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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Regional Subsidence Analysis Through a Multi-Scale Modeling Framework Based on Breakage Mechanics

Although poroelastic models are often used to explain the delay between subsurface fluid depletion and ground subsidence, inelastic compaction involving permanent changes of rock microstructure may exacerbate hydro-mechanical coupling, thus influencing the interpretation of measurements and long-term forecasts. Here, a multi-scale modeling approach is discussed, which accounts for the inherent connection between rock microstructure, hydraulic conductivity, and pore compaction. A constitutive model built within the framework of breakage mechanics is proposed to link the hydraulic conductivity of granular rocks with inelastic deformations and changes in grading caused by injection-depletion cycles at stress levels far from yielding. The proposed model has been incorporated into large-scale simulation frameworks, thus enabling the spatiotemporal mapping of regional subsidence through a hybrid, semi-analytical approach. Numerical results based on this strategy show that the model allows isolating near-field and far-field effects into the computation of land subsidence and can generate forecasts for different modeling scenarios (e.g., elastic and inelastic compaction, constant permeability, and concurrent change of compressibility and permeability). In particular, examples of simulations for the case of the Groningen gas field are discussed, showing the model capabilities to use both field measurements and laboratory tests for the generation of reasonable subsidence maps, without expensive computational costs. Results indicate that ignoring coupled inelastic effects has major consequences on the predicted timescale of subsidence. Specifically, while all the model scenarios produced similar long-term ground settlements, those ignoring breakage-dependent permeability changes result in a variation of the temporal window of residual subsidence of the order of several decades.

58 GEOSCIENCES↗
DOE OSTI2019

Learning from the density to correct total energy and forces in first principle simulations

We propose a new molecular simulation framework that combines the transferability, robustness, and chemical flexibility of an ab initio method with the accuracy and efficiency of a machine learning model. The key to achieve this mix is to use a standard density functional theory (DFT) simulation as a preprocessor for the atomic and molecular information, obtaining a good quality electronic density. General, symmetry preserving, atom-centered electronic descriptors are then built from this density to train a neural network to correct the baseline DFT energies and forces. These electronic descriptors encode much more information than local atomic environments, allowing a simple neural network to reach the accuracy required for the problem of study at a negligible additional cost. The balance between accuracy and efficiency is determined by the baseline simulation. This is shown in results where high level quantum chemical accuracy is obtained for simulations of liquid water at standard DFT cost or where high level DFT-accuracy is achieved in simulations with a low-level baseline DFT calculation at a significantly reduced cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

COSMIC DAWN: Distributed Analysis of Wireless at Nextscale

Distributed Analysis of Wireless at Nextscale (DAWN) is a novel simulation framework for large-scale design-space exploration (DSE) of unmodified software-defined radio (SDR) applications interacting in a scalable, high-fidelity, virtual physics environment. The software-defined nature of the coupled software-physics simulation leverages hardware emulation to permit in-depth examination and modification of not only the electromagnetic environment, including each signal in flight, but also the precise state of system software and components. DAWN supports modular, customizable physics environments allowing realistic propagation effects so that computationally efficient empirical models, reduced order/surrogate models, or large-scale, high-fidelity, site-specific simulations can be used as a propagation medium based on scenario requirements. This paper introduces DAWN’s design and initial implementation, detailing key architectural components, including the Physics Realization Engine (PhyRE), Runtime Infrastructure for Simulation Environments (RISE), and the design space exploration (DSE) suite. It concludes with demonstrations using unmodified 4G/LTE software available from srsRAN on computing resources ranging from a small cluster to ORNL’s Frontier Exascale system.

