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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Theoretical Technology Research for the International Solar Terrestrial Physics (ISTP) Program

During the last four years the UCLA (University of California, Los Angeles) IGPP (Institute of Geophysics and Planetary Physics) Space Plasma Simulation Group has continued its theoretical effort to develop a Mission Oriented Theory (MOT) for the International Solar Terrestrial Physics (ISTP) program. This effort has been based on a combination of approaches: analytical theory, large-scale kinetic (LSK) calculations, global magnetohydrodynamic (MHD) simulations and self-consistent plasma kinetic (SCK) simulations. These models have been used to formulate a global interpretation of local measurements made by the ISTP spacecraft. The regions of applications of the MOT cover most of the magnetosphere: solar wind, low- and high- latitude magnetospheric boundary, near-Earth and distant magnetotail, and auroral region. Most recent investigations include: plasma processes in the electron foreshock, response of the magnetospheric cusp, particle entry in the magnetosphere, sources of observed distribution functions in the magnetotail, transport of oxygen ions, self-consistent evolution of the magnetotail, substorm studies, effects of explosive reconnection, and auroral acceleration simulations. A complete list of the activities completed under the grant follow.

Ashour-Abdalla, Maha↗
DOE OSTI2025

Stable Simulation of the Community Atmosphere Model Using Machine‐Learning Physical Parameterization Trained With Experience Replay

In recent years, machine learning (ML) models have been used to improve physical parameterizations of general circulation models (GCMs). A significant challenge of integrating ML models into GCMs is the online instability when they are coupled for long‐term simulation. We present a new strategy that demonstrates robust online stability when the physical parameterization package of an atmospheric GCM is replaced by a deep ML model. The method uses experience replay with a multistep training scheme of the ML model in which the model's own output at the previous time step is used in the training. Predicted physics tendencies in the replay buffer with the most recent errors in the training iterations are reused, making the ML model learn from its own errors. The training method reduces the gap between the offline and online environments of the ML model. The method is used to train the ML model as the physical parameterization of the Community Atmosphere Model (CAM5) with training data from the Multi‐scale Modeling Framework high resolution simulations. Three 6‐year online simulations of the CAM5 are carried out by using the ML physics package. The simulated spatial distributions of precipitation, surface temperature and zonally averaged atmospheric fields demonstrate overall better accuracy than that of the standard CAM5 and benchmark model even without the use of additional physical constraints or tuning. This work is the first to demonstrate a solution to address the online instability problem in climate modeling with ML physics by using experience replay.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

Observing Planets and Small Bodies in Sputtered High Energy Atom (SHEA) Fluxes

The evolution of the surfaces of bodies unprotected by either strong magnetic fields or thick atmospheres in the Solar System is caused by various processes, induced by photons, energetic ions and micrometeoroids. Among these processes, the continuous bombardment of the solar wind or energetic magnetospheric ions onto the bodies may significantly affect their surfaces, with implications for their evolution. Ion precipitation produces neutral atom releases into the exosphere through ion sputtering, with velocity distribution extending well above the particle escape limits. We refer to this component of the surface ejecta as sputtered high-energy atoms (SHEA). The use of ion sputtering emission for studying the interaction of exposed bodies (EB) with ion environments is described here. Remote sensing in SHEA in the vicinity of EB can provide mapping of the bodies exposed to ion sputtering action with temporal and mass resolution. This paper speculates on the possibility of performing remote sensing of exposed bodies using SHEA The evolution of the surfaces of bodies unprotected by either strong magnetic fields or thick atmospheres in the Solar System is caused by various processes, induced by photons, energetic ions and micrometeoroids. Among these processes, the continuous bombardment of the solar wind or energetic magnetospheric ions onto the bodies may significantly affect their surfaces, with implications for their evolution. Ion precipitation produces neutral atom releases into the exosphere through ion sputtering, with velocity distribution extending well above the particle escape limits. We refer to this component of the surface ejecta as sputtered high-energy atoms (SHEA). The use of ion sputtering emission for studying the interaction of exposed bodies (EB) with ion environments is described here. Remote sensing in SHEA in the vicinity of EB can provide mapping of the bodies exposed to ion sputtering action with temporal and mass resolution. This paper speculates on the possibility of performing remote sensing of exposed bodies using SHEA and suggests the need for quantitative results from laboratory simulations and molecular physic modeling in order to understand SHEA data from planetary missions. In the Appendix, referenced computer simulations using existing sputtering data are reviewed.

