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At least 1,675 records · Page 93

LDEXPT, an intelligent database system for the Composite Load Spectra project

The Composite Load Spectra project develops probabilistic models to simulate the probabilistic loads for selected components of a generic space propulsion system. Tremendous information such as engine load variables and their distributions is needed by the simulation program. An intelligent data base system was constructed and integrated with the probabilistic load simulation program to manage and maintain the knowledge base of the Composite Load Spectra project. The intelligent data base system takes care of the data retrieval and storage functions and has expert knowledge on engine load models and associated engine variables. The integration of the intelligent data base into the load simulation program achieves a smooth coupling between the numeric processing (load simulation calculation) and the symbolic processing (intelligent load information management).

Ho, H.↗

Structural reliability assessment capability in NESSUS

The principal capabilities of NESSUS (Numerical Evaluation of Stochastic Structures Under Stress), an advanced computer code developed for probabilistic structural response analysis, are reviewed, and its structural reliability assessed. The code combines flexible structural modeling tools with advanced probabilistic algorithms in order to compute probabilistic structural response and resistance, component reliability and risk, and system reliability and risk. An illustrative numerical example is presented.

Millwater, H.↗

Mapping methods for computationally efficient and accurate structural reliability

The influence of mesh coarseness in the structural reliability is evaluated. The objectives are to describe the alternatives and to demonstrate their effectiveness. The results show that special mapping methods can be developed by using: (1) deterministic structural responses from a fine (convergent) finite element mesh; (2) probabilistic distributions of structural responses from a coarse finite element mesh; (3) the relationship between the probabilistic structural responses from the coarse and fine finite element meshes; and (4) probabilistic mapping. The structural responses from different finite element meshes are highly correlated.

Shiao, Michael C.↗

Reliability based structural optimization - A simplified safety index approach

A probabilistic optimal design methodology for complex structures modelled with finite element methods is presented. The main emphasis is on developing probabilistic analysis tools suitable for optimization. An advanced second-moment method is employed to evaluate the failure probability of the performance function. The safety indices are interpolated using the information at mean and most probable failure point. The minimum weight design with an improved safety index limit is achieved by using the extended interior penalty method of optimization. Numerical examples covering beam and plate structures are presented to illustrate the design approach. The results obtained by using the proposed approach are compared with those obtained by using the existing probabilistic optimization techniques.

Reddy, Mahidhar V.↗

Quantification of uncertainties in composites

An integrated methodology is developed for computationally simulating the probabilistic composite material properties at all composite scales. The simulation requires minimum input consisting of the description of uncertainties at the lowest scale (fiber and matrix constituents) of the composite and in the fabrication process variables. The methodology allows the determination of the sensitivity of the composite material behavior to all the relevant primitive variables. This information is crucial for reducing the undesirable scatter in composite behavior at its macro scale by reducing the uncertainties in the most influential primitive variables at the micro scale. The methodology is computationally efficient. The computational time required by the methodology described herein is an order of magnitude less than that for Monte Carlo Simulation. The methodology has been implemented into the computer code PICAN (Probabilistic Integrated Composite ANalyzer). The accuracy and efficiency of the methodology/code are demonstrated by simulating the uncertainties in the heat-transfer, thermal, and mechanical properties of a typical laminate and comparing the results with the Monte Carlo simulation method and experimental data. The important observation is that the computational simulation for probabilistic composite mechanics has sufficient flexibility to capture the observed scatter in composite properties.

Liaw, D. G.↗

Quantification of uncertainties in the performance of smart composite structures

A composite wing with spars, bulkheads, and built-in control devices is evaluated using a method for the probabilistic assessment of smart composite structures. Structural responses (such as change in angle of attack, vertical displacements, and stresses in regular plies with traditional materials and in control plies with mixed traditional and actuation materials) are probabilistically assessed to quantify their respective scatter. Probabilistic sensitivity factors are computed to identify those parameters that have a significant influence on a specific structural response. Results show that the uncertainties in the responses of smart composite structures can be quantified. Responses such as structural deformation, ply stresses, frequencies, and buckling loads in the presence of defects can be reliably controlled to satisfy specified design requirements.

