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At least 109 records · Page 6

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion systems components

Summarized here is the technical effort and computer code developed during the five year duration of the program for probabilistic structural analysis methods. The summary includes a brief description of the computer code manuals and a detailed description of code validation demonstration cases for random vibrations of a discharge duct, probabilistic material nonlinearities of a liquid oxygen post, and probabilistic buckling of a transfer tube liner.

Source record↗

Probabilistic progressive buckling of trusses

A three-bay, space, cantilever truss is probabilistically evaluated to describe progressive buckling and truss collapse in view of the numerous uncertainties associated with the structural, material, and load variables (primitive variables) that describe the truss. Initially, the truss is deterministically analyzed for member forces, and member(s) in which the axial force exceeds the Euler buckling load are identified. These member(s) are then discretized with several intermediate nodes and a probabilistic buckling analysis is performed on the truss to obtain its probabilistic buckling loads and respective mode shapes. Furthermore, sensitivities associated with the uncertainties in the primitive variables are investigated, margin of safety values for the truss are determined, and truss end node displacements are noted. These steps are repeated by sequentially removing the buckled member(s) until onset of truss collapse is reached. Results show that this procedure yields an optimum truss configuration for a given loading and for a specified reliability.

Pai, Shantaram S.↗

Data analysis using scale-space filtering and Bayesian probabilistic reasoning

This paper describes a program for analysis of output curves from Differential Thermal Analyzer (DTA). The program first extracts probabilistic qualitative features from a DTA curve of a soil sample, and then uses Bayesian probabilistic reasoning to infer the mineral in the soil. The qualifier module employs a simple and efficient extension of scale-space filtering suitable for handling DTA data. We have observed that points can vanish from contours in the scale-space image when filtering operations are not highly accurate. To handle the problem of vanishing points, perceptual organizations heuristics are used to group the points into lines. Next, these lines are grouped into contours by using additional heuristics. Probabilities are associated with these contours using domain-specific correlations. A Bayes tree classifier processes probabilistic features to infer the presence of different minerals in the soil. Experiments show that the algorithm that uses domain-specific correlation to infer qualitative features outperforms a domain-independent algorithm that does not.

Kulkarni, Deepak↗

Probabilistic assessment of space trusses subjected to combined mechanical and thermal loads

A three-bay, space, cantilever truss is probabilistically evaluated to quantify the range of uncertainties of buckling loads and member forces due to nonuniform thermal loads, applied loads and moments (mechanical loads), and combination of both. The truss members are assumed to be made from Aluminum tubes or high modulus graphite-fiber/intermediate modulus epoxy-matrix composite tubes. Cumulative distribution function results show that certain combinations of thermal loads with mechanical loads reduce the probabilistic buckling loads and increase the magnitude of the member axial forces for the aluminum truss. The same trend is observed for the composite truss as well, as however, the thermal effects on the probabilistic buckling loads and member axial forces are not as substantial as that for an aluminum truss. This can be attributed to the large differences in the values of coefficient of thermal expansion. Finally, the sensitivities associated with the uncertainties in the structural, material, and load variables (primitive variables) are investigated. They show that buckling loads and member axial forces are most sensitive to the uncertainties in spacial (geometry) variables.

Pai, Shantaram S.↗

Probabilistic progressive buckling of trusses

A three-bay, space, cantilever truss is probabilistically evaluated to describe progressive buckling and truss collapse in view of the numerous uncertainties associated with the structural, material, and load variables (primitive variables) that describe the truss. Initially, the truss is deterministically analyzed for member forces, and member(s) in which the axial force exceeds the Euler buckling load are identified. These member(s) are then discretized with several intermediate nodes and a probabilistic buckling analysis is performed on the truss to obtain its probabilistic buckling loads and respective mode shapes. Furthermore, sensitivities associated with the uncertainties in the primitive variables are investigated, margin of safety values for the truss are determined, and truss end node displacements are noted. These steps are repeated by sequentially removing the buckled member(s) until onset of truss collapse is reached. Results show that this procedure yields an optimum truss configuration for a given loading and for a specified reliability.

Pai, Shantaram S.↗

Probabilistic material degradation model for aerospace materials subjected to high temperature, mechanical and thermal fatigue, and creep

A probabilistic general material strength degradation model has been developed for structural components of aerospace propulsion systems subjected to diverse random effects. The model has been implemented in two FORTRAN programs, PROMISS (Probabilistic Material Strength Simulator) and PROMISC (Probabilistic Material Strength Calibrator). PROMISS calculates the random lifetime strength of an aerospace propulsion component due to as many as eighteen diverse random effects. Results are presented in the form of probability density functions and cumulative distribution functions of lifetime strength. PROMISC calibrates the model by calculating the values of empirical material constants.

