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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Axial focusing of impact energy in the Earth's interior: Proof-of-principle tests of a new hypothesis

A causal link between major impact events and global processes would probably require a significant change in the thermal state of the Earth's interior, presumably brought about by coupling of impact energy. One possible mechanism for such energy coupling from the surface to the deep interior would be through focusing due to axial symmetry. Antipodal focusing of surface and body waves from earthquakes is a well-known phenomenon which has previously been exploited by seismologists in studies of the Earth's deep interior. Antipodal focusing from impacts on the Moon, Mercury, and icy satellites has also been invoked by planetary scientists to explain unusual surface features opposite some of the large impact structures on these bodies. For example, 'disrupted' terrains have been observed antipodal to the Caloris impact basis on Mercury and Imbrium Basin on the Moon. Very recently there have been speculations that antipodal focusing of impact energy within the mantle may lead to flood basalt and hotspot activity, but there has not yet been an attempt at a rigorous model. A new hypothesis was proposed and preliminary proof-of-principle tests for the coupling of energy from major impacts to the mantle by axial focusing of seismic waves was performed. Because of the axial symmetry of the explosive source, the phases and amplitudes are dependent only on ray parameter (or takeoff angle) and are independent of azimuthal angle. For a symmetric and homogeneous Earth, all the seismic energy radiated by the impact at a given takeoff angle will be refocused (minus attenuation) on the axis of symmetry, regardless of the number of reflections and refractions it has experienced. Mantle material near the axis of symmetry will experience more strain cycles with much greater amplitude than elsewhere and will therefore experience more irreversible heating. The situation is very different than for a giant earthquake, which in addition to having less energy, has an asymmetric focal mechanism and a larger area. Two independent proof-of-principle approaches were used. The first makes use of seismic simulations, which are being performed with a realistic Earth model to determine the degree of focusing along the axis and to estimate the volume of material, if any, that experiences significant irreversible heating. The second involves two-dimensional hydrodynamic code simulations to determine the stress history, internal energy, and temperature rise as a function of radius along the axis.

Boslough, M. B.↗
NASA NTRS2012

Design of a Laboratory Hall Thruster with Magnetically Shielded Channel Walls, Phase III: Comparison of Theory with Experiment

A proof-of-principle effort to demonstrate a technique by which erosion of the acceleration channel in Hall thrusters of the magnetic-layer type can be eliminated has been completed. The first principles of the technique, now known as "magnetic shielding," were derived based on the findings of numerical simulations in 2-D axisymmetric geometry. The simulations, in turn, guided the modification of an existing 6-kW laboratory Hall thruster. This magnetically shielded (MS) thruster was then built and tested. Because neither theory nor experiment alone can validate fully the first principles of the technique, the objective of the 2-yr effort was twofold: (1) to demonstrate in the laboratory that the erosion rates can be reduced by >order of magnitude, and (2) to demonstrate that the near-wall plasma properties can be altered according to the theoretical predictions. This paper concludes the demonstration of magnetic shielding by reporting on a wide range of comparisons between results from numerical simulations and laboratory diagnostics. Collectively, we find that the comparisons validate the theory. Near the walls of the MS thruster, theory and experiment agree: (1) the plasma potential has been sustained at values near the discharge voltage, and (2) the electron temperature has been lowered by at least 2.5-3 times compared to the unshielded (US) thruster. Also, based on carbon deposition measurements, the erosion rates at the inner and outer walls of the MS thruster are found to be lower by at least 2300 and 1875 times, respectively. Erosion was so low along these walls that the rates were below the resolution of the profilometer. Using a sputtering yield model with an energy threshold of 25 V, the simulations predict a reduction of ~600 at the MS inner wall. At the outer wall ion energies are computed to be below 25 V, for which case we set the erosion to zero in the simulations. When a 50-V threshold is used the computed ion energies are below the threshold at both sides of the channel. Uncertainties, sensitivities and differences between theory and experiment are also discussed.

plasma simulations↗
NASA NTRS2013

Ionospheric Simulation System for Satellite Observations and Global Assimilative Model Experiments - ISOGAME

Modeling and imaging the Earth's ionosphere as well as understanding its structures, inhomogeneities, and disturbances is a key part of NASA's Heliophysics Directorate science roadmap. This invention provides a design tool for scientific missions focused on the ionosphere. It is a scientifically important and technologically challenging task to assess the impact of a new observation system quantitatively on our capability of imaging and modeling the ionosphere. This question is often raised whenever a new satellite system is proposed, a new type of data is emerging, or a new modeling technique is developed. The proposed constellation would be part of a new observation system with more low-Earth orbiters tracking more radio occultation signals broadcast by Global Navigation Satellite System (GNSS) than those offered by the current GPS and COSMIC observation system. A simulation system was developed to fulfill this task. The system is composed of a suite of software that combines the Global Assimilative Ionospheric Model (GAIM) including first-principles and empirical ionospheric models, a multiple- dipole geomagnetic field model, data assimilation modules, observation simulator, visualization software, and orbit design, simulation, and optimization software.

