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At least 217 records · Page 12

Probabilistic simulation of uncertainties in thermal structures

Development of probabilistic structural analysis methods for hot structures is a major activity at Lewis Research Center. It consists of five program elements: (1) probabilistic loads; (2) probabilistic finite element analysis; (3) probabilistic material behavior; (4) assessment of reliability and risk; and (5) probabilistic structural performance evaluation. Recent progress includes: (1) quantification of the effects of uncertainties for several variables on high pressure fuel turbopump (HPFT) blade temperature, pressure, and torque of the Space Shuttle Main Engine (SSME); (2) the evaluation of the cumulative distribution function for various structural response variables based on assumed uncertainties in primitive structural variables; (3) evaluation of the failure probability; (4) reliability and risk-cost assessment, and (5) an outline of an emerging approach for eventual hot structures certification. Collectively, the results demonstrate that the structural durability/reliability of hot structural components can be effectively evaluated in a formal probabilistic framework. In addition, the approach can be readily extended to computationally simulate certification of hot structures for aerospace environments.

Chamis, Christos C.↗

Probabilistic simulation of uncertainties in thermal structures

Development of probabilistic structural analysis methods for hot structures is a major activity at NASA-Lewis, and consists of five program elements: (1) probabilistic loads, (2) probabilistic finite element analysis, (3) probabilistic material behavior, (4) assessment of reliability and risk, and (5) probabilistic structural performance evaluation. Attention is given to quantification of the effects of uncertainties for several variables on High Pressure Fuel Turbopump blade temperature, pressure, and torque of the Space Shuttle Main Engine; the evaluation of the cumulative distribution function for various structural response variables based on assumed uncertainties in primitive structural variables; evaluation of the failure probability; reliability and risk-cost assessment; and an outline of an emerging approach for eventual hot structures certification. Collectively, the results demonstrate that the structural durability/reliability of hot structural components can be effectively evaluated in a formal probabilistic framework. In addition, the approach can be readily extended to computationally simulate certification of hot structures for aerospace environments.

Chamis, C. C.↗

A probabilistic Hu-Washizu variational principle

A Probabilistic Hu-Washizu Variational Principle (PHWVP) for the Probabilistic Finite Element Method (PFEM) is presented. This formulation is developed for both linear and nonlinear elasticity. The PHWVP allows incorporation of the probabilistic distributions for the constitutive law, compatibility condition, equilibrium, domain and boundary conditions into the PFEM. Thus, a complete probabilistic analysis can be performed where all aspects of the problem are treated as random variables and/or fields. The Hu-Washizu variational formulation is available in many conventional finite element codes thereby enabling the straightforward inclusion of the probabilistic features into present codes.

Liu, W. K.↗

NASA Ground-based Layered Pressure Vessels Materials Report

A significant portion of Layered Pressure Vessels (LPVs) manufactured for NASA in the 1950s and ’60s are of non-code construction. These vessels were constructed to the standards of individual manufacturers rather than an industry or consensus standard and often contain legacy or proprietary materials, which have poor or no characterization. Obtaining correct material properties is the first step in assuring vessel safety and predicting life and critical failure modes before they happen. This report details the efforts of the LPV Project related to material properties and characterization. The goal in testing materials from deconstructed vessels was to provide material characterization utilizing modern test methods that would give a strong probabilistic base as an option for future analysis. ASTM E1820, Standard Test Method for Measurement of Fracture Toughness was used for fracture toughness; ASTM E1921, Standard Test Method for Determination of Reference Temperature, T0, for Ferritic Steels in the Transition Range for transition temperature; and ASTM E647, Standard Test Method for Measurement of Fatigue Crack Growth Rates for fatigue crack growth. Particular focus was placed on determination of transition temperature through evaluation of the T0 reference temperature in accordance with ASTM E1921. Transition temperature testing allows for a probabilistic analysis of vessel materials that may be operating at temperatures below the transition from ductile tearing to brittle cleavage failure. This test method was not available at the time of construction and has proved invaluable to the characterization of older ferritic steels. The values reported are specific to the largest body of materials found in the current NASA fleet, but do not claim to be all inclusive. As demonstrated in this report, some materials contain extreme lot-to-lot variability. In some cases, this can be comfortably bounded by worst case probabilistic methods, however it is always recommended that vessel specific data be collected in as much depth as possible to ensure correct assumptions and avoid unduly restricting vessel usage.