Shiao, Michael C.↗

Interdisciplinary technology

The 'computational test-cell' will enable the incorporation of new methodologies, such as concurrent engineering and probabilistic methods, into the propulsion design process. This will provide the capability to conduct credible, interdisciplinary analyses of new propulsion concepts and designs. Probabilistic methods can be used as the basis for reliability-based design. Recently methods have been devised that provide the capability of simulating the performance of propulsion systems at several levels of resolution. These methods make it possible to quantify uncertainty and to establish confidence bounds for the calculated values. The introduction of reliability-based design methodology along with probabilistic analyses will provide a tool to reduce the design space for new systems and to reduce our dependence on hardware testing for proof-of-concept and system integration demonstrations. The resulting simulations will reduce the need for testing and identify potential operational problems early in the design process. This capability will make it possible to compute the expected performance, stability, reliability, and life of propulsion components, subsystems, and systems at design and off-design conditions, to bring life cycle cost trade-offs early into the design process and to determine optimum designs to satisfy specified mission requirements.

Nichols, Lester D.↗

Composite Load Spectra for Select Space Propulsion Structural Components

Generic load models are described with multiple levels of progressive sophistication to simulate the composite (combined) load spectra (CLS) that are induced in space propulsion system components, representative of Space Shuttle Main Engines (SSME), such as transfer ducts, turbine blades and liquid oxygen (LOX) posts. These generic (coupled) models combine the deterministic models for composite load dynamic, acoustic, high-pressure and high rotational speed, etc., load simulation using statistically varying coefficients. These coefficients are then determined using advanced probabilistic simulation methods with and without strategically selected experimental data. The entire simulation process is included in a CLS computer code. Applications of the computer code to various components in conjunction with the PSAM (Probabilistic Structural Analysis Method) to perform probabilistic load evaluation and life prediction evaluations are also described to illustrate the effectiveness of the coupled model approach.

Ho, Hing W.↗

Structural Probability Concepts Adapted to Electrical Engineering

Through the use of equivalent variable analogies, the authors demonstrate how an electrical subsystem can be modeled by an equivalent structural subsystem. This allows the electrical subsystem to be probabilistically analyzed by using available structural reliability computer codes such as NESSUS. With the ability to analyze the electrical subsystem probabilistically, we can evaluate the reliability of systems that include both structural and electrical subsystems. Common examples of such systems are a structural subsystem integrated with a health-monitoring subsystem, and smart structures. Since these systems have electrical subsystems that directly affect the operation of the overall system, probabilistically analyzing them could lead to improved reliability and reduced costs. The direct effect of the electrical subsystem on the structural subsystem is of secondary order and is not considered in the scope of this work.

Steinberg, Eric P.↗

Optimization of Adaptive Intraply Hybrid Fiber Composites with Reliability Considerations

The reliability with bounded distribution parameters (mean, standard deviation) was maximized and the reliability-based cost was minimized for adaptive intra-ply hybrid fiber composites by using a probabilistic method. The probabilistic method accounts for all naturally occurring uncertainties including those in constituent material properties, fabrication variables, structure geometry, and control-related parameters. Probabilistic sensitivity factors were computed and used in the optimization procedures. For actuated change in the angle of attack of an airfoil-like composite shell structure with an adaptive torque plate, the reliability was maximized to 0.9999 probability, with constraints on the mean and standard deviation of the actuation material volume ratio (percentage of actuation composite material in a ply) and the actuation strain coefficient. The reliability-based cost was minimized for an airfoil-like composite shell structure with an adaptive skin and a mean actuation material volume ratio as the design parameter. At a O.9-mean actuation material volume ratio, the minimum cost was obtained.

