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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

A modified Monte Carlo model for the ionospheric heating rates.

A Monte Carlo method is adopted as a basis for the derivation of the photoelectron-heat input into the ionospheric plasma. Since a great number of Monte Carlo runs are required normally for the computation of the heating rates, this approach is modified in an attempt to minimize the computation time. The heat-input distributions are computed for arbitrarily small source elements that are spaced apart at distances corresponding to the photoelectron dissipation range. By means of a nonlinear interpolation procedure their individual heating-rate distributions are utilized to produce synthetic ones that fill the gaps between the Monte Carlo generated distributions. By varying these gaps and the corresponding number of Monte Carlo runs the accuracy of the results is tested to verify the validity of this procedure. It is concluded that this model can reduce the computation time by as much as an order of magnitude, thus improving the feasibility of including Monte Carlo calculations in self-consistent ionosphere models.

Mayr, H. G.↗
NASA NTRS1972

A modified Monte Carlo model for the ionospheric heating rates

A Monte Carlo method is adopted as a basis for the derivation of the photoelectron heat input into the ionospheric plasma. This approach is modified in an attempt to minimize the computation time. The heat input distributions are computed for arbitrarily small source elements that are spaced at distances apart corresponding to the photoelectron dissipation range. By means of a nonlinear interpolation procedure their individual heating rate distributions are utilized to produce synthetic ones that fill the gaps between the Monte Carlo generated distributions. By varying these gaps and the corresponding number of Monte Carlo runs the accuracy of the results is tested to verify the validity of this procedure. It is concluded that this model can reduce the computation time by more than a factor of three, thus improving the feasibility of including Monte Carlo calculations in self-consistent ionosphere models.

Mayr, H. G.↗
NASA NTRS1968

A modified Monte Carlo procedure.

Histogram construction via algebraic Monte Carlo method, determining simultaneous effect of several input statistical variables on output variable

Africano, R. C.↗
NASA NTRSDate not supplied

Adaptive Stress Testing of Trajectory Predictions in Flight Management Systems

To find failure events and their likelihoods in flight-critical systems, we investigate the use of an advanced black-box stress testing approach called adaptive stress testing. We analyze a trajectory predictor from a developmental commercial flight management system which takes as input a collection of lateral waypoints and en-route environmental conditions. Our aim is to search for failure events relating to inconsistencies in the predicted lateral trajectories. The intention of this work is to find likely failures and report them back to the developers so they can address and potentially resolve shortcomings of the system before deployment. To improve search performance, this work extends the adaptive stress testing formulation to be applied more generally to sequential decision-making problems with episodic reward by collecting the state transitions during the search and evaluating at the end of the simulated rollout. We use a modified Monte Carlo tree search algorithm with progressive widening as our adversarial reinforcement learner. The performance is compared to direct Monte Carlo simulations and to the cross-entropy method as an alternative importance sampling baseline. The goal is to find potential problems otherwise not found by traditional requirements-based testing. Results indicate that our adaptive stress testing approach finds more failures and finds failures with higher likelihood relative to the baseline approaches.

adaptive stress testing↗
NASA NTRS2020

Adaptive Stress Testing: Finding Likely Failure Events with Reinforcement Learning

Finding the most likely path to a set of failure states is important to the analysis of safety-critical systems that operate over a sequence of time steps, such as aircraft collision avoidance systems and autonomous cars. In many applications such as autonomous driving, failures cannot be completely eliminated due to the complex stochastic environment in which the system operates.As a result, safety validation is not only concerned about whether a failure can occur, but also discovering which failures are most likely to occur. This article presents adaptive stress testing (AST), a framework for finding the most likely path to a failure event in simulation. We consider a general black box setting for partially observable and continuous-valued systems operating in an environment with stochastic disturbances. We formulate the problem as a Markov decision process and use reinforcement learning to optimize it. The approach is simulation-based and does not require internal knowledge of the system, making it suitable for black-box testing of large systems. We present different formulations depending on whether the state is fully observable or partially observable. In the latter case, we present a modified Monte Carlo tree search algorithm that only requires access to the pseudorandom number generator of the simulator to overcome partial observability. We also present an extension of the framework, called differential adaptive stress testing (DAST), that can find failures that occur in one system but not in another. This type of differential analysis is useful in applications such as regression testing, where we are concerned with finding areas of relative weakness compared to a baseline. We demonstrate the effectiveness of the approach on an aircraft collision avoidance application, where a prototype aircraft collision avoidance system is stress tested to find the most likely scenarios of near mid-air collision.

Verification and Validation↗
NASA NTRS1997

Development of a Space Radiation Monte Carlo Computer Simulation

The ultimate purpose of this effort is to undertake the development of a computer simulation of the radiation environment encountered in spacecraft which is based upon the Monte Carlo technique. The current plan is to adapt and modify a Monte Carlo calculation code known as FLUKA, which is presently used in high energy and heavy ion physics, to simulate the radiation environment present in spacecraft during missions. The initial effort would be directed towards modeling the MIR and Space Shuttle environments, but the long range goal is to develop a program for the accurate prediction of the radiation environment likely to be encountered on future planned endeavors such as the Space Station, a Lunar Return Mission, or a Mars Mission. The longer the mission, especially those which will not have the shielding protection of the earth's magnetic field, the more critical the radiation threat will be. The ultimate goal of this research is to produce a code that will be useful to mission planners and engineers who need to have detailed projections of radiation exposures at specified locations within the spacecraft and for either specific times during the mission or integrated over the entire mission. In concert with the development of the simulation, it is desired to integrate it with a state-of-the-art interactive 3-D graphics-capable analysis package known as ROOT, to allow easy investigation and visualization of the results. The efforts reported on here include the initial development of the program and the demonstration of the efficacy of the technique through a model simulation of the MIR environment. This information was used to write a proposal to obtain follow-on permanent funding for this project.

Pinsky, Lawrence S.↗
NASA NTRS1992

Monte Carlo simulation of electron acceleration in modified relativistic shocks

We give a brief review of Monte Carlo simulations of nonlinear Fermi shock acceleration and then give new results on electron acceleration in SNRs and in relativistic parallel shocks. The acceleration of low energy electrons in shocks is poorly understood, but even when energetic electrons are considered, where electron and proton scattering should be qualitatively similar, dramatic differences result between electron and proton acceleration in relativistic shocks. If the shocked plasma is a mixture of electrons and protons, the electrons are accelerated much less efficiently than protons. We predict that only e(-)-e(+) pair dominated plasmas can produce significant radio emission in relativistic flows if the standard Fermi mechanism operates in parallel shocks.

Ellison, Donald C.↗
NASA NTRS2000

Testing Models of Resonant Compton Scattering in X-Ray Pulsars

Over the performance period covered by the grant, the principal investigator modified a Monte Carlo Compton scattering code to model the propagation of x-rays through the magnetosphere of accreting neutron stars. These modifications were made to enable the author to compare the observations of x-ray pulsars to theoretical models of the system. The original code was designed to study relativistic plasmas with one of two geometries: a plane parallel plasma with a differential relativistic bulk velocity, and a static spherically symmetric plasma.- This code did not treat gravitational bending or bulk motion in the magnetosphere of a neutron star. Under the grant, the author incorporated code to trace light paths in a Schwarzschild metric. The code was modified to keep track of the photon polarization during propagati on. The investigator also modified the code so that bulk motion in an axisymmetric system is treated properly. An approximate treatment for resonant Compton scattering was added to the code. Finally, code was added that creates model observables that can be compared to observations, such as projected x-ray emission maps and energy-dependent light curves. Comparison to observations is now commencing.

Brainerd, Jerome J.↗
DOE OSTI2024

Reparameterizing Litter Decomposition Using a Simplified Monte Carlo Method Improves Litter Decay Simulated by a Microbial Model and Alters Bioenergy Soil Carbon Estimates

Litter decomposition determines soil organic matter (SOM) formation and plant-available nutrient cycles. Therefore, accurate model representation of litter decomposition is critical to improving soil carbon (C) projections of bioenergy feedstocks. Soil C models that simulate microbial physiology (i.e., microbial models) are new to bioenergy agriculture, and their parameterization is often based on small datasets or manual calibration to reach benchmarks. Here, we reparameterized litter decomposition in a microbial soil C model (CORPSE - Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment) using the continental-scale Long-term Inter-site Decomposition Experiment Team (LIDET) dataset which documents decomposition across a range of litter qualities over a decade. Here, we conducted a simplified Monte Carlo simulation that constrained parameter values to reduce computational costs. The LIDET-derived parameters improved modeled C and nitrogen (N) remaining, decomposition rates, and litter mean residence times as compared to Baseline parameters. We applied the LIDET litter decomposition parameters to a microbial bioenergy model (Fixation and Uptake of Nitrogen – Bioenergy Carbon, Rhizosphere, Organisms, and Protection) to examine soil C estimates generated by Baseline and LIDET parameters. LIDET parameters increased estimated soil C in bioenergy feedstocks, with even greater increases under elevated plant inputs (i.e., by increasing residue, N fertilization). This was due to the integrated effects of plant litter quantity, quality, and agricultural practices (tillage, fertilization). Collectively, we developed a simple framework for using large-scale datasets to inform the parameterization of microbial models that impacts projections of soil C for bioenergy feedstocks.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

Navigation requirements for rendezvous with the satellites of Mars.

Navigation aspects of a rendezvous mission to Deimos (the outer satellite of Mars) were examined using a modified Viking Monte Carlo error analysis program. Rendezvous is initiated by two-impulse transfer from an observation orbit cotangent with the orbit of Deimos. Television sightings of the satellite against a star background will allow a 20 km closest approach radius (R99) 99% of the time. This is well within the 100 km range of the terminal rendezvous radar. An additional delta-V capability of about 100 m/sec (above the nominal) must be allocated to account for the statistical nature of the mission. This delta-V requirement was found to be very sensitive to the level of satellite ephemeris error and maneuver execution error. The R99 on the other hand, is sensitive to the in-orbit DSN error and the maneuver execution error.

Satin, A. L.↗
NASA NTRS1989

Determination of solar flare accelerated ion angular distributions from SMM gamma ray and neutron measurements and determination of the He-3/H ratio in the solar photosphere from SMM gamma ray measurements

Comparisons of Solar Maximum Mission (SMM) observations of gamma-ray line and neutron emission with theoretical calculation of their expected production by flare accelerated ion interactions in the solar atmosphere have led to significant advances in the understanding of solar flare particle acceleration and interaction, as well as the flare process itself. These comparisons have enabled the determination of, not only the total number and energy spectrum of accelerated ions trapped at the sun, but also the ion angular distribution as they interact in the solar atmosphere. The Monte Carlo program was modified to include in the calculations of ion trajectories the effects of both mirroring in converging magnetic fields and of pitch angle scattering. Comparing the results of these calculations with the SMM observations, not only the angular distribution of the interacting ions can be determined, but also the initial angular distribution of the ions at acceleration. The reliable determination of the solar photospheric He-3 abundance is of great importance for understanding nucleosynthesis in the early universe and its implications for cosmology, as well as for the study of the evolution of the sun. It is also essential for the determinations of the spectrum and total number of flare accelerated ions from the SMM/GRS gamma-ray line measurements. Systematic Monte Carlo calculations of the time dependence were made as a function of the He-3 abundance and other variables. A new series of calculations were compared for the time-dependent flux of 2.223 MeV neutron capture line emission and the ratio of the time-integrated flux in the 2.223 MeV line to that in the 4.1 to 6.4 MeV nuclear deexcitation band.

Lingenfelter, Richard E.↗
NASA NTRS1975

Solid-propellant rocket motor ballistic performance variation analyses

Results are presented of research aimed at improving the assessment of off-nominal internal ballistic performance including tailoff and thrust imbalance of two large solid-rocket motors (SRMs) firing in parallel. Previous analyses using the Monte Carlo technique were refined to permit evaluation of the effects of radial and circumferential propellant temperature gradients. Sample evaluations of the effect of the temperature gradients are presented. A separate theoretical investigation of the effect of strain rate on the burning rate of propellant indicates that the thermoelastic coupling may cause substantial variations in burning rate during highly transient operating conditions. The Monte Carlo approach was also modified to permit the effects on performance of variation in the characteristics between lots of propellants and other materials to be evaluated. This permits the variabilities for the total SRM population to be determined. A sample case shows, however, that the effect of these between-lot variations on thrust imbalances within pairs of SRMs is minor in compariosn to the effect of the within-lot variations. The revised Monte Carlo and design analysis computer programs along with instructions including format requirements for preparation of input data and illustrative examples are presented.

Sforzini, R. H.↗
NASA NTRS1989

Statistical fluctuations in Monte Carlo calculations

The time counter and modified Nanbu simulation techniques are analyzed, with emphasis placed on the convergence of the calculations to a steady macroscopic state. Such variables as translational and rotational temperature, and flow velocity, sampled at several points in the flowfield, are considered. Both macroscopic averages and molecular distribution functions are analyzed. The calculation of inelastic collisions, in which transfer of energy between translational and internal energy modes is performed, is achieved through the use of the Larsen-Borgnakke phenomenological model. It is noted that, with reference to translational temperature, the time counter method shows less statistical scatter than that found with the modified Nanbu simulation technique.

Boyd, I. D.↗
NASA NTRS2002

Monte Carlo transport model comparison with 1A GeV accelerated iron experiment: heavy-ion shielding evaluation of NASA space flight-crew foodstuff

Deep-space manned flight as a reality depends on a viable solution to the radiation problem. Both acute and chronic radiation health threats are known to exist, with solar particle events as an example of the former and galactic cosmic rays (GCR) of the latter. In this experiment Iron ions of 1A GeV are used to simulate GCR and to determine the secondary radiation field created as the GCR-like particles interact with a thick target. A NASA prepared food pantry locker was subjected to the iron beam and the secondary fluence recorded. A modified version of the Monte Carlo heavy ion transport code developed by Zeitlin at LBNL is compared with experimental fluence. The foodstuff is modeled as mixed nuts as defined by the 71st edition of the Chemical Rubber Company (CRC) Handbook of Physics and Chemistry. The results indicate a good agreement between the experimental data and the model. The agreement between model and experiment is determined using a linear fit to ordered pairs of data. The intercept is forced to zero. The slope fit is 0.825 and the R2 value is 0.429 over the resolved fluence region. The removal of an outlier, Z=14, gives values of 0.888 and 0.705 for slope and R2 respectively. c2002 COSPAR. Published by Elsevier Science Ltd. All rights reserved.

NASA Discipline Radiation Health↗
DOE OSTI2024

The Transient Multi-Level method for Monte Carlo reactor statics calculations

The Transient Multi-Level (TML) method is applied to a time-dependent Monte Carlo transport solver to offload some of the computational burden of the expensive Monte Carlo solve to lower-order Coarse Mesh Finite Difference (CMFD) and Exact Point Kinetics Equations (EPKE) solvers via factorization of the neutron flux at the transport and CMFD levels using the Predictor Corrector Quasi-Static Method (PCQM). The Monte Carlo transient is solved by a modified fission source iteration scheme that introduces a single transient source bank. The method is implemented in the production-level Monte Carlo code, Shift, and verified with prescribed reactivity ramps from the two-dimensional version of the C5G7-TD reactor benchmark. The results show that, as compared to other quasi-static methods, the TML reduces the stochastic noise inherent to the transient Monte Carlo solver by factors of ~2 to 6 for various norm comparisons of the reactor power amplitude. Finally, the TML additionally reduces the number of Monte Carlo evaluations needed to simulate the transient, leading to roughly an order of magnitude improvement in CPU time relative to the standard PCQM for the problems tested.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1990

A multigenerational Monte Carlo model of a comet coma

A steady state multigenerational Monte Carlo model was developed to describe the distribution of a neutral coma species which was produced after several photodissociation steps. This distribution can be compared with either line profiles derived from long slit spectroscopic observations or narrow band imaging, and be used to determine the elemental abundances present in the comet coma. A Monte Carlo model was chosen due to limitations in standard forms of more analytic models, such as those of Haser and Festou. In contrast to the analytical models, the Monte Carlo method can be modified to include new physical parameters.

Ferro, Anthony J.↗
NASA NTRS1991

Segregation parameters and pair-exchange mixing models for turbulent nonpremixed flames

The progress of chemical reactions in nonpremixed turbulent flows depends on the coexistence of reactants, which are brought together by mixing. The degree of mixing can strongly influence the chemical reactions and it can be quantified by segregation parameters. In this paper, the relevance of segregation parameters to turbulent mixing and chemical reactions is explored. An analysis of the pair-exchange mixing models is performed and an explanation is given for the peculiar behavior of such models in homogeneous turbulence. The nature of segregation parameters in a H2/Ar-air nonpremixed jet flame is investigated. The results show that Monte Carlo simulation with the modified Curl's mixing model predicts segregation parameters in close agreement with the experimental values, providing an indirect validation for the theoretical model.

Chen, J.-Y.↗