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NASA NTRS2013

Vehicle Integrated Prognostic Reasoner (VIPR) Metric Report

This document outlines a set of metrics for evaluating the diagnostic and prognostic schemes developed for the Vehicle Integrated Prognostic Reasoner (VIPR), a system-level reasoner that encompasses the multiple levels of large, complex systems such as those for aircraft and spacecraft. VIPR health managers are organized hierarchically and operate together to derive diagnostic and prognostic inferences from symptoms and conditions reported by a set of diagnostic and prognostic monitors. For layered reasoners such as VIPR, the overall performance cannot be evaluated by metrics solely directed toward timely detection and accuracy of estimation of the faults in individual components. Among other factors, overall vehicle reasoner performance is governed by the effectiveness of the communication schemes between monitors and reasoners in the architecture, and the ability to propagate and fuse relevant information to make accurate, consistent, and timely predictions at different levels of the reasoner hierarchy. We outline an extended set of diagnostic and prognostics metrics that can be broadly categorized as evaluation measures for diagnostic coverage, prognostic coverage, accuracy of inferences, latency in making inferences, computational cost, and sensitivity to different fault and degradation conditions. We report metrics from Monte Carlo experiments using two variations of an aircraft reference model that supported both flat and hierarchical reasoning.

Cornhill, Dennis↗
NASA NTRS2017

Development of a Detailed Surface Chemistry Framework in DSMC

Many of the current direct simulation Monte Carlo (DSMC) codes still employ only simple surface catalysis models. These include only basic mechanisms such as dissociation, recombination, and exchange reactions, without any provision for adsorption and finite rate kinetics. Incorporating finite rate chemistry at the surface is increasingly becoming a necessity for various applications such as high speed re-entry flows over thermal protection systems (TPS), micro-electro-mechanical systems (MEMS), surface catalysis, etc. In the recent years, relatively few works have examined finite-rate surface reaction modeling using the DSMC method.In this work, a generalized finite-rate surface chemistry framework incorporating a comprehensive list of reaction mechanisms is developed and implemented into the DSMC solver SPARTA. The various mechanisms include adsorption, desorption, Langmuir-Hinshelwood (LH), Eley-Rideal (ER), Collision Induced (CI), condensation, sublimation, etc. The approach is to stochastically model the various competing reactions occurring on a set of active sites. Both gas-surface (e.g., ER, CI) and pure-surface (e.g., LH, desorption) reaction mechanisms are incorporated. The reaction mechanisms could also be catalytic or surface altering based on the participation of the bulk-phase species (e.g., bulk carbon atoms). Marschall and MacLean developed a general formulation in which multiple phases and surface sites are used and we adopt a similar convention in the current work. Microscopic parameters of reaction probabilities (for gas-surface reactions) and frequencies (for pure-surface reactions) that are require for DSMC are computed from the surface properties and macroscopic parameters such as rate constants, sticking coefficients, etc. The energy and angular distributions of the products are decided based on the reaction type and input parameters. Thus, the user has the capability to model various surface reactions via user-specified reaction rate constants, surface properties and parameters.

Gas↗
NASA NTRS2019

Sensor Analysis, Modeling, and Test for Robust Propulsion System Autonomy

An approach is presented supporting analysis, modeling, and test validation of operational flight instrumentation (OFI) that facilitates critical functions for the Space Launch System (SLS) main propulsion system (MPS). Certain types of OFI sensors were shown to exhibit highly nonlinear and non-gaussian noise characteristics during acceptance testing, motivating the development of advanced modeling and simulation (M&S) capability to support algorithm verification and flight certification. Hardware model and algorithm simulation fidelity was informed by a risk scoring metric; redesign of high-risk algorithms using test-validated sensor models significantly improved their expected performance as evaluated using Monte Carlo acceptance sampling methods. Autonomous functions include closed-loop ullage pressure regulation, pressurant leak detection, and fault isolation for automated safing and crew caution and warning (C&W).

Orr, Jeb S.↗
NASA NTRS2019

FIGS: spectral fitting constraints on the star formation history of massive galaxies since the cosmic noon

We constrain the stellar population properties of a sample of 52 massive galaxies – with stellar mass log (M(s)/M(⊙)) ≳ 10.5 – over the redshift range 0.5 < z < 2 by use of observer-frame optical and near-infrared slitless spectra from Hubble Space Telescope’s ACS and WFC3 grisms. The deep exposures (∼100 ks) allow us to target individual spectra of massive galaxies to F160W = 22.5 AB. Our spectral fitting approach uses a set of six base models adapted to the redshift and spectral resolution of each observation, and fits the weights of the base models, including potential dust attenuation, via a Markov Chain Monte Carlo method. Our sample comprises a mixed distribution of quiescent (19) and star-forming galaxies (33). We quantify the width of the age distribution (Δt) that is found to dominate the variance of the retrieved parameters according to principal component analysis. The population parameters follow the expected trend towards older ages with increasing mass, and Δt appears to weakly anticorrelate with stellar mass, suggesting a more efficient star formation at the massive end. As expected, the redshift dependence of the relative stellar age (measured in units of the age of the Universe at the source) in the quiescent sample rejects the hypothesis of a single burst (aka monolithic collapse). Radial colour gradients within each galaxy are also explored, finding a wider scatter in the star-forming subsample, but no conclusive trend with respect to the population parameters.

