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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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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Can We Model Forest Demography Globally? Benchmarking of State-of-the-Art Demographic DGVMs

Forests in Dynamic Global Vegetation Models (DGVMs) have historically been simulated as area-averaged plant functional types in each gridcell instead of representing communities of trees of different sizes and ages (demography). Just as the behaviour of a tree differs according to its ontogeny, so the behaviour of forests is known to differ depending on their demography. Accurately simulating demography is therefore key in order to address questions on afforestation and management strategies, as well as assessments of resilience of forests to disturbances such as drought and fire or diversity changes after a disturbance. Ultimately, demography determines the overall forest biomass in natural forests and is a key arbiter of growth and mortality rates. DGVMs are now able to simulate size and age structure of the trees in forests. However, these models have so far not been benchmarked alongside each other. We evaluate 6 DGVMs (BiomeE, CABLE-POP, FATES, LPJ-GUESS, JULES-RED, ORCHIDEE) against observations on regrowth dynamics as well as natural forests at boreal, temperate and tropical sites. We examine whether the models capture observed regrowth dynamics after disturbance, well-known stand size structure and well-established processes such as self-thinning. We outline the planned route forward towards a standardised international benchmarking framework for demographic DGVMs.

Dynamic Global Vegetation Models↗
NASA NTRS2024

Benchmarking GOCART-2G in the Goddard Earth Observing System (GEOS)

The Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, which controls the sources sinks and chemistry within the Goddard Earth Observing System, recently underwent a major refactoring and update to the representation of physical processes. This paper serves to document code changes that were included in GOCART 2nd Generation (GOCART-2G) and establishes a benchmark simulation that is to be used for future development of the system. The code refactoring increases flexibility such multiple instances of an aerosol species can be run and interact with radiation and cloud microphysics, in addition to the output of multiple wavelength aerosol optical properties in support of data assimilation. From a science perspective, a new radiatively active tracer, brown carbon, was added to distinguish smoke from other sources of organic aerosol thereby improving optical properties entering the radiative calculations. A four-year benchmark simulation was evaluated using in situ and space borne measurements to develop a baseline and prioritize future development. A comparison of simulated aerosol optical depth between GOCART-2G and MODIS retrievals indicates the model captures the overall spatial pattern and seasonal cycle of aerosol optical depth but overestimates aerosol extinction over dusty regions and underestimates aerosol extinction over northern hemisphere boreal forests, requiring further tuning of emissions. This MODIS-based analysis is corroborated by comparisons to MISR and selected AERONET stations. Despite the underestimate of aerosol optical depth in biomass burning regions in GEOS, there is an overestimate in the surface mass of organic carbon in the United States, especially during the summer months.

Allison B Collow↗
NASA NTRS2024

NASA Space Observatory Precision Pointing Benchmark Problem Development

An interagency workshop in May 2021 on guidance, navigation, and control (GNC) verification and validation (V&V) methods and techniques identified needs for the formulation and public release of relevant V&V benchmark problems as a practical way forward for the discipline. A decision was made by the NASA Technical Fellow for GNC and the NASA Engineering and Safety Center (NESC) GNC Technical Discipline Team (TDT) to produce a benchmark problem focusing on the problem of space observatory precision pointing. This report contains the results of the NESC assessment.

NASA Engineering and Safety Center↗
DOE OSTI2017

Semi-Analytical Benchmarks for MCNP6 [Slides]

This presentation begins with an Introduction and some background on semi-analytical benchmarks for MCNP6. Discussion topics include: verification & validation, MCNP history of V&V, semi-analytic benchmarks, numerical Results, comparison of semi-analytic to MCNP, and tips for proper comparison. This presentation ends with conclusions & future Work.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Demonstration of MAMMOTH Strongly-Coupled Multiphysics Simulation with the Godiva Benchmark Problem

This paper provides a detailed description of the Godiva benchmark problem suitable for multiphysics code verification. Multigroup transport weak forms for general curvilinear coordinates are derived using SAAF (self-adjoint angular flux) formulation. A new scheme based on spherical harmonics expansion for evaluating the angular derivative terms using the SN method are presented and tested. A one-dimensional spherical coordinate system is used by MAMMOTH for modeling the Godiva benchmark. Strongly-coupled multiphysics simulation mode of MAMMOTH is exercised and numerical results are given.

