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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
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

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

This paper describes the design and use at of the Trick Simulation Toolkit, a simulation development environment for creating high fidelity training and engineering simulations at the NASA Johnson Space Center and many other NASA facilities. It describes Trick's design goals and how the development environment attempts to achieve those goals. It describes how Trick is used in some of the many training and engineering simulations at NASA. Finally it describes the Trick NASA/Open source project on Github.

Penn, John M.↗
NASA NTRS2019

Physical Models for Accreting Pulsars at High Luminosity

A new window for better understanding the accretion onto strongly magnetized neutron stars in X-ray binaries is opening. In these systems the accreted material follows the magnetic field lines as it approaches the neutron star, forming accretion columns above the magnetic poles. The plasma falls toward the neutron star surface at near-relativistic speeds, losing energy by emitting X-rays. The X-ray spectral continua are commonly described using phenomenological models, i.e., power laws with different types of curved cut-offs at higher energies. Here we consider high luminosity pulsars. In these systems the mass transfer rate is high enough that the accreting plasma is thought to be decelerated in a radiation-dominated radiative shock in the accretion columns. While the theory of the emission from such shocks had already been developed by 2007, a model for direct comparison with X-ray continuum spectra in xspec or isis has only recently become available. Here we analyze the broadband X-ray spectra of the accreting pulsars Centaurus X-3 and 4U1626-67 obtained withNuSTAR. We present results from traditional empirical modeling as well as successfully apply the radiation-dominated radiative shock model. We also fit the energy-dependent pulse profiles of 4U 1626-67 using a new relativistic light bending model.

Pottschmidt, Katja↗
NASA NTRS1999

Physical Model of Immune Inspired Computing

Artificial Immune System is a rapidly growing field of information processing and computing based upon immune inspired paradigns of nonlinear dynamics. This paper introduces stochastic models which mimic the phenomenology of basic functions of immune systems such as self-nonself discrimination, self-repair, predator-prey pursuit, and reproduction.

Immune↗
NASA NTRSDate not supplied

Particle Interaction Physics Model Formulation for Plume-Surface Interaction Erosion and Cratering

The Predictive Simulation Capability development team of the STMD Game Changing Development sponsored PSI project is implementing computational simulation capability for the efficient and accurate prediction of Plume-Surface Interaction induced surface erosion and cratering in Martian and Lunar environments. The status of the Focus Area 3 of the PSI project in the generation and efficient application of accurate soil particle composition modeling in the Gas-Granular Flow Solver (GGFS) computational framework is presented. The process of constitutive closure model database generation using DEM particle interaction modeling for capturing the effects of irregular particle shape and poly-disperse mixture distribution effects is outlined. This capability has now been ported to NASA supercomputer assets and NASA engineers successfully demonstrated technology and skillset transfer in model generation for spherical and irregularly shaped, mono-disperse and bi-disperse mixture compositions. Assessment of the computational efficiency and practicality of the academic serially executed DEM tools on NASA supercomputers identified the need to migrate to a DEM framework capable of performing parallel simulations in a simultaneous process orchestrated in an automated setup, execution, database extraction, and dataset delivery ready for application simulations. The LIGGGHTS DEM toolset has been selected as the most suitable tool to migrate the DEM simulations. Once the soil model generation process is implemented, models capturing the shape and poly-dispersity effects will be generated to perform much refined validation simulations against the experiments performed under the PSI project. The application readiness of the soil models currently operational in GGFS was presented for the example of a full scale, 3-D simulation of the plume induced erosion and crater formation of the Apollo LM at an elevation of 5m above ground in a low pressure, near vacuum background.

Peter A Liever↗
NASA NTRSDate not supplied

Particle Interaction Physics Model Formulation for Plume-Surface Interaction Erosion and Cratering

The Predictive Simulation Capability development team of the STMD Game Changing Development sponsored PSI project is implementing computational simulation capability for the efficient and accurate prediction of Plume-Surface Interaction induced surface erosion and cratering in Martian and Lunar environments. The status of the Focus Area 3 of the PSI project in the generation and efficient application of accurate soil particle composition modeling in the Gas-Granular Flow Solver (GGFS) computational framework is presented. The process of constitutive closure model database generation using DEM particle interaction modeling for capturing the effects of irregular particle shape and poly-disperse mixture distribution effects is outlined. This capability has now been ported to NASA supercomputer assets and NASA engineers successfully demonstrated technology and skillset transfer in model generation for spherical and irregularly shaped, mono-disperse and bi-disperse mixture compositions. Assessment of the computational efficiency and practicality of the academic serially executed DEM tools on NASA supercomputers identified the need to migrate to a DEM framework capable of performing parallel simulations in a simultaneous process orchestrated in an automated setup, execution, database extraction, and dataset delivery ready for application simulations. The LIGGGHTS DEM toolset has been selected as the most suitable tool to migrate the DEM simulations. Once the soil model generation process is implemented, models capturing the shape and poly-dispersity effects will be generated to perform much refined validation simulations against the experiments performed under the PSI project. The application readiness of the soil models currently operational in GGFS was presented for the example of a full scale, 3-D simulation of the plume induced erosion and crater formation of the Apollo LM at an elevation of 5m above ground in a low pressure, near vacuum background.

Peter A Liever↗
NASA NTRS2024

In-depth Analysis of LISA Pathfinder Performance Results: Time Evolution, Noise Projection, Physical Models, and Implications for LISA

We present an in-depth analysis of the LISA Pathfinder differential acceleration performance over the entire course of its science operations, spanning approximately 500 days. We find: (1) The evolution of the Brownian noise that dominates the acceleration amplitude spectral density (ASD), for frequencies f≳1 mHz, is consistent with the decaying pressure due to the outgassing of a single gaseous species. (2) Between f=36 μHz and 1 mHz, the acceleration ASD shows a 1/f tail in excess of the Brownian noise of almost constant amplitude, with ≃20% fluctuations over a period of a few days, with no particular time pattern over the course of the mission. (3) At the lowest considered frequency of f=18 μHz, the ASD significantly deviates from the 1/f behavior, because of temperature fluctuations that appear to modulate a quasistatic pressure gradient, sustained by the asymmetries of the outgassing pattern. We also present the results of a projection of the observed acceleration noise on the potential sources for which we had either a direct correlation measurement or a quantitative estimate from dedicated experiments. These sources account for approximately 40% of the noise power in the 1/f tail. Finally, we analyze the possible sources of the remaining unexplained fraction and identify the possible measures that may be taken to keep those under control in LISA.

M Armano↗
NASA NTRS2014

The Impacts of Microphysics and Planetary Boundary Layer Physics on Model Simulations of U. S. Deep South Summer Convection

Inspection of output from various configurations of high-resolution, explicit convection forecast models such as the Weather Research and Forecasting (WRF) model indicates significant sensitivity to the choices of model physics parameterizations employed. Some of the largest apparent sensitivities are related to the specifications of the cloud microphysics and planetary boundary layer physics packages. In addition, these sensitivities appear to be especially pronounced for the weakly-sheared, multicell modes of deep convection characteristic of the Deep South of the United States during the boreal summer. Possible ocean-land sensitivities also argue for further examination of the impacts of using unique ocean-land surface initialization datasets provided by the NASA Short-term Prediction Research and Transition (SPoRT Center to select NOAA/NWS weather forecast offices. To obtain better quantitative understanding of these sensitivities and also to determine the utility of the ocean-land initialization data, we have executed matrices of regional WRF forecasts for selected convective events near Mobile, AL (MOB), and Houston, TX (HGX). The matrices consist of identically initialized WRF 24-h forecasts using any of eight microphysics choices and any of three planetary boundary layer choices. The resulting 24 simulations performed for each event within either the MOB or HGX regions are then compared to identify the sensitivities of various convective storm metrics to the physics choices. Particular emphasis is placed on sensitivities of precipitation timing, intensity, and coverage, as well as amount and coverage of lightning activity diagnosed from storm kinematics and graupel in the mixed phase layer. The results confirm impressions gleaned from study of the behavior of variously configured WRF runs contained in the ensembles produced each spring at the Center for the Analysis and Prediction of Storms, but with the benefit of more straightforward control of the physics package choices. The design of the experiments thus allows for more direct interpretation of the sensitivities to each possible physics combination. The results should assist forecasters in their efforts to anticipate and correct for possible biases in simulated WRF convection patterns, and help the modeling community refine their model parameterizations.

