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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2010

A Simplified HTTR Diffusion Theory Benchmark

The Georgia Institute of Technology (GA-Tech) recently developed a transport theory benchmark based closely on the geometry and the features of the HTTR reactor that is operational in Japan. Though simplified, the benchmark retains all the principal physical features of the reactor and thus provides a realistic and challenging test for the codes. The purpose of this paper is twofold. The first goal is an extension of the benchmark to diffusion theory applications by generating the additional data not provided in the GA-Tech prior work. The second goal is to use the benchmark on the HEXPEDITE code available to the INL. The HEXPEDITE code is a Green’s function-based neutron diffusion code in 3D hexagonal-z geometry. The results showed that the HEXPEDITE code accurately reproduces the effective multiplication factor of the reference HELIOS solution. A secondary, but no less important, conclusion is that in the testing against actual HTTR data of a full sequence of codes that would include HEXPEDITE, in the apportioning of inevitable discrepancies between experiment and models, the portion of error attributable to HEXPEDITE would be expected to be modest. If large discrepancies are observed, they would have to be explained by errors in the data fed into HEXPEDITE. Results based on a fully realistic model of the HTTR reactor are presented in a companion paper. The suite of codes used in that paper also includes HEXPEDITE. The results shown here should help that effort in the decision making process for refining the modeling steps in the full sequence of codes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Performance Characterization for Fusion Co-design Applications

Magnetic fusion is a long-term solution for producing electrical power for the world, and the large thermonuclear international device (ITER) being constructed will produce net energy and a path to fusion energy provided the computer modeling is accurate. To effectively address the requirements of the high-end fusion simulation community, application developers, algorithm designers, and hardware architects must have reliable simulation data gathered at scale for scientifically valid configurations. This paper presents detailed benchmarking results for a set of magnetic fusion applications with a wide variety of underlying mathematical models including both particle-in-cell and Eulerian codes using both implicit and explicit numerical solvers. Our evaluation on a petascale Cray XE6 platform focuses on profiling these simulations at scale identifying critical performance characteristics, including scalability, memory/network bandwidth limitations, and communication overhead. Overall results are a key in improving fusion code design, and are a critical first step towards exascale hardware-software co-design — a process that tightly couples applications, algorithms, imple- mentation, and computer architecture.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Long-range correlation energy calculated from coupled atomic response functions

An accurate determination of the electron correlation energy is an essential prerequisite for describing the structure, stability, and function in a wide variety of systems. Therefore, the development of efficient approaches for the calculation of the correlation energy (and hence the dispersion energy as well) is essential and such methods can be coupled with many density-functional approximations, local methods for the electron correlation energy, and even interatomic force fields. In this work, we build upon the previously developed many-body dispersion (MBD) framework, which is intimately linked to the random-phase approximation for the correlation energy. We separate the correlation energy into short-range contributions that are modeled by semi-local functionals and long-range contributions that are calculated by mapping the complex all-electron problem onto a set of atomic response functions coupled in the dipole approximation. We propose an effective range-separation of the coupling between the atomic response functions that extends the already broad applicability of the MBD method to non-metallic materials with highly anisotropic responses, such as layered nanostructures. Application to a variety of high-quality benchmark datasets illustrates the accuracy and applicability of the improved MBD approach, which offers the prospect of first-principles modeling of large structurally complex systems with an accurate description of the long-range correlation energy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Nuclear Software Validation for 7% Enriched UO 2 Fuel Lattices

This analysis performs validation for the Virtual Environment for Reaction Application’s (VERA’s) neutronics codes MPACT and Shift against measured data from the Seven Percent Critical Experiment (7uPCX) at Sandia National Laboratory. The benchmarking supports the future application of VERA for analysis of high-assay low-enriched uranium (HALEU) fuel in commercial pressurized water reactors (PWRs). VERA demonstrates very good agreement with measured data, and the deterministic code MPACT also agrees very well with higher-fidelity stochastic methods KENO-VI and Shift in both total neutron flux and fission rate distribution comparisons. Despite some significant differences between the 7uPCX and existing commercial PWRs that challenge the neutron cross section data and transport solver methods used by MPACT, all of the results are excellent. The agreement increases the confidence in the applicability and accuracy of VERA for reactor analysis of HALEU fuels in commercial reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Reactor physics benchmark of Westinghouse PWR core design suite for high burnup/high enrichment fuel - Part 2: 2D and 3D core simulations

