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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

A physical model of radiated enhancement of plasma-surrounded antenna

A phenomenon that the radiated power may be enhanced when an antenna is surrounded by a finite plasma shell has been found in numerical and experimental studies. In this paper, a physical model was built to express the mechanism of the radiated enhancement. In this model, the plasma shell is treated as a parallel connection of a capacitance and a conductance whose parameters change with the system parameters (plasma density, collision frequency, and antenna frequency). So, the radiated enhancement can be explained by the resonance between the plasma shell and the infinite free space. Furthermore, the effects of system parameters on the radiated power are given and effects corresponding to mechanisms are performed based on the physical model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Biochemical physics modeling of biological nano-motors

We present a biochemical physics model accounting for the dynamics and energetics of both translational and rotational protein motors. A modified version of the hand-over-hand mechanism considering competitive inhibition by ADP is presented. Transition state-like theory is used to reconstruct the time dependent free-energy landscape of the cycle catalyst process that allows to predicting the number of steps or rotations that a single motor can perform. In addition, following the usual approach of chemical kinetics, we calculate the average translational velocity and also the stopping time of processes involving a collectivity of motors, such as exocytosis and endocytosis processes. Finally, we formulate a stochastic model reproducing very well single realizations of kinesin and rotary ATPases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Skeletides: A Modular, Simplified Physical Model of Protein Secondary Structure

Three-dimensional (3D) models are essential for visualization and conceptual understanding of complex architectures such as protein structure. Although there is a plethora of software platforms that allow digital depictions of protein structure at an atomic level in silico, physical models are needed to convey an intuitive understanding of biomolecular architecture. However, it is a challenge to represent all the relevant features of proteins in a single physical model due to their sheer structural complexity. Here, we describe a modular protein model that focuses only on representation of the secondary structure—the underlying structural skeleton. The simplified model consists of amino acid units, which can be linked together to reproduce the two most fundamental structural features of protein secondary structure: the relative positions of the amino acid alpha carbon atoms, and the intra-main chain hydrogen bonding pattern. We use 3D printing and magnets to create a set of three modular amino acid building blocks, which when linked together into a chain, can faithfully represent alpha helices, beta sheets, and turns. These simple to make models can be used to quickly assemble the alpha carbon trace of an entire protein domain, which conveys a tactile experience of the complexity of protein skeletal architecture. These models highlight the modularity of protein structure: where a single structural unit, the amino acid, can be linked together to form a larger, regular secondary structure. These models also have a propensity to spontaneously organize into alpha helices and beta sheets, as demonstrated by their ability to autonomously assemble when placed in a circulating water tank. These models provide a missing educational tool to expand knowledge of protein structure, foster deeper insight into protein folding, and inspire greater interest in biomacromolecular architecture.

36 MATERIALS SCIENCE↗
NASA NTRS1990

Comparison of analytical and physical modeling of planetesimal accumulation

Three cases for which the analytic solutions to the planetary embryo coagulation equation are known, namely those of constant coagulation rate, of rate proportional to the sum of the masses of the two colliding bodies, and of rate proportional to the product of their masses, are presently used to test the mathematical validity of the Wetherill and Stewart (1989) physical model for the evolution of planetary embryos' mass distribution. In all cases, excellent agreement is found between numerical physical modeling results and those of the analytic solutions. The treatment of the runaway case can proceed via extension of the efforts of Trubnikov (1971).

Wetherill, George W.↗
NASA NTRS2008

Interpolating Fields of Carbon Monoxide Data Using a Hybrid Statistical-Physical Model

Atmospheric Carbon Monoxide (CO) is a pollutant gas of which the US congress has mandated regular monitoring, and satellite sensors can be used to retrieve regional concentrations of CO over several vertical layers. However, CO at cloudy locations cannot be observed and have to be estimated from the observed data set, resulting in an interpolation problem. The current state-of-the-art solution is to combine prior information, computed by a deterministic physical model, with observations. However, the deterministic model may introduce uncertainties that do not derive from the data. While sharing certain features with the physical model, this paper presents a Bayesian hierarchical model for interpolating CO on a 3-dimensional spatial grid, across time. To our knowledge such a model has not been considered before. The model is applied to a hypothetical air-quality monitoring scenario, and is compared to existing interpolation methods. The results provide motivation for the use of the statistical model for regional to local applications.