McCaul, E. W., Jr.↗
NASA NTRS2014

The Impact of Microphysics and Planetary Boundary Layer Physics on Model Simulation of U.S. Deep South Summer Convection

Inspection of output from various configurations of high-resolution, explicit convection forecast models such as the Weather Research and Forecasting (WRF) model indicates significant sensitivity to the choices of model physics pararneterizations employed. Some of the largest apparent sensitivities are related to the specifications of the cloud microphysics and planetary boundary layer physics packages. In addition, these sensitivities appear to be especially pronounced for the weakly-sheared, multicell modes of deep convection characteristic of the Deep South of the United States during the boreal summer. Possible ocean-land sensitivities also argue for further examination of the impacts of using unique ocean-land surface initialization datasets provided by the NASA Short-term Prediction Research and Transition (SPoRn Center to select NOAAlNWS weather forecast offices. To obtain better quantitative understanding of these sensitivities and also to determine the utility of the ocean-land initialization data, we have executed matrices of regional WRF forecasts for selected convective events near Mobile, AL (MOB), and Houston, TX (HGX). The matrices consist of identically initialized WRF 24-h forecasts using any of eight microphysics choices and any of three planetary boWldary layer choices. The resulting 24 simulations performed for each event within either the MOB or HGX regions are then compared to identify the sensitivities of various convective storm metrics to the physics choices. Particular emphasis is placed on sensitivities of precipitation timing, intensity, and coverage, as well as amount and coverage oflightuing activity diagnosed from storm kinematics and graupel in the mixed phase layer. The results confirm impressions gleaned from study of the behavior of variously configured WRF runs contained in the ensembles produced each spring at the Center for the Analysis and Prediction of Storms, but with the benefit of more straightforward control of the physics package choices. The design of the experiments thus allows for more direct interpretation of the sensitivities to each possible physics combination. The results should assist forecasters in their efforts to anticipate and correct for possible biases in simulated WRF convection patterns, and help the modeling community refine their model parameterizations.

McCaul, Eugene W., Jr.↗
NASA NTRS2014

The Impacts of Microphysics and Planetary Boundary Layer Physics on Model Simulations of U.S. Deep South Summer Convection

Convection-allowing numerical weather simula- tions have often been shown to produce convective storms that have significant sensitivity to choices of model physical parameterizations. Among the most important of these sensitivities are those related to cloud microphysics, but planetary boundary layer parameterizations also have a significant impact on the evolution of the convection. Aspects of the simulated convection that display sensitivity to these physics schemes include updraft size and intensity, simulated radar reflectivity, timing and placement of storm initi- ation and decay, total storm rainfall, and other storm features derived from storm structure and hydrometeor fields, such as predicted lightning flash rates. In addition to the basic parameters listed above, the simulated storms may also exhibit sensitivity to im- posed initial conditions, such as the fields of soil temper- ature and moisture, vegetation cover and health, and sea and lake water surface temperatures. Some of these sensitivities may rival those of the basic physics sensi- tivities mentioned earlier. These sensitivities have the potential to disrupt the accuracy of short-term forecast simulations of convective storms, and thereby pose sig- nificant difficulties for weather forecasters. To make a systematic study of the quantitative impacts of each of these sensitivities, a matrix of simulations has been performed using all combinations of eight separate microphysics schemes, three boundary layer schemes, and two sets of initial conditions. The first version of initial conditions consists of the default data from large-scale operational model fields, while the second features specialized higher- resolution soil conditions, vegetation conditions and water surface temperatures derived from datasets created at NASA's Short-term Prediction and Operational Research Tran- sition (SPoRT) Center at the National Space Science and Technology Center (NSSTC) in Huntsville, AL. Simulations as outlined above, each 48 in number, were conducted for five midsummer weakly sheared coastal convective events each at two sites, Mobile, AL (MOB) and Houston, TX (HGX). Of special interest to operational forecasters at MOB and HGX were accuracy of timing and placement of convective storm initiation, reflectivity magnitudes and coverage, rainfall and inferred lightning threat.

