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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Modulation of thermal conductivity of iron-doped ß-Ga2O3 by helium-ion irradiation

This study examines the impact of helium-ion irradiation on the thermal conductivity of ß-Ga2O3. A laser-based spatial domain thermoreflectance technique is used to investigate thermal conductivity map for both un-irradiated and irradiated ß-Ga2O3, which are then validated against simulation results derived from density functional theory-based phonon transport simulations. Since helium bubble evolution was ob- served at the nanoscale using transmission electron microscopy, the simulation study was carried out on eight distinct helium-induced sites in ß-Ga2O3. Our findings indicate a reduction in thermal conductivity for the irradiated samples. Experimental results show a significant reduction in thermal conductivity in irradiated samples, with de- creases of approximately 25% along the [100] direction and 40% along [001] directions. Phonon transport simulations closely replicate these findings, particularly when helium occupying interstitial sites, predicting reductions of ˜53% along [100] and ˜50% along [001] directions. This work underscores the role of irradiation-induced microstructural changes in the heat transport properties of ß-Ga2O3 which is crucial for its application in sensor devices in extreme environments.

36 - MATERIALS SCIENCE↗
DOE OSTI2020

RouteE: A Vehicle Energy Consumption Prediction Engine

The emergence of connected and automated vehicles and smart cities technologies create the opportunity for new mobility modes and routing decision tools, among many others. To achieve maximum mobility and minimum energy consumption, it is critical to understand the energy cost of decisions and optimize accordingly. The Route Energy prediction model (RouteE) enables accurate estimation of energy consumption for a variety of vehicle types over trips or sub-trips where detailed drive cycle data are unavailable. Applications include vehicle route selection, energy accounting and optimization in transportation simulation, and corridor energy analyses, among others. The software is a Python package that includes a variety of pre-trained models from the National Renewable Energy Laboratory (NREL). However, RouteE also enables users to train custom models using their own data sets, making it a robust and valuable tool for both fast calculations and rigorous, data-rich research efforts. The pre-trained RouteE models are established using NREL’s Future Automotive Systems Technology Simulator paired with approximately 1 million miles of drive cycle data from the Transportation Secure Data Center, resulting in energy consumption behavior estimates over a representative sample of driving conditions for the United States. Validations have been performed using on-road fuel consumption data for conventional and electrified vehicle powertrains. Transferring the results of the on-road validation to a larger set of real-world origin-destination pairs, it is estimated that implementing the present methodology in a green-routing application would accurately select the route that consumes the least fuel 90% of the time. The novel machine learning techniques used in RouteE make it a flexible and robust tool for a variety of transportation applications.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Transport model comparison studies of intermediate-energy heavy-ion collisions

Transport models are the main method to obtain physics information on the nuclear equation of state and in-medium properties of particles from low to relativistic-energy heavy-ion collisions. The Transport Model Evaluation Project (TMEP) has been pursued to test the robustness of transport model predictions in reaching consistent conclusions from the same type of physical model. To this end, calculations under controlled conditions of physical input and set-up were performed with various participating codes. These included both calculations of nuclear matter in a box with periodic boundary conditions, which test separately selected ingredients of a transport code, and more realistic calculations of heavy-ion collisions. Over the years, six studies have been performed within this project. In this intermediate review, we summarize and discuss the present status of the project. We also provide condensed descriptions of the 26 participating codes, which contributed to some part of the project. These include the major codes in use today. After a compact description of the underlying transport approaches, we review the main results of the studies completed so far. They show, that in box calculations the differences between the codes can be well understood and a convergence of the results can be reached. These studies also highlight the systematic differences between the two families of transport codes, known under the names of Boltzmann–Uehling–Uhlenbeck (BUU) and Quantum Molecular Dynamics (QMD) type codes. However, when the codes were compared in full heavy-ion collisions using different physical models, as recently for pion production, they still yielded substantially different results. This calls for further comparisons of heavy-ion collisions with controlled models and of box comparisons of important ingredients, like momentum-dependent fields, which are currently underway. Furthermore, our evaluation studies often indicate improved strategies in performing transport simulations and thus can provide guidance to code developers. Results of transport simulations of heavy-ion collisions from a given code will have more significance if the code can be validated against benchmark calculations such as the ones summarized in this review.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Applying Constrained Bayesian Optimization to the Design of Critical Experiments

