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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

A guidance and navigation system for continuous low-thrust vehicles

A midcourse guidance and navigation system for continuous low thrust vehicles was developed. The equinoctial elements are the state variables. Uncertainties are modelled statistically by random vector and stochastic processes. The motion of the vehicle and the measurements are described by nonlinear stochastic differential and difference equations respectively. A minimum time trajectory is defined; equations of motion and measurements are linearized about this trajectory. An exponential cost criterion is constructed and a linear feedback quidance law is derived. An extended Kalman filter is used for state estimation. A short mission using this system is simulated. It is indicated that this system is efficient for short missions, but longer missions require accurate trajectory and ground based measurements.

Jack-Chingtse, C.↗
NASA NTRS1974

Micrometeoroid abrasion of lunar rocks - A Monte Carlo simulation

A Monte Carlo computer model simulating the randomness of the impact process both in space and in time is developed in order to provide insight into lunar rock erosion by single particle abrasion and into bombardment history of fractional surface areas of lunar rocks. Microcrater frequencies derived from lunar rocks are used to calculate magnitude and probability of each cratering event, and experimental cratering results are employed to determine the eroded volumina for individual crater sizes. It is shown that a fractional surface area of a lunar rock sample may have a completely different bombardment history, and that the exposure histories and actual erosion depths of the surfaces vary accordingly and are highly heterogeneous. A minimum erosion rate of 0.3 to 0.6 mm for the past one million years is obtained.

Hoerz, F.↗
NASA NTRS1990

Stochastic estimation of tropospheric path delays in global positioning system geodetic measurements

Water vapor radiometric and surface meteorological measurements taken during three GPS geodetic experiments are used to calculate process noise levels for random walk and first-order Gauss-Markov temporal models of tropospheric path delays. Entire wet and combined wet and dry zenith delays at each network site are estimated simultaneously with the geodetic parameters without prior calibration. The path delays and corresponding baseline estimates are compared to those obtained with calibrated data and stochastic residual delays. In this manner, the marginal utility of a priori tropospheric calibration is assessed given the ability to estimate the path delays directly using only the GPS data. Estimation of total zenith path delays with appropriate random walk or Gauss-Markov models yields baseline repeatabilities of a few parts in 100 million. Results suggest that GPS data alone have sufficient strength to resolve centimeter-level zenith path delay fluctuations over periods of a few minutes.

Tralli, David M.↗
NASA NTRS1997

Low Cost Manufacturing Approach of High Temperature PMC Components

The overall objective is to develop a satisfactory sheet molding compound (SMC) of a high temperature polyimide, such as PMR-11-50, VCAP-75, or NB2-76, and to develop compression molding processing parameters for a random, chopped fiber, high temperature, sheet molding compound that will be more affordable than the traditional hand lay-up fabrication methods. Compression molding will reduce manufacturing costs of composites by: (1) minimizing the conventional machining required after fabrication due to the use of full 360 deg matched tooling, (2) reducing fabrication time by minimizing the intensive hand lay-up operations associated with individual ply fabrication techniques, such as ply orientation and ply count and (3) possibly reducing component mold time by advanced B-staging prior to molding. This program is an integral part of Allison's T406/AE engine family's growth plan, which will utilize technologies developed under NASA's Sub-sonic Transport (AST) programs, UHPTET initiatives, and internally through Allison's IR&D projects. Allison is aggressively pursuing this next generation of engines, with both commercial and military applications, by reducing the overall weight of the engine through the incorporation of advanced, lightweight, high temperature materials, such as polymer matrix composites. This infusion of new materials into the engine is also a major factor in reducing engine cost because it permits the use of physically smaller structural components to achieve the same thrust levels as the generation that it replaced. A lighter, more efficient propulsion system translates to a substantial cost and weight savings to an airframe's structure.

