Critical Reactor Research Articles

Enhanced heavy oil fouling resistance of cobalt-based spray-deposited coatings by alloy design and heat treatment

Heavy oil hydrocracking fouls critical reactor components, causing premature turnarounds. Developing materials with superior resistance to coking, sulfidation, and wear proves crucial. High-velocity oxy-fuel (HVOF) coating improves materials' properties as an industrial-ready solution. This study explores the effect of alloying elements on the HVOF-sprayed CoCrMoSi coating model and their role in protecting against heavy oil fouling. Heat treatment reduced the coatings' inhomogeneity and microstructural defects, substantially improving their protection against fouling. A novel optical image treatment has been developed to semi-quantitatively assess the surface fouling intensity. The study provides insights into the complex interplay between alloy composition, microstructure, heat treatment, and surface energy in optimizing coating protection against heavy oil fouling.

Constitutive Modeling of Anisotropic Plasticity with ML Algorithms in Metals

Nuclear reactors hold significant promise for mitigating the environmental crisis and achieving a carbon-free world. The advancement of nuclear technology, however, is intricately tied to the materials used in reactors, with metals and alloys forming their core components. Understanding the plasticity and degradation of these materials is crucial to prevent critical reactor failures caused by factors such as radiation-induced embrittlement, creep, and fuel-cladding interactions. While traditional plasticity modeling has relied on constitutive laws and yield functions, the advent of machine learning (ML) and artificial intelligence has opened new avenues for this field. This paper explores the potential of data-driven approaches to enhance plasticity modeling for metals used in nuclear reactors. Recent studies have leveraged ML algorithms, including support vector machines and artificial neural networks, to model yield surfaces and correct theoretical yield functions with experimental data. Despite their accuracy, these models often lack interpretability and generality. To address these challenges, we investigate the applicability of various ML algorithms, i.e. neural networks, logistic regressions, decision trees, K-nearest neighbors, and Gaussian processes (GPs), in developing data-oriented flow rules for plasticity modeling. The paper demonstrates the superiority of GPs in terms of interpretability and generality. Using stress data generated from PyLabFEA, we compared the performance of these algorithms, highlighting the intrinsic uncertainties associated with GP predictions. Our findings indicate that Gaussian process classifiers (GPCs) offer a promising approach for modeling plasticity in metals, providing a balance between precision and physical insight. Additionally, this work presents a deep neural network (DNN) to model anisotropic Hill-type plasticity with perfect test data accuracy (accuracy score: 1.0), which is often hard to achieve with a classification problem. This shows the superiority of DNNs in terms of accuracy in modeling yield functions. The implications of our results for bridging the scale gaps in macrolevel simulations are discussed, and future directions for incorporating microstructural features into ML-based plasticity models are proposed. Overall, the ML framework presented in this paper can be employed for modeling constitutive relations that can be incorporated within traditional Finite Element Method (FEM)–based codes. Specifically, the GPC or DNN developed in this work can be readily swapped with the yield function within the so-called return mapping algorithm of nonlinear FEM-based plasticity subroutines to indicate yielding. Consequently, this merging of ML and FEM will allow us to leverage the geometric representational ability of FEM alongside the superior modeling capabilities of the ML algorithms.

Comparison of Neutronic Analysis for 250 MWth Molten Salt Reactor using Monte Carlo OpenMC Code with Different Nuclear Data Libraries of JENDL 5.0, ENDF/B-VII.1, ENDF/B-VIII.0, and JEFF 3.3

Abstract Nuclear data libraries playian important role in the accuracy of neutronic aspect calculations, which determine various factors in a nuclear reactor design. Likewise, deterministic or Monte Carlo methods significantly affect the calculation results. Thus, the combination of nuclear data library and calculation methods needs to be studied carefully. This research will conduct neutronic analysis for the Molten Salt Reactor (MSR) design, one of the Generation IV reactor types with advanced features for future energy resources, using the Monte Carlo-based program OpenMC and different nuclear data libraries. MSR will be designed for a 250 MWth power capacity, operable for five years. The fuel used will be LiF-BeF2 as a coolant and ThF4-UF4 as the fuel. The compositions for each fuel will be optimized to achieve critical conditions during five years of operation. This research aims to evaluate the use of differentinuclear data libraries on reactor criticality conditions, using the nuclear data libraries ENDF/VIII-B, ENDF/VII.0, JEFF 3.3, and JENDL 5.0. To perform the calculation and analysis, MSR chain depletion modification has to be done for different nuclear data libraries. Then, evaluation will be conducted on effective multiplicationifactor (k-eff), neutron flux spectrum, and cross-section. The results of this research show that the use of JENDL 5.0 provides more optimal critical conditions. This is due to the completeness of JENDL 5.0 nuclear data covering 795 nuclide data and higher fission cross-section values. While ENDF/VIII-B has 557 nuclide data evaluations compared to ENDF/VII.0’s 423 nuclide data, more stable k-eff values are shown for the use of ENDF nuclear data libraries. This research is expected to significantly contribute to meeting Indonesia’s energy needs by providing efficient solutions in MSR design in neutronic aspects using the most accurate nuclear data library.