Often when planning a criticality experiment, many design configurations are iteratively investigated with a Monte Carlo transport code. The goal is that the experiment will be optimal with respect to some variable, like the fraction of fissions occurring at a certain energy range, while simultaneously being critical. Unfortunately, the Monte Carlo transport simulations are expensive, which can ultimately limit the number of configurations that can be explored. In this work, we present how Gaussian processes (GPs) can be used as a reduced-order model in a constrained Bayesian optimization (CBO) algorithm to design a criticality experiment. The GPs replace the Monte Carlo transport simulations that explore the design space. The CBO algorithm efficiently identifies new points in the design space to run the Monte Carlo transport code while respecting the criticality constraint. It does so in a manner that both improves the accuracy of the GP and finds the approximate global optimum. We demonstrate the performance of CBO with the design of a Thermal Epithermal eXperiment (TEX) for the criticality safety validation of nuclear waste models of the Hanford Tank Farm.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Alquimia v1.0: a generic interface to biogeochemical codes – a tool for interoperable development, prototyping and benchmarking for multiphysics simulators

Alquimia v1.0 is a generic interface to geochemical solvers that facilitates development of multiphysics simulators by enabling code coupling, prototyping and benchmarking. The interface enforces the function arguments and their types for setting up, solving, serving up output data and carrying out other common auxiliary tasks while providing a set of structures for data transfer between the multiphysics code driving the simulation and the geochemical solver. Alquimia relies on a single-cell approach that permits operator splitting coupling and parallel computation. We describe the implementation in Alquimia of two widely used open-source codes that perform geochemical calculations: PFLOTRAN and CrunchFlow. We then exemplify its use for the implementation and simulation of reactive transport in porous media by two open-source flow and transport simulators: Amanzi and ParFlow. We also demonstrate its use for the simulation of coupled processes in novel multiphysics applications including the effect of multiphase flow on reaction rates at the pore scale with OpenFOAM, the role of complex biogeochemical processes in land surface models such as the E3SM Land Model (ELM) and the impact of surface–subsurface hydrological interactions on hydrogeochemical export from watersheds with the Advanced Terrestrial Simulator (ATS). These applications make it apparent that the availability of a well-defined yet flexible interface has the potential to improve the software development workflow, freeing up resources to focus on advances in process models and mechanistic understanding of coupled problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

The dependence of confinement on the isotope mass in the core and the edge of AUG and JET-ILW H-mode plasmas

Experiments in ASDEX Upgrade (AUG) and JET with the ITER-like wall (JET-ILW) are performed to separate the pedestal and core contributions to confinement in H-modes with different main ion masses. A strong isotope mass dependence in the pedestal is found which is enhanced at high gas puffing. This is because the ELM type changes when going from D to H for matched engineering parameters, which is likely due to differences in the inter ELM transport with isotope mass. The pedestal can be matched in H and D plasmas by varying only the triangularity and keeping the engineering parameters relevant for core transport the same. With matched pedestals Astra/TGLF (Sat1geo) core transport simulations predict the experimental profiles equally well for H and D. These core transport simulations show a negligible mass dependence and no gyro-Bohm scaling is observed. However, to match the experimental observations at medium β it is required to take the fast-ion dilution and rotation into account. This is not enough for high β plasmas where for the first time a profile match between H and D plasmas was achieved experimentally. Under these conditions quasilinear modelling with TGLF over predicts the transport in the core of H and D plasmas alike.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

HL-2A's ELM cycle simulations by integrating BOUT++'s drift MHD and transport code

A new integrating model has been developed to couple tokamak edge multiscale magnetohydrodynamic (MHD) events and transport simulations, such as edge-localized mode (ELM) cycles. As a proof of principle, we first start from a set of three-field two-fluid model equations, which includes the pressure, current, and vorticity. Here, the equations are separated into the slowly evolving part of the axisymmetric component by taking a time average of the axisymmetric component. The time-averaged fluxes, which are quadratic in fluctuating quantities, act as driven terms for the time-averaged axisymmetric quantities that determine the plasma transport, and therefore the large-scale evolution of the plasma profiles. Then the HL-2A's ELM cycles are simulated using the model. Good agreements of ELM size and pedestal recovery time have been achieved for the solutions obtained from the coupled simulation compared with experiment. For one ELM cycle simulation, the coupled code can achieve a speedup of a factor of up to 30 over standalone code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

A Versatile Simulated Data Transport Layer for in Situ Workflows Performance Evaluation

