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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Lunar Regolith Albedos Using Monte Carlos

The analysis of planetary regoliths for their backscatter albedos produced by cosmic rays (CRs) is important for space exploration and its potential contributions to science investigations in fundamental physics and astrophysics. Albedos affect all such experiments and the personnel that operate them. Groups have analyzed the production rates of various particles and elemental species by planetary surfaces when bombarded with Galactic CR fluxes, both theoretically and by means of various transport codes, some of which have emphasized neutrons. Here we report on the preliminary results of our current Monte Carlo investigation into the production of charged particles, neutrons, and neutrinos by the lunar surface using FLUKA. In contrast to previous work, the effects of charm are now included.

Wilson, T. L.↗
NASA NTRS2010

Failure Bounding And Sensitivity Analysis Applied To Monte Carlo Entry, Descent, And Landing Simulations

In the study of entry, descent, and landing, Monte Carlo sampling methods are often employed to study the uncertainty in the designed trajectory. The large number of uncertain inputs and outputs, coupled with complicated non-linear models, can make interpretation of the results difficult. Three methods that provide statistical insights are applied to an entry, descent, and landing simulation. The advantages and disadvantages of each method are discussed in terms of the insights gained versus the computational cost. The first method investigated was failure domain bounding which aims to reduce the computational cost of assessing the failure probability. Next a variance-based sensitivity analysis was studied for the ability to identify which input variable uncertainty has the greatest impact on the uncertainty of an output. Finally, probabilistic sensitivity analysis is used to calculate certain sensitivities at a reduced computational cost. These methods produce valuable information that identifies critical mission parameters and needs for new technology, but generally at a significant computational cost.

Gaebler, John A.↗
NASA NTRS2015

Comparison of Spares Logistics Analysis Techniques for Long Duration Human Spaceflight

As the durations and distances involved in human exploration missions increase, the logistics associated with the repair and maintenance becomes more challenging. Whereas the operation of the International Space Station (ISS) depends upon regular resupply from the Earth, this paradigm may not be feasible for future missions. Longer mission durations result in higher probabilities of component failures as well as higher uncertainty regarding which components may fail, and longer distances from Earth increase the cost of resupply as well as the speed at which the crew can abort to Earth in the event of an emergency. As such, mission development efforts must take into account the logistics requirements associated with maintenance and spares. Accurate prediction of the spare parts demand for a given mission plan and how that demand changes as a result of changes to the system architecture enables full consideration of the lifecycle cost associated with different options. In this paper, we utilize a range of analysis techniques - Monte Carlo, semi-Markov, binomial, and heuristic - to examine the relationship between the mass of spares and probability of loss of function related to the Carbon Dioxide Removal System (CRS) for a notional, simplified mission profile. The Exploration Maintainability Analysis Tool (EMAT), developed at NASA Langley Research Center, is utilized for the Monte Carlo analysis. We discuss the implications of these results and the features and drawbacks of each method. In particular, we identify the limitations of heuristic methods for logistics analysis, and the additional insights provided by more in-depth techniques. We discuss the potential impact of system complexity on each technique, as well as their respective abilities to examine dynamic events. This work is the first step in an effort that will quantitatively examine how well these techniques handle increasingly more complex systems by gradually expanding the system boundary.

Owens, Andrew↗
NASA NTRS2010

Accelerated Monte Carlo Simulation for Safety Analysis of the Advanced Airspace Concept

Safe separation of aircraft is a primary objective of any air traffic control system. An accelerated Monte Carlo approach was developed to assess the level of safety provided by a proposed next-generation air traffic control system. It combines features of fault tree and standard Monte Carlo methods. It runs more than one order of magnitude faster than the standard Monte Carlo method while providing risk estimates that only differ by about 10%. It also preserves component-level model fidelity that is difficult to maintain using the standard fault tree method. This balance of speed and fidelity allows sensitivity analysis to be completed in days instead of weeks or months with the standard Monte Carlo method. Results indicate that risk estimates are sensitive to transponder, pilot visual avoidance, and conflict detection failure probabilities.

