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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

FY23 Report on Water NSTF Testing at Two-Phase Conditions: Off-normal Scenarios

Under support from the Department of Energy (DOE) and the Office of Advanced Reactor Technologies (ART), a large-scale test facility has been constructed at Argonne National Laboratory to generate NQA-1 qualified validation data for passive decay heat removal systems in advanced reactors. The Natural convection Shutdown heat removal Test Facility (NSTF) reflects key features of a ½ scale, water-based, Reactor Cavity Cooling System (RCCS) and is intended to study the behavior, bound performance, and ultimately guide design decisions for passive decay heat removal systems for advanced reactors. In addition to the experimental activities detailed in this report, a supportive computational modeling effort is on-going which has been demonstrated to significantly strengthen the experimental program while also improving accuracy of the computer models. Together these create a mutually beneficial relationship integral to meeting the overall program objective of examining the heat removal performance of the RCCS concept. This report details the experimental activities and upgrades performed during the program’s fifth year of water-based operation. The theme of this year of testing was examining off-normal scenarios. In practice, that meant examining scenarios with blockages or other design basis conditions. From a maintenance and capability standpoint that meant assessing valving options for implementing blockages, assessing drain and refill capabilities, and ensuring in all cases that operators could safely, efficiently, and repeatably bring the facility to an off-normal condition and return it to the normal operating state. In one notable case, no solution existed, nor was a solution commercially available, that met the facility needs for implementing blockages within the two-phase region of the chimney. A valve and feedthrough were custom-designed for NSTF to operate submerged in saturated water while being safely actuated from outside the tank. The fifth year of testing included eight matrix tests consisting of 162 hours of active heating, 9,735 kWh of electrical heating, with seven tests classified as Accepted per NQA-1 and one as Trending. All matrix tests were performed at two-phase flow conditions. The power parametric series from previous years was extended to include another scenario with a decay load equivalent to 1.75 MWt, full scale, further resolving the system flow oscillation response as a function of input power. A depletion test was performed to extend previous work and examine the system’s approach to stagnation and geysering that were not previously observed. This test began at an initial inventory level of 50%, prototypic power of 2.1 MWt, and employed an accelerated drain of 0.75 gpm plus boiloff until stagnation conditions were achieved and multiple geysering events were recorded. Further exploring the geysering phenomenon was a separate effects test examining static boiling in the risers and chimney. This static boiling test was performed at 48 kWe, a higher power than testing in the previous year, and included enhancements to the drain system to remove inventory in a better-controlled and more reliable manner. Two tests were performed, at prototypic conditions of 1.4 MWt and 2.4 MWt, respectively, examining the system response to throttled conditions in the singlephase region of the piping. A ball valve immediately before he riser inlet header was increasingly throttled, progressing the system through a repeatable pattern of two-phase oscillations and stable regimes before ultimately inducing stagnation and geysering. Concluding the year, two tests were performed at baseline conditions of 70% initial inventory level and 2.1 MWt of prototypic decay heat to examine both repeatability and the response to throttling within the two-phase region, at the inventory tank inlet using the custom valve mentioned above. The first such test repeated transient operating conditions and revealed significant sensitivity t

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Insights into scale translation of methane transport in nanopores

Accurate prediction of flow behavior in shale matrix is critical for efficient development of shale gas reservoirs. In these systems, the majority of pores are in the nano-size range. As a result, continuum-based approaches may not be appropriate to simulate flow in such systems. Molecular dynamics (MD) simulations are capable of capturing the relevant microscale physics. Their relatively high computational expense, however, restricts MD simulations to rather small systems and domains. This limitation creates a gap between computational need of macroscale systems and capabilities of MD simulations. The lattice Boltzmann method (LBM) is a suitable candidate to bridge this gap. In this work, the multiple-relaxation-time (MRT)-LBM is used to study methane transport in nano-size pores. Adsorption effects near solid boundaries, as well as non-ideal behavior of fluids, are accounted for via incorporating appropriate force terms in LBM. In this work, parameters associated with the force terms in the equation of state are studied in detail, and a workflow is proposed to determine optimal values of these parameters for gas flow in slit pores. Specifically, we establish these parameters such that the range of density values that the model is able to simulate is maximized. We demonstrate this workflow by simulating gas flow where velocity and density profiles from MD simulations are used as reference data. Results from LBM simulations are in good agreement with MD reference data for pores that are 4 nm in width or larger. Moreover, we propose a preconditioning scheme to improve the stability of LBM in dealing with complex geometries. The robustness of this scheme is demonstrated by simulating several roughness geometries. This work motivates the use of LBM in scale translation of the physics of mass transport in more complex permeable media.

