA-8968
Jiao Guoyang, MK
Reliability Analysis of Crack Growth under Random Loading, considering Model Updating. (Dr.Ing. Thesis)
MTA-8969
Arnt Olufsen, MK
Uncertainty and Reliability Analysis of Fixed Offshore Structures. (Dr.Ing. Thesis)
MTA-8970
Wu Yu-Lin, MR
System Reliability Analyses of Offshore Structures using improved Truss and Beam Models. (Dr.Ing. Thesis)
MTA-9071
Jan Roger Hoff, MH
Three-dimensional Green function of a vessel with forward speed in waves. (Dr.Ing. Thesis)
MTA-9072
Rong Zhao, MH
Slow-Drift Motions of a Moored Two-Dimensional Body in Irregular Waves. (Dr.Ing. Thesis)
MTA-9073
Atle Minsaas, MP
Economical Risk Analysis. (Dr.Ing. Thesis)
MTA-9074
Knut-Aril Farnes, MK
Long-term Statistics of Response in Non-linear Marine Structures. (Dr.Ing. Thesis)
MTA-9075
Torbjørn Sotberg, MK
Application of Reliability Methods for Safety Assessment of Submarine Pipelines. (Dr.Ing. Thesis)
MTA-9076
Zeuthen, Steffen, MP
SEAMAID. A computational model of the design process in a constraint-based logic programming environment. An example from the offshore domain. (Dr.Ing. Thesis)
MTA-9177
Haagensen, Sven, MM
Fuel Dependant Cyclic Variability in a Spark Ignition Engine - An Optical Approach. (Dr.Ing. Thesis)
MTA-9178
Løland, Geir, MH
Current forces on and flow through fish farms. (Dr.Ing. Thesis)
MTA-9179
Hoen, Christopher, MK
System Identification of Structures Excited by Stochastic Load Processes. (Dr.Ing. Thesis)
MTA-9180
Haugen, Stein, MK
Probabilistic Evaluation of Frequency of Collision between Ships and Offshore Platforms. (Dr.Ing. Thesis)
MTA-9181
Sødahl, Nils, MK
Methods for Design and Analysis of Flexible Risers. (Dr.Ing. Thesis)
MTA-9182
Ormberg, Harald, MK
Non-linear Response Analysis of Floating Fish Farm Systems. (Dr.Ing. Thesis)
88
MTA-9183
Marley, Mark J., MK
Time Variant Reliability under Fatigue Degradation. (Dr.Ing. Thesis)
MTA-9184
Krokstad, Jørgen R., MH
Second-order Loads in Multidirectional Seas. (Dr.Ing. Thesis)
MTA-9185
Molteberg, Gunnar A., MM
The Application of System Identification Techniques to Performance Monitoring of Four Stroke Turbocharged Diesel Engines. (Dr.Ing. Thesis)
MTA-9286
Mørch, Hans Jørgen Bjelke, MH
Aspects of Hydrofoil Design: with Emphasis on Hydrofoil Interaction in Calm Water. (Dr.Ing. Thesis)
MTA-9287
Chan Siu Hung, MM
Nonlinear Analysis of Rotordynamic Instabilities in Highspeed Turbomachinery. (Dr.Ing. Thesis)
MTA-9288
Bessason, Bjarni, MK
Assessment of Earthquake Loading and Response of Seismically Isolated Bridges. (Dr.Ing. Thesis)
MTA-9289
Langli, Geir, MP
Improving Operational Safety through exploitation of Design Knowledge - an investigation of offshore platform safety. (Dr.Ing. Thesis)
MTA-9290
Sæ vik, Svein, MK
On Stresses and Fatigue in Flexible Pipes. (Dr.Ing. Thesis)
MTA-9291
Ask, Tor Ø ., MM
Ignition and Flame Growth in Lean Gas-Air Mixtures. An Experimental Study with a Schlieren System. (Dr.Ing. Thesis)
MTA-8692
Hessen, Gunnar, MK
Fracture Mechanics Analysis of Stiffened Tubular Members. (Dr.Ing. Thesis)
MTA-9393
Steinebach, Christian, MM
Knowledge Based Systems for Diagnosis of Rotating Machinery. (Dr.Ing. Thesis)
MTA-9394
Dalane, Jan Inge, MK
System Reliability in Design and Maintenance of Fixed Offshore Structures. (Dr.Ing. Thesis)
MTA-9395
Steen, Sverre, MH
Cobblestone Effect on SES. (Dr.Ing. Thesis)
MTA-9396
Karunakaran, Daniel, MK
Nonlinear Dynamic Response and Reliability Analysis of Drag-dominated Offshore Platforms. (Dr.Ing. Thesis)
MTA-9397
Hagen, Arnulf, MP
The Framework of a Design Process Language. (Dr.Ing. Thesis)
MTA-9398
Nordrik, Rune, MM
Investigation of Spark Ignition and Autoignition in Methane and Air Using Computational Fluid Dynamics and Chemical Reaction Kinetics. A Numerical Study of Ignition Processes in Internal Combustion Engines. (Dr.Ing. Thesis)
89
MTA-9499
Passano, Elizabeth, MK
Efficient Analysis of Nonlinear Slender Marine Structures. (Dr.Ing. Thesis)
MTA-94100
Kvålsvold, Jan, MH
