Search NASASearch

SEARCH · Search NASA

Results for “Simulation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

268 records · Page 3

Smart Charging of Fleet and Personal Electric Vehicles through Joint Vehicle-to-Grid Optimization

As electric vehicle (EV) adoption accelerates, vehicle-to-grid (V2G) strategies offer advantages over unmanaged charging (V0G) by enhancing grid stability, reducing fleet operation costs, and supporting integration of variable generation resources. This research develops a day-ahead optimization framework linked with agent-based simulations to evaluate coordinated V2G participation by fleet and personal EVs under 5 energy-pricing settings in Austin, Texas. Three scenarios (V0G, fleet-only V2G, and joint-V2G) are examined, considering real-time price and grid profiles, health-damage costs, and operational constraints for both fleet and personal EVs. Results show how V2G scenarios shift fleet EV charging to mid-day while enabling strategic battery-discharge during evening peaks, mitigating grid stress and lowering EV energy costs. V2G delivers close to 80% energy-cost savings for a 2000-EV fleet in Austin on grid-stressed days, with 55% lower charging pollutant outputs. Joint-V2G amplifies system-level benefits by complementing fleet discharge, but smart-charging equipment costs can offset those benefits.

Electric vehicle

SAVY-4000 Finite-Element Drop Test Analysis

PFE Auxiliary Systems conducted drop testing on SAVY-4000 containers to evaluate structural response under 12-foot drop conditions. In support of that effort, a finite-element modeling capability was developed to simulate drop response across multiple container sizes and impact orientations. The purpose of this work was to provide a consistent analysis framework that could support interpretation of testing, compare response trends across multiple configurations, and generate quantities of interest for later comparison with experimental data. More broadly, the analysis and testing were intended to assess whether the containers continued to perform their primary function after a 12-foot drop, namely maintaining structural integrity and containment of the contents. The modeling approach combined an implicit preload analysis with an explicit drop simulation so that each drop event began from a mechanically realistic assembled condition, including compression of the silicone O-ring. Separate models were developed for 2-quart, 5-quart, 12-quart, and 10-gallon containers. The results were evaluated in terms of strain-gauge response, collar-lid gap behavior, and accumulated plastic strain. In addition, parametric studies were performed on the 2-quart container to assess sensitivity to O-ring stiffness, friction, canister thickness, geometry tolerance, and mesh density. The simulations showed that predicted drop responses depended strongly on both container size and drop orientation. Gap metrics identified cases in which the predicted collar-lid opening exceeded the nominal O-ring cross-section threshold, while plastic strain metrics identified localized regions of elevated permanent deformation. Parametric studies showed that the predicted response was especially sensitive to the assumed O-ring stiffness and contact friction, while the geometry tolerance study produced smaller changes in the cases examined. The main value of this work was that it established a repeatable modeling and simulation workflow to support drop-test implementation, evaluate effects of future configuration changes, and understand modeling assumptions that most influenced predicted response. At the current stage, the results were viewed as preliminary model predictions rather than validated predictions. The next step would be to compare drop-test data to the model so that predictive values of the workflow could be refined and used with greater confidence to assess whether the containers maintained structural integrity and containment of the contents after a 12-foot drop.

42 ENGINEERING

Galaxy Size and Rotation Curve Diversity in ΛCDM with Baryons

The observed rotation curves of dwarf galaxies exhibit significant diversity at fixed halo mass, challenging galaxy formation within the cold dark matter (CDM) model. Previous cosmological galaxy formation simulations with baryonic physics fail to reproduce the full diversity of rotation curves, suggesting that there is a flaw in baryonic feedback models, observational bias, or that an alternative to CDM must be invoked. In this work, we use the Marvelous Massive Dwarf zoom-in simulations, a suite of high-resolution dwarf simulations with M 200 ∼ 10 10 –10 11 M ⊙ and M * ∼ 10 7 –10 9 M ⊙ , designed to target the mass range where the galaxy rotation curve diversity is maximized, i.e., between and 100 km s −1 . We add to this a set of low-mass galaxies from the Marvel Dwarf Zoom Volumes to extend the galaxy mass range to lower values. Our fiducial star formation and feedback models produce simulated dwarfs with a broader range of rotation curve shapes, similar to observations. These simulations both create dark matter cores via baryonic feedback, reproducing the slower-rising rotation curves, while also allowing for compact galaxies and steeply rising rotation curves. Our simulated dwarfs also reproduce the observed size–M * relation, including scatter, producing both extended and compact dwarfs for the first time in simulated field dwarfs. However, the slowly rising and high baryon mass fraction, as well as the steeply rising and low baryon mass fraction, remain missing. We explore star formation and feedback models and conclude that previous simulations may have had feedback that was too strong to produce compact dwarfs.