The Effect of Adding Minor Actinide Fuel Rods on GFR Reactor in Radiopharmaceutical Waste Production Using OpenMC Program

GFR is a generation IV reactor based on helium gas refrigeration capable of working at very high temperatures. The fast spectrum in this reactor makes it possible to use nitride-based fuel, namely Uranium Plutonium Nitride (UN-PuN). Adding minor actinide (MA) material to the primary fuel, UN-PuN can maximize reactor performance to near critical from the beginning to the end of burn-up. This study aims to analyze the effect of adding MA fuel rods to the heterogeneous core of 5 fuel variations (F1, F2, F3, F4, F5) on the probability of radiopharmaceutical waste production. The method in this research is to place MA fuel rods in this study using four designs based on the highest neutron flux value in one fuel assembly. The results of the neutron flux calculation show that the reactor’s active core’s central region (F1, F2, F3) needs to be added to MA fuel rods so that the resulting flux is more evenly distributed. The calculation of reactor criticality shows that Np fuel rod design 4 and Am fuel rod design 1 have the best keff value (keff ≈ 1) among other designs. The burn-up of MA fuel rods produces a minimal probability of producing Tc99m, Sr89, Y90, Rh105, Ag111, I231, and Sm15 radiopharmaceutical waste, even less than 1 kg.

At-power subcritical multiplication in the Advanced Test Reactor during nuclear requalification testing

Power division information during nuclear requalification of the Advanced Test Reactor (ATR) is of considerable interest as an importance function for observed changes to core reactivity. The degree to which a given physical subdivision of a critical reactor acts as a neutron source for other lobes is not analytically characterized for general application. When ATR operates at power, individual power-producing lobes rely on each other as neutron sources in order to maintain constant power, which in general requires either exactly critical multiplication within a reactor or an external neutron source. This work shows that fuel element and lobe powers in ATR can be related with subcritical multiplication theory. Subcritical multiplication factors are computed with a physically validated analytical method based on actual at-power operation, quantifying for each lobe its dependence on other lobes as an external neutron source. This explanation is significant for ATR due to the desire to irradiate a large variety of experiments simultaneously, each having its impact on the core neutron population. For any physical subdivision of any other critical reactor, it is likewise true that the subdivision undergoes only subcritical multiplication.

Burnup and neutronic parameter analysis of GAMA molten salt reactor (GAMA-MSR)

The GAMA molten salt reactor (GAMA-MSR) is a small modular MSR design developed by the Nuclear Reactor Research Team of the Department of Nuclear Engineering and Engineering Physics, Universitas Gadjah Mada. In the GAMA-MSR design, the reactor core is placed above the primary heat exchanger. The primary heat exchanger is partially filled with fuel in normal operation, allowing room to be filled with the fuel drained from the reactor. Thus, in addition to control rods, the design of GAMA-MSR provides unique reactivity control through the balance of fuel salt fuel from the reactor core to the primary heat exchanger vice versa by adjusting fuel pump capacity. This design allows to shutdown the reactor by switching off the fuel pump. The reactor is initially fueled with 7LiF-ThF4-UF4 with 75: 20.1: 4.9 mol composition. The uranium has 19.75 % U-235 mol fraction. The reactor criticality and nuclide composition in the reactor fuel are calculated using OpenMC code during the reactor operation lifetime, with periodic adjustments to the fuel composition to simulate the effects of the fissile and fertile additions to the fuel and the extraction of actinides and fission products from the fuel. The calculated reactor thermal power is 60 MWth in this paper. The reactor is operated until it achieves a burnup value of 34,000 MWd/tHM. At this burnup value, the U-235 inventory is consumed and the amount is reduced from 794 kg to 250 kg. The U-233, Pu-239 and Pu-241 are produced with the amount are 246 kg, 24 kg and 8 kg respectively at the end of reactor operation. The effects of temperature, fuel density change, and fission product neutron poisons are also calculated. The average temperature reactivity coefficient value is approximately -4.4395×10-5Δk/k per °C. The effect of thermal expansion has been included in the calculation of this temperature reactivity coefficient value. The average value of the void reactivity coefficient is +1.2606×10-3Δk/k per % of void fraction for the void fraction value range up to 50 %. However, molten salt fuel suffers only small changes in density during operation. The negative value of the temperature reactivity coefficient will be dominant; thus, the GAMA-MSR becomes inherently safe. The GAMA-MSR is designed for a 30-year operation time. The effect of the fission product to the reactor reactivity is -1.4597×10-2Δk/k. Full draining of the fuel to primary heat exchanger brings the reactor to shutdown condition with the reactivity of −0.20525. Results showed that this reactor has an inherently safe characteristic and has an effective shutdown system, especially due to the fuel draining system.