97 MATHEMATICS AND COMPUTING↗
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 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↗
DOE OSTI2017

MC21/CTF and VERA-CS Mutiphysics Solutions to VERA Core Physics Benchmark Problems 6 and 7

The continuous energy Monte Carlo neutron transport code, MC21, was coupled to the CTF subchannel thermal-hydraulics code using a combination of CASL tools and in-house Python scripts. An MC21/CTF solution for VERA Core Physics Benchmark Progression Problem 6 demonstrated excellent agreement with MC21/COBRA-IE and VERA solutions. The MC21/CTF solution for VERA Core Physics Benchmark Progression Problem 7, Watts Bar Unit 1 at beginning of cycle (BOC) hot full power (HFP) equilibrium xenon conditions, is the first published coupled Monte Carlo neutronics / subchannel T-H solution for this problem. MC21/CTF predicted a critical boron concentration of 854.5 ppm, yielding a critical eigenvalue of 0.99994 ± 6.8E-6 (95% CI). Excellent agreement with a VERA solution of Problem 7 was also demonstrated for integral and local power and temperature parameters.

Aviles, Brian↗
DOE OSTI2017

U-10Mo Conversion Burnup Benchmarking Activities for Full-Size LEU Fuel Plates

Validation benchmark experiments for low-enriched uranium (LEU) U-Mo fuel systems are currently being developed from existing experiments irradiated in the Advanced Test Reactor. (ATR) and ATR Critical Facility (ATRC). The experiments chosen include the ATR Full size plate In center Flux trap Position (AFIP-7) experiment and the Ki-Jang Research Reactor Lead Test Assembly (KJRR-LTA) located in the Northeast Flux Trap. Each experiment was modeled using a high-fidelity three-dimensional Monte Carlo code with depletion capabilities. A description of the validation experiments will be provided as well as comparison to post irradiation examination results for the AFIP-7 experiment. The PIE results for the AFIP-7 experiment have demonstrated good agreement with analytical models. Due to the complex nature in of the ATR, modeling simplifications to support benchmark activities using lower fidelity reactor physics software. A discussion of the analytical bias associated with modeling simplifications will also be provided.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Land Model Testbed: Accelerating Development, Benchmarking and Analysis of Land Surface Models

A Land Model Testbed (LMT), designed to provide a computational framework for systematically assessing model fidelity and supporting rapid development of complex multiscale models, offers a general-purpose workflow for conducting large ensemble simulations of multiple land surface models, post-processing large volumes of model output, and evaluating model results. It leverages existing tools for launching model simulations and the International Land Model Benchmarking (ILAMB) package for assessing model fidelity through comparison with best-available observational datasets. Increased complexity and proliferation of uncertain parameters in process representations in land surface models has driven the need for frequent and intensive testing and evaluating of models to quantify uncertainties and optimize parameters such that results are consistent with observations. The LMT described here meets these needs by providing tools to run thousands of ensemble simulations simultaneously and post-process their output files, by automating execution of an enhanced version of ILAMB with site-specific benchmarks and multivariate functional relationships, and by offering ensemble diagnostics and a customizable dashboard for displaying model performance metrics and associated graphics. We envision the LMT capabilities will serve as a foundational computational resource for a proposed user facility focused on terrestrial multiscale model--data integration.

Sreepathi, Sarat↗
DOE OSTI2021

Transparent Object Tracking Benchmark

Visual tracking has achieved considerable progress in recent years. However, current research in the field mainly focuses on tracking of opaque objects, while little attention is paid to transparent object tracking. In this paper, we make the first attempt in exploring this problem by proposing a Transparent Object Tracking Benchmark (TOTB). Specifically, TOTB consists of 225 videos (86K frames) from 15 diverse transparent object categories. Each sequence is manually labeled with axis-aligned bounding boxes. To the best of our knowledge, TOTB is the first benchmark dedicated to transparent object tracking. In order to understand how existing trackers perform and to provide comparison for future research on TOTB, we extensively evaluate 25 state-of-the-art tracking algorithms. The evaluation results exhibit that more efforts are needed to improve transparent object tracking. Besides, we observe some nontrivial findings from the evaluation that are discrepant with some common beliefs in opaque object tracking. For example, we find that deeper features are not always good for improvements. Moreover, to encourage future research, we introduce a novel tracker, named TransATOM, which leverages transparency features for tracking and surpasses all 25 evaluated approaches by a large margin. By releasing TOTB, we expect to facilitate future research and application of transparent object tracking in both the academia and industry.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Towards a Benchmark Experiment with the Compact Nuclear Power Source