Milillo, A.↗
NASA NTRSDate not supplied

Development of Computational Materials Workflows for Additively Manufactured Metallic Materials to Enable Accelerated Prediction of Fatigue Performance

The maturation of computational materials approaches for fatigue performance prediction in a qualification and certification process is stifled by the ability to validate complex, microstructure-based simulations. Such a validation strategy bears immediate challenges including generating accurate virtual microstructures, efficiently solving physics-based mechanical simulations over relevant spatial and temporal scales, and acquiring high-fidelity calibration and validation data at the appropriate length scale. This presentation will overview these common challenges and present a case study to demonstrate a computational materials workflow for additively manufactured metallic materials. In this study, process-specific defects are characterized using segmented X-Ray micro-computed tomography measurements and overlaid on virtual microstructures. Accelerated crystal plasticity-based fatigue simulations are performed to demonstrate cyclic evolution and localization of mechanical fields in the vicinity of defects in response to their precise spatial configuration. An example of how this computational materials workflow may support next-generation qualification is discussed.

computational materials↗
NASA NTRS2017

A Simulation Based Investigation of High Latency Space Systems Operations

This study was the first in a series of planned tests to use physics-based subsystem simulations to investigate the interactions between a spacecraft's crew and a ground-based mission control center for vehicle subsystem operations across long communication delays. The simulation models the life support system of a deep space habitat. It contains models of an environmental control and life support system, an electrical power system, an active thermal control systems, and crew metabolic functions. The simulation has three interfaces: 1) a real-time crew interface that can be use to monitor and control the subsystems; 2) a mission control center interface with data transport delays up to 15 minute each way; and 3) a real-time simulation test conductor interface used to insert subsystem malfunctions and observe the interactions between the crew, ground, and simulated vehicle. The study was conducted at the 21st NASA Extreme Environment Mission Operations (NEEMO) mission. The NEEMO crew and ground support team performed a number of relevant deep space mission scenarios that included both nominal activities and activities with system malfunctions. While this initial test sequence was focused on test infrastructure and procedures development, the data collected in the study already indicate that long communication delays have notable impacts on the operation of deep space systems. For future human missions beyond cis-lunar, NASA will need to design systems and support tools to meet these challenges. These will be used to train the crew to handle critical malfunctions on their own, to predict malfunctions and assist with vehicle operations. Subsequent more detailed and involved studies will be conducted to continue advancing NASA's understanding of space systems operations across long communications delays.

Li, Zu Qun↗
NASA NTRS2017

A Simulation Based Investigation of High Latency Space Systems Operations

This study was the first in a series of planned tests to use physics-based subsystem simulations to investigate the interactions between a spacecraft's crew and a ground-based mission control center for vehicle subsystem operations across long communication delays. The simulation models the life support system of a deep space habitat. It contains models of an environmental control and life support system, an electrical power system, an active thermal control system, and crew metabolic functions. The simulation has three interfaces: 1) a real-time crew interface that can be use to monitor and control the subsystems; 2) a mission control center interface with data transport delays up to 15 minute each way; and 3) a real-time simulation test conductor interface used to insert subsystem malfunctions and observe the interactions between the crew, ground, and simulated vehicle. The study was conducted at the 21st NASA Extreme Environment Mission Operations (NEEMO) mission. The NEEMO crew and ground support team performed a number of relevant deep space mission scenarios that included both nominal activities and activities with system malfunctions. While this initial test sequence was focused on test infrastructure and procedures development, the data collected in the study already indicate that long communication delays have notable impacts on the operation of deep space systems. For future human missions beyond cis-lunar, NASA will need to design systems and support tools to meet these challenges. These will be used to train the crew to handle critical malfunctions on their own, to predict malfunctions, and to assist with vehicle operations. Subsequent more detailed and involved studies will be conducted to continue advancing NASA's understanding of space systems operations across long communications delays.

