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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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DOE OSTI2021

Updates to Improve the Evaluated Nuclear Data of Copper Isotopes in the Resolved and Unresolved Resonance Regions

The evaluated nuclear data of the 63,65 Cu isotopes have been updated in the resolved and unresolved resonance energy regions with the goal of improving the fidelity between calculated and measured critical benchmarks. Particular focus was devoted to the 63 Cu(n, γ) cross sections because of their large sensitivity to the reactivity in the benchmark calculations. By focusing on these cross sections, the set of parameters in both resolved and unresolved resonance regions were fitted to available experimental data. The newly updated evaluations were compared to the currently available ENDF/B-VIII.0 evaluations in reactivity calculations for copper-sensitive integral benchmarks. An initial study of the sensitivity of the benchmarks to the angular distributions was performed, finding it necessary to describe the angular distributions more accurately above 100 keV. This investigation uncovered the need for more accurate data for the 63 Cu(n, γ) cross section above 100 keV. An increase in the capture cross section was found to improve agreement for the considered benchmarks.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2019

A performance evaluation framework for building fault detection and diagnosis algorithms

Fault detection and diagnosis (FDD) algorithms for building systems and equipment represent one of the most active areas of research and commercial product development in the buildings industry. However, far more effort has gone into developing these algorithms than into assessing their performance. As a result, considerable uncertainties remain regarding the accuracy and effectiveness of both research-grade FDD algorithms and commercial products - a state of affairs that has hindered the broad adoption of FDD tools. This article presents a general, systematic framework for evaluating the performance of FDD algorithms. The article focuses on understanding the possible answers to two key questions: in the context of FDD algorithm evaluation, what defines a fault and what defines an evaluation input sample? The answers to these questions, together with appropriate performance metrics, may be used to fully specify evaluation procedures for FDD algorithms.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Algal Biomass Production via Open Pond Algae Farm Cultivation: 2021 State of Technology and Future Research

The annual State of Technology (SOT) assessment is an essential activity for platform research conducted under the Bioenergy Technologies Office. It allows for the impact of research progress to be quantified in terms of economic improvements in the overall biofuel production process for a particular biomass processing pathway, whether based on terrestrial or algal biomass feedstocks. As such, initial benchmarks can be established for currently demonstrated performance, and progress can be tracked towards out-year goals to ultimately demonstrate economically viable biofuel technologies. NREL's algae state of technology benchmarking efforts focus both on front-end algal biomass production and separately on back-end conversion to fuels through NREL's "combined algae processing" (CAP) pathway. The production model is based on outdoor long-term cultivation data, enabled by comprehensive algal biomass production trials conducted under Development of Integrated Screening, Cultivar Optimization, and Verification Research (DISCOVR) consortium efforts, driven by data furnished by Arizona State University (ASU) at the Arizona Center for Algae Technology and Innovation (AzCATI) testbed site. The CAP model is based on experimental efforts conducted under NREL research and development projects. This report focuses on front-end algal biomass production, documenting the pertinent algal biomass cultivation parameters that were input to the NREL open pond algae farm model based on the latest DISCOVR cultivation performance data. Relative to the fiscal year (FY) 2020 SOT at $683/ton or $603/ton for ASU and FA evaporation scenarios, respectively (unlined pond basis), the FY 2021 SOT represents a slight increase in MBSP of 1%-2%. This is primarily attributed to a slight 4% reduction in annual cultivation productivity achieved at the AzCATI site (supported by the efforts under the DISCOVR consortium noted above) observed during FY 2021 cultivation campaigns.

