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Submitted to the 21 International Conference on Nuclear Engineering ICONE21
SMALL MODULAR REACTORS: URANIUM RESOURCE REQUIREMENTS, WASTE GENERATION AND PROLIFERATION RISK ASSESSMENT
M. V. Ramana*, Alexander Glaser, and Laura Berzak Hopkins Nuclear Futures Laboratory, Princeton University Princeton, New Jersey, USA *email:
[email protected] Keywords: small modular reactors, SMR, neutronic models, uranium requirements, proliferation risk
ABSTRACT Small Modular Reactors (SMRs) with power levels of below 300 MW(e) appear to have several favorable characteristics and their deployment might help bring about a big change in how nuclear power fares in the future. Numerous SMR designs with distinct characteristics are under development in several countries. To capture the impacts of these different designs, we have developed notional models for two leading SMR types and performed neutronics calculations on these to estimate uranium resource requirements. These are then used to explore the resulting waste generation and potential proliferation risks.
1. INTRODUCTION Over the last few years, nuclear reactor suppliers in the United States, Russia, China, Japan, South Korea, India, France, and Argentina are developing Small Modular Reactors (SMRs) with power levels below 300 MW(e) [1–3]. These reactors are expected to cost significantly less than current gigawatt-scale reactors and to take much less time to construct, and thereby address some of the economic challenges faced by utilities interested in constructing nuclear power plants [4,5]. Because they are smaller, SMRs will be easier to transport,
which might enable installation in more diverse sites, including off-grid in remote regions [6]. Due to these and other desirable factors, deployment of such SMRs is expected to help significantly change how nuclear power fares in the future. While economics is undoubtedly a significant constraint, there are other considerations that affect prospects for nuclear power, in particular, radioactive waste generation and the potential for nuclear weapons proliferation. In the following part of the paper, we introduce some notional SMR designs and explore their uranium fuel and enrichment requirements, and their consequent rate of waste generation. This is followed by an analysis of the associated risks of proliferation using a Markov-chain methodology. 2. NEUTRONIC MODELS FOR NOTIONAL SMR DESIGNS AND URANIUM RESOURCE REQUIREMENTS SMR designs under development vary by power output, fuel type and enrichment level, refueling frequency, fuel geometry, and siting. In order to explore these, we have developed and analyzed two notional SMRs that capture some generic features of many proposed SMRs. Using neutronics calculations carried out with the MCODE computer code system, which links the Monte Carlo neutron transport code
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MCNP and the ORIGEN2 point-depletion code and permits full-core burnup calculations [7–9], we carry out an assessment of resource and fuel requirements. In the initial phase, our analysis focuses on the neutronics of once-through systems. The first category of SMRs that we model are based on light-water reactor technology.1 These integral pressurizedwater reactors (iPWRs) do not envision fuel-element shuffling but aim to adopt a simplified all-in/all-out core management scheme. They typically use standard fuel elements, but variants with reduced height have also been proposed to achieve typical diameter-to-height ratios for the core.2 Average core power densities on the order of 100 W/cm3 can be achieved in these designs; when scaled to a reference power level of 200 MW(e) (η = 0.33, 600 MWt), this corresponds to about 35 full-height or 50–70 reduced height fuel assemblies. A typical arrangement could be a 37 or 69 element core.2
Figure 2 shows k(eff) versus core average burnup with a reactivity drop of Δρ = –0.0064 per MWd/kg for burnups higher than 10 MWd/kg. A core-average burnup of 26–34 MWd/kg can be achieved for this configuration; this corresponds to a refueling frequency of 2½–3½ years and is consistent with values quoted by many reactor vendors. Note that this burnup is significantly lower than the 50 MWd/kg achieved in large light-water reactors using fuel of the same initial enrichment. This is a direct consequence of the renunciation of fuel shuffling and the smaller core size, which increases neutron leakage from the core. The spent fuel composition is similar to typical spent fuel from PWRs. At a discharge burnup of 30 MWd/kg, about 156 kg of plutonium (66% Pu-239, 17% Pu 240, and 13% Pu 241) have built up in the core of the iPWR, which corresponds to a mass fraction of about 0.9%.
