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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Benchmarking black hole heat engines, I

We present the results of initiating a benchmarking scheme that allows for cross-comparison of the efficiencies of black holes used as working substances in heat engines. We use a circular cycle in the [Formula: see text] plane as the benchmark engine. We test it on Einstein–Maxwell, Gauss–Bonnet and Born–Infeld black holes. Also, we derive a new and surprising exact result for the efficiency of a special “ideal gas” system to which all the black holes asymptote.

Astronomy & Astrophysics↗
DOE OSTI2020

A Sparse Tensor Benchmark Suite for CPUs and GPUs

Tensor computations present significant performance chal- lenges that impact a wide spectrum of applications ranging from machine learning, healthcare analytics, social network analysis, data mining to quantum chemistry and signal processing. Efforts to improve the perfor- mance of tensor computations include exploring data layout, execution scheduling, and parallelism in common tensor kernels. This work presents a benchmark suite for arbitrary-order sparse tensor kernels using state- of-the-art tensor formats: coordinate (COO) and hierarchical coordinate (HiCOO) on CPUs and GPUs. It presents a set of reference tensor kernel implementations that are compatible with real-world tensors and power law tensors extended from synthetic graph generation techniques. We also propose Roofline performance models for these kernels to provide insights of computer platforms from sparse tensor view. This benchmark suite along with the synthetic tensor generator is publicly available.

Li, Jiajia↗
DOE OSTI2026

wa-hls4ml: A Benchmark and Surrogate Models for hls4ml Resource and Latency Estimation

As machine learning (ML) is increasingly implemented in hardware to address real-time challenges in scientific applications, the development of advanced toolchains has significantly reduced the time required to iterate on various designs. These advancements have solved major obstacles, but also exposed new challenges. For example, processes that were not previously considered bottlenecks, such as hardware synthesis, are becoming limiting factors in the rapid iteration of designs. To mitigate these emerging constraints, multiple efforts have been undertaken to develop an ML-based surrogate model that estimates resource usage of ML accelerator architectures. We introduce wa-hls4ml, a benchmark for ML accelerator resource and latency estimation, and its corresponding initial dataset of over 680,000 fully connected and convolutional neural networks, all synthesized using hls4ml and targeting Xilinx FPGAs. The benchmark evaluates the performance of resource and latency predictors against several common ML model architectures, primarily originating from scientific domains, as exemplar models, and the average performance across a subset of the dataset. Additionally, we introduce GNN- and transformer-based surrogate models that predict latency and resources for ML accelerators. We present the architecture and performance of the models and find that the models generally predict latency and resources for the 75% percentile within several percent of the synthesized resources on the synthetic test dataset.

Hawks, Benjamin [Fermilab] (ORCID:0000000157000288↗
DOE OSTI2017

Application of Benchmarked Kinetic Resistive Wall Mode Stability Codes to ITER, Including Additional Physics

Leading resistive wall mode (RWM) stability codes MARS-K [Y. Liu, et al., Phys. Plasmas 15, 112503 (2008)] and MISK [B. Hu, et al., Phys. Plasmas 12, 057301 (2005)] have been previously benchmarked. The benchmarking has now been extended to include additional physics, and used to project the stability of ITER in a realistic operating space. Due to ITER's relatively low plasma rotation and collisionality, collisions and non-resonance rotational effects were both found to have little impact on stability, and these non-resonance rotational effects also will not self-consistently affect the ITER RWM eigenfunction. Resonances between thermal ions and electrons and the expected level of ITER toroidal rotation were found to be important to stability, as were alpha particles, which are not in rotational resonance. MISK calculations show that without alpha particles, ITER is projected to be unstable to the RWM, but the expected level of alphas is calculated to provide a sufficient level of stability.

Resistive Wall Mode Stability↗
DOE OSTI2017

Algebraic Multigrid Benchmark

AMG is a parallel algebraic multigrid solver for linear systems arising from problems on unstructured grids. It has been derived directly from the BoomerAMG solver in the hypre library, a large linear solvers library that is being developed in the Center for Applied Scientific Computing (CASC) at LLNL and is very similar to the AMG2013 benchmark with additional optimizations. The driver provided in the benchmark can build various test problems. The default problem is a Laplace type problem with a 27-point stencil, which can be scaled up and is designed to solve a very large problem. A second problem simulates a time dependent problem, in which successively various smnllcr systems are solved.