Arellano, A. A.↗
DOE OSTI2015

On the Statistical Calibration of Physical Models

ABSTRACT We introduce a novel statistical calibration framework for physical models, relying on probabilistic embedding of model discrepancy error within the model. For clarity of illustration, we take the measurement errors out of consideration, calibrating a chemical model of interest with respect to a more detailed model, considered as “truth” for the present purpose. We employ Bayesian statistical methods for such model‐to‐model calibration and demonstrate their capabilities on simple synthetic models, leading to a well‐defined parameter estimation problem that employs approximate Bayesian computation. The method is then demonstrated on two case studies for calibration of kinetic rate parameters for methane air chemistry, where ignition time information from a detailed elementary‐step kinetic model is used to estimate rate coefficients of a simple chemical mechanism. We show that the calibrated model predictions fit the data and that uncertainty in these predictions is consistent in a mean‐square sense with the discrepancy from the detailed model data.

Sargsyan, K.↗
DOE OSTI2014

SU-E-T-64: CG-Based Radiation Therapy Simulator with Physical Modeling for Avoidance of Collisions Between Gantry and Couch Or Patient

Purpose: It is time-consuming and might cause re-planning to check couch-gantry and patient-gantry collisions on a radiotherapy machine when using couch rotations for non-coplanar beam angles. The aim of this study was to develop a computer-graphics (CG)-based radiation therapy simulator with physical modeling for avoidance of collisions between gantry and couch or patient on a radiotherapy machine. Methods: The radiation therapy simulator was three-dimensionally constructed including a radiotherapy machine (Clinac iX, Varian Medical Systems), couch, and radiation treatment room according to their designs by using a physical-modeling-based computer graphics software (Blender, free and open-source). Each patient was modeled by applying a surface rendering technique to their planning computed tomography (CT) images acquired from 16-slice CT scanner (BrightSpeed, GE Healthcare). Immobilization devices for patients were scanned by the CT equipment, and were rendered as the patient planning CT images. The errors in the collision angle of the gantry with the couch or patient between gold standards and the estimated values were obtained by fixing the gantry angle for the evaluation of the proposed simulator. Results: The average error of estimated collision angles to the couch head side was -8.5% for gantry angles of 60 to 135 degree, and -5.5% for gantry angles of 225 to 300 degree. Moreover, the average error of estimated collision angles to the couch foot side was -1.1% for gantry angles of 60 to 135 degree, and 1.4% for gantry angles of 225 to 300 degree. Conclusion: The CG-based radiation therapy simulator could make it possible to estimate the collision angle between gantry and couch or patient on the radiotherapy machine without verifying the collision angles in the radiation treatment room.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

THE IMPORTANCE OF PHYSICAL MODELS FOR DERIVING DUST MASSES AND GRAIN SIZE DISTRIBUTIONS IN SUPERNOVA EJECTA. I. RADIATIVELY HEATED DUST IN THE CRAB NEBULA

Recent far-infrared (IR) observations of supernova remnants (SNRs) have revealed significantly large amounts of newly condensed dust in their ejecta, comparable to the total mass of available refractory elements. The dust masses derived from these observations assume that all the grains of a given species radiate at the same temperature, regardless of the dust heating mechanism or grain radius. In this paper, we derive the dust mass in the ejecta of the Crab Nebula, using a physical model for the heating and radiation from the dust. We adopt a power-law distribution of grain sizes and two different dust compositions (silicates and amorphous carbon), and calculate the heating rate of each dust grain by the radiation from the pulsar wind nebula. We find that the grains attain a continuous range of temperatures, depending on their size and composition. The total mass derived from the best-fit models to the observed IR spectrum is 0.019-0.13 M{sub Sun }, depending on the assumed grain composition. We find that the power-law size distribution of dust grains is characterized by a power-law index of 3.5-4.0 and a maximum grain size larger than 0.1 {mu}m. The grain sizes and composition are consistent with what is expected for dust grains formed in a Type IIP supernova (SN). Our derived dust mass is at least a factor of two less than the mass reported in previous studies of the Crab Nebula that assumed more simplified two-temperature models. These models also require a larger mass of refractory elements to be locked up in dust than was likely available in the ejecta. The results of this study show that a physical model resulting in a realistic distribution of dust temperatures can constrain the dust properties and affect the derived dust masses. Our study may also have important implications for deriving grain properties and mass estimates in other SNRs and for the ultimate question of whether SNe are major sources of dust in the Galactic interstellar medium and in external galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1987

Detecting forest structure and biomass with C-band multipolarization radar - Physical model and field tests

