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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 NTRSDate not supplied

Multi-Model Monte Carlo Estimators for Trajectory Simulation

Predicting landing radius and other quantities of interest (QoI) for entry, descent, andlanding (EDL) applications requires a viable uncertainty propagation method for quantifying the impact of uncertainties in aerodynamics, atmosphere, mass properties, etc. While standard Monte Carlo (MC) simulation is the de facto standard for producing robust and unbiasedstatistical estimators, it is often infeasible for expensive, high-fidelity models. Low-fidelity models are commonly constructed to replace the high-fidelity model in MC simulation for computational speedup, but at the expense of accuracy and unbiasedness. Emerging multi-model MC methods are bridging this gap by combining predictions from two or more modelsof varying fidelity and computational cost for efficient and unbiased uncertainty propagation.This works establishes a proof of concept for using multi-model MC to increase the speed and precision of trajectory simulation for EDL. It is shown that combining a high-fidelity EDL model with low-fidelity models (e.g., data-driven, reduced physics) in this manner has the potential to yield significant efficiency and accuracy gains for certain EDL QoIs versusa standard MC approach. Moreover, the unbiasedness of multi-model MC predictions ishighlighted by showing increased accuracy versus an approach that leverages a low-fidelity model alone.

James E Warner↗
NASA NTRS1989

Monte-Carlo modeling of polar wind photoelectron distributions with anomalous heat flux

In situ measurements above the polar cap by the DE satellites show asymmetric field-aligned electron velocity distributions in the photoelectron energy range 5-60 eV. The formation of these anisotropic distributions is described by a collisional kinetic equation that includes the effects of Coulomb collisions (via a Fokker-Planck operator), those of a parallel electric field, and the magnetic mirror effects of the geomagnetic field. This equation is solved using a Monte Carlo simulation method. The simulation illustrates the formation of the portion of the observed electron distributions originating in the ionosphere and makes it possible to evaluate the significance of the suprathermal electrons at higher altitude. Both observations and calculations indicate that these electrons possess an energy flux which, by its effect on the polar-wind electric field, may influence the dynamics of the polar-wind outflow.

Yasseen, F.↗
NASA NTRSDate not supplied

Fast and Precise Trajectory Simulation for Entry, Descent, and Landing Using A Multi-Model Monte Carlo Approach

Predicting landing radius and other quantities of interest (QoI) for entry, descent, and landing (EDL) applications requires a viable uncertainty propagation method for quantifying the impact of uncertainties in wind pattern variations, atmospheric uncertainties, etc. While standard MC simulation is the defacto standard for providing robust and unbiased predictions,it is often infeasible for expensive, high-fidelity EDL models. Low-fidelity models are commonly constructed to replace the high-fidelity model in MC simulation for computational speedup,but at the expense of accuracy and unbiasedness. Emerging multi-model MC methods are bridging this gap by combining predictions from two or more models of varying fidelity and computational cost for efficient and unbiased uncertainty propagation. This work explores the use of multi-model MC for increasing the speed and precision of trajectory simulation for EDL. It is shown that combining a high-fidelity EDL model with low-fidelity models (e.g,data-driven, reduced physics) yields substantial computational speedup versus standard MCwith only the high-fidelity model. Moreover, the unbiasedness of multi-model MC predictions is highlighted by showing increased accuracy versus an approach that leverages a low-fidelity surrogate model alone.

James E. Warner↗
NASA NTRS2009

A Monte-Carlo Model for the Formation of Radiation-induced Chromosomal Aberrations

Purpose: To simulate radiation-induced chromosome aberrations in mammalian cells (e.g., rings, translocations, and dicentrics) and to calculate their frequency distributions following exposure to DNA double strand breaks (DSBs) produced by high-LET ions. Methods: The interphase genome was assumed to be comprised of a collection of 2 kbp rigid-block monomers following the random-walk geometry. Additional details for the modeling of chromosomal structure, such as chromosomal domains and chromosomal loops, were included. A radial energy profile for heavy ion tracks was used to simulate the high-LET pattern of induced DSBs. The induced DSB pattern depended on the ion charge and kinetic energy, but always corresponded to the DSB yield of 25 DSBs/cell/Gy. The sum of all energy contributions from Poisson-distributed particle tracks was taken to account for all possible one-track and multi-track effects. The relevant output of the model was DNA fragments produced by DSBs. The DSBs, or breakpoints, were defined by (x, y, z, l) positions, where x, y, z were the Euclidian coordinates of a DSB, and where l was the relative position along the genome. Results: The code was used to carry out Monte Carlo simulations for DSB rejoinings at low doses. The resulting fragments were analyzed to estimate the frequencies of specific types of chromosomal aberrations. Histograms for relative frequencies of chromosomal aberrations and P.D.F.s (probability density functions) of a given aberration type were produced. The relative frequency of dicentrics to rings was compared to empirical data to calibrate rejoining probabilities. Of particular interest was the predicted distribution of ring sizes, irrespective of their frequencies relative to other aberrations. Simulated ring sizes were . 4 kbp, which are far too small to be observed experimentally (i.e., by microscopy) but which, nevertheless, are conjectured to exist. Other aberrations, for example, inversions, translocations, as well as multi-centrics were also recorded. Conclusion: High-LET DNA damage affects the frequencies of chromosomal aberrations. The ratio of rings to dicentrics is correct for the genomic size cut-offs corresponding to available experimental data. The present work predicts a relative abundance of small rings following irradiation by heavy ions.