Thipphavong, David↗
NASA NTRSDate not supplied

Evaluation of CFD as a Surrogate for Wind Tunnel Testing - Experimental Uncertainty Quantification

A series of wind tunnel tests is being performed at the Unitary Plan Wind Tunnel at Langley Research Center to assess the validity of using computational fluid dynamics (CFD) as a surrogate for wind tunnel testing. In order to make proper comparisons, uncertainties in CFD results and experimental data must be well understood. The material presented will highlight the methods, assumptions, and elemental inputs used to achieve experimental uncertainty estimates for several variables of interest.The work performed to date has focused on gaining insight into random uncertainty via statistical analysis of repeat data and systematic uncertainty via Monte Carlo propagation analysis. These methods were combined using a second-order Monte Carlo propagation, resulting in a probability box (P-box) for each variable and at all conditions of interest. Figure 1 provides an example of one such P-box, showing the experimental uncertainty in a locally determined dynamic pressure (QC10) for one of many tunnel conditions evaluated during the Flow Survey experiment. This particular condition (Condition 27) has nominal set points of Mach number = 3.85, Reynolds number = 3x10(exp 6) ft(exp -1), total pressure = 5160 psfa, and total temperature = 150°F. The uncertainty in dynamic pressure at this condition is now well defined by this plot. Armed with this experimental data uncertainty, meaningful comparisons can be made with computational results, when their associated uncertainties are also considered.

Heather P Houlden↗
NASA NTRS2011

Pattern Recognition for a Flight Dynamics Monte Carlo Simulation

The design, analysis, and verification and validation of a spacecraft relies heavily on Monte Carlo simulations. Modern computational techniques are able to generate large amounts of Monte Carlo data but flight dynamics engineers lack the time and resources to analyze it all. The growing amounts of data combined with the diminished available time of engineers motivates the need to automate the analysis process. Pattern recognition algorithms are an innovative way of analyzing flight dynamics data efficiently. They can search large data sets for specific patterns and highlight critical variables so analysts can focus their analysis efforts. This work combines a few tractable pattern recognition algorithms with basic flight dynamics concepts to build a practical analysis tool for Monte Carlo simulations. Current results show that this tool can quickly and automatically identify individual design parameters, and most importantly, specific combinations of parameters that should be avoided in order to prevent specific system failures. The current version uses a kernel density estimation algorithm and a sequential feature selection algorithm combined with a k-nearest neighbor classifier to find and rank important design parameters. This provides an increased level of confidence in the analysis and saves a significant amount of time.

Restrepo, Carolina↗
NASA NTRS1986

A Monte Carlo study of Weibull reliability analysis for space shuttle main engine components

The incorporation of a number of additional capabilities into an existing Weibull analysis computer program and the results of Monte Carlo computer simulation study to evaluate the usefulness of the Weibull methods using samples with a very small number of failures and extensive censoring are discussed. Since the censoring mechanism inherent in the Space Shuttle Main Engine (SSME) data is hard to analyze, it was decided to use a random censoring model, generating censoring times from a uniform probability distribution. Some of the statistical techniques and computer programs that are used in the SSME Weibull analysis are described. The methods documented in were supplemented by adding computer calculations of approximate (using iteractive methods) confidence intervals for several parameters of interest. These calculations are based on a likelihood ratio statistic which is asymptotically a chisquared statistic with one degree of freedom. The assumptions built into the computer simulations are described. The simulation program and the techniques used in it are described there also. Simulation results are tabulated for various combinations of Weibull shape parameters and the numbers of failures in the samples.

Abernethy, K.↗
NASA NTRS2007

Escalation: How Much is Enough?

Determining the escalation percentage to an estimate is often the subject of fierce debate. Cost increases are determined by dynamic relati onships between many factors, including acts of nature, interest rate s, oil prices, global commodity markets, wars, wage rates, and the ov erall health of the economy, as well as supply and demand for the required goods or services. How much escalation is enough? Are the recen t price increases temporary aberrations, or will they continue to pla gue us? This paper examines historical escalation rates, as well as i ndications of trends. Various analysis methods -- Monte Carlo simulations, neural networks, trend impact analysis, and the Delphi method -- are examined in an attempt to determine future trends.