Li, Zu Qun↗
DOE OSTI2026

Overview of the physics basis for the ARC fusion power plant

Commonwealth Fusion Systems plans to build ARC as the first fusion power plant at a site in Chesterfield County, Virginia, USA by the early 2030s. We present an overview of analysis comprising the physics basis of the ARC V3A design, a high-magnetic-field tokamak with 𝐵 0 =11.4 T, 𝐼 𝑝 =12.0 MA, 𝑅 0 =4.62 m, 𝑎 =1.18 m. ARC V3A is designed to produce 𝑃 𝑓⁡𝑢⁢𝑠 ≈1.13 GW DT fusion power and deliver ⩾400 MW net electric power to the grid. This overview includes quantitative analysis of fundamental issues for design of and operational plasma scenarios for a tokamak power plant, and lays out the design targets and strategic choices for ARC, including empirical fusion performance projections, assessment of H-mode access, ion cyclotron resonance heating simulations, alpha particle physics and time-dependent full-pulse simulations. This is complemented by topical papers on fusion performance and transport, disruption physics, boundary physics and magnetohydrodynamic stability. Critically, these studies identify key model uncertainties and physics risks to be retired through SPARC operation. Due to the modular nature of ARC, early results from SPARC can be incorporated into the design of the first ARC as well as subsequent replacements of the ARC vacuum vessel.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2008

Under the Radar: Trials and Tribulations of Landing on Mars

The Mars Phoenix Mission requires a ground-sensing radar altimeter/ velocimeter to meet touchdown velocity requirements During Phase C/D, the radar underwent a testing triptych: a) Aerial Testing, both captive carry and tethered drop tests (36 sorties, approx. 80 hrs). b) Testing with Electronic Ground Support Equipment (EGSE) on the bench (500+ hrs). c) Detailed Simulation including both RF physics and internal firmware logic (100,000+ simulated landings). All three venues were implemented to provide sufficient uniqueness and overlap to: a) Verify the radar is meeting its requirements. b) Validate radar performance within the flight system and environment. Significant discoveries were attributed to each of the three elements of the testing triptych, leading to greatly improved EDL system robustness. An overview of the testing triptych methodology, discoveries, and responses to them will be subsequently discussed.

Mars Phoenix Mission↗
NASA NTRS2010

Physical Invariants of Intelligence

A program of research is dedicated to development of a mathematical formalism that could provide, among other things, means by which living systems could be distinguished from non-living ones. A major issue that arises in this research is the following question: What invariants of mathematical models of the physics of systems are (1) characteristic of the behaviors of intelligent living systems and (2) do not depend on specific features of material compositions heretofore considered to be characteristic of life? This research at earlier stages has been reported, albeit from different perspectives, in numerous previous NASA Tech Briefs articles. To recapitulate: One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Mathematical models of motor dynamics are used to simulate the observable physical behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. At the time of reporting the information for this article, the focus of this research was upon the following aspects of the formalism: Intelligence is considered to be a means by which a living system preserves itself and improves its ability to survive and is further considered to manifest itself in feedback from the mental dynamics to the motor dynamics. Because of the feedback from the mental dynamics, the motor dynamics attains quantum-like properties: The trajectory of the physical aspect of the system in the space of dynamical variables splits into a family of different trajectories, and each of those trajectories can be chosen with a probability prescribed by the mental dynamics. From a slightly different perspective, the mechanism of decision-making is feedback from the mental dynamics to the motor dynamics, and this mechanism provides a quantum-like collapse of a random motion into an appropriate deterministic state, such that entropy undergoes a pronounced decrease. The existence of this mechanism is considered to be an invariant of intelligent behavior of living systems, regardless of the origins and material compositions of the systems.

