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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 1,297 records · Page 72

Identifying rolling resistance and air resistance simultaneously for an electric truck

Accurately estimating rolling and air resistance is essential for predicting the energy consumption of vehicles. This study presents a field-based approach using a rolldown test to simultaneously determine rolling and air resistance coefficients. Unlike prior methods that frequently used simulations or models, we employ a goal programming methodology to improve precision and evaluate the actual vehicle and environmental conditions. Our methodology was tested using a Class 8 Freightliner eCascadia on a surveyed road section, ensuring controlled conditions for data collection. By analyzing the time–velocity relationship across multiple test runs, we derived resistance coefficients for both loaded and unloaded conditions. The study confirms that rolling resistance is largely independent of velocity at low speeds but exhibits a nonlinear dependency at higher speeds. Additionally, road surface conditions, tire condition, axle configuration, aerodynamic properties, and weather conditions significantly impact resistance values, emphasizing the need for real-world testing rather than relying solely on standardized projections. Our results align with existing literature while demonstrating the efficacy of the goal programming approach in refining resistance estimates. This work contributes to improved vehicle energy modeling, offering practical insights for fleet operators and policymakers seeking accurate energy consumption predictions for electric trucks operating under varying environmental conditions.

47 OTHER INSTRUMENTATION↗

Expanding the capability of reaction-diffusion codes using pseudo traps and temperature partitioning: Applied to hydrogen uptake and release from tungsten

Simulating the implantation and thermal desorption evolution in a reaction-diffusion model requires solving a set of coupled differential equations that describe the trapping and release of atomic species in Plasma Facing Materials (PFMs). These fundamental equations are well outlined by the Tritium Migration Analysis Program (TMAP) which can model systems with no more than three active traps per atomic species. To overcome this limitation, we have developed a Pseudo Trap and Temperature Partition (PTTP) scheme allowing us to lump multiple inactive traps into one pseudo trap, simplifying the system of equations to be solved. For all temperatures, we show the trapping of atoms from solute is exactly accounted for when using a pseudo trap. However, a single effective pseudo trap energy can not well replicate the release from multiple traps, each with its own detrapping energy. However, atoms held in a high energy trap will remain trapped at relatively low temperatures, and thus there is a temperature range in which release from high energy traps is effectively inactive. By partitioning the temperature range into segments, a pseudo trap can be defined for each segment to account for multiple high energy traps that are actively trapping but are effectively not releasing atoms. With increasing temperature, as in controlled thermal desorption, the lowest energy trap is nearly emptied and can be removed from the set of coupled equations, while the next higher energy trap becomes an actively releasing trap. Each segment is thus calculated sequentially, with the last time step of a given segment solution being used as an initial input for the next segment as only the pseudo and actively releasing traps are modeled. This PTTP scheme is then applied to experimental thermal desorption data for tungsten (W) samples damaged with heavy ions, which display six distinct release peaks during thermal desorption. Without modifying the TMAP7 source code the PTTP scheme is shown to successfully model the D retention in all six traps. In conclusion, we demonstrate the full reconstruction from the plasma implantation phase through the controlled thermal desorption phase with detrapping energies near 0.9, 1.1, 1.4, 1.7, 1.9 and 2.1 eV for a W sample damaged at room temperature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The ARM Cloud Radar Simulator for Global Climate Models: Bridging Field Data and Climate Models

Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have had difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the concept of instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to improve and to facilitate the comparison of modeled clouds with observations. Many simulators have (and continue to be developed) for a variety of instruments and purposes. A community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Klein et al. 2013; Zhang et al. 2010). This article introduces a ground-based cloud radar simulator developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program for comparing climate model clouds with ARM observations from its vertically pointing 35-GHz radars. As compared to CloudSat radar observations, ARM radar measurements occur with higher temporal resolution and finer vertical resolution. This enables users to investigate more fully the detailed vertical structures within clouds, resolve thin clouds, and quantify the diurnal variability of clouds. Particularly, ARM radars are sensitive to low-level clouds, which are difficult for the CloudSat radar to detect due to surface contamination (Mace et al. 2007; Marchand et al. 2008). Therefore, the ARM ground-based cloud observations can provide important observations of clouds that complement measurements from space.