09 BIOMASS FUELS↗
DOE OSTI2020

The ESIF-HPC-2 Benchmark Suite

We describe the development of the ESIF-HPC-2 benchmark suite, a collection of kernel and application benchmark codes for measuring computational and I/O performance from single nodes to full HPC systems that was used for acceptance testing in our recent HPC procurement. The configurations of the benchmarks used for our system is presented. We also describe a set of "dimensions" that can be used to classify benchmarks and assess coverage of a suite systematically. The collection is offered cost-free as a GitHub repository for general usage and further development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

The ESIF-HPC-2 Benchmark Suite: Preprint

We describe the development of the ESIF-HPC-2 benchmark suite, a collection of kernel and application benchmark codes for measuring computational and I/O performance from single nodes to full HPC systems that was used for acceptance testing in our recent HPC procurement. The configurations of the benchmarks used for our system is presented. We also describe a set of 'dimensions' that can be used to classify benchmarks and assess coverage of a suite systematically. The collection is offered cost-free as a GitHub repository for general usage and further development.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Reactor physics benchmark of Westinghouse PWR core design suite for high burnup/high enrichment fuel - Part 1: Pin and lattice

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. This paper focuses on analysis of the predictions for pin and lattice designs representative of HB/HE core reloads from the Westinghouse advanced lattice code PARAGON2, the Monte-Carlo code SERPENT2 and MPACT, the deterministic neutronic component of VERA. A companion paper presented at this conference analyzes results obtained with the Westinghouse ANC9 core simulator, using lattice data provided by PARAGON2 with the NEXUS cross-section methodology, and MPACT for 2D and 3D core configurations incorporating HB/HE fuel reloads to achieve cycle length extension to 24-month in high-power density PWRs. The results of the pin and lattice benchmark presented in this paper show that the neutronic predictions from PARAGON2 for HB/HE fueled PWRs are in remarkable agreement with predictions from both SERPENT2 and MPACT including for depletion to high fuel burnup values, and employing a set of challenging lattices which feature combined use of burnable absorbers to obtain the required reactivity hold-down to support PWR transition to HB/HE fuel and 24-month operational cycles. As corroborated by this analysis and the analysis contained in the companion paper, the Westinghouse NEXUS-based PWR core analysis package can be confidently applied by industry for design analysis of PWR core reloads adopting HB/HE fuel and properly support the industry commercialization plans for in-reactor deployment. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

A Performance Study of Quantum ESPRESSO’s PWscf Code on Multi-core and GPU Systems

We describe the porting of PWscf (Plane-Wave Self Consistent Field), a key component of the Quantum ESPRESSO open-source suite of codes for materials modeling, to GPU systems using CUDA Fortran. Kernel loop directives (CUF kernels) have been extensively used in order to have a single source code for both CPU and GPU implementations. The results of the GPU version have been carefully validated and the performance of the code on several GPU systems (both x86 and POWER8 based) has been compared with traditional Intel multi-core (CPU only) systems. This current GPU version can reduce the time-to-solution by an average factor of 2–3 running two different input cases widely used as benchmarks on small and large high performance computing systems.

CUDA Fortran↗
DOE OSTI2020

Detection of Defects in Additively Manufactured Metallic Materials with Machine Learning of Pulsed Thermography Images

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of nuclear reactor parts. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores and anisotropy. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures due to exposure to high temperature, radiation and corrosive environment in a nuclear reactor. Quality control (QC) requires nondestructive evaluation (NDE) of actual AM structures. Pulsed thermography is a potentially promising QC technique because it is scalable to arbitrary structure size. However, detection sensitivity of this method is limited by noises. We investigate separation of signal from noise in thermography images using several machine learning (ML) methods, including new spatio-temporal blind source separation (STBSS) and spatio-temporal sparse dictionary learning (STSDL) methods. Performance of the ML methods is benchmarked using thermography data obtained from imaging stainless steel 316L and Inconel 718 specimens produced LPBF method with imprinted calibrated porosity defects. The ML methods are ranked by F-score and execution runtime. The ML methods with higher accuracy require longer run time. However, this runtime is sufficiently short to perform QC within a realistic time frame.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Quality Control of Additively Manufactured Metallic Structures with Machine Learning of Thermography Images