Zak, Michail↗
NASA NTRSDate not supplied

Precision Landing Navigation Performance of Human-Scale Lunar and Mars Landers

To meet the unique challenges of crewed Lunar and Mars precision landings, NASA’s Safe and Precise Landing Integrated Capabilities Evolution project has worked to advance autonomous spacecraft navigation by increasing the technology readiness level of key deorbit, entry, descent, and landing systems, including navigation sensors. Different sensors and their effects on overall system performance are evaluated using six-degree-of-freedom simulations with physics-based engineering models that capture the relevant vehicle systems and environmental effects. Building on an existing simulation framework, this work demonstrates how improved modeling fidelity enables rapid and detailed assessment of various navigation sensors on human-scale Lunar and Mars landing vehicles using NASA reference architectures.

navigation↗
DOE OSTI2024

Increased accuracy of multiphysics simulations through flexible execution, transient algorithms, and modular physics

The MOOSE framework is a foundational capability used by the NEAMS program to create over 15 different simulation tools for advanced nuclear reactors. Due to MOOSE’s broad use, improvements to the framework in support of modeling and simulation goals are critical to the program. Such improvements can take many forms, including optimization, improved user experience, streamlined application programming interfaces (APIs), parallelism, and new capabilities. The work described in this report was conducted in direct support of the simulation tools and has already been deployed. The capabilities were implemented in the same order as they are covered in this report: multiple time integrators in the same input file, initial design of framework Components, an input file Application block, extension of NetGen to 3D geometries in MOOSE, and deployment of executors in the multi-system paradigm. These five additions are fundamental capabilities that will be leveraged by many NEAMS applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Quantum Information for Fusion Energy Sciences (Final Technical Report)

The simulation of plasma dynamics is a critical area of Fusion Energy Sciences (FES) due to it’s usefulness in predicting, controlling, and confining plasmas in the context of potential fusion reactors. The simulation of plasmas is a computationally difficult problem in both classical and quantum physics, motivating investigation into the potential of quantum computers to simulate these systems. This project took several concrete steps towards this goal by developing tools for improving the control, characterization, and calibration of quantum gates on a superconducting quantum computer, developing error suppression and mitigation tools to reduce errors on the quantum computer, and utilizing these advancements to simulate reduced models of plasma dynamics on the quantum computer. In order to efficiently simulate plasma physics, an optimal control method which synthesizes, directly at the pulse level, any quantum gate on qubit and qutrit systems was developed. Using four superconducting transmon quantum processors at Rigetti and LLNL, it was demonstrated that any arbitrary quantum gate on qubits and qutrits could be implemented with high fidelity, leading to a significantly reduced length of a gate sequence. A problem of interest in FES is the nonlinear optical process of laser pulse compression within a plasma. Since quantum physics is linear, simulating nonlinear operations is not naturally feasible on a quantum computer, however it is possible to simulated a quantized version of the nonlinear process. A quantization approach to convert nonlinear wave-wave interaction problems to Hamiltonian simulation problems was developed and demonstrated using two qubits on a Rigetti device. In this experiment, a number of error suppression and mitigation techniques were investigated to determine how best to utilize the finite quantum resources. This study provides an example of how plasma problems may be solved on near-term, noisy quantum computing platforms and identified a promising set of techniques. Building on the insights of these experiments, the investigation turned to linear electron-plasma wave physics. A connection was identified between a local one-dimensional lattice spin model and linear wave phenomena, allowing a plasma physics problem to be efficiently mapped to the quantum computer. In this framework, reflection and transmission of plasma waves at a sharp boundary was studied, as well as the propagation of waves through an inhomogeneous plasma medium. In addition to the suite of error suppression and mitigation techniques developed, this experiment introduced the use of a digital-analog gate scheme designed to efficiently simulate the plasma Hamiltonian. With hardware available at the conclusion of the project, simulation at the scale of 9 qubits and 15 timesteps (60 entangling layers) was achieved.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