In situ processing does not only allow scientific applications to face the explosion in data volume and velocity but also to address the time constraints of many simulation-analysis workflows by providing scientists with early insights about their applications at runtime. Multiple frameworks implement the concept of a data transport layer (DTL) to enable such in situ workflows. These tools are very versatile, directly or indirectly access the data generated on the same node, another node of the same compute cluster, or a completely distinct node, and allow data publishers and subscribers to run on the same computing resources or not. This versatility puts on researchers the onus of taking key decisions related to resource allocation and how to transport data to ensure the most efficient execution of their in situ workflows. However, domain scientists and workflow practitioners lack the appropriate tools to assess the respective performance of particular design and deployment options. In this paper we introduce a versatile simulated DTL designed to provide researchers with insights on the respective performance of different execution scenarios of in situ workflows. This open-source, standalone library builds on the SimGrid toolkit and can be linked to any SimGrid-based simulator. It facilitates the evaluation of the performance behavior, at scale, of different data transport configurations and the study of the effects of resource allocation strategies. We demonstrate the scalability, versatility, and accuracy of this simulated DTL by reproducing the execution of two synthetic benchmarks and of a real-world in situ workflow composed of an MPI application and a parallel data analysis. Results of simulations run on a single core show that the proposed library can simulate the interactions of tens of thousands of simulated processes deployed on two interconnected commodity clusters in a few seconds, and the execution by a thousand simulated processes of an in situ workflow in less than three minutes.

Suter, Fred [ORNL] (ORCID:0000000319021955)↗
DOE OSTI2023

Simulating the Transport and Rupture of Pollen in the Atmosphere

Pollen, one type of primary biological aerosol particle (PBAP), is emitted from the terrestrial biosphere and can undergo physical changes in the atmosphere via particle rupture. To examine the fate of pollen and its atmospheric processing, a pollen emission and transport scheme is coupled to the Weather Research and Forecasting Model with Chemistry (WRF-Chem). We simulate the emission of pollen and its impacts on the cloud properties and precipitation in the Southern Great Plains from 12 to 19 April 2013, a period with both high pollen emissions and convective activity. We conduct a suite of ensemble runs that simulate primary pollen and three different pollen rupture mechanisms that generate subpollen particles, including (a) high humidity-induced surface rupture, (b) high humidity-induced in-atmosphere plus surface rupture, and (c) lightning-induced rupture, where in-cloud and cloud-to-ground lightning strikes trigger pollen rupture events. When relative humidity is high (>80%), coarse primary pollen (~1 μg m –3 ) is converted into fine subpollen particles (~1.2e –4 μg m –3 ), which produces 80% more subpollen particles than lightning-induced rupture. The in-atmosphere humidity-driven rupture predominantly produces subpollen particles, which is further enhanced during a frontal thunderstorm. During strong convection, vertical updrafts lift primary pollen and subpollen particles (~0.5e –4 μg m –3 ) to the upper troposphere (~12 km) and laterally transports the ruptured pollen in the anvil top outflow. In regions of high pollen and strong convection, ruptured pollen can influence warm cloud formation by decreasing low cloud (<4 km) cloud water mixing ratios and increasing ice phase hydrometeors aloft (>10 km)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Benchmarking GEANT4 and PHITS for 14.8-MeV neutron transport in polyethylene and graphite materials

The feasibility of GEANT4 and PHITS with ENDF/B-VIII.0, JEFF-3.3 and JENDL-4.0 evaluated nuclear data libraries in 14.8-MeV neutron transport simulation are verified by comparing with the MCNP calculations and the experimental data. Here the measured data are from neutron integral experiments including graphite and polyethylene samples. For 6 cm-thick polyethylene and 20 cm-thick graphite samples, the results from GEANT4 and PHITS with three evaluated nuclear data libraries agree well with the MCNP calculations. For a 2 cm-thick graphite sample, the simulated results from GEANT4 and PHITS agree with the MCNP calculations, and they all underestimate the experiment data in below 3 MeV and overestimate them in the energy range of 5–7 MeV. The difference between the simulation results and the experimental data depends on the evaluated nuclear data libraries. In overall, GEANT4 and PHITS are performing reasonable jobs for 14.8-MeV neutron transport simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Impact of aquifer properties on the extent and timeline of CO 2 trapping

