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NASA NTRS1983

Measurements and predictions for nonevaporating sprays in a quiescent environment

Yule et al. (1982) have conducted a study of vaporizing sprays with the aid of laser techniques. The present investigation has the objective to supplement the measurements performed by Yule et al., by considering the limiting case of a spray in a stagnant environment. Mean and fluctuating velocities of the continuous phase are measured by means of laser Doppler anemometry (LDA) techniques, while Fraunhofer diffraction and slide impaction methods are employed to determine drop sizes. Liquid fluxes in the spray are found by making use of an isokinetic sampling probe. The obtained data are used as a basis for the evaluation of three models of the process, including a locally homogeneous flow (LHF) model, a deterministic separated flow (DSF) model, and a stochastic separated flow (SSF) model. It is found that the LHF and DSF models do not provide very satisfactory predictions for the test sprays, while the SSF model does provide reasonably good predictions of the observed structure.

Solomon, A. S. P.↗

NASA NTRS2003

Modeling and Simulation for Mission Operations Work System Design

Work System analysis and design is complex and non-deterministic. In this paper we describe Brahms, a multiagent modeling and simulation environment for designing complex interactions in human-machine systems. Brahms was originally conceived as a business process design tool that simulates work practices, including social systems of work. We describe our modeling and simulation method for mission operations work systems design, based on a research case study in which we used Brahms to design mission operations for a proposed discovery mission to the Moon. We then describe the results of an actual method application project-the Brahms Mars Exploration Rover. Space mission operations are similar to operations of traditional organizations; we show that the application of Brahms for space mission operations design is relevant and transferable to other types of business processes in organizations.

Sierhuis, Maarten↗

NASA NTRS2006

Probabilistic Structural Evaluation of Uncertainties in Radiator Sandwich Panel Design

The Jupiter Icy Moons Orbiter (JIMO) Space System is part of the NASA's Prometheus Program. As part of the JIMO engineering team at NASA Glenn Research Center, the structural design of the JIMO Heat Rejection Subsystem (HRS) is evaluated. An initial goal of this study was to perform sensitivity analyses to determine the relative importance of the input variables on the structural responses of the radiator panel. The desire was to let the sensitivity analysis information identify the important parameters. The probabilistic analysis methods illustrated here support this objective. The probabilistic structural performance evaluation of a HRS radiator sandwich panel was performed. The radiator panel structural performance was assessed in the presence of uncertainties in the loading, fabrication process variables, and material properties. The stress and displacement contours of the deterministic structural analysis at mean probability was performed and results presented. It is followed by a probabilistic evaluation to determine the effect of the primitive variables on the radiator panel structural performance. Based on uncertainties in material properties, structural geometry and loading, the results of the displacement and stress analysis are used as an input file for the probabilistic analysis of the panel. The sensitivity of the structural responses, such as maximum displacement and maximum tensile and compressive stresses of the facesheet in x and y directions and maximum VonMises stresses of the tube, to the loading and design variables is determined under the boundary condition where all edges of the radiator panel are pinned. Based on this study, design critical material and geometric parameters of the considered sandwich panel are identified.

Kuguoglu, Latife↗

NASA NTRS2010

Meeting Radiation Protection Requirements and Reducing Spacecraft Mass - A Multifunctional Materials Approach

Both crew and radio-sensitive systems, especially electronics must be protected from the effects of the space radiation environment. One method of mitigating this radiation exposure is to use passive-shielding materials. In previous vehicle designs such as the International Space Station (ISS), materials such as aluminum and polyethylene have been used as parasitic shielding to protect crew and electronics from exposure, but these designs add mass and decrease the amount of usable volume inside the vehicle. Thus, it is of interest to understand whether structural materials can also be designed to provide the radiation shielding capability needed for crew and electronics, while still providing weight savings and increased useable volume when compared against previous vehicle shielding designs. In this paper, we present calculations and analysis using the HZETRN (deterministic) and FLUKA (Monte Carlo) codes to investigate the radiation mitigation properties of these structural shielding materials, which includes graded-Z and composite materials. This work is also a follow-on to an earlier paper, that compared computational results for three radiation transport codes, HZETRN, HETC, and FLUKA, using the Feb. 1956 solar particle event (SPE) spectrum. In the following analysis, we consider the October 1989 Ground Level Enhanced (GLE) SPE as the input source term based on the Band function fitting method. Using HZETRN and FLUKA, parametric absorbed doses at the center of a hemispherical structure on the lunar surface are calculated for various thicknesses of graded-Z layups and an all-aluminum structure. HZETRN and FLUKA calculations are compared and are in reasonable (18% to 27%) agreement. Both codes are in agreement with respect to the predicted shielding material performance trends. The results from both HZETRN and FLUKA are analyzed and the radiation protection properties and potential weight savings of various materials and materials lay-ups are compared.