Cruz, Akaxia [Flatiron Institute, New York, NY (Un

The phase diagram of quantum chromodynamics in one dimension on a quantum computer

The quantum chromodynamics (QCD) phase diagram, which reveals the state of strongly interacting matter at different temperatures and densities, is key to answering open questions in physics, ranging from the behaviour of particles in neutron stars to the conditions of the early universe. However, classical simulations of QCD face significant computational barriers, such as the sign problem at finite matter densities. Quantum computing offers a promising solution to overcome these challenges. Here, we take an important step toward exploring the QCD phase diagram with quantum devices by preparing thermal states in one-dimensional non-Abelian gauge theories. We experimentally simulate the thermal states of SU(2) and SU(3) gauge theories at finite densities on a trapped-ion quantum computer using a variational method. This is achieved by introducing two features: Firstly, we add motional ancillae to the existing qubit register to efficiently prepare thermal probability distributions. Secondly, we introduce charge-singlet measurements to enforce colour-neutrality constraints. This work pioneers the quantum simulation of QCD at finite density and temperature for two and three colours, laying the foundation to explore QCD phenomena on quantum platforms.

Quantum information

Evidence for large baryonic feedback at low and intermediate redshifts from kinematic Sunyaev-Zel’dovich observations with ACT and DESI photometric galaxies

Recent advances in cosmological observations have provided an unprecedented opportunity to investigate the distribution of baryons relative to the underlying matter. In this work, we show that the gas is more extended than the dark matter, and the amount of baryonic feedback at $z \lesssim 1$ disfavors low-feedback models such as that of state-of-the-art hydrodynamical simulation IllustrisTNG compared with high-feedback models such as that of the original Illustris simulation. This has important implications for bridging the gap between theory and observations and understanding galaxy formation and evolution. Furthermore, a better grasp of the baryon-dark matter link is critical to future cosmological analyses, which are currently impeded by our limited knowledge of baryonic feedback. Here, we measure the kinematic Sunyaev-Zel'dovich (kSZ) effect from the Atacama Cosmology Telescope (ACT), stacked on the luminous red galaxy (LRG) sample of the Dark Energy Spectroscopic Instrument (DESI) imaging survey. This is the first analysis to use photometric redshifts for reconstructing galaxy velocities. Due to the large number of galaxies comprising the DESI imaging survey, this is the highest signal-to-noise stacked kSZ measurement to date: we detect the signal at 13$σ$, finding strong evidence that the gas is more spread out than the dark matter, as well as a preference for larger feedback compared to some commonly used state-of-the-art hydrodynamical simulations. Here, our work opens up the possibility of recalibrating large hydrodynamical simulations using the kSZ effect. In addition, our findings highlight the importance of properly accounting for baryonic feedback with future surveys such as LSST through direct probes such as the kSZ, and shed light on long-standing enigmas in astrophysics, such as the “missing baryon” problem.

79 ASTRONOMY AND ASTROPHYSICS

CASM Monte Carlo: Calculations of the thermodynamic and kinetic properties of complex multicomponent crystals

Monte Carlo techniques play a central role in statistical mechanics approaches that connect macroscopic thermodynamic and kinetic properties to the electronic structure of a material. This paper describes the implementation of Monte Carlo techniques for the study of multicomponent crystalline materials within the Clusters Approach to Statistical Mechanics (CASM) software suite, and demonstrates their use in model systems to calculate free energies and kinetic coefficients, study phase transitions, and construct phase diagrams from first principles. Many crystal structures are complex, with multiple sublattices occupied by differing sets of chemical species, along with the presence of vacancies or interstitial species. This imposes constraints on concentration variables, the form of thermodynamic potentials, and the values of kinetic transport coefficients. The framework used by CASM to formulate thermodynamic potentials and kinetic transport coefficients accounting for arbitrarily complex crystal structures is presented and demonstrated with examples of increasing complexity. Additionally, an overview of the capabilities of the CASM software specific to Monte Carlo methods is given, and a new CASM software package is introduced, casm-flow, which helps automate the setup, submission, management, and analysis of Monte Carlo simulations.