Abstract Geologic CO 2 sequestration in porous saline aquifers is a promising approach to reducing atmospheric concentrations of CO 2 . Reactive transport simulations provide the opportunity to analyze which factors influence geochemical reactivity in the reservoir, understand those most important for promoting CO 2 trapping, and assess individual sites. Field‐scale aquifer characterization is time and resource intensive such that here, reactive transport simulations are leveraged to enhance understanding of selected aquifer properties including porosity, permeability, depth of storage, and carbonate mineralogy on the overall CO 2 trapping potential to better select sites promoting geochemical reactivity for CO 2 trapping. There are different mechanisms for sequestrating CO 2 . Once injected, CO 2 will dissolve into the brine to create an acidic environment, resulting in the dissolution of pre‐injection formation minerals. Released ions can reprecipitate as secondary minerals. The dissolved CO 2 and mineralized CO 2 are considered as a more secure form of CO 2 trapping in this study compared to the free supercritical CO 2 . Here, a framework leveraging a controlled set of field scale simulations is developed to facilitate rapid, optimized site selection. Simulations vary aquifer properties to understand the impact of each unique property on CO 2 trapping, tracking, and comparing the amount of supercritical, aqueous, and mineralized CO 2 . The rate at which the CO 2 injected into the aquifer is converted to aqueous or mineralized CO 2 is newly defined here as the sequestration efficiency and used to compare simulation results. The reservoir depth and fraction of carbonate minerals in the formation are shown to be more important factors than reservoir porosity and permeability in affecting CO 2 trapping. However, the impact of aquifer properties on the evolution of injected CO 2 depends on the stage of the sequestration project. © 2023 Society of Chemical Industry and John Wiley & Sons, Ltd.

Energy & Fuels↗
DOE OSTI2022

The PFLOTRAN Reaction Sandbox

Abstract. As modern reactive transport simulators evolve to accommodate the demands of a user community, researchers need a platform for prototyping new biogeochemical processes, many of which are niche and specific to laboratory or field experiments. The PFLOTRAN Reaction Sandbox leverages modern, object-oriented Fortran in an attempt to provide such an environment within an existing reactive transport simulator. This work describes the PFLOTRAN Reaction Sandbox concept and implementation through several illustrative examples. Reaction Sandbox Biodegradation Hill customizes the existing microbially mediated biodegradation reaction formulation within PFLOTRAN to better match empirical data. Reaction Sandbox Simple provides an isolated environment for testing numerous preconfigured kinetic rate expressions and developing user intuition. Reaction Sandbox Example serves as a template for creating new sandboxes within PFLOTRAN.

58 GEOSCIENCES↗
DOE OSTI2023

Data-driven predictions of complex organic mixture permeation in polymer membranes

Membrane-based organic solvent separations are rapidly emerging as a promising class of technologies for enhancing the energy efficiency of existing separation and purification systems. Polymeric membranes have shown promise in the fractionation or splitting of complex mixtures of organic molecules such as crude oil. Determining the separation performance of a polymer membrane when challenged with a complex mixture has thus far occurred in an ad hoc manner, and methods to predict the performance based on mixture composition and polymer chemistry are unavailable. Here, we combine physics-informed machine learning algorithms (ML) and mass transport simulations to create an integrated predictive model for the separation of complex mixtures containing up to 400 components via any arbitrary linear polymer membrane. We experimentally demonstrate the effectiveness of the model by predicting the separation of two crude oils within 6-7% of the measurements. Integration of ML predictors of diffusion and sorption properties of molecules with transport simulators enables for the rapid screening of polymer membranes prior to physical experimentation for the separation of complex liquid mixtures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Optimized collision-specific parameters for binary mixtures of nitrogen, oxygen, argon, and helium

Recently proposed collision-specific parameters for direct simulation Monte Carlo simulations are tested for binary mixtures of nitrogen, oxygen, and argon. Near ambient conditions, the traditional collision-averaged parameters are highly accurate, whereas the collision-specific parameters are not. The simulated transport using the collision-averaged parameters for mixtures with helium, however, is found to be inaccurate. Therefore, we propose a novel method to determine molecular parameters by combining the Chapman–Enskog theory with empirical mixing rules and experimental data. The optimized parameters are highly accurate for the binary mixtures of nitrogen, oxygen, and argon and greatly improve the simulated transport for the helium mixtures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Skyshine Calculations for a Large Spent Nuclear Fuel Storage Facility with SCALE 6.2.3