Wise, Mike [ORNL] (ORCID:0000000266120641)↗
DOE OSTI2018

Could a bioenergy program stimulate electric vehicle market penetration? Potential impacts of biogas to electricity annual rebate program

Abstract The biogas‐to‐electricity pathway under the Renewable Fuel Standard (RFS) allows for Renewable Identification Number (RIN) credits to be generated when electricity produced from biogas is used in the transportation sector. Though approved as a general pathway, EPA has proposed multiple credit allocation methods to functionalize this pathway. This study describes and evaluates a potential credit allocation framework where vehicle manufacturers generate electricity RIN (E‐RIN) credits and use these credits to increase the sales of plug‐in electric vehicles (PEVs). Under this framework, manufacturers use part of the credit value to reimburse electricity generators, offsetting potential higher biogas electricity generation cost. The remaining credit value is passed on to consumers as an annual PEV rebate to stimulate PEV sales. An iterative simulation framework is developed to fulfill two tasks: (a) to estimate the annual rebate amounts and their upfront value to consumers based on various factors, such as vehicle mileage, E‐RIN equivalence value, and biogas capacity, and (b) to evaluate potential impacts of the E‐RIN program on electrification of the future light‐duty vehicles (LDVs) and energy use. The annual rebate amount varies by vehicle technology and could be up to $870/year for battery electric vehicles (BEVs) and range between $230 and 825/year for plug‐in hybrid electric vehicles (PHEVs) depending on the electric range. These per vehicle rebates decrease when demand for electricity exceeds biogas electricity availability. The effectiveness of the program as modeled here is subject to different factors, such as the E‐RIN equivalence value, biogas electricity generation cost, biogas electricity generation capacity, and consumers’ valuation of the E‐RIN rebate. Our modeling results indicate that an E‐RIN program has the potential to produce nearly $12 billion in E‐RIN credits annually and to significantly increase PEV annual sales by up to 2.3 million and the PEV population by about 19.7 million in 2030.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Reducing Operating Temperature in Photovoltaic Modules

Reducing the operating temperature of photovoltaic modules increases their efficiency and lifetime. This can be achieved by reducing the production of waste heat or by improving the rejection of waste heat. We tested, using a combination of simulation and experiment, several thermal modifications in each category. To predict operating temperature and energy yield changes in response to changes to the module, we implemented a physics-based transient simulation framework based almost entirely on measured properties. The most effective thermal modifications reduced the production of waste heat by reflecting unusable light from the cell or the module. Consistent with previous results and verified in this work through year-long simulations, the ideal reflector resulted in an annual irradiance-weighted temperature reduction of 3.8 K for crystalline silicon (c-Si). Our results illustrate that more realistic reflector concepts must balance detrimental optical effects with the intended thermal effects to realize the optimal energy production advantage. Methods improving thermal conductivity or back-side emissivity showed only modest improvements of less than 1 K. We also studied a GaAs module, which uses high-efficiency and high-subbandgap reflectivity to operate at an annual irradiance-weighted temperature 12 K cooler than that of a c-Si module under the same conditions.

14 SOLAR ENERGY↗
DOE OSTI2025

Numerical Simulation Studies of Ultrasonic De-Icing for Heating, Ventilation, Air Conditioning, and Refrigeration Structures

Ice accumulation on heating, ventilation, air conditioning, and refrigeration (HVACR) structures presents significant operational challenges. These challenges include reduced efficiency, increased energy consumption, and potential damage to equipment. Traditional de-icing methods, such as chemical treatments, mechanical scraping, or heating-based techniques, are often labor-intensive, costly, and environmentally harmful. Here, this study uniquely investigates ultrasonic de-icing as an energy-efficient alternative for HVACR applications, focusing on the specific structural geometries found in these systems. A comprehensive numerical simulation framework was developed using finite element analysis to explore ultrasonic wave propagation across four distinct HVACR structures. Key parameters such as ultrasonic frequency, power levels, and the number and placement of actuators were examined for their impact on ice detachment efficiency. Results from simulations on a plate structure reveal that ultrasonic excitation can propagate effectively across large areas (at least 150 × 150 mm), enhancing the de-icing coverage. Lower frequency (e.g., 30 to 45 kHz) excitation results in greater displacement, improving de-icing performance, while increased actuator numbers with the same total power input also enhance effectiveness. Two actuators seem sufficient for the de-icing of a 300 × 300 mm plate. For tube-and-fin structures, specific high-power ultrasonic frequencies selectively excite the fin plates, demonstrating efficient ice removal when actuated on the tube. However, optimal performance requires careful design of actuator placement and vibration modes to accommodate the irregular shapes of these structures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Load-Direction-Derived Support Structures for Wind Turbines: A Lattice Tower Concept and Preparations for Future Certifications: Preprint