Ignacio Ferreras↗
NASA NTRSDate not supplied

Monte Carlo simulations of neutrino and charged lepton propagation in the Earth with nuPyProp

An accurate modeling of neutrino flux attenuation and the distribution of leptons they produce in transit through the Earth is an essential component to determine neutrino flux sensitivities of underground, sub-orbital and space-based detectors. Through neutrino oscillations over cosmic distances, astrophysical neutrino sources are expected to produce nearly equal fluxes of electron, muon and tau neutrinos. Of particular interest are tau neutrinos that interact in the Earth at modest slant depths to produce leptons. Some leptons emerge from the Earth and decay in the atmosphere to produce extensive air showers. Future balloon-borne and satellite-based opticalCherenkov neutrino telescopes will be sensitive to upward air showers from tau neutrino induced lepton decays. We present nuPyProp, a python code that is part of the nuSpaceSim package. nuPyProp generates look-up tables for exit probabilities and energy distributions for (see paper for proper equation) propagation in the Earth. This flexible code runs with either stochastic or continuous electromagnetic energy losses for the lepton transit through the Earth. Current neutrino cross section models and energy loss models are included along with templates for user input of other models. Results from nuPyProp are compared with other recent simulation packages for neutrino and charged lepton propagation. Sources of modeling uncertainties are described and quantified.

Yosui Akaike↗
NASA NTRS1989

Three-dimensional Monte Carlo simulation of gamma-ray scattering and production in the atmosphere

Results are reported from Monte Carlo numerical simulations of atmospheric gamma-ray scattering and production. The basic physical principles involved in the construction of the models are reviewed, and results are presented in extensive graphs for low-energy gamma rays with the spectra of gamma-ray bursts, solar flares, the Crab pulsar, and 511-keV line radiation. It is shown that the model accurately reproduces the characteristics of atmospheric albedo radiation, including details of the angular distribution. The potential applicability of the Monte Carlo technique to studies of the near-earth radiation environment is indicated.

Morris, Daniel J.↗
NASA NTRS1978

Three-dimensional radiative exchange factors for nongray, nondiffuse surfaces

A computer program using a variation of the Monte Carlo method was developed to predict radiative exchange factors in three-dimensional configurations with curved surfaces. The model allows for arbitrary emission, absorption, and reflection characteristics and for radiation exchange between surfaces as well as external irradiation through openings. It was shown that exchange factors can be determined efficiently by using the normal Monte Carlo method for closed configurations and/or high surface emissivities, while energy partitioning is vastly superior in the case of open configurations and/or low surface emissivities. Comparison with some experiments performed on the Space Shuttle heat rejection system demonstrates the model's accuracy as well as its superiority over a simplified diffuse-surface analysis, which requires similar amounts of computer time.

Modest, M. F.↗
NASA NTRS1999

SOLPOL: A Solar Polarimeter for Hard X-Rays and Gamma-Rays

Th goal of this project was to continue the development of a hard X-ray polarimeter for studying solar flares. In earlier work (funded by a previous SR&T grant), we had already achieved several goals, including the following: 1) development of a means of producing a polarized radiation source in the lab that could be used for prototype development; 2) demonstrated the basic Compton scatter polarimeter concept using a simple laboratory setup; 3) used the laboratory results to verify our Monte Carlo simulations; and 4) investigated various detector technologies that could be incorporated into the polarimeter design. For the current one-year program, we wanted to fabricate and test a laboratory science model based on our SOLPOL (Solar Polarimeter) design. The long-term goal of this effort is to develop and test a prototype design that could be used to study flare emissions from either a balloon- or space-borne platform. The current program has achieved its goal of fabricating and testing a science model of the SOLPOL design, although additional testing of the design (and detailed comparison with Monte Carlo simulations) is still desired. This one-year program was extended by six months (no-cost extension) to cover the summer of 1999, when undergraduate student support was available to complete some of the laboratory testing.