Kannmacher, Kevin↗
NASA NTRS2011

Sleep Disruption Medical Intervention Forecasting (SDMIF) Module for the Integrated Medical Model

The NASA Integrated Medical Model (IMM) assesses the risk, including likelihood and impact of occurrence, of all credible in-flight medical conditions. Fatigue due to sleep disruption is a condition that could lead to operational errors, potentially resulting in loss of mission or crew. Pharmacological consumables are mitigation strategies used to manage the risks associated with sleep deficits. The likelihood of medical intervention due to sleep disruption was estimated with a well validated sleep model and a Monte Carlo computer simulation in an effort to optimize the quantity of consumables. METHODS: The key components of the model are the mission parameter program, the calculation of sleep intensity and the diagnosis and decision module. The mission parameter program was used to create simulated daily sleep/wake schedules for an ISS increment. The hypothetical schedules included critical events such as dockings and extravehicular activities and included actual sleep time and sleep quality. The schedules were used as inputs to the Sleep, Activity, Fatigue and Task Effectiveness (SAFTE) Model (IBR Inc., Baltimore MD), which calculated sleep intensity. Sleep data from an ISS study was used to relate calculated sleep intensity to the probability of sleep medication use, using a generalized linear model for binomial regression. A human yes/no decision process using a binomial random number was also factored into sleep medication use probability. RESULTS: These probability calculations were repeated 5000 times resulting in an estimate of the most likely amount of sleep aids used during an ISS mission and a 95% confidence interval. CONCLUSIONS: These results were transferred to the parent IMM for further weighting and integration with other medical conditions, to help inform operational decisions. This model is a potential planning tool for ensuring adequate sleep during sleep disrupted periods of a mission.

Lewandowski, Beth↗
NASA NTRS2014

Exploring Inflated Pahohoe Lava Flow Morphologies and the Effects of Cooling Using a New Simulation Approach

Pahoehoe lavas are recognized as an important landform on Earth, Mars and Io. Observations of such flows on Earth (e.g., Figure 1) indicate that the emplacement process is dominated by random effects. Existing models for lobate a`a lava flows that assume viscous fluid flow on an inclined plane are not appropriate for dealing with the numerous random factors present in pahoehoe emplacement. Thus, interpretation of emplacement conditions for pahoehoe lava flows on Mars requires fundamentally different models. A new model that implements a simulation approach has recently been developed that allows exploration of a variety of key influences on pahoehoe lobe emplacement (e.g., source shape, confinement, slope). One important factor that has an impact on the final topographic shape and morphology of a pahoehoe lobe is the volumetric flow rate of lava, where cooling of lava on the lobe surface influences the likelihood of subsequent breakouts.

PAHOHOE LAVA↗
NASA NTRS2011

Filtering Methods for Error Reduction in Spacecraft Attitude Estimation Using Quaternion Star Trackers

Precision attitude determination for recent and planned space missions typically includes quaternion star trackers (ST) and a three-axis inertial reference unit (IRU). Sensor selection is based on estimates of knowledge accuracy attainable from a Kalman filter (KF), which provides the optimal solution for the case of linear dynamics with measurement and process errors characterized by random Gaussian noise with white spectrum. Non-Gaussian systematic errors in quaternion STs are often quite large and have an unpredictable time-varying nature, particularly when used in non-inertial pointing applications. Two filtering methods are proposed to reduce the attitude estimation error resulting from ST systematic errors, 1) extended Kalman filter (EKF) augmented with Markov states, 2) Unscented Kalman filter (UKF) with a periodic measurement model. Realistic assessments of the attitude estimation performance gains are demonstrated with both simulation and flight telemetry data from the Lunar Reconnaissance Orbiter.

Calhoun, Philip C.↗
DOE OSTI2013

Solution of stochastic media transport problems using a numerical quadrature-based method

We present a new conceptual framework for analyzing transport problems in random media. We decompose such problems into stratified subproblems according to the number of material pseudo-interfaces within realizations. For a given subproblem we assign pseudo-interface locations in each realization according to product quadrature rules, which allows us to deterministically generate a fixed number of realizations. Quadrature integration of the solutions of these realizations thus approximately solves each subproblem; the weighted superposition of solutions of the subproblems approximately solves the general stochastic media transport problem. We revisit some benchmark problems to determine the accuracy and efficiency of this approach in comparison to randomly generated realizations. We find that this method is very accurate and fast when the number of pseudo-interfaces in a problem is generally low, but that these advantages quickly degrade as the number of pseudo-interfaces increases. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