The call for more cost-effective and environmentally friendly tower concepts is motivated by tower costs [1] and tower CO2-emission contributions [2], which are high relative to the whole wind turbine system. The proposed rotatable tower concept with yaw bearing at the bottom instead of the top of the tower will provide beneficial economic and environmental impacts to the turbine system. This wind alignment capability indicates a load-direction-derived tower design. By combining this approach with a lattice concept, large material and cost savings for the tower can be achieved. This paper presents a way to analyze and verify the proposed design through aero-servo-elastic simulations, which make future certifications of rotatable tower concepts viable. For this reason, the state-of-the-art, open-source lattice-tower finite-element-method (FEM) module SubDyn [10], developed by the National Renewable Energy Laboratory, has been modified to account for arbitrary member cross-sections. Required changes in the beam element stiffness and mass matrix formulation took place according to an energy method [13]. All validated adaptions will be usable within the aero-servo-elastic simulation framework FAST and are also beneficial for other nonrotatable lattice structures.

17 WIND ENERGY↗
DOE OSTI2023

Computational studies of impurity migration during induction stirring of molten uranium

Understanding and controlling impurity behavior in actinide metal casting processes are foundational for efficient part production yet remain major challenges for researchers and industry. To help provide insight regarding impurity distribution during actinide metal casting, we have developed computational fluid dynamics (CFD) models for a laboratory-scale system using commercial and open-source code. Multiple simulation frameworks allow for improved confidence in the resulting outputs, while taking advantage of the maturity and convenience offered by commercial platforms and simultaneously maintaining the transparency and flexibility often provided by open-source software. Here, we describe multiple experiment-informed models designed to simulate a specific laboratory system in which uranium melt, containing a known starting concentration of carbon impurity, is electromagnetically stirred in an induction furnace. Here, the goal of the simulations is to predict the motion of uranium carbide microparticles in the velocity field of the melt. Prior to simulating the uranium-carbon system, numerical models were validated using a previously published nonradioactive experimental system. Effects of the size and shape of impurity particles in the models were investigated and agree with experimental findings. Simulation of smaller particles (< 50 µm) shows more homogenous distribution throughout the stirred melt. With increased particle size (100 µm), the body forces, which include the buoyancy force, dominate over the drag force, causing larger particles to move toward the crucible walls and upward in the system.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Roadmap on methods and software for electronic structure based simulations in chemistry and materials

This Roadmap article provides a succinct, comprehensive overview of the state of electronic structure methods and software for molecular and materials simulations. Seventeen distinct sections collect insights by 51 leading scientists in the field. Each contribution addresses the status of a particular area, as well as current challenges and anticipated future advances, with a particular eye towards software related aspects and providing key references for further reading. Foundational sections cover density functional theory and its implementation in real-world simulation frameworks, Green's function based many-body perturbation theory, wave-function based and stochastic electronic structure approaches, relativistic effects and semiempirical electronic structure theory approaches. Subsequent sections cover nuclear quantum effects, real-time propagation of the electronic structure, challenges for computational spectroscopy simulations, and exploration of complex potential energy surfaces. The final sections summarize practical aspects, including computational workflows for complex simulation tasks, the impact of current and future high-performance computing architectures, software engineering practices, education and training to maintain and broaden the community, as well as the status of and needs for electronic structure based modeling from the vantage point of industry environments. Overall, the field of electronic structure software and method development continues to unlock immense opportunities for future scientific discovery, based on the growing ability of computations to reveal complex phenomena, processes and properties that are determined by the make-up of matter at the atomic scale, with high precision.

