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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 919 records · Page 51

An Integrated High-performance Computing and Digital Real-time Simulation Testbed to Benchmark Closed-loop Load Shedding Algorithms in Power Systems

An integrated testbed using digital real-time simulator (DRTS) and a high-performance computing (HPC) cluster is presented here to compare speed and performance of computational schemes to mitigate time-critical issues in electric power systems. The first approach in this testbed validation is taken by running a set of closed-loop load shedding algorithms to compare and contrast two paradigms of arresting cascading failure propagation. Two algorithms involve solving DC and AC power flow model-based optimization problems to compute load shedding at different buses, while a model-based stochastic search using parallel computing provides a viable alternative. The algorithms are implemented in the DRTS-HPC testbed for the IEEE 14-bus benchmark transmission system. As a proof of the concept, simulation results are presented for implementation of closed-loop load-shedding algorithms for cascading failures in the DRTS-HPC testbed

24 POWER TRANSMISSION AND DISTRIBUTION↗

Issue Summary of INL Phase IV Transient Results for IAEA CRP on HTGR UAM Benchmark

This report details the Parallel and Highly Innovative Simulation for Idaho National Laboratory (INL) Code System (PHISICS)/Reactor Excursions and Leak Analysis Program (RELAP5)-3D results obtained for the transient core exercises defined for Phase IV of the International Atomic Energy Agency (IAEA) Coordinated Research Project (CRP) on high-temperature gas cooled reactor (HTGR) uncertainty analysis in modeling (UAM). The Phase III models and results are linked to the earlier Standardized Computer Analyses for Licensing Evaluation (SCALE)/Sampler/New ESC-based Weighting Transport (NEWT) data generated for the lattice physics (lattice) stage Phase I of the CRP. The focus of this report is the Uncertainty/Sensitivity Assessment (U/SA) of the prismatic modular high-temperature gas cooled reactor (MHTGR)-350 design, and specifically for Exercises IV-1 and IV-2 of the benchmark: the Control Rod Withdrawal (CRW) and Pressurised Loss of Cooling (PLOFC) events. The statistical U/SA methodology is implemented and demonstrated using the RAVEN code, based on perturbed cross-section libraries obtained from the SCALE/Sampler sequence. Uncertainties in nuclear data (cross-sections and the average number of neutrons produced per fission, 235U[¯v ]) lead to standard deviations (uncertainties of one s) of approximately 0.5% in the core eigenvalues of the MHTGR-350 and core models. For the coupled neutronics/thermal fluid model, local power density uncertainties up to 3.6% were observed in the colder regions of the core, while the local maximum fuel temperature uncertainties reached 1.5% for the models that included thermal fluid uncertainties. The addition of thermal fluid uncertainties dominated the impacts of nuclear data uncertainties in all cases. The main contributors to uncertainties in the power density and fuel temperatures during the transients were uncertainties in the reactor operating conditions (total power, inlet mass flow rate and inlet gas temperature). Variations in the bypass flows did not have significant impact on any of the output variables. For the nuclear data uncertainties it was found that the 235U(¯v ) / 235U(¯v ) covariance produced the largest sensitivities in terms of its impact on the eigenvalue and peak reactor power. It was also observed that the impact of any nuclear data uncertainties on the maximum fuel temperature was much less significant that the impact on eigenvalue and power. Another important finding was that although the use of eight or more energy groups is recommended for best-estimate HTGR simulation, two-group models produced acceptable uncertainty and sensitivity results for most FOMs. Since the statistical U/SA methodology is computationally expensive, and most transient solver requirements will scale directly with the number of energy groups, two energy groups could be used by HTGR developers during the early stages of design when larger uncertainty margins can be tolerated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Machine Learning-based Prediction of Departure from Nucleate Boiling Power for the PSBT Benchmark