The Compact Nuclear Power Source (CNPS) was a high-assay low enriched uranium (HALEU) tristructural isotropic (TRISO)-fueled, graphite-moderated microreactor constructed in 1987 at Los Alamos National Laboratory. The reactor, conceived as a power source for short-range radar stations, was designed to be "walk-away safe," and was cooled by heat pipes and ambient air. Though the project was formally cancelled after the fuel and moderator material had been received, its potential to meaningfully advance the body of critical and integral data was evident, and critical experiments with a mock-up of the reactor proceeded at TA-18 until its disassembly in 1991. The reflector and some components of the core would later go on to see service as part of the New Production Reactor Modular High-Temperature Gas-Cooled Reactor (NP-MHTGR) critical experiments. In light of the progress made by groups like Westinghouse and X-Energy towards contemporary graphite-moderated microreactors, the system remains an attractive candidate for the basis of a benchmark experiment even today. Uncertainties remain, however, in some features of the system–inconsistencies in the dimensions and composition of the reactor’s components as described in literature and implemented in current computational models. The identification, quantification, and to the extent possible, the minimization of these uncertainties is a crucial task on the path towards creating a benchmark based on the CNPS system. The present work seeks to initiate this process with a survey of available documentation and improvements to the accuracy of CNPS neutronics models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Wind Turbine Noise Code Benchmark: A Comparison and Verification Exercise: Preprint

In a number of institutions and companies, researchers and engineers are developing modeling numerical frameworks that are used to predict the aerodynamic noise emission from a wind turbine rotor. The simulation codes vary from empirically-tuned engineering models to high-fidelity computational ones. Their common feature is the fact that they all specifically model the main aerodynamic noise mechanisms occurring at the rotating blades, namely trailing edge noise and turbulent inflow noise. Nevertheless, it can be expected that these different modeling frameworks will produce different results for a same given rotor design, and identical operating conditions. Trailing edge noise is put at the forefront of the study as it is recognized as the main audible source of noise from wind turbines. The present benchmark aims at comparing the results from the different modeling approaches, and drawing some conclusions from these comparisons. This effort, denoted as Wind Turbine Noise Code benchmark, was initiated in 2019 as a joint-activity between the IEA Wind Task 39 (Quiet Wind Turbine Technology) and Task 29 (Detailed Aerodynamics of Wind Turbines, now Task 47). In addition to the investigation of the noise emissions themselves, the rotor aerodynamic characteristics are investigated as they have a significant impact on the noise generation mechanisms. A number of test cases are defined and the aerodynamic and aeroacoustic predictions from the various models are compared. There exist some discrepancies between the different methods, but it is difficult to conclude if one methodology is better than another in order to design a wind turbine with noise as a constraint.

aeroacoustics↗
DOE OSTI2016

OECD RIA Benchmark Phase II - Towards a better understanding of the RIA fuel modelling

This paper deals with the second phase of the RIA (reactivity initiated accident) fuel rod code benchmark for water-cooled reactors that began in 2014. This second phase has been organized around 2 complementary activities: the first activity is to compare the results of different simulations on simplified cases in order to provide additional bases for understanding the differences in modelling of the concerned phenomena, while the second activity is focused on the assessment of the uncertainty of the results. The detailed specification and comparison of the results from the first activity is presented in this paper. Based on the Phase-I and Phase-II conclusions, some generic recommendations can be made. First, fuel and clad thermomechanical models (with the associated material properties) should be further improved and validated more extensively against a sound RIA database. Secondly, build-up of a comprehensive and robust database consisting of both separate-effect tests and integral tests should be pursued in the short term to reinforce the basis for assessment of both individual model and model integration into codes. Thirdly, an assessment of the uncertainty of fuel thermo-mechanics is of high interest (which is consistent with the second activity of this RIA benchmark Phase-II). Finally, as RIA fuel codes are more and more likely to be used for reactor accident studies, particularly for those involving safety analyses, the fuel rod failure criteria (generally used in such analyses) will have to be carefully justified and validated. The current RIA fuel failure criteria are mainly based on the fuel thermal variables and the verification is based on 'conservative' assumptions for the heat transfer conditions. As all codes give rather consistent evaluations of such variables, it appears possible, taking into account adequate provisions, to derive criteria based on thermal variables from experimental values or from an analytical approach. However, if in the future more mechanistic modelling is ever to be used to establish fuel-failure criteria based on mechanical variables, weaknesses in the validation of the codes identified above will have to be accounted for.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Investigation of the Impact of TSL Data Libraries and Geometry Variations on the MSRE Benchmark