For the analysis below, we have defined a notional iPWR that is representative for reactors in this group (Figure 1).3
Figure 1. Core layout and fuel design for the notional iPWR. The geometry of the fuel assemblies and the fuel pins is based on typical PWR specifications. Fuel pins of the 69 fuel assemblies in the core (left) are assigned to seven radial zones as indicated in the figure for the reactor burnup calculations. The uranium enrichment level of the fuel is 5.0% throughout the core, and the total heavy-metal inventory in the core is 18.0 metric tons at beginning-of-life. The core consists of 69 PWR-type fuel assemblies with a 17x17 geometry and a reduced active height of 2.0 m on a 9x9 grid; each fuel assembly has 264 fueled and 25 unfueled positions. For the (full-core) reactor burnup calculations performed with MCODE (MCNP/ORIGEN), 35 burnup zones with 7 radial zones and 5 axial zones have been defined. Fuel pins from the same assembly are assigned to different radial burnup zones depending on their position in the assembly to assure best numerical results. 1
These appear to be aimed at demonstrating the commercial viability of the SMR concept in the near term and includes designs such as the W-SMR (Westinghouse), mPower (Babcock & Wilcox), NuScale (NuScale Power), SMART (KAERI), and HI-SMUR 140 (Holtec). 2 These standard configurations are based on square grids, in which three assemblies have been removed from each corner, i.e., 9 x 9 – 4 x 3 = 69 and 7 x 7 – 4 x 3 = 37. See also Figure 2. 3 The MCNP input deck is available at http://nuclearfutures.princeton.edu/smr/ipwr.
Figure 2. k(eff) versus core average burnup for the notional iPWR. MCODE (MCNP/ORIGEN) reactor burnup calculations. Because of the higher neutron leakage from the core and the all-in/all-out core management scheme, the reactivity drops more rapidly than in a gigawatt-scale reactor. With an initial fuel enrichment of 5%, the core average burnup is between 26–34 MWd/kg. The second category of proposed reactors have long-lived core (LLC) designs that do not require refueling for two or more decades. These reactors are typically fast-spectrum designs and may be cooled by helium, sodium, or other liquidmetals such as lead and lead-bismuth eutectics. Some vendors claim that these will be suitable for dealing with spent fuel or plutonium stockpiles.4 Other vendors aim for selling to countries with small electric grids interested in developing nuclear power systems (or remote locations in developed countries) and claim that these reactors are designed for the possibility of unattended operation or with minimal staff.5 The idea seems to be to deliver a self-contained reactor unit and 4
This group includes waste or plutonium burner reactors such as EM2 (General Atomics), PRISM (GE-Hitachi), and TWR (Terrapower). Several power ratings (low, medium, and high) have been proposed for the TWR concept. 5 Reactor designs include Gen4 Module (G4M) (Gen 4 Energy, formerly known as Hyperion), 4S (Toshiba), SSTAR (Lawrence Livermore, Los Alamos, and Argonne National Laboratories), and KLT-40S (Atomenergoprom/OKBM).
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remove a spent unit at the end of the reactor lifetime, most likely after some years of on-site cooling. Because of various technical challenges, large-scale deployment of such fastneutron SMRs cannot be expected within the next decade or two, especially given the history of fast-neutron reactors constructed so far [10].
Figure 3: Uranium-235 depletion and plutonium buildup in the core of a notional 200 MW(e) SMR with a long-lived core. The total plutonium inventory in the core is about 2.8 tons after 30 years of operation, with an average plutonium-239 content of 80%. MCODE (MCNP/ORIGEN) reactor burnup calculations.