Westinghouse has performed a comprehensive set of code-to-code benchmark comparisons to corroborate application of its state-of-the-art NEXUS-based code suite to high burnup and high enrichment (HB/HE) fueled PWR core design and reload analysis. The benchmark consisted of a progression in complexity from modeling single 2D pin cells, through 2D lattices and finally to whole core 2D and then 3D scenarios. The accompanying paper (Part 1) presented the results for a variety of pin cell and lattices representative of high energy cores and established the ability of the MPACT code to accurately match the predictions of the Monte-Carlo code SERPENT2 such that the former may be used as a surrogate reference code in spatially complex whole core modeling applications where using Monte-Carlo methods is somewhat impractical. This paper focuses on comparisons at the whole core level using a representative high power density 3-loop Westinghouse NSSS core operating for 24 month cycles employing high enriched fuel with use of combined burnable absorbers to hold down excess reactivity. The evolution of the core reactivity and power distribution characteristics throughout the cycle are calculated using the Westinghouse NEXUS-based code suite and compared to the results using MPACT. The results of this whole core benchmark confirm the conclusions that the Westinghouse code suite accurately models HB/HE fuel designs, with very good prediction of core reactivity and power distribution throughout the cycle. The industry can be confident that the NEXUS code system can be deployed to support PWR reload safety and operational analyses for cores featuring HB/HE fuel and 24-month cycle operation. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2012

Testing (Validating?) Cross Sections with ICSBEP Benchmarks [Slides]

We discuss how to use critical benchmarks from the International Handbook of Evaluated Criticality Safety Benchmark Experiments to determine the applicability of specific cross sections to the end-user's problem of interest. Particular attention is paid to making sure the selected suite of benchmarks includes the user's range of applicability (ROA).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Designing Critical Experiments Using Gaussian Process Optimization

New nuclear applications may lack similarity between the application and existing ICSBEP benchmarks. Without accurate benchmark data, predictive simulations will have high uncertainty in the estimate of a parameter of interest (such as k eff ). The design of critical experiments tuned for specific applications of interest is one solution to reducing uncertainty in the necessarily nuclear data. We propose an optimization technique to design critical experiments that match the cross-section sensitivities of an application model while minimizing the number of simulation runs in the optimization. The optimization of a critical experiment is slow because the potential design space covers many qualitative variables (types of material and geometries) and corresponding quantitative variables (e.g., material dimensions) and the evaluation of any specific design requires running an expensive code like MCNP1 and Whisper. The optimization of expensive black-box computer codes with quantitative variables has been extensively explored in the literature of design of computer experiments. We propose a modified version of standard Gaussian process (GP) optimization that optimizes over multiple discrete configurations of qualitative variables in parallel which reduces the computational cost of the entire optimization. The goal of this work is to minimize the number of MCNP evaluations while still exploring many different design configurations in parallel.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

The TENNLab Suite of LIDAR-Based Control Applications for Recurrent, Spiking, Neuromorphic Systems

Recurrent, spiking neuromorphic systems (RSNS’s) have several desirable features compared to conventional neural networks when applied to applications that require real-time control. The TENNLab Exploratory Neuromorphic Computing Framework contains a variety of real-time control applications that use LIDAR for input, and allow a trained RSNS to make real-time decisions for navigation, surveillance and targeting. While each application is interesting on its own, the collection of applications is very useful for benchmarking RSNS’ s, evaluating training algorithms, and designing neuromorphic processing elements. In this paper, we describe the applications that compose the suite, and use them to benchmark four different RSNS’s.

Plank, James↗
DOE OSTI2018

The future of Sinbad: learning from the best practices of ICSBEP - 24622

Two projects sanctioned by the Organisation for Economic Co-operation and Development (OECD) Nuclear Energy Agency (NEA) have over two decades of experience established comprehensive data sets in handbooks supporting criticality safety and reactor physics. The International Criticality Safety Benchmark Evaluation Project (ICSBEP), and later the International Reactor Physics Experiment Evaluation Project (IRPhEP) that was patterned after the success of the ICSBEP, serves as an example of quality and excellence in preserving our nuclear data heritage and establishing benchmark standards upon which current and future modeling, validation, and safety efforts can be supported. Many of the best practices and lessons learned from these benchmark projects can be adopted and adapted for use with the Shielding Integral Benchmark Archive and Database (SINBAD) to prepare higher quality shielding benchmark data to effectively expand the availability of qualified experimental data available to the nuclear community. The unique experiments performed and aggregated within SINBAD represent characteristic measurements, techniques, and applications not captured with the specificity of nuclear criticality safety or traditional reactor physics applications. Application of evaluated SINBAD benchmark data would challenge and enhance our current nuclear data and modeling and simulation strategies. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Fast-Spectrum Critical Assemblies with a Pb-HEU Core Surrounded by a Copper Reflector