The increasing demand for green, low-carbon energy solutions has amplified the focus on advanced nuclear reactor technologies. Among these, Molten Salt Reactors (MSRs) have been spotlighted because of their special features. Historically, Oak Ridge National Laboratory (ORNL) started the Molten Salt Reactor Experiment (MSRE) in 1956. Later, ORNL and the University of California, Berkeley (UCB) jointly developed the MSRE benchmark. This was then reviewed by the International Reactor Physics Experiment Evaluation Project (IRPhEP) committee and added to their 2019 handbook. In the current study, the benchmark model was recreated via the Serpent code. The calculated effective multiplication factor was 1.02087 ± 0.00019, which gives a deviation of about 2000 pcm compared to the benchmark/experimental result. At North Carolina State University (NCSU), recent evaluations were conducted on thermal scattering cross sections for molten salt FLiBe and 20% porous nuclear graphite, anticipated for incorporation in the ENDF/B-VIII.1 library. The influences of these thermal scattering law (TSL) data and geometry changes on the multiplication factor were examined using the ENDF/B-VII.1 and ENDF/B-VIII.0 libraries. Introducing the TSL data for FLiBe and 20% porous graphite resulted in an effective multiplication factor of +270 pcm compared to the reference value obtained with ENDF/B-VII.1 in this study. The adjustment of the reactor vessel dimensions resulted in decrease of -448 pcm in the calculated effective multiplication factor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Status of the CERBERUS Evaluation for the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook

Modeling & Simulation (M&S) tools are used to analyze advanced reactor designs and the safety of current nuclear operations. As computers continue to improve, we are able to enhance resolution in our calculations. Therefore, the limitations of simulation capability are in the quality of data that is being used, including our ability to quantify the uncertainty and sensitivity of that data. In order to model systems of interest with increasing accuracy, the industry must improve key nuclear data measurements. 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. These experiments, along with differential measurements, can help improve the quality of nuclear data. Concerns regarding the accuracy of Cu nuclear data have been published. The large values and trend of C-E for the Zeus intermediate energy benchmark, being one of the primary examples. Furthermore, very few experiments have been designed to be sensitive to Cu (as shown in Figure 1), so an integral, critical experiment is needed to help resolve these differences.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

NEA HTTR LOFC Project Test#3 Benchmark Results

In the second half of FY23, the High Temperature Engineering Test Reactor (HTTR) Loss Of Forced Cooling (LOFC)#3 data for the 9 MW test case with Vessel Cooling System (VCS) off were made available through the Nuclear Energy Agency (NEA) LOFC project framework; the neutronic model developed for the initial test (LOFC#1) achieved a satisfactory level of maturity, demonstrating its accuracy in predicting power evolution and core re-criticality, but LOFC#3 should be used primarily to investigate thermal hydraulic phenomena, as the reactor was shut down prematurely due to overheating in the upper reactor components, which prevented re-criticality; this report focuses on advancing the HTTR thermal hydraulic model to accurately simulate the LOFC#3 scenario, including simulating the LOFC#3 benchmark and generating the corresponding benchmark specifications, aiming to ensure consistency across participant models and provide essential data for future participants, including private industry stakeholders seeking to validate their computational tools.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

LC-Opt: Benchmarking Reinforcement Learning and Agentic AI for End-to-End Liquid Cooling Optimization in Data Centers

Liquid cooling is critical for thermal management in high-density data centers with the rising AI workloads. However, machine learning-based controllers are essential to unlock greater energy efficiency and reliability, promoting sustainability. We present LC-Opt, a Sustainable Liquid Cooling (LC) benchmark environment, for reinforcement learning (RL) control strategies in energy-efficient liquid cooling of high-performance computing (HPC) systems. Built on the baseline of a high-fidelity digital twin of Oak Ridge National Lab's Frontier Supercomputer cooling system, LC-Opt provides detailed Modelica-based end-to-end models spanning site-level cooling towers to data center cabinets and server blade groups. RL agents optimize critical thermal controls like liquid supply temperature, flow rate, and granular valve actuation at the IT cabinet level, as well as cooling tower (CT) setpoints through a Gymnasium interface, with dynamic changes in workloads. This environment creates a multi-objective real-time optimization challenge balancing local thermal regulation and global energy efficiency, and also supports additional components like a heat recovery unit (HRU). We benchmark centralized and decentralized multi-agent RL approaches, demonstrate policy distillation into decision and regression trees for interpretable control, and explore LLM-based methods that explain control actions in natural language through an agentic mesh architecture designed to foster user trust and simplify system management. LC-Opt democratizes access to detailed, customizable liquid cooling models, enabling the ML community, operators, and vendors to develop sustainable data center liquid cooling control solutions.

Naug, Avisek [Hewlett Packard Enterprise]↗