Hydroelastic Modelling of Wetdeck Slamming on Multihull Vessels. (Dr.Ing. Thesis)
MTA-94102
Bech, Sidsel M., MK
Experimental and Numerical Determination of Stiffness and Strength of GRP/PVC Sandwich Structures. (Dr.Ing. Thesis)
MTA-95103
Paulsen, Hallvard, MM
A Study of Transient Jet and Spray using a Schlieren Method and Digital Image Processing. (Dr.Ing. Thesis)
MTA-95104
Hovde, Geir Olav, MK
Fatigue and Overload Reliability of Offshore Structural Systems, Considering the Effect of Inspection and Repair. (Dr.Ing. Thesis)
MTA-95105
Wang, Xiaozhi, MK
Reliability Analysis of Production Ships with Emphasis on Load Combination and Ultimate Strength. (Dr.Ing. Thesis)
MTA-95106
Ulstein, Tore, MH
Nonlinear Effects of a Flexible Stern Seal Bag on Cobblestone Oscillations of an SES. (Dr.Ing. Thesis)
MTA-95107
Solaas, Frøydis, MH
Analytical and Numerical Studies of Sloshing in Tanks. (Dr.Ing. Thesis)
MTA-95108
Hellan, Ø yvind, MK
Nonlinear Pushover and Cyclic Analyses in Ultimate Limit State Design and Reassessment of Tubular Steel Offshore Structures. (Dr.Ing. Thesis)
MTA-95109
Hermundstad, Ole A., MK
Theoretical and Experimental Hydroelastic Analysis of High Speed Vessels. (Dr.Ing. Thesis)
MTA-96110
Bratland, Anne K., MH
Wave-Current Interaction Effects on Large-Volume Bodies in Water of Finite Depth. (Dr.Ing. Thesis)
MTA-96111
Herfjord, Kjell, MH
A Study of Two-dimensional Separated Flow by a Combination of the Finite Element Method and Navier-Stokes Equations. (Dr.Ing. Thesis)
MTA-96112
Æ søy, Vilmar, MM
Hot Surface Assisted Compression Ignition in a Direct Injection Natural Gas Engine. (Dr.Ing. Thesis)
MTA-96113
Eknes, Monika L., MK
Escalation Scenarios Initiated by Gas Explosions on Offshore Installations. (Dr.Ing. Thesis)
MTA-96114
Erikstad, Stein O., MP
A Decision Support Model for Preliminary Ship Design. (Dr.Ing. Thesis)
MTA-96115
Pedersen, Egil, MH
A Nautical Study of Towed Marine Seismic Streamer Cable Configurations. (Dr.Ing. Thesis)
MTA-97116
Moksnes, Paul O., MM
Modelling Two-Phase Thermo-Fluid Systems Using Bond Graphs. (Dr.Ing. Thesis)
90
MTA-97117
Halse, Karl H., MK
On Vortex Shedding and Prediction of VortexInduced Vibrations of Circular Cylinders. (Dr.Ing. Thesis)
MTA-97118
Igland, Ragnar T., MK
Reliability Analysis of Pipelines during Laying, considering Ultimate Strength under Combined Loads. (Dr.Ing. Thesis)
MTA-97119
Pedersen, Hans-P., MP
Levendefiskteknologi Thesis)
MTA-98120
Vikestad, Kyrre, MK
Multi-Frequency Response of a Cylinder Subjected to Vortex Shedding and Support Motions. (Dr.Ing. Thesis)
MTA-98121
Azadi, Mohammad R. E., MK
Analysis of Static and Dynamic Pile-Soil-Jacket Behaviour. (Dr.Ing. Thesis)
MTA-98122
Ulltang, Terje, MP
A Communication Model for Product Information. (Dr.Ing. Thesis)
MTA-98123
Torbergsen, Erik, MM
Impeller/Diffuser Interaction Forces in Centrifugal Pumps. (Dr.Ing. Thesis)
MTA-98124
Hansen, Edmond, MH
A Discrete Element Model to Study Marginal Ice Zone Dynamics and the Behaviour of Vessels Moored in Broken Ice. (Dr.Ing. Thesis)
MTA-98125
Videiro, Paulo M., MK
Reliability Based Design of Marine Structures. (Dr.Ing. Thesis)
MTA-99126
Mainçon, Philippe, MK
Fatigue Reliability of Long Welds Application to Titanium Risers. (Dr.Ing. Thesis)
MTA-99127
Haugen, Elin M., MH
Hydroelastic Analysis of Slamming on Stiffened Plates with Application to Catamaran Wetdecks. (Dr.Ing. Thesis)
MTA-99128
Langhelle, Nina K., MK
Experimental Validation and Calibration of Nonlinear Finite Element Models for Use in Design of Aluminium Structures Exposed to Fire. (Dr.Ing. Thesis)
MTA-99129
Berstad, Are J., MK
Calculation of Fatigue Damage in Ship Structures. (Dr.Ing. Thesis)
MTA-99130
Andersen, Trond M., MM
Short Term Maintenance Planning. (Dr.Ing. Thesis)
MTA-99131
Tveiten, Bård Wathne, MK
Fatigue Assessment of Welded Aluminium Ship Details. (Dr.Ing. Thesis)
MTA-99132
Søreide, Fredrik, MP
Applications of underwater technology in deep water archaeology. Principles and practice. (Dr.Ing. Thesis)
91
for
fiskefartøy.