Pi, Xiaoqing↗
NASA NTRS1993

The IRGen infrared data base modeler

IRGen is a modeling system which creates three-dimensional IR data bases for real-time simulation of thermal IR sensors. Starting from a visual data base, IRGen computes the temperature and radiance of every data base surface with a user-specified thermal environment. The predicted gray shade of each surface is then computed from the user specified sensor characteristics. IRGen is based on first-principles models of heat transport and heat flux sources, and it accurately simulates the variations of IR imagery with time of day and with changing environmental conditions. The starting point for creating an IRGen data base is a visual faceted data base, in which every facet has been labeled with a material code. This code is an index into a material data base which contains surface and bulk thermal properties for the material. IRGen uses the material properties to compute the surface temperature at the specified time of day. IRGen also supports image generator features such as texturing and smooth shading, which greatly enhance image realism.

Bernstein, Uri↗
NASA NTRS1992

Error analysis of optical correlators

With the growing interest in using binary phase only filters (BPOF) in optical correlators that are implemented on magnetooptic spatial light modulators, an understanding of the effect of errors in system alignment and optical components is critical in obtaining optimal system performance. We present simulations of optical correlator performance degradation in the presence of eight errors. We break these eight errors into three groups: 1) alignment errors, 2) errors due to a combination of component imperfections and alignment errors, and 3) errors which result solely from non-ideal components. Under the first group, we simulate errors in the distance from the object to the first principle plane of the transform lens, the distance from the second principle plane of the transform lens to the filter plane, and rotational misalignment of the input mask with the filter mask. Next we consider errors which result from a combination of alignment and component imperfections. These include errors in the transform lens, the phase compensation lens, and the inverse Fourier transform lens. Lastly we have the component errors resulting from the choice of spatial light modulator. These include contrast error and phase errors caused by the non-uniform flatness of the masks. The effects of each individual error are discussed, and the result of combining all eight errors under assumptions of reasonable tolerances and system parameters is also presented. Conclusions are drawn as to which tolerances are most critical for optimal system performance.

Ma, Paul W.↗
NASA NTRS2018

Integrated Real-Time Modeling System for Heliospheric Space Weather Forecasting

The Sun lies at the center of space weather and is the source of its variability. The primary input to coronal and solar wind models is the activity of the magnetic field in the solar photosphere. What is needed is to develop physics-based models for the dynamics of the magnetic field from the deep convection zone of the Sun to the corona with the goal of providing robust near real-time boundary conditions at the base of space weather forecast models. NASA strategic capabilities efforts toward this goal will be summarized during the talk. These have the objective to enable characterizing and predicting the magnetic field structure and flow dynamics of the Sun by assimilating data from helioseismology and magnetic field observations into physics-based realistic magnetohydrodynamics (MHD) simulations. It is argued that an effort in integrating first-principle modeling of solar magnetism and flow dynamics with real-time observational data via advanced data assimilation methods is needed for transformative steps in space weather research and prediction.

Mansour, Nagi N.↗
NASA NTRS2016

Considerations for the Use of Remote Gaze Tracking to Assess Behavior in Flight Simulators

Complex user interfaces (such as those found in an aircraft cockpit) may be designed from first principles, but inevitably must be evaluated with real users. User gaze data can provide valuable information that can help to interpret other actions that change the state of the system. However, care must be taken to ensure that any conclusions drawn from gaze data are well supported. Through a combination of empirical and simulated data, we identify several considerations and potential pitfalls when measuring gaze behavior in high-fidelity simulators. We show that physical layout, behavioral differences, and noise levels can all substantially alter the quality of fit for algorithms that segment gaze measurements into individual fixations. We provide guidelines to help investigators ensure that conclusions drawn from gaze tracking data are not artifactual consequences of data quality or analysis techniques.

eye tracking↗
NASA NTRS1985

Nondestructive evaluation of composites by optical time domain reflectometry

Results in the measurement of slowly varying mechanical loading functions on composites using optical time domain reflectometry (OTDR) in imbedded optical fiber during both simulated manufacture and use are reviewed. First, the basic theoretical and experimental principles of the OTDR system are described. Next, the mechanical system of the composite and the imbedded fiber is analyzed. Results of measurement obtained for various loading functions applied to material specimens are then described and system limitations on spatial resolution, strain amplitude sensitivity, and frequency response are explained in terms of the range and resolution limits of the OTDR system.