Layered Pressure Vessel↗

Structural Deterministic Safety Factors Selection Criteria and Verification

Though current deterministic safety factors are arbitrarily and unaccountably specified, its ratio is rooted in resistive and applied stress probability distributions. This study approached the deterministic method from a probabilistic concept leading to a more systematic and coherent philosophy and criterion for designing more uniform and reliable high-performance structures. The deterministic method was noted to consist of three safety factors: a standard deviation multiplier of the applied stress distribution; a K-factor for the A- or B-basis material ultimate stress; and the conventional safety factor to ensure that the applied stress does not operate in the inelastic zone of metallic materials. The conventional safety factor is specifically defined as the ratio of ultimate-to-yield stresses. A deterministic safety index of the combined safety factors was derived from which the corresponding reliability proved the deterministic method is not reliability sensitive. The bases for selecting safety factors are presented and verification requirements are discussed. The suggested deterministic approach is applicable to all NASA, DOD, and commercial high-performance structures under static stresses.

Verderaime, V.↗

A probabilistic approach to the evaluation of fatigue damage in a space propulsion system injector element

The fatigue damage of a space propulsion system component is computed using probabilistic structural analysis methods. The analysis takes into account the variations in static and dynamic loads, the uncertainty in structural damping, and the scatter in material fatigue resistance. The key elements of the probabilistic approach include: (1) a numerical engine model for describing the global component interface loads consistent with engine balance, (2) models for computing the local mode boundary conditions on the component, (3) a static structural analysis model that captures the strains at a damage critical location as a function of engine performance variables, (4) a finite element model for assessment of the random amplitude stress response due to random base and pressure excitations with uncertain power and correlation length, and (5) advanced first order reliability methods for computing the probabilities associated with the fatigue damage.

Rajagopal, K. R.↗

Probabilistic Risk Analysis and Margin Process for a Flexible Thermal Protection System

Atmospheric entry vehicle thermal protection systems are margined due to the uncertainties that exist in entry aeroheating environments and the thermal response of the materials and structures. Entry vehicle thermal protections systems are traditionally over-margined for the heat loads that are experienced along the entry trajectory by designing to survive stacked worst-case scenarios. Additionally, the conventional heat shield design and margin process offers very little insight into the risk of over-temperature during flight and the corresponding reliability of the heat shield performance. A probabilistic margin process can be used to appropriately margin the thermal protection system based on rigorously calculated risk of failure. This probabilistic margin process allows engineers to make informed aeroshell design, entry-trajectory design, and risk trades while preventing excessive margin from being applied. This study presents the methods of the probabilistic margin process and how the uncertainty analysis is used to determine the reliability of the entry vehicle thermal protection system and associated risks of failure.

Tobin, Steven A.↗

Probabilistic structural analysis for space propulsion system components

Probabilistic design and analysis methods for the achievement of greater reliability in structural systems are especially useful in those cases where the structure operates in such severe environments as that of the Space Shuttle. Attention is presently given to the development status of a NASA-sponsored program for probabilistic structural analysis methods applicable to current and future reusable space propulsion systems. Methodologies for the assessment of structural response by means of integrated finite element and probabilistic analysis techniques are discussed, with illustrative examples.

Burnside, O. H.↗

Probabilistic load model development and validation for composite load spectra for select space propulsion engines

A major task of the program to develop an expert system to predict the loads on selected components of a generic space propulsion engine is the design development and application of a probabilitic loads model. This model is being developed in order to account for the random nature of the loads and assess the variable load ranges' effect on the engine performance. A probabilistic model has been developed. The model is based primarily on simulation methods, but also has a Gaussian algebra method (if all variables are near normal), a fast probability integrator routine (for the calculation of low probability events), and a separate, stand alone program for performing barrier crossing calculations. Each of these probabilistic methods has been verified with theoretical calculations using assumed distributional forms.