Yang, Ulrike↗
DOE OSTI2026

Benchmarking the performance of uncertainty quantification methods for neural network-based interatomic potentials

Machine-learned interatomic potentials (ML-IAPs) continue to gain popularity as accurate, computationally efficient replacements for traditional, physics-based interatomic potentials and expensive ab initio methods. Uncertainty quantification (UQ) of ML-IAPs is a growing area of research as UQ is critical in many applications of IAPs, such as developing curated datasets, active learning-based data augmentation, self-improving models, and estimating the uncertainty of molecular dynamics simulations. In this paper, we construct and benchmark a series of different neural network potentials (NNPs) with varying network architectures to determine the performance of these models with respect to both the mean and uncertainty calibration error. Each NNP method is specifically designed to predict either epistemic or aleatoric uncertainty with particular focus on the differences in behavior between the epistemic and aleatoric uncertainty estimates. We benchmark these methods using multiple datasets common in the ML-IAP literature. The results show that the aleatoric uncertainty from single-shot model architectures is a competitive alternative to ensemble-based epistemic uncertainty predictions in regions of sufficient data-density. However, in regions where the representative data is sparse, aleatoric uncertainty models tend to overpredict and epistemic methods tend to underpredict the actual model error. We conclude that the type of UQ is crucial when discussing performance of probabilistic model results as different methods have different performance characteristics depending on the regime in which they are evaluated. Therefore, the type of UQ method should be carefully evaluated against both the data characteristics and requirements for the intended application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Reference solutions for linear radiation transport: the Hohlraum and Lattice Benchmarks

Radiation transport describes the propagation of energetic particles through space as they interact with a surrounding material medium. In a kinetic description, radiation transport is modeled by a radiation transport equation (RTE) that prescribes the density of the radiation in position-momentum phase space. The purpose of this dataset is to provide highly resolved solutions to two benchmark problems. These two benchmarks do not possess exact solutions; moreover, the construction of a manufactured solution may require a non-physical source that is not desirable, especially if it spoils the physical nature of the solution. Thus the goal of this computational study is to provide a highly resolved reference solution for testing newer, more cost efficient methods that are currently being developed in the research community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Li1−xNiO2 Many-body DMC Benchmark Dataset

The dataset contains all numerical data generated in support of the manuscript “Many‑body Benchmark of Electronic Charge and Spin Densities for Li1–xNiO2​” (Journal of Chemical Theory and Computation, DOI: 10.1021/acs.jctc.5c02097, URL: https://pubs.acs.org/doi/10.1021/acs.jctc.5c02097). The materials included in this repository are: 1. Data files used to produce all figures and tables in the main manuscript and supporting information. 2. Benchmark density‑functional theory (DFT) datasets used for the charge‑ and spin‑density analyses. 3. Reference many‑body diffusion Monte Carlo (DMC) calculations and associated input/output files.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Comparison of Spatial Discretization Methods for Solving the S N Equations Using a Three-Dimensional Method of Manufactured Solutions Benchmark Suite with Escalating Order of Nonsmoothness

For this study, a comparison of the accuracy and computational efficiency of spatial discretization methods of the three-dimensional S N equations is conducted, including discontinuous Galerkin finite element methods, the arbitrarily high-order transport method of nodal type (AHOTN), the linear-linear method, the linear-nodal (LN) method, and the higher-order diamond difference method. For this purpose, we have developed a suite of method of manufactured solutions benchmarks that provides an exact solution of the S N equations even in the presence of scattering. Most importantly, our benchmark suite permits the user to set an arbitrary level of smoothness of the exact solution across the singular characteristics. Our study focuses on the computational efficiency of the considered spatial discretization methods. Numerical results indicate that the best-performing method depends on the norm used to measure the discretization error. We employ discrete Lp norms and integral error norms in this work. For configurations with continuous exact angular flux, high-order AHOTNs perform best under L p error norms, while the LN method performs best when measured by integral error norms. Lastly, when the angular flux is discontinuous, a new singular-characteristic tracking method for three-dimensional geometries performs best among the considered methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Benchmarking of ENDF/B-VIII.0 cross sections for LWR ex-core transport applications

ENDF/B-VIII.0 cross section data is benchmarked on a simple Monte-Carlo model representative of the ex-core geometry of a PWR used for reactor vessel neutron fluence calculations. The benchmarking indicates that the ENDF/B-VIII.0 results show large differences as compared to previous evaluations, which have been extensively compared to measured data. This exercise suggests that ENDF/B-VIII.0 nuclear data is not suitable for ex-core LWR radiation transport applications. Evaluators are aware of the problems with the ENDF/B-VIII.0 evaluation of iron and work is underway to improve the evaluations for an upcoming release.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Data Testing of Polyethylene Thermal Scattering Law with New Thermal Epithermal eXperiments (TEX) Plutonium Baseline Benchmark, PU-MET-MIXED-002