Atwell, William↗

NASA NTRS1992

Distance estimation and collision prediction for on-line robotic motion planning

An efficient method for computing the minimum distance and predicting collisions between moving objects is presented. This problem is incorporated into the framework of an in-line motion-planning algorithm to satisfy collision avoidance between a robot and moving objects modeled as convex polyhedra. In the beginning, the deterministic problem where the information about the objects is assumed to be certain is examined. L(1) or L(infinity) norms are used to represent distance and the problem becomes a linear programming problem. The stochastic problem is formulated where the uncertainty is induced by sensing and the unknown dynamics of the moving obstacles. Two problems are considered: First, filtering of the distance between the robot and the moving object at the present time. Second, prediction of the minimum distance in the future in order to predict the collision time.

Kyriakopoulos, K. J.↗

NASA NTRS1991

Distance estimation and collision prediction for on-line robotic motion planning

An efficient method for computing the minimum distance and predicting collisions between moving objects is presented. This problem has been incorporated in the framework of an in-line motion planning algorithm to satisfy collision avoidance between a robot and moving objects modeled as convex polyhedra. In the beginning the deterministic problem, where the information about the objects is assumed to be certain is examined. If instead of the Euclidean norm, L(sub 1) or L(sub infinity) norms are used to represent distance, the problem becomes a linear programming problem. The stochastic problem is formulated, where the uncertainty is induced by sensing and the unknown dynamics of the moving obstacles. Two problems are considered: (1) filtering of the minimum distance between the robot and the moving object, at the present time; and (2) prediction of the minimum distance in the future, in order to predict possible collisions with the moving obstacles and estimate the collision time.

Kyriakopoulos, K. J.↗

NASA NTRS2010

Hidden Statistics Approach to Quantum Simulations

Recent advances in quantum information theory have inspired an explosion of interest in new quantum algorithms for solving hard computational (quantum and non-quantum) problems. The basic principle of quantum computation is that the quantum properties can be used to represent structure data, and that quantum mechanisms can be devised and built to perform operations with this data. Three basic non-classical properties of quantum mechanics superposition, entanglement, and direct-product decomposability were main reasons for optimism about capabilities of quantum computers that promised simultaneous processing of large massifs of highly correlated data. Unfortunately, these advantages of quantum mechanics came with a high price. One major problem is keeping the components of the computer in a coherent state, as the slightest interaction with the external world would cause the system to decohere. That is why the hardware implementation of a quantum computer is still unsolved. The basic idea of this work is to create a new kind of dynamical system that would preserve the main three properties of quantum physics superposition, entanglement, and direct-product decomposability while allowing one to measure its state variables using classical methods. In other words, such a system would reinforce the advantages and minimize limitations of both quantum and classical aspects. Based upon a concept of hidden statistics, a new kind of dynamical system for simulation of Schroedinger equation is proposed. The system represents a modified Madelung version of Schroedinger equation. It preserves superposition, entanglement, and direct-product decomposability while allowing one to measure its state variables using classical methods. Such an optimal combination of characteristics is a perfect match for simulating quantum systems. The model includes a transitional component of quantum potential (that has been overlooked in previous treatment of the Madelung equation). The role of the transitional potential is to provide a jump from a deterministic state to a random state with prescribed probability density. This jump is triggered by blowup instability due to violation of Lipschitz condition generated by the quantum potential. As a result, the dynamics attains quantum properties on a classical scale. The model can be implemented physically as an analog VLSI-based (very-large-scale integration-based) computer, or numerically on a digital computer. This work opens a way of developing fundamentally new algorithms for quantum simulations of exponentially complex problems that expand NASA capabilities in conducting space activities. It has been illustrated that the complexity of simulations of particle interaction can be reduced from an exponential one to a polynomial one.

Zak, Michail↗

NASA NTRS2004

SPIN or LURCH : a Comparative Assessment of Model Checking and Stochastic Search for Temporal Properties in Procedural Code

The difficulty of how to test large systems, such as the one on board a NASA robotic remote explorer (RRE) vehicle, is fundamentally a search issue: the global state space representing all possible has yet to be solved, even after many decades of work. Randomized algorithms have been known to outperform their deterministic counterparts for search problems representing a wide range of applications. In the case study presented here, the LURCH randomized algorithm proved to be adequate to the task of testing a NASA RRE vehicle. LURCH found all the errors found by an earlier analysis of a more complete method (SPIN). Our empirical results are that LURCH can scale to much larger models than standard model checkers like SMV and SPIN. Further, the LURCH analysis was simpler than the SPIN analysis. The simplicity and scalability of LURCH are two compelling reasons for experimenting further with this tool.