The Department of Energy invests tens of millions of dollars each year to develop the next generation of nuclear engineering modeling & simulation (M&S) tools. These M&S tools are used to analyze advanced reactor designs and the safety of current nuclear operations. As computers become more powerful, we are able to enhance resolution in our calculations. This improved resolution is taking us to a point where the limitations of simulation capability are in the quality of data, including our ability to quantify the uncertainty and sensitivity of the data. In order to accurately model systems of interest, the industry must improve key nuclear data measurements and our confidence of how well we understand the data. Thus, M&S tools need evaluated and quality-assured experimental data for validation purposes. The International Criticality Safety Benchmark Evaluation Project (ICSBEP) compiles benchmark experiment data in a handbook that can be used by criticality safety engineers to validate computer codes and cross-section libraries at nuclear facilities. Both critical and subcritical experiments are included in the handbook. Figure 1 organizes all the benchmark evaluations that have been performed by the isotope of interest, in this case Pb, and the neutron energy within the system. Compared to other isotopes of interest for nuclear applications, there are few benchmark evaluations for Pb systems. This has caused the latest nuclear cross-section libraries to over/underestimate changes in the neutron population compared to experimental results. Therefore, this evaluation fills an important knowledge gap in benchmark evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Status of HEU-Pb in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook

The Department of Energy invests tens of millions of dollars each year to develop the next generation of nuclear engineering modeling & simulation (M&S) tools. These tools are used to analyze advanced reactor designs and the safety of current nuclear operations. As computers become more powerful, we are able to enhance resolution in our calculations. This improved resolution is taking us to a point where the limitations of simulation capability are in the quality of data, including our ability to quantify the uncertainty and sensitivity of the data. In order to model systems of interest with increasing accuracy, the industry must improve key nuclear data measurements. Thus, M&S tools need evaluated and quality-assured experimental data for validation purposes. The International Criticality Safety Benchmark Evaluation Project (ICSBEP) compiles and evaluates experiment data in a handbook that can be used by criticality safety engineers and others to validate computer codes and cross-section libraries at nuclear facilities. Both critical and subcritical experiments are included in the handbook. Figure 1 organizes all the benchmark evaluations that have been performed by the isotope of interest, in this case Pb, and the average neutron energy the system. Compared to other isotopes of interest for nuclear applications, there are few benchmark evaluations for Pb systems. The lack of integral measurements to determine errors in Pb cross-section data has caused the latest nuclear cross-section libraries to over/underestimate k eff compared to experimental results. Therefore, this evaluation fills an important knowledge gap in benchmark evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

A Benchmark Case for the Grid Survivability Analysis

Among current priorities of the power system analysis is the development of metrics and computational tools for the resilience analysis during catastrophic events. New methods and tools are required for such an analysis and they have to be validated prior application to real systems. However, benchmark problems are not readily available due to the analysis novelty. The current paper presents a case based on the IEEE 14-bus system for this purpose. The grid is simplified to a graph with nodes representing generators, loads, and buses. Power inputs are imported from real-time simulations of the IEEE 14-bus system. Outcomes of all possible combinations of failed elements are presented in terms of probabilities for the grid to survive, partially survive, or fail. Only the power grid's ability to withstand adverse events (survivability) is analyzed. The grid's recoverability, the other part of the resilience analysis, is not considered.

power system↗
DOE OSTI2025

Benchmarking large language models for materials synthesis: The case of atomic layer deposition

In this work, we introduce an open-ended question benchmark, ALDbench, to evaluate the performance of large language models (LLMs) in materials synthesis, and, in particular, in the field of atomic layer deposition, a thin film growth technique used in energy applications and microelectronics. Our benchmark comprises questions with a level of difficulty ranging from the graduate level to domain expert current with the state of the art in the field. Human experts reviewed the questions along the criteria of difficulty and specificity, and the model responses along four different criteria: overall quality, specificity, relevance, and accuracy. We ran this benchmark on an instance of OpenAI’s GPT-4o. The responses from the model received a composite quality score of 3.7 on a 1–5 scale, consistent with a passing grade. However, 36% of the questions received at least one below average score. An in-depth analysis of the responses identified at least five instances of suspected hallucination. Finally, we observed statistically significant correlations between the difficulty of the question and the quality of the response, the difficulty of the question and the relevance of the response, the specificity of the question, and the accuracy of the response as graded by the human experts. Furthermore, this emphasizes the need to evaluate LLMs across multiple criteria beyond difficulty or accuracy.