Five plutonium baseline experiments completed in September of 2018 from the Thermal Epithermal eXperiments (TEX) program have been accepted by the International Criticality Safety Benchmark Evaluation Project as PU-MET-MIXED-002 and will be included in the 2020 version of the handbook. The experiments were made up of stacked layers of plutonium Zero Power Physics Reactor (ZPPR) plates moderated by polyethylene (PE, chemical formula C2H4) to varying degrees to create configurations with five different neutron spectra, including one fast configuration, one thermal configuration, and three mixed configurations. Calculations of the benchmark show overprediction of k eff when using the most recent release of the Evaluated Nuclear Data File Version B (ENDF/B) library release (VIII.0) cross sections, particularly when compared to the previous ENDF/B-VII.1 results. One potential source of overprediction was hypothesized to be the new Molecular Dynamics (MD) generated PE Thermal Scattering Law (TSL). The overprediction was shown via calculation to not be caused by the new ENDF/B-VIII.0 thermal scattering law, and in fact the overprediction was mitigated by the new PE TSL.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Charged point defect benchmark of Hybrid and GGA-PBE

Data used by the publication "High-throughput calculations of charged point defect properties with semi-local density functional theory - performance benchmarks for materials screening applications." This work presented an in-depth benchmark analysis of automated, semi-local point defect calculations with a-posteriori corrections, compared to 245 “gold standard” hybrid calculations previously published. We considered three different a-posteriori correction sets for semi-local calculations, implemented in a fully automated workflow, and consider the qualitative and quantitative differences for four different categories of defect information: thermodynamic transition levels, formation energies, fermi levels, and dopability limits. We highlighted the type of qualitative information about point defect properties that can be extracted from high-throughput calculations based on semi-local DFT methods, while also demonstrating the limits of quantitative accuracy that can be achieved by these approaches.

Broberg, Danny↗
DOE OSTI2026

Wire-arc Additive Manufacturing Benchmark

This is the dataset associated with the 2022 SRP Additive Manufacturing Prediction Challenge, originally hosted on Github at https://github.com/SRP-AM/SRP_AM_Prediction_Challenge. The benchmark was designed for validating prediction for the temperature history, residual stress, and distortion of an additively manufactured metal part with relatively simple geometry. A calibration problem with the same as-built geometry is provided with measured quantities of interest; including temperature histories at selective locations, post-build residual stress at selective locations, and overall distortion measurements. The challenge problem is presented with a different build sequence (i.e. thermal history). In this dataset, we include the actual recorded calibration and challenge measurements, as well as benchmark template files for testing predictions without incorporating the challenge data. Supplementary files around the materials and setup are available for transparency and reproducibility.

Bachus, Nicholas [UC Davis, Davis, CA]↗
DOE OSTI2022

Benchmarking Demand Flexibility in Commercial Buildings and Flattening the Duck – Addressing Baseline and Commissioning Challenges

With the transition from our traditional electric grid to a cleaner grid with renewable power generation, there is a need to enable building loads to be flexible. Load shedding and shifting will be essential for flattening the “Duck” for decarbonization. This paper explored the trend in the timing of DR events as a reflection of the grid’s needs using recent four years of event data from 203 retail stores in 11 states. The events are becoming significantly shorter with 2-hour duration being the most popular; shifting to late afternoon and early evening is another trend beyond California. Benchmarking will be essential for accounting DF as a reliable grid resource. This paper addresses a challenging aspect of benchmarking – inaccuracies in counterfactual baseline methods can introduce significant DF metrics variations in addition to weather and building characteristics related factors. The conventional “10/10” with adjustment baseline method has inherent limitation by design for load shifting applications. Therefore, it is imperative to identify alternative methods. This study compared three hourly regression baseline methods with “10/10” methods using two groups of commercial buildings that participated in DR programs: (1) 121 big-box retail stores, and (2) 11 office buildings in CA. The 14-day hourly outdoor temperature regression method was found to produce least error in the tested datasets and is promising for load shifting. The paper also pointed out that commissioning issues can also be a significant barrier for achieving consistent DF performance, which building managers and utilities should be aware of.