Machine Learning (ML) has seen an exponential growth in its applications due to its advanced data driven prediction capabilities. The study presents a data-driven approach as a preliminary attempt to predict the power at which departure from nucleate boiling (DNB) occurs in pressurized water reactors (PWRs) by constructing an advanced ML algorithm that takes outlet pressure, inlet temperature and inlet mass flux as the input features. DNB is a critical heat flux (CHF) phenomenon seen in PWRs. The experimental data from the PWR subchannel and bundle tests (PSBT) benchmark is first used to train an artificial neural network (ANN) to predict the DNB power, which produces a root mean square error (RMSE) of 6.89 kW/m when tested on a blind subset of the PSBT data. Since the PSBT dataset is relatively small to train an accurate ANN, a data augmentation methodology based on generative adversarial networks (GANs) is used to expand the training dataset. By assuming that the real data follows a certain distribution, GANs try to learn that underlying distribution to generate similar synthetic data to augment the database and to improve the predictive capabilities of the ANN. The data generated from GANs are validated using 1-nearest neighbor and kernel maximum mean discrepancy. To further ensure data from GAN is similar to PSBT, the data is tested and filtered out using the sub-channel thermal-hydraulic code CTF. The results indicate that with the addition of 120 data points from GAN the RMSE reduces to 4.84 kW/m showing promising results for future developments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Generalized Bayesian Framework for Evaluation of Integral Benchmark Experiments

A recently published generalized Bayesian optimization framework has provided a way to retract any or all of the three common assumptions underlying the conventional Generalized Linear Least Squares (GLLS) optimization method based on the concepts introduced in reference two. These assumptions are: 1. Perfection: The model used for data evaluation and the prior probability distribution function (PDF) of generalized* data are perfect; 2. Normality: The prior and posterior PDF are normal; and 3. Linearity: The model is linear. In this work we outline how the framework in 1 could be directly adopted for improved evaluation of nuclear criticality integral benchmark experiments (IBEs) by: 1. Removing the first assumption alone by utilizing the concept of imperfections introduced in 1 to enable evaluation in the presence of discrepancies between the data and model or of missing covariance information by a GLLS method that will be seen as a generalization of the conventional GLLS method employed by the TSURFER code, and by 2. Removing the remaining two assumptions by implement- ing a Markov Chain Monte Carlo method for computation of the posterior PDF in the SAMPLER code, where TSURFER and SAMPLER are the uncertainty quantification (UQ) codes for IBEs in the SCALE code system based on the GLLS, and the stochastic method, respectively.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

SPEChpc 2021 Benchmark Suites for Modern HPC Systems

The SPEChpc 2021 suites are application-based benchmarks de- signed to measure performance of modern HPC systems. The bench- marks support MPI, MPI+OpenMP, MPI+OpenMP target offload, MPI+OpenACC and are portable across all major HPC platforms.

Boehm, Swen↗

Generating Models of the Flattop Critical Assembly for Benchmark Experiments with Python

Los Alamos National Laboratory has been performing nuclear criticality experiments since 1946 at the Pajarito site, starting the Los Alamos Critical Experiments Facility in 1948. A transition period occurred between 2004 and 2011 as operations moved to the National Criticality Experiments Research Center (NCERC), where criticality experiments are now performed. Criticality experiments are essential for determination and verification of nuclear data used in calculations and modeling—such as radiation transport codes—throughout the industry, enhancing nuclear criticality safety. In addition to nuclear data validation and benchmarking, the remotely operated critical assemblies at NCERC are used for a variety of experiments and training classes supporting criticality safety.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Benchmark of the LAMMPS code on CRESCO and SUMMIT HPC systems

In this work we present the benchmark results of a numerical model where the solid Deuterium grows under gas pressure. The two-phase molecular Deuterium systems (gas + solid) is modeled using classical molecular dynamics approach and the LAMMPS code. The performance between different modern supercomputers are analyzed and compared. In addition, the numerical simulations reach high accuracy to produce results that match with the data collected through laboratory experiments.

Lupo Pasini, Massimiliano↗

Sensitivity Studies, Gap Analysis, and Benchmark Experiment Optimization for Reactor Applications

In regards to nuclear data, some reactor applications may lack validation experiments, which reduces confidence in predicted results. This is especially true for emerging advanced reactor, micro reactor, and Accelerator Driven System (ADS) designs. This work presents an approach to design new criticality experiments that have similar k eff cross section sensitivities to an application of interest. This process involves simulations to generate cross-section sensitivities to a parameter of interest (such as k eff ), a gap analysis to determine which existing benchmarks are most similar to the application, and an experiment optimization. This work focuses on cross-section sensitives and gap analysis for three examples relevant to the reactor physics community including a Travelling Wave Reactor (TWR) type-design, Kilopower (a space reactor design), and a lead-bismuth eutectic cooled accelerator-driven system (ADS) to transmute minor actinides.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