Zhang, Yuying↗

Simulation of the RPI Reactor Critical Facility Core Using High-Fidelity Neutronics Code PROTEUS

The PROTEUS code is a high-fidelity three-dimensional (3D) deterministic neutron transport code developed by ANL under the DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. The code contains the SN2ND (second order discrete ordinates method) and two MOC transport solvers, MOCFE and MOCEX (first order methods of characteristics), based on unstructured finite element meshes which allow users to model complex or unconventional geometry reactor problems. Among the two MOC solvers which normally perform better than SN for heterogeneous geometry problems, MOCEX is based on a rigorous formulation using the two-dimensional (2D) MOC radially and the discontinuous Galerkin finite element method axially to overcome the drawbacks of MOCFE with the full 3D MOC representation which requires enormous memory and computational efforts. The Reactor Critical Facility (RCF), an open tank research reactor at the Rensselaer Polytechnic Institute (RPI), became operational in 1956 under the American Locomotive company and has been operating using low-enriched uranium fuel pins, which makes it the only university research facility to use fuel rods similar to operating commercial light water reactors (LWRs). This paper presents modeling and simulation results of the RCF using PROTEUS for code verification and validation which also supports an ongoing NEUP project in which a set of benchmark validation experiments for multiphysics coupling is being developed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

VERA Integration in the NEAMS Workbench

The Virtual Environment for Reactor Applications (VERA) is a cutting edge simulation code suite used to solve complex multiphysics problems for nuclear reactors. VERA makes use of high performance computing (HPC) systems to solve large problems that were not historically tractable. While extensive work has been put into the usability of VERA, it still takes significant effort to build reactor models, ensure their correctness, properly execute the calculations, and conduct the necessary analysis of the results. This difficulty is common for many complex codes such as VERA. As part of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the NEAMS Workbench has been developed and maintained. The goal of the NEAMS Workbench is to provide a single interface with which to execute a wide variety of physics codes, from building the input models to analyzing the results. This document serves as a manual detailing the current integration of VERA with the NEAMS Workbench and a guide for configuring Workbench to allow remote execution of VERA.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A crystal plasticity model for body-centered cubic molybdenum: Experiments and simulations

Here, a physics-based finite strain crystal plasticity constitutive model for body-centered-cubic (BCC) single crystals is developed to capture the strong temperature, rate, and orientation dependence of mechanical behavior. The key features of the model include twinning-anti-twinning asymmetry of shearing resistance, a yield criterion that incorporates atomistics-informed non-Schmid effects, and a flow rule formulated based on the theory of thermally activated motion of screw dislocations via nucleation of double kinks. The implementation of the constitutive model in a finite-element program is briefly discussed. The material constants in the model are determined by calibrating the model against literature-based experimental data on single-crystal Molybdenum subjected to uniaxial compression and uniaxial tension. Experiments of uniaxial compression on a single crystal specimen with a hole were performed for validation of the calibrated model for BCC Molybdenum. Measurements of deformations in the vicinity of the hole were used to assess the ability of the model in predicting localized deformation patterns around the hole. Lastly, the model is able to effectively describe the anisotropic and temperature-dependent stress-strain response of a molybdenum crystal up to a homologous temperature of 0.3.

