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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 127 records · Page 7

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NASA NTRS1976

Human dynamic orientation model applied to motion simulation

The Ormsby model of dynamic orientation, in the form of a discrete time computer program was used to predict non-visually induced sensations during an idealized coordinated aircraft turn. To predict simulation fidelity, the Ormsby model was used to assign penalties for incorrect attitude and angular rate perceptions. It was determined that a three rotational degree of freedom simulation should remain faithful to attitude perception even at the expense of incorrect angular rate sensations. Implementing this strategy, a simulation profile for the idealized turn was designed for a Link GAT-1 trainer. A simple optokinetic display was added to improve the fidelity of roll rate sensations.

Borah, J. D.↗

NASA NTRS1979

Short term magnetospheric particle variations (1 minute T 1 day), appendix 1

A schematic representation of the generation and propagation processes for energetic particles of concern in solar terrestrial predictions is given. Particle precipitation at low, mid, and high altitudes is discussed with emphasis on prediction techniques. Methods given for testing of such techniques include traditional collaborations, enhanced collaborations, simulated prediction schemes, and field tests.

Higbie, P. R.↗

NASA NTRS1986

Numerical simulations of comets - Predictions for Comet Giacobini-Zinner

Simulations of Comet Giacobini-Zinner's interaction with solar wind are described and results are presented. The simulations are carried out via the numerical solution of the ideal MHD equations as an initial value problem in a uniform solar wind. The calculations are performed on a Cartesian mesh centered at the comet. Results reveal that the first significant modifications of the solar wind along the ISEE/ICE trajectory will occur 100,000 km from the solar wind comet axis.

Fedder, J. A.↗

NASA NTRS2004

HiPEP Ion Optics System Evaluation Using Gridlets

Experimental measurements are presented for sub-scale ion optics systems comprised of 7 and 19 aperture pairs with geometrical features that are similar to the HiPEP ion optics system. Effects of hole diameter and grid-to-grid spacing are presented as functions of applied voltage and beamlet current. Recommendations are made for the beamlet current range where the ion optics system can be safely operated without experiencing direct impingement of high energy ions on the accelerator grid surface. Measurements are also presented of the accelerator grid voltage where beam plasma electrons backstream through the ion optics system. Results of numerical simulations obtained with the ffx code are compared to both the impingement limit and backstreaming measurements. An emphasis is placed on identifying differences between measurements and simulation predictions to highlight areas where more research is needed. Relatively large effects are observed in simulations when the discharge chamber plasma properties and ion optics geometry are varied. Parameters investigated using simulations include the applied voltages, grid spacing, hole-to-hole spacing, doubles-to-singles ratio, plasma potential, and electron temperature; and estimates are provided for the sensitivity of impingement limits on these parameters.

Willliams, John D.↗

NASA NTRS2013

Damping Effects of Drogue Parachutes on Orion Crew Module Dynamics

Currently, simulation predictions of the Orion Crew Module (CM) dynamics with drogue parachutes deployed are under-predicting the amount of damping as seen in free-flight tests. The Apollo Legacy Chute Damping model has been resurrected and applied to the Orion system. The legacy model has been applied to predict CM damping under drogue parachutes for both Vertical Spin Tunnel free flights and the Pad Abort-1 flight test. Comparisons between the legacy Apollo prediction method and test data are favorable. A key hypothesis in the Apollo legacy drogue damping analysis is that the drogue parachutes' net load vector aligns with the CM drogue attachment point velocity vector. This assumption seems reasonable and produces good results, but has never been quantitatively proven. The wake of the CM influences the drogue parachutes, which makes performance predictions of the parachutes difficult. Many of these effects are not currently modeled in the simulations. A forced oscillation test of the CM with parachutes was conducted in the NASA LaRC 20-Ft Vertical Spin Tunnel (VST) to gather additional data to validate and refine the Apollo legacy drogue model. A second loads balance was added to the original Orion VST model to measure the drogue parachute loads independently of the CM. The objective of the test was to identify the contribution of the drogues to CM damping and provide additional information to quantify wake effects and the interactions between the CM and parachutes. The drogue parachute force vector was shown to be highly dependent on the CM wake characteristics. Based on these wind tunnel test data, the Apollo Legacy Chute Damping model was determined to be a sufficient approximation of the parachute dynamics in relationship to the CM dynamics for preliminary entry vehicle system design. More wake effects should be included to better model the system. These results are being used to improve simulation model fidelity of CM flight with drogues deployed, which has been identified by the project as key to a successful Orion Critical Design Review.