OECD-NEA HTTF Benchmark Progress and Updates

General slides discussing High Temperature Test Facility benchmark progress, Prismatic HTGR deployment, modeling and simulation tools for validating systems, and verification and validation issues. Also discuss collaboration and conclusions of RELAP5-3D validation activities based on HTTF with trends in data and international impact to accelerate deployment of prismatic HTGR microreactors by providing an opportunity for designers to assess their codes against experimental data and solutions from other codes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

SERPENT 2 and TRIPOLI-4 neutronics benchmarking of the Jules Horowitz reactor

Jules Horowitz Reactor (JHR) is a future center for nuclear material testing in Europe, currently under construction at CEA Cadarache in southern France. It has been modelled extensively with CEA's HORUS3D/N neutron calculation package, that includes a Monte-Carlo neutron transport code TRIPOLI-4. In order to support the future computational analyses on the reactor core physics, VTT's Monte Carlo neutronics code SERPENT 2 has been used to create an alternative model of the JHR, taking advantage of the pre-existing Constructive Solid Geometry (CSG) structures on which the TRIPOLI-4 model was built. This work describes a benchmark, in which two JHR core configurations were analyzed using both of these models. The first configuration is a fresh fuel core at the beginning of life, in which aluminum based dummy-devices are installed in the reactor test positions. The second configuration represents the end-of-cycle equilibrium core with a heterogeneous burnup distribution, in which CALIPSO devices containing cladding material samples are installed at the in-core experimental positions, while the reflector positions are occupied by DEN-REP devices containing UO{sub 2} fuel. Neutron flux spectra and heat deposition are the parameters of interest in this study, due to their high importance in creating the desired experimental irradiation environment. The impact of delayed gamma energy deposition will be studied in detail, since the two models account for it with different methods. This work aims to establish a SERPENT 2 model of JHR, understanding its differences and agreements with TRIPOLI-4, and discussing its potential future applications. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A High-Fidelity Electromagnetic Transient Model of Inverter-based Resources Integrated to an IEEE-9 Bus System for Benchmarking Studies

An inverter-based resource (IBR) is a source of electricity that is asynchronously connected to the electrical grid via an electronic power converter. These power sources lack the intrinsic behaviors of the standard power plants, presenting specific challenges to system stability. These power sources lack the intrinsic behaviors of the standards power plants and their features are almost entirely defined by the control strategy used on them, presenting specific challenges to system stability as their penetration increases into the already fragile Bulk Power System (BPS). Utilizing renewable energy has a great upside but the electrical industry needs to understand the requirements like performing electromagnetic transient (EMT) simulation studies in planning and/or in interconnection studies. This paper presents the development of a high-fidelity EMT model based on commercial equipment and field parameters, which at the same time aims to study the increasing penetration of IBRs and their impact on the actual BPS. The open-source EMT model developed will be a benchmarking example that can be used to evaluate algorithms in the power grid (including evaluating grid-forming controls, power system monitoring and operation, etc.).

Martinez Montejano, Misael↗

Preliminary Benchmark Uncertainties for Deimos, a HALEU-Fueled and Graphite-Moderated Advanced Reactor Testbed

Many advanced reactor concepts will make use of various uranium fuels with levels of enrichment higher than previously seen in current light water reactors. In particular, High-Assay Low Enriched Uranium (HALEU), that is uranium enriched to 235 U ≈ 20 w/o%, is planned to be used in over ten new reactor concepts. HALEU is attractive for advanced reactors as it enables longer intervals between refueling. Unfortunately, little to no experience with HALEU is available in experimental literature raising concerns for not only licensing advanced re actors but also fabrication and transportation of HALEU fuels. This is where Deimos, a Los Alamos National Laboratory internal project, comes in. Deimos is a new critical experiment scheduled for FY24 at the National Criticality Experiments Research Center (NCERC). Deimos is a graphite moderated, graphite and beryllium reflected critical experiment making use of HALEU TRi-structural ISOtropic (TRISO) fuel from the Compact Nuclear Power System (CNPS). This transaction entails a brief description of efforts to benchmark Deimos for inclusion into the International Criticality Safety

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Benchmark Testing of Two Residential Refrigerators Using R-600a

Household refrigerators provide a convenient and safe means of food preservation and storage. More than 100 million refrigerators are used in US homes, resulting in significant primary energy consumption and carbon emissions. As a greenhouse gas with a 100-year global warming potential of 1,430, R-134a has been banned in new US domestic refrigerators and freezers since 2021, and R-600a with a global warming potential of 3 is widely employed as a working fluid in the current US household refrigerator market. In this paper, benchmark testing was conducted for two 2023 refrigerators using R-600a. Moreover, the effect of representative customer use patterns, such as door opening and warm food storage, was studied to evaluate the effect on the energy consumption of the refrigerators. These results will provide background knowledge for facilitating the integration of new technologies to achieve significantly reduced greenhouse gas emissions in future efficient refrigerators.

