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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 OSTI2021

Verification and Validation of Systems in which AI is a Key Element

Many systems are being considered in which artificial intelligence (AI) will be a key element. Failure of an AI element can lead to system failure, hence the need for AI verification and validation (V&V). This article addresses V&V of such a system, focusing on the issues created by characteristics of AI that make V&V challenging. The element(s) containing AI capabilities is treated as a subsystem and V&V is conducted on that subsystem and its interfaces with other elements of the system under study, just as V&V would be conducted on other subsystems. That is, the high-level definitions of verification and of validation do not change for systems containing one or more AI elements. However, AI V&V challenges require approaches and solutions beyond those for conventional or traditional (those without AI elements) systems. This article provides an overview of how machine learning components/subsystems “fit” in the systems engineering framework (Section 1), identifies characteristics of AI subsystems that create challenges in their V&V (Section 2), describes those challenges (Section 3) and provides some potential solutions (Section 4).

Pullum, Laura↗
DOE OSTI2021

Dark Energy Survey Year 3 Results: Multi-Probe Modeling Strategy and Validation

This paper details the modeling pipeline and validates the baseline analysis choices of the DES Year 3 joint analysis of galaxy clustering and weak lensing (a so-called "3$\times$2pt" analysis). These analysis choices include the specific combination of cosmological probes, priors on cosmological and systematics parameters, model parameterizations for systematic effects and related approximations, and angular scales where the model assumptions are validated. We run a large number of simulated likelihood analyses using synthetic data vectors to test the robustness of our baseline analysis. We demonstrate that the DES Year 3 modeling pipeline, including the calibrated scale cuts, is sufficiently accurate relative to the constraining power of the DES Year 3 analyses. Our systematics mitigation strategy accounts for astrophysical systematics, such as galaxy bias, intrinsic alignments, source and lens magnification, baryonic effects, and source clustering, as well as for uncertainties in modeling the matter power spectrum, reduced shear, and estimator effects. We further demonstrate excellent agreement between two independently-developed modeling pipelines, and thus rule out any residual uncertainties due to the numerical implementation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Verdant Power: Thermoplastic Blade Validation at Full Scale

For the first time in history, thermoplastic composite blades, which have the potential to revolutionize the marine energy industry, are being validated on a large-scale tidal power turbine. Thanks to funding from the U.S. Department of Energy's Water Power Technologies Office and a collaboration with Verdant Power, NREL researchers constructed thermoplastic composite turbine blades and are validating their performance on one of Verdant Power's tidal turbines deployed in New York City's East River.

HYDRO ENERGY↗
DOE OSTI2022

Prototype HB650 Transportation Validation For The PIP-II Project

The PIP-II Project at Fermilab is centered around a superconducting 800 MeV proton linac to upgrade and modernize the Fermilab accelerator complex, allowing increased beam current to intensity frontier experiments such as LBNF-DUNE. PIP-II includes strong international collaborations, including the delivery of 12 cryomodules from European labs to FNAL (3 from STFC-UKRI in the UK and 9 from CEA in France). The transatlantic shipment of these completed modules is identifed as a serious risk for the project. To mitigate this risk, a rigorous and systematic process has been developed to design and validate a transport system, including specifcation, procedures, logistics, and realistic testing. This paper will detail the engineering process used to manage this effort across the collaboration and the results of the first major validation testing of the integrated shipping system prior to use with a cryomodule.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Uniformly Ordered Binary Decision Algorithm for Benchmark Experiment Correlations in Whisper Validation