Cluster expansion

Carbon Utilization and Storage Partnership of the Western United States

This technical report documents research conducted under DOE Award No. DE-FE0031837 focused on evaluating the feasibility of carbon capture, utilization, and storage (CCUS) systems in the central and western United States. The project integrated geologic characterization, reservoir simulation, infrastructure modeling, and economic analysis to assess CO₂ storage potential near industrial sources and develop strategies for transport and sequestration. The work included subsurface modeling, risk assessment, monitoring and verification (MRV) planning, and evaluation of regulatory pathways such as EPA Underground Injection Control (UIC) Class VI permitting and IRS 45Q tax credit eligibility. Results demonstrate the viability of multiple storage approaches, including saline formations, enhanced coalbed methane recovery, and basalt mineralization, supported by data-driven workflows and regional analyses. The project also produced permitting templates, technology transfer activities, and stakeholder engagement efforts to support deployment readiness. These findings contribute to the development of scalable, economically viable CCUS systems and provide a repeatable framework for future carbon management projects.

20 FOSSIL-FUELED POWER PLANTS

Performance of Heterostructural TaC/AlGaN Schottky Diodes Based on First Principles Electronic Structure Properties

Advances in ultra-wide bandgap materials, such as high Al-content AlxGa1-xN (AlGaN), are essential for next generation power electronics, but the requirement for lattice matched substrates is currently a significant obstacle. Recently, conductive TaC has emerged as a promising virtual substrate for AlGaN heteroepitaxy, with wurtzite (0001) AlxGa1-xN lattice-matched to rocksalt (111) TaC at x ~ 0.5. Thus, understanding and controlling the electronic properties of the TaC/AlGaN interface is key for developing technological applications based on TaC/AlGaN devices. Using density functional theory and electronic structure calculations, we here investigate TaC/Al0.5Ga0.5N interfaces, where we include explicit alloy models in the slab calculations. We predict the Schottky barrier height and the electric field discontinuity resulting from interface charges. Considering all possible combinations of (Ta, C) substrate termination, (Al/Ga, N) nucleation, and (Al/Ga, N) polarity, we construct a chemical potential phase diagram to identify the stable interfaces that can be accessed through variation of the synthesis conditions. The predicted interface electronic properties are implemented in device performance simulations to demonstrate a practical design for a strain-free, high-efficiency TaC/AlGaN Schottky diode with a low barrier height and without interface charges, underscoring the potential of TaC as a substrate for ultra-wide bandgap devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC

Characterization of Flashback and Flame-Holding in a Jet-in-Crossflow Mixing Configuration With Methane–Hydrogen Fuel Blends

An approach that combines experimental and numerical analyses has been implemented to characterize the fundamentals of flashback events and flame-holding phenomena during high-hydrogen combustion in a jet-in-crossflow (JICF) configuration. Such flame dynamics are visualized experimentally using nanosecond (ns)-based hydroxyl planar laser-induced fluorescence (OH-PLIF) and chemiluminescence diagnostics techniques. The JICF burner has an optically accessible premixing tube allowing the optical diagnostics. The testing was conducted for varied premixer velocities (V) and equivalence ratio (ϕ) for 90–100% (H 2 , by mole) H 2 /CH 4 reactant mixtures at atmospheric temperature and pressure conditions. Two distinct flashback events were identified – conventional rich flashback and lean flashback, recorded while increasing ϕ and decreasing ϕ, respectively. The cause of lean flashback was attributed to lower momentum flux ratio which bends the jet sharply, closer toward the injection plane. The mean OH-PLIF images characterized the flame-holding behavior, where the flame was found to be stabilized on the leeward side only or on both windward and leeward sides as a lifted flame near the fuel port. A large eddy simulation (LES) with detailed chemistry combustion modeling approach was implemented along with an OH* submechanism, and it showed qualitative agreement with the integrated line-of-sight chemiluminescence results as well as the planar OH-PLIF measurements.

chemiluminescence diagnostic

Synthesis and investigation into explosive sensitivity for a series of new picramide explosives

Tailoring the molecular properties that govern energetic material sensitivity is essential to improve safety and help develop new energetic materials. Despite this need, understanding the complex chemistry and physics of explosive initiation and propagation is still a challenge. Recent work by our group has reinforced the view that explosive sensitivity under sub-shock conditions is connected to the strength of the weakest covalent bond in the molecule, that is, its “trigger linkage.” These correlations have been observed with different classes of energetic molecules and indicate that “trigger linkage” bond breaking, and heat of explosion are good indicators for the sensitivity trends. Herein we report the synthesis of aliphatic energetic materials with ethane, propane and neopentane backbones. Experimental and computational studies show that the trigger linkage model, based on results from quantum molecular dynamics simulations, correctly predicts trends observed in the impact sensitivity of the molecules. However, while the model predicts the impact sensitivities of the ethane series, the neopentane series has higher impact sensitivities than predicted, which is presumably influenced by crystal packing effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Solvent-Mediated Control of Nanocellulose Dispersion: An Integrated Computational and Experimental Investigation

