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NASA NTRS1987

A covariance analysis algorithm for interconnected systems

A covariance analysis algorithm for propagation of signal statistics in arbitrarily interconnected nonlinear systems is presented which is applied to six-degree-of-freedom systems. The algorithm uses statistical linearization theory to linearize the nonlinear subsystems, and the resulting linearized subsystems are considered in the original interconnection framework for propagation of the signal statistics. Some nonlinearities commonly encountered in six-degree-of-freedom space-vehicle models are referred to in order to illustrate the limitations of this method, along with problems not encountered in standard deterministic simulation analysis. Moreover, the performance of the algorithm shall be numerically exhibited by comparing results using such techniques to Monte Carlo analysis results, both applied to a simple two-dimensional space-intercept problem.

Cheng, Victor H. L.↗

NASA NTRS1990

Near infrared radiances observed by the UK C130 multi-channel radiometer during the marine stratocumulus IFO and preliminary comparison with model calculations

A preliminary analysis of some of the narrow band radiance data measured on the U.K. Meteorological Office's C130 aircraft during the marine stratocumulus intensive field observation of First ISCCP Regional Experiment (FIRE), San Diego 29 June to 18 July 1987, is presented. The data are compared with Monte Carlo calculations of the reflectance and transmittance of the cloud based upon the observed droplet size distribution. The main scientific question being addressed is whether there is any evidence of anomalous absorption within the cloud which had been observed in similar measurements (Rozenberg et al., 1974; Twomey and Cocks, 1982; Foot, 1988). The measurements also indicate the potential for remotely sensing cloud properties. The data and method of presentation discussed here clearly separates out clouds in terms of the size of the cloud droplets. All of the daytime C130 FIRE flights have been studied and are consistent with the data presented here. There appears to be no peculiarities that might arise, for example if pollution were to be a significant factor in determining cloud absorption. Variation in the inferred size parameters, r sub e, along runs are also very small.

Foot, J. S.↗

NASA NTRS2002

Modeling the Stability of Volatile Deposits in Lunar Cold Traps

There are several mechanisms acting at the cold traps that can alter the inventory of volatiles there. Primarily, the lunar surface is bombarded by meteoroids which impact, melt, process, and redistribute the regolith. Further, solar wind and magnetospheric ion fluxes are allowed limited access onto the regions in permanent shadow. Also, although cold traps are in the permanent shadow of the Sun, there is a small flux of radiation incident on the regions from interstellar sources. We investigate the effects of these space weathering processes on a deposit of volatiles in a lunar cold trap through simulations. We simulate the development of a column of material near the surface of the Moon resulting from space weathering. This simulation treats a column of material at a lunar cold trap and focuses on the hydrogen content of the column. We model space weathering processes on several time and spatial scales to simulate the constant rain of micrometeoroids as well as sporadic larger impactors occurring near the cold traps to determine the retention efficiency of the cold traps. We perform the Monte Carlo simulation over many columns of material to determine the expectation value for hydrogen content of the top few meters of soil for comparison with Lunar Prospector neutron data.

Crider, D. H.↗

NASA NTRS2005

Entry Abort Determination Using Non-Adaptive Neural Networks for Mars Precision Landers

The 2009 Mars Science Laboratory (MSL) will attempt the first precision landing on Mars using a modified version of the Apollo Earth entry guidance program. The guidance routine, Entry Terminal Point Controller (ETPC), commands the deployment of a supersonic parachute after converging the range to the landing target. For very dispersed cases, ETPC may not converge the range to the target and safely command parachute deployment within Mach number and dynamic pressure constraints. A full-lift up abort can save 85% of these failed trajectories while abandoning the precision landing objective. Though current MSL requirements do not call for an abort capability, an autonomous abort capability may be desired, for this mission or future Mars precision landers, to make the vehicle more robust. The application of artificial neural networks (NNs) as an abort determination technique was evaluated by personnel at the National Aeronautics and Space Administration (NASA) Johnson Space Center (JSC). In order to implement an abort, a failed trajectory needs to be recognized in real time. Abort determination is dependent upon several trajectory parameters whose relationships to vehicle survival are not well understood, and yet the lander must be trained to recognize unsafe situations. Artificial neural networks (NNs) provide a way to model these parameters and can provide MSL with the artificial intelligence necessary to independently declare an abort. Using the 2009 Mars Science Laboratory (MSL) mission as a case study, a non-adaptive NN was designed, trained and tested using Monte Carlo simulations of MSL descent and incorporated into ETPC. Neural network theory, the development history of the MSL NN, and initial testing with severe dust storm entry trajectory cases are discussed in Reference 1 and will not be repeated here. That analysis demonstrated that NNs are capable of recognizing failed descent trajectories and can significantly increase the survivability of MSL for very dispersed cases. NN testing was then broadened to evaluate fully dispersed entry trajectories. The NN correctly classified 99.7% of descent trajectories as abort or nonabort and reduced the probability of an unsafe parachute deployment by 83%. This second, broader testing phase is discussed in this paper.