Ponomarev, Artem L.↗
NASA NTRS2011

The Effects of Surface Roughness on the NEAR XRS Elemental Results: Monte-Carlo Modeling

The objective of the NEAR-Shoemaker X-ray Gamma-Ray Spec1roscopy ("XGRS") investigation was to determine the elemental composition of the near-Earth asteroid 433 Eros. The X-ray Spectrometer (XRS) system measured the characteristic fluorescence of six major elements (Mg, Al, Si, S, Ca, Fe) in the 1-10 keV energy range excited by the interaction of solar X-rays with the upper 100 microns of the surface of 433 Eros. Various investigators, using both laboratory experiments and computer simulations have established that X-ray fluorescent line ratios can be influenced by small-scale surface roughness at high incidence or emission angles. The effect on the line ratio is specific to the geometry, excitation spectrum, and composition involved, In general, however, the effect is only substantial for ratios of lines with a significant energy difference between them: Fe/Si and Ca/Si are much more likely to be affected than AI/Si or Mg/Si. We apply a Monte-Carlo code to the specific geometry and spectrum of a major NEAR XRS solar flare observation, using an H chondrite composition as the substrate. The seventeen most abundant elements were included in the composition model, from oxygen to titanium.

Lin, Lucy F.↗
DOE OSTI2021

Monte Carlo Modeling and Design of Photon Energy Attenuation Layers for >10× Quantum Yield Enhancement in Si-Based Hard X-ray Detectors

High-energy (>20 keV) X-ray photon detection at high quantum yield, high spatial resolution, and short response time has long been an important area of study in physics. Scintillation is a prevalent method but limited in various ways. Directly detecting high-energy X-ray photons has been a challenge to this day, mainly due to low photon-to-photoelectron conversion efficiencies. Commercially available state-of-the-art Si direct detection products such as the Si charge-coupled device (CCD) are inefficient for >10 keV photons. Here, we present Monte Carlo simulation results and analyses to introduce a highly effective yet simple high-energy X-ray detection concept with significantly enhanced photon-to-electron conversion efficiencies composed of two layers: a top high-Z photon energy attenuation layer (PAL) and a bottom Si detector. We use the principle of photon energy down conversion, where high-energy X-ray photon energies are attenuated down to ≤10 keV via inelastic scattering suitable for efficient photoelectric absorption by Si. Our Monte Carlo simulation results demonstrate that a 10–30× increase in quantum yield can be achieved using PbTe PAL on Si, potentially advancing high-resolution, high-efficiency X-ray detection using PAL-enhanced Si CMOS image sensors.

47 OTHER INSTRUMENTATION↗
NASA NTRSDate not supplied

Trajectory Simulation Using Multi Model Monte Carlo with Python (MXMCPy)

EDL (Entry, Descent and Landing) is the process from a vehicle approaching a surface to landing on it, such as a Mars rover approaching the planet before landing. POST2 (Program to Optimize Simulated Trajectories 2) is Langley’s primary EDL simulation tool and is used NASA-wide for simulations. POST2 can generate highly accurate results by running a precise, but time consuming, Monte Carlo (MC) simulation hundreds or thousands of times. Though POST2 can produce highly accurate results, it can take unrealistic time spans to generate these results, which has created a need to speed up the simulations. The new NASA software MXMCPy offers various ways to speed up the simulations while getting just as precise results. Instead of running high-precision POST2 simulations many times for traditional MC, MXMCPy can run fewer high-precision POST2 simulations and many less precise POST2 simulations and merge the results. MXMCPy contains 30+ different methods which will each suggest different allocations between model precision levels, which result in results of varying precision based on the POST2 simulation. I created Python and Bash code to automate the 5 steps of MXMCPy’s application to POST2. I also tested the precision of traditional Monte Carlo simulations to MXMCPy aided simulations and found that MXMCPy can achieve substantially more precise solutions at the same computer runtime. I learned Test Driven Development (TDD), a software programming workflow which involves writing computer-automated tests before writing the code which is being tested. These tests are ran every time the code is changed and they can find glitches in the code much quicker than a human can. This programming workflow saved me a lot of time because the automated tests could tell me exactly where the code had stopped working. I plan on using this software development method for future academic and professional software projects. I have greatly enjoyed my work at NASA, so I have been applying to NASA internships and Pathways positions. In addition, I plan on applying what I have learned about Test Driven Development to my computer science courses next semester