The SCALE code system developed at Oak Ridge National Laboratory includes state-of-the-art capabilities for radiation source term and radiation transport simulations that can be used in numerous applications, including dose rate analyses of complex consolidated interim storage facilities (CISFs). A licensed CISF could be used to store tens of thousands of tonnes of spent nuclear fuel discharged from commercial power reactors using various cask and storage pad designs. A CISF design must comply with the regulatory requirements provided in 10 CFR Part 72, including requirements related to annual dose limits applicable to real individuals located beyond the area controlled by the licensee. Therefore, calculating a dose to the public is a necessary part of the licensing process for the construction of a CISF. These calculations are very challenging because of the complexity of the CISF design and the low magnitude of dose rate at large distances from the facility. This paper describes detailed far-field dose rate calculations performed for a proposed CISF using MAVRIC, the Monte Carlo radiation shielding sequence in SCALE 6.2.3, with automated variance reduction based on discrete ordinates calculations. The method presented in this paper uses a detailed Monte Carlo radiation transport simulation in one step from source to dose rate. A series of independent simulations was made using the complete site geometry (all casks present), but with only one cask containing radiation sources to obtain the dose rate maps produced by each storage cask. The CISF dose rate map was obtained by adding the dose rate maps produced by the independent individual cask simulations. Ample volumes of air and soil extending beyond the location of interest for dose rate calculation were included in the calculation model to properly simulate important radiation attenuation and scattering events that affect far-field dose rates. Furthermore, a comprehensive sensitivity study is included in this paper to illustrate the importance of selecting appropriate air volume, mass density, and composition for CISF skyshine dose rate calculations. Dry soil and soil containing water were analyzed to determine their effects on groundshine radiation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

The impact of simplified window and exhaust fan assumptions on indoor air quality in multifamily buildings

In residential buildings, the indoor air quality can be significantly affected by ventilation measures initiated by occupants, including the operation of windows and in-unit exhaust fans in kitchens and bathrooms. Many simulations simplify these factors by disregarding window opening behaviors and using fixed schedules for exhaust fan operation across all residential units. To estimate the impact of these simplifications in the U.S. context, this study used coupled CONTAM and EnergyPlus models to simulate airflow and contaminant transport in multifamily buildings. The coupled models parametrically varied climate zone, building airtightness, and mechanical ventilation system types. The study conducted a sensitivity analysis on two key occupant behaviors: (1) operating kitchen and bathroom exhausts on different schedules in individual dwelling units, and (2) scheduling open windows on ground and top floors. The simplified assumptions (i.e. uniform in-unit exhaust fan operation and window operation) had a minimal impact on inter-unit air flow and contaminant transport simulations across a broad range of building air leakage and mechanical ventilation system types. These findings suggest that for buildings with tight construction it is reasonable for most modelling and simulation efforts to ignore the effects of non-uniform exhaust fan operation and window opening.

Occupant behavior↗
DOE OSTI2020

Commensuration Effects in Layered Nanoparticle Solids.

We have developed a hierarchical nanoparticle transport simulator (HINTS) and adapted it to study commensuration effects in two classes of nanoparticle (NP) solids: (1) a bilayer NP solid (BNS) with an energy offset and (2) a BNS as part of a field effect transistor (FET). HINTS integrates the ab initio characterization of single NPs with the phonon-assisted tunneling transition model of the NP-NP transitions into a kinetic Monte Carlo based simulation of the charge transport in NP solids. First, we studied a BNS with an interlayer energy offset Delta, possibly caused by a fixed electric field. Our results include the following. First, in the independent energy-offset model, we observed the emergence of commensuration effects when scanning the electron filling factor (FF) across integer values. These commensuration effects were profound as they reduced the mobility by several orders of magnitude. We analyzed these commensuration effects in a five-dimensional parameter space, as a function of the on-site charging energy E-C, energy offset Delta, disorder D, the electron FF, and temperature k(B)T. We demonstrated the complexity of our model by showing that at integer FFs commensuration effects are present in some regions of the parameter space, while they vanish in other regions, thus defining distinct dynamical phases of the model. We determined the phase boundaries between these dynamical phases. Second, using these results as a foundation, we shifted our focus to the experimentally much-studied NP-FETs. NP-FETs are also characterized by an interlayer energy offset Delta, which, in contrast to our first model, is set by the gate voltage V-G and thereby related to the electron FF. We repeated many of our simulations and again demonstrated the emergence of commensuration effects and distinct dynamical phases in these NP-FETs. Notably, the commensuration effects in the NP-FETs showed many similarities to those in the independent energy-offset BNS.

Qu, Luman↗