Nevertheless, we explore the fuel and resource requirements of a notional SMR with a long-lived core. These reactors typically envision in-situ breed-and-burn to maximize fuel burnup. A natural assumption for the core configuration is to use enriched “starter fuel” in the center of the core surrounded by axial and radial depleted-uranium blankets. Here, we envision a core with a diameter and height of 2.0 meters and a power level of 200 MW(e) (η = 0.40, 500 MWt), which corresponds to an average core power density of about 80 W/cm3. We further assume that the central fuel zone and the blanket zone each account for 50% of the available core volume. In our simplified model, the core is fully homogenized using fuel, cladding, and coolant volume fractions in the core of 50%, 25%, and 25%, respectively. The core itself is surrounded by a thick beryllium-oxide reflector. The full-core model is subdivided into 90 separate burnup zones (42 core and 48 blanket zones). Neutronics calculations for this configuration confirm that an enrichment level of 10–15% for the starter fuel is sufficient to achieve a core average burnup of 110 MWd/kg and the target core life of 25–30 years. Specifically, for 12%enriched starter fuel, reactivity reaches a maximum of keff = 1.06 after 3–4 years and stabilizes thereafter at a quasi-constant reactivity loss rate of Δρ = –0.0003 per MWd/kg, which is equivalent to Δρ = –0.0012 per year.
The results from the neutronics calculations for these two notional SMRs can be used to determine basic resource and fuel requirements and to compare them to reference values for standard gigawatt-scale light-water reactors. Table 1 summarizes fuel demand, uranium and enrichment requirements, plutonium inventory in spent fuel, and waste volumes scaled to a reference power generation of 1000 MW(e) for 9000 effective full-power days, e.g. 300 days per year for 30 years.6 This electricity could be generated by one gigawattscale reactor or a suite of five 200-MW(e) SMRs.
Figure 3 shows the depletion of uranium-235 and the buildup of plutonium from beginning to end of life of the core. The plutonium isotopics in the core and blanket zones are very similar, and the material remains weapon-grade (90–93% Pu239) for the first 7–10 years. By that time, 1.0–1.3 tons of plutonium would have accumulated in the reactor. Upon discharge, the core contains 2.8 tons of plutonium with an average Pu-239 content of 80%.
Table 1. Basic resource and fuel requirements for a standard light-water reactor (1000 MW(e)), five small modular LWRs (iPWRs, 200 MW(e) each), and five notional SMR (200 MW(e) each) with a long-lived core. Significant differences to the reference case are highlighted. All numbers are scaled to a power generation of 1000 MW(e) for 9000 effective full-power days (e.g. 30 g years, 300 days per year). The low burnup of the small modular LWR (iPWR) directly translates into a respective increase of 67% in uranium, enrichment, and fuel demands. While fuel-related costs represent a smaller fraction of the total cost of nuclear electricity, this increase could affect supply and demand of uranium and enrichment capacities, and be used as an argument for reprocessing, especially if this technology is deployed on a scale similar to the one shown in Figure 1.7 Due to the lower burnup and the associated higher fuel throughput, cumulative 6
This corresponds to a capacity factor of about 82%, which is somewhat lower than values achieved today in some countries but does not affect the comparison of different reactor systems here. More importantly, SMR vendors often emphasize that multi-module sites offer the opportunity for load following operation, which would increase flexibility but decrease overall capacity factor. 7 We are not suggesting that the use of iPWR versus standard LWR could lead to shortages of uranium supplies or enrichment capacities. The incremental increase could, however, be used to justify new reprocessing or enrichment programs.
