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At least 217 records · Page 12

Reliability evaluation methodology for NASA applications

Liquid rocket engine technology has been characterized by the development of complex systems containing large number of subsystems, components, and parts. The trend to even larger and more complex system is continuing. The liquid rocket engineers have been focusing mainly on performance driven designs to increase payload delivery of a launch vehicle for a given mission. In otherwords, although the failure of a single inexpensive part or component may cause the failure of the system, reliability in general has not been considered as one of the system parameters like cost or performance. Up till now, quantification of reliability has not been a consideration during system design and development in the liquid rocket industry. Engineers and managers have long been aware of the fact that the reliability of the system increases during development, but no serious attempts have been made to quantify reliability. As a result, a method to quantify reliability during design and development is needed. This includes application of probabilistic models which utilize both engineering analysis and test data. Classical methods require the use of operating data for reliability demonstration. In contrast, the method described in this paper is based on similarity, analysis, and testing combined with Bayesian statistical analysis.

Taneja, Vidya S.↗

Stochastic damage evolution in textile laminates

A probabilistic model utilizing random material characteristics to predict damage evolution in textile laminates is presented. Model is based on a division of each ply into two sublaminas consisting of cells. The probability of cell failure is calculated using stochastic function theory and maximal strain failure criterion. Three modes of failure, i.e. fiber breakage, matrix failure in transverse direction, as well as matrix or interface shear cracking, are taken into account. Computed failure probabilities are utilized in reducing cell stiffness based on the mesovolume concept. A numerical algorithm is developed predicting the damage evolution and deformation history of textile laminates. Effect of scatter of fiber orientation on cell properties is discussed. Weave influence on damage accumulation is illustrated with the help of an example of a Kevlar/epoxy laminate.

Dzenis, Yuris A.↗

Experimental evaluation of the certification-trail method

Certification trails are a recently introduced and promising approach to fault-detection and fault-tolerance. A comprehensive attempt to assess experimentally the performance and overall value of the method is reported. The method is applied to algorithms for the following problems: huffman tree, shortest path, minimum spanning tree, sorting, and convex hull. Our results reveal many cases in which an approach using certification-trails allows for significantly faster overall program execution time than a basic time redundancy-approach. Algorithms for the answer-validation problem for abstract data types were also examined. This kind of problem provides a basis for applying the certification-trail method to wide classes of algorithms. Answer-validation solutions for two types of priority queues were implemented and analyzed. In both cases, the algorithm which performs answer-validation is substantially faster than the original algorithm for computing the answer. Next, a probabilistic model and analysis which enables comparison between the certification-trail method and the time-redundancy approach were presented. The analysis reveals some substantial and sometimes surprising advantages for ther certification-trail method. Finally, the work our group performed on the design and implementation of fault injection testbeds for experimental analysis of the certification trail technique is discussed. This work employs two distinct methodologies, software fault injection (modification of instruction, data, and stack segments of programs on a Sun Sparcstation ELC and on an IBM 386 PC) and hardware fault injection (control, address, and data lines of a Motorola MC68000-based target system pulsed at logical zero/one values). Our results indicate the viability of the certification trail technique. It is also believed that the tools developed provide a solid base for additional exploration.

Sullivan, Gregory F.↗

Use of common time base for checkpointing and rollback recovery in a distributed system

An approach to checkpointing and rollback recovery in a distributed computing system using a common time base is proposed. A common time base is established in the system using a hardware clock synchronization algorithm. This common time base is coupled with the idea of pseudo-recovery points to develop a checkpointing algorithm that has the following advantages: reduced wait for commitment for establishing recovery lines, fewer messages to be exchanged, and less memory requirement. These advantages are assessed quantitatively by developing a probabilistic model.

Ramanathan, Parameswaran↗

A Probabilistic Tool that Aids Logistics Engineers in the Establishment of High Confidence Repair Need-Dates at the NASA Shuttle Logistics Depot