03 NATURAL GAS↗
DOE OSTI2023

Engaging the Regulatory Community to Aid Environmental Consenting/Permitting Processes for Marine Renewable Energy

Regulators involved in consenting/permitting marine renewable energy (MRE) have faced multiple challenges due to relatively new, unfamiliar technologies and uncertainty surrounding potential environmental impacts. This has resulted in slow progress for the MRE industry, including long consenting timeframes and extensive and expensive monitoring requirements, which increase financial risk for investors. OES-Environmental has surveyed regulators internationally to understand their key knowledge gaps and perspectives to support the development of the MRE industry. From the results of these surveys a data transferability process and a risk retirement pathway have been developed to assess consenting and monitoring requirements in proportion to risk. A tool for discovering existing data sets by using an online matrix has been developed, along with training materials, regulatory guidance documents, and a strategic outreach plan to engage regulators and advisers. his engagement and the application of these products should lead to a better understanding of the environmental effects of marine energy, and more efficient consenting processes.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Characterization of the Sulfur Saturated Versions of the High-Chromium Matrix Glasses

In this report, the Savannah River National Laboratory provides chemical analysis of a series of sulfur saturated melt versions of simulated nuclear waste glasses, and chemical analysis of the wash solutions resulting from the preparation of these glasses. The glasses were selected and fabricated by the Pacific Northwest National Laboratory as part of a broader study of the influence of glass composition on chemical durability, sulfur retention, and other properties. The resulting data will be used in the development of improved property/composition models to support operation of the Hanford Tank Waste Treatment and Immobilization Plant. Some degree of scatter among the Al₂O₃, B₂O₃, CaO, K₂O, Na₂O, and SiO₂ measurements was noted for the study glasses. The measured concentrations of B₂O₃, chlorine, and fluorine were below the targeted values for most of the study glasses, likely because of volatility during the multiple melting steps. The measured concentrations of Cr₂O₃ and K₂O were generally low relative to the targeted values. These components were identified in the wash solutions, indicating partitioning to the excess sulfate phase that was washed from the glasses prior to analyses. As expected, the measured concentrations of SO₃ in the glasses were higher than targeted due to the use of the sulfur saturation method in fabricating these glasses. Minor scatter among the triplicate measurements of some of the analytes of the wash solutions was noted. The wash solutions contained mainly sulfur and sodium, with moderate concentrations of chromium and potassium. Revision 1 of this report corrects the omission of Al₂O₃ values from Table A-4 in Appendix A.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Raman Spectroscopy Coupled with Chemometric Analysis for Speciation and Quantitative Analysis of Aqueous Phosphoric Acid Systems

Complex chemical systems that exhibit varied and matrix-dependent speciation are notoriously difficult to monitor and characterize on-line and in real-time. Optical spectroscopy is an ideal tool for in situ characterization of chemical species that can enable quantification as well as species identification. Chemometric modeling, a multivariate method, has been successfully paired with optical spectroscopy to enable measurement of analyte concentrations even in complex solutions where univariate methods such as Beer’s law analysis fail. Here, Raman spectroscopy is used to quantify the concentration of phosphoric acid and its three deprotonated forms during a titration. In this system, univariate approaches would be difficult to apply due to multiple species being present simultaneously within the solution as pH is varied. Locally Weighted Regression (LWR) modeling was used to determine phosphate concentration from spectral signature. LWR results, in tandem with Multivariate Curve Resolution modeling, provide direct measurement of the concentration of each phosphate species using only the Raman signal. Furthermore, results are presented within the context of fundamental solution chemistry, including Pitzer equations to compensate for activity coefficients and non-idealities associated with high ionic strength systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Multi-instanton calculus in $c$ = 1 string theory