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plutonium production in the iPWR is about 40% higher than for a standard PWR but the concentration of plutonium in the spent fuel is slightly lower than in the high-burnup case (0.9–1.0% versus 1.2%); overall, the “attractiveness” of spent fuel from an iPWR for reprocessing is similar to the reference case. Fast-spectrum SMR with a long-lived core (LLC), on the other hand, have very different requirements for uranium resources. In principle, of course, a traditional fast-breeder fuel cycle could be used to “self-sustain” the reactor and further reduce resource requirements. In fact, many SMR developers with designs in this category propose exactly this strategy, i.e., eventual reprocessing of the discharged cores and reuse of recovered plutonium as fuel.8 However, even if, after 30 years of operation, the spent fuel unloaded from such a LLC SMR is not further processed and prepared for final disposal, a significant reduction of uranium and enrichment requirements would be achieved: for this particular notional design, they are 53% and 44% below those of a standard LWR.9 This could be perceived as an important advantage of reactors in this category. The total amount of plutonium generated with this notional long-lived design, however, is much larger than for the other reactors: at end-of-life, it amounts to 14 tons of plutonium for the reference fleet of five SMR—or 2.8 tons of plutonium per unit as shown in Figure 4; this corresponds to a 60% to 110% increase in net plutonium production as compared to iPWRs and LWRs respectively. More importantly, the concentration of plutonium in the spent fuel is about 6–7 times higher than in LWR fuel, i.e., almost 70 kg versus 10–12 kg per ton of fuel upon discharge. Overall, these characteristics could create a strong incentive to recover the plutonium from the spent fuel, just as the developers of many designs suggest,10 which in turn has to be taken into account for a comprehensive proliferation risk assessment of SMRs with long-lived cores. The remainder of this paper offers a preliminary assessment of this kind. 3. ASSESSING PROLIFERATION RISK USING A MARKOV-CHAIN METHOD The extent to which the presence of a nuclear power reactor and its attendant technical and human resource systems contributes to the risk of proliferation is debated in the 8
Even though SMR vendors have by and large refrained from calling for reprocessing, recycling of fuel is implicit in the statements that no or very little enrichment services are needed after the first generation of reactors. 9 For the estimate of resource requirements, the depleted uranium needed for the blankets (102 metric tons) is not considered. Note also that the LLC SMR operates at a higher thermal efficiency, which further improves resource utilization. 10 The Nuclear Energy Agency points out that “Generically, all fast spectrum small and modular reactors are being designed to operate in a closed fuel cycle. […] The spent fuel, after cooling and reprocessing, can be reloaded in the core with an addition of natural or depleted uranium. The reprocessing would then be limited to removal of the fission products without further separation of heavy nuclides” [3]. Note that this is a generic assessment and there may be some exceptions.
literature. In general, the proliferation risk related to any nuclear system depends on both non-technical and technical factors, which include characteristics of the proliferator, including goals, resources, motivations, and technical capabilities; intrinsic features of the nuclear energy system (i.e., characteristics of the technology and design); fuel-cycle choices related to uranium enrichment or spent fuel reprocessing; extrinsic measures, such as domestic institutional measures and international safeguards; and consequences of proliferation success, especially ones related to security and geo-strategy [11]. Any efforts at proliferation resistance “will need to involve intrinsic (technological) features and extrinsic (institutional) measures” [12]. When assessing a new technology such as SMRs, however, it is the intrinsic features that are of the greatest interest. Below, we compare the differences in proliferation risk between meeting the same power requirements using SMRs, both iPWRs and LLC SMRs, and standard-sized LWRs, assuming that the types of applied safeguards and associated efficacy are identical for all systems. Our assessment of the proliferation risk for these systems depends on the requirements and types of fresh fuel and the characteristics of the spent fuel, which have been described in the previous section. For the purposes of this assessment, we assume that the host country in question has adopted an open fuel cycle and has no declared uranium enrichment or reprocessing plants. But since we are interested in proliferation risk, we assume that it has constructed a clandestine reprocessing plant that it uses to separate plutonium from diverted spent fuel assemblies. Spent fuel elements can be diverted from any stage in the fuel cycle where they are present. The approach we have adopted uses Markov-models and the software code PRCALC, developed by analysts at Brookhaven National Laboratory to study the proliferation risks associated with nuclear power systems [13,14]. Previous studies using this approach have examined a range of systems; for example, one study compared the proliferation risks of stages such as TRU extraction and pin fabrication in the sodium fast reactor (ESFR) system. Results presented here are based on an updated 2012 version of PRCALC. In a Markov model, the quantity of interest is represented as a stochastic process with a conditional probability distribution of future states dependent only upon the present state, not on the sequence of states leading to the present state. Models contain sets of discrete nodes (states) with specified nuclear material at each state and transitions between them treated as time-dependent random processes characterized by physically meaningful time parameters; the transition is modeled as an exponentially distributed random process, where the time parameter is the mean value of the exponential distribution. Models can incorporate various states, declared and clandestine, (e.g., fresh fuel transport, reactor operation, spent fuel transport, and clandestine separation) with associated
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fuel types transitioning from state to state with associated transition time periods.
storage facility, and in Stage VI they are stored before being transported back to the country of origin.