The NASA Shuttle Logistics Depot (NSLD) is tasked with the responsibility for repair and manufacture of Line Replaceable Unit (LRU) hardware and components to support the Space Shuttle Orbiter. Due to shrinking budgets, cost effective repair of LRU's becomes a primary objective. To achieve this objective, is imperative that resources be assigned to those LRU's which have the greatest expectation of being needed as a spare. Forecasting the times at which spares are needed requires consideration of many significant factors including: failure rate, flight rate, spares availability, and desired level of support, among others. This paper summarizes the results of the research and development work that has been accomplished in producing an automated tool that assists in the assignment of effective repair start-times for LRU's at the NSLD. This system, called the Repair Start-time Assessment System (RSAS), uses probabilistic modeling technology to calculate a need date for a repair that considers the current repair pipeline status, as well as, serviceable spares and projections of future demands. The output from the system is a date for beginning the repair that has significantly greater confidence (in the sense that a desired probability of support is ensured) than times produced using other techniques. Since an important output of RSAS is the longest repair turn-around time that will ensure a desired probability of support, RSAS has the potential for being applied to operations at any repair depot where spares are on-hand and repair start-times are of interest. In addition, RSAS incorporates tenants of Just-in-Time (JIT) techniques in that the latest repair start-time (i.e., the latest time at which repair resources must be committed) may be calculated for every failed unit This could reduce the spares inventory for certain items, without significantly increasing the risk of unsatisfied demand.

Bullington, J. V.↗

Self-Directed Cooperative Planetary Rovers

The project is concerned with the development of decision-theoretic techniques to optimize the scientific return of planetary rovers. Planetary rovers are small unmanned vehicles equipped with cameras and a variety of sensors used for scientific experiments. They must operate under tight constraints over such resources as operation time, power, storage capacity, and communication bandwidth. Moreover, the limited computational resources of the rover limit the complexity of on-line planning and scheduling. We have developed a comprehensive solution to this problem that involves high-level tools to describe a mission; a compiler that maps a mission description and additional probabilistic models of the components of the rover into a Markov decision problem; and algorithms for solving the rover control problem that are sensitive to the limited computational resources and high-level of uncertainty in this domain.

Zilberstein, Shlomo↗

Fundamental space radiobiology

The unique feature of the space radiation environment is the dominance of high-energy charged particles (HZE or high LET radiation) emitted by the Sun and galactic sources, or trapped in the Van Allen radiation belts. These charged particles present a significant hazard to space flight crews, and accelerator-based experiments are underway to quantify the health risks due to unavoidable radiation exposure. There are three principal properties of charged particles that distinguish them from conventional radiation, i.e. gamma rays and x-rays. First, they have a defined range in matter rather than an exponential absorption profile. Second, they undergo nuclear reactions to produce secondary particles. Third, and most important, they deposit their energy along well-defined linear paths or tracks rather than diffuse fields. The structured energy deposition pattern interacts on multiple scales with the biological structures of DNA, cells and tissues to produce correlated patterns of damage that evade repair systems. Traditional concepts of dose and its associated normalization parameter, RBE (relative biological effectiveness), break down under experimental scrutiny, and probabilistic models of risk based on the number of particle traversals per cell may be more appropriate. Unique patterns of DNA damage, gene expression, mobilization of repair proteins, activation of cytokines and remodeling of cellular microenvironment are observed following exposure to high LET radiation. At low levels of exposure the communication of bioactive substances from irradiated to unirradiated "bystander" cells can amplify the damage and cause a significant deviation from linearity in dose vs. response relations. Under some circumstances, there is even a multigenerational delay in the expression of radiation-induced genetic damage (genomic instability) which is not strictly dose dependent. These issues and the experimental evidence derived from ground based experiments at particle accelerators are presented along with speculation about how modified inertial conditions might perturb homeostatic responses to radiation to further complicate risk assessment for space flight.

NASA Discipline Radiation Health↗

Classification image analysis: estimation and statistical inference for two-alternative forced-choice experiments

We consider estimation and statistical hypothesis testing on classification images obtained from the two-alternative forced-choice experimental paradigm. We begin with a probabilistic model of task performance for simple forced-choice detection and discrimination tasks. Particular attention is paid to general linear filter models because these models lead to a direct interpretation of the classification image as an estimate of the filter weights. We then describe an estimation procedure for obtaining classification images from observer data. A number of statistical tests are presented for testing various hypotheses from classification images based on some more compact set of features derived from them. As an example of how the methods we describe can be used, we present a case study investigating detection of a Gaussian bump profile.

Non-NASA Center↗

Using information Theory in Optimal Test Point Selection for Health Management in NASA's Exploration Vehicles

In this paper, we will present a new methodology that measures the "worth" of deploying an additional testing instrument (sensor) in terms of the amount of information that can be retrieved from such measurement. This quantity is obtained using a probabilistic model of RLV's that has been partially developed in the NASA Ames Research Center. A number of correlated attributes are identified and used to obtain the worth of deploying a sensor in a given test point from an information-theoretic viewpoint. Once the information-theoretic worth of sensors is formulated and incorporated into our general model for IHM performance, the problem can be formulated as a constrained optimization problem where reliability and operational safety of the system as a whole is considered. Although this research is conducted specifically for RLV's, the proposed methodology in its generic form can be easily extended to other domains of systems health monitoring.

Mehr, Ali Farhang↗

Obstacle detection in foliage with ladar and radar

Autonomous off-road navigation is central to several important applications of unmanned ground vehicles. This requires the ability to detect obstacles in vegetation. We examine the prospects for doing so with scanning ladar and with a linear array of 2.2 GHz micro-impulse radar transceivers. For ladar, we summarize our work to date on algorithms for detecting obstacles in tall grass with single-axis ladar, then present a simple probabilistic model of the distance into tall grass that ladar-based obstacle detection is possible.

ladar↗

A Bayesian Framework for Landing Site Selection During Autonomous Spacecraft Descent

The success of a landed space exploration mission depends largely on the final landing site. Factors influencing site selection include safety, fuel-consumption, and scientific return. This paper addresses the problem of selecting the best available landing site based on these factors in real-time during autonomous spacecraft descent onto a planetary surface. The problem is modeled probabilistically using Bayesian Networks (BNs). BNs provide a means of representing the causal relationships between variables that impact the quality of a landing site. The final landing site is determined via probabilistic reasoning based on terrain safety derived from on-board sensors, available fuel based on spacecraft descent dynamics, and regions of interest defined by mission scientists.

entry, descent, landing (EDL)↗

Statistical Prediction of Solar Particle Event Frequency Based on the Measurements of Recent Solar Cycles for Acute Radiation Risk Analysis

Large solar particle events (SPEs) present significant acute radiation risks to the crew members during extra-vehicular activities (EVAs) or in lightly shielded space vehicles for space missions beyond the protection of the Earth's magnetic field. Acute radiation sickness (ARS) can impair performance and result in failure of the mission. Improved forecasting capability and/or early-warning systems and proper shielding solutions are required to stay within NASA's short-term dose limits. Exactly how to make use of observations of SPEs for predicting occurrence and size is a great challenge, because SPE occurrences themselves are random in nature even though the expected frequency of SPEs is strongly influenced by the time position within the solar activity cycle. Therefore, we developed a probabilistic model approach, where a cumulative expected occurrence curve of SPEs for a typical solar cycle was formed from a non-homogeneous Poisson process model fitted to a database of proton fluence measurements of SPEs that occurred during the past 5 solar cycles (19 - 23) and those of large SPEs identified from impulsive nitrate enhancements in polar ice. From the fitted model, the expected frequency of SPEs was estimated at any given proton fluence threshold (Phi(sub E)) with energy (E) >30 MeV during a defined space mission period. Corresponding Phi(sub E) (E=30, 60, and 100 MeV) fluence distributions were simulated with a random draw from a gamma distribution, and applied for SPE ARS risk analysis for a specific mission period. It has been found that the accurate prediction of deep-seated organ doses was more precisely predicted at high energies, Phi(sub 100), than at lower energies such as Phi(sub 30) or Phi(sub 60), because of the high penetration depth of high energy protons. Estimates of ARS are then described for 90th and 95th percentile events for several mission lengths and for several likely organ dose-rates. The ability to accurately measure high energy protons (50-300 MeV) in real-time is shown to be a crucial issue for crew protection.

Myung-Hee, Y. Kim↗

An Extreme-Value Approach to Anomaly Vulnerability Identification

The objective of this paper is to present a method for importance analysis in parametric probabilistic modeling where the result of interest is the identification of potential engineering vulnerabilities associated with postulated anomalies in system behavior. In the context of Accident Precursor Analysis (APA), under which this method has been developed, these vulnerabilities, designated as anomaly vulnerabilities, are conditions that produce high risk in the presence of anomalous system behavior. The method defines a parameter-specific Parameter Vulnerability Importance measure (PVI), which identifies anomaly risk-model parameter values that indicate the potential presence of anomaly vulnerabilities, and allows them to be prioritized for further investigation. This entails analyzing each uncertain risk-model parameter over its credible range of values to determine where it produces the maximum risk. A parameter that produces high system risk for a particular range of values suggests that the system is vulnerable to the modeled anomalous conditions, if indeed the true parameter value lies in that range. Thus, PVI analysis provides a means of identifying and prioritizing anomaly-related engineering issues that at the very least warrant improved understanding to reduce uncertainty, such that true vulnerabilities may be identified and proper corrective actions taken.