Shiao, Michael C.↗

A Reliable Earth Return System for Safe Recovery of Mars Samples

The objective of a Mars sample return mission is to bring selected Mars surface materials to Earth. Numerous approaches for the Earth-return segment have been analyzed including propulsive or aerocapture return to low-Earth orbit followed by Space Shuttle rendezvous and direct entry. Of these approaches, ballistic entry of a small capsule terminating in a ground landing has been shown to be the lowest risk strategy. Over the past two years, significant work has been performed towards development of a robust direct entry vehicle for Mars sample return. In June 1999, the NASA Planetary Protection Officer provided initial guidance to the former Mars Sample Return Project. The sample return phase of the mission was assigned a restricted Earth return planetary protection classification. The draft mission requirement states that the total mean probability of release of unsterilized Mars material into the Earth;s biosphere must be less than 1.0E-06 (1 in a million). This strict requirement drives the approach and design of the Earth return system. To meet this requirement, selection of the Earth return strategy and development of the Earth return system must be guided by risk, not performance, based decisions. An initial Probabilistic Risk Assessment (PRA) was performed to address the direct entry Earth return system containment assurance reliability and to identify high-risk elements of this system. The results of this PRA identified risk elements that include thermal protection system performance during entry, spin-eject orientation and aerodynamic stability during entry, structural integrity under atmospheric deceleration and impact loads, and tracking/recovery of this system. This initial probabilistic risk quantification demonstrates that, with the proper development program, a prototypical direct entry design can satisfy the containment assurance reliability requirement. Through the current Mars Sample Return Advanced Technology Development effort, an extensive design, analysis, and test program is presently proceeding with the aim of reducing the containment assurance risk of this system. This technology development effort, guided by a continuing PRA, focuses on key risk areas of a direct entry Earth return system including: the thermal protection system, impact dynamics, structural performance, aerodynamic stability, and ground recovery. This development program will culminate in a system validation flight test, 1-2 years prior to launch of the flight system. This flight test would include the launch, entry, and recovery of a full-scale Earth return system, as a scientific validation of the key risk elements to verify nominal design performance. The results of the initial PRA suggested several dominant failure sequences that can be validated in a flight test. These include: demonstrating the thermal protection system reliability and performance during entry, demonstrating the spin-eject orientation and aero-dynamic stability during entry, demonstrating the structural integrity under atmospheric deceleration and impact loads, and demonstrating tracking and recovery of the Earth return system. This single test will directly address over 50% of the total containment assurance risk elements. This presentation will begin by presenting the relative risk of various Earth return strategies. The results of the initial probabilistic risk assessment will be presented followed by a discussion of the development accomplishments and plans for demonstration of a highly reliable direct entry Earth return system.

Braun, R.↗

Interrelation Between Safety Factors and Reliability

An evaluation was performed to establish relationships between safety factors and reliability relationships. Results obtained show that the use of the safety factor is not contradictory to the employment of the probabilistic methods. In many cases the safety factors can be directly expressed by the required reliability levels. However, there is a major difference that must be emphasized: whereas the safety factors are allocated in an ad hoc manner, the probabilistic approach offers a unified mathematical framework. The establishment of the interrelation between the concepts opens an avenue to specify safety factors based on reliability. In cases where there are several forms of failure, then the allocation of safety factors should he based on having the same reliability associated with each failure mode. This immediately suggests that by the probabilistic methods the existing over-design or under-design can be eliminated. The report includes three parts: Part 1-Random Actual Stress and Deterministic Yield Stress; Part 2-Deterministic Actual Stress and Random Yield Stress; Part 3-Both Actual Stress and Yield Stress Are Random.

Elishakoff, Isaac↗

Dynamic Stability of Uncertain Laminated Beams Under Subtangential Loads

Because of the inherent complexity of fiber-reinforced laminated composites, it can be challenging to manufacture composite structures according to their exact design specifications, resulting in unwanted material and geometric uncertainties. In this research, we focus on the deterministic and probabilistic stability analysis of laminated structures subject to subtangential loading, a combination of conservative and nonconservative tangential loads, using the dynamic criterion. Thus a shear-deformable laminated beam element, including warping effects, is derived to study the deterministic and probabilistic response of laminated beams. This twenty-one degrees of freedom element can be used for solving both static and dynamic problems. In the first-order shear deformable model used here we have employed a more accurate method to obtain the transverse shear correction factor. The dynamic version of the principle of virtual work for laminated composites is expressed in its nondimensional form and the element tangent stiffness and mass matrices are obtained using analytical integration The stability is studied by giving the structure a small disturbance about an equilibrium configuration, and observing if the resulting response remains small. In order to study the dynamic behavior by including uncertainties into the problem, three models were developed: Exact Monte Carlo Simulation, Sensitivity Based Monte Carlo Simulation, and Probabilistic FEA. These methods were integrated into the developed finite element analysis. Also, perturbation and sensitivity analysis have been used to study nonconservative problems, as well as to study the stability analysis, using the dynamic criterion.