Graybeal, Sarah R.↗

NASA NTRS2010

Applying Monte Carlo Simulation to Launch Vehicle Design and Requirements Verification

This paper is focused on applying Monte Carlo simulation to probabilistic launch vehicle design and requirements verification. The approaches developed in this paper can be applied to other complex design efforts as well. Typically the verification must show that requirement "x" is met for at least "y" % of cases, with, say, 10% consumer risk or 90% confidence. Two particular aspects of making these runs for requirements verification will be explored in this paper. First, there are several types of uncertainties that should be handled in different ways, depending on when they become known (or not). The paper describes how to handle different types of uncertainties and how to develop vehicle models that can be used to examine their characteristics. This includes items that are not known exactly during the design phase but that will be known for each assembled vehicle (can be used to determine the payload capability and overall behavior of that vehicle), other items that become known before or on flight day (can be used for flight day trajectory design and go/no go decision), and items that remain unknown on flight day. Second, this paper explains a method (order statistics) for determining whether certain probabilistic requirements are met or not and enables the user to determine how many Monte Carlo samples are required. Order statistics is not new, but may not be known in general to the GN&C community. The methods also apply to determining the design values of parameters of interest in driving the vehicle design. The paper briefly discusses when it is desirable to fit a distribution to the experimental Monte Carlo results rather than using order statistics.

Hanson, John M.↗

NASA NTRS1974

Reflection of a thick planar shock wave from a coplanar surface

The reflection of a thick shock wave from an adsorbing surface has been studied for argon and neon test gases using the direct simulation Monte Carlo method and laboratory shock-tube experiments. In the simulation, collisions between gas atoms were calculated with a point-center repulsive intermolecular potential, and collisions between gas atoms and the surface were described by a simple two-parameter model which includes the effects of adsorption and thermal accommodation. Experimental data included normal stress and temperature time histories on the surface of a shock-tube and wall. These data and published data of density variations near the end wall were compared with simulation results to assess the influence of adsorption and accommodation on the flowfield and the surface and also to infer optimum values for the surface-interaction model parameters. Good quantitative agreement between simulation and laboratory data was found with this simple surface-interaction model.

Deiwert, G. S.↗

NASA NTRS1981

Compositional inhomogeneities in a single Icelandic tholeiite flow

New trace element analyses of 25 basalt samples from a vertical traverse in an 11 m thick flow of Icelandic tholeiite show compositional differences which exceed analytical uncertainties and are random with respect to height. These variations suggest a short-range segregation model in which the amounts of phenocrysts, groundmass materials, and residual liquid vary randomly in different samples of the flow; a least-squares method is applied to determine if these variations reflect different proportions of crystallizing phases and residual liquid. Monte Carlo computations indicate that short-range segregation results in inhomogeneity of a magnitude of interflow compositional differences; this causes incoherence in elements with different geochemical behaviors while preserving coherence in elements of similar behavior.

Lindstrom, M. M.↗

NASA NTRS1988

Creep life prediction based on stochastic model of microstructurally short crack growth

A nondimensional model of microstructurally short crack growth in creep is developed based on a detailed observation of the creep fracture process of 304 stainless steel. In order to deal with the scatter of small crack growth rate data caused by microstructural inhomogeneity, a random variable technique is used in the model. A cumulative probability of the crack length at an arbitary time, G(bar a, bar t), and that of the time when a crack reaches an arbitary length, F(bar t, bar a), are obtained numerically by means of a Monte Carlo method. G(bar a, bar t), and F(bar t, bar a) are the probabilities for a single crack. However, multiple cracks generally initiate on the surface of a smooth specimen from the early stage of creep life to the final stage. TAking into account the multiple crack initiations, the actual crack length distribution observed on the surface of a specimen is predicted by the combination of probabilities for a single crack. The prediction shows a fairly good agreement with the experimental result for creep of 304 stainless steel at 923 K. The probability of creep life is obtained from an assumption that creep fracture takes place when the longest crack reaches a critical length. The observed and predicted scatter of the life is fairly small for the specimens tested.