Aubuchon, Vanessa V.↗

DOE OSTI2026

Comparison between Alcator C-Mod ICRF experiments and 3D full wave simulations

Reliable modeling of ion cyclotron range of frequencies (ICRF) antenna performance is essential for interpreting present experiments and guiding the design of future reactors. In this work, a 3D model of the Alcator C-Mod field-aligned antenna is implemented in the Petra-M finite-element framework [S. Shiraiwa et al 2023 Nucl. Fusion 63 026024] and benchmarked against experimental results. Four experimental cases are examined. First, the simulated rectified sheath potentials on the antenna limiters are compared with measurements from a power tapering experiment. Second, proof-of-principle far-field sheath simulations are performed. In scenarios with low single-pass absorption, simulations predict enhanced sheath potentials on a distant poloidal limiter in the far field of the antenna, consistent with experimental observations. Third, the simulated antenna loading during edge localized modes follows experimental trends and appears to be dominated by the density gradient at the pedestal. Finally, Petra-M predicts the unintended excitation of high-$k$ ∥ modes during monopole phasing operation, in agreement with experimental evidence of poor wave coupling and accessibility to the plasma core. Overall, reasonable agreement is found between the simulations and experiments. At the same time, areas of imperfect agreement are identified. These provide important guidance on the limits of the current state-of-the-art modeling, which should be kept in mind when using it as a predictive tool for future reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1984

Predictions of Cockpit Simulator Experimental Outcome Using System Models

This study involved predicting the outcome of a cockpit simulator experiment where pilots used cockpit displays of traffic information (CDTI) to establish and maintain in-trail spacing behind a lead aircraft during approach. The experiments were run on the NASA Ames Research Center multicab cockpit simulator facility. Prior to the experiments, a mathematical model of the pilot/aircraft/CDTI flight system was developed which included relative in-trail and vertical dynamics between aircraft in the approach string. This model was used to construct a digital simulation of the string dynamics including response to initial position errors. The model was then used to predict the outcome of the in-trail following cockpit simulator experiments. Outcome included performance and sensitivity to different separation criteria. The experimental results were then used to evaluate the model and its prediction accuracy. Lessons learned in this modeling and prediction study are noted.

Sorensen, J. A.↗

NASA NTRS2015

The Integrated Medical Model: A Probabilistic Simulation Model for Predicting In-Flight Medical Risks

The Integrated Medical Model (IMM) is a probabilistic model that uses simulation to predict mission medical risk. Given a specific mission and crew scenario, medical events are simulated using Monte Carlo methodology to provide estimates of resource utilization, probability of evacuation, probability of loss of crew, and the amount of mission time lost due to illness. Mission and crew scenarios are defined by mission length, extravehicular activity (EVA) schedule, and crew characteristics including: sex, coronary artery calcium score, contacts, dental crowns, history of abdominal surgery, and EVA eligibility. The Integrated Medical Evidence Database (iMED) houses the model inputs for one hundred medical conditions using in-flight, analog, and terrestrial medical data. Inputs include incidence, event durations, resource utilization, and crew functional impairment. Severity of conditions is addressed by defining statistical distributions on the dichotomized best and worst-case scenarios for each condition. The outcome distributions for conditions are bounded by the treatment extremes of the fully treated scenario in which all required resources are available and the untreated scenario in which no required resources are available. Upon occurrence of a simulated medical event, treatment availability is assessed, and outcomes are generated depending on the status of the affected crewmember at the time of onset, including any pre-existing functional impairments or ongoing treatment of concurrent conditions. The main IMM outcomes, including probability of evacuation and loss of crew life, time lost due to medical events, and resource utilization, are useful in informing mission planning decisions. To date, the IMM has been used to assess mission-specific risks with and without certain crewmember characteristics, to determine the impact of eliminating certain resources from the mission medical kit, and to design medical kits that maximally benefit crew health while meeting mass and volume constraints.