When performing a validation exercise for determining the upper subcritical limit of a nuclear criticality safety application, an analyst should select and perform a statistical analysis on a population of benchmark experiments that are neutronically similar to the application. The size of this population should be sufficiently large such that the statistical analysis has a high degree of confidence that the bias plus bias uncertainty (calculational margin) has been accurately quantified. A complication arises because many benchmark experiments share common components, leading to correlations in their measured effective multiplication factors. Correlations between benchmark experiments within the population reduces its predictive power. This motivates the need for methods that consider benchmark experiment correlations and ensure adequate statistical significance of results. The Whisper code is a statistical analysis pack- age that incorporates nuclear data sensitivity coefficients from MCNP to assess benchmark experiment similarity and then performs an extreme-value analysis to estimate the bias plus bias uncertainty. The original methodology in Whisper does not consider the effect of benchmark experiment correlations when making this estimation, and this summary proposes the uniformly ordered binary decision algorithm to address this shortcoming. The original methodology in Whisper computes similarity coefficients ck for an application compared to all benchmark experiments in its library and develops weighting factors for a selected population proportional to the ck values. The methodology can be interpreted as statistically emulating a validation exercise for a particular application where the weighting factors may be viewed as the likelihood that an analyst would include a particular benchmark experiment within the population. The effective sample size of the population is the expected or mean number of benchmark experiments in the population. The uniformly ordered binary decision algorithm identifies clusters of correlated benchmark experiments within the population and then computes adjusted weighting factors based on the magnitude of the correlation coefficients within the cluster to compute a reduced effective sample size accounting for the lower information content because of correlations. Benchmark experiments within the cluster are ordered randomly with equal probability and probabilistic decisions are made as to whether a benchmark. experiment within the cluster should treated as redundant with a previous one; if two redundant benchmark experiments are included, then the conservative worst case bias plus bias uncertainty is used and the pair is counted as a single benchmark experiment in the population. Results are provided for HEU solutions in a research version of the Whisper software using benchmark experiment correlations provided by DICE, the Database for the International Criticality Safety Benchmark Evaluation Project (ICSBEP). These show that there can be a significant increase in the bias plus bias uncertainty because the effective sample size is reduced, and therefore the algorithm, needing to meet sample size requirements, expands the benchmark experiment population by accepting less similar benchmark experiments that would have otherwise not been included.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

BISON Capability, Validation and Demonstration for Reactivity-Initiated Accidents

Reactivity Initiated Accidents (RIA) are design basis accidents that could have adverse impacts on the core coolability. In the unlikely event that sufficient reactivity is inserted into the reactor core by the ejected/dropped control rod, prompt energy deposition into the fuel can occur, which when sufficiently high can lead to fuel rod failure or, at large energy deposition levels, expulsion of UO2 fragments or molten UO2 material from the fuel rod. This results in a release of fission product and fuel into the coolant and has the potential to compromise core coolability and threatening the pressure boundary of the primary coolant system. The design basis RIA is one of the industry challenging problems that the CASL aimed to address; the CASL RIA Challenge Problem Charter [1] states, ?The Pressurized Water Reactor (PWR) Rod Ejection Accident (REA) and Boiling Water Reactor (BWR) Control Rod Drop Accident (CRDA) are postulated accidents with consequences that are important to nuclear safety (fuel rod integrity and core coolability). Currently each reload core design must be analyzed to meet regulatory acceptance criteria. The goal of CASLs ModSim capability for RIA is to model the event at a higher fidelity, with validation to existing tests, to better model the transient neutronics and the progression of the fuel and cladding thermal-mechanical behavior. These improved analytical capabilities can be used to better inform reload core design, limits on fuel assembly discharge burnup, restrictions on placement of fuel in the reactor, control rod insertion limits, operating margin, and performance sensitivities.? In support of that charter, BISON, the fuel performance code has been used to demonstrate the simulation of thermal-mechanical behavior of LWR fuels during a reactivity-initiated accident. The combination of mechanical, thermal, and thermal-hydraulic phenomena all present during an RIA makes a multi-physics code such as BISON a valuable tool for modeling these scenarios. This paper will highlight many of the activities associated with BISON relevant to reactivity-initiated accident capability development and validation efforts. These efforts have been performed under both CASL and the Nuclear Energy Advanced Modeling and Simulation (NEAMS) programs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