Gao, Zhiming↗

Comparison of Results between the Legacy and Refined RELAP5-3D Models of the High Temperature Test Facility in Exercises 1 and 2 of the HTTF Benchmark

Work conducted in FY23 identified that RELAP5-3D was capable of reproducing trends in HTTF data during experiment PG-27 but was incapable of reproducing measured values. The primary cause of this discrepancy between RELAP5-3D results and experimental data was hypothesized to be a distortion in power density that was introduced by the radial nodalization of the model. We further hypothesized that a new model would provide better results when compared to the experiments PG-27 and PG-29. Work this FY developed a new model that is better capable of capturing local heat generation rates and contains a representation of each 1/6 azimuthal sector of the core. We used this model to develop a new set of solutions to Exercises 1 and 2 of Problems 2 and 3 in the benchmark. In this report, we present the first comprehensive comparison of the results between the two models. We see that in Exercise 1A, which is common between problems 2 and 3, the results are similar, though the results from the new model show greater detail than those from the legacy model. In Problem 2 Exercise 1B and Problem 3 Exercise 1B, we see that heat removal is slower in the new model than the legacy model. Problem 3 Exercise 1C shows temperatures that are lower in most places in the new model than the legacy model, but the area with active heat generation has higher block temperatures in the new model than the legacy model. Problem 3 Exercise 1D further shows that long-term heat removal is lower in the new model. Problem 2 Exercise 1C demonstrated that the new model observes higher temperatures in the core regions than the legacy model, justifying the need to preserve the power density in HTTF. The validation of PG-27 and PG-29 also demonstrated the improved temperature agreement in the core regions, particularly with a calibrated model that implements an effective thermal conductivity for the core material. Overall, PG-27 models show reasonable to excellent agreement for steady-state temperatures and minimal to reasonable agreement for transients. PG-29 models showed minimal to insufficient agreement with the data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Benchmark results with a new evaluation of 155 Gd and 157 Gd

Evaluations of gadolinium isotopes 155 Gd and 157 Gd in the resolved resonance region were performed with the code SAMMY. The main objective for revising the resonance evaluations of these isotopes was to address issues related to critical benchmark results.

07 ISOTOPE AND RADIATION SOURCES↗

Practical Scalability of LuGo: Benchmarking the HHL Algorithm Using an Enhanced QPE Algorithm

The HHL algorithm is a prominent quantum algorithm that offers exponential speedup over its classical counterparts for solving a system of linear equations. However, synthesizing and executing HHL circuits demand significant computational resources from both classical and quantum systems. In this paper, we benchmark the HHL algorithm using the optimized Quantum Phase Estimation (QPE) generation algorithm, LuGo \cite{lu2025lugo}, to enhance its scalability and efficiency. We leverage the National Energy Research Scientific Computing Center's (NERSC) Perlmutter supercomputer to evaluate the scalability of generating HHL circuits and to measure the time to simulate the generated circuits. Additionally, we provide a comprehensive analysis of the algorithm's performance on various state-of-the-art superconducting and trapped-ion quantum devices, including studies on qubit connectivity, fidelity comparisons, and hardware compatibility and robustness. Our results offer preliminary insights into potential practical applications of the HHL algorithm enabled by LuGo and the performance of various types of quantum hardware.

Lu, Chao [ORNL] (ORCID:0000000179346933)↗

TRISO-form HALEU-fueled Experiment for Transport Applications (THETA) Serpent 2 Benchmarking

A number of new advanced reactor designs use TRI-structural ISO-topic (TRISO) fuel. The uranium enrichment for the TRISO fuel is in the 5- to 19.75-weight percent range, which is considered High-Assay Low Enriched Uranium (HALEU). The Nuclear Regulatory Commission and vendors both have a strong interest in benchmarking these advanced reactor designs and having confidence in the predictive capabilities of the computer codes used to model them. In the recent years, Serpent 2 gained several capabilities focused on the reactor applications making it attractive for many reactor vendors.

Critical Experiment↗