Fibrillated cellulose derived from forestry feedstocks represents a renewable and high-strength materials platform for circular bioeconomies. However, its practical implementation is hindered by the irreversible aggregation of nanocellulose architectures, including cellulose nanofibers (CNFs). Solvent-based dispersion offers a simple and practical route to prevent CNF aggregation. Here, in this work, we integrate classical and enhanced sampling molecular dynamics (MD) simulations with experimental suspension rheology and atomic force microscopy (AFM) to elucidate how solvent environments tune CNF–CNF interactions and dispersion stability. CNF–CNF contact free energies computed from MD simulations reveal reduced aggregation in acetone/water, γ-valerolactone (GVL)/water, and tetrahydrofuran (THF)/water and pure acetone compared with pure water, reflecting stronger CNF-solvent relative to inter-CNF interactions. Correspondingly, CNF-solvent suspensions in these solvent systems exhibit stronger inter-fibril network structures and enhanced recovery compared to water, indicating improved CNF-solvent affinity. Liquid cell AFM imaging in acetone–water mixtures and in pure acetone further confirm the presence of well-dispersed CNFs. By combining multiscale computation with targeted experiments, this study establishes a rational framework for solvent design to achieve stable nanocellulose dispersions for high-strength biobased materials and efficient bioenergy conversion.

cellulose

Material-dependent photon ionizing radiation effects in Si and GaAs PIN diodes: A numerical investigation

We present a finite-element drift-diffusion-Poisson model in the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework to compare the radiation response of silicon (Si) and gallium arsenide (GaAs) PIN diodes under high-energy photon irradiation. The model solves coupled carrier continuity and Poisson’s equations with Shockley-Read-Hall recombination, and is verified against standard analytical J-V behavior. Using a simplified 1D geometry with ideal Ohmic contacts, we quantify device response under forward and reverse bias with a 100 MeV photon flux. Under forward bias, Si exhibits markedly greater radiation sensitivity than GaAs, including larger increases in current density, stronger local field and carrier-product perturbations, and higher recombination. Under reverse bias, GaAs shows larger radiation-induced photocurrent and broader current-density peaks near junctions, indicating an advantage for photodetection. Integrated steady-state recombination is consistently higher in Si across voltages. Under periodic photon pulses, GaAs produces higher-amplitude photoresponse and settles more rapidly than Si. These results highlight material-dependent trade-offs for radiation-tolerant, high-speed optoelectronics and provide guidance for selecting PIN architectures in aerospace, nuclear, and high-energy physics environments.

36 MATERIALS SCIENCE

End-To-End Decentralized Transmission Line Protection in IBR-Dominated Weak Grids Using Interpretable Data-Driven Methods

Traditional transmission line protection relies on predictable synchronous-based fault signatures, which frequently fail under the non-standard, current-limited fault characteristics of Inverter-Based Resources (IBRs). This study investigates how to achieve secure, communication-free fault isolation in IBR-dominated weak grids without relying on opaque, computationally heavy "black-box" machine learning algorithms. To address this, we propose a novel, standalone, and inherently interpretable data-driven protection framework. Unlike centralized methods requiring multi-terminal communication, this decentralized approach relies solely on local measurements using a hierarchical linear-kernel Support Vector Machine (SVM). The methodology decomposes the protection task into four sequential stages that mimic traditional protection elements: fault detection and fault direction identification, fault type classification, zone classification, and location estimation. This multi-stage architecture allows for specialized feature engineering at each stage, combining high computational efficiency with logic traceability. The framework's end-to-end performance was validated via C-code and PSCAD/EMTDC co-simulation, utilizing a real-world utility network and an OEM black-box IBR model. The proposed relay achieves 97.2% overall accuracy and provides a reliable trip decision within a 2.5-cycle window. The results confirm 100% accuracy in fundamental fault detection, reliable zone selectivity across low to moderate fault resistances, and robust security against non-fault transients, proving its immediate viability for integration into commercial numerical relays.