The ability of C-band radar (4.75 GHz) to discriminate features of forest structure, including biomass, is tested using a truck-mounted scatterometer for field tests on a 1.5-3.0 m pygmy forest of cypress (Cupressus pygmaea) and pine (Pinus contorta ssp, Bolanderi) near Mendocino, CA. In all, 31 structural variables of the forest are quantified at seven sites. Also measured was the backscatter from a life-sized physical model of the pygmy forest, composed of nine wooden trees with 'leafy branches' of sponge-wrapped dowels. This model enabled independent testing of the effects of stem, branch, and leafy branch biomass, branch angle, and moisture content on radar backscatter. Field results suggested that surface area of leaves played a greater role in leaf scattering properties than leaf biomass per se. Tree leaf area index was strongly correlated with vertically polarized power backscatter (r = 0.94; P less than 0.01). Field results suggested that the scattering role of leaf water is enhanced as leaf surface area per unit leaf mass increases; i.e., as the moist scattering surfaces become more dispersed. Fog condensate caused a measurable rise in forest backscatter, both from surface and internal rises in water content. Tree branch mass per unit area was highly correlated with cross-polarized backscatter in the field (r = 0.93; P less than 0.01), a result also seen in the physical model.

Westman, Walter E.↗
NASA NTRS2014

Advanced Ground Systems Maintenance Physics Models for Diagnostics Project

The project will use high-fidelity physics models and simulations to simulate real-time operations of cryogenic and systems and calculate the status/health of the systems. The project enables the delivery of system health advisories to ground system operators. The capability will also be used to conduct planning and analysis of cryogenic system operations.

Technology Portfolio System↗
NASA NTRS1988

Moment constraints on physical models for quasi-periodic oscillations from Galactic X-ray sources

Shot-noise models provide a useful mathematical representation for some physical models for the quasi-periodic oscillations (QPOs) recently observed from several bright Galactic bulge and burst X-ray sources. Expressions are calculated for the first three moments for several versions of QPO shot-noise models that have appeared in the literature. It is shown that measurement of the third moment, together with measurement of the mean intensity and the power spectrum, can provide model-dependent constraints on important parameters of QPO shot-noise models, including the fraction of the X-ray intensity in shots and the shot rate. Under certain condtitions, a complete solution for all the shot-model parameters is possible.

Elsner, R. F.↗
NASA NTRSDate not supplied

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

As part of the Game Changing Development (GCD) Program, funded by NASA’s Space Technology Mission Directorate (STMD), the development of simulation capability for the prediction of extra-terrestrial Plume Surface Interaction (PSI) environments has been undertaken by the Fluid Dynamics Branch at NASA/MSFC. The Predictive Simulation Capability (PSC) Element is focused on creating simulation capability for the reliable and accurate prediction of PSI in Martian (~650 Pa) and Lunar (vacuum) ambient environments. In addition to the predictive simulation capability, the GCD Program also contains a companion Ground Testing Element for development of focused datasets for validation of predictive capability as well as a Flight-focused Instrumentation Element. This paper will present the status of implementing and maturing particle-particle interaction constituent physics models essential in simulating the landing surface granular material flow under PSI effects. This gas-particle multi-phase interaction modeling of plume impingement flow on the extra-terrestrial soil material is performed with the Gas-Granular Flow Solver (GGFS) addressed in a companion paper. The response of regolith particle flow induced by lander PSI requires accurate representation of the regolith granular material fluidic behavior and gas-granular interactions. The lunar regolith, as the extreme example, is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking particle shapes for the very jagged particles. The combination of particle shape and size distribution has been identified as major drivers in the complex particle flow response and resulting crater shape characteristics of extraterrestrial granular material. Constituent models for spherical particles can be formulated directly from particle kinetics theory. Complex particle shapes can be modeled by gluing together elemental spherical shapes into composite particles, requiring a Discrete Element Model (DEM) particle kinetics modeling approach to extract data and formulate constituent models. Mixture constituent models for poly-disperse mixtures (i.e, containing distribution of particle sizes) have recently been developed. The required non-spherical particle mixture granular material response closure models are then obtained through small-scale unit physics DEM simulations for the range of particle shapes, mixtures and packing densities. The granular material response closure models are then implemented in the Eulerian granular flow formulation. This DEM-based constituent model extraction process and formulation of poly-disperse particle mixtures has been successfully developed by small business and academic partners in the development of the Gas-Granular Flow Solver (GGFS) simulation program simulation framework. The currently implemented capabilities have reached the capability level of modeling bi-disperse, non-spherical particle mixtures is being continuously extended towards computational modeling of full range irregular particle mixtures. Under the GCD project, this technology is being further developed, transferred to NASA analysts, and matured towards application readiness. The predictive simulation capability team under the GCD project has acquired the modeling tools and processes of the DEM based constituent model formulation from the GGFS development team and is developing the capability to replicate the existing process. This is the first important step towards the ability of the NASA team to independently perform such model development in a production setting. Further efforts are underway to migrate the DEM based model simulation process performed with the academic based tools to more capable Open Source, highly parallelized simulation tools for efficient operation on NASA HPC assets. Evaluation of the currently implemented (such as mono-disperse and bi-disperse spherical and irregular shape particle constituent model applications) and continuously evolving full-range particle physics models in the GGFS tool is performed by the NASA team to advance application readiness of the simulations. Application testing for complex PSI erosions and cratering scenarios such as the Apollo LM is performed for axi-symmetric and full 3D simulations to aid the tool developers in achieving practical application readiness for NASA projects. Important validation and application testing will further be performed against experimental data generated under the GCD PSI project experimental component.

