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At least 397 records · Page 22

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↗

Development of a Probabilistic Component Mode Synthesis Method for the Analysis of Non-Deterministic Substructures

Standard methods of structural dynamic analysis assume that the structural characteristics are deterministic. Recognizing that these characteristics are actually statistical in nature, researchers have recently developed a variety of methods that use this information to determine probabilities of a desired response characteristic, such as natural frequency, without using expensive Monte Carlo simulations. One of the problems in these methods is correctly identifying the statistical properties of primitive variables such as geometry, stiffness, and mass. This paper presents a method where the measured dynamic properties of substructures are used instead as the random variables. The residual flexibility method of component mode synthesis is combined with the probabilistic methods to determine the cumulative distribution function of the system eigenvalues. A simple cantilever beam test problem is presented that illustrates the theory.

Brown, Andrew M.↗

Uncertainty Estimation Cheat Sheet for Probabilistic Risk Assessment

"Uncertainty analysis itself is uncertain, therefore, you cannot evaluate it exactly," Source Uncertain Quantitative results for aerospace engineering problems are influenced by many sources of uncertainty. Uncertainty analysis aims to make a technical contribution to decision-making through the quantification of uncertainties in the relevant variables as well as through the propagation of these uncertainties up to the result. Uncertainty can be thought of as a measure of the 'goodness' of a result and is typically represented as statistical dispersion. This paper will explain common measures of centrality and dispersion; and-with examples-will provide guidelines for how they may be estimated to ensure effective technical contributions to decision-making.

Britton, Paul T.↗

Space system operations and support cost analysis using Markov chains

This paper evaluates the use of Markov chain process in probabilistic life cycle cost analysis and suggests further uses of the process as a design aid tool. A methodology is developed for estimating operations and support cost and expected life for reusable space transportation systems. Application of the methodology is demonstrated for the case of a hypothetical space transportation vehicle. A sensitivity analysis is carried out to explore the effects of uncertainty in key model inputs.

Unal, Resit↗

A comparison of economic evaluation models as applied to geothermal energy technology

Several cost estimation and financial cash flow models have been applied to a series of geothermal case studies. In order to draw conclusions about relative performance and applicability of these models to geothermal projects, the consistency of results was assessed. The model outputs of principal interest in this study were net present value, internal rate of return, or levelized breakeven price. The models used were VENVAL, a venture analysis model; the Geothermal Probabilistic Cost Model (GPC Model); the Alternative Power Systems Economic Analysis Model (APSEAM); the Geothermal Loan Guarantee Cash Flow Model (GCFM); and the GEOCOST and GEOCITY geothermal models. The case studies to which the models were applied include a geothermal reservoir at Heber, CA; a geothermal eletric power plant to be located at the Heber site; an alcohol fuels production facility to be built at Raft River, ID; and a direct-use, district heating system in Susanville, CA.

Ziman, G. M.↗

Entry, Descent, and Landing technological barriers and crewed MARSvehicle performance analysis

Mars has been explored historically only by robotic crafts, but a crewed mission encompasses several new engineering challenges – high ballistic coefficient entry, hypersonic decelerators, guided entry for reaching intended destinations within acceptable margins for error in the landing ellipse, and payload mass are all critical factors for evaluation. A comprehensive EDL parametric analysis has been conducted in support of a high mass landing architecture by evaluating three types of vehicles −70° Sphere Cone, Ellipsled and SpaceX hybrid architecture called Red Dragon as potential candidate options for crewed entry vehicles. Aerocapture at the Martian orbit of about 400 km and subsequent Entry-from-orbit scenarios were investigated at velocities of 6.75 km/s and 4 km/s respectively. A study on aerocapture corridor over a range of entry velocities (6–9 km/s) suggests that a hypersonic L/D of 0.3 is sufficient for a Martian aerocapture. Parametric studies conducted by varying aeroshell diameters from 10 m to 15 m for several entry masses up to 150 mt are summarized and results reveal that vehicles with entry masses in the range of about 40–80 mt are capable of delivering cargo with a mass on the order of 5–20 mt. For vehicles with an entry mass of 20 mt to 80 mt, probabilistic Monte Carlo analysis of 5000 cases for each vehicle were run to determine the final landing ellipse and to quantify the statistical uncertainties associated with the trajectory and attitude conditions during atmospheric entry. Strategies and current technological challenges for a human rated Entry, Descent, and Landing to the Martian surface are presented in this study.

Prabhakar Subrahmanyam↗

Probabilistic Fracture Mechanics and Optimum Fracture Control Analytical Procedures for a Reusable Solid Rocket Motor Case

A methodology for the reliability analysis of a reusable solid rocket motor case is discussed. The analysis is based on probabilistic fracture mechanics and probability distribution for initial flaw sizes. The developed reliability analysis is used to select the structural design variables of the solid rocket motor case on the basis of minimum expected cost and specified reliability bounds during the projected design life of the case. Effects of failure prevention plans such as nondestructive inspection and the material erosion between missions are also considered in the developed procedure for selection of design variables. The reliability-based procedure can be modified to consider other similar structures of reusable space vehicle systems with different failure prevention plans.