Additive manufacturing (AM) of high-strength metals is currently based on the laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores and anisotropy. Quality control (QC) requires nondestructive evaluation of actual AM structures. Flash thermography is a potentially promising QC technique because it is scalable to arbitrary structure size. However, the detection sensitivity of this method is limited by noise. We investigate separation of signal from noise in thermography images using several machine learning (ML) methods, including new spatial–temporal blind source separation and spatial–temporal sparse dictionary learning methods. Performance of the ML methods is benchmarked using thermography data obtained from imaging stainless steel 316L and Inconel 718 specimens produced by the LPBF method with imprinted calibrated porosity defects. The ML methods are ranked by F-score and execution runtime. Finally, the ML methods with higher accuracy require a longer runtime. However, this runtime is sufficiently short to perform QC within a realistic time frame.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Algal Biomass Conversion to Fuels via Combined Algae Processing (CAP): 2020 State of Technology and Future Research

The annual State of Technology (SOT) assessment is an essential activity for platform research conducted under the Bioenergy Technologies Office. It allows for the impact of research progress to be quantified in terms of economic improvements in the overall biofuel production process for a particular biomass processing pathway, whether based on terrestrial or algal biomass feedstocks. As such, initial benchmarks can be established for currently demonstrated performance, and progress can be tracked towards out-year goals to ultimately demonstrate economically viable biofuel technologies. NREL's algae state of technology benchmarking efforts focus both on front-end algal biomass production and separately on back-end conversion to fuels through NREL's "combined algae processing" (CAP) pathway. The production model is based on outdoor long-term cultivation data, enabled by comprehensive algal biomass production trials conducted under the Development of Integrated Screening, Cultivar Optimization, and Verification Research consortium (DISCOVR) efforts, driven by data furnished by Arizona State University (ASU) at the Arizona Center for Algae Technology and Innovation (AzCATI) testbed site. The CAP model is based on experimental efforts conducted under NREL research and development projects. This report focuses on back-end conversion of algal biomass through the CAP pathway, highlighting the 2020 updates to minimum fuel selling price (MFSP). Notably, this analysis marks the first time that polyurethane (PU) is included as a value-added coproduct in the SOT case. Relative to prior 2019 benchmarks, the 2020 CAP SOT achieved further MFSP reductions of over $4/gallon gasoline equivalent, reflective of (a) the inclusion of PU co-production, (b) reduced SOT biomass production costs, and (c) higher pretreatment sugar yield data.

09 BIOMASS FUELS↗
DOE OSTI2022

Algal Biomass Conversion to Fuels via Combined Algae Processing (CAP) (2021 State of Technology and Future Research)

The annual State of Technology (SOT) assessment is an essential activity for platform research conducted under the Bioenergy Technologies Office. It allows for the impact of research progress to be quantified in terms of economic improvements in the overall biofuel production process for a particular biomass processing pathway, whether based on terrestrial or algal biomass feedstocks. As such, initial benchmarks can be established for currently demonstrated performance, and progress can be tracked towards out-year goals to ultimately demonstrate economically viable biofuel technologies. NREL's algae state of technology benchmarking efforts focus both on front-end algal biomass production and separately on back-end conversion to fuels through NREL's "combined algae processing" (CAP) pathway. The production model is based on outdoor long-term cultivation data, enabled by comprehensive algal biomass production trials conducted under the Development of Integrated Screening, Cultivar Optimization, and Verification Research consortium (DISCOVR) efforts, driven by data furnished by Arizona State University (ASU) at the Arizona Center for Algae Technology and Innovation (AzCATI) testbed site. The CAP model is based on experimental efforts conducted under NREL research and development projects. This report focuses on back-end conversion of algal biomass through the CAP pathway, highlighting the 2021 updates to minimum fuel selling price (MFSP). This update maintains an important recent inclusion of polyurethane (PU) previously incorporated in the 2020 SOT as a value-added coproduct. Relative to the 2020 SOT case, this indicates a minimal increase of $0.10-$0.14/GGE (roughly 2%) for both the acids and BDO pathways, attributed to minimal increases in upstream algal biomass costs from slightly lower demonstrated cultivation productivities in the 2021 SOT.