24 POWER TRANSMISSION AND DISTRIBUTION

Dust Survival in Galactic Winds

This repository contains three-dimensional volumetric data from an Eulerian hydrodynamical simulation (conducted on a uniform Cartesian grid) generated by the Cholla hydrodynamics code. The datasets contain snapshots (full-grid, projections, and slices) in the HDF5 format of a multi-phase medium in which a hot, diffuse, dust-free background wind accelerates a cool, dense cloud of gas and dust. This scenario is intended to represent a supernova-driven galactic outflow, in which hot supernova winds are thought to accelerate cool interstellar medium material out of the galactic disk into the surrounding circumgalactic medium. There are three separate datasets for simulations corresponding to three cloud evolutionary scenarios: long-term cloud survival (surv), marginal cloud survival (disr), and cloud destruction (dest). Projection and slice images of the simulations are also included in this repository.

79 ASTRONOMY AND ASTROPHYSICS

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

Laboratory Development of a Pot Calcination Process for Converting Liquid Wastes to Solids

Simulated Darex, Purex, Thorex, and TBP-25 wastes were batch-evaporated and calcined to solids. The weight of residue was decreased to ~ 8% of the original waste for Darex, to ~ 4% for Purex, to ~ 2% for Thorex, and ~ 7% for TBP-25 by calcination to 1200°C. Semicontinuous evaporation and calcination to solids at 900°C of Darex and Purex wastes gave volume reduction factors of ~ 8 and 7 to 10, respectively. The nitrate contents of the residues from batch calcination to 800°C were from ~ 0.07 to 0.5 wt % while the nitrate contents of the residues from semicontinuous calcination to 900°C were from ~ 0.1 to 0.7 wt %. Sodium, calcium, and magnesium additives to Purex waste decreased the percent of sulfate volatilized into the condensate from ~ 30% to <0.5%. Replacement of the atmosphere above the waste with nitric oxide decreased ruthenium volatility from 50 to 60% of that originally present in Purex waste to 0.5 to 3.5%. The thermal conductivities for the calcined wastes, measured in situ, were all >0.1 Btu/hr ft °F at ~ 400°F and increased almost linearly with increasing temperature to >0.3 Btu/hr ft °F at ~ 1600°F in all cases studied.

052001* -- Nuclear Fuels-- Waste Processing

Full-core high-burnup BWR LOCA fuel performance analysis and FFRD susceptibility

The susceptibility of the boiling water reactor (BWR) Limerick Unit 1 to fuel fragmentation, relocation, and dispersal during a postulated large-break loss-of-coolant accident (LBLOCA) was calculated using a multiphysics framework. The simulations include full-core, rod-resolved neutronic, thermal hydraulic, and fuel performance models using the VERA, TRACE, and BISON codes. This work focused on the transient BISON simulations, which include both the normal operation and LBLOCA periods in the same simulations. Cladding integrity was assessed using two correlations that are included with BISON. make page break Several new BWR-specific features were recently added to BISON. This work represents the first time these features have been included in a core-scale set of simulations. This study hence evaluates the performance of these new models for an operating reactor with realistic operating conditions. Simulation results showed that cladding integrity was maintained (i.e., no rods burst). Finally, future work to improve BWR and PWR predictions using this framework is suggested.

BISON

Nanoscopic Imaging of Self-Propelled Ultrasmall Catalytic Nanomotors

Ultrasmall nanomotors (<100 nm) are highly desirable nanomachines for their size-specific advantages over their larger counterparts in applications spanning nanomedicine, directed assembly, active sensing, and environmental remediation. While there are extensive studies on motors larger than 100 nm, the design and understanding of ultrasmall nanomotors have been scant due to the lack of high-resolution imaging of their propelled motions with orientation and shape details resolved. Here, we report the imaging of the propelled motions of catalytically powered ultrasmall nanomotors─hundreds of them─at the nanometer resolution using liquid-phase transmission electron microscopy. These nanomotors are Pt nanoparticles of asymmetric shapes (“tadpoles” and “boomerangs”), which are colloidally synthesized and observed to be fueled by the catalyzed decomposition of NaBH4 in solution. Statistical analysis of the orientation and position trajectories of fueled and unfueled motors, coupled with finite element simulation, reveals that the shape asymmetry alone is sufficient to induce local chemical concentration gradient and self-diffusiophoresis to act against random Brownian motion. Our work elucidates the colloidal design and fundamental forces involved in the motions of ultrasmall nanomotors, which hold promise as active nanomachines to perform tasks in confined environments such as drug delivery and chemical sensing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH