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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Scattering Processes from Quantum Simulation Algorithms for Scalar Field Theories

We provide practical simulation methods for scalar field theories on a quantum computer that yield improved asymptotics as well as concrete gate estimates for the simulation and physical qubit estimates using the surface code. We achieve these improvements through two optimizations. First, we consider a finite volume approach for estimating the elements of the S-matrix. This approach is appropriate in general for 1+1D and for certain low-energy elastic collisions in higher dimensions. Second, we implement our approach using a series of different fault-tolerant simulation algorithms for Hamiltonians formulated both in the field occupation basis and field amplitude basis. Our algorithms are based on either second-order Trotterization or qubitization. The cost of Trotterization in occupation basis scales as O ( λ N 7 | Ω | 3 / ( M 5 / 2 ϵ 3 / 2 ) ) where λ is the coupling strength, N is the occupation cutoff, | Ω | is the volume of the spatial lattice, M is the mass of the particles and ϵ is the uncertainty in the energy calculation used for the S -matrix determination. Qubitization in the field basis scales as O ( | Ω | 2 ( k 2 Λ + k M 2 ) / ϵ ) , where k is the cutoff in the field and Λ is a scaled coupling constant. We find in both cases that the bounds suggest physically meaningful simulations can be performed using on the order of 4 × 10 6 physical qubits and 10 12 T -gates which corresponds to roughly one day on a superconducting quantum computer with surface code and a cycle time of 100 ns. This places the simulation of scalar field theory within striking distance of the gate counts for the best available chemistry simulation results.

Hardy, Andrew [Toronto U.] (ORCID:0000000235817382↗
DOE OSTI2025

Simulation Models for Exploring Magnetic Reconnection

Simulations have played a critical role in the advancement of our knowledge of magnetic reconnection. However, due to the inherently multiscale nature of reconnection, it is impossible to simulate all physics at all scales. For this reason, a wide range of simulation methods have been crafted to study particular aspects and consequences of magnetic reconnection. This article reviews many of these methods, laying out critical assumptions, numerical techniques, and giving examples of scientific results. Plasma models described include magnetohydrodynamics (MHD), Hall MHD, Hybrid, kinetic particle-in-cell (PIC), kinetic Vlasov, Fluid models with embedded PIC, Fluid models with direct feedback from energetic populations, and the Rice Convection Model (RCM).

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2013

Dynamic Acquisition and Retrieval Tool (DART) for Comet Sample Return : Session: 2.06.Robotic Mobility and Sample Acquisition Systems

The 2011 Decadal Survey for planetary science released by the National Research Council of the National Academies identified Comet Surface Sample Return (CSSR) as one of five high priority potential New Frontiers-class missions in the next decade. The main objectives of the research described in this publication are: develop a concept for an end-to-end system for collecting and storing a comet sample to be returned to Earth; design, fabricate and test a prototype Dynamic Acquisition and Retrieval Tool (DART) capable of collecting 500 cc sample in a canister and eject the canister with a predetermined speed; identify a set of simulants with physical properties at room temperature that suitably match the physical properties of the comet surface as it would be sampled. We propose the use of a dart that would be launched from the spacecraft to impact and penetrate the comet surface. After collecting the sample, the sample canister would be ejected at a speed greater than the comet's escape velocity and captured by the spacecraft, packaged into a return capsule and returned to Earth. The dart would be composed of an inner tube or sample canister, an outer tube, a decelerator, a means of capturing and retaining the sample, and a mechanism to eject the canister with the sample for later rendezvous with the spacecraft. One of the significant unknowns is the physical properties of the comet surface. Based on new findings from the recent Deep Impact comet encounter mission, we have limited our search of solutions for sampling materials to materials with 10 to 100 kPa shear strength in loose or consolidated form. As the possible range of values for the comet surface temperature is also significantly different than room temperature and testing at conditions other than the room temperature can become resource intensive, we sought sample simulants with physical properties at room temperature similar to the expected physical properties of the comet surface material. The chosen DART configuration, the efforts to identify a test simulant and the properties of these simulants, and the results of the preliminary testing will be described in this paper.