Liu, Jingjing↗
DOE OSTI2022

The Dark Machines Anomaly Score Challenge: Benchmark Data and Model Independent Event Classification for the Large Hadron Collider

We describe the outcome of a data challenge conducted as part of the Dark Machines (https://www.darkmachines.org) initiative and the Les Houches 2019 workshop on Physics at TeV colliders. The challenged aims to detect signals of new physics at the Large Hadron Collider (LHC) using unsupervised machine learning algorithms. First, we propose how an anomaly score could be implemented to define model-independent signal regions in LHC searches. We define and describe a large benchmark dataset, consisting of >1 billion simulated LHC events corresponding to 10\, fb^{-1} 10 f b − 1 of proton-proton collisions at a center-of-mass energy of 13 TeV. We then review a wide range of anomaly detection and density estimation algorithms, developed in the context of the data challenge, and we measure their performance in a set of realistic analysis environments. We draw a number of useful conclusions that will aid the development of unsupervised new physics searches during the third run of the LHC, and provide our benchmark dataset for future studies at https://www.phenoMLdata.org. Code to reproduce the analysis is provided at https://github.com/bostdiek/DarkMachines-UnsupervisedChallenge.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

PDF4LHC21: Update on the benchmarking of the CT, MSHT and NNPDF global PDF fits

There have been recent updates to the three global PDF fits (CT, MSHT and NNPDF), all adding large amounts of data from the LHC, and this has resulted in significant changes to the global PDFs. Given the impact that the new PDFs will have on physics comparisons at the LHC, it is crucial to perform a benchmarking among the PDFs, similar in spirit to that which was carried out for PDF4LHC15, widely used for LHC physics. In this article we detail a benchmarking comparison of three global PDF sets - CT18, MSHT20 and NNPDF3.1 - and their similarities and differences that have been observed. The end result of this study will be a new PDF4LHC21 ensemble of combined PDFs suitable for a wide range of LHC applications.

Cridge, Thomas↗
DOE OSTI2017

Installed Cost Benchmarks and Deployment Barriers for Residential Solar Photovoltaics with Energy Storage: Q1 2016

In this report, we fill a gap in the existing knowledge about PV-plus-storage system costs and value by providing detailed component- and system-level installed cost benchmarks for residential systems. We also examine other barriers to increased deployment of PV-plus-storage systems in the residential sector. The results are meant to help technology manufacturers, installers, and other stakeholders identify cost-reduction opportunities and inform decision makers about regulatory, policy, and market characteristics that impede solar plus storage deployment. In addition, our periodic cost benchmarks will document progress in cost reductions over time. To analyze costs for PV-plus-storage systems deployed in the first quarter of 2016, we adapt the National Renewable Energy Laboratory's component- and system-level cost-modeling methods for standalone PV. In general, we attempt to model best-in-class installation techniques and business operations from an installed-cost perspective. In addition to our original analysis, model development, and review of published literature, we derive inputs for our model and validate our draft results via interviews with industry and subject-matter experts. One challenge to analyzing the costs of PV-plus-storage systems is choosing an appropriate cost metric. Unlike standalone PV, energy storage lacks universally accepted cost metrics, such as dollars per watt of installed capacity and lifetime levelized cost of energy. We explain the difficulty of arriving at a standard approach for reporting storage costs and then provide the rationale for using the total installed costs of a standard PV-plus-storage system as our primary metric, rather than using a system-size-normalized metric.

14 SOLAR ENERGY↗
DOE OSTI2017

U.S. Solar Photovoltaic System Cost Benchmark: Q1 2017

NREL has been modeling U.S. photovoltaic (PV) system costs since 2009. This year, our report benchmarks costs of U.S. solar PV for residential, commercial, and utility-scale systems built in the first quarter of 2017 (Q1 2017). Costs are represented from the perspective of the developer/installer, thus all hardware costs represent the price at which components are purchased by the developer/installer, not accounting for preexisting supply agreements or other contracts. Importantly, the benchmark this year (2017) also represents the sales price paid to the installer; therefore, it includes profit in the cost of the hardware, along with the profit the installer/developer receives, as a separate cost category. However, it does not include any additional net profit, such as a developer fee or price gross-up, which are common in the marketplace. We adopt this approach owing to the wide variation in developer profits in all three sectors, where project pricing is highly dependent on region and project specifics such as local retail electricity rate structures, local rebate and incentive structures, competitive environment, and overall project or deal structures.

14 SOLAR ENERGY↗