09 BIOMASS FUELS↗
DOE OSTI2022

Biochemical Conversion of Lignocellulosic Biomass to Hydrocarbon Fuels and Products (2021 State of Technology and Future Research)

The annual State of Technology (SOT) assessment is an essential activity for biochemical platform research. It allows the impact of research progress to be quantified in terms of economic improvements in the overall cellulosic biofuel production process for a particular conversion pathway. As such, initial benchmarks can be established for currently demonstrated performance and progress can be tracked towards out-year goals to ultimately demonstrate cost-competitive cellulosic biofuel technology. The purpose of this report is to benchmark the latest experimental developments across a number of potential bioconversion pathways as quantified by modeled minimum fuel selling prices (MFSPs), as a measure of current status relative to those final targets. For this state of technology, TEA models were run for two separate biological conversion pathways to fuels, based on available data for integrated biomass deconstruction and hydrolysate processing; namely carboxylic acids (primarily butyric acid) and diols (2,3-butanediol [BDO]), reflecting NREL's recently-published 2018 biochemical design report focused on those two pathways. The models were run across three scenarios for lignin utilization, namely combustion, conversion to coproducts based on "base case" performance with biomass hydrolysate, and conversion to coproducts based on "high" performance demonstrated with model lignin monomer components. A key improvement reflected in the 2021 SOT is centered around making use of the latest lignin conversion data, which over the past year focused primarily on production of ß-ketoadipate (BKA) as a more optimal molecule compared to the closely-related adipic acid coproduct of prior recent focus, both in terms of superior product properties and biology, as well as reduced processing complexity (reducing two steps for sequential production of muconate followed by hydrogenation to adipic acid down to a single step for direct production of BKA). This update translated to a roughly 17% increase in mass yield of final coproduct output at a nearly four-fold increase in fermentation productivity on lignin monomers relative to prior 2020 SOT benchmarks for muconic/adipic acid production.

09 BIOMASS FUELS↗
DOE OSTI2023

Defect Quantification in Metal Halide Perovskites Anticipates Photoluminescence and Photovoltaic Performance

Semiconductor material optimization requires quantification of performance and stability-dependent near-valence maximum and near-conduction minimum defects with sufficient energy resolution and sensitivity. In this work, we utilize a spectroscopy-electrochemistry approach to resolve the energy-distinct donor and acceptor defect concentrations in wide-gap (Cs .05 FA .79 MA .16 )Pb(I .87 Br .13 ) 3 perovskites, benchmarked against photoluminescence and photovoltaic device performance. Monitoring charge transfer events to electron acceptor and donor molecules within solid electrolyte top contacts enables defect quantification below 10 15 cm –3 at an energy resolution of 10 meV under device-relevant bias, well below levels reported by other methods. Further method sensitivity is demonstrated for defects arising from <2% formamidinium concentration modifications, mimicking compositional imperfections resulting from nonoptimized processing. This method provides the first complete perovskite energetic diagrams with small changes in composition, is nondestructive, compatible with in-line processing characterization, and will enable the semiconductor community to link molecular origins of defects with limitations in device performance across a wide array of optoelectronic platforms.

14 SOLAR ENERGY↗
DOE OSTI2014

A local-view array library for partitioned global address space C++programs

Multidimensional arrays are an important data structure in many scientific applications. Unfortunately, built-in support for such arrays is inadequate in C++, particularly in the distributed setting where bulk communication operations are required for good performance. In this paper, we present a multidimensional library for partitioned global address space (PGAS) programs, supporting the one-sided remote access and bulk operations of the PGAS model. The library is based on Titanium arrays, which have proven to provide good productivity and performance. These arrays provide a local view of data, where each rank constructs its own portion of a global data structure, matching the local view of execution common to PGAS programs and providing maximum flexibility in structuring global data. Unlike Titanium, which has its own compiler with array-specific analyses, optimizations, and code generation, we implement multidimensional arrays solely through a C++library. The main goal of this effort is to provide a library-based implementation that can match the productivity and performance of a compiler-based approach. We implement the array library as an extension to UPC++, a C++library for PGAS programs, and we extend Titanium arrays with specializations to improve performance. We evaluate the array library by porting four Titanium benchmarks to UPC++, demonstrating that it can achieve up to 25% better performance than Titanium without a significant increase in programmer effort..