Risk Analysis↗

NASA NTRS1984

Control system testing

A three stage process of ground testing of the Space Telescope Pointing Control System is used for verification prior to on-orbit operation. First, development tests are conducted in a laboratory environment using flight/engineering model control sensor and actuators configured with an engineering model of the flight computer and data management system breadboards. These development tests validate the results of computer simulations predicting control system performance. Integration tests bring together flight system elements and software interfaced to a software simulation of vehicle dynamics to confirm closed loop performance. The final ground test phase, flight systems testing, is conducted on the fully assembled Space Telescope, verifies interfaces with the Fine Guidance Sensors and includes a thermal vacuum testing period. During the final test phase, the Point Control System is exercised with the dynamics simulator running in real time.

Whittler, W. H.↗

NASA NTRS2014

Chandra Contaminant Migration Model

High volatility cleans OBFs and low volatility produces a high build-up at OBF centers; only a narrow (factor of 2 or less) volatility range produces the observed spatial pattern. Simulations predict less accumulation above outer S-array CCDs; this may explain, in part, gratings/imaging C/MnL discrepancies. Simulations produce a change in center accumulation due solely to DH heater ON/OFF temperature change; but a 2nd contaminant and perhaps a change in source rate is also required. Emissivity E may depend on thickness; another model parameter. Additional physics, e.g., surface migration, is not warranted at this time. At t approx. 14 yrs, model produced 0.22 grams of contaminant, 0.085 grams remaining within ACIS cavity; 7 percent (6mg) on OBFs.

Swartz, Douglas A.↗

DOE OSTI2026

Computational modeling of graphite degradation in molten salt reactors: Role of infiltration

Molten salt reactors (MSRs) often employ graphite as a moderator and reflector. An important challenge for deploying graphite in these reactors is that, due to limited experimental data, our understanding of graphite’s structural integrity in molten salt environments remains incomplete. Here, this study addresses heat generation from fuel-bearing salt that has infiltrated open pores in the graphite, driven primarily by pressure differentials. This is one of multiple identified physical and chemical mechanisms through which molten salt could potentially degrade graphite. Thermally driven stresses are quantified using the Molten-Salt Reactor Experiment (MSRE) graphite moderator elements as a case study. Finite element simulations predict stress distributions at varying infiltration levels, indicating that thermal stresses increase with higher infiltration. Rare-event simulations using the parallel subset simulation framework identify the combinations and corresponding ranges of input parameters that lead to stresses above a specified threshold. In particular, combinations involving high infiltration amounts, high power density, and low thermal conductivity tend to induce the highest stresses. Under the inputs and assumptions considered in this work, the magnitudes of the thermally driven stresses are quite low, with a very low likelihood of causing failure due to exceeding the graphite’s tensile strength. Additionally, rare-event simulations were performed for two more scenarios: a scaled-up moderator geometry and a localized hotspot in the original geometry. Both cases resulted in increased susceptibility to failure, though not to a detrimental extent. Furthermore, the combined effects of irradiation and infiltration-induced thermal stresses were evaluated. The results showed that thermal stresses from infiltration were negligible compared to those caused by irradiation. The findings of such a study are inherently component-specific, but the methodology presented here could be used for similar assessments of salt-infiltration effects in other graphite components.