Goyal, Vijay K.↗

System Level Uncertainty Assessment for Collaborative RLV Design

A collaborative design process utilizing Probabilistic Data Assessment (PDA) is showcased. Given the limitation of financial resources by both the government and industry, strategic decision makers need more than just traditional point designs, they need to be aware of the likelihood of these future designs to meet their objectives. This uncertainty, an ever-present character in the design process, can be embraced through a probabilistic design environment. A conceptual design process is presented that encapsulates the major engineering disciplines for a Third Generation Reusable Launch Vehicle (RLV). Toolsets consist of aerospace industry standard tools in disciplines such as trajectory, propulsion, mass properties, cost, operations, safety, and economics. Variations of the design process are presented that use different fidelities of tools. The disciplinary engineering models are used in a collaborative engineering framework utilizing Phoenix Integration's ModelCenter and AnalysisServer environment. These tools allow the designer to join disparate models and simulations together in a unified environment wherein each discipline can interact with any other discipline. The design process also uses probabilistic methods to generate the system level output metrics of interest for a RLV conceptual design. The specific system being examined is the Advanced Concept Rocket Engine 92 (ACRE-92) RLV. Previous experience and knowledge (in terms of input uncertainty distributions from experts and modeling and simulation codes) can be coupled with Monte Carlo processes to best predict the chances of program success.

Charania, A. C.↗

UNIPASS for AvSP? A Broader View

UNIPASS is a general-purpose probabilistic computer program consisting of three major modules, including preprocessor, solver and postprocessor. UNIPASS contains a user-friendly Graphical User Interface (GUI), numerous state-of-the-art probabilistic analysis techniques, a large library of statistical distributions and a function module with a large library of support functions that can easily define any complex limit-state function in a scripting FORTRAN-like syntax format. Its inverse probability analysis and sensitivities analysis capabilities make it a powerful design aid in any product cycle. Its precise numerical analysis engine is accurate enough to push the failure probabilities of a design to well below 10 (exp -50). UNIPASS is equipped with advanced artificial intelligence that is designed to handle systems with an essentially unlimited number of random variables with ease and efficiency. Its modular arrangement allows you to tailor an analysis to the desired level of accuracy and efficiency. The depth and comprehensiveness of UNIPASS are built upon the decades of experience and expertise of industry leaders including Boeing Aircraft, NASA and the DoD. Its rich content also makes UNIPASS a valuable instructional tool for random processes and probabilistic mechanics. The topics include: 1) Reliability in AvSP; 2) Role of UNIPASS in AvSP; and 3) Examples. This paper is in viewgraph form.

Wu, N. Eva↗

Integrated Technology Assessment Center (ITAC) Update

The Integrated Technology Assessment Center (ITAC) has developed a flexible systems analysis framework to identify long-term technology needs, quantify payoffs for technology investments, and assess the progress of ASTP-sponsored technology programs in the hypersonics area. For this, ITAC has assembled an experienced team representing a broad sector of the aerospace community and developed a systematic assessment process complete with supporting tools. Concepts for transportation systems are selected based on relevance to the ASTP and integrated concept models (ICM) of these concepts are developed. Key technologies of interest are identified and projections are made of their characteristics with respect to their impacts on key aspects of the specific concepts of interest. Both the models and technology projections are then fed into the ITAC's probabilistic systems analysis framework in ModelCenter. This framework permits rapid sensitivity analysis, single point design assessment, and a full probabilistic assessment of each concept with respect to both embedded and enhancing technologies. Probabilistic outputs are weighed against metrics of interest to ASTP using a multivariate decision making process to provide inputs for technology prioritization within the ASTP. ITAC program is currently finishing the assessment of a two-stage-to-orbit (TSTO), rocket-based combined cycle (RBCC) concept and a TSTO turbine-based combined cycle (TBCC) concept developed by the team with inputs from NASA. A baseline all rocket TSTO concept is also being developed for comparison. Boeing has recently submitted a performance model for their Flexible Aerospace System Solution for Tomorrow (FASST) concept and the ISAT program will provide inputs for a single-stage-to-orbit (SSTO) TBCC based concept in the near-term. Both of these latter concepts will be analyzed within the ITAC framework over the summer. This paper provides a status update of the ITAC program.