Dynamic Acquisition and Retrieval Tool (DART)↗
NASA NTRS2008

Characterization and Simulation of the Thermoacoustic Instability Behavior of an Advanced, Low Emissions Combustor Prototype

Extensive research is being done toward the development of ultra-low-emissions combustors for aircraft gas turbine engines. However, these combustors have an increased susceptibility to thermoacoustic instabilities. This type of instability was recently observed in an advanced, low emissions combustor prototype installed in a NASA Glenn Research Center test stand. The instability produces pressure oscillations that grow with increasing fuel/air ratio, preventing full power operation. The instability behavior makes the combustor a potentially useful test bed for research into active control methods for combustion instability suppression. The instability behavior was characterized by operating the combustor at various pressures, temperatures, and fuel and air flows representative of operation within an aircraft gas turbine engine. Trends in instability behavior versus operating condition have been identified and documented, and possible explanations for the trends provided. A simulation developed at NASA Glenn captures the observed instability behavior. The physics-based simulation includes the relevant physical features of the combustor and test rig, employs a Sectored 1-D approach, includes simplified reaction equations, and provides time-accurate results. A computationally efficient method is used for area transitions, which decreases run times and allows the simulation to be used for parametric studies, including control method investigations. Simulation results show that the simulation exhibits a self-starting, self-sustained combustion instability and also replicates the experimentally observed instability trends versus operating condition. Future plans are to use the simulation to investigate active control strategies to suppress combustion instabilities and then to experimentally demonstrate active instability suppression with the low emissions combustor prototype, enabling full power, stable operation.

DeLaat, John C.↗
NASA NTRS2008

Characterization and Simulation of Thermoacoustic Instability in a Low Emissions Combustor Prototype

Extensive research is being done toward the development of ultra-low-emissions combustors for aircraft gas turbine engines. However, these combustors have an increased susceptibility to thermoacoustic instabilities. This type of instability was recently observed in an advanced, low emissions combustor prototype installed in a NASA Glenn Research Center test stand. The instability produces pressure oscillations that grow with increasing fuel/air ratio, preventing full power operation. The instability behavior makes the combustor a potentially useful test bed for research into active control methods for combustion instability suppression. The instability behavior was characterized by operating the combustor at various pressures, temperatures, and fuel and air flows representative of operation within an aircraft gas turbine engine. Trends in instability behavior vs. operating condition have been identified and documented. A simulation developed at NASA Glenn captures the observed instability behavior. The physics-based simulation includes the relevant physical features of the combustor and test rig, employs a Sectored 1-D approach, includes simplified reaction equations, and provides time-accurate results. A computationally efficient method is used for area transitions, which decreases run times and allows the simulation to be used for parametric studies, including control method investigations. Simulation results show that the simulation exhibits a self-starting, self-sustained combustion instability and also replicates the experimentally observed instability trends vs. operating condition. Future plans are to use the simulation to investigate active control strategies to suppress combustion instabilities and then to experimentally demonstrate active instability suppression with the low emissions combustor prototype, enabling full power, stable operation.

DeLaat, John C.↗
NASA NTRS1982

Simulation studies of the physical and chemical processes occurring in the stratospheric clouds of the Mount St. Helens eruptions of May and June 1980

The large and diverse set of observational data collected in the high-altitude clouds of May 18, May 25, and June 13, 1980 was organized and analyzed for trends which reveal the processes at work. The data were used to guide and constrain model simulations of the volcanic eruptions. A comprehensive one-dimensional model of stratospheric sulfate aerosols, sulfur precursor gases, and volcanic ash and dust particles is utilized which accounts for homogeneous and heterogeneous chemistry in the clouds, aerosol nucleation and growth, and cloud expansion. Computational results are given for the time histories of the gaseous species concentrations, sulfate aerosol size dispersions, and ash burdens in the eruption clouds. The long-term buildup of stratospheric aerosols in the Northern Hemisphere and the persistent effects of injected chlorine and water vapor on ozone are discussed. It is concluded that SO2, water vapor, and ash are the most important substances injected by the volcano into the stratosphere, with respect to both the widespread effects on composition and the impact on climate. It is found that the volcano probably had little influence on the climate ( 0.05 K global surface cooling) or on stratospheric ozone ( 0.2 percent maximum hemispherical reduction).

Turco, R. P.↗
NASA NTRSDate not supplied

Exploitation of a Validation Hierarchy for Modeling and Simulation

Across engineering there is an evolving need to increase reliance on physics-based simulation to develop, design and optimize engineering systems. This increased reliance on modeling and simulation has highlighted a growing need to transform the confidence that modeling and simulation analysts have in their results into credibility for systems engineers to design and field systems more quickly and with less physical testing. For isolated components of a complex system, where a single discipline may drive product design, this is less of a concern as the relationship is often straightforward and easy to explain. However, when these isolated components are integrated, and are expected to operate in a multi-disciplinary context in which safety critical systems are involved, new concepts and model assurance standards are required. In this paper we address this challenge by showing how a model validation hierarchy can be exploited to identify those model validation experiments that will contribute most to increasing confidence and credibility of modeling and simulation predictions. The approach that is adopted contains four main steps. The first step is the construction of a model validation hierarchy that links subsystems, assemblies, and components to a hierarchy of physical experiments that can be used support model validation. This hierarchy connects the concerns of systems engineers to those of the modeling and simulation analyst in a clear and logical way. The structure and content of this hierarchy is then used in a second step to establish which physical phenomena have the greatest impact on overall system performance metrics. A gap analysis technique, based upon modeling and simulation concerns, is then used to prioritize the important physical phenomenon. Unfortunately, a common outcome of such gap analyses is the identification of many important gaps and so, in the final step of our process, we advocate the use of a global sensitivity analysis as a means to complete the prioritization.

Verification and Validation↗
NASA NTRSDate not supplied

Exploitation of a Validation Hierarchy for Modeling and Simulation

Across engineering there is an evolving need to increase reliance on physics-based simulation to develop, design and optimize engineering systems. This increased reliance on modeling and simulation has highlighted a growing need to transform the confidence that modeling and simulation analysts have in their results into credibility for systems engineers to design and field systems more quickly and with less physical testing. For isolated components of a complex system, where a single discipline may drive product design, this is less of a concern as the relationship is often straightforward and easy to explain. However, when these isolated components are integrated, and are expected to operate in a multi-disciplinary context in which safety critical systems are involved, new concepts and model assurance standards are required. In this paper we address this challenge by showing how a model validation hierarchy can be exploited to identify those model validation experiments that will contribute most to increasing confidence and credibility of modeling and simulation predictions. The approach that is adopted contains four main steps. The first step is the construction of a model validation hierarchy that links subsystems, assemblies, and components to a hierarchy of physical experiments that can be used support model validation. This hierarchy connects the concerns of systems engineers to those of the modeling and simulation analyst in a clear and logical way. The structure and content of this hierarchy is then used in a second step to establish which physical phenomena have the greatest impact on overall system performance metrics. A gap analysis technique, based upon modeling and simulation concerns, is then used to prioritize the important physical phenomenon. Unfortunately, a common outcome of such gap analyses is the identification of many important gaps and so, in the final step of our process, we advocate the use of a global sensitivity analysis as a means to complete the prioritization.

Verification and Validation↗
NASA NTRS2000

Information Power Grid: Distributed High-Performance Computing and Large-Scale Data Management for Science and Engineering

The term "Grid" refers to distributed, high performance computing and data handling infrastructure that incorporates geographically and organizationally dispersed, heterogeneous resources that are persistent and supported. The vision for NASN's Information Power Grid - a computing and data Grid - is that it will provide significant new capabilities to scientists and engineers by facilitating routine construction of information based problem solving environments / frameworks that will knit together widely distributed computing, data, instrument, and human resources into just-in-time systems that can address complex and large-scale computing and data analysis problems. IPG development and deployment is addressing requirements obtained by analyzing a number of different application areas, in particular from the NASA Aero-Space Technology Enterprise. This analysis has focussed primarily on two types of users: The scientist / design engineer whose primary interest is problem solving (e.g., determining wing aerodynamic characteristics in many different operating environments), and whose primary interface to IPG will be through various sorts of problem solving frameworks. The second type of user if the tool designer: The computational scientists who convert physics and mathematics into code that can simulate the physical world. These are the two primary users of IPG, and they have rather different requirements. This paper describes the current state of IPG (the operational testbed), the set of capabilities being put into place for the operational prototype IPG, as well as some of the longer term R&D tasks.

Johnston, William E.↗
NASA NTRS1987

Vortical flow aerodynamics - Physical aspects and numerical simulation

Progress in the numerical simulation of vortical flow due to three-dimensional flow separation about flight vehicles at high angles of attack and quasi-steady flight conditions is surveyed. Primary emphasis is placed on Euler and Reynolds-averaged Navier-Stokes methods where the vortices are 'captured' as a solution to the governing equations. A discussion of the relevant flow physics provides a perspective from which to assess numerical solutions. Current numerical prediction capabilities and their evolutionary development are surveyed. Future trends and challenges are identified and discussed.