Claus, R. O.↗
NASA NTRSDate not supplied

Effects of Rotation on Internal Structure and Dynamics of Main-Sequence Stars

Current state-of-the-art computer simulations allow us to build 3D dynamical and radiative models of stars from physical first principles with a high degree of realism. The radiative 3D dynamical stellar models obtained with the StellarBox code take into account the effects of turbulence, stellar abundances, a realistic equation of state, and radiative energy transport. In this talk, I will discuss the effects of rotation on the turbulent dynamics and surface structure for a 1.47Msun star for rotational periods of 1 and 14 days. The simulations are performed with the computational domain at various latitudes. The models reproduce stellar granulation, the subsurface shear layer, structural changes in convection, and the tachocline, which is the interface between the inner radiative zone and the outer convection zone and plays a crucial role in stellar variability. In particular, the model results reveal the formation of differential rotation and meridional circulation.

SMD↗
NASA NTRS1997

The Effects of Magnetic Nozzle Configurations on Plasma Thrusters

Over the course of eight years, the Ohio State University has performed research in support of electric propulsion development efforts at the NASA Lewis Research Center, Cleveland, OH. This research has been largely devoted to plasma propulsion systems including MagnetoPlasmaDynamic (MPD) thrusters with externally-applied, solenoidal magnetic fields, hollow cathodes, and Pulsed Plasma Microthrusters (PPT's). Both experimental and theoretical work has been performed, as documented in four master's theses, two doctoral dissertations, and numerous technical papers. The present document is the final report for the grant period 5 December 1987 to 31 December 1995, and summarizes all activities. Detailed discussions of each area of activity are provided in appendices: Appendix 1 - Experimental studies of magnetic nozzle effects on plasma thrusters; Appendix 2 - Numerical modeling of applied-field MPD thrusters; Appendix 3 - Theoretical and experimental studies of hollow cathodes; and Appendix 4 -Theoretical, numerical and experimental studies of pulsed plasma thrusters. Especially notable results include the efficacy of using a solenoidal magnetic field downstream of a plasma thruster to collimate the exhaust flow, the development of a new understanding of applied-field MPD thrusters (based on experimentally-validated results from state-of-the art, numerical simulation) leading to predictions of improved performance, an experimentally-validated, first-principles model for orificed, hollow-cathode behavior, and the first time-dependent, two-dimensional calculations of ablation-fed, pulsed plasma thrusters.

Turchi, P. J.↗
NASA NTRS2019

3D Radiative Hydrodynamics Modeling of Convection of Stars to Probe Their Interiors and Photospheric Properties

The dramatic flow of data from the Kepler and K2 missions opens the opportunity to significantly improve our knowledge of stellar interiors, surface dynamics, and structure. However, interpretation of these observations is a challenging task because it depends on tiny effects that can be studied only with advanced first-principles modeling. We present results of 3D time-dependent radiative hydrodynamic simulations of stellar outer convection zones and atmospheres taking into account chemical composition, radiative transfer, turbulence effects, and a realistic equation of state for main sequence stars. We will discuss properties of convective structure and dynamics, convective overshoot, effects of magnetic fields and rotation, as well as the potential influence of turbulent surface dynamics on high-precision RV measurements.

Photospheric↗
NASA NTRS2019

High-Performance Computing Optimization for Aladyn – Adaptive Neural Network Molecular Dynamics Mini-Application