36 MATERIALS SCIENCE↗
DOE OSTI2023

SILCC – VII. Gas kinematics and multiphase outflows of the simulated ISM at high gas surface densities

ABSTRACT We present magnetohydrodynamic (MHD) simulations of the star-forming multiphase interstellar medium (ISM) in stratified galactic patches with gas surface densities Σgas = 10, 30, 50, and 100 $\mathrm{M_\odot \, pc^{-2}}$. The silcc project simulation framework accounts for non-equilibrium thermal and chemical processes in the warm and cold ISM. The sink-based star formation and feedback model includes stellar winds, hydrogen-ionizing UV radiation, core-collapse supernovae, and cosmic ray (CR) injection and diffusion. The simulations follow the observed relation between Σgas and the star formation rate surface density ΣSFR. CRs qualitatively change the outflow phase structure. Without CRs, the outflows transition from a two-phase (warm and hot at 1 kpc) to a single-phase (hot at 2 kpc) structure. With CRs, the outflow always has three phases (cold, warm, and hot), dominated in mass by the warm phase. The impact of CRs on mass loading decreases for higher Σgas and the mass loading factors of the CR-supported outflows are of order unity independent of ΣSFR. Similar to observations, vertical velocity dispersions of the warm ionized medium (WIM) and the cold neutral medium (CNM) correlate with the star formation rate as $\sigma _\mathrm{z} \propto \Sigma _\mathrm{SFR}^a$, with a ∼ 0.20. In the absence of stellar feedback, we find no correlation. The velocity dispersion of the WIM is a factor ∼2.2 higher than that of the CNM, in agreement with local observations. For $\Sigma _\mathrm{SFR} \gtrsim 1.5 \times 10^{-2}\, \mathrm{M}_\odot \, \mathrm{yr}^{-1}\, \mathrm{kpc}^{-2}$ the WIM motions become supersonic.

Astronomy & Astrophysics↗
DOE OSTI2026

Updating the BNB Flux Prediction at SBND

Precise, accurate neutrino flux predictions for neutrino beam experiments are crucial for physics results. Flux uncertainties contribute significantly to the total systematic uncertainties seen in modern accelerator neutrino measurements such as cross sections, oscillations, and BSM studies.. For over a decade, experiments utilizing Fermilab’s Booster Neutrino Beam (BNB) have relied on the 2009 MiniBooNE flux prediction. However, the high-statistics era of the Short-Baseline Neutrino (SBN) program, with both SBND and ICARUS now operating, demands a modernized flux model and framework. While SBND is using the MiniBooNE flux model for its Generation 1 analyses, including many upcoming cross section measurements, future work will be based on a new flux model. In this talk, the ongoing work towards this new model will be outlined, including a new simulation framework (G4BNB), a new evaluation of model parameters from hadron scattering data, and a new framework for evaluating systematic uncertainties (BNBFP). Additionally, expansions to the flux model to include BSM contributions from neutral mesons will be discussed, as well as the PRISM capabilities of SBND to observe a wide range of off axis angles of the neutrino beam.

Paton, Josephine [Fermilab]↗
DOE OSTI2026

Updating the BNB Flux Prediction at SBND

Precise, accurate neutrino flux predictions for neutrino beam experiments are crucial for physics results. Flux uncertainties contribute significantly to the total systematic uncertainties seen in modern accelerator neutrino measurements such as cross sections, oscillations, and BSM studies.. For over a decade, experiments utilizing Fermilab’s Booster Neutrino Beam (BNB) have relied on the 2009 MiniBooNE flux prediction. However, the high-statistics era of the Short-Baseline Neutrino (SBN) program, with both SBND and ICARUS now operating, demands a modernized flux model and framework. While SBND is using the MiniBooNE flux model for its Generation 1 analyses, including many upcoming cross section measurements, future work will be based on a new flux model. In this talk, the ongoing work towards this new model will be outlined, including a new simulation framework (G4BNB), a new evaluation of model parameters from hadron scattering data, and a new framework for evaluating systematic uncertainties (BNBFP). Additionally, expansions to the flux model to include BSM contributions from neutral mesons will be discussed, as well as the PRISM capabilities of SBND to observe a wide range of off axis angles of the neutrino beam.