We formulate a strategy for computing the complete set of non-perturbative corrections to closed string scattering in c = 1 string theory from the worldsheet per spective. This requires taking into account the effect of multiple ZZ-instantons, including higher instantons constructed from ZZ boundary conditions of type (m, 1), with a careful treatment of the measure and contour in the integration over the instanton moduli space. The only a priori ambiguity in our prescription is a normalization constant $\mathcal{N}_m$ that ap pears in the integration measure for the (m, 1)-type ZZ instanton, at each positive integer m. We investigate leading corrections to the closed string reflection amplitude at the n instanton level, i.e. of order e -n/g s , and find striking agreement with our recent proposal on the non-perturbative completion of the dual matrix quantum mechanics, which in turn fixes $\mathcal{N}_m$ for all m.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Machine learning Frenkel Hamiltonian parameters to accelerate simulations of exciton dynamics

In this manuscript, we develop multiple machine learning (ML) models to accelerate a scheme for parameterizing site-based models of exciton dynamics from all-atom configurations of condensed phase sexithiophene systems. This scheme encodes the details of a system’s specific molecular morphology in the correlated distributions of model parameters through the analysis of many single-molecule excited-state electronic-structure calculations. These calculations yield excitation energies for each molecule in the system and the network of pair-wise intermolecular electronic couplings. In this work, we demonstrate that the excitation energies can be accurately predicted using a kernel ridge regression (KRR) model with Coulomb matrix featurization. We present two ML models for predicting intermolecular couplings. The first one utilizes a deep neural network and bi-molecular featurization to predict the coupling directly, which we find to perform poorly. The second one utilizes a KRR model to predict unimolecular transition densities, which can subsequently be analyzed to compute the coupling. We find that the latter approach performs excellently, indicating that an effective, generalizable strategy for predicting simple bimolecular properties is through the indirect application of ML to predict higher-order unimolecular properties. Such an approach necessitates a much smaller feature space and can incorporate the insight of well-established molecular physics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Thermal Stability Testing of LANA.75

Savannah River Site has used the metal hydride LaNi 4.25 Al 0.75 (LANA.75) in the Tritium Facilities for over two decades. LANA.75 beds store significant quantities of tritium but have a limited service life due to the radiolytic decay of tritium to 3He within the metal matrix. It has been shown that the isotherm performance of a tritium-aged LANA.75 sample can be restored by heating under vacuum. Additional investigation is needed to ensure there are no unexpected changes to the hydride before this technique is employed in full-scale beds in the Tritium Facilities. In addition, it is necessary to verify the regenerable behavior and thermal stability of LANA.75 on a small scale prior to it being implemented on a large scale. In this work, a non-tritiated bench-scale LANA.75 sample was held at 750°C under vacuum for 200 h to simulate exposure to multiple restoration evolutions. Hydride isotherm performance, chemical composition, crystallinity, and morphology are compared between the pre-restorative and post-restorative testing samples. No significant changes were observed in composition or crystallinity. Comparison of pre-anneal and post-anneal isotherms showed that performance improved rather than deteriorated during the evolution. Scanning electron microscopy analysis showed small growths on the particle surface after exposure to regeneration conditions. Additional testing will be required to determine the cause of these growths.