This report provides a description and performance evaluation of the optimization techniques for high performance computing (HPC) implementation of the open source Computational Materials mini-application Aladyn (https://github.com/nasa/aladyn). Aladyn is a basic molecular dynamics code written in FORTRAN 2003, which is designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to efficiently reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of the more expensive quantum mechanics-based calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory (DFT) method. While achieving orders of magnitude faster computational performance than DFT, the ANN-based approach was still very computationally demanding compared to the conventional approach of using empirically fitted energy functions. After its initial development, Aladyn was evaluated and optimized by experts at the NASA Advanced Supercomputing (NAS) division to exploit modern supercomputer architectures. The code has been optimized for execution on multicore central processing units (CPUs), including Intel® Skylake microarchitecture, and on graphic accelerators, such as Nvidia® V100 graphic processing units (GPUs), using Open Multi-Processing (OpenMP) and Open Accelerators (OpenACC) programming interfaces. The optimization achieved a speedup of 4.7 times the baseline version on CPU performance and an additional 2.4 times on CPU+GPU performance. Atomistic computer simulations are a fundamental tool in materials research to model material properties form physics-based first principles. Atomic interaction, governed by Quantum Mechanics (QM) require sophisticated and highly computationally demanding mathematical models to calculate [1]. Classical methods use approximate functional forms, empirically fitted through a set of variable parameters to emulate atomic energies as direct functions of atomic coordinates [2]. While empirical potentials are computationally much simpler, allowing simulations of large-scale systems of up to a trillion (1012) atoms [3], they are substantially less accurate compared to quantum calculations and applicable only to very specific atomic configurations or predefined crystallographic phases. A recently suggested approach is to use heuristic machine learning methods [4], such as those based on Adaptive Neural Networks (ANNs) to predict atomic energies, after being trained on a sufficiently large database of QM-calculated structures [5,6]. This approach reduces significantly the computational complexity, allowing for simulations of orders of magnitude larger systems compared to QM-based methods without compromising accuracy. Still, compared to classical methods using empirical energy functions, ANN methods remain two- to three orders of magnitude more computationally demanding. Hence, the computational cost of simulations, together with the need for extensive training of ANNs, still makes the practical implementation of ANN-based methods quite challenging. The purpose of the Aladyn mini-application software [7], available as open source at https://github.com/nasa/aladyn, is to be a testbed for exploring possible optimization strategies to develop highly scalable parallel algorithms for ANN-based atomistic simulations. Aladyn is aimed at utilizing the architecture of the high-end modern highperformance computing (HPC) hardware based on multicore central processing units (CPUs) equipped with graphic processing unit (GPU) accelerators. Specifically, the goal is to optimize the performance on a single HPC compute node, before implementing scaling to multi-node parallelization using message passing interface (MPI). At the same time, the open source code of Aladyn can serve as a training model for students and professors in academia.

Yamakov, Vesselin I.↗
NASA NTRS2012

Understanding Differences in the Response to Composition Change as Simulated by CCMVal Models

Chemistry climate models (CCMs) have a common conceptual basis. Differences in implementation lead to differences in the stratospheric ozone response to changes in composition and climate. Although evaluation by CCMVal-2 identified strengths and weaknesses of participant models, the evaluation results were not used to discriminate among projections for future ozone evolution, at least in part because the overall diagnostic evaluation did not cleanly relate to the differences in CCM response. Here we use a subset of CCMVal diagnostics and additional analysis to understand the differences in response. In the upper stratosphere, differences in simulated temperature and total odd nitrogen prior to increases in chlorine loading explain the large differences in CCM sensitivity. In the lower atmosphere, there are two principle contributions to differences in CCM sensitivity to chlorine and climate change. First, differences in the lower stratospheric ClO affect simulated sensitivity to chlorine. CCMs with best transport performance match NDACC column HCl measurements at a broad range of latitudes. Other CCMs disagree with observations due to differences in total inorganic chlorine, partitioning between HCl and ClONO2, or both. Differences in ClONO2 are directly related to differences in simulated ClO. Second, although all CCMs predict increased tropical upwelling, the rate of increase varies and contributes to differences in tropical ozone and the 60N-60S column average.

Douglass, Anne R.↗
NASA NTRS1993

Numerical simulations of a pulsed detonation wave augmentation device

We present here the concept of a hybrid engine for Single Stage To Orbit (SSTO) air-breathing hypersonic vehicle. This concept relies on the use of pulsed detonation waves, both for thrust generation and mixing/combustion augmentation. We describe the principles behind the engine concept, which we call the Pulsed Detonation Wave Augmentor (PDWA). We demonstrate the principles of operation for two possible configurations through numerical simulations. We also attempt a first approximation to engine design, and propose various applications.

Cambier, Jean-Luc↗
NASA NTRS2010

Modeling Common-Sense Decisions in Artificial Intelligence

A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable 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. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation of the dynamical models in a parameterized form reduces the task of common-sense-based decision making to a solution of the following hetero-associated-memory problem: store a set of m predetermined stochastic processes given by their probability distributions in such a way that when presented with an unexpected change in the form of an input out of the set of M inputs, the coupled motormental dynamics converges to the corresponding one of the m pre-assigned stochastic process, and a sample of this process represents the decision.