Paton, Josephine [Fermilab]↗
DOE OSTI2017

Metal Big Area Additive Manufacturing: Process Modeling and Validation

Metal Big Area Additive Manufacturing (mBAAM) is a new additive manufacturing (AM) technology for printing large-scale 3D objects. mBAAM is based on the gas metal arc welding process and uses a continuous feed of welding wire to manufacture an object. An electric arc forms between the wire and the substrate, which melts the wire and deposits a bead of molten metal along the predetermined path. In general, the welding process parameters and local conditions determine the shape of the deposited bead. The sequence of the bead deposition and the corresponding thermal history of the manufactured object determine the long range effects, such as thermal-induced distortions and residual stresses. Therefore, the resulting performance or final properties of the manufactured object are dependent on its geometry and the deposition path, in addition to depending on the basic welding process parameters. Physical testing is critical for gaining the necessary knowledge for quality prints, but traversing the process parameter space in order to develop an optimized build strategy for each new design is impractical by pure experimental means. Computational modeling and optimization may accelerate development of a build process strategy and saves time and resources. Because computational modeling provides these opportunities, we have developed a physics-based Finite Element Method (FEM) simulation framework and numerical models to support the mBAAM process s development and design. In this paper, we performed a sequentially coupled heat transfer and stress analysis for predicting the final deformation of a small rectangular structure printed using the mild steel welding wire. Using the new simulation technologies, material was progressively added into the FEM simulation as the arc weld traversed the build path. In the sequentially coupled heat transfer and stress analysis, the heat transfer was performed to calculate the temperature evolution, which was used in a stress analysis to evaluate the residual stresses and distortions. In this formulation, we assume that physics is directionally coupled, i.e. the effect of stress of the component on the temperatures is negligible. The experiment instrumentation (measurement types, sensor types, sensor locations, sensor placements, measurement intervals) and the measurements are presented. The temperatures and distortions from the simulations show good correlation with experimental measurements. Ongoing modeling work is also briefly discussed.

Additive Manufacturing↗
DOE OSTI2023

A physics-driven Σ-Y atomization model for heavy-duty engine simulations

The atomization of a liquid jet is a multi-scale and multi-physics problem of interest for many engineering applications. Particularly, it drives the fuel-oxidizer mixing and dictates the efficiency of combustion engines. High-fidelity multi-phase simulations remain challenging due to the excessive computational cost required to capture all the atomization scales. Thus, atomization models are necessary to represent sub-grid liquid structures. Here, in this work, a modified Σ-Y model in the context of Eulerian-Lagrangian Spray Atomization (ELSA) is used to transport the surface area density of the spray. The model's predictive performance is assessed under various operating conditions relevant to heavy-duty engines using the Engine Combustion Network (ECN) Spray C and Spray D research-grade injectors. The classic droplet collision formulation of the Σ-Y model alone does not replicate the response of the measured spray surface area to changes in injector, ambient pressure, and injection pressure, requiring individual tuning of the model's parameters. Instead, a transition between dense and dilute spray breakup mechanisms is proposed in terms of the average droplet spacing. The collision breakup mechanism represents the dilute spray, whereas the droplet size in the dense spray is driven by a competition between the integral scale of turbulence and the balance between the turbulent kinetic energy and the surface energy of the droplets. Such an approach minimizes the requirements for model tuning. Moreover, the role of the constants of a compressible standard k-ε RANS model is assessed in the injector's internal flow and external spray simulation framework, and an updated set is proposed. The results are validated against x-ray radiography and Ultra-Small Angle X-ray Scattering (USAXS) data and highlight the predictive capabilities of the proposed physics-driven Σ-Y model, which is compatible with engine simulation turnaround times.