High Performance Heat Pipe Power Transient Testing at SPHERE Facility

Microreactors are being researched, designed, and built at Idaho National Laboratory (INL). Microreactors are small reactors defined at less than 20MW of power. These reactor concepts are also being looked at throughout industry for various applications. An important aspect of these reactor designs is economic feasibility i.e. lower overnight capital cost. The driving factors for implementing microreactors are quick setup and takedown, minimal operators, and the ability to manufacture them readily and to fit in mid-sized containers for transport. A specific area of research to aid in successful integration of these factors within the designs is passive heat removal of the core’s thermal power. Interest in heat pipes to achieve this passive heat removal has been shown across multiple industry partners. Because of this interest, INL has developed a test facility to facilitate experimental tests for sodium filled heat pipes. INL has developed the Single Primary Heat Extraction and Removal Emulator (SPHERE) facility to run experiments on high performance, sodium filled heat pipes. As mentioned above, heat pipes are passive heat transfer devices. Radially, heat pipes are broken up into an outer wall, a small annular gap, a wick structure, and a centerline gap. They function by utilizing latent heat transfer. Heat pipes are traditionally separated into three regions, an evaporator (heat input), an adiabatic region, and finally a condenser region (heat removal). As heat is being applied to the evaporator, the working fluid undergoes a phase change to a vapor. This phase change causes a differential pressure across the axial length of the pipe driving flow down the center gap of the heat pipe. The vapor flows down past the adiabatic region to the condenser where the heat is removed. This heat removal forces the working fluid to phase change back to a liquid. The wick structure is then utilized to drive the flow back towards the evaporator by capillary forces. This backflow is aided by the annular gap. Because this heat transfer mechanism functions with latent heat transfer, the heat pipe is close to isothermal down the axial length. Heat pipes can operate under a wide range of working fluids. Considerations for these working fluids are primarily driven by operating temperatures amongst other important factors based around overall performance. Sodium filled heat pipes operate from 450°C up to 900°C. This temperature range works well for the current microreactor designs. In conjunction with this experimental capability, INL has developed a modeling software to simulate heat pipe physics within reactor cores. This modeling software is called Sockeye and functions under the established INL Multiphysics Object Oriented Simulation Environment (MOOSE). SPHERE also supports Sockeye development by providing the modeling team with experimental data on an array of setups and operating parameters to support validation efforts. A power transient experiment was performed utilizing the SPHERE facility to continue to aid with Sockeye development. The testing followed a proposed test plan to ramp up and down the temperature of the heat pipe. Sockeye models steady state heat pipe operation with high accuracy, the data provided by the power transient testing aims to assist with the validation efforts and further enhance transient modeling capability of the tool [2].

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2005

DEVELOPMENT OF STANDARDIZED LUNAR REGOLITH SIMULANT MATERIALS

Lunar exploration activities require scientific and engineering studies that use standardized testing procedures and ultimately support flight certification of hardware and the development of technologies for their use on the lunar surface. It is necessary to anticipate the full range of source materials and environmental constraints that are expected on the Moon and Mars, and to evaluate in-situ resource utilization (ISRU) coupled with testing and development. Historical use of lunar simulants has focused on physical aspects of the lunar regolith for landing and transportation activities. Lunar mare simulants MLS-1 and JSC-1 have been developed, but supplies have been exhausted. Renewed emphasis on exploration and ISRU activities requires development of standardized simulant reference materials that are traceable interlaboratory standards for testing and simulate the lunar regolith in terms of physical, chemical, and mineralogical properties. This new generation of lunar regolith simulants must therefore support both technological development and testing methods. These issues were extensively discussed at the 2005 Lunar Regolith Simulant Materials Workshop.