verification↗

NASA NTRS1988

Symbolic inversion of control relationships in model-based expert systems

Symbolic inversion is examined from several perspectives. First, a number of symbolic algebra and mathematical tool packages were studied in order to evaluate their capabilities and methods, specifically with respect to symbolic inversion. Second, the KATE system (without hardware interface) was ported to a Zenith Z-248 microcomputer running Golden Common Lisp. The interesting thing about the port is that it allows the user to have measurements vary and components fail in a non-deterministic manner based upon random value from probability distributions. Third, INVERT was studied as currently implemented in KATE, its operation documented, some of its weaknesses identified, and corrections made to it. The corrections and enhancements are primarily in the way that logical conditions involving AND's and OR's and inequalities are processed. In addition, the capability to handle equalities was also added. Suggestions were also made regarding the handling of ranges in INVERT. Last, other approaches to the inversion process were studied and recommendations were made as to how future versions of KATE should perform symbolic inversion.

Thomas, Stan↗

NASA NTRS2010

Proton Lateral Broadening Distribution Comparisons Between GRNTRN, MCNPX, and Laboratory Beam Measurements

Recent developments in NASA s deterministic High charge (Z) and Energy TRaNsport (HZETRN) code have included lateral broadening of primary ion beams due to small-angle multiple Coulomb scattering, and coupling of the ion-nuclear scattering interactions with energy loss and straggling. This new version of HZETRN is based on Green function methods, called GRNTRN, and is suitable for modeling transport with both space environment and laboratory boundary conditions. Multiple scattering processes are a necessary extension to GRNTRN in order to accurately model ion beam experiments, to simulate the physical and biological-effective radiation dose, and to develop new methods and strategies for light ion radiation therapy. In this paper we compare GRNTRN simulations of proton lateral broadening distributions with beam measurements taken at Loma Linda University Proton Therapy Facility. The simulated and measured lateral broadening distributions are compared for a 250 MeV proton beam on aluminum, polyethylene, polystyrene, bone substitute, iron, and lead target materials. The GRNTRN results are also compared to simulations from the Monte Carlo MCNPX code for the same projectile-target combinations described above.

Mertens, Christopher J.↗

NASA NTRS1988

Observer design for compensation of network-induced delays in integrated communication and control systems

A method for compensating the effects of network-induced delays in integrated communication and control systems (ICCS) is proposed, and a finite-dimensional time-invariant ICCS model is developed. The problem of analyzing systems with time-varying and stochastic delays is circumvented by the application of a deterministic observer. For the case of controller-to-actuator delays, the observed design must rely on an extended model which represents the delays as additional states.

Luck, R.↗

NASA NTRS1997

Spectral Density of Laser Beam Scintillation in Wind Turbulence: Theory - Part 1

The temporal spectral density of the log-amplitude scintillation of a laser beam wave due to a spatially dependent vector-valued crosswind (deterministic as well as random) is evaluated. The path weighting functions for normalized spectral moments are derived, and offer a potential new technique for estimating the wind velocity profile. The Tatarskii-Klyatskin stochastic propagation equation for the Markov turbulence model is used with the solution approximated by the Rytov method. The Taylor 'frozen-in' hypothesis is assumed for the dependence of the refractive index on the wind velocity, and the Kolmogorov spectral density is used for the refractive index field.

Balakrishnan, A. V.↗

NASA NTRS2006

Towards Robust Designs Via Multiple-Objective Optimization Methods

Fabricating and operating complex systems involves dealing with uncertainty in the relevant variables. In the case of aircraft, flow conditions are subject to change during operation. Efficiency and engine noise may be different from the expected values because of manufacturing tolerances and normal wear and tear. Engine components may have a shorter life than expected because of manufacturing tolerances. In spite of the important effect of operating- and manufacturing-uncertainty on the performance and expected life of the component or system, traditional aerodynamic shape optimization has focused on obtaining the best design given a set of deterministic flow conditions. Clearly it is important to both maintain near-optimal performance levels at off-design operating conditions, and, ensure that performance does not degrade appreciably when the component shape differs from the optimal shape due to manufacturing tolerances and normal wear and tear. These requirements naturally lead to the idea of robust optimal design wherein the concept of robustness to various perturbations is built into the design optimization procedure. The basic ideas involved in robust optimal design will be included in this lecture. The imposition of the additional requirement of robustness results in a multiple-objective optimization problem requiring appropriate solution procedures. Typically the costs associated with multiple-objective optimization are substantial. Therefore efficient multiple-objective optimization procedures are crucial to the rapid deployment of the principles of robust design in industry. Hence the companion set of lecture notes (Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks ) deals with methodology for solving multiple-objective Optimization problems efficiently, reliably and with little user intervention. Applications of the methodologies presented in the companion lecture to robust design will be included here. The evolutionary method (DE) is first used to solve a relatively difficult problem in extended surface heat transfer wherein optimal fin geometries are obtained for different safe operating base temperatures. The objective of maximizing the safe operating base temperature range is in direct conflict with the objective of maximizing fin heat transfer. This problem is a good example of achieving robustness in the context of changing operating conditions. The evolutionary method is then used to design a turbine airfoil; the two objectives being reduced sensitivity of the pressure distribution to small changes in the airfoil shape and the maximization of the trailing edge wedge angle with the consequent increase in airfoil thickness and strength. This is a relevant example of achieving robustness to manufacturing tolerances and wear and tear in the presence of other objectives.