Performance evaluation and validation of OpenMC code for criticality analysis of an MTR-type research reactor

This paper assesses the performance of OpenMC, an open-source Monte Carlo code for particle transport, through criticality analysis of an MTR-type research reactor. The evaluation involves validation against experimental data from the NUR research reactor's first fresh fuel core and a code-to-code comparison with MCNP5, using a consistent methodology ensuring identical input conditions. Key parameters, including excess reactivity, control rod worths, shutdown margin, critical configurations, kinetics parameters, neutron flux, power distributions, and peaking factors, were examined. Results indicate good agreement between OpenMC simulations, experimental data, and MCNP5 results, with marginal differences well within acceptable ranges. Discrepancies with experimental data are below 5 %, considering measurement accuracy, while code-to-code comparisons reveal relative differences below 1 % in most cases. This study supports OpenMC's reliability for MTR reactor criticality analysis, affirming the validity of the developed NUR reactor model for future applications and highlighting the code's credibility and applicability in the nuclear reactor simulations.

Advancing nuclear science education through IRL Integration: A case experiment on criticality mass determination at the Kartini research reactor

Research reactors serve critical roles across multiple domains—from physics to medicine—while distinctly not being used for electrical power generation. The Kartini Research Reactor located in Indonesia exemplifies the integration of research reactors in education and scientific research, particularly highlighting its educational applications through the Internet Reactor Laboratory (IRL). Established in 1978 and operational since 1979, the Training Research and Isotope Production by General Atomic (TRIGA) Mark II reactor is instrumental in advancing nuclear science with facilities like the Lazy Suzan/Rotate Rack and Beam Port. The IRL significantly enhances its educational process, enabling remote access to reactor physics experiments, thus facilitating global university participation in nuclear engineering education. This capability allows for the real-time visualization of reactor operations and detailed presentation of operational data and experiment results, enriching the learning experience. This paper demonstrates the Kartini Reactor's educational utility through a case study investigating reactor criticality and determining the critical fuel mass under safe operational parameters. Employing telecommunication hardware and software, the study achieved reactor criticality by inserting 5 fuel elements, totaling 2524.57 g. The critical mass determination was further refined by plotting the inverse of counts against the total mass of U-235. This approach utilized both polynomial and linear trend lines to analyze the data. While the polynomial analysis provided upper and lower thresholds for critical mass, the linear regression offered a precise critical mass value of 2428.62 g, showcasing a deviation of only 4% from the experimental findings.

Gamma noise to non-invasively monitor nuclear research reactors

Autonomous nuclear reactor monitoring is a key aspect of the International Atomic Energy Agency’s strategy to ensure nonproliferation treaty compliance. From the rise of small modular reactor technology, decentralized nuclear reactor fleets may strain the capacities of such monitoring and requires new approaches. We demonstrate the superior capabilities of a gamma detection system to monitor the criticality of a zero power nuclear reactor from beyond typical vessel boundaries, offering a powerful alternative to neutron-based systems by providing direct information on fission chain propagation. Using the case example of the research reactor CROCUS, we demonstrate how two bismuth germanate scintillators placed outside the reactor vessel can precisely observe reactor criticality using so called noise methods and provide core status information in seconds. Our results indicate a wide range of applications due to the newly gained geometric flexibility that could find use in fields beyond nuclear safety.