36 MATERIALS SCIENCE↗

Hubbard-corrected oxide formation enthalpies without adjustable parameters

A density functional theory (DFT) approach to computing transition metal oxide heat of formation without adjustable parameters is presented. Different degrees of d-electron localization in oxides are treated within the DFT+U approach with site-dependent, first-principles Hubbard U-parameters obtained from linear response theory, and delocalized states in the metallic phases are treated without Hubbard corrections. Comparison of relative stabilities of these differently treated phases is enabled by a local d-electron density matrix-dependent model, which was found by genetic programming against experimental reference formation enthalpies. This mathematically simple model does not explicitly depend on the Hubbard-corrected ionic species and is shown to reproduce the heats of formation of the Mott insulators Ca 2 RuO 4 and Y 2 Ru 2 O 7 within ~3% of experimental results, where the experimental training data did not contain Ru oxides. This newly developed method thus absolves from the need for element-specific corrections fitted to experiments in existing Hubbard-corrected approaches to the prediction of reaction energies of transition metal oxides and metals. The absence of fitting parameters opens up here the possibility to predict relative thermodynamic stabilities and reaction energies involving d-states of varying degree of localization at transition metal oxide interfaces and defects, where site-dependent U-parameters will be particularly important and devising a fitting scheme against experimental data with predictive power would be exceedingly difficult.

transition metal oxides↗

The Early Career Research Program Annual Progress Report: Using ARM Data and Multiscale Models to Advance the Understanding of Liquid-Phase Cloud Response to Aerosol Perturbation over Ocean and Land

This report is for the first fiscal year of this ECRP project. This ECRP project aims to study the response of liquid-phase clouds to aerosol perturbation and reduce the related uncertainty in the DOE Earth system model. During this fiscal year, this project mainly made progress on the tasks about observational analyses for Objective 1; and successfully set up two Large-Eddy Simulation (LES) models for Objective 2. A postdoctoral researcher and a graduate student summer intern are on board and fully dedicated to this project. In addition to internal collaboration within LLNL, this project has routinely maintained external collaboration with scientists from universities, NASA Langley Research Center, and other DOE national laboratories. For the next reporting period, we plan to complete the tasks scheduled for the second year. Furthermore, we will promote the findings to communities of interest and proactively seek new collaborations to increase the impact of this project.

54 ENVIRONMENTAL SCIENCES↗

The Early Career Research Program Annual Progress Report: Using ARM Data and Multiscale Models to Advance the Understanding of Liquid-Phase Cloud Response to Aerosol Perturbation over Ocean and Land

This project aims to study the response of liquid-phase clouds to aerosol perturbation and reduce the related uncertainty in the DOE Earth system model. Specific objectives include: Objective 1: Quantify the aerosol indirect effect on liquid-phase clouds using ARM observations and satellite retrievals while constraining the confounding large-scale conditions; Objective 2: Harness LES case studies, untangle the confounding meteorological impacts on the observed aerosol indirect effect, and identify key cloud processes controlling the net radiative forcing of aerosol-cloud interactions at different spatiotemporal scales; Objective 3: Evaluate the aerosol indirect effect on liquid-phase clouds with process-level understanding in E3SM multiscale model configurations.

54 ENVIRONMENTAL SCIENCES↗

Assessment and Improvement of Fission Product Transport Predictions of Particle Fuel in BISON

The U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims to develop predictive capabilities by applying computational methods to the analysis and design of advanced reactor and fuel cycle systems. This program has been providing engineering-scale support for the development of BISON, a high-fidelity and high-resolution fuel performance tool. This study was motivated by the need to incorporate more physics-based models in BISON in order to foster tri-structural isotropic (TRISO) applications. This document details the integration of new modeling capabilities in BISON, including (1) development of pyrolytic carbon (PyC) and silicon carbide (SiC) layer anisotropic thermal and mass transport capabilities, (2) verification of the mass diffusion solution in TRISO modeling, (3) calibration of fission product diffusivity using Advanced Gas Reactor (AGR) experiments, (4) improved fission product release modeling by developing compact diffusion modeling capabilities, and (5) documentation of accelerated failure analysis on the BISON website. Improvements made to the diffusion models and parameters were documented and validated against AGR-1 and -2 experiment data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Planning and Execution of a Marine Methane Hydrate Pressure Coring Program for the Walker Ridge and Green Canyon Areas of the Gulf of Mexico

The objective of this project (and report) is to produce a guide to developing scientific, operational, and logistical plans for a future methane hydrate-focused offshore pressure coring program. This report focuses primarily on a potential coring program in the Walker Ridge 313 and Green Canyon 955 blocks where previous investigations were undertaken as part of the 2009 Department of Energy JIP Leg II expedition, however, the approach to designing a pressure coring program that was utilized for this project may also serve as a useful model for planning pressure coring programs for hydrates in other areas. The initial portion of the report provides a brief overview of prior investigations related to gas hydrates in general and at the Walker Ridge 313 and Green Canyon 955 blocks in particular. The main content of the report provides guidance for various criteria that will come into play when designing a pressure coring program.