Everett, Chris↗

Probabilistic Assessment of Risks from Solar Energetic Particle Events

Solar energetic particle events pose a radiation hazard for space crews and a risk of harmful radiation effects in spacecraft electronics. To assess these risks, engineers need to know the worst-case environment that they must plan for or design to withstand. Depending on the application, engineers may need to know the instantaneous worst-case environment, the radiation environment that accumulates during one solar particle event or the cumulative worst-case environment for their entire mission. Also, depending on their application, they will need to know this environment at a confidence level which they will specify. We will present a probabilistic model for the peak fluxes, event-integrated fluences and mission-integrated fluences for solar protons and heavy ions. The model will provide these worst-case environments at user-specified confidence levels. Examples of the use of this model will also be shown.

Adams, James H., Jr.↗

Comparison of Traditional Design Nonlinear Programming Optimization and Stochastic Methods for Structural Design

Structural design generated by traditional method, optimization method and the stochastic design concept are compared. In the traditional method, the constraints are manipulated to obtain the design and weight is back calculated. In design optimization, the weight of a structure becomes the merit function with constraints imposed on failure modes and an optimization algorithm is used to generate the solution. Stochastic design concept accounts for uncertainties in loads, material properties, and other parameters and solution is obtained by solving a design optimization problem for a specified reliability. Acceptable solutions were produced by all the three methods. The variation in the weight calculated by the methods was modest. Some variation was noticed in designs calculated by the methods. The variation may be attributed to structural indeterminacy. It is prudent to develop design by all three methods prior to its fabrication. The traditional design method can be improved when the simplified sensitivities of the behavior constraint is used. Such sensitivity can reduce design calculations and may have a potential to unify the traditional and optimization methods. Weight versus reliabilitytraced out an inverted-S-shaped graph. The center of the graph corresponded to mean valued design. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure. Weight can be reduced to a small value for a most failure-prone design. Probabilistic modeling of load and material properties remained a challenge.

Patnaik, Surya N.↗

Calculating Launch Vehicle Flight Performance Reserve

This paper addresses different methods for determining the amount of extra propellant (flight performance reserve or FPR) that is necessary to reach orbit with a high probability of success. One approach involves assuming that the various influential parameters are independent and that the result behaves as a Gaussian. Alternatively, probabilistic models may be used to determine the vehicle and environmental models that will be available (estimated) for a launch day go/no go decision. High-fidelity closed-loop Monte Carlo simulation determines the amount of propellant used with each random combination of parameters that are still unknown at the time of launch. Using the results of the Monte Carlo simulation, several methods were used to calculate the FPR. The final chosen solution involves determining distributions for the pertinent outputs and running a separate Monte Carlo simulation to obtain a best estimate of the required FPR. This result differs from the result obtained using the other methods sufficiently that the higher fidelity is warranted.

Hanson, John M.↗

Model Calibration Efforts for the International Space Station's Solar Array Mast

The International Space Station (ISS) relies on sixteen solar-voltaic blankets to provide electrical power to the station. Each pair of blankets is supported by a deployable boom called the Folding Articulated Square Truss Mast (FAST Mast). At certain ISS attitudes, the solar arrays can be positioned in such a way that shadowing of either one or three longerons causes an unexpected asymmetric thermal loading that if unchecked can exceed the operational stability limits of the mast. Work in this paper documents part of an independent NASA Engineering and Safety Center effort to assess the existing operational limits. Because of the complexity of the system, the problem is being worked using a building-block progression from components (longerons), to units (single or multiple bays), to assembly (full mast). The paper presents results from efforts to calibrate the longeron components. The work includes experimental testing of two types of longerons (straight and tapered), development of Finite Element (FE) models, development of parameter uncertainty models, and the establishment of a calibration and validation process to demonstrate adequacy of the models. Models in the context of this paper refer to both FE model and probabilistic parameter models. Results from model calibration of the straight longerons show that the model is capable of predicting the mean load, axial strain, and bending strain. For validation, parameter values obtained from calibration of straight longerons are used to validate experimental results for the tapered longerons.

Elliott, Kenny B.↗

Scale Dependence of Spatiotemporal Intermittence of Rain

It is a common experience that rainfall is intermittent in space and time. This is reflected by the fact that the statistics of area- and/or time-averaged rain rate is described by a mixed distribution with a nonzero probability of having a sharp value zero. In this paper we have explored the dependence of the probability of zero rain on the averaging space and time scales in large multiyear data sets based on radar and rain gauge observations. A stretched exponential fannula fits the observed scale dependence of the zero-rain probability. The proposed formula makes it apparent that the space-time support of the rain field is not quite a set of measure zero as is sometimes supposed. We also give an ex.planation of the observed behavior in tenus of a simple probabilistic model based on the premise that rainfall process has an intrinsic memory.

Kundu, Prasun K.↗