Analyze the Impact of Nuclear Energy on Many Aspects of Life Cycles—Review

AbstractEnergy has long been seen as an important factor in meeting needs of people, in order to sustain and support the economic growth and livelihood. To understand the various technological processes in the nuclear power life cycle, it is first necessary to know the types of fuels used today. There are two types of gasoline in use today, “open” and “partially closed,” respectively, referred to as “single cycle” (OTC) and “double cycle” (TTC). A distinction must be made between “partial” closed fuel cycles, as they apply to current critical (thermal neutron spectrum) reactor technology, which is limited to two passes, and “full” closed cycles, which allow for greater circulation of spent oil but must be used. Fast reactors (FR) are included in the reactor fleet. Many recoveries of FR—already proven but not yet widely used in industry—will lead to reduced demand for uranium mining. In this section, references to “closed” fuel cycles include “partially” closed cycles, i.e., TTCs. What type, if any, is the correct content or information in question? Analysis of the world's energy consumption in recent years shows that the world's energy consumption has increased by 50% in less than a decade.

Effect of Different Temperature and Nuclear Data Libraries in Criticality Calculations of 300 MWt Molten Salt Reactor

The Molten Salt Reactor (MSR) is a type of reactor in which coolant and fuel are blended with liquid salts. Liquid fuel enhances heat transfer and temperature control, establishing the MSR as one of the Generation IV reactor types. This study aims to analyze the impact of temperature variations on MSR reactor criticality and evaluate the effect of different nuclear data libraries, namely JENDL 3.2, JENDL 3.3, and JENDL 4.0, in neutron analysis. The observed temperature variations are 600 K, 700 K, 833 K, 903 K, and 1000 K. The analysis spans low to operational temperatures to comprehend reactor performance under differing thermal conditions. The study is conducted on a 300 MWTh MSR design, utilizing SRAC2006 with PIJ and CITATION modules for calculations. The results reveal the impact of temperature variations and nuclear data library disparities on reactor criticality. The outcomes demonstrate that higher temperatures correspond to lower values of the effective multiplication factor. At lower temperatures, neutrons experience greater moderation compared to higher temperatures. As a result, a higher number of thermal neutrons influences an increased probability of fission reactions within the reactor. Different nuclear data libraries also yield varied criticality values due to differing cross-sectional areas and quantities of data within each JENDL library. JENDL 4.0 generates the highest criticality value, attributed to elevated cross-sectional regions of each respective nuclear data entry and a greater quantity of nuclear data entries than JENDL 3.2 and JENDL 3.3.

A comparative analysis of gas-cooled fast reactor using heterogeneous core configurations with three and five fuel variations

GFR or Gas-cooled Fast Reactor is one type of fast generation-IV that uses a very high cooling temperature. Thus, it is necessary to have the right reactor core design so that the power distribution of neutrons produced reaches a safe and even limit point. The use of a uniform (homogeneous) reactor core can produce peaking power. This is very avoidable because it will cause a reactor accident. In this study, researchers tried to compare the results of the analysis for two heterogeneous reactor core designs including the configuration of 3 fuel variations and 5 fuel variations using UN-PuN fuel. This study aims to determine the keff value produced by both types of fuel variations during 5 years of burn-up and determine the characteristics of neutron flux, fission rate, and fission product during 15 years of burn-up. This study was started by calculating the homogeneous and heterogeneous core of 3 and 5 fuel variations with neutron transport simulation involving OpenMC. The calculation results show that the heterogeneous core configuration of 5 fuel variations for the keff value is more optimal than 3 fuel variations, because it has the smallest excess reactivity value. The neutron flux and fission rate characteristics for 5 fuel variations are more evenly distributed when compared to 3 fuel variations to maintain neutron lifetime and reactor life in operation. Burn-up residual plutonium material and minor actinide waste for 5 fuel variations have less mass than 3 fuel variations. The results of neutronic analysis of GFR reactors with heterogeneous reactor core designs for 5 fuel variations are better in terms of reactor criticality, neutron power distribution, and waste produced. Finally, optimization of the UN-PuN fuel volume fraction of 60 % provides the optimal keff value