Once a system’s states (nodes and transitions with associated time and material parameters) are defined, and proliferators’ potential target nodes, target material, and proliferation rate are selected, the PRCALC code calculates several quantities related to proliferation risk and resistance. The quantities of particular interest are the probability of the proliferator successfully acquiring one significant quantity (SQ) of material by diverting small quantities from various points in the fuel cycle model and the average time taken for such diversion. This latter diversion time is given by:
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TDIV =
Mj
∑ ( EQ ∑ d j
j
j i
)
i
where Mj represents the annual quantity of material j; EQj represents the quantity of material j needed for 1 SQ, and dij is the diversion rate at node i of material type j. In the Markov methodology, the scenario we have chosen to analyze corresponds to a continuous material flow scenario [15]. The fuel cycle and diversion are schematically shown in Figure 4.
Figure 4. Reference Markov Model for plutonium diversion scenario. Takes into account intrinsic and extrinsic features (safeguards) and assumes existence of clandestine system elements, in this case a clandestine reprocessing plant. The stage times listed in each of the nodes correspond to the average residence time for a fuel assembly in that stage; the in-core residence time is 4.5 years for the PWR, 3 years for the iPWR, and 30 years for the LLC SMR. Diversion of spent fuel is not equivalent to successful proliferation. Proliferators may still fail to separate out 1 SQ of material due to technical difficulties in the reprocessing of the diverted material. Stage I represents the delivery of fresh fuel assemblies from outside the country to one centralized location (e.g. a storage facility near a port). In Stage II, these fresh fuel assemblies are transported to the reactor site. Stage III refers to the period when the fuel assemblies are loaded in the reactor(s). During Stage IV, the spent fuel assemblies are unloaded from the reactor and cooled in a pool at the reactor site. In Stage V, the spent fuel assemblies are transported to a centralized
Table 2. Fuel assemblies and plutonium inventories associated with a 10-GW fleet of standard light-water reactor technology, small modular iPWRs, and LLC SMRs. These figures are used as inputs by PRCALC in the scenario involving the diversion of spent fuel and separating it in a clandestine reprocessing plant. Corresponding figures for uranium are needed for a scenario involving clandestine enrichment. All declared facilities are assumed to be safeguarded. The safeguards methods assumed include auditing of nuclear material accounting records or reports, including records of power history, physical inventory listings, and shipment receipts; physical inventory verification using visual inspection, Cerenkov viewing devices, gamma spectroscopy of spent fuel, and so on; surveillance and monitoring using cameras, neutron counting, and radioisotope assays; and containment through the use of seals on reactor vessels, shipping casks, and safeguards equipment [13,14,16]. Figure 5 below shows the proliferation success probability to divert 1 SQ of plutonium (8 kg) as a function of installed capacity met with reactors, all located at the same site. For comparison, we have also plotted the analogous results for the same capacity met with gigawatt-scale LWRs. These results implicitly assume an equilibrium or steady-state situation, which is a reasonable approximation to a case with a larger fleet of reactors operating. Based on the neutronics calculations from Part II, each spent fuel assembly contains 2.3 kg, 5.2 kg, and 40.5 kg of plutonium in the cases of iPWR, LWR, and LLC SMR, respectively. Thus, obtaining 8 kg (1 SQ) of plutonium would require diversion of 2–4 fuel assemblies for LWRs and iPWRs, whereas even the diversion of one spent fuel assembly from an SMR with a long-lived core would suffice for over 5 SQs.11
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The International Atomic Energy Agency has noted that “except in some specific cases, the Agency does not have a general technique for partial defects verification” [17].
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time decreases with the number of fuel assemblies and approaches an asymptotic value of 24 weeks, the assumed time that it takes to reprocess the diverted spent fuel and obtain enough separated plutonium for one weapon. The calculated times are valid for an equilibrium or steady-state situation that corresponds to case with a very large number of reactors operating.