36 - MATERIALS SCIENCE↗

DOE OSTI2025

MBX V1.2: Accelerating Data-Driven Many-Body Molecular Dynamics Simulations

The MBX software provides an advanced platform for molecular dynamics simulations, leveraging state-of-the-art MB-pol and MB-nrg data-driven many-body potential energy functions. Developed over the past decade, these potential energy functions integrate physics-based and machine-learned many-body terms trained on electronic structure data calculated at the "gold standard" coupled-cluster level of theory. Recent advancements in MBX have focused on optimizing its performance, resulting in the release of MBX v1.2. While the inherently many-body nature of MB-pol and MB-nrg ensures high accuracy, it poses computational challenges. MBX v1.2 addresses these challenges with significant performance improvements, including enhanced parallelism that fully harnesses the power of modern multicore CPUs. In conclusion, these advancements enable simulations on nanosecond time scales for condensed-phase systems, significantly expanding the scope of high-accuracy, predictive simulations of complex molecular systems powered by data-driven many-body potential energy functions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

MPEX AI Digital Twins

All magnetically confined plasma fusion power plant concepts (Tokamak, Spherical Tokamak, Stellarator, Mirror, ...) must exhaust the heat and plasma from the core confinement region to the material walls. The primary channel for this exhaust is through a plasma divertor which directs plasma along open magnetic field lines to a material target. The Material Plasma Exposure eXperiment (MPEX) illustrated in Figure 1, is a high-power, steady-state linear plasma device designed to produce the plasma material interaction (PMI) conditions of the divertor of future magnetic confinement fusion power plants: energy flux 20MW/m 2 , ion fluence 1031/m 2 , pulse duration 106 sec. These goals of plasma exposure in MPEX are well beyond those achieved in magnetic fusion experimental devices. Successfully achieving these high power steady state conditions for long pulses requires operational control of the heating and particle sources and the plasma flux to the walls and target. The MPEX AI Hot Spot Controller, proposed in this project, will help achieve the operational milestones of MPEX. The MPEX device will begin commissioning at the end of FY26. A smaller proto-MPEX was operated for 14,666 plasma discharges and will resume operation in September of 2025 as proto-MPEX-lite, with reduced capability, to test a new window for the Helicon plasma source. The proto-MPEX data has undergone surrogate modeling with machine learning methods (R. Archibald, 2022 IEEE International Conference on Big Data). This proto-MPEX data will be used to begin development of the AI digital twins described in this white paper. The scientific mission of MPEX is to qualify materials of different composition for use in the high energy and plasma flux conditions of a fusion power plant. The materials exposed in MPEX will in some cases be exposed to high neutron fluxes at other ORNL facilities to measure the changes to their PMI properties. The targets exposed in MPEX will be transported under vacuum to a Surface Analysis Station (SAS). The SAS will be equipped with the following diagnostics: Focused Ion Beam (FIB) for trench milling, 100-400 angstrom resolution scanning electron microscope (SEM), surface mapping x-ray spectrometer, high resolution camera, and a future upgrade to a laser induced breakdown spectroscopy quadruple mass spectrometer (LIBS-QMS). The MPEX experiments will generate diverse pre- and post-exposure measurement data of detailed material properties down to the crystal grain level in 3D for post-exposure assessment of PMI damage (e.g. cracking, melting, erosion and redeposition of the material). Physics models for the PMI, and how the material composition and manufacturing impact its performance under high energy plasma exposure, need to be validated with MPEX data to guide the selection of new candidate materials. Our vision for the MPEX AI Digital Twins project is to supply experimental and physics model simulation data to train Artificial Intelligence (AI) models for data processing, analysis, operational control, PMI and materials simulation to maximize the scientific output of the MPEX device. Ultimately, an AI digital twin of MPEX material assessment metrics for tested and synthetic material types with simulated PMI will be trained by the AI Modeling Teams on the experimental and physics simulation data submitted to the American Science Cloud by this project. A purely empirical search for the best material is inefficient given the finite number of samples that can be tested on MPEX. In order to expand the material properties database for training the MPEX Material Assessment AI Digital Twin, and to gain physics understanding of the PMI processes, physics models of the material properties and PMI processes are required. The physics simulations provide detailed simulation data, like impact angles for plasma ions, sputtering yields, transport of the ionized sputtered target material in the plasma, and redeposition locations. This simulation data expands the measurement data for deeper physics understanding. The experimental data is essential to validate the PMI and material structure simulation models. The validated models can then be used to generate new simulation data of MPEX material assessments for synthetic material compositions that have not been exposed in MPEX. These predictive simulations, plus the whole experimental dataset, will be used to train the MPEX Material Assessment AI Digital Twin allowing a rapid generative AI search for new materials with reduced PMI damage by interpolating the domain of the training set. These new optimum materials can be simulated with the physics codes and/or tested in MPEX. The ability of AI neural networks to interpolate multi-dimensional parameter spaces and generate virtual data is exploited for a more efficient search for optimum materials. The advent of the Transformational AI Models Consortium (TAIMC) is an opportunity to engage with state of the art private and public AI developers to achieve the goals of the AI digital twins and AI accelerated physics models proposed in this project. Our partners at ORNL from the Advance Scientific Computing Research (ASCR) organization will collaborate in accelerating the integrated plasma material interaction simulation framework. This simulation framework will provide a platform for generating simulation data across a range of physical fidelities, including hybrid methods that produce multi-fidelity results. This data will be leveraged for AI model development, both for generation of surrogates and the automation of simulation campaigns. A part of the research below will include collaborative efforts with the TAIMC to (i) adapt data storage approaches to ensure AI-readiness, (ii) provide a protypical exemplar to inform and exercise constructed workflows, and (iii) generate and share data, using the TAIMC unified AI data standard, for foundational models that will be trained from multiple sources across the DOE complex. We will also collaborate with the TAIMC, as well as the planned AI modeling teams, to develop approaches for reducing the cost of data generation. These include tailored multi-fidelity approaches as well as fine-tuning strategies to augment general, large-scale foundational models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRSDate not supplied