(Dr.Ing.
MTA-99133
Tønnessen, Rune, MH
A Finite Element Method Applied to Unsteady Viscous Flow Around 2D Blunt Bodies With Sharp Corners. (Dr.Ing. Thesis)
MTA-99134
Elvekrok, Dag R., MP
Engineering Integration in Field Development Projects in the Norwegian Oil and Gas Industry. The Supplier Management of Norne. (Dr.Ing. Thesis)
MTA-99135
Fagerholt, Kjetil, MP
Optimeringsbaserte Metoder for Ruteplanlegging innen skipsfart. (Dr.Ing. Thesis)
MTA-99136
Bysveen, Marie, MM
Visualization in Two Directions on a Dynamic Combustion Rig for Studies of Fuel Quality. (Dr.Ing. Thesis)
MTA2000-137
Storteig, Eskild, MM
Dynamic characteristics and leakage performance of liquid annular seals in centrifugal pumps. (Dr.Ing. Thesis)
MTA2000-138
Sagli, Gro, MK
Model uncertainty and simplified estimates of long term extremes of hull girder loads in ships. (Dr.Ing. Thesis)
MTA2000-139
Tronstad, Harald, MK
Nonlinear analysis and design of cable net structures like fishing gear based on the finite element method. (Dr.Ing. Thesis)
MTA2000-140
Kroneberg, André, MP
Innovation in shipping by using scenarios. (Dr.Ing. Thesis)
MTA2000-141
Haslum, Herbjørn Alf, MH
Simplified methods applied to nonlinear motion of spar platforms. (Dr.Ing. Thesis)
MTA2001-142
Samdal, Ole Johan, MM
Modelling of Degradation Mechanisms and Stressor Interaction on Static Mechanical Equipment Residual Lifetime. (Dr.Ing. Thesis)
MTA2001-143
Baarholm, Rolf Jarle, MH
Theoretical and experimental studies of wave impact underneath decks of offshore platforms. (Dr.Ing. Thesis)
MTA2001-144
Wang, Lihua, MK
Probabilistic Analysis of Nonlinear Wave-induced Loads on Ships. (Dr.Ing. Thesis)
MTA2001-145
Kristensen, Odd H. Holt, MK
Ultimate Capacity of Aluminium Plates under Multiple Loads, Considering HAZ Properties. (Dr.Ing. Thesis)
MTA2001-146
Greco, Marilena, MH
A Two-Dimensional Study of Green-Water Loading. (Dr.Ing. Thesis)
MTA2001-147
Heggelund, Svein E., MK
Calculation of Global Design Loads and Load Effects in Large High Speed Catamarans. (Dr.Ing. Thesis)
MTA2001-148
Babalola, Olusegun T., MK
Fatigue Strength of Titanium Risers – Defect Sensitivity. (Dr.Ing. Thesis)
92
MTA2001-149
Mohammed, Abuu K., MK
Nonlinear Shell Finite Elements for Ultimate Strength and Collapse Analysis of Ship Structures. (Dr.Ing. Thesis)
MTA2002-150
Holmedal, Lars E., MH
Wave-current interactions in the vicinity of the sea bed. (Dr.Ing. Thesis)
MTA2002-151
Rognebakke, Olav F., MH
Sloshing in rectangular tanks and interaction with ship motions. (Dr.Ing. Thesis)
MTA2002-152
Lader, Pål Furset, MH
Geometry and Kinematics of Breaking Waves. (Dr.Ing. Thesis)
MTA2002-153
Yang, Qinzheng, MH
Wash and wave resistance of ships in finite water depth. (Dr.Ing. Thesis)
MTA2002-154
Melhus, Ø yvin, MM
Utilization of VOC in Diesel Engines. Ignition and combustion of VOC released by crude oil tankers. (Dr.Ing. Thesis)
MTA2002-155
Ronæ ss, Marit, MH
Wave Induced Motions of Two Ships Advancing on Parallel Course. (Dr.Ing. Thesis)
MTA2002-156
Ø kland, Ole D., MK
Numerical and experimental investigation of whipping in twin hull vessels exposed to severe wet deck slamming. (Dr.Ing. Thesis)
MTA2002-157
Ge, Chunhua, MK
Global Hydroelastic Response of Catamarans due to Wet Deck Slamming. (Dr.Ing. Thesis)
MTA2002-158
Byklum, Eirik, MK
Nonlinear Shell Finite Elements for Ultimate Strength and Collapse Analysis of Ship Structures. (Dr.Ing. Thesis)
IMT2003-1
Chen, Haibo, MK
Probabilistic Evaluation of FPSO-Tanker Collision in Tandem Offloading Operation. (Dr.Ing. Thesis)
IMT2003-2
Skaugset, Kjetil Bjørn, MK
On the Suppression of Vortex Induced Vibrations of Circular Cylinders by Radial Water Jets. (Dr.Ing. Thesis)
IMT2003-3
Chezhian, Muthu
Three-Dimensional Analysis of Slamming. (Dr.Ing. Thesis)
IMT2003-4
Buhaug, Ø yvind
Deposit Formation on Cylinder Liner Surfaces in Medium Speed Engines. (Dr.Ing. Thesis)
IMT2003-5
Tregde, Vidar
Aspects of Ship Design: Optimization of Aft Hull with Inverse Geometry Design. (Dr.Ing. Thesis)
IMT2003-6
Wist, Hanne Therese
Statistical Properties of Successive Ocean Wave Parameters. (Dr.Ing. Thesis)
93
IMT2004-7
Ransau, Samuel
Numerical Methods for Flows with Evolving Interfaces. (Dr.Ing. Thesis)
IMT2004-8
Soma, Torkel
Blue-Chip or Sub-Standard. A data interrogation approach of identity safety characteristics of shipping organization. (Dr.Ing. Thesis)
IMT2004-9
Ersdal, Svein
An experimental study of hydrodynamic forces on cylinders and cables in near axial flow. (Dr.Ing. Thesis)
IMT2005-10
Brodtkorb, Per Andreas
The Probability of Occurrence of Dangerous Wave Situations at Sea. (Dr.Ing. Thesis)
IMT2005-11
Yttervik, Rune
Ocean current variability in relation to offshore engineering. (Dr.Ing. Thesis)
IMT2005-12
Fredheim, Arne
Current Forces on Net-Structures. (Dr.Ing. Thesis)
IMT2005-13
Heggernes, Kjetil
Flow around marine structures. (Dr.Ing. Thesis
IMT2005-14
Fouques, Sebastien
Lagrangian Modelling of Ocean Surface Waves and Synthetic Aperture Radar Wave Measurements. (Dr.Ing. Thesis)
IMT2006-15
Holm, Håvard
Numerical calculation of viscous free surface flow around marine structures. (Dr.Ing. Thesis)
IMT2006-16
Bjørheim, Lars G.
Failure Assessment of Long Through Thickness Fatigue Cracks in Ship Hulls. (Dr.Ing. Thesis)
IMT2006-17
Hansson, Lisbeth
Safety Management for Prevention of Occupational Accidents. (Dr.Ing. Thesis)
IMT2006-18
Zhu, Xinying
Application of the CIP Method to Strongly Nonlinear Wave-Body Interaction Problems. (Dr.Ing. Thesis)
IMT2006-19
Reite, Karl Johan
Modelling and Control of Trawl Systems. (Dr.Ing. Thesis)
IMT2006-20
Smogeli, Ø yvind Notland
Control of Marine Propellers. From Normal to Extreme Conditions. (Dr.Ing. Thesis)
IMT2007-21
Storhaug, Gaute
Experimental Investigation of Wave Induced Vibrations and Their Effect on the Fatigue Loading of Ships. (Dr.Ing. Thesis)
IMT2007-22
Sun, Hui
A Boundary Element Method Applied to Strongly Nonlinear Wave-Body Interaction Problems. (PhD Thesis, CeSOS)
IMT2007-23
Rustad, Anne Marthine
Modelling and Control of Top Tensioned Risers. (PhD Thesis, CeSOS)
94
IMT2007-24
Johansen, Vegar
Modelling flexible slender system for real-time simulations and control applications
IMT2007-25
Wroldsen, Anders Sunde
Modelling and control of tensegrity structures. (PhD Thesis, CeSOS)
IMT2007-26
Aronsen, Kristoffer Høye
An experimental investigation of in-line and combined inline and cross flow vortex induced vibrations. (Dr. avhandling, IMT)
IMT2007-27
Gao, Zhen
Stochastic Response Analysis of Mooring Systems with Emphasis on Frequency-domain Analysis of Fatigue due to Wide-band Response Processes (PhD Thesis, CeSOS)
IMT2007-28
Thorstensen, Tom Anders
Lifetime Profit Modelling of Ageing Systems Utilizing Information about Technical Condition. (Dr.ing. thesis, IMT)
IMT2008-29
Refsnes, Jon Erling Gorset
Nonlinear Model-Based Control of Slender Body AUVs (PhD Thesis, IMT)
IMT2008-30
Berntsen, Per Ivar B.
Structural Reliability Based Position Mooring. (PhD-Thesis, IMT)
IMT2008-31
Ye, Naiquan
Fatigue Assessment of Aluminium Welded Boxstiffener Joints in Ships (Dr.ing. thesis, IMT)
IMT2008-32
Radan, Damir
Integrated Control of Marine Electrical Power Systems. (PhD-Thesis, IMT)
IMT2008-33
Thomassen, Paul
Methods for Dynamic Response Analysis and Fatigue Life Estimation of Floating Fish Cages. (Dr.ing. thesis, IMT)
IMT2008-34
Pákozdi, Csaba
A Smoothed Particle Hydrodynamics Study of Twodimensional Nonlinear Sloshing in Rectangular Tanks. (Dr.ing.thesis, IMT/ CeSOS)
IMT2007-35
Grytøyr, Guttorm
A Higher-Order Boundary Element Method and Applications to Marine Hydrodynamics. (Dr.ing.thesis, IMT)
IMT2008-36
Drummen, Ingo
Experimental and Numerical Investigation of Nonlinear Wave-Induced Load Effects in Containerships considering Hydroelasticity. (PhD thesis, CeSOS)
IMT2008-37
Skejic, Renato
Maneuvering and Seakeeping of a Singel Ship and of Two Ships in Interaction. (PhD-Thesis, CeSOS)
IMT2008-38
Harlem, Alf
An Age-Based Replacement Model for Repairable Systems with Attention to High-Speed Marine Diesel Engines. (PhD-Thesis, IMT)
IMT2008-39
Alsos, Hagbart S.