McConnell, Michael L.↗
NASA NTRS2007

Non-Parametric Collision Probability for Low-Velocity Encounters

An implicit, but not necessarily obvious, assumption in all of the current techniques for assessing satellite collision probability is that the relative position uncertainty is perfectly correlated in time. If there is any mis-modeling of the dynamics in the propagation of the relative position error covariance matrix, time-wise de-correlation of the uncertainty will increase the probability of collision over a given time interval. The paper gives some examples that illustrate this point. This paper argues that, for the present, Monte Carlo analysis is the best available tool for handling low-velocity encounters, and suggests some techniques for addressing the issues just described. One proposal is for the use of a non-parametric technique that is widely used in actuarial and medical studies. The other suggestion is that accurate process noise models be used in the Monte Carlo trials to which the non-parametric estimate is applied. A further contribution of this paper is a description of how the time-wise decorrelation of uncertainty increases the probability of collision.

Carpenter, J. Russell↗
NASA NTRS2004

Probabilistic Study Conducted on Sensor-Based Engine Life Calculation

Turbine engine life management is a very complicated process to ensure the safe operation of an engine subjected to complex usage. The challenge of life management is to find a reasonable compromise between the safe operation and the maximum usage of critical parts to reduce maintenance costs. The commonly used "cycle count" approach does not take the engine operation conditions into account, and it oversimplifies the calculation of the life usage. Because of the shortcomings, many engine components are regularly pulled for maintenance before their usable life is over. And, if an engine has been running regularly under more severe conditions, components might not be taken out of service before they exceed their designed risk of failure. The NASA Glenn Research Center and its industrial and academic partners have been using measurable parameters to improve engine life estimation. This study was based on the Monte Carlo simulation of 5000 typical flights under various operating conditions. First a closed-loop engine model was developed to simulate the engine operation across the mission profile and a thermomechanical fatigue (TMF) damage model was used to calculate the actual damage during takeoff, where the maximum TMF accumulates. Next, a Weibull distribution was used to estimate the implied probability of failure for a given accumulated cycle count. Monte Carlo simulations were then employed to find the profiles of the TMF damage under different operating assumptions including parameter uncertainties. Finally, probabilities of failure for different operating conditions were analyzed to demonstrate the importance of a sensor-based damage calculation in order to better manage the risk of failure and on-wing life.

Guo, Ten-Huei↗
NASA NTRS2001

Chemical and Flowfield Modeling for Enhanced Analysis of Contamination Experiments

This paper describes the application of a new Direct Simulation Monte Carlo (DSMC) code, the Molecular Beam Simulator (MBS), which is designed to analyze laboratory scale molecular beam-surface (and crossed-beam) experiments. The MBS is primarily intended to model experiments associated with spacecraft contamination effects, but it can also be used to simulate a variety of surface chemistry and reactive flow measurements. The MBS code is fully three-dimensional, includes a wide-range of chemical processes, and can model one or multiple pulsed (non-steady) sources. As an example application of the MBS code, a fast, pulsed, oxygen atom-surface experiment which examines the chemistry behind erosion of graphite by oxygen atoms is analyzed. Unsteady DSMC simulations show that experimental observations of excited molecular states after the pulse has hit the surface are consistent with two distinct chemical mechanisms: a direct one where the excited molecules are formed on the surface, and a two-step mechanism where ground state molecules formed on the surface are collisionally excited after they leave the surface by trailing oxygen atoms in the pulse. Further DSMC calculations suggest experiments which can distinguish between these mechanisms.

Braunstein, Matthew↗
NASA NTRS2018

Solar Wind Implantation into Lunar Regolith II: Monte Carlo Simulations of Hydrogen Retention in a Surface with Defects and the Hydrogen (H, H2) Exosphere

Recently, the near-infrared observations of the OH veneer on the lunar surface by the Moon Mineralogy Mapper (M3) have been refined to constrain the OH content to 500-750 parts per million (ppm). The observations indicate diurnal variations in OH up to 200 ppm possibly linked to warmer surface temperatures at low latitude. We examine the M3 observations using a statistical mechanics approach to model the diffusion of implanted H in the lunar regolith. We present results from Monte Carlo simulations of the diffusion of implanted solar wind H atoms and the subsequently derived H and H2 exospheres.

Exosphere↗
NASA NTRS1997

Monte Carlo Simulation of THz Multipliers

Schottky Barrier diode frequency multipliers are critical components in submillimeter and Thz space based earth observation systems. As the operating frequency of these multipliers has increased, the agreement between design predictions and experimental results has become poorer. The multiplier design is usually based on a nonlinear model using a form of harmonic balance and a model for the Schottky barrier diode. Conventional voltage dependent lumped element models do a poor job of predicting THz frequency performance. This paper will describe a large signal Monte Carlo simulation of Schottky barrier multipliers. The simulation is a time dependent particle field Monte Carlo simulation with ohmic and Schottky barrier boundary conditions included that has been combined with a fixed point solution for the nonlinear circuit interaction. The results in the paper will point out some important time constants in varactor operation and will describe the effects of current saturation and nonlinear resistances on multiplier operation.