Kurth, R.↗

Probabilistic and Possibilistic Analyses of the Strength of a Bonded Joint

The effects of uncertainties on the predicted strength of a single lap shear joint are examined. Probabilistic and possibilistic methods are used to account for uncertainties. A total of ten variables are assumed to be random, with normal distributions. Both Monte Carlo Simulation and the First Order Reliability Method are used to determine the probability of failure. Triangular membership functions with upper and lower bounds located at plus or minus three standard deviations are used to model uncertainty in the possibilistic analysis. The alpha cut (or vertex) method is used to evaluate the possibility of failure. Linear and geometrically nonlinear finite element analyses are used calculate the response of the joint; fracture in the adhesive and material strength failure in the strap are used to evaluate its strength. Although probabilistic and possibilistic analyses provide significantly more information than do conventional deterministic analyses, they are computationally expensive. A novel scaling approach is developed and used to substantially reduce the computational cost of the probabilistic and possibilistic analyses. The possibilistic approach for treating uncertainties appears to be viable during the conceptual and preliminary design stages when limited data are available and high accuracies are not needed. However, this viability is mixed with several cautions that are discussed herein.

Stroud, W. Jefferson↗

Methods for Determining Subsets of High Impact, Probabilistically Dependent Medical Conditions Represented in a Directed Graph

One of the longest standing questions in network theory is how a component influences other parts in the system, and how that role is affected when restricting the navigation through the network. The Katz score, one of many centrality measures created for this purpose, takes into account all possible walks through the network, penalizing each additional step in a walk by a scalar called the Katz parameter. This centrality measure often covers an infinite number of walks with infinite length. In this paper we identify the maximum path length which has influence on the Katz score. We ultimately provide guidance when deciding which Katz parameter to use as it depends on the path length of interest. We show how changing the Katz parameter affects the ranking of the vertices in some synthetic graphs as well as NASA's expert informed network of medical dependencies called the Susceptibility Inference Network (SIN).

Hunter Rehm↗

Best Merge Region Growing with Integrated Probabilistic Classification for Hyperspectral Imagery

A new method for spectral-spatial classification of hyperspectral images is proposed. The method is based on the integration of probabilistic classification within the hierarchical best merge region growing algorithm. For this purpose, preliminary probabilistic support vector machines classification is performed. Then, hierarchical step-wise optimization algorithm is applied, by iteratively merging regions with the smallest Dissimilarity Criterion (DC). The main novelty of this method consists in defining a DC between regions as a function of region statistical and geometrical features along with classification probabilities. Experimental results are presented on a 200-band AVIRIS image of the Northwestern Indiana s vegetation area and compared with those obtained by recently proposed spectral-spatial classification techniques. The proposed method improves classification accuracies when compared to other classification approaches.

Tarabalka, Yuliya↗

Probalistic Finite Elements (PFEM) structural dynamics and fracture mechanics

The purpose of this work is to develop computationally efficient methodologies for assessing the effects of randomness in loads, material properties, and other aspects of a problem by a finite element analysis. The resulting group of methods is called probabilistic finite elements (PFEM). The overall objective of this work is to develop methodologies whereby the lifetime of a component can be predicted, accounting for the variability in the material and geometry of the component, the loads, and other aspects of the environment; and the range of response expected in a particular scenario can be presented to the analyst in addition to the response itself. Emphasis has been placed on methods which are not statistical in character; that is, they do not involve Monte Carlo simulations. The reason for this choice of direction is that Monte Carlo simulations of complex nonlinear response require a tremendous amount of computation. The focus of efforts so far has been on nonlinear structural dynamics. However, in the continuation of this project, emphasis will be shifted to probabilistic fracture mechanics so that the effect of randomness in crack geometry and material properties can be studied interactively with the effect of random load and environment.