Ship Grounding. Analysis of Ductile Fracture, Bottom Damage and Hull Girder Response. (PhDthesis, IMT)
95
IMT2008-40
Graczyk, Mateusz
Experimental Investigation of Sloshing Loading and Load Effects in Membrane LNG Tanks Subjected to Random Excitation. (PhD-thesis, CeSOS)
IMT2008-41
Taghipour, Reza
Efficient Prediction of Dynamic Response for Flexible amd Multi-body Marine Structures. (PhDthesis, CeSOS)
IMT2008-42
Ruth, Eivind
Propulsion control and thrust allocation on marine vessels. (PhD thesis, CeSOS)
IMT2008-43
Nystad, Bent Helge
Technical Condition Indexes and Remaining Useful Life of Aggregated Systems. PhD thesis, IMT
IMT2008-44
Soni, Prashant Kumar
Hydrodynamic Coefficients for Vortex Induced Vibrations of Flexible Beams, PhD thesis, CeSOS
IMT2009-45
Amlashi, Hadi K.K.
Ultimate Strength and Reliability-based Design of Ship Hulls with Emphasis on Combined Global and Local Loads. PhD Thesis, IMT
IMT2009-46
Pedersen, Tom Arne
Bond Graph Modelling of Marine Power Systems. PhD Thesis, IMT
IMT2009-47
Kristiansen, Trygve
Two-Dimensional Numerical and Experimental Studies of Piston-Mode Resonance. PhD-Thesis, CeSOS
IMT2009-48
Ong, Muk Chen
Applications of a Standard High Reynolds Number Model and a Stochastic Scour Prediction Model for Marine Structures. PhD-thesis, IMT
IMT2009-49
Hong, Lin
Simplified Analysis and Design of Ships subjected to Collision and Grounding. PhD-thesis, IMT
IMT2009-50
Koushan, Kamran
Vortex Induced Vibrations of Free Span Pipelines, PhD thesis, IMT
IMT2009-51
Korsvik, Jarl Eirik
Heuristic Methods for Ship Routing and Scheduling. PhD-thesis, IMT
IMT2009-52
Lee, Jihoon
Experimental Investigation and Numerical in Analyzing the Ocean Current Displacement of Longlines. Ph.d.-Thesis, IMT.
IMT2009-53
Vestbøstad, Tone Gran
A Numerical Study of Wave-in-Deck Impact usin a Two-Dimensional Constrained Interpolation Profile Method, Ph.d.thesis, CeSOS.
IMT2009-54
Bruun, Kristine
Bond Graph Modelling of Fuel Cells for Marine Power Plants. Ph.d.-thesis, IMT
IMT 2009-55
Holstad, Anders
Numerical Investigation of Turbulence in a Sekwed Three-Dimensional Channel Flow, Ph.d.-thesis, IMT.
96
IMT 2009-56
Ayala-Uraga, Efren
Reliability-Based Assessment of Deteriorating Shipshaped Offshore Structures, Ph.d.-thesis, IMT
IMT
Kong, Xiangjun
A Numerical Study of a Damaged Ship in Beam Sea Waves. Ph.d.-thesis, IMT/CeSOS.
IMT 2010-58
Kristiansen, David
Wave Induced Effects on Floaters of Aquaculture Plants, Ph.d.-thesis, CeSOS.
IMT 2010-59
Ludvigsen, Martin
An ROV-Toolbox for Optical and Acoustic Scientific Seabed Investigation. Ph.d.-thesis IMT.
IMT
Hals, Jørgen
Modelling and Phase Control of Wave-Energy Converters. Ph.d.thesis, CeSOS.
Shu, Zhi
Uncertainty Assessment of Wave Loads and Ultimate Strength of Tankers and Bulk Carriers in a Reliability Framework. Ph.d. Thesis, IMT/ CeSOS
Shao, Yanlin
Numerical Potential-Flow Studies on WeaklyNonlinear Wave-Body Interactions with/without Small Forward Speed, Ph.d.thesis,CeSOS.
Califano, Andrea
Dynamic Loads on Marine Propellers due to Intermittent Ventilation. Ph.d.thesis, IMT.
El Khoury, George
Numerical Simulations of Massively Separated Turbulent Flows, Ph.d.-thesis, IMT
Seim, Knut Sponheim
Mixing Process in Dense Overflows with Emphasis on the Faroe Bank Channel Overflow. Ph.d.thesis, IMT
Jia, Huirong
Structural Analysis of Intect and Damaged Ships in a Collission Risk Analysis Perspective. Ph.d.thesis CeSoS.
IMT 2010-67
Jiao, Linlin
Wave-Induced Effects on a Pontoon-type Very Large Floating Structures (VLFS). Ph.D.-thesis, CeSOS.
IMT 2010-68
Abrahamsen, Bjørn Christian
Sloshing Induced Tank Roof with Entrapped Air Pocket. Ph.d.thesis, CeSOS.
IMT 2011-69
Karimirad, Madjid
Stochastic Dynamic Response Analysis of SparType Wind Turbines with Catenary or Taut Mooring Systems. Ph.d.-thesis, CeSOS.