On the Optimal Stabilization of an Integral Manifold

By the method of Lyapunov functions, we study the problem of optimal stabilization of an analytically defined integral manifold in the class of stochastic differential equations in the case where random perturbations belong to the class of processes with independent increments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Treating random sequential addition via the replica method

While many physical processes are non-equilibrium in nature, the theory and modeling of such phenomena lag behind theoretical treatments of equilibrium systems. The diversity of powerful theoretical tools available to describe equilibrium systems has inspired strategies that map non-equilibrium systems onto equivalent equilibrium analogs so that interrogation with standard statistical mechanical approaches is possible. In this work, we revisit the mapping from the non-equilibrium random sequential addition process onto an equilibrium multi-component mixture via the replica method, allowing for theoretical predictions of non-equilibrium structural quantities. We validate the above approach by comparing the theoretical predictions to numerical simulations of random sequential addition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Expected Power-Utility Maximization Under Incomplete Information and with Cox-Process Observations

We consider the problem of maximization of expected terminal power utility (risk sensitive criterion). The underlying market model is a regime-switching diffusion model where the regime is determined by an unobservable factor process forming a finite state Markov process. The main novelty is due to the fact that prices are observed and the portfolio is rebalanced only at random times corresponding to a Cox process where the intensity is driven by the unobserved Markovian factor process as well. This leads to a more realistic modeling for many practical situations, like in markets with liquidity restrictions; on the other hand it considerably complicates the problem to the point that traditional methodologies cannot be directly applied. The approach presented here is specific to the power-utility. For log-utilities a different approach is presented in Fujimoto et al. (Preprint, 2012).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1972

On the first-excursion probability in stationary narrow-band random vibration. II.

The first-excursion probability of a stationary narrow-band Gaussian process with mean zero has been studied. Within the framework of point process approach, series approximations derived from the theory of random points and approximations based on the maximum entropy principle have been developed. With the aid of numerical examples, merits of the approximations proposed previously as well as of those developed in this paper have been compared. The results indicate that the maximum entropy principle has not produced satisfactory approximations but the approximation based on nonapproaching random points is found to be the best among all the approximations proposed herein. A conclusion drawn from the present and the previous studies is that the point process approach produces a number of useful approximations for the first-excursion probability, particularly those based on the concepts of the Markov process, the clump-size, and the nonapproaching random points.

Yang, J.-N.↗
DOE OSTI2015

Viable chemical approach for patterning nanoscale magnetoresistive random access memory

A reactive ion etching process with alternating Cl{sub 2} and H{sub 2} exposures has been shown to chemically etch CoFe film that is an integral component in magnetoresistive random access memory (MRAM). Starting with systematic thermodynamic calculations assessing various chemistries and reaction pathways leading to the highest possible vapor pressure of the etch products reactions, the potential chemical combinations were verified by etch rate investigation and surface chemistry analysis in plasma treated CoFe films. An ∼20% enhancement in etch rate was observed with the alternating use of Cl{sub 2} and H{sub 2} plasmas, in comparison with the use of only Cl{sub 2} plasma. This chemical combination was effective in removing metal chloride layers, thus maintaining the desired magnetic properties of the CoFe films. Scanning electron microscopy equipped with energy-dispersive x-ray spectroscopy showed visually and spectroscopically that the metal chloride layers generated by Cl{sub 2} plasma were eliminated with H{sub 2} plasma to yield a clean etch profile. This work suggests that the selected chemistries can be used to etch magnetic metal alloys with a smooth etch profile and this general strategy can be applied to design chemically based etch processes to enable the fabrication of highly integrated nanoscale MRAM devices.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Analysis of the stochastic excitability in the flow chemical reactor

A dynamic model of the thermochemical process in the flow reactor is considered. We study an influence of the random disturbances on the stationary regime of this model. A phenomenon of noise-induced excitability is demonstrated. For the analysis of this phenomenon, a constructive technique based on the stochastic sensitivity functions and confidence domains is applied. It is shown how elaborated technique can be used for the probabilistic analysis of the generation of mixed-mode stochastic oscillations in the flow chemical reactor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1984