Hanagud, S.↗

Improved Hierarchical Optimization-Based Classification of Hyperspectral Images Using Shape Analysis

A new spectral-spatial method for classification of hyperspectral images is proposed. The HSegClas method is based on the integration of probabilistic classification and shape analysis within the hierarchical step-wise optimization algorithm. First, probabilistic support vector machines classification is applied. Then, at each iteration two neighboring regions with the smallest Dissimilarity Criterion (DC) are merged, and classification probabilities are recomputed. The important contribution of this work consists in estimating a DC between regions as a function of statistical, classification and geometrical (area and rectangularity) features. Experimental results are presented on a 102-band ROSIS image of the Center of Pavia, Italy. The developed approach yields more accurate classification results when compared to previously proposed methods.

Classification↗

Probabilistic micromechanics for high-temperature composites

The three-year program of research had the following technical objectives: the development of probabilistic methods for micromechanics-based constitutive and failure models, application of the probabilistic methodology in the evaluation of various composite materials and simulation of expected uncertainties in unidirectional fiber composite properties, and influence of the uncertainties in composite properties on the structural response. The first year of research was devoted to the development of probabilistic methodology for micromechanics models. The second year of research focused on the evaluation of the Chamis-Hopkins constitutive model and Aboudi constitutive model using the methodology developed in the first year of research. The third year of research was devoted to the development of probabilistic finite element analysis procedures for laminated composite plate and shell structures.

Reddy, J. N.↗

Probabilistic assessment of uncertain adaptive hybrid composites

Adaptive composite structures using actuation materials, such as piezoelectric fibers, were assessed probabilistically utilizing intraply hybrid composite mechanics in conjunction with probabilistic composite structural analysis. Uncertainties associated with the actuation material as well as the uncertainties in the regular (traditional) composite material properties were quantified and considered in the assessment. Static and buckling analyses were performed for rectangular panels with various boundary conditions and different control arrangements. The probability density functions of the structural behavior, such as maximum displacement and critical buckling load, were computationally simulated. The results of the assessment indicate that improved design and reliability can be achieved with actuation material.

Shiao, Michael C.↗

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.↗

Optimization Testbed Cometboards Extended into Stochastic Domain

COMparative Evaluation Testbed of Optimization and Analysis Routines for the Design of Structures (CometBoards) is a multidisciplinary design optimization software. It was originally developed for deterministic calculation. It has now been extended into the stochastic domain for structural design problems. For deterministic problems, CometBoards is introduced through its subproblem solution strategy as well as the approximation concept in optimization. In the stochastic domain, a design is formulated as a function of the risk or reliability. Optimum solution including the weight of a structure, is also obtained as a function of reliability. Weight versus reliability traced out an inverted-S-shaped graph. The center of the graph corresponded to 50 percent probability of success, or one failure in two samples. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure that corresponded to unity for reliability. Weight can be reduced to a small value for the most failure-prone design with a compromised reliability approaching zero. The stochastic design optimization (SDO) capability for an industrial problem was obtained by combining three codes: MSC/Nastran code was the deterministic analysis tool, fast probabilistic integrator, or the FPI module of the NESSUS software, was the probabilistic calculator, and CometBoards became the optimizer. The SDO capability requires a finite element structural model, a material model, a load model, and a design model. The stochastic optimization concept is illustrated considering an academic example and a real-life airframe component made of metallic and composite materials.

Patnaik, Surya N.↗

Topic Modeling Tool for PeTaL (Periodic Table of Life)

A topic modeling tool is constructed for the purpose of providing insights from biology to the engineer within the framework of PeTaL (Periodic Table of Life). The machine learning text mining tools–latent Dirichlet allocation (LDA) and nonnegative matrix factorization (NMF) with Kullback-Leibler (KL) divergence—are used to provide topic clusters to the user. Topic clusters are the underlying themes of a paper. For the text modeling problem, NMF-KL is the equivalent of probabilistic latent semantic analysis. Both LDA and NMF-KL are top-performing modeling tools. These tools are used to identify biological specimens relevant to the user. Various organisms solve a particular survival problem in nature differently. The topic clusters allow people without domain expertise to find these cross-topic themes in the body of documents and then branch out and examine papers whose target organisms solve the engineer’s problem. Abstracts from the Journal of Experimental Biology were used as input for the clustering tool in addition to a curated set of articles for validation. The tool is able to accept alternate input sources.