East, J.↗
NASA NTRS1973

LP-search and its use in analysis of the accuracy of control systems with acoustical models

The LP-search is proposed as an analog of the Monte Carlo method for finding values in nonlinear statistical systems. It is concluded that: To attain the required accuracy in solution to the problem of control for a statistical system in the LP-search, a considerably smaller number of tests is required than in the Monte Carlo method. The LP-search allows the possibility of multiple repetitions of tests under identical conditions and observability of the output variables of the system.

Sergeyev, V. I.↗
NASA NTRS1992

Preliminary results of a Monte Carlo simulation of burst directions by BATSE

The effect of varying BATSE trigger parameters on the modeled BATSE detection rate is investigated numerically. Quantitative estimates are obtained of the systematic effects generated by the complex interplay of trigger times, variations in the signal-to-noise ratio for burst detection as well as the time scale over which backgrounds are determined, and the number of required detections above threshold. It is found, in particular that employing a third detection, at a reduced signal-to-noise ratio, to resolve a burst does not increase the detection rate. It is also shown that the BATSE detection rate is insensitive to variations in the time scale over which the background is determined.

Higdon, J. C.↗
NASA NTRS2019

Uncertainty Quantification of a Rotorcraft Conceptual Sizing Toolsuite

A computational framework to support the quantification of system uncertainties and sensitivities for rotorcraft applications is presented using the NASA Design and Analysis of Rotorcraft (NDARC) conceptual sizing tool. A 90 passenger conceptual tiltrotor configuration was used for case demonstration in the modeling of uncertainties in NDARCs emission module. A non-intrusive forward propagation uncertainty quantification approach was applied to ensemble simulations using a Monte Carlo methodology with stratified Latin hypercube sampling. An off-the-shelf software, DAKOTA, which supports trade studies and design space exploration, including optimization, surrogate modeling and uncertainty analysis was used to address the research goals. A toolsuite was further developed incorporating DAKOTA with automated design processes and methods using function wrappers to execute program routines including support for data post-processing. Uncertainties in rotorcraft emissions modeling using the Average Temperature Response metric for a set mission profile were studied. It was shown that for the current study, using the base-line best estimate modeling parameters for the Average Temperature Response metric, NDARC under-estimates the effects of emissions when compared with results from Monte Carlo simulations. A global sensitivity analysis was further undertaken to quantify the contribution of the various emission species on output sensitivity, hence uncertainty. The work demonstrates that the developed toolsuite is robust and will support the quantification of system uncertainties and sensitivities in future rotorcraft design efforts.

Rotorcraft↗
NASA NTRS1992

Dynamically stratified Monte Carlo forecasting

A new method for performing Monte Carlo forecasts is introduced. The method, called dynamic stratification, selects initial perturbations based on a stratification of the error distribution. A simple implementation is presented in which the error distribution used for the stratification is estimated from a linear model derived from a large ensemble of 12-h forecasts with the full dynamic model. The stratification thus obtained is used to choose a small subsample of initial states with which to perform the dynamical Monte Carlo forecasts. Several test cases are studied using a simple two-level general circulation model with uncertain initial conditions. It is found that the method provides substantial reductions in the sampling error of the forecast mean and variance when compared to the more traditional approach of choosing the initial perturbations at random. The degree of improvement, however, is sensitive to the nature of the initial error distribution and to the base state. In practice the method may be viable only if the computational burden involved in obtaining an adequate estimate of the error distribution is shared with the data-assimilation procedure.

Schubert, Siegfried↗
NASA NTRS1992

The evolution of a primordial binary population in a globular cluster

A simple model is presented for the evolution of a primordial binary population in a globular cluster. Monte Carlo simulations are given for an initial population of 50,000 binaries against a fixed background population of 500,000 single stars in a tidally truncated cluster model. Individual histories of all binaries are followed through mass segregation, scattering recoil, escape from the cluster, or coalescence. It is found that most binaries are destroyed by binary-binary interactions, with the rest escaping in the point-mass approximation. In a more realistic model, the majority of the rest merge. At any instant, most of the remaining binaries are drifting in toward the center before their first strong encounter. A typical binary spends most of its active life in or near the cluster core. The few binaries which receive a recoil sufficient to place them in the halo past the half-mass radius remain there long enough to make a significant contribution to the radial binary distribution.

Hut, Piet↗