Arguments for fundamental emission by the parametric process L yields T + S in interplanetary type III bursts

Observations of low frequency ion acoustic-like waves associated with Langmuir waves present during interplanetary Type 3 bursts are used to study plasma emission mechanisms and wave processes involving ion acoustic waves. It is shown that the observed wave frequency characteristics are consistent with the processes L yields T + S (where L = Langmuir waves, T = electromagnetic waves, S = ion acoustic waves) and L yields L' + S proceeding. The usual incoherent (random phase) version of the process L yields T + S cannot explain the observed wave production time scale. The clumpy nature of the observed Langmuir waves is vital to the theory of IP Type 3 bursts. The incoherent process L yields T + S may encounter difficulties explaining the observed Type 3 brightness temperatures when Langmuir wave clumps are incorporated into the theory. The parametric process L yields T + S may be the important emission process for the fundamental radiation of interplanetary Type 3 bursts.

Cairns, I. H.↗
DOE OSTI2015

Reproducible radiation-damage processes in proteins irradiated by intense x-ray pulses

X-ray free-electron lasers have enabled femtosecond protein nanocrystallography, a novel method to determine the structure of proteins. It allows time-resolved imaging of nanocrystals that are too small for conventional crystallography. The short pulse duration helps in overcoming the detrimental effects of radiation damage because x rays are scattered before the sample has been significantly altered. It has been suggested that, fortuitously, the diffraction process self-terminates abruptly once radiation damage destroys the crystalline order. Our calculations show that high-intensity x-ray pulses indeed trigger a cascade of damage processes in ferredoxin crystals, a particular metalloprotein of interest. However, we found that the damage process is initially not completely random. Correlations exist among the protein monomers, so that Bragg diffraction still occurs in the damaged crystals, despite significant atomic displacements. Our results show that the damage process is reproducible to a certain degree, which is potentially beneficial for the orientation step in single-molecule imaging.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Exits in order: How crowding affects particle lifetimes

Diffusive processes are often represented using stochastic random walk frameworks. The amount of time taken for an individual in a random walk to intersect with an absorbing boundary is a fundamental property that is often referred to as the particle lifetime, or the first passage time. The mean lifetime of particles in a random walk model of diffusion is related to the amount of time required for the diffusive process to reach a steady state. Mathematical analysis describing the mean lifetime of particles in a standard model of diffusion without crowding is well known. However, the lifetime of agents in a random walk with crowding has received much less attention. Since many applications of diffusion in biology and biophysics include crowding effects, here we study a discrete model of diffusion that incorporates crowding. Using simulations, we show that crowding has a dramatic effect on agent lifetimes, and we derive an approximate expression for the mean agent lifetime that includes crowding effects. Our expression matches simulation results very well, and highlights the importance of crowding effects that are sometimes overlooked.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Probabilistic learning on manifolds constrained by nonlinear partial differential equations for small datasets

A novel extension of the Probabilistic Learning on Manifolds (PLoM) is presented. It makes it possible to synthesize solutions to a wide range of nonlinear stochastic boundary value problems described by partial differential equations (PDEs) for which a stochastic computational model (SCM) is available and which depend on a vector-valued random control parameter. The cost of a single numerical evaluation of this SCM is assumed to be such that only a limited number of points can be computed for constructing the training dataset (small data). Each point of the training dataset is made up of realizations from a vector-valued stochastic process (the stochastic solution) and the associated random control parameter on which it depends. The presented PLoM constrained by PDE allows for generating a large number of learned realizations of the stochastic process and its corresponding random control parameter. These learned realizations are generated so as to minimize the vector-valued random residual of the PDE in the mean-square sense. Appropriate novel methods are developed to solve this challenging problem. Three applications are presented. The first one is a simple uncertain nonlinear dynamical system with a nonstationary stochastic excitation. The second one concerns the 2D nonlinear unsteady Navier–Stokes equations for incompressible flows in which the Reynolds number is the random control parameter. Here, the last one deals with the nonlinear dynamics of a 3D elastic structure with uncertainties. The results obtained make it possible to validate the PLoM constrained by stochastic PDE but also provide further validation of the PLoM without constraint.

Machine learning↗