Butts, Glenn↗
NASA NTRS1984

Vectorized Monte Carlo methods for reactor lattice analysis

Some of the new computational methods and equivalent mathematical representations of physics models used in the MCV code, a vectorized continuous-enery Monte Carlo code for use on the CYBER-205 computer are discussed. While the principal application of MCV is the neutronics analysis of repeating reactor lattices, the new methods used in MCV should be generally useful for vectorizing Monte Carlo for other applications. For background, a brief overview of the vector processing features of the CYBER-205 is included, followed by a discussion of the fundamentals of Monte Carlo vectorization. The physics models used in the MCV vectorized Monte Carlo code are then summarized. The new methods used in scattering analysis are presented along with details of several key, highly specialized computational routines. Finally, speedups relative to CDC-7600 scalar Monte Carlo are discussed.

Brown, F. B.↗
NASA NTRS2012

Axisymmetric Plume Simulations with NASA's DSMC Analysis Code

A comparison of axisymmetric Direct Simulation Monte Carlo (DSMC) Analysis Code (DAC) results to analytic and Computational Fluid Dynamics (CFD) solutions in the near continuum regime and to 3D DAC solutions in the rarefied regime for expansion plumes into a vacuum is performed to investigate the validity of the newest DAC axisymmetric implementation. This new implementation, based on the standard DSMC axisymmetric approach where the representative molecules are allowed to move in all three dimensions but are rotated back to the plane of symmetry by the end of the move step, has been fully integrated into the 3D-based DAC code and therefore retains all of DAC s features, such as being able to compute flow over complex geometries and to model chemistry. Axisymmetric DAC results for a spherically symmetric isentropic expansion are in very good agreement with a source flow analytic solution in the continuum regime and show departure from equilibrium downstream of the estimated breakdown location. Axisymmetric density contours also compare favorably against CFD results for the R1E thruster while temperature contours depart from equilibrium very rapidly away from the estimated breakdown surface. Finally, axisymmetric and 3D DAC results are in very good agreement over the entire plume region and, as expected, this new axisymmetric implementation shows a significant reduction in computer resources required to achieve accurate simulations for this problem over the 3D simulations.

Stewart, B. D.↗
NASA NTRS1993

A Monte Carlo approach to the analysis of control system robustness

Stochastic robustness, a simple technique used to estimate the stability and performance robustness of linear, time-invariant systems, is described. The scalar probability of instability is introduced as a measure of stability robustness. Examples are given of stochastic performance robustness measures based on classical time-domain specifications. The relationship between stochastic robustness measures and control system design parameters is discussed. The technique is demonstrated by analyzing an LQG/LTR system designed for a flexible robot arm. It is concluded that the analysis of stochastic robustness offers a good alternative to existing robustness metrics.

Ray, Laura R.↗
NASA NTRS1984

Feature selection and the information content of Thematic Mapper simulator data for forest structural assessment

An assessment is made of the information content of Thematic Mapper Simulator (TMS) data for the case of a forested region, in order to determine the sensitivity of such data to forest crown closure and tree size class. Principal components analysis and Monte Carlo simulation indicated that channels 4, 7, 5 and 3 were optimal for four-channel forest structure analysis. As the number of channels supplied to the Monte Carlo feature selection routine increased, classification accuracy increased. The greatest sensitivity to the forest structural parameters, which included succession within clearcuts as well as crown closure and size class, was obtained from the 7-channel TMS data.

Spanner, M. A.↗
NASA NTRS1994

Globular cluster photometry with the Hubble Space Telescope. 2: U, V, and I measurements of M15

The projected density distribution of resolved stars near the center of M15 is shown to be consistent with either a power-law cusp N(r) approximately r(exp alpha), with alpha approximately -0.85 +/- 0.2, or with a King model with a core of radius approximately less than 2 sec. The inferred slope is in agreement with the theoretical value, alpha = -0.75, calculated by Bahcall and Wolf for the distribution of equal-mass stars surrounding a massive black hole and is also consistent with the radial profile expected from core collapse without a central black hole. The object AC 214 is a candidate for the central density cusp. Analysis of Monte Carlo simulations of the diffuse light indicates that, using current analysis techniques and available data, the residual light is not a reliable indicator of the true density distribution. This is contrary to earlier work. Photometric measurements in V and I of more than 5 x 10(exp 3) stars (and in U, V, and I of approximately greater than 1500 stars) are used to construct color-magnitude diagrams in the central 1 min of M15. Fourteen blue straggler candidates are identified in the inner 20 sec. The central color gradient noticed by previous researchers is caused by a central depletion of bright red giant stars rather than an excess of blue stragglers or blue horizontal branch stars.

Yanny, Brian↗