Peter A Liever↗
DOE OSTI2020

A Simple Physical Model for Three-Terminal Tandem Cell Operation

We present a simple physical model that explains the device operation of a three-terminal (3T) IBC Si bottom cell platform that enables an efficient 3T tandem. If the IBC cell has two p-n junctions and one high-low junction (bipolar transistor), the two p-n junctions strongly interact via minority carrier diffusion in the base. In a two-BSF junction and one p-n junction IBC platform (single emitter), the BSF terminals interact via ohmic majority carrier current in the base. This interaction creates wide 'generating' power islands in the 2D current J 1 J 2 plane. The area and shape of these islands are determined by dissipative losses in the wafer base and in the cell contacts. Both positive and negative terminal currents are allowed for 3T operation, thus enabling both the top and bottom cells to operate at their full light currents. This opens new possibilities for 3T use in modules.

14 SOLAR ENERGY↗
DOE OSTI2021

Constraining Physical Models at Gigabar Pressures

High-energy-density (HED) experiments in convergent geometry are able to test physical models at pressures beyond hundreds of millions of atmospheres. The measurements from these experiments are generally highly integrated and require unique analysis techniques to procure quantitative information. This work describes a methodology to constrain the physics in convergent HED experiments by adapting the methods common to many other fields of physics. As an example, a mechanical model of an imploding shell is constrained by data from a thin-shelled direct-drive exploding-pusher experiment on the OMEGA Laser System using Bayesian inference, resulting in the reconstruction of the shell dynamics and energy transfer during the implosion. The model is tested by analyzing synthetic data from a 1-D hydrodynamics code and is sampled using a Markov chain Monte Carlo to generate the posterior distributions of the model parameters. The goal of this work is to demonstrate a general methodology that can be used to draw conclusions from a wide variety of HED experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Constraining physical models at gigabar pressures

High-energy-density (HED) experiments in convergent geometry are able to test physical models at pressures beyond hundreds of millions of atmospheres. The measurements from these experiments are generally highly integrated and require unique analysis techniques to procure quantitative infor mation. This work describes a methodology to constrain the physics in convergent HED experiments by adapting the methods common to many other fields of physics. As an example, a mechanical model of an imploding shell is constrained by data from a thin-shelled direct-drive exploding-pusher experiment on the OMEGA Laser System using Bayesian inference, resulting in the reconstruction of the shell dynamics and energy transfer during the implosion. The model is tested by analyzing synthetic data from a 1-D hydrodynamics code and is sampled using a Markov chain Monte Carlo to generate the posterior distributions of the model parameters. As a result, the goal of this work is to demonstrate a general methodology that can be used to draw conclusions from a wide variety of HED experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Physical model of the contact resistivity of metal-graphene junctions

While graphene-based technology shows great promise for a variety of electronic applications, including radio-frequency devices, the resistance of the metal-graphene contact is a technological bottleneck for the realization of viable graphene electronics. One of the most important factors in determining the resistance of a metal-graphene junction is the contact resistivity. Despite the large number of experimental works that exist in the literature measuring the contact resistivity, a simple model of it is still lacking. In this paper, we present a comprehensive physical model for the contact resistivity of these junctions, based on the Bardeen Transfer Hamiltonian method. This model unveils the role played by different electrical and physical parameters in determining the specific contact resistivity, such as the chemical potential of interaction, the work metal-graphene function difference, and the insulator thickness between the metal and graphene. In addition, our model reveals that the contact resistivity is strongly dependent on the bias voltage across the metal-graphene junction. This model is applicable to a wide variety of graphene-based electronic devices and thus is useful for understanding how to optimize the contact resistance in these systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1999

Physical Model of Asteroid 1620 Geographos From Radar and Optical Data

We develop a physical model of asteroid 1620 Geographos using Goldstone delay-Doppler radar images obtained Aug. 1994 (Ostro et al. 1996, Icarus 121, 46-66) with resolution as fine as 75 m, and optical lighcurves obtained in 1969, 1983, and 1993-94 (Magnusson et al. 1996, Icarus 123, 227-244).

asteroid 1620 Geographos delay-Doppler radar image↗