54 ENVIRONMENTAL SCIENCES↗

The Double Galaxy Cluster A2465. III. X-Ray and Weak-lensing Observations

We report Chandra X-ray observations and optical weak-lensing measurements from Subaru/Suprime-Cam images of the double galaxy cluster A2465 ( z = 0.245). The X-ray brightness data are fit to a β model to obtain the radial gas density profiles of the northeast (NE) and southwest (SW) subcomponents, which are seen to differ in structure. We determine core radii, central temperatures, the gas masses within r {sub 500c}, and the total masses for the broader NE and sharper SW components assuming hydrostatic equilibrium. There is no large X-ray excess between the two components. The central entropy of the NE subcluster is about two times higher than the SW. Along with its structural properties and an apparent radio halo that is a sign of a merger, this suggests that the NE component has undergone merging on its own. The weak-lensing analysis gives virial masses for each substructure, which compare well with earlier dynamical results. The derived outer mass contours of the SW sub-component from weak lensing are more irregular and extended than those of the NE. Although there is a weak enhancement and small offsets between X-ray gas and mass centers from weak lensing, the lack of large amounts of gas between the two subclusters indicates that A2465 is in a pre-merger state. We discuss star formation enhancement in this system resulting from its dynamics and shock-induced star formation scenarios. A dynamical model that is consistent with the observed cluster data, based on the FLASH program and the radial infall model, is constructed, where the subclusters currently separated by ∼1.2 Mpc are approaching each other at ∼2000 km s{sup −1} and will meet in ∼0.4 Gyr.

79 ASTRONOMY AND ASTROPHYSICS↗

Coupling a Cellular Automaton Model with a Finite Element Model for Simulating Deformation and Recrystallization of a Low-Carbon Micro-alloyed Steel During Hot Compression

This study simulated the dynamic recrystallization (DRX) of a 2.25Cr-1Mo-0.25V steel by coupling a cellular automaton (CA) method with a finite element (FE) model. A secondary development program (SDP) on DEFORM-2D was carried out and the stress strain response, dislocation density evolution and DRX were considered. In this way, an interaction between the microstructural evolution and the deformation behavior can be taken into account. The values of temperature, strain and strain rate from the FE analysis were passed to the CA model. In turn, the recrystallized grain size and volume fraction of DRX predicted by the CA model were passed back to the FE model, which influenced the flow stress. To validate the SDP, the predicted loads and flow stress were compared with the experimental values, which show a good agreement. Then, the SDP program was used to simulate the microstructural evolution. Morphological characteristic, recrystallized grain size and volume fraction of DRX were predicted and compared with experimental data. The results show that the comparison is in a good agreement, which indicates the SDP is reliable.

36 MATERIALS SCIENCE↗

Simulated impact of the renewable fuels standard on US Conservation Reserve Program enrollment and conversion