Kamil, A↗
DOE OSTI2012

Detailed high-accuracy megavoltage transmission measurements: A sensitive experimental benchmark of EGSnrc

Purpose: There are three goals for this study: (a) to perform detailed megavoltage transmission measurements in order to identify the factors that affect the measurement accuracy, (b) to use the measured data as a benchmark for the EGSnrc system in order to identify the computational limiting factors, and (c) to provide data for others to benchmark Monte Carlo codes. Methods: Transmission measurements are performed at the National Research Council Canada on a research linac whose incident electron parameters are independently known. Automated transmission measurements are made on-axis, down to a transmission value of {approx}1.7%, for eight beams between 10 MV (the lowest stable MV beam on the linac) and 30 MV, using fully stopping Be, Al, and Pb bremsstrahlung targets and no fattening filters. To diversify energy differentiation, data are acquired for each beam using low-Z and high-Z attenuators (C and Pb) and Farmer chambers with low-Z and high-Z buildup caps. Experimental corrections are applied for beam drifts (2%), polarity (2.5% typical maximum, 6% extreme), ion recombination (0.2%), leakage (0.3%), and room scatter (0.8%)-the values in parentheses are the largest corrections applied. The experimental setup and the detectors are modeled using EGSnrc, with the newly added photonuclear attenuation included (up to a 5.6% effect). A detailed sensitivity analysis is carried out for the measured and calculated transmission data. Results: The developed experimental protocol allows for transmission measurements with 0.4% uncertainty on the smallest signals. Suggestions for accurate transmission measurements are provided. Measurements and EGSnrc calculations agree typically within 0.2% for the sensitivity of the transmission values to the detector details, to the bremsstrahlung target material, and to the incident electron energy. Direct comparison of the measured and calculated transmission data shows agreement better than 2% for C (3.4% for the 10 MV beam) and typically better than 1% for Pb. The differences can be explained by acceptable photon cross section changes of Less-Than-Or-Slanted-Equal-To 0.4%. Conclusions: Accurate transmission measurements require accounting for a number of influence quantities which, if ignored, can collectively introduce errors larger than 10%. Accurate transmission calculations require the use of the most accurate data and physics options available in EGSnrc, particularly the more accurate bremsstrahlung angular sampling option and the newly added modeling of photonuclear attenuation. Comparison between measurements and calculations implies that EGSnrc is accurate within 0.2% for relative ion chamber response calculations. Photon cross section uncertainties are the ultimate limiting factor for the accuracy of the calculated transmission data (Monte Carlo or analytical).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Toward a persistent event-streaming system for high-performance computing applications

High-performance computing (HPC) applications have traditionally relied on parallel file systems and file transfer services to manage data movement and storage. Alternative approaches have been proposed that use direct communications between application components, trading persistence and fault tolerance for speed. Event-driven architectures, as popularized in enterprise contexts, present a compelling middle ground, avoiding the performance cost and API constraints of parallel file systems while retaining persistence and offering impedance matching between application components. However, adapting streaming frameworks to HPC workloads requires addressing challenges unique to HPC systems. This paper investigates the potential for a streaming framework designed for HPC infrastructures and use cases. We introduce Mofka, a persistent event-streaming framework designed specifically for HPC environments. Mofka combines the capabilities of a traditional streaming service with optimizations tailored to the HPC context, such as support for massively multicore nodes, efficient scaling for large producer-consumer workflows, RDMA-enabled high-performance network communications, specialized network fabrics with multiple links per node, and efficient handling of large scientific data payloads. Built using the Mochi suite of HPC data service components, Mofka provides a lightweight, modular, and high-performance solution for persistent streaming in HPC systems. We present the architecture of Mofka and evaluate its performance against Kafka and Redpanda using benchmarks on diverse platforms, including Argonne's Polaris and Oak Ridge's Frontier supercomputers, showing up to 8× improvement in throughput in some scenarios. We then demonstrate its utility in several real-world applications: a tomographic reconstruction pipeline, a workflow for the discovery of metal-organic frameworks for carbon capture, and the instrumentation of Dask workflows for provenance tracking and performance analysis.