IMT 2011-70
Erlend Meland
Condition Monitoring of Safety Critical Valves. Ph.d.-thesis, IMT.
IMT – 2011-71
Yang, Limin
Stochastic Dynamic System Analysis of Wave Energy Converter with Hydraulic Power Take-Off, with Particular Reference to Wear Damage Analysis, Ph.d. Thesis, CeSOS.
2009-57
2010-60
IMT 2010- 61 IMT 2010-62 IMT 2010-63 IMT 2010-64 IMT 2010-65 IMT 2010-66
97
IMT – 2011-72
Visscher, Jan
Application of Particla Image Velocimetry on Turbulent Marine Flows, Ph.d.Thesis, IMT.
IMT – 2011-73
Su, Biao
Numerical Predictions of Global and Local Ice Loads on Ships. Ph.d.Thesis, CeSOS.
IMT – 2011-74
Liu, Zhenhui
Analytical and Numerical Analysis of Iceberg Collision with Ship Structures. Ph.d.Thesis, IMT.
IMT – 2011-75
Aarsæ ther, Karl Gunnar
Modeling and Analysis of Ship Traffic by Observation and Numerical Simulation. Ph.d.Thesis, IMT.
Imt – 2011-76
Wu, Jie
Hydrodynamic Force Identification from Stochastic Vortex Induced Vibration Experiments with Slender Beams. Ph.d.Thesis, IMT.
Imt – 2011-77
Amini, Hamid
Azimuth Propulsors in Off-design Conditions. Ph.d.Thesis, IMT.
IMT –
Nguyen, Tan-Hoi
Toward a System of Real-Time Prediction and Monitoring of Bottom Damage Conditions During Ship Grounding. Ph.d.thesis, IMT.
IMT2011-79
Tavakoli, Mohammad T.
Assessment of Oil Spill in Ship Collision and Grounding, Ph.d.thesis, IMT.
IMT2011-80
Guo, Bingjie
Numerical and Experimental Investigation of Added Resistance in Waves. Ph.d.Thesis, IMT.
IMT2011-81
Chen, Qiaofeng
Ultimate Strength of Aluminium Panels, considering HAZ Effects, IMT
IMT-
Kota, Ravikiran S.
Wave Loads on Decks of Offshore Structures in Random Seas, CeSOS.
Sten, Ronny
Dynamic Simulation of Deep Water Drilling Risers with Heave Compensating System, IMT.
Berle, Ø yvind
Risk and resilience in global maritime supply chains, IMT.
Fang, Shaoji
Fault Tolerant Position Mooring Control Based on Structural Reliability, CeSOS.
You, Jikun
Numerical studies on wave forces and moored ship motions in intermediate and shallow water, CeSOS.
Xiang ,Xu
Maneuvering of two interacting ships in waves, CeSOS
2011-78
2012-82 IMT2012-83 IMT2012-84 IMT2012-85 IMT2012-86 IMT2012-87
98
IMT-
Dong, Wenbin
Time-domain fatigue response and reliability analysis of offshore wind turbines with emphasis on welded tubular joints and gear components, CeSOS
IMT2012-89
Zhu, Suji
Investigation of Wave-Induced Nonlinear Load Effects in Open Ships considering Hull Girder Vibrations in Bending and Torsion, CeSOS
IMT2012-90
Zhou, Li
Numerical and Experimental Investigation of Station-keeping in Level Ice, CeSOS
IMT2012-91
Ushakov, Sergey
Particulate matter emission characteristics from diesel enignes operating on conventional and alternative marine fuels, IMT
IMT2013-1
Yin, Decao
Experimental and Numerical Analysis of Combined In-line and Cross-flow Vortex Induced Vibrations, CeSOS
IMT-
Kurniawan, Adi
Modelling and geometry optimisation of wave energy converters, CeSOS
IMT2013-3
Al Ryati, Nabil
Technical condition indexes doe auxiliary marine diesel engines, IMT
IMT2013-4
Firoozkoohi, Reza
Experimental, numerical and analytical investigation of the effect of screens on sloshing, CeSOS
IMT-
Ommani, Babak
Potential-Flow Predictions of a Semi-Displacement Vessel Including Applications to Calm Water Broaching, CeSOS
IMT2013-6
Xing, Yihan
Modelling and analysis of the gearbox in a floating spar-type wind turbine, CeSOS
IMT-72013
Balland, Océane
Optimization models for reducing air emissions from ships, IMT
IMT-82013
Yang, Dan
Transitional wake flow behind an inclined flat plate----Computation and analysis, IMT
IMT-92013
Abdillah, Suyuthi
Prediction of Extreme Loads and Fatigue Damage for a Ship Hull due to Ice Action, IMT
IMT-102013
Ramìrez, Pedro Agustìn Pèrez
Ageing management and life extension of technical systemsConcepts and methods applied to oil and gas facilities, IMT
IMT-112013
Chuang, Zhenju
Experimental and Numerical Investigation of Speed Loss due to Seakeeping and Maneuvering. IMT
IMT-122013
Etemaddar, Mahmoud
Load and Response Analysis of Wind Turbines under Atmospheric Icing and Controller System Faults with Emphasis on Spar Type Floating Wind Turbines, IMT
2012-88
2013-2
2013-5
99
IMT-132013
Lindstad, Haakon
Strategies and measures for reducing maritime CO2 emissons, IMT
IMT-142013
Haris, Sabril
Damage interaction analysis of ship collisions, IMT
IMT-152013
Shainee, Mohamed
Conceptual Design, Numerical and Experimental Investigation of a SPM Cage Concept for Offshore Mariculture, IMT