Computational Prediction of Broadband Noise from a Representative Unmanned Aerial System Rotor

This work details the application of a lattice-Boltzmann method–very-large-eddy simulation (LBM-VLES) employed by the software suite, PowerFLOW. This LBM-VLES simulation predicted the aeroacoustic noise emanating from a representative, small unmanned aircraft system rotor, namely, the DJI-9450 in a hover condition. Predicted total aerodynamic loading as well as 2D aerodynamic loading along discrete spanwise sections of a rotor blade were compared to lower fidelity predictions and experimental results acquired in the Structural Acoustic Loads and Transmission anechoic chamber facility at the NASA Langley Research Center. The total acoustic spectra were decomposed into tonal and broadband components, which showed that broadband noise was a dominant contributor above 1 kHz for this rotor. These data were then compared to experimentally acquired data, showing good agreement up to approximately 11 kHz. Above 11 kHz, however, a grid sensitivity study showed dependency of the highest resolvable frequency on the spatial resolution of the computational domain, explaining the roll off in predicted data. Individual broadband noise sources were further investigated by calculating one-third octave sound pressure levels of the unsteady pressure fluctuations acting on the rotor, providing evidence that blade self-noise was the prominent noise source. Using these results, blade wake interaction noise was seen to be negligible for this particular rotor, which was further validated by calculating blade vortex miss distances and comparing to theory.

Christopher S. Thurman↗

DOE OSTI2026

Ultra-low thermal resistance and pressure drop copper and copper-tungsten diamond-shaped pin fin cold plates for liquid cooling of electronics