08 HYDROGEN↗
DOE OSTI2026

Fast Active-Set Thresholding Method for Nonnegative Least Squares

Nonnegative Least Squares (NNLS) is a fundamental constrained optimization problem encountered in many applications such as image deblurring, signal processing, nonnegative matrix factorization, magnetic microscopy, and hyperspectral imaging. Active-set based methods are a common class of algorithms for solving NNLS which identify the optimal variable set of the NNLS solution. They do so by iteratively solving a series of unconstrained least squares problems, identifying which variables violate the nonnegativity constraints, and then swapping variables in/out of consideration until the optimal set of variables is found. Several variations improving upon this method exist in the literature. In this work, we propose an active-set swap heuristic which further improves upon existing active-set based methods for NNLS. Our optimizations are based upon adding multiple variables to the passive set within a threshold of the smallest gradient value and removing variables within a similar threshold of the closest boundary constraint. We leverage these optimizations to yield a Fast Active-Set Thresholding NNLS (FAST-NNLS) algorithm which significantly outperforms the existing state-of-the-art NNLS algorithms for a wide range of problems. Rigorous convergence guarantees are proven for the proposed method. We demonstrate the effectiveness of our proposed method on multiple synthetic datasets and two realworld text analysis applications. In doing so, we present the most comprehensive NNLS solver comparison in the literature to date.

Cobb, Benjamin [Georgia Institute of Technology]↗
DOE OSTI2023

A comparison of machine learning methods to classify radioactive elements using prompt-gamma-ray neutron activation data

The detection of illicit radiological materials is critical to establishing a robust second line of defence in nuclear security. Neutron-capture prompt-gamma activation analysis (PGAA) can be used to detect multiple radioactive materials across the entire Periodic Table. However, long detection times and a high rate of false positives pose a significant hindrance in the deployment of PGAA-based systems to identify the presence of illicit substances in nuclear forensics. In the present work, six different machine-learning algorithms were developed to classify radioactive elements based on the PGAA energy spectra. The model performance was evaluated using standard classification metrics and trend curves with an emphasis on comparing the effectiveness of algorithms that are best suited for classifying imbalanced datasets. We analyse the classification performance based on Precision, Recall, F1-score, Specificity, Confusion matrix, ROC-AUC curves, and Geometric Mean Score (GMS) measures. The tree-based algorithms (Decision Trees, Random Forest and AdaBoost) have consistently outperformed Support Vector Machine and K-Nearest Neighbours. Based on the results presented, AdaBoost is the preferred classifier to analyse data containing PGAA spectral information due to the high recall and minimal false negatives reported in the minority class.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

GSoFa: Scalable Sparse Symbolic LU Factorization on GPUs

Decomposing a matrix $\mathbf {A}$ into a lower matrix $\mathbf {L}$ and an upper matrix $\mathbf {U}$, which is also known as LU decomposition, is an essential operation in numerical linear algebra. For a sparse matrix, LU decomposition often introduces more nonzero entries in the $\mathbf {L}$ and $\mathbf {U}$ factors than in the original matrix. A symbolic factorization step is needed to identify the nonzero structures of $\mathbf {L}$ and $\mathbf {U}$ matrices. Attracted by the enormous potentials of the Graphics Processing Units (GPUs), an array of efforts have surged to deploy various LU factorization steps except for the symbolic factorization, to the best of our knowledge, on GPUs. This article introduces gSoFa, the first GPU-based symbolic factorization design with the following three optimizations to enable scalable LU symbolic factorization for nonsymmetric pattern sparse matrices on GPUs. First, here we introduce a novel fine-grained parallel symbolic factorization algorithm that is well suited for the Single Instruction Multiple Thread (SIMT) architecture of GPUs. Second, we tailor supernode detection into a SIMT friendly process and strive to balance the workload, minimize the communication and saturate the GPU computing resources during supernode detection. Third, we introduce a three-pronged optimization to reduce the excessive space consumption problem faced by multi-source concurrent symbolic factorization. Taken together, gSoFa achieves up to 31× speedup from 1 to 44 Summit nodes (6 to 264 GPUs) and outperforms the state-of-the-art CPU project, on average, by 5×. Notably, gSoFa also achieves up to 47 percent of the peak memory throughput of a V100 GPU in the Summit Supercomputer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Elucidating the role of Cr migration in Ni-Cr exposed to molten FLiNaK via multiscale characterization