42 ENGINEERING↗
DOE OSTI2019

Dark matter search in a Beam-Dump eXperiment (BDX) at Jefferson Lab (2018 update to PR12-16-001)

This document complements and completes what was submitted last year to PAC45 as an update to the proposal PR12-16-001 "Dark matter search in a Beam-Dump eXperiment (BDX)" at Jefferson Lab submitted to JLab-PAC44 in 2016. Following the suggestions contained in the PAC45 report, in coordination with the lab, we ran a test to assess the beam-related backgrounds and validate the simulation framework used to design the BDX experiment. Using a common Monte Carlo framework for the test and the proposed experiment, we optimized the selection cuts to maximize the reach considering simultaneously the signal, cosmic-ray background (assessed in Catania test with BDX-Proto) and beam-related backgrounds (irreducible NC and CC neutrino interactions as determined by simulation). Our results confirmed what was presented in the original proposal: with 285 days of a parasitic run at 65 $\mu$A (corresponding to $10^{22}$ EOT) the BDX experiment will lower the exclusion limits in the case of no signal by one to two orders of magnitude in the parameter space of dark-matter coupling versus mass.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

DEMOS (Demographic Microsimulator Tool for Longitudinal Synthetic Population) [SWR-25-135] related to NLR SWR-26-076

The Demographic Microsimulator (DEMOS) is an agent-based simulation framework used to model the evolution of population demographic characteristics and lifecycle events, such as education attainment, marital status, and other key transitions. DEMOS modules are designed to capture the interdependencies between short-term and long-term lifecycle events, which are often influential in downstream transportation and land-use modeling. A key feature of DEMOS is its ability to track changes in an agent’s demographic status from year t to year t + 1. This structure allows the model to evolve populations over any user-defined time horizon. As a result, DEMOS is well suited for analyzing medium- and long-term transportation-related decisions, including household vehicle transactions (e.g., purchasing, selling, or replacing vehicles) and work location choices. Core features of DEMOS include the modeling of more than ten lifecycle events, behaviorally realistic patterns informed by long-running panel data, explicit representation of interdependencies among lifecycle processes, and a flexible, modular simulation architecture. A technical memorandum describing DEMOS is available here. The memorandum provides an overview of the framework’s functionality, model structure, input and output data, and its applications in transportation planning and broader policy analysis contexts. Interested readers are also encouraged to consult the paper listed below for additional details on the DEMOS methodology. Sun, Bingrong, Shivam Sharda, Venu M. Garikapati, Mohamed Amine Bouzaghrane, Juan Caicedo, Srinath Ravulaparthy, Isabel Viegas de Lima, Ling Jin, C. Anna Spurlock, and Paul Waddell. "Demographic Microsimulator for Integrated Urban Systems: Adapting Panel Survey of Income Dynamics to Capture the Continuum of Life." Transportation Research Record (2025): 03611981251333339.

Sun, Bingrong [National Laboratory of the Rockies ↗
DOE OSTI2021

An Integrated Multiscale Modeling Framework for Unconventional Stimulation and Production (Final Report)

The production of oil and gas from unconventional reservoirs largely depends upon two main features operating at different scales: (1) the establishment of a reservoir scale stimulated fracture network that effectively communicates with the rock volume, enhancing permeability and transport to the wellbore and (2) the coupled multi-phase flow, chemical and mechanical processes affecting the migration of hydrocarbons from the low permeability country rock adjacent to the stimulated fracture network. To date, there has been no simulation framework that allows seamless and integrated prediction of these features across spatial scales extending from the pore structure of the reservoir rock to the volume of the reservoir. In addition, there has been a lack of suitable field measurements to test such models, as stimulation and production data are often proprietary and not freely available to national laboratories and academic institutions. New multi-scale simulation capabilities are needed that are validated against suitable field-based research experiments on hydraulic fracturing and shale production.

02 PETROLEUM↗