Economically optimized design point of high-field stellarator power-plant

High temperature superconductors (HTSs) expand the design space of stellarator power-plants (PPs) toward high magnetic fields B, enabling compact major radii R. The present paper scans the space of B, R and other design parameters, finding solutions that are promising from a physics and engineering standpoint, while minimizing the capital cost of the PP and the levelized cost of fusion electricity. Similarly, it identifies minimum-cost design points for next-step burning plasma stellarator experiments of fusion gain 1<Q<10 . The study assumes advanced stellarator configurations of reduced aspect ratio, heated by neutral beam injection. Plasma-facing, flowing liquid metal (LM) walls protect it from high heat and neutron fluxes. The study relies on analytical first-principle calculations, and established zero-dimensional (0D) empirical scaling laws. Power flows are illustrated by Sankey diagrams. Plasma operating contours are used to determine the reactor’s start-up path. Sensitivity analyses are conducted to identify the most critical reactor parameters within physics, engineering and costing, quantifying their influence on the economics of the PPs. Such 0D study suggests that the assumed next generation HTS, flowing LM walls, and advances in compact plasma configurations could lead to an ignited stellarator PP of aspect ratio A∼4 , R⩽4 m, B > 9 T, and normalized plasma pressure β∼5% which would minimize both the cost of electricity and capital cost while achieving a net electric power of about 1 GW.

Radiation characterization summary of the NETL beam port 1/5 free-field environment at the 128-inch core centerline adjacent location

The characterization of the neutron, prompt gamma-ray, and delayed gamma-ray radiation fields in the University of Texas at Austin Nuclear Engineering Teaching Laboratory (NETL) TRIGA reactor for the beam port (BP) 1/5 free-field environment at the 128-inch location adjacent to the core centerline has been accomplished. NETL is being explored as an auxiliary neutron test facility for the Sandia National Laboratories radiation effects sciences research and development campaigns. The NETL reactor is a TRIGA Mark-II pulse and steady-state, above-ground pool-type reactor. NETL is intended as a university research reactor typically used to perform irradiation experiments for students and customers, radioisotope production, as well as a training reactor. Initial criticality of the NETL TRIGA reactor was achieved on March 12, 1992, making it one of the newest test reactor facilities in the US. The neutron energy spectra, uncertainties, and covariance matrices are presented as well as a neutron fluence map of the experiment area of the cavity. For an unmoderated condition, the neutron fluence at the center of BP 1/5, at the adjacent core axial centerline, is about 8.2×1012 n/cm2 per MJ of reactor energy. About 67% of the neutron fluence is below 1 keV and 22% above 100 keV. The 1-MeV Damage-Equivalent Silicon (DES) fluence is roughly 1.6×1012 n/cm2 per MJ of reactor energy.

Reactor Optimization Benchmark by Reinforced Learning

Neutronic calculations for reactors are a daunting task when using Monte Carlo (MC) methods. As high-performance computing has advanced, the simulation of a reactor is nowadays more readily done, but design and optimization with multiple parameters is still a computational challenge. MC transport simulations, coupled with machine learning techniques, offer promising avenues for enhancing the efficiency and effectiveness of nuclear reactor optimization. This paper introduces a novel benchmark problem within the OpenNeoMC framework designed specifically for reinforcement learning. The benchmark involves optimizing a unit cell of a research reactor with two varying parameters (fuel density and water spacing) to maximize neutron flux while maintaining reactor criticality. The test case features distinct local optima, representing different physical regimes, thus posing a challenge for learning algorithms. Through extensive simulations utilizing evolutionary and neuroevolutionary algorithms, we demonstrate the effectiveness of reinforcement learning in navigating complex optimization landscapes with strict constraints. Furthermore, we propose acceleration techniques within the OpenNeoMC framework, including model updating and cross-section usage by RAM utilization, to expedite simulation times. Our findings emphasize the importance of machine learning integration in reactor optimization and contribute to advancing methodologies for addressing intricate optimization challenges in nuclear engineering. The sources of this work are available at our GitHub repository: RLOpenNeoMC.

A Monte Carlo Fuel Assembly Model Validation Adopting Post Irradiation Experiment Dataset