Structural materials used in nuclear reactor environments are subjected to coupled extremes such as high temperature, irradiation, and corrosion which act in concert to degrade their functional performance. Connecting alloy microstructure such as grain boundaries, and accumulating point defects with corrosion attack and pore morphology is critical to understanding underlying mechanisms. We uncover the compositional variations and morphology at multiple length scales in corrosion-damaged Ni-Cr alloy after exposure to oxidants in molten fluoride salts. A complex network of dense corrosion pores is detected by surface-level SEM observations. The corrosion pores take on a 1-dimensional morphology and are enriched with Ni and depleted of Cr 1–5 µm from the pore surface. STEM-EDS and 4D-STEM strain maps acquired simultaneously highlight the local variations in composition and structure of a ≤ 200 nm Cr-rich layer identified from a cross-section taken at the bottom of an isolated corrosion pore between the Ni-Cr alloy matrix and the embedded salt. However, the absence of an observed interface between the Ni-Cr alloy matrix and the FCC-structured Cr-rich layer suggests that Cr plating from the salt did not transpire. These findings support a proposed Cr lattice diffusion mechanism rather than Cr-precipitation from the salt to accommodate temperature transient conditions during sample cooling. Through the development of a 1D phase field model, these results are rationalized by formation energies for the Ni- and Cr-oxidation into the molten salt. This study reveals the locally altered microstructure caused by high temperature corrosion in non-steady-state molten salt nuclear reactor environments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

User Role Identification in Software Vulnerability Discussions over Social Networks

Understanding and early awareness of software vulnerabilities is vital for preventing and mitigating potential impacts from cybersecurity events. One step toward early characterization of software vulnerabilities may involve analyzing discussion and spread of information in online social networks. Prior work has used information from such discussions over multiple online forums to develop dynamic networks among users followed by analysis of structure, spread, and information evolution. In this work, we advance the state-of-the-art by focusing on data-driven learning of types, roles, and transition of roles exhibited by users over time. In social networks, users take on particular roles based on their actions and structure of the network. Identifying “meaningful” roles can help separate potential users of interest from the larger community, and identify patterns in a network. We will identify and compare roles found in online forums (e.g., Twitter) using techniques such as feature-based Non-negative Matrix Factorization coupled with topological and influence-based measures of centrality. Since users’ activities change over time, we also analyze role evolution in dynamic networks.

Jones, Rebecca D.↗
DOE OSTI2021

TUMME: Tsinghua University Minnesota Master Equation program

We report that TUMME is a program for assembling and solving master equations for gas-phase chemical kinetics based on chemically significant eigenmodes. TUMME has interfaces to the Gaussian, Polyrate, and/or MSTor output files that allow the master equation code to obtain the microcanonical flux coefficients needed for the coefficient matrix of the master equation. The flux coefficients for reactions with barriers can be calculated by multi-structural variational transition state theory with small-curvature tunneling (MS-VTST/SCT) or by simpler approximations to this such as conventional transition state theory without tunneling (also called RRKM theory). The flux coefficients for barrierless reactions are provided by a hard-sphere model. TUMME is written in double precision with Python 3; quadruple and octuple precision are also available for some subtasks in C++. The Python code can run in serial or parallel (MP or MPI), and the C++ code can run on a single processor or on multiple processors with OpenMP.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Mineral Protection and Resource Limitations Combine to Explain Profile-Scale Soil Carbon Persistence

The fate of soil carbon (C) is largely controlled by microbial oxidation of organic matter (OM), which is constrained by a variety of mechanisms. OM association with soil minerals provides pronounced protection against microbial decomposition. However, factors such as climate, occlusion, and resource limitations also contribute to OM preservation. Here, we explore the factors explaining C distribution and age within an upland rainforest soil in Hawai'i, a site with abundant preferential flow paths (PFPs) and high short-range order (SRO) mineral content. We characterized lateral and vertical changes in Δ 14 C, SRO mineral content, C-functional group chemistry, and microbial community composition to elucidate the contributions of multiple protection mechanisms to OM preservation. Consistent with our expectation, SRO mineral content and Δ 14 C were strongly correlated (R 2 = 0.95), indicating strong mineral protection of OM throughout the profile. Surprisingly, distance from PFP was also a significant predictor of Δ 14 C and improved model fit, particularly in the shallow horizons (R 2 = 0.97). Elevated C/N ratios, decreased microbial abundance, and greater SRO mineral content suggest nitrogen limitations and enhanced mineral protection constrain OM turnover with distance from PFPs in deep, subsurface mineral horizons. Steady microbial abundance, increasing putative anaerobe abundance, and changes in C-functional group chemistry indicate oxygen limitations constrain OM turnover in the matrix of shallow mineral horizons. Given that oxygen and nutrient limitations contribute to OM preservation in this high SRO system—an exemplar of mineral protection—resource limitations may play an even more important role in OM preservation in other well-structured soils.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Convergence Analysis of the Alternating Anderson–Picard Method for Nonlinear Fixed-Point Problems