Machine learning↗

TPSAS-NF1676L-17243-DND

This presentation captures ERA Project's effort in using integrated cost-schedule-risk analysis tool, identifying and capturing explicit relationships between program funds, schedule, and discrete risks. The project team merged a myriad of cost and schedule data for timely, objective, uncertainty analysis of the ITD's budget and schedule. The project team conducted detailed schedule uncertainty analysis showing schedule activities and how their interrelationships were impacted, representing an impressive advance beyond routine Gantt charts. Furthermore, the ERA Project collected discrete risk events including their impacts to costs and/or schedule and interwove these risks into cost and schedule logic networks, providing the foundation to conduct cost and schedule analyses. The team integrated this data into the analysis model, providing probabilistic results that were then used by the ERA Project's senior management for decision-making purposes. The ERA Project management team, through technical and pathfinder expertise in integrating cost, schedule, risk, and technical content, consistently provided risk-informed recommendations to Implementing Centers and ISRP senior management which ultimately ensured the successful ARMD Key Decision Point (KDP) review of the ERA Phase 2 ITD Portfolio and increased the likelihood of achieving technical objectives within cost and schedule constraints.

Gaudy M Bezos-O'Connor↗

Quantifying Risk to Improve Medical System Design for Long Duration Artemis Missions: A Demonstration of NASA's IMPACT Tradespace Analysis Tool

BACKGROUND NASA’s human exploration spaceflight missions to the Moon and Mars present unprecedented challenges for in-mission medical care. A greater distance from Earth will mean increased mission durations, communication delays, limited to no resupply opportunities, and constraints on the evacuation of ill or injured crew. Mass, volume, and power will be limited while higher demands will be placed on the crews to manage medical events. NASA’s Moon to Mars exploration strategy outlines increasingly complex Artemis missions both in terms of duration and operations. In these more challenging deep space missions, it is important to quantitatively estimate the human system risk attributable to medical conditions and use these estimates to advance medical system design. METHODS IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a probabilistic risk assessment (PRA) and tradespace analysis tool developed by NASA to advance exploration mission medical system design. IMPACT v1.0 includes a novel evidence library baselined to exploration environments; an expanded list of 119 medical conditions; a large increase in the number of medical resources and the flexibility of their use; and the ability for rapid and iterative analysis. Medical system risk estimates include loss of crew life, consideration of the need for return to definitive care (medical evacuation), and an estimate of crew time affected due to medical conditions. A notional long duration lunar orbit and lunar surface design reference mission (DRM) was chosen with a 4-astronaut crew to mimic a foundational exploration Artemis mission. The DRM profile includes outbound transit on Orion, Gateway space station rendezvous in lunar orbit, 6 months on the Lunar surface with extravehicular activity (EVA), return rendezvous with Gateway, and transit back to Earth. RESULTS/DISCUSSION: Overall, IMPACT successfully quantified medical risk and derived an optimal medical system to support crew on a long duration lunar mission. In this DRM, the calculated loss of crew life from a medical event was 0.008 events per mission, risk of potential need for evacuation was 0.30 events per mission, and cumulative crew time affected by medical conditions was 103 days. The medical conditions that most contributed to medical risk were decompression sickness, trauma, and respiratory failure. The conditions that had the largest effects on crew performance included musculoskeletal injuries and lunar dust exposure. The IMPACT-generated medical system included resources that target the most common and highest risk conditions and performed as expected. This demonstrates the value of the IMPACT tool in medical system design for human exploration spaceflight missions.

Arian Anderson↗

Preliminary Approach to Assess the Seismic Hazard on a Lunar Site

The passive seismic network deployed on the Moon during the Apollo missions operated for eight years and allowed the observation of seismic activity. More than 12500 seismic events were registered, where 28 were classified as shallow moonquakes with moment magnitudes up to 4.1. Seismic events of this nature pose a significant risk to future long-term lunar habitats; thus, these events must be carefully studied and considered in the seismic design of these structures. This paper proposes a preliminary seismic hazard assessment imposed by shallow moonquakes. The hazard assessment is performed using the Probabilistic Seismic Hazard Analysis (PSHA) methodology, considering previous studies and theories regarding the seismic environment of the Moon. The study zone covers ~860 km2 of the Taurus-Littrow Valley, containing the Apollo 17 landing site and the Lee-Lincoln lobate scarp as the considered seismic source. The seismic hazard is quantified in terms of peak ground acceleration (PGA) and spectral acceleration (5% damped pseudo-acceleration, PSA). Seismic hazard deaggregation scenarios, Uniform Hazard Spectra (UHS) for different hazard levels, and a Conditional Mean Spectrum (CMS) for a target period of 0.2 s are obtained to quantify the seismic hazard on a specific site on the Moon. The developed seismic hazard assessment provides a preliminary approach for realistic scenarios to conduct structural designs that ensure the seismic performance of fully operational long-term lunar structures.

Moonquake↗

Probabilistic fracture mechanics and optimum fracture control of the solid rocket motor case of the shuttle

Development of a procedure for the reliability analysis of the solid rocket motor case of the space shuttle is described. The analysis is based on probabilistic fracture mechanics and consideration of a probability distribution for the initial flaw sizes. The reliability analysis can be used to select design variables, such as the thickness of the SRM case, projected design life and proof factor, on the basis of minimum expected cost and specified reliability bounds. Effects of fracture control plans such as the non-destructive inspections and the material erosion between missions can also be considered in the developed methodology for selection of design variables. The reliability-based procedure can be easily modified to consider other similar structures and different fracture control plans.

Hanagud, S.↗