Modern and future data centers face increasing cooling challenges due to increasing chip thermal design power and die size, along with the need to reduce energy consumption used for cooling. High performance cooling solutions that maintain a low chip junction temperature are needed to ensure electronics reliability. This work develops an ultra-low thermal resistance and low pressure drop 75 mm × 75 mm cold plate, intended for next-generation electronics cooling. The cold plate features an array of diamond-shaped pin fins and integrated copper tungsten heat spreader, selected for its low coefficient of thermal expansion which reduces thermomechanical deformation and allows for closer integration of the cold plate with silicon dies. Starting with 300 candidate designs, three-dimensional computational fluid dynamics simulations predict the thermal-hydraulic performance of cold plate subsections. The highest performing geometries are evaluated with high fidelity simulations. Four cold plates are manufactured for experiments: three with diamond-shaped pin fins and one with straights fins for comparison purposes. The cold plates are fabricated from copper-tungsten (CuW), copper (Cu), or aluminum-silicon-magnesium alloy (AlSi10Mg). The diamond-shaped pin fins achieve a roughly 15 % lower thermal resistance compared to the conventional straight fin microchannel. The highest performing design achieves a chip-to-coolant (including thermal interface material) thermal resistance of 9.0 K/kW in CuW and 6.9 K/kW in Cu under a 1 kW heat load with an inlet-to-outlet pressure drop of 9.0 kPa and water as the working fluid. This work demonstrates ultra-low thermal resistance and pressure drop cold plates for large die, high heat load applications, and shows that CuW is an attractive cold plate material for improved reliability in next generation data center cooling.

Coefficient of thermal expansion↗

DOE OSTI2024

Charged particle transport coefficient challenges in high energy density plasmas

High energy density physics (HEDP) and inertial confinement fusion (ICF) research typically relies on computational modeling using radiation-hydrodynamics codes in order to design experiments and understand their results. These tools, in turn, rely on numerous charged particle transport and relaxation coefficients to account for laser energy absorption, viscous dissipation, mass transport, thermal conduction, electrical conduction, non-local ion (including charged fusion product) transport, non-local electron transport, magnetohydrodynamics, multi-ion-species thermalization, and electron-ion equilibration. In many situations, these coefficients couple to other physics, such as imposed or self-generated magnetic fields. Furthermore, how these coefficients combine are sensitive to plasma conditions as well as how materials are distributed within a computational cell. Uncertainties in these coefficients and how they couple to other physics could explain many of the discrepancies between simulation predictions and experimental results that persist in even the most detailed calculations. This paper reviews the challenges faced by radiation-hydrodynamics in predicting the results of HEDP and ICF experiments with regard to these and other physics models typically included in simulation codes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2025

Design and Simulation of Greatly Improved Future Generation 4H-SiC JFET-R Integrated Circuits for Prolonged 500 °C Operation

This work compares design layouts and circuit simulations of the next two prototype NASA Glenn SiC JFET-R IC fabrication runs designated “IC Gen. 12” and “IC Gen. 13”. Even though both generations employ the same physical JFET gate length and chip size, SPICE simulations predict drastic improvements to IC capabilities and performance metrics for Gen. 13 over Gen. 12. The main factors behind simulated performance differences are thinner n-channel layer leading to reduced operating voltages and switch to stepper-based photolithography that enables roughly 4-fold layout area reductions for functionally identical circuit blocks.

Silicon Carbide↗

NASA NTRSDate not supplied

A Hybrid CFD/Engineering Model Tool for Lunar Lander Surface Erosion Prediction

Plume-Surface Interaction (PSI) between lander engine plumes and landing area regolith poses risks to the landers and space exploration missions through view obscuration and high-energy ejecta impacts from eroded particle clouds and vehicle tilting from plume-induced craters. To address these risks, NASA MSFC Fluid Dynamics Branch (ER42) has developed a cascade of predictive simulation capabilities for PSI, including the recent development of a hybrid CFD/engineering model tool that allows for rapid PSI simulations with a descending/ascending vehicle and an eroding surface. The development of this fully-coupled, moving body/eroding surface simulation capability is detailed along with a demonstration of the tool’s capabilities on the Apollo 12 Lunar Module landing. Predictions of eroded mass flow rates as a function of time are verified against Apollo 12 flight data, from which the developed, viscous erosion model has been calibrated.

Plume Surface Interaction↗