Taylor, J. L.↗

Scatter in Carbon/Silicon Carbide (C/SiC) Composites Quantified

Carbon-fiber-reinforced silicon carbide matrix (C/SiC) composites processed by chemical vapor infiltration are candidate materials for aerospace thermal structures. Carbon fibers can retain properties at very high temperatures, but they are known to have poor oxidation resistance in adverse, high-temperature environments. Nevertheless, the combination of CVI-SiC matrix with higher stiffness and oxidation resistance, the interfacial coating, and additional surface-seal coating provides the necessary protection to the carbon fibers, and makes the material viable for high-temperature space applications operating under harsh environments. Furthermore, C/SiC composites, like other ceramic matrix composites (CMCs), exhibit graceful non-catastrophic failure because of various inherent energy dissipating mechanisms. The material exhibits nonlinearity in deformation even at very low stress levels. This is the result of the severe matrix microcracking present in the as processed composite because of large differences between the coefficients of thermal expansion of the fiber and the matrix. Utilization of these advanced composites in next generation space vehicles will require innovative structural configurations, updated materials, and refined analyses. Structural safety issues for these vehicles are in direct competition with performance and cost. One would have to quantify the uncertainties associated with the design using formal probabilistic methods. Specifically four fundamental aspects on which analyses are based-- (1) loading conditions, (2) material behavior, (3) geometrical configurations, and (4) structural connections between the composite components and baseline structure--are stochastic in nature. A direct way to formally account for uncertainties is to develop probabilistic structural analysis methods where all participating variables are described by appropriate probability density functions. The present work, however, focuses on analyzing the stochastic material behavior of these advanced composites using formal probabilistic analysis methods. Often, some of the desirable property characteristics that allow composites to offer advantages over conventional structural materials (like tailoring of composite properties) and the complexity are in fact responsible for their greater statistical variability and the requirements for more characterization tests. Composite properties are anisotropic as well, having different properties in different directions. This means that characterization of a property such as stiffness--which will vary greatly depending on the orientation of the fiber relative to the direction of the testing--must be repeated for several different directions and loading conditions. The fabrication process for composites also introduces statistical variations in properties and geometry. A composite part is produced in a number of steps, each of which introduces statistical variability. The matrix is usually produced from a combination of raw materials; and the fiber, which has its own set of properties, is often coated or surface treated, introducing yet another source of variability.

Murthy, Pappu L. N.↗

Science Goals in Radiation Protection for Exploration

Space radiation presents major challenges to future missions to the Earth s moon or Mars. Health risks of concern include cancer, degenerative and performance risks to the central nervous system, heart and lens, and the acute radiation syndromes. The galactic cosmic rays (GCR) contain high energy and charge (HZE) nuclei, which have been shown to cause qualitatively distinct biological damage compared to terresterial radiation, such as X-rays or gamma-rays, causing risk estimates to be highly uncertain. The biological effects of solar particle events (SPE) are similar to terresterial radiation except for their biological dose-rate modifiers; however the onset and size of SPEs are difficult to predict. The high energies of GCR reduce the effectiveness of shielding, while SPE s can be shielded however the current gap in radiobiological knowledge hinders optimization. Methods used to project risks on Earth must be modified because of the large uncertainties in projecting health risks from space radiation, and thus impact mission requirements and costs. We describe NASA s unique approach to radiation safety that applies probabilistic risk assessments and uncertainty based criteria within the occupational health program for astronauts and to mission design. The two terrestrial criteria of a point estimate of maximum acceptable level of risk and application of the principle of As Low As Reasonably Achievable (ALARA) are supplemented by a third requirement that protects against risk projection uncertainties using the upper 95% confidence level (CL) in radiation risk projection models. Exploration science goals in radiation protection are centered on ground-based research to achieve the necessary biological knowledge, and in the development of new technologies to improve SPE monitoring and optimize shielding. Radiobiology research is centered on a ground based program investigating the radiobiology of high-energy protons and HZE nuclei at the NASA Space Radiation Laboratory (NSRL) located at DoE s Brookhaven National Laboratory in Upton, NY. We describe recent NSRL results that are closing the knowledge gap in HZE radiobiology and improving exploration risk estimates. Linking probabilistic risk assessment to research goals makes it possible to express risk management objectives in terms of quantitative metrics, which include the number of days in space without exceeding a given risk level within well defined confidence limits, and probabilistic assessments of the effectiveness of design trade spaces such as material type, mass, solar cycle, crew selection criteria, and biological countermeasures. New research in SPE alert and risk assessment, individual radiation sensitivity, and biological countermeasure development are described.

Cucinotta, Francs A.↗