Abstract Within an energy system where nuclear reactors will likely play a critical role, it is fundamental to have access to accurate and reliable computational tools that can predict the plants' behavior under different operating conditions; compared to other energy sources, models and analysis methods for nuclear systems should be able to provide, among other things, detailed information on reactor criticality and fuel evolution. Thanks to the advancements in computational hardware, using three-dimensional codes to obtain a local description of the reactor core has now become feasible, not only for what concerns deterministic codes but also for Monte Carlo (MC) based codes. Those computational methods must be compared with experimental measurements to assess their reliability. For this reason, the 3D Monte Carlo code serpent is currently being validated for light water reactor fuel cycle simulations. This work will compare the isotopic concentrations measured in a Post-Irradiation Experiment (PIE) and the results of the Monte Carlo routine, examining the Takahama-3 fuel assembly test case. Since key information related to the history of the plant under consideration is available, it was possible to follow the depletion cycles of two fuel rods (SF95 and SF97) placed in two separate assemblies. From literature reports, more than 35 nuclide species have been measured at different axial locations by destructive analysis following several radiochemical techniques. A sensitivity analysis, aiming to evaluate the impact of design features on the results, was carried out investigat-ing the cross section libraries, the simulation time Discretization and the imposition of an axial time-varying temperature. During the process, systematic sources of geometry-related errors were analyzed as well. Over-all, the model showed good agreement with the experimental data under an acceptable error threshold. The sensitivity studies also showed how the prediction capability could be increased up to +6%, adopting a realistic temperature mesh for the fuel instead of a uniform temperature approach. Finally, this analysis will focus more deeply on the Antimony-125 evolution, whose concentration is the one with the worst agreement to the experimental dataset not only for this work but also for other benchmarks available in the literature: results will show how the prediction error for this nuclide is systematic for all considered codes, and look for possible causes.

Neutronic performance evaluation of Plutonium Recycling in two core sizes for a 250 MWt Molten salt reactor

MSR has a unique feature in the fuel system, using liquid salt as fuel, and has flexibility on material utilization in the fuel, such as Plutonium. Recycling Plutonium into fuel is a good option to increase the non-proliferation and fuel sustainability aspects. This paper investigates the effect of different reactor core sizes and different Plutonium grades in neutronic performances on 250 MWt MSR. The calculation is performed using PIJ and CITATION modules in the SRAC program and JENDL 4.0 as a nuclear data library. The reactor core size is varied into two different sizes (type-A and type-B), where the type-A reactor has double the size of type-B. The variation of Plutonium grades is employed in this study for several fuel cases. The fraction of Plutonium in the salt (PuF4) is optimized based on the obtained reactor criticality for 2000 days of operation time. The results indicate that reactor type-B has a higher PuF4 consumption, and the percentage of plutonium reduction becomes higher than reactor type-A. Additionally, the comparison of neutronic performance on the varied fuel cases is also analyzed in this paper.

Nuclear data uncertainty on generation IV fast reactors criticality calculations analysis comparison

The new calculation code capabilities are applied in the current work as well as important fast reactor criticality parameters uncertainty assessment articles’ results based on different nuclear data libraries and covariance matrices. A comparative analysis of uncertainty estimations related to neutron reactions is presented for lead-cooled reactor models and sodium-cooled reactor models. For the models of advanced BN and BR fast reactors with three fuel types (UO2, MOX, MNUP), the multiplication factor uncertainty calculations are performed using 252-group covariance matrices based on ENDF/B-VII.1 library via the SCALE 6.2.4 code system. The main nuclear data uncertainty contributors in the multiplication factor are determined. Recommendations are formulated for improving the cross sections accuracy for several nuclides in order to provide more reliable results of fast reactor criticality calculations. Lead-cooled reactors have no operational history compared to light-water and sodium-cooled reactors. The experimental data insufficiency calls in the question about reliability of the simulation results and requires a comprehensive initial data uncertainty analysis for the neutron transport simulation. The obtained results support the idea that lead- and sodium-cooled reactors have close nuclear data sensitivity using one and the same computation tools, nuclear data libraries and fuel compositions. This makes it possible to use the accumulated data of benchmarks for sodium-cooled reactors in the safety determination of lead-cooled reactors.

Neutronic design performance of 100 MWe MSR with thorium-enriched uranium and thorium-plutonium-minor actinide fuel