Artificial intelligence↗
DOE OSTI2019

Designing Critical Experiments using Gaussian Process Optimization [Slides]

When designing new nuclear applications, there may be a lack of similarity between the application and existing ICSBEP benchmarks. Without appropriate benchmark data, predictive simulations will have high uncertainty in parameters of interest, such as K eff . The goal of the project is to create an algorithm to optimally design critical experiments that match cross-section sensitivities of an application model while minimizing the number of simulation runs in the optimization.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Accelerating Application Bulk Synchronous Writes in HPC Environments

High-bandwidth storage tiers are becoming more common for their capability to absorb high-rate, bursty I/Os. Notably, the designs of these fast storage tiers differ from system to system. The variation of these layers and non-uniform methods of access can pose chal- lenges for applications seeking to run at multiple HPC facilities. Therefore, in this work, we present Spectral, a rapid-output ab- straction library to accelerate application, bulk-synchronous writes on HPC systems. We design Spectral to enable applications to use high-bandwidth storage, such as node-local storage and dis- tributed, write-caches (e.g., burst buffers) transparently without requiring modifications to the application or file system source code. The key idea is to allow applications to spend most of the time performing productive work and to not require any source code changes for maximum portability on different HPC archi- tectures. Spectral internally re-routes write-only files through available, high-performance I/O resources before ultimately mi- grating them to the shared global parallel file system. For instance, on Summit, Spectral transparently places application outputs on node-local storage and then utilizes asynchronous migration to the center-wide GPFS file system. We evaluate Spectral on the Summit HPC system (1024 nodes) using the IOR benchmark and real scientific applications. Spectral shows linear performance scaling, improving application write performance by over an order of magnitude when compared to GPFS.

Khan, Awais↗
DOE OSTI2018

The OpenACC data model: Preliminary study on its major challenges and implementations

This paper describes how the OpenACC data model is implemented in current OpenACC compilers, ranging from research compilers (OpenUH and OpenARC) to a commercial compiler (the PGI OpenACC compiler). First, we summarize various memory architectures in today’s accelerator systems. We then describe details and issues in implementing the OpenACC data model in three different OpenACC compilers. This includes managing page tables, asynchronous data transfers, asynchronous memory allocate and free, host data construct, aliasing on a data directive, reusing device memory, partially present data, and adjacent data. We also discusses ongoing work to manage large, complex dynamic data structures. We measured the present table lookups, device memory allocation, pinned memory allocation, and managed memory in the three OpenACC compilers using eight OpenACC applications (seven from the SPEC ACCEL benchmark suite and a shock-hydrodynamics mini-application called LULESH).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Benchmarking the Suitability of Novec$^{\mathrm{TM}}$ 4710 for Application in Flux Compression Generators

Here, an experimental study evaluated the feasibility of replacing traditional insulating gases such as SF 6 with C 4 F 7 N (3M TM , Novec 4710) in flux compression generator (FCG) applications. Currently available data indicate that Novec 4710 could offer certain performance benefits over SF 6 . However, the available literature is focused on low frequency (50–60 Hz) and dc at static pressures. To evaluate the performance of Novec 4710 under the pulsed dynamic pressure and temperature conditions found in an FCG, we report a performance comparison between three sets of identical FCGs using air, SF 6 , and Novec 4710 as the insulating gas. The generators used in this study had a single stage, directly seeded design with an armature diameter of 25 mm and a stator diameter of 46 mm. To highlight the performance of the different gases rather than any wire insulation, the stator was constructed with uninsulated wire. Furthermore, the generators were seeded aggressively, making the performance difference between the different gases more apparent. The performance was monitored with a pair of differential Rogowski coils that captured the generators’ di / dt while also using high-speed videography to capture possible gaseous breakdown signatures. The data gathered during this study indicate that Novec 4710 performs at least as well as SF 6 in FCG applications, if not significantly better.

42 ENGINEERING↗
DOE OSTI2022

FastML Science Benchmarks: Accelerating Real-Time Scientific Edge Machine Learning

Applications of machine learning (ML) are growing by the day for many unique and challenging scientific applications. However, a crucial challenge facing these applications is their need for ultra low-latency and on-detector ML capabilities. Given the slowdown in Moore's law and Dennard scaling, coupled with the rapid advances in scientific instrumentation that is resulting in growing data rates, there is a need for ultra-fast ML at the extreme edge. Fast ML at the edge is essential for reducing and filtering scientific data in real-time to accelerate science experimentation and enable more profound insights. To accelerate real-time scientific edge ML hardware and software solutions, we need well-constrained benchmark tasks with enough specifications to be generically applicable and accessible. These benchmarks can guide the design of future edge ML hardware for scientific applications capable of meeting the nanosecond and microsecond level latency requirements. To this end, we present an initial set of scientific ML benchmarks, covering a variety of ML and embedded system techniques.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