Boyce, L.↗

Nonlinear probabilistic finite element models of laminated composite shells

A probabilistic finite element analysis procedure for laminated composite shells has been developed. A total Lagrangian finite element formulation, employing a degenerated 3-D laminated composite shell with the full Green-Lagrange strains and first-order shear deformable kinematics, forms the modeling foundation. The first-order second-moment technique for probabilistic finite element analysis of random fields is employed and results are presented in the form of mean and variance of the structural response. The effects of material nonlinearity are included through the use of a rate-independent anisotropic plasticity formulation with the macroscopic point of view. Both ply-level and micromechanics-level random variables can be selected, the latter by means of the Aboudi micromechanics model. A number of sample problems are solved to verify the accuracy of the procedures developed and to quantify the variability of certain material type/structure combinations. Experimental data is compared in many cases, and the Monte Carlo simulation method is used to check the probabilistic results. In general, the procedure is quite effective in modeling the mean and variance response of the linear and nonlinear behavior of laminated composite shells.

Engelstad, S. P.↗

Probabilistic simulation of multi-scale composite behavior

A methodology is developed to computationally assess the probabilistic composite material properties at all composite scale levels due to the uncertainties in the constituent (fiber and matrix) properties and in the fabrication process variables. The methodology is computationally efficient for simulating the probability distributions of material properties. The sensitivity of the probabilistic composite material property to each random variable is determined. This information can be used to reduce undesirable uncertainties in material properties at the macro scale of the composite by reducing the uncertainties in the most influential random variables at the micro scale. This methodology was implemented into the computer code PICAN (Probabilistic Integrated Composite ANalyzer). The accuracy and efficiency of this methodology are demonstrated by simulating the uncertainties in the material properties of a typical laminate and comparing the results with the Monte Carlo simulation method. The experimental data of composite material properties at all scales fall within the scatters predicted by PICAN.

Liaw, D. G.↗

Expert system development for probabilistic load simulation

A knowledge based system LDEXPT using the intelligent data base paradigm was developed for the Composite Load Spectra (CLS) project to simulate the probabilistic loads of a space propulsion system. The knowledge base approach provides a systematic framework of organizing the load information and facilitates the coupling of the numerical processing and symbolic (information) processing. It provides an incremental development environment for building generic probabilistic load models and book keeping the associated load information. A large volume of load data is stored in the data base and can be retrieved and updated by a built-in data base management system. The data base system standardizes the data storage and retrieval procedures. It helps maintain data integrity and avoid data redundancy. The intelligent data base paradigm provides ways to build expert system rules for shallow and deep reasoning and thus provides expert knowledge to help users to obtain the required probabilistic load spectra.

Ho, H.↗

Probabilistic structural analysis of space truss structures for nonuniform thermal environmental effects

A three-bay, space, cantilever truss is probabilistically evaluated to quantify the range of uncertainties of vibration frequencies and truss free end vertical displacements due to nonuniform thermal loads, applied loads and moments (mechanical loads), and combination of both. The truss members are assumed to be made from (1) aluminum tubes or (2) high modulus graphite-fiber/intermediate modulus epoxy-matrix composite tubes. Cumulative distribution function results show that certain combination of thermal loads with mechanical loads reduce the probabilistic vibration frequencies and increase the magnitude of the truss free end vertical displacements for the aluminum truss. However, for the composite truss, the thermal effects on the probabilistic vibration frequencies are not as substantial as that for an aluminum truss. This can be attributed to the large differences in the values of coefficient of thermal expansion. Finally, the sensitivities associated with the uncertainties in the structural, material and load variables (primative variables) are investigated. Results indicate that vibration frequencies and truss free end vertical displacements are sensitive to the uncertainties in spacial (geometry) variables as well as member modulus.

Pai, Shantaram S.↗

Probabilistic assessment of composite structures

A general purpose methodology for integrated probabilistic assessment of composite structures is demonstrated using aircraft fuselage type structures with rectangular cutouts. The computational simulation took into account buckling loads, vibration frequencies, global displacements, and local stresses. The procedure was embedded into the computer code IPACS (Integrated Probabilistic Assessment of Composite Structures) that calculates the simulated scatter, the sensitivity of the composite structural behavior to all the primitive variables that affect the structural behavior. The probabilistic assessment for the composite structure with rectangular cutouts indicates that the uncertainty in the longitudinal ply stress is mainly due to uncertainty in the laminate thickness.