Abstract A socioeconomic model is used to estimate the land‐use implications on the U.S. Conservation Reserve Program from potential increases in second‐generation biofuel production. A baseline scenario with no second‐generation biofuel production is compared to a scenario where the Renewable Fuels Standard ( RFS 2) volumes are met by 2022. We allow for the possibility of converting expiring CRP lands to alternative uses such as conventional crops, dedicated second‐generation biofuel crops, or harvesting existing CRP grasses for biomass. Results indicate that RFS 2 volumes ( RFS 2‐v) can be met primarily with crop residues (78% of feedstock demand) and woody residues (19% of feedstock demand) compared with dedicated biomass (3% of feedstock demand), with only minimal conversion of cropland (0.27 million hectares, <1% of total cropland), pastureland (0.28 million hectares of pastureland, <1% of total pastureland), and CRP lands (0.29 million hectares of CRP lands, 3% of existing CRP lands) to biomass production. Meeting RFS 2 volumes would reduce CRP re‐enrollment by 0.19 million hectares, or 4%, below the baseline scenario where RFS 2 is not met. Yet under RFS 2‐v scenario, expiring CRP lands are more likely to be converted to or maintain perennial cover, with 1.78 million hectares of CRP lands converting to hay production, and 0.29 million hectares being harvested for existing grasses. A small amount of CRP is harvested for existing biomass, but no conversion of CRP to dedicated biomass crops, such as switchgrass, are projected to occur. Although less land is enrolled in CRP under RFS 2‐v scenario, total land in perennial cover increases by 0.15 million hectares, or 2%, under RFS 2‐v. Sensitivity to yield, payment and residue retention assumptions are evaluated.

09 BIOMASS FUELS↗

Data-Driven Modeling and Optimization of Building Energy Consumption: a Case Study

Installing sensors and Building Automation Systems (BAS) allows controlling the facility operations while generating data that can be analyzed for model development. This work focuses on data-driven modeling of the building to optimize energy consumption. The City of Orlando aims to reduce its energy consumption so, they provided us access to their BAS for data and studying the operation of its facilities. We selected a mid-size pilot building to conduct data analysis and modeling. We develop an Application Programming Interface (API) to login to the servers and scrape data. The scraped data contains features ranging from environmental conditions to equipment activity. This dataset is a time series so, it's handled in accordance and analyzed to investigate patterns and relations between data points that help choose parameters for predictive models for building and equipment. Finally, the models are optimized to reduce the energy consumption of the facility.

Grover, Divas↗

Becoming a 10: A Closer Look at the U.S. Department of Energy Home Energy Score's Updates, Improvements, and Expansion

The U.S. Department of Energy (DOE)'s Home Energy Score provides homeowners, buyers, and renters directly comparable and credible information about a home's estimated energy use and costs. Certified Qualified Assessors conduct low-cost assessments to provide each home a 1-10 score alongside a set of cost-effective upgrades to improve the score. As of February 2022, hundreds of assessors have delivered over 175,000 scores to homes across the country. Originally released in 2012 using DOE2.1e as the modeling backend, after years of effort, a new version of Home Energy Score was released in 2021 utilizing DOE's flagship energy modeling software, EnergyPlus. The updated architecture leverages modeling advancements and enables new building technologies to be added to the Scoring Tool. The new release represents a leap forward in harmonizing modeling assumptions across DOE and industry programs. In this paper we discuss the rigorous approach to model comparison with DOE2 undertaken prior to the update, utilizing test homes and real homes from the Home Energy Score database to strike a balance between consistency and more accurate energy predictions. We also discuss additional new capabilities, including improvements made to the upgrade recommendations methodology, the inclusion of an energy cost estimate metric based on ResStock analysis for use in home appraisals, and improved data analysis for quality assurance. Finally, we look at the impact Home Energy Score has had over the last decade and its future potential as its uptake in state energy plans, local ordinances, utility programs, and real estate data continues to grow.

building energy modeling↗

BISON Capabilities for LWR Fuel Behavior Analysis During Accident and High-burnup Conditions

The U.S. Department of Energy (DOE)'s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims to develop predictive capabilities using computational methods for the analysis and design of advanced reactor and fuel cycle systems. This program has been supporting the development of BISON which is a high-fidelity and high-resolution fuel performance tool at the engineering scale. Increasing recent interest in applications at extended burnups motivated this study to incorporate more physically based models in BISON. This document details integration of newly implemented modeling capabilities into BISON, which includes (1) new thermal conductivity models that are valid up to 100 GWd/t, (2) models for the formation of the high-burnup structure (HBS), (3) two porosity correction methods beingapplied on the thermal conductivity due to the conducting pores during the HBS formation. BISON's results are verified and validated to test the new modeling capabilities

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