Man Mohan, Rai↗

NASA NTRS1987

Fault-tolerant clock synchronization validation methodology

A validation method for the synchronization subsystem of a fault-tolerant computer system is presented. The high reliability requirement of flight-crucial systems precludes the use of most traditional validation methods. The method presented utilizes formal design proof to uncover design and coding errors and experimentation to validate the assumptions of the design proof. The experimental method is described and illustrated by validating the clock synchronization system of the Software Implemented Fault Tolerance computer. The design proof of the algorithm includes a theorem that defines the maximum skew between any two nonfaulty clocks in the system in terms of specific system parameters. Most of these parameters are deterministic. One crucial parameter is the upper bound on the clock read error, which is stochastic. The probability that this upper bound is exceeded is calculated from data obtained by the measurement of system parameters. This probability is then included in a detailed reliability analysis of the system.

Computer systems↗

NASA NTRS1989

Probabilistic structural analysis of space propulsion system turbine blades

Probabilistic loads and stress analysis methods are presently applied to the second-stage blade of the SSME's high-pressure fuel turbopump, in order to illustrate how loads and stress responses can be quantified probabilistically and how the sensitivity of such component- and engine-level independent variables as engine inlet temperatures and local seal wear within the turbopump can be determined. Attention is given to a method for the derivation of probabilistic pressure, temperature, and centrifugal steady-state load descriptions of this second-stage blade from the top of the airfoil to its intersection with the firtree. Dependent-load random variables are obtained from a multilevel physical model in which duty cycle-dependent deterministic loads and related probabilistic variations are accounted for.

Newell, J. F.↗

NASA NTRS2020

Modeling Uncertainty in Large Natural Resource Allocation Problems

The productivity of the world's natural resources is critically dependent on a variety of highly uncertain factors, which obscure individual investors and governments that seek to make long-term, sometimes irreversible investments in their exploration and utilization. These dynamic considerations are poorly represented in disaggregated resource models, as incorporating uncertainty into large-dimensional problems presents a challenging computational task. This study introduces a novel numerical method to solve large-scale dynamic stochastic natural resource allocation problems that cannot be addressed by conventional methods. The method is illustrated with an application focusing on the allocation of global land resource use under stochastic crop yields due to adverse climate impacts and limits on further technological progress. For the same model parameters, the range of land conversion is considerably smaller for the dynamic stochastic model as compared to deterministic scenario analysis. The scenario analysis can thus significantly overstate the magnitude of expected land conversion under uncertain crop yields.

Cai, Yongyang↗

NASA NTRSDate not supplied

A Practical Approach to Uncertainty Quantification Using Probability Boxes

To date, while the use of CFD for aerospace vehicle design and development is prevalent, the documentation of uncertainties associated with the simulations are rare. Instead, the current state-of-the-art relies heavily on the experience of the CFD practitioner to estimate the uncertainty associated with their simulations through simple sensitivity studies or subject matter expertise. This practice will have to be replaced with a formal uncertainty quantification (UQ) process if CFD is to play an expanded role in the research and engineering design community, test and evaluation community, and ultimately certification for flight. Accounting for uncertainties in a formal manner is a tedious process. Moreover, the typical CFD practitioner is not likely to be familiar with formal UQ methods. These factors have prevented the adoption of UQ methods in the engineering design and development cycle. This presentation will outline a credible approach to UQ using Probability Boxes that is straightforward to apply, and can readily be automated using existing UQ tool sets such as the DAKOTA packaged developed at Sandia. The added expense incurred when moving away from a deterministic CFD process to a stochastic one that captures uncertainties to enable risk-informed decision making will be discussed, as well as effective ways to reduce the computational costs.

Uncertainty Quantification↗

NASA NTRS2004

MESTRN: A Deterministic Meson-Muon Transport Code for Space Radiation

A safe and efficient exploration of space requires an understanding of space radiations, so that human life and sensitive equipment can be protected. On the way to these sensitive sites, the radiation fields are modified in both quality and quantity. Many of these modifications are thought to be due to the production of pions and muons in the interactions between the radiation and intervening matter. A method used to predict the effects of the presence of these particles on the transport of radiation through materials is developed. This method was then used to develop software, which was used to calculate the fluxes of pions and muons after the transport of a cosmic ray spectrum through aluminum and water. Software descriptions are given in the appendices.

Blattnig, Steve R.↗