Zak, Michail↗
NASA NTRS2023

Simulated Inherent Optical Properties of Aquatic Particles Using the Equivalent Algal Populations (EAP) Model

Paired measurements of phytoplankton absorption and backscatter, the inherent optical properties central to the interpretation of ocean colour remote sensing data, are notoriously rare. We present a dataset of Chlorophyll a (Chl a) -specific phytoplankton absorption, scatter and backscatter for 17 different phytoplankton groups, derived from first principles using measured in vivo pigment absorption and a well-validated semi-analytical coated sphere model which simulates the full suite of biophysically consistent phytoplankton optical properties. The optical properties of each simulated phytoplankton cell are integrated over an entire size distribution and are provided at high spectral resolution. The model code is additionally included to enable user access to the complete set of wavelength-dependent, angularly resolved volume scattering functions. This optically coherent dataset of hyperspectral optical properties for a set of globally significant phytoplankton groups has potential for use in algorithm development towards the optimal exploitation of the new age of hyperspectral satellite radiometry.

Equivalent Algal Populations↗
NASA NTRS2022

First-Principles Theory of the Rate of Magnetic Reconnection in Magnetospheric and Solar Plasmas

The rate of magnetic reconnection is of the utmost importance in a variety of processes because it controls, for example, the rate energy is released in solar flares, the speed of the Dungey convection cycle in Earth’s magnetosphere, and the energy release rate in harmful geomagnetic substorms. It is known from numerical simulations and satellite observations that the rate is approximately 0.1 in normalized units, but despite years of effort, a full theoretical prediction has not been obtained. Here, we present a first-principles theory for the reconnection rate in non-relativistic electron-ion collisionless plasmas, and show that the same prediction explains why Sweet-Parker reconnection is considerably slower. The key consideration of this analysis is the pressure at the reconnection site (i.e., the x-line). We show that the Hall electromagnetic fields in antiparallel reconnection cause an energy void, equivalently a pressure depletion, at the x-line, so the reconnection exhaust opens out, enabling the fast rate of 0.1. If the energy can reach the x-line to replenish the pressure, the exhaust does not open out. In addition to heliospheric applications, these results are expected to impact reconnection studies in planetary magnetospheres, magnetically confined fusion devices, and astrophysical plasmas.

Yi-Hsin Liu↗
NASA NTRS2012

Numerical Simulation of Rocket Exhaust Interaction with Lunar Soil

This technology development originated from the need to assess the debris threat resulting from soil material erosion induced by landing spacecraft rocket plume impingement on extraterrestrial planetary surfaces. The impact of soil debris was observed to be highly detrimental during NASA s Apollo lunar missions and will pose a threat for any future landings on the Moon, Mars, and other exploration targets. The innovation developed under this program provides a simulation tool that combines modeling of the diverse disciplines of rocket plume impingement gas dynamics, granular soil material liberation, and soil debris particle kinetics into one unified simulation system. The Unified Flow Solver (UFS) developed by CFDRC enabled the efficient, seamless simulation of mixed continuum and rarefied rocket plume flow utilizing a novel direct numerical simulation technique of the Boltzmann gas dynamics equation. The characteristics of the soil granular material response and modeling of the erosion and liberation processes were enabled through novel first principle-based granular mechanics models developed by the University of Florida specifically for the highly irregularly shaped and cohesive lunar regolith material. These tools were integrated into a unique simulation system that accounts for all relevant physics aspects: (1) Modeling of spacecraft rocket plume impingement flow under lunar vacuum environment resulting in a mixed continuum and rarefied flow; (2) Modeling of lunar soil characteristics to capture soil-specific effects of particle size and shape composition, soil layer cohesion and granular flow physics; and (3) Accurate tracking of soil-borne debris particles beginning with aerodynamically driven motion inside the plume to purely ballistic motion in lunar far field conditions. In the earlier project phase of this innovation, the capabilities of the UFS for mixed continuum and rarefied flow situations were validated and demonstrated for lunar lander rocket plume flow impingement under lunar vacuum conditions. Applications and improvements to the granular flow simulation tools contributed by the University of Florida were tested against Earth environment experimental results. Requirements for developing, validating, and demonstrating this solution environment were clearly identified, and an effective second phase execution plan was devised. In this phase, the physics models were refined and fully integrated into a production-oriented simulation tool set. Three-dimensional simulations of Apollo Lunar Excursion Module (LEM) and Altair landers (including full-scale lander geometry) established the practical applicability of the UFS simulation approach and its advanced performance level for large-scale realistic problems.

Liever, Peter↗