The ARENA Test Bed – A Versatile Resource for I&C Development and Validation

The Accelerated and Real-time Experimental Nodal Assessment (ARENA) Test Bed at the Pacific Northwest National Laboratory (PNNL) is a versatile resource for development and validation of instrumentation and control (I&C) technologies. This capability was created to facilitate in-situ testing of nuclear electrical cables in various simulated operational environments. Using cable trays, a control box, and selected test components, low voltage cables can be staged to experience local adverse environments such as elevated temperature and water immersion. Cable condition can be continuously monitored over time to track the effect of local stresses using nondestructive assessment tools. A heads-up display (ARENA TV) plots key data in real-time for users. The ARENA Test Bed has recently been used to evaluate the potential for spread spectrum time domain reflectometry (SSTDR) to monitor thermal aging of a portion of live cable powering a three-phase motor. The arrangement provided the opportunity to directly compare the performance of the novel online SSTDR method with offline results from the more standard frequency domain reflectometry (FDR) method. The ability of SSTDR and FDR to identify the presence of water in immersed shielded and unshielded cables and to detect ground faults was also assessed. A digital twin is being developed to track and predict FDR signals from a thermally aging conceptual cable region to compare with measured signals from the ARENA physical counterpart. The test bed concept addresses an important need in nuclear I&C monitoring tool development. New tools and techniques can be developed in the test bed and validated versus known methods and physical measurements. Digital twins and machine learning engines can be populated with measured data in a controlled environment that would not be readily available in the actual nuclear power plant. Proposed monitoring strategies can be confirmed for effectiveness through objective evaluation. It is anticipated that the PNNL ARENA Test Bed will be a valuable resource in advancing nuclear plant instrumentation.

nuclear electrical cables, ARENA Test Bed, conditi↗
DOE OSTI2023

HTGR Validation: NEUP Survey and Database Database Development for HTGR Thermal-Fluid Experiments

This set of slides is aimed to improve access to the High-Temperature Gas-cooled Reactor (HTGR) validation data and optimize the return on the significant investment made by DOE. Supported by the Advanced Reactor Technologies (ART) Gas-Cooled Reactor (GCR) program. Slides include information from FY2009 to FY2023, there are in total 35 DOE NEUP projects focusing on the thermal-fluid experiments related with High-Temperature Gas-cooled Reactor (HTGR), producing a large amount of high-quality validation data. NEUP Survey and Database Development for HTGR Thermal-Fluid Experiments is distributed at universities and has not been disseminated to the HTGR community. More collaborating with university PIs and refining the HTGR phenomena summary chart continuously is expected in the future.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

The international research reactor conversion effort and its contribution to the validation of reactor physics and thermal-hydraulics codes

Full text of publication follows. With about 200 reactors in operation, civilian Research and Test Reactors (RTRs) represent approximately a third of the global nuclear fleet. RTRs make use of core designs that are drastically different from commercial power plants to perform a wide variety of non-power applications that greatly benefit society. Because they often rely on high neutron fluxes, RTRs are designed with relatively compact cores and as a result, prior to the 1980's, were often deployed using Highly Enriched Uranium fuel (HEU, {sup 235}U/U = 20 wt. %). Due to proliferation concerns, the international community aims at eliminating the use of HEU in civilian facilities and favor instead the use of Low Enriched Uranium fuel (LEU, {sup 235}U/U < 20 wt. %). A program to support conversion of the world's RTRs to LEU fuel has been initiated in 1978 by the U.S. Department of Energy (DOE). This program is still alive today and has achieved more than 103 conversion metrics. Today, the program focuses heavily on the conversion of so-called high-performance RTRs, which are far more challenging than previous conversions as they require new fuel element designs and the use of new, higher density LEU fuel forms. Development and qualification of new LEU fuel elements is ongoing and requires extensive engineering analysis and testing. Both activities require the development and validation of codes and methods for reactor physics, thermal-hydraulics, and multi-physics, which in turn rely on experiments performed in RTRs or other experimental facilities. This talk will present the collection of RTR experimental data and benchmark analyses from the international conversion program that contribute to the validation of computer codes and methods.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

High Efficacy Validation of Hydride Mega Tanks at ARIES Lab (HEVHY METAL)

The High Efficacy Validation of Hydride Mega Tanks at ARIES Lab (HEVHY METAL) project will advance materials-based hydrogen storage technologies by large-scale demonstration and identification of deployment pathways. This includes demonstrating how two metal hydride HY2MEGA subsystems are installed with megawatt-scale green hydrogen infrastructure; validating its performance via rates, capacities, and efficiencies; and investigating supply and demand side techno-economics.