Figure 5. Proliferation success probability for a plutonium diversion scenario. The probability scales roughly with the number of fuel assemblies and their plutonium content. These calculations assume that the types of applied safeguards and their effectiveness are identical for all systems. The scenario does not take into account the potential impact of geographical distribution of reactors, which is likely to be different for SMRs and gigawatt-scale reactors. The results of the Markov analysis show that for each reactor type both measures of proliferation risk change in an intuitive way—success probability increases (Figure 5) and time decreases (Figure 6)—with increasing flow of material. The success probability for diversion of plutonium is greatest for SMRs with long-lived cores and smallest for the 1 GW LWR, with the iPWRs in between. This is a reflection of the larger quantities of plutonium in the spent fuel as described earlier. Note that the calculated probabilities of proliferation success are quite small on the whole and are based on the implicit assumption that the host state intends to proliferate. This comparative analysis shows, however, that the relative differences between the different concepts can be significant unless they are offset by reactor design or dedicated safeguards approaches.
These results implicitly assume that the efficiency of safeguards is similar in all these systems. Since safeguards are implemented in a system-specific fashion, this would have to be re-evaluated once there is greater clarity on the exact nature of safeguards to be applied to SMRs. This is particularly relevant because of ongoing “Safeguards and Security by Design” activities that aim to evaluate reactor and other nuclear facility designs for proliferation vulnerabilities at an early stage.12At the same time, some technical characteristics of SMRs do increase some diversion risks while reducing others. For example, in the case of one SMR design, the use of a “common refueling area for multiple modules” was found to reduce the effectiveness of safeguards [19]. 4. CONCLUSIONS Small Modular Reactors (SMRs) have been advocated as a "game changer" for nuclear energy and interest in this technology remains high in a number of countries. This paper analyzes two broad kinds of SMR technologies, to assess their resource demands, waste generation characteristics, and proliferation risks. We find that small modular reactors are both similar and different from standard light-water reactors. As shown, iPWRs are likely to have higher requirements for uranium ore and enrichment services, and produce a larger volume of nuclear waste compared to gigawatt-scale reactors. This is because of the lower burnup of fuel in iPWRs, which is difficult to avoid because of smaller core size and all-in/all-out core management. On the other hand, in the case of fastspectrum SMRs with long-lived cores, uranium and uranium enrichment requirements as well as waste generation rate are reduced. For both kinds of SMRs discussed here, the increased plutonium production per unit of electrical energy generated translates into an increased proliferation risk. Our results show that the probability of proliferation success probability for a plutonium diversion scenario is higher for a LLC SMR and an iPWR as compared to a LWR, and scales roughly with the number of fuel assemblies and their plutonium content. Likewise, the time needed to acquire 1 SQ of plutonium decreases with the number of fuel assemblies and approaches an asymptotic value of 24 weeks, the assumed time that it takes to reprocess the diverted spent fuel and obtain enough separated plutonium for one weapon.
Figure 6. Proliferation time for a plutonium diversion scenario. Under equilibrium conditions, the proliferation
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The United States Department of Energy Budget Request for 2011-12 indicated that DOE would “conduct ‘safeguards and security by design’ activities that consider proliferation and terrorism risks from the very earliest stages of development” [18].
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While these are preliminary indications of proliferation risk, they do indicate the need for follow-on assessments of greater specificity and including several other factors. More detailed assessments have to account for the geographically more distributed deployment expected for SMRs and design specific details. As is common with proliferation resistance and physical protection methodologies [20], these assessments could also progressively become more detailed as more design information about SMRs and their proposed deployment modes becomes available. However, even at this preliminary stage, the results point to the importance of increased safeguards effectiveness for SMRs. The latter objective might be advanced if SMR designers made “safeguards-friendly” design choices. It also points to the need to rigorously explore new fuel-cycle architectures and the political and economic conditions need to realize those architectures, in advance of actual deployment of SMRs on a wide scale.
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[14] ACKNOWLEDGMENTS The authors are grateful to Meng Yue, Lap-Yan Cheng and Robert Bari of the Brookhaven National Laboratory for sharing the PRCALC software package. REFERENCES [1] [2] [3] [4] [5]
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