Newsome, Richard W.↗
NASA NTRS2016

The Trick Simulation Toolkit: A NASA/Opensource Framework for Running Time Based Physics Models

The Trick Simulation Toolkit is a simulation development environment used to create high fidelity training and engineering simulations at the NASA Johnson Space Center and many other NASA facilities. Its purpose is to generate a simulation executable from a collection of user-supplied models and a simulation definition file. For each Trick-based simulation, Trick automatically provides job scheduling, numerical integration, the ability to write and restore human readable checkpoints, data recording, interactive variable manipulation, a run-time interpreter, and many other commonly needed capabilities. This allows simulation developers to concentrate on their domain expertise and the algorithms and equations of their models. Also included in Trick are tools for plotting recorded data and various other supporting utilities and libraries. Trick is written in C/C++ and Java and supports both Linux and MacOSX computer operating systems. This paper describes Trick's design and use at NASA Johnson Space Center.

Penn, John M.↗
DOE OSTI2026

Differentiable multiphase flow model for physics-informed machine learning in reservoir pressure management

Accurate subsurface reservoir pressure control is extremely challenging due to geological heterogeneity and multiphase fluid-flow dynamics. Predicting behavior in this setting relies on high-fidelity physics-based simulations that are computationally expensive. Yet, the uncertain, heterogeneous properties that control these flows make it necessary to perform many of these expensive simulations, which is often prohibitive. To address these challenges, we introduce a physics-informed machine learning workflow that couples a fully differentiable multiphase flow simulator, which is implemented in the DPFEHM framework with a convolutional neural network (CNN). The CNN learns to predict fluid extraction rates from heterogeneous permeability fields to enforce pressure limits at critical reservoir locations. By incorporating transient multiphase flow physics into the training process, our method enables more practical and accurate predictions for realistic injection-extraction scenarios compared to previous works. To speed up training, we pretrain the model on single-phase, steady-state simulations and then finetune it on full multiphase scenarios, which dramatically reduces the computational cost. We demonstrate that high-accuracy training can be achieved with fewer than three thousand full-physics multiphase flow simulations – compared to previous estimates requiring up to ten million. This drastic reduction in the number of simulations is achieved by leveraging transfer learning from much less expensive single phase simulations.

25 ENERGY STORAGE↗
NASA NTRS2004

Recent developments in the ROAMS planetary rover simulation environment

This paper describes recent developments in the ROAMS physics-based simulator for planetary surface exploration rover vehicles. ROAMS includes models for various subsystems and components of the robotic vehicle including its mechanical subsystem, sensors, on-board resources, on-board control software, the terrain environment and terrain/vehicle interactions. The ROAMS simulator can be used for stand-alone simulation, closed-loop simulations with on-board software or for operator-in-the-loop simulations.

Sohl, G.↗
NASA NTRS1992

Identification of time-varying structural dynamic systems - An artificial intelligence approach

An application of the artificial intelligence-derived methodologies of heuristic search and object-oriented programming to the problem of identifying the form of the model and the associated parameters of a time-varying structural dynamic system is presented in this paper. Possible model variations due to changes in boundary conditions or configurations of a structure are organized into a taxonomy of models, and a variant of best-first search is used to identify the model whose simulated response best matches that of the current physical structure. Simulated model responses are verified experimentally. An output-error approach is used in a discontinuous model space, and an equation-error approach is used in the parameter space. The advantages of the AI methods used, compared with conventional programming techniques for implementing knowledge structuring and inheritance, are discussed. Convergence conditions and example problems have been discussed. In the example problem, both the time-varying model and its new parameters have been identified when changes occur.

Glass, B. J.↗
NASA NTRS2019

Physics-Based Modeling and Simulation of Emerging Battery Technologies for Aerospace

Recently there is a growing interest in the aviation sector to reduce air and noise pollution. Electrochemical energy storage devices such as batteries coupled with a distributed electric propulsion system can reduce noise concerns as well as emissions and allow the concept of Urban Air Mobility to come to fruition. The battery performance needs to improve considerably compared from current state-of-art Li-ion battery (about 200Wh/Kg) to realize all-electric passenger jet for short flights (up to 690 miles). NASA is exploring lithium-oxygen battery chemistry to power hybrid (battery powered electrical system) and all-electric aircraft for short distance and long-distance flights. Li-O2 is one of the advanced Li-ion technologies that promise to provide specific energy of more than 750Wh/Kg. For this presentation, we present our work on improving power density of Li-O2 batteries through the use of multiphysics simulations. Next, a path is outlined to port these model to simulate performance for a new battery chemistry for space application, Li-CO2. Li-CO2 uses carbon dioxide as the active material instead of oxygen. Although this technology is in its early development, the offers two benefits: it can be used as a CO2 scrubber, as oxygen is one of the by-products on charging, and as a backup or a standalone battery for various Mars or Venus missions, where the carbon dioxide content in the atmosphere is high and need battery to operate at higher temperatures.

Mehta, Mohit↗