Molten Salt Reactors offer fuel flexibility, allowing the use of different starting fuels, including U-233, U-235, and Pu-239. U-233 is not a fissile nuclide that is commercially accessible. However, it can be produced through the utilization of the thorium cycle. In this paper, the neutronic performance of MSR with a power output of 100 MWe is analyzed for Th-U(enriched) and Th-Pu-MA as a starting fuel. The fuel composition is varied to show the neutronic parameter change and obtain the reactor criticality for five years of operation time. The calculation used SRAC Program and JENDL 4.0 as nuclear data libraries. It was found that the reactor with a Th-U fuel case can be operated in critical condition with a minimal fuel loading of UF4 of 7.30 mol%. Similarly, in the Th-Pu-MA fuel case, a minimal amount of PuF4 is at least 3.87 mol%. The Th-U fuel case exhibits a higher initial keff and reactivity swing compared to the Th-Pu-MA fuel case. At the end of the reactor cycle, the Th-U fuel produces several plutonium isotopes, such as Pu-238, Pu-239, Pu-240, Pu-241, and Pu-242. In contrast, the density of plutonium isotopes in the Th-Pu-MA fuel decreases during operation such as Pu-239 and Pu-241. Therefore, using Th-Pu-MA fuel is a viable approach to reducing spent nuclear fuel, as it reduces the number of plutonium isotopes.

Hydrogen, Ammonia and Symbiotic/Smart Fertilizer Production Using Renewable Feedstock and CO2 Utilization through Catalytic Processes and Nonthermal Plasma with Novel Catalysts and In Situ Reactive Separation: A Roadmap for Sustainable and Innovation-Based Technology

This multi-disciplinary paper aims to provide a roadmap for the development of an integrated, process-intensified technology for the production of H2, NH3 and NH3-based symbiotic/smart fertilizers (referred to as target products) from renewable feedstock with CO2 sequestration and utilization while addressing environmental issues relating to the emerging Food, Energy and Water shortages as a result of global warming. The paper also discloses several novel processes, reactors and catalysts. In addition to the process intensification character of the processes used and reactors designed in this study, they also deliver novel or superior products so as to lower both capital and processing costs. The critical elements of the proposed technology in the sustainable production of the target products are examined under three-sections: (1) Materials: They include natural or synthetic porous water absorbents for NH3 sequestration and symbiotic and smart fertilizers (S-fertilizers), synthesis of plasma interactive supported catalysts including supported piezoelectric catalysts, supported high-entropy catalysts, plasma generating-chemical looping and natural catalysts and catalysts based on quantum effects in plasma. Their performance in NH3 synthesis and CO2 conversion to CO as well as the direct conversion of syngas to NH3 and NH3—fertilizers are evaluated, and their mechanisms investigated. The plasma-generating chemical-looping catalysts (Catalysts, 2020, 10, 152; and 2016, 6, 80) were further modified to obtain a highly active piezoelectric catalyst with high levels of chemical and morphological heterogeneity. In particular, the mechanism of structure formation in the catalysts BaTi1−rMrO3−x−y{#}xNz and M3O4−x−y{#}xNz/Si = X was studied. Here, z = 2y/3, {#} represents an oxygen vacancy and M is a transition metal catalyst. (2) Intensified processes: They include, multi-oxidant (air, oxygen, CO2 and water) fueled catalytic biomass/waste gasification for the generation of hydrogen-enriched syngas (H2, CO, CO2, CH4, N2); plasma enhanced syngas cleaning with ca. 99% tar removal; direct syngas-to-NH3 based fertilizer conversion using catalytic plasma with CO2 sequestration and microwave energized packed bed flow reactors with in situ reactive separation; CO2 conversion to CO with BaTiO3−x{#}x or biochar to achieve in situ O2 sequestration leading to higher CO2 conversion, biochar upgrading for agricultural applications; NH3 sequestration with CO2 and urea synthesis. (3) Reactors: Several patented process-intensified novel reactors were described and utilized. They are all based on the Multi-Reaction Zone Reactor (M-RZR) concept and include, a multi-oxidant gasifier, syngas cleaning reactor, NH3 and fertilizer production reactors with in situ NH3 sequestration with mineral acids or CO2. The approach adopted for the design of the critical reactors is to use the critical materials (including natural catalysts and soil additives) in order to enhance intensified H2 and NH3 production. Ultimately, they become an essential part of the S-fertilizer system, providing efficient fertilizer use and enhanced crop yield, especially under water and nutrient stress. These critical processes and reactors are based on a process intensification philosophy where critical materials are utilized in the acceleration of the reactions including NH3 production and carbon dioxide reduction. When compared with the current NH3 production technology (Haber–Bosch process), the proposed technology achieves higher ammonia conversion at much lower temperatures and atmospheric pressure while eliminating the costly NH3 separation process through in situ reactive separation, which results in the production of S-fertilizers or H2 or urea precursor (ammonium carbamate). As such, the cost of NH3-based S-fertilizers can become competitive with small-scale distributed production platforms compared with the Haber–Bosch fertilizers.