IMT-162013
Gansel, Lars
Flow past porous cylinders and effects of biofouling and fish behavior on the flow in and around Atlantic salmon net cages, IMT
IMT-172013
Gaspar, Henrique
Handling Aspects of Complexity in Conceptual Ship Design, IMT
IMT-182013
Thys, Maxime
Theoretical and Experimental Investigation of a Free Running Fishing Vessel at Small Frequency of Encounter, CeSOS
IMT-192013
Aglen, Ida
VIV in Free Spanning Pipelines, CeSOS
IMT-12014
Song, An
Theoretical and experimental studies of wave diffraction and radiation loads on a horizontally submerged perforated plate, CeSOS
IMT-22014
Rogne, Ø yvind Ygre
Numerical and Experimental Investigation of a Hinged 5-body Wave Energy Converter, CeSOS
IMT-32014
Dai, Lijuan
Safe and efficient operation and maintenance of offshore wind farms ,IMT
IMT-42014
Bachynski, Erin Elizabeth
Design and Dynamic Analysis of Tension Leg Platform Wind Turbines, CeSOS
IMT-52014
Wang, Jingbo
Water Entry of Freefall Wedged – Wedge motions and Cavity Dynamics, CeSOS
IMT-62014
Kim, Ekaterina
Experimental and numerical studies related to the coupled behavior of ice mass and steel structures during accidental collisions, IMT
IMT-72014
Tan, Xiang
Numerical investigation of ship’s continuous- mode icebreaking in leverl ice, CeSOS
IMT-82014
Muliawan, Made Jaya
Design and Analysis of Combined Floating Wave and Wind Power Facilities, with Emphasis on Extreme Load Effects of the Mooring System, CeSOS
IMT-92014
Jiang, Zhiyu
Long-term response analysis of wind turbines with an emphasis on fault and shutdown conditions, IMT
IMT-102014
Dukan, Fredrik
ROV Motion Control Systems, IMT
100
IMT-112014
Grimsmo, Nils I.
Dynamic simulations of hydraulic cylinder for heave compensation of deep water drilling risers, IMT
IMT-122014
Kvittem, Marit I.
Modelling and response analysis for fatigue design of a semisubmersible wind turbine, CeSOS
IMT-132014
Akhtar, Juned
The Effects of Human Fatigue on Risk at Sea, IMT
IMT-142014
Syahroni, Nur
Fatigue Assessment of Welded Joints Taking into Account Effects of Residual Stress, IMT
IMT-12015
Bøckmann, Eirik
Wave Propulsion of ships, IMT
IMT-22015
Wang, Kai
Modelling and dynamic analysis of a semisubmersible floating vertical axis wind turbine, CeSOS
IMT-32015
Fredriksen, Arnt Gunvald
A numerical and experimental study of a twodimensional body with moonpool in waves and current, CeSOS
IMT-42015
Jose Patricio Gallardo Canabes
Numerical studies of viscous flow around bluff bodies, IMT
IMT-52015
Vegard Longva
Formulation and application of finite element techniques for slender marine structures subjected to contact interactions, IMT
IMT-62015
Jacobus De Vaal
Aerodynamic modelling of floating wind turbines, CeSOS
IMT-72015
Fachri Nasution
Fatigue Performance of Copper Power Conductors, IMT
IMT-82015
Oleh I Karpa
Development of distributions for technology,CeSOS
IMT-92015
Daniel de Almeida Fernandes
An output feedback motion control system for ROVs, AMOS
IMT-102015
Bo Zhao
Particle Filter for Fault Diagnosis: Application to Dynamic Positioning Vessel and Underwater Robotics, CeSOS
IMT-112015
Wenting Zhu
Impact of emission transportation, IMT
IMT-122015
Amir Rasekhi Nejad
Dynamic Analysis and Design of Gearboxes in Offshore Wind Turbines in a Structural Reliability Perspective, CeSOS
IMT-132015
Arturo Jesùs Ortega Malca
Dynamic Response of Flexibles Risers due to Unsteady Slug Flow, CeSOS
101
bivariate extreme value applications in marine
allocation
in
maritime
IMT-142015
Dagfinn Husjord
Guidance and decision-support system for safe navigation of ships operating in close proximity, IMT
IMT-152015
Anirban Bhattacharyya
Ducted Propellers: Behaviour in Waves and Scale Effects, IMT
IMT-162015
Qin Zhang
Image Processing for Ice Parameter Identification in Ice Management, IMT
IMT-12016
Vincentius Rumawas
Human Factors in Ship Design and Operation: An Experiential Learning, IMT
IMT-22016
Martin Storheim
Structural response in ship-platform and ship-ice collisions, IMT
IMT-32016
Mia Abrahamsen Prsic
Numerical Simulations of the Flow around single and Tandem Circular Cylinders Close to a Plane Wall, IMT
IMT-42016
Tufan Arslan
Large-eddy simulations of cross-flow around ship sections, IMT
IMT-52016
Pierre Yves-Henry
Parametrisation of aquatic vegetation in hydraulic and coastal research,IMT
IMT-62016
Lin Li
Dynamic Analysis of the Instalation of Monopiles for Offshore Wind Turbines, CeSOS
IMT-72016
Ø ivind Kåre Kjerstad
Dynamic Positioning of Marine Vessels in Ice, IMT