ARIES↗
DOE OSTI2024

Development and Validation of a Scoring System for Abnormalities in the Gopher Frog (Rana capito)

Headstarting efforts are thought to be critical in supplementing populations of the at-risk Gopher Frog (Rana capito); however, recent efforts have occasionally resulted in juveniles with developmental abnormalities. In response, we developed a scoring system to collect quantitative data on the presence and severity of these developmental abnormalities. Our objective was to describe and validate the abnormality scoring system so that it can be used by all Gopher Frog headstarting facilities. The scoring system covers five primary conditions encompassing commonly observed abnormalities. Two groups of participants with different levels of prior experience working with Gopher Frogs assigned scores to a set of images presented to them for each condition. We used intra-class correlation coefficients (ICC) to test the scoring system for inter- and intra-rater agreement as well as agreement with the benchmark standard (established by the authors). We found high ICC values for inter-rater agreement, intra-rater agreement, and agreement to the benchmark standard indicating either excellent or good reliability for all five conditions and for all raters when grouped together. These findings support the reliability and validity of the proposed developmental abnormality scoring system. Gopher Frog headstarting facilities can implement this scoring system to assist in tracking the frequency and severity of abnormalities observed in future headstarting efforts. We hope that by creating a reliable scoring system for Gopher Frogs, it can provide an overall framework and serve as a valuable resource to evaluate abnormalities across any amphibian species.

abnormality↗
DOE OSTI2024

Development and Validation of a Probabilistic Risk Assessment Model for a Generic Modular High Temperature Gas-Cooled Reactor

This study looks to develop and validate a probabilistic risk assessment (PRA) model for the modular high temperature gas-cooled reactor (MHTGR) using INL’s Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE) software. Validation against a General Atomics design involves matching event and fault trees to historical frequencies, with a goal of under 15% difference. The research aims to deliver a reliable PRA model to assess the safety of MHTGRs for use within high-temperature industrial applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Validation and Calibration of Energy Models with Real Vehicle Data from Chassis Dynamometer Experiments

Accurate estimation of vehicle fuel consumption typically requires detailed modeling of complex internal powertrain dynamics, often resulting in computationally intensive simulations. However, many transportation applications-such as traffic flow modeling, optimization, and control-require simplified models that are fast, interpretable, and easy to implement, while still maintaining fidelity to physical energy behavior. This work builds upon a recently developed model reduction pipeline that derives physics-like energy models from high-fidelity Autonomie vehicle simulations. These reduced models preserve essential vehicle dynamics, enabling realistic fuel consumption estimation with minimal computational overhead. While the reduced models have demonstrated strong agreement with their Autonomie counterparts, previous validation efforts have been confined to simulation environments. This study extends the validation by comparing the reduced energy model's outputs against real-world vehicle data. Focusing on the MidSUV category, we tune the baseline Autonomie model to closely replicate the characteristics of a Toyota RAV4. We then assess the accuracy of the resulting reduced model in estimating fuel consumption under actual drive conditions. Our findings suggest that, when the reference Autonomie model is properly calibrated, the simplified model produced by the reduction pipeline can provide reliable, semi-principled fuel rate estimates suitable for large-scale transportation applications.

42 ENGINEERING↗
DOE OSTI2025

Validation of the DESI-DR1 3x2-pt analysis: scale cut and shear ratio tests

Combined survey analyses of galaxy clustering and weak gravitational lensing (3x2-pt studies) will allow new and accurate tests of the standard cosmological model. However, careful validation is necessary to ensure that these cosmological constraints are not biased by uncertainties associated with the modelling of astrophysical or systematic effects. In this study we validate the combined 3x2-pt analysis of the Dark Energy Spectroscopic Instrument Data Release 1 (DESI-DR1) spectroscopic galaxy clustering and overlapping weak lensing datasets from the Kilo-Degree Survey (KiDS), the Dark Energy Survey (DES), and the Hyper-Suprime-Cam Survey (HSC). By propagating the modelling uncertainties associated with the non-linear matter power spectrum, non-linear galaxy bias and baryon feedback, we design scale cuts to ensure that measurements of the matter density and the amplitude of the matter power spectrum are biased by less than 30% of the statistical error. We also test the internal consistency of the data and weak lensing systematics by performing new measurements of the lensing shear ratio. We demonstrate that the DESI-DR1 shear ratios can be successfully fit by the same model used to describe cosmic shear correlations, and analyse the additional information that can be extracted about the source redshift distributions and intrinsic alignment parameters. This study serves as crucial preparation for the upcoming cosmological parameter analysis of these datasets.