Carpenter, P.↗
DOE OSTI2026

A hybrid Penman-Monteith and machine learning model for simulating evapotranspiration and its components

Integrating physical processes with machine learning has advanced evapotranspiration (ET) simulation, yet most hybrid models fail to partition total ET into its components: soil evaporation (E) and vegetation transpiration (T). This study introduces Residual Neural Network–Penman–Monteith (RNN-PM), a novel hybrid dual-source ET model designed to overcome this limitation. The model synergizes the physically-based Penman–Monteith framework with three specialized residual neural networks trained to estimate key conductance parameters (canopy conductance, soil surface conductance, and aerodynamic conductance). Furthermore this explicit parameterization allows for the direct partitioning of total ET. Validation at National Ecological Observatory Network (NEON) flux sites using high-frequency partitioned E and T shows that RNN-PM reliably reproduces ET and the transpiration fraction (T/ET). For ET, the model achieves an average Kling–Gupta efficiency (KGE) of 0.89 and a root-mean-square error (RMSE) of 0.55 mm/day; for T/ET, the KGE is 0.87 with an RMSE of 0.06. Furthermore, RNN-PM demonstrates robust generalization, accurately simulating ET and its components well beyond the initial training dataset, even under extreme climatic conditions. This study extended the analysis by comparing the RNN-PM model with seven established dual-source ET models. The results indicate that RNN-PM outperforms both conventional machine learning models and purely physical process-based models in simulating ET components in most cases. Among the purely physical process-based dual-source models, those based on surface temperature decomposition showed improved performance as the leaf area index (LAI) decreased when evaluated against high-frequency ET component datasets. In contrast, the performance of conductance-based dual-source models declined with decreasing LAI. Although purely machine learning-based models can produce relatively accurate simulations of ET components, they often exhibit limited generalization capability, an issue that the RNN-PM model effectively overcomes. Ultimately, the RNN-PM model represents a significant advance in simulating ET components, offering a novel and scalable approach for improving the representation of land–atmosphere interactions in Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Assessment of Current MACCS Capabilities for Modeling Atmospheric Physical and Chemical Transformations

The physical and chemical transformation during atmospheric transport of radionuclides released into the environment has the possibility of impacting consequence modeling results. Accordingly, this report identifies physical and chemical transformations that may occur following release of chemically reactive radioactive species, how those transformations may affect modeling of consequences of release to the atmosphere and identifies current capabilities – in both MACCS and other state-of-practice atmospheric transport and dispersions models– to model those transformations. It was found that the inclusion of physical and chemical transformations is currently very limited in current state-of-practice codes for atmospheric dispersion of radionuclides. State-of-practice atmospheric dispersion codes appear to be typically limited to simulating either physical-chemical transformations or radioactive transformations, but not both. A state-of-practice atmospheric dispersion code capable of performing parallel physical, chemical, and radioactive transformation was not identified. A few atmospheric dispersion codes capable of modeling physical and chemical transport of specific species such as tritium or uranium hexafluoride were identified. Consequently, there is currently no information available that clearly suggests updates to the MACCS code are needed to bring it up to state-of-practice. However, investigations concluded that the MACCS computational framework can currently accommodate multiple physical/chemical forms in one simulation. Additionally, with some major assumptions, the computational framework in MACCS can accommodate parallel physical-chemical and radioactive transformations.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

Classical and quantum simulations of 1+1-dimensional ${\mathbb{Z}}_{2}$ gauge theory at finite temperature and density

Simulating strongly coupled gauge theories at finite temperature and density is a longstanding challenge in nuclear and high-energy physics with fundamental implications for condensed matter physics. Here, we simulate such systems using minimally entangled typical thermal state (METTS) approaches, which combine classical random sampling with imaginary-time evolution, implementable on either classical or quantum computers, to estimate thermal averages of observables. We study 1+1-dimensional ${\mathbb{Z}}_{2}$ gauge theory coupled to spinless fermionic matter, which maps onto a local quantum spin chain. We benchmark both a classical matrix-product-state implementation of METTS and a recently proposed adaptive variational approach for near-term quantum devices, focusing on the equation of state and measures of fermion confinement. Of particular importance is the choice of basis for METTS sampling, which impacts both the sampling overhead and quantum circuit complexity. Our work sets the stage for future studies of strongly coupled gauge theories using classical and quantum hardware.

Chen, I-Chi [Iowa State Univ., Ames, IA (United St↗