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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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Nonlinear Variability due to Mode Coupling in a Bolted Benchmark Structure.
Abstract not provided.
Benchmarking VQE for the square-octagon-lattice Kitaev model [Slides\
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DECOVALEX 2023 TASK G: Step1 Benchmark Exercise: G1-M-BE-2D SNL Modeling Progress.
Abstract not provided.
Challenge Problem 1: Benchmark Specifications for the Direct Numerical Simulation of Canonical Flows
In this report detailed specifications for the canonical problems to study the heat transfer in different coolants, geometries and conditions are presented. The scope has been chosen with industry input and will address the outstanding challenges in predictive capabilities of coolant flows in advanced reactor-relevant conditions.
Benchmarking consistent observable and material properties from an average-atom model to predictions from TDDFT.
Abstract not provided.
Benchmark Comparison of HyRAM and ALDEA Software for Hydrogen Release Behavior
There are several different calculation approaches and tools that can be used to evaluate the risk of hydrogen energy applications. A comparative study of Air Liquide’s ALDEA (Air Liquide Dispersion and Explosion Assessment) tools suite and Sandia’s HyRAM (Hydrogen Risk Assessment Models) toolkit has been conducted. The purpose of this study was to understand and evaluate the differences between the two calculation approaches, and identify areas for model improvements. There were several scenarios examined in this effort regarding hydrogen release dynamics. These scenarios include free jet release cases at varying pressures, vessel blowdown, and hydrogen build-up scenarios with and without ventilation. For each scenario, the input and output of the HyRAM calculations are documented, along with a comparison to the ALDEA results. Generally, the results from the two different tools were reasonably aligned. However, there were fundamental differences in evaluation methodology and functional limitations in HyRAM that caused discrepancies in some calculations.
Using pygsti for quantum processor characterization and benchmarking .
Abstract not provided.
FastML Science Benchmarks: Accelerating Scientific Edge ML [Poster]
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IER-297: TEX-HEU Baseline Assemblies Benchmark and Results [Slides]
The pending resolution of comments was accepted by the ICSBEP TRG in December 2021. Subgroup includes Catherine Percher, Dave Heinrichs, Michael Zerkle (NNL), and Jeffrey Favorite (LANL). The full resolution of comments is anticipated by March 31, 2022. Plans to execute TEX-HEU-Hf variant of experiment design are anticipated for FY22.
Cubit for MCNP Unstructured Mesh Analysis of Oktavian Benchmarks
The Monte Carlo N-Particle (MCNP) transport code developed by Los Alamos National Laboratory (LANL) can be used to transport various particles across user defined three dimensional (3D) geometries. Traditionally, these geometries are created as constructive solid geometry (CSG), involving the use of Boolean operators on defined surfaces to create 3D regions known as cells. A newer method of geometry definition in the MCNP code is unstructured mesh (UM) embedded within a CSG cell using the universe and fill repeated-structure features. An MCNP UM calculation requires an MCNP input file and mesh geometry file. The MCNP code cannot be used to generate UM geometry models. A computer-aided design (CAD) software is typically used to construct a solid geometry model, and a CAD file is then imported into a mesh generation software to prepare and generate a mesh model. Some mesh generation software packages have the ability to create a solid geometry and thus a separate CAD software for creating a CAD model is not needed. In this work, Cubit, a geometry creation and meshing software developed by Sandia National Laboratories, is used to construct UM models for MCNP simulations.
Code-to-code benchmarking of high energy beam transport in a gas cell.
Abstract not provided.
Benchmark Comparisons of Monte Carlo Algorithms for One-Dimensional N-ary Stochastic Media.
Abstract not provided.
MiniMod: A Modular Miniapplication Benchmarking Framework for HPC .
Abstract not provided.
Open-source Tools for Solving Grid Optimization Problems: ARPA-e Benchmark Algorithm Overview [Slides]
This document contains the official formulation that will be used for evaluation in Challenge 2 of the Grid Optimization (GO) Competition. Minor changes may occur within the formulation. Entrants will be notified when a new version is released. Changes are not expected to be of a significance that would cause a change in approach for the Entrants. This formulation builds upon the Challenge 1 formulation published in ARPA-E DE-FOA-0001952. Entrants will be judged based on the current official Challenge 2 formulation posted on the GO Competition website (this document, which is subject to change), not the formulation posted in DE-FOA-0001952. Entrants are permitted and encouraged to use any alternative problem formulation and modeling convention within their own software (such as convex relaxation, decoupled power flow formulations, current-voltage formulations, etc.) in an attempt to produce an exact or approximate solution to this particular mathematical program. However, the judging of all submitted approaches must conform to the official formulation presented here.