Anderson acceleration (AA) has been widely used to solve nonlinear fixed-point problems due to its rapid convergence. This work focuses on a variant of AA in which multiple Picard iterations are performed between each AA step, referred to as the Alternating Anderson–Picard (AAP) method. Furthermore, despite introducing more “slow” Picard iterations, this method has been shown to be efficient and even more robust in both linear and nonlinear cases. However, there is a lack of theoretical analysis for AAP in the nonlinear case. In this paper, we address this gap by establishing the equivalence between AAP and a multisecant-GMRES method that uses GMRES to solve a multisecant linear system at each iteration. From this perspective, we show that AAP “converges” to the Newton-GMRES method. Specifically, as the residual approaches zero, the multisecant matrix, the approximate Jacobian inverse, the search direction, and the optimization gain of AAP converge to their counterparts in the Newton-GMRES method. These connections provide insights for analyzing the asymptotic convergence properties of AAP. Consequently, we show that AAP is locally 𝑞-linear convergent and provide an upper bound for the convergence factor of AAP. To validate the theoretical results, numerical examples are provided.

Anderson acceleration↗
DOE OSTI2025

Developing Fluorescence-Based Sensors to Support Rare Earth Element Separation

Rare earth elements (REEs) are essential to most renewable energy technologies. Unfortunately, as we transition to sustainable energy production, the demand for REEs is rapidly growing well beyond current rates of production. As a result, novel means of efficient, scalable, and easily adaptable methods for processing primary and recycle feedstocks are needed. Development and integration of sensors for highly selective in-line monitoring can support more efficient design and testing of such novel separation processes, as well as more cost-effective deployment of those separation flowsheets. Work here will explore the application of fluorescence spectroscopy, a highly sensitive and selective technique, to quantify multiple lanthanides in complex mixtures including known interferents or quenching agents. Results include identification of the optimal excitation wavelength and the limit of detection of various rare earth elements as well as the performance of data-science-based quantification approaches in streams where “unknowns” are present. Overall, the data science tools in conjunction with optical sensor data were able to quantify analytes in the presence of other lanthanides which can be anticipated in the actual industrial stream. Here we include characterization of lanthanides in a microfluidic device similar to those used in new process development. This study demonstrates the capability of utilizing fluorescence spectroscopy to quantify analytes in a complicated solution matrix, suggesting this is a successful approach for in-line monitoring to optimize the separation efficiency in an industrial stream.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Progress on the reevaluation and validation of the n+233U neutron cross sections

The set of 233 U resonance parameters of the ENDF/B-VIII.0 nuclear data library was adopted from the previous ENDF/B-VII.1 evaluation using the external levels to update the thermal values. Adoption of IAEA 2017 thermal standards ( σ f = 533.0 ± 2.2 b, σ c = 44.9 ± 0.9 b, and ν ‾ tot = 2.487 ± 0.011 ) and of the IAEA-recommended thermal-neutron induced prompt fission neutron spectrum (PFNS) with average PFNS energy of 2.030 ± 0.013 MeV requires a re-evaluation of 233 U neutron cross sections in the resolved resonance region. A newly produced evaluation is being tested on benchmarks carefully selected from the Handbook of International Criticality Safety Benchmark Experiments (ICSBEP) which are highly sensitive to 233 U data. An important goal of this work was to eliminate the strong negative gradient of the calculated effective multiplication factors with respect to the epithermal fission fraction observed in the validation of the ENDF/B-VIII.0 library for those assemblies. A significant improvement in integral performance of critical 233 U solutions is observed for the newly proposed evaluation. Further work addressing the fast neutron region is needed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