Liu, Wing-Kam↗

Design of Oil-Lubricated Machine for Life and Reliability

In the post-World War II era, the major technology drivers for improving the life, reliability, and performance of rolling-element bearings and gears have been the jet engine and the helicopter. By the late 1950s, most of the materials used for bearings and gears in the aerospace industry had been introduced into use. By the early 1960s, the life of most steels was increased over that experienced in the early 1940s, primarily by the introduction of vacuum degassing and vacuum melting processes in the late 1950s. The development of elastohydrodynamic (EHD) theory showed that most rolling bearings and gears have a thin film separating the contacting bodies during motion and it is that film which affects their lives. Computer programs modeling bearing and gear dynamics that incorporate probabilistic life prediction methods and EHD theory enable optimization of rotating machinery based on life and reliability. With improved manufacturing and processing, the potential improvement in bearing and gear life can be as much as 80 times that attainable in the early 1950s. The work presented summarizes the use of laboratory fatigue data for bearings and gears coupled with probabilistic life prediction and EHD theories to predict the life and reliability of a commercial turboprop gearbox. The resulting predictions are compared with field data.

Zaretsky, Erwin V.↗

Dynamic Probabilistic Instability of Composite Structures

A computationally effective method is described to evaluate the non-deterministic dynamic instability (probabilistic dynamic buckling) of thin composite shells. The method is a judicious combination of available computer codes for finite element, composite mechanics and probabilistic structural analysis. The solution method is incrementally updated Lagrangian. It is illustrated by applying it to thin composite cylindrical shell subjected to dynamic loads. Both deterministic and probabilistic buckling loads are evaluated to demonstrate the effectiveness of the method. A universal plot is obtained for the specific shell that can be used to approximate buckling loads for different load rates and different probability levels. Results from this plot show that the faster the rate, the higher the buckling load and the shorter the time. The lower the probability, the lower is the buckling load for a specific time. Probabilistic sensitivity results show that the ply thickness, the fiber volume ratio and the fiber longitudinal modulus, dynamic load and loading rate are the dominant uncertainties in that order.

Chamis, Christos C.↗

Fatigue Reliability of Gas Turbine Engine Structures

The results of an investigation are described for fatigue reliability in engine structures. The description consists of two parts. Part 1 is for method development. Part 2 is a specific case study. In Part 1, the essential concepts and practical approaches to damage tolerance design in the gas turbine industry are summarized. These have evolved over the years in response to flight safety certification requirements. The effect of Non-Destructive Evaluation (NDE) methods on these methods is also reviewed. Assessment methods based on probabilistic fracture mechanics, with regard to both crack initiation and crack growth, are outlined. Limit state modeling techniques from structural reliability theory are shown to be appropriate for application to this problem, for both individual failure mode and system-level assessment. In Part 2, the results of a case study for the high pressure turbine of a turboprop engine are described. The response surface approach is used to construct a fatigue performance function. This performance function is used with the First Order Reliability Method (FORM) to determine the probability of failure and the sensitivity of the fatigue life to the engine parameters for the first stage disk rim of the two stage turbine. A hybrid combination of regression and Monte Carlo simulation is to use incorporate time dependent random variables. System reliability is used to determine the system probability of failure, and the sensitivity of the system fatigue life to the engine parameters of the high pressure turbine. 'ne variation in the primary hot gas and secondary cooling air, the uncertainty of the complex mission loading, and the scatter in the material data are considered.

Cruse, Thomas A.↗

A Prognostic Launch Vehicle Probability of Failure Assessment Methodology for Conceptual Systems Predicated on Human Causal Factors

Lessons learned from past failures of launch vehicle developments and operations were used to create a new method to predict the probability of failure of conceptual systems. Existing methods such as Probabilistic Risk Assessments and Human Risk Assessments were considered but found to be too cumbersome for this type of system-wide application for yet-to-be-flown vehicles. The basis for this methodology were historic databases of past failures, where it was determined that various faulty human-interactions were the predominant root causes of failure rather than deficient component reliabilities evaluated through statistical analysis. This methodology contains an expert scoring part which can be used in either a qualitative or a quantitative mode. The method produces two products: a numerical score of the probability of failure and guidance to program management on critical areas in need of increased focus to improve the probability of success. In order to evaluate the effectiveness of this new method, data from a concluded vehicle program (USAF's Titan IV with the Centaur G-Prime upper stage) was used as a test case. The theoretical vs. actual probability of failure was found to be 4.46% vs. 6.67% respectively. Recommendations are made for future applications of this method to ongoing launch vehicle development programs.

Launch Vehicle↗