Kitamura, Takayuki↗

NASA NTRS1989

Creep life prediction based on stochastic model of microstructurally short crack growth

A nondimensional model of microstructurally short crack growth in creep is developed based on a detailed observation of the creep fracture process of 304 stainless steel. In order to deal with the scatter of small crack growth rate data caused by microstructural inhomogeneity, a random variable technique is used in the model. A cumulative probability of the crack length at an arbitrary time, G(bar a, bar t), and that of the time when a crack reaches an arbitrary length, F(bar t, bar a), are obtained numerically by means of a Monte Carlo method. G(bar a, bar t), and F(bar t, bar a) are the probabilities for a single crack. However, multiple cracks generally initiate on the surface of a smooth specimen from the early stage of creep life to the final stage. Taking into account the multiple crack initiations, the actual crack length distribution observed on the surface of a specimen is predicted by the combination of probabilities for a single crack. The prediction shows a fairly good agreement with the experimental result for creep of 304 stainless steel at 923 K. The probability of creep life is obtained from an assumption that creep fracture takes place when the longest crack reaches a critical length. The observed and predicted scatter of the life is fairly small for the specimens tested.

Kitamura, Takayuki↗

NASA NTRS1991

Three-dimensional rarefied flow simulations for the Aeroassist Flight Experiment vehicle

Hypersonic rarefied flow about the Aeroassist Flight Experiment vehicle has been investigated using a three-dimensional direct simulation Monte Carlo method. Calculations are performed for the transitional flows encountered during the vehicle's atmospheric entry for altitudes of 110 and 100 km with an entry velocity of 9.9 km/s. The simulations are performed using a five-species reacting gas model that account for rotational and vibrational internal energies. The solutions indicate that dissociation is important at altitudes of 110 km and below. Results are presented for surface pressures, convective heating, flowfield structure, and aerodynamic coefficient variations with altitude.

Celenligil, M. Cevdet↗

NASA NTRS2020

Mid Lift-to-Drag Ratio Rigid Vehicle 6-DoF Performance for Human Mars Entry, Descent, and Landing: A Fractional Polynomial Powered Descent Guidance Approach

Defining a feasible vehicle design and mission architecture capable of reliably delivering apayload of 20 metric tons (mt) or more is a great challenge for landing humans on Mars. TheMid Lift-to-Drag Rigid Vehicle (MRV), a rigid decelerator studied in NASA’s Entry, Descent,and Landing Architecture Study (EDLAS), has shown to be a viable vehicle candidate forfuture human Mars missions. As the vehicle concept matures, models of increasing fidelity areadded to the six-degree-of-freedom (6DoF) EDL simulation. This paper presents 6DoFsimulation results using model updates for vehicle mass properties, fineness ratio, andaerodynamic-propulsive interactions. Additionally, an assessment of the Fractional-Polynomial Powered Descent Guidance (FP2DG) performance is presented, and the vehicleperformance is compared with the Tunable Apollo Powered Descent Guidance (TAPDG).Finally, Monte Carlo results of the vehicle design trades are presented.

Johnson, Breanna J.↗

NASA NTRSDate not supplied

Validation and Sensitivity Analyses of Arc-Jet Performance of Woven Thermal Protection Entry Systems

A material response model is developed for the determination of erosion rates and thermal response of woven materials to enable accurate thermal protection material sizing and future missions to Venus and giant planets. The stagnation-point thermal response is further evaluated using a Monte Carlo global sensitivity analysis to determine the interactions between key parameters in the material surface energy balance, such as, convective blowing correction parameter and weave material properties including isotropic and orthotropic thermal conductivites. The time-accurate material response for the dual layer weave erosion and surface temperatures show excellent agreement with stagnation flat face arc-jet tests involving time-varying aeroheating-cooling cycles. The high-fidelity Monte Carlo sensitivity analysis technique was used to address challenges in thermal protection sizing for the Adaptive Deployable Entry and Placement Technology (ADEPT) system, a low ballistic coefficient hypersonic decelerator. The results represent new correlations for such weaves involving Carbon-air oxidation equilibrium chemistry. Through the multi-variate regression analyses and uncertainty rankings performed, only three properties were found to contribute to the transient thermal response of the gore, with emissivity contributing to nearly 95% of the total output uncertainty.