McCaul, Eugene W., Jr.↗
NASA NTRS2018

Application of PoF Based Virtual Qualification Methods for Reliability Assessment of Mission Critical PCBs

Reliability is the ability of a product to perform the function for which it was intended for a specified period of time (or cycles) for a given set of life cycle conditions. In today's compressed mission development cycles where designing, building and testing the physical models has to occur in a matter of months not years, Projects don't have the luxury of iteratively building and testing those models. Physics of failure (PoF) is an engineering-based approach to reliability that begins with an understanding of materials, processes, physical interactions, degradation and failure mechanisms, as well as identifying failure models. The PoF approach uses modeling and simulation to qualify a design and manufacturing process, with the ultimate intent of eliminating failures early in the design process by addressing the root cause. The physics-of-failure analysis proactively incorporates reliability into the design process by establishing a scientific basis for evaluating new materials, structures and technologies. Virtual physics-of-failure modeling allows engineers to determine if new technological node can be added to an existing system. This presentation will illustrate an application of a PoF based tool during the initial phases of a printed circuit board assembly development and how the NASA GSFC team was able to dynamically study the effects of electronics parts and printed circuit board material configuration changes under simulated thermal and vibrational stresses.

Physics of Failure↗
NASA NTRS2018

Application of PoF Based Virtual Qualification Methods for Reliability Assessment of Mission Critical PCBs

Reliability is the ability of a product to perform the function for which it was intended for a specified period of time (or cycles) for a given set of life cycle conditions. In today's compressed mission development cycles where designing, building and testing the physical models has to occur in a matter of months not years, Projects don't have the luxury of iteratively building and testing those models. Physics of failure (PoF) is an engineering-based approach to reliability that begins with an understanding of materials, processes, physical interactions, degradation and failure mechanisms, as well as identifying failure models. The PoF approach uses modeling and simulation to qualify a design and manufacturing process, with the ultimate intent of eliminating failures early in the design process by addressing the root cause. The physics-of-failure analysis proactively incorporates reliability into the design process by establishing a scientific basis for evaluating new materials, structures and technologies. Virtual physics-of-failure modeling allows engineers to determine if new technological node can be added to an existing system. This presentation will illustrate an application of a PoF based tool during the initial phases of a printed circuit board assembly development and how the NASA GSFC team was able to dynamically study the effects of electronics parts and printed circuit board material configuration changes under simulated thermal and vibrational stresses

Electronics packaging↗
NASA NTRS2024

Transfer-AE: A novel autoencoder-based impact detection model for structural digital twin

Accurately detecting the location and intensity of impacts is crucial for ensuring structural safety. Currently, AI-based structural impact detection methods are widely used for their excellent detection accuracy. However, their generalization capability is limited by the scenarios present in the training data. Many complex and dangerous impact scenarios are difficult to conduct real-world experiments on to collect sufficient samples. To capture all impact scenarios and fully leverage the advantages of AI-based detection technologies, advanced methods involve combining real-world structural monitoring data with corresponding numerical models to construct digital twins. These methods continuously refine the created numerical models with limited real-world data and provide diverse impact scenarios through numerical model simulations. However, there are inevitable differences between digital models and physical models that are challenging to correct through mechanical means. This discrepancy in data distribution between the two models significantly hinders the application of digital twin technology in impact/event identification tasks. To address this challenge, this study proposes a novel model based on autoencoders, named Transfer-AE. Transfer-AE encodes the common features of digital twins in the latent space to bridge the uncertainty gap at a macro scale between numerical models and physical models and synchronously fits the magnitude and location of the impact load in the decoder. This enables consistent detection results for the same impact event, whether the sample comes from the numerical model or the physical model. Transfer-AE includes two operating modes: Mode 1 has a fixed computational complexity with stable inference speed, but the training cost and difficulty increase with data distribution. Mode 2's computational complexity increases with data distribution, but it has a fixed training cost and speed. In both cases involving the geodesic dome structure simulating a deep space habitat and the IASC-ASCE benchmark structure, Transfer-AE demonstrated the best performance in impact localization and quantification tasks compared to mainstream domain-adaptive transfer models.

Chengjia Han↗