Emas, N. [Swinburne U., Ctr. Astrophys. Supercompu↗
DOE OSTI2026

V1G Frequency Regulation: Algorithm Development, Validation & Analysis at Scale

Researchers at Argonne National Laboratory developed and validated a high-fidelity digital twin of a smart charging (V1G) ecosystem to model the participation of up to 1,000 unique electric vehicles (EVs) in the PJM frequency regulation market. Utilizing a discrete-event framework, the simulation models complex interactions, from dynamic grid signals (updated every 2 seconds) to individual EV charging dynamics. The simulation incorporates multiple EV models created from real-world lab test data. Researchers tested multiple control algorithms to balance the dual objectives of maximizing aggregator’s revenue and driver charging needs. Results demonstrate that aggregated EVs function as a controllable, highly effective grid resource, achieving high PJM Performance Scores (80–90%). Additionally, an optimized, market-aware bidding strategy was identified as key to profitability. The platform was shown to provide drivers with an average charging discount of nearly 50%. The algorithm was further validated in the lab using production EVs and charging stations to compare simulation results with real-world performance.

Manne, Nithin↗
DOE OSTI2025

Development and Validation of MALAMUTE model for Electric Field Assisted Sintering of Structural Materials

Fusion power plant designs feature extreme material performance requirements for structural material candidates. In addition to conventional alloys, more advanced composites and oxide dispersion strengthened (ODS) alloys are being explored, however, achieving the desired microstructures to maximize performance using traditional manufacturing methods can be challenging. The advanced manufacturing (AM) electric field-assisted sintering (EFAS) technique offers improved control over the final microstructure through higher heating and cooling rates and moderate pressures. Modeling and simulation tools show promise in elucidating the process-structure-property-performance (PSPP) correlation for AM-produced parts, including the EFAS process. An inherently multiscale process, the EFAS technique aligns well with the multiscale modeling capability of the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE)[cite]. We present here an electro-thermo-mechanical approach to modeling the EFAS process using the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) code. Prediction of the field and gradient distributions across the EFAS tooling is required to accurately describe the conditions for the lower-scale microstructural evolution models. In this work we present the MALAMUTE model developed to predict the electrical potential, temperature, and mechanical stress distribution across the EFAS graphite tooling and part at the larger engineering-scale. Validation of the MALAMUTE engineering-scale model is completed using data from experimental densification and pre-densified runs of iron powder via EFAS at 1000oC. These runs were conducted using a Thermal Technology DCS-5 EFAS system. Data collected during the experiment runs include the direct current (DC) supplied to the graphite tooling, the temperature of the graphite tooling as measured with a pyrometer, and the force applied to the top of the graphite tooling stack, and the data were recorded every 10 seconds. Our validation approach used the current and force data from the EFAS run as boundary condition inputs to the MAMALUTE simulation; the temperature data were used to evaluate the MALAMUTE EFAS model prediction. Results of the MALAMUTE simulations are employed to connect the external pyrometer temperature measurement to the temperature profile across the part undergoing consolidation. We investigate the impact of material property variation and mesh deformation on the temperature profile as predicted by MALAMUTE. We conclude by highlighting projects where the MALAMUTE EFAS modeling and simulation capabilities will be used to assist experimental design.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Air-Cooled RCCS CFD Modeling Validation 2025

Slide deck for the Advanced Reactor Technologies Gas Cooled Reactor (ART-GCR) program review. The slides show the progress on the air-cooled reactor cavity cooling system (RCCS) CFD validation work. The validation of the air-cooled RCCS is performed using the experimental facility at the University of Wisconsin-Madison. The slide deck provides a progress update on this year's achievements. The natural convection tests under uniform power are modeled and compared with the experimental results. The results show good agreement with the experimental results. A sensitivity study on the RANS turbulence models is performed. Additionally, the contribution of radiative and convective heat transfer within the heated cavity is calculated and compared to forced convection setups.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

SEM Milestone Report for MARMOT Validation Project

MARMOT is a meso-scale fuel code under development by NEAMS designed to predict the microstructure evolution of fuel materials to determine updated thermal and mechanical property models. These updated models can be used by engineering scale codes such as BISON. To support its development and validation the MARMOT Validation Project (MVP) was initiated and consists of extensive microstructure and thermal characterization of U-10Zr fuel material before and at discreet levels of irradiation. This report summarizes the SEM and EDS characterization of the lowest burnup samples (1.5% FIMA) and how they compare to pre-irradiation SEM and EDS.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