Pratibha Raghunandan↗

NASA NTRS2021

Validation and Sensitivity Analyses of Arc-Jet Performance of Woven Thermal Protection Entry Systems

Pratibha Raghunandan↗

NASA NTRSDate not supplied

Solid-state Precipitation in Molecular Dynamics: KMC-MD Hybrid Simulations

A critical drawback of molecular dynamics (MD) simulations when modeling physical properties is the limitation to short timescales. Solid state precipitation is one behavior that is not significantly observable at timescales accessible to MD, and thus has been difficult to simulate at an MD scale. Taking inspiration from Kinetic Monte-Carlo (KMC) methods for simulating diffusion on a rigid lattice, we have developed a hybrid KMC-MD approach to enable simulation of solid-state precipitation during MD simulation implemented in LAMMPS. This method incorporates the atomic neighbor hopping behavior utilized by KMC simulations into a MD simulation with a variable local lattice configuration. By accelerating nearest-neighbor atomic hopping with this technique, solid-state precipitation can be observed at an MD timescale. Utilizing theory based on persistent-embryo methods for liquid-solid precipitation in MD we demonstrate the calculation of critical nucleus size for the gamma’ precipitation out of gamma phase in the Ni-Al system.

Molecular Dynamics↗

NASA NTRSDate not supplied

Solid-state Precipitation in Molecular Dynamics: kMC-MD Hybrid Simulations

Molecular Dynamics↗

NASA NTRS2012

Stochastic Convection Parameterizations

computational fluid dynamics, radiation, clouds, turbulence, convection, gravity waves, surface interaction, radiation interaction, cloud and aerosol microphysics, complexity (vegetation, biogeochemistry, radiation versus turbulence/convection stochastic approach, non-linearities, Monte Carlo, high resolutions, large-Eddy Simulations, cloud structure, plumes, saturation in tropics, forecasting, parameterizations, stochastic, radiation-clod interaction, hurricane forecasts

atmospheric models↗

NASA NTRS1989

Rarefied-continuum gas dynamics transition for SUMS project

This program is to develop an analytic method for reducing SUMS data for the determination of the undisturbed atmosphere conditions ahead of the shuttle along its descending trajectory. It is divided into an internal flow problem, an external flow problem and their matching conditions. Since the existing method of Direct Simulation Monte Carlo (DSMC) failed completely for the internal flow problem, the emphasis is on the internal flow of a highly non-equilibrium, rarefied air through a short tube of a diameter much less than the gaseous mean free path. A two fluid model analysis of this internal flow problem has been developed and studied with typical results illustrated. A computer program for such an analysis and a technical paper published in Lecture Notes in Physics No. 323 (1989) are included as Appendices 3 and 4. A proposal for in situ determination of the surface accommodation coefficients sigma sub t and sigma e is included in Appendix 5 because of their importance in quantitative data reduction. A two fluid formulation for the external flow problem is included as Appendix 6 and a review article for AIAA on Hypersonic propulsion, much dependent on ambient atmospheric density, is also included as Appendix 7.

Cheng, Sin-I↗

NASA NTRS1999

The Behavior of Filters and Smoothers for Strongly Nonlinear Dynamics

The Kalman filter is the optimal filter in the presence of known Gaussian error statistics and linear dynamics. Filter extension to nonlinear dynamics is non trivial in the sense of appropriately representing high order moments of the statistics. Monte Carlo, ensemble-based, methods have been advocated as the methodology for representing high order moments without any questionable closure assumptions (e.g., Miller 1994). Investigation along these lines has been conducted for highly idealized dynamics such as the strongly nonlinear Lorenz (1963) model as well as more realistic models of the oceans (Evensen and van Leeuwen 1996) and atmosphere (Houtekamer and Mitchell 1998). A few relevant issues in this context are related to the necessary number of ensemble members to properly represent the error statistics and, the necessary modifications in the usual filter equations to allow for correct update of the ensemble members (Burgers 1998). The ensemble technique has also been applied to the problem of smoothing for which similar questions apply. Ensemble smoother examples, however, seem to quite puzzling in that results of state estimate are worse than for their filter analogue (Evensen 1997). In this study, we use concepts in probability theory to revisit the ensemble methodology for filtering and smoothing in data assimilation. We use Lorenz (1963) model to test and compare the behavior of a variety implementations of ensemble filters. We also implement ensemble smoothers that are able to perform better than their filter counterparts. A discussion of feasibility of these techniques to large data assimilation problems will be given at the time of the conference.

Zhu, Yanqiu↗