IMT-82016
Xiaopeng Wu
Numerical Analysis of Anchor Handling and Fish Trawling Operations in a Safety Perspective, CeSOS
IMT-92016
Zhengshun Cheng
Integrated Dynamic Analysis of Floating Vertical Axis Wind Turbines, CeSOS
IMT-102016
Ling Wan
Experimental and Numerical Study of a Combined Offshore Wind and Wave Energy Converter Concept
IMT-112016
Wei Chai
Stochastic dynamic analysis and reliability evaluation of the roll motion for ships in random seas, CeSOS
IMT-122016
Ø yvind Selnes Patricksson
Decision support for conceptual ship design with focus on a changing life cycle and future uncertainty, IMT
IMT-132016
Mats Jørgen Thorsen
Time domain analysis of vortex-induced vibrations, IMT
IMT-142016
Edgar McGuinness
Safety in the Norwegian Fishing Fleet – Analysis and measures for improvement, IMT
IMT-152016
Sepideh Jafarzadeh
Energy effiency and emission abatement in the fishing fleet, IMT
102
IMT-162016
Wilson Ivan Guachamin Acero
Assessment of marine operations for offshore wind turbine installation with emphasis on response-based operational limits, IMT
IMT-172016
Mauro Candeloro
Tools and Methods for Autonomous Operations on Seabed and Water Coumn using Underwater Vehicles, IMT
IMT-182016
Valentin Chabaud
Real-Time Hybrid Model Testing of Floating Wind Tubines, IMT
IMT-12017
Mohammad Saud Afzal
Three-dimensional streaming in a sea bed boundary layer
IMT-22017
Peng Li
A Theoretical and Experimental Study of Waveinduced Hydroelastic Response of a Circular Floating Collar
IMT-32017
Martin Bergström
A simulation-based design method for arctic maritime transport systems
IMT-42017
Bhushan Taskar
The effect of waves on marine propellers and propulsion
IMT-52017
Mohsen Bardestani
A two-dimensional numerical and experimental study of a floater with net and sinker tube in waves and current
IMT-62017
Fatemeh Hoseini Dadmarzi
Direct Numerical Simualtion of turbulent wakes behind different plate configurations
IMT-72017
Michel R. Miyazaki
Modeling and control of hybrid marine power plants
IMT-82017
Giri Rajasekhar Gunnu
Safety and effiency enhancement of anchor handling operations with particular emphasis on the stability of anchor handling vessels
IMT-92017
Kevin Koosup Yum
Transient Performance and Emissions of a Turbocharged Diesel Engine for Marine Power Plants
IMT-102017
Zhaolong Yu
Hydrodynamic and structural aspects of ship collisions
IMT-112017
Martin Hassel
Risk Analysis and Modelling of Allisions between Passing Vessels and Offshore Installations
IMT-122017
Astrid H. Brodtkorb
Hybrid Control of Marine Vessels – Dynamic Positioning in Varying Conditions
IMT-132017
Kjersti Bruserud
Simultaneous stochastic model of waves and current for prediction of structural design loads
IMT-142017
Finn-Idar Grøtta Giske
Long-Term Extreme Response Analysis of Marine Structures Using Inverse Reliability Methods
103
IMT-152017
Stian Skjong
Modeling and Simulation of Maritime Systems and Operations for Virtual Prototyping using coSimulations
IMT-12018
Yingguang Chu
Virtual Prototyping for Marine Crane Design and Operations
IMT-22018
Sergey Gavrilin
Validation of ship manoeuvring simulation models
IMT-32018
Jeevith Hegde
Tools and methods to manage risk in autonomous subsea inspection,maintenance and repair operations
IMT-42018
Ida M. Strand
Sea Loads on Closed Flexible Fish Cages
IMT-52018
Erlend Kvinge Jørgensen
Navigation and Control of Underwater Robotic Vehicles
IMT-62018
Bård Stovner
Aided Intertial Navigation of Underwater Vehicles
IMT-72018
Erlend Liavåg Grotle
Thermodynamic Response Enhanced by Sloshing in Marine LNG Fuel Tanks
IMT-82018
Børge Rokseth
Safety and Verification of Advanced Maritime Vessels
IMT-92018
Jan Vidar Ulveseter
Advances in Semi-Empirical Time Modelling of Vortex-Induced Vibrations
IMT-102018
Chenyu Luan
Design and analysis for a steel braceless semisubmersible hull for supporting a 5-MW horizontal axis wind turbine
IMT-11-
Carl Fredrik Rehn
Ship Design under Uncertainty
Ø yvind Ø degård
Towards Autonomous Operations and Systems in Marine Archaeology
Stein Melvæ r Nornes
Guidance and Control of Marine Robotics for Ocean Mapping and Monitoring
Petter Norgren
Autonomous Underwater Vehicles in Arctic Marine Operations: Arctic marine research and ice monitoring
Minjoo Choi
Modular Adaptable Ship Design for Handling Uncertainty in the Future Operating Context
Domain
2018 IMT-122018 IMT-132018 IMT-142018 IMT-152018
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