HPC↗
DOE OSTI2022

IER 555: Godiva Benchmark Update CED-2 (Final Design Report)

The International Criticality Safety Benchmark Evaluation Project (ICSBEP) evaluation of the Godiva IV critical assembly, HEU-MET-FAST-086: GODIVA-IV DELAYED-CRITICAL EXPERIMENTS (HMF-086), was completed by Russ Mosteller. Five critical experiment configurations performed at the Los Alamos National Laboratory (LANL) Technical Area (TA)-18 were evaluated as acceptable benchmark cases. The five cases consist of four delayed critical configurations which differ in control rod positions and one prompt critical configuration. All cases calculated a lower $k_{eff}$ than measured by experiment. This data is referred to as the TA-18 Godiva IV benchmark in this report. In 2005, Godiva IV was disassembled for relocation to the Nevada Test Site (NTS), now Nevada National Security Site (NNSS), at the National Criticality Experiments Research Center (NCERC). Following the disassembly and subsequent reassembly and startup of Godiva IV at NCERC, additional information about the Godiva IV components was obtained. An errata note was added to the HMF-086 evaluation in the ICSBEP handbook to provide this new information until a revision to the benchmark evaluation could be performed. In addition to those corrections, there are differences between the Godiva IV assembly at TA-18 and the Godiva IV assembly at NCERC. These differences include both assembly-specific differences (differences in the safety block gap, differences in the control rod positions, a new NCERC Top Hat and contamination shield) as well as environmental differences, such as the size and shape of the experimental building where the assembly is located. An additional model with similar cases, referred to as the NCERC Godiva IV benchmark in this report, will be added to the revised HMF-086 to capture these additional differences. This will provide the best benchmark model of Godiva for use by those performing experiments at NCERC. The IER 555 CED-2 report documents the information that will be updated in the HMF-086 revision, both the corrections to the TA-18 Godiva IV benchmark and the subsequent changes to create a NCERC Godiva IV benchmark. It describes the measurements that will be performed for cases similar to those performed at TA-18. It also describes measurements that will be included in the evaluation as additional data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Recent Updates in ETOE-2 and MC 2 -3

The MC 2 -3 code is a multigroup cross section generation code for fast reactor applications, developed by Argonne National Laboratory (ANL) under the DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. In this work, first, the cross section libraries for ENDF/B-VII.1 and ENDF/B-VIII.0 data were generated using the updated ETOE-2 code. Preliminary verification and validation tests of the ENDF/B-VII.1 MC 2 -3 library were performed with the selected fast reactor benchmark problems. Processing and verifying the libraries suggested that significant efforts would be required for thoroughly verifying the ENDF/B-VII.1 MC 2 -3 library and successfully processing the ENDF/B-VIII.0 MC 2 -3 library. Secondly, the cross section generation capability of MC 2 -3 was updated with the intermediate group lattice calculation and the equivalent Dancoff-factor cell (EDC) method to significantly improve the performance of a twodimensional assembly calculation using the method of characteristics (MOC). This effort was made useful in implementing and verifying the EDC method in the Griffin cross section API. Finally, we analyzed a SFR problem, for which unusually large deviations in core eigenvalues from Monte Carlo solutions were reported, by generating multigroup cross sections with MC 2 -3, performing core calculations with DIF3D-VARIANT, and analyzing cross section and eigenvalue results against Monte Carlo solutions. The analysis confirmed that the MC 2 -3/DIF3D solutions were in good agreement with Monte Carlo solutions, providing the correct process of accurately generating broad-group cross sections with MC 2 -3

97 MATHEMATICS AND COMPUTING↗