James Warner↗
DOE OSTI2021

Atomic-Level Features for Kinetic Monte Carlo Models of Complex Chemistry from Molecular Dynamics Simulations

The high computational cost of evaluating atomic interactions recently motivated the development of computationally inexpensive kinetic models, which can be parametrized from MD simulations of complex chemistry of thousands of species or other processes and accelerate the prediction of the chemical evolution by up to four order of magnitude. Such models go beyond the commonly employed potential energy surface fitting methods in that they are aimed purely at describing kinetic effects. So far, such kinetic models utilize molecular descriptions of reactions and have been constrained to only reproduce molecules previously observed in MD simulations. Therefore, these descriptions fail to predict the reactivity of unobserved molecules, for example in the case of large molecules or solids. In this work, we propose a new approach for the extraction of reaction mechanisms and reaction rates from MD simulations, namely the use of atomic-level features. Using the complex chemical network of hydrocarbon pyrolysis as example, it is demonstrated that kinetic models built using atomic features are able to explore chemical reaction pathways never observed in the MD simulations used to parametrize them, a critical feature to describe rare events. Atomic-level features are shown to construct reaction mechanisms and estimate reaction rates of unknown molecular species from elementary atomic events. Through comparisons of the model ability to extrapolate to longer simulation timescales and different chemical compositions than the ones used for parameterization, it is demonstrated that kinetic models employing atomic features retain the same level of accuracy and transferability as the use of features based on molecular species, while being more compact and parametrized with less data. We also find that atomic features can better describe the formation of large molecules enabling the simultaneous description of small molecules and condensed phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1987

Electron heating in a Monte Carlo model of a high Mach number, supercritical, collisionless shock

Preliminary work in the investigation of electron injection and acceleration at parallel shocks is presented. A simple model of electron heating that is derived from a unified shock model which includes the effects of an electrostatic potential jump is described. The unified shock model provides a kinetic description of the injection and acceleration of ions and a fluid description of electron heating at high Mach number, supercritical, and parallel shocks.

Ellison, Donald C.↗
NASA NTRS2004

A Massively Parallel Hybrid Dusty-Gasdynamics and Kinetic Direct Simulation Monte Carlo Model for Planetary Applications

In order to understand the global structure, dynamics, and physical and chemical processes occurring in the upper atmospheres, exospheres, and ionospheres of the Earth, the other planets, comets and planetary satellites and their interactions with their outer particles and fields environs, it is often necessary to address the fundamentally non-equilibrium aspects of the physical environment. These are regions where complex chemistry, energetics, and electromagnetic field influences are important. Traditional approaches are based largely on hydrodynamic or magnetohydrodynamic (MHD) formulations and are very important and highly useful. However, these methods often have limitations in rarefied physical regimes where the molecular collision rates and ion gyrofrequencies are small and where interactions with ionospheres and upper neutral atmospheres are important. At the University of Michigan we have an established base of experience and expertise in numerical simulations based on particle codes which address these physical regimes. The Principal Investigator, Dr. Michael Combi, has over 20 years of experience in the development of particle-kinetic and hybrid kinetichydrodynamics models and their direct use in data analysis. He has also worked in ground-based and space-based remote observational work and on spacecraft instrument teams. His research has involved studies of cometary atmospheres and ionospheres and their interaction with the solar wind, the neutral gas clouds escaping from Jupiter s moon Io, the interaction of the atmospheres/ionospheres of Io and Europa with Jupiter s corotating magnetosphere, as well as Earth s ionosphere. This report describes our progress during the year. The contained in section 2 of this report will serve as the basis of a paper describing the method and its application to the cometary coma that will be continued under a research and analysis grant that supports various applications of theoretical comet models to understanding the inner comae of comets (grant NAGS- 13239 from the Planetary Atmospheres program).

Combi, Michael R.↗
NASA NTRS2003

A Monte Carlo Model for LET Spectra of 200 MeV Protons Used for Microelectronic Testing

The direct ionization Linear Energy Transfer (LET) for 200 MeV protons in silicon is much smaller than that for higher charged particles since LET increases as the square of the ion charge. However, occasionally the proton interacts with the silicon nuclei and produces a shower of fragments and a recoiling nucleus. When this happens, the LET produced is much greater than the direct ionization LET. Testing the single event effect susceptibility of components using energetic (200 MeV) protons is often the only viable option for system level testing commercial-off-the-shelf (COTS) avionics that have not been designed for space environments. However, the question of how a system tested with protons will perform in a heavy ion environment arises. Here the concern is not only with prediction of on-orbit upset rate, but also about possibility of on-orbit failures that were not observed during proton testing.

O'Neill, Patrick M.↗