Shiao, Michael C.↗

Probabilistic and structural reliability analysis of laminated composite structures based on the IPACS code

Probabilistic predictions based on the Integrated Probabilistic Assessment of Composite Structures (IPACS) code are presented for the material and structural response of unnotched and notched, 1M6/3501-6 Gr/Ep laminates. Comparisons of predicted and measured modulus and strength distributions are given for unnotched unidirectional, cross-ply, and quasi-isotropic laminates. The predicted modulus distributions were found to correlate well with the test results for all three unnotched laminates. Correlations of strength distributions for the unnotched laminates are judged good for the unidirectional laminate and fair for the cross-ply laminate, whereas the strength correlation for the quasi-isotropic laminate is deficient because IPACS did not yet have a progressive failure capability. The paper also presents probabilistic and structural reliability analysis predictions for the strain concentration factor (SCF) for an open-hole, quasi-isotropic laminate subjected to longitudinal tension. A special procedure was developed to adapt IPACS for the structural reliability analysis. The reliability results show the importance of identifying the most significant random variables upon which the SCF depends, and of having accurate scatter values for these variables.

Sobel, Larry↗

Parallel computing for probabilistic fatigue analysis

This paper presents the results of Phase I research to investigate the most effective parallel processing software strategies and hardware configurations for probabilistic structural analysis. We investigate the efficiency of both shared and distributed-memory architectures via a probabilistic fatigue life analysis problem. We also present a parallel programming approach, the virtual shared-memory paradigm, that is applicable across both types of hardware. Using this approach, problems can be solved on a variety of parallel configurations, including networks of single or multiprocessor workstations. We conclude that it is possible to effectively parallelize probabilistic fatigue analysis codes; however, special strategies will be needed to achieve large-scale parallelism to keep large number of processors busy and to treat problems with the large memory requirements encountered in practice. We also conclude that distributed-memory architecture is preferable to shared-memory for achieving large scale parallelism; however, in the future, the currently emerging hybrid-memory architectures will likely be optimal.

Sues, Robert H.↗

Probabilistically configured adaptive composite structures

A composite wing with spars, bulkheads and built-in sensor/control devices is probabilistically configured with a methodology for the probabilistic assessment of smart composite structures. Structural responses such as changes in angle of attack, vertical displacements and stresses in the non-control and control plies are probabilistically assessed to quantify their respective scatter ranges. Sensitivity factors are evaluated to identify those parameters that have the greatest influence on a specific structural response. Results show that smart composite structures can be configured to control distortions and ply stresses, and to have specified scatter ranges in the frequencies, buckling loads in the presence of defects to satisfy specified design requirements.

Shiao, Michael C.↗

Probabilistic Material Strength Degradation Model for Inconel 718 Components Subjected to High Temperature, Mechanical Fatigue, Creep and Thermal Fatigue Effects

This thesis presents the on-going development of methodology for a probabilistic material strength degradation model. The probabilistic model, in the form of a postulated randomized multifactor equation, provides for quantification of uncertainty in the lifetime material strength of aerospace propulsion system components subjected to a number of diverse random effects. This model is embodied in the computer program entitled PROMISS, which can include up to eighteen different effects. Presently, the model includes four effects that typically reduce lifetime strength: high temperature, mechanical fatigue, creep, and thermal fatigue. Statistical analysis was conducted on experimental Inconel 718 data obtained from the open literature. This analysis provided regression parameters for use as the model's empirical material constants, thus calibrating the model specifically for Inconel 718. Model calibration was carried out for four variables, namely, high temperature, mechanical fatigue, creep, and thermal fatigue. Methodology to estimate standard deviations of these material constants for input into the probabilistic material strength model was developed. Using the current version of PROMISS, entitled PROMISS93, a sensitivity study for the combined effects of mechanical fatigue, creep, and thermal fatigue was performed. Results, in the form of cumulative distribution functions, illustrated the sensitivity of lifetime strength to any current value of an effect. In addition, verification studies comparing a combination of mechanical fatigue and high temperature effects by model to the combination by experiment were conducted. Thus, for Inconel 718, the basic model assumption of independence between effects was evaluated. Results from this limited verification study strongly supported this assumption.

Bast, Callie Corinne Scheidt↗

A method for the probabilistic design assessment of composite structures

A formal procedure for the probabilistic design assessment of a composite structure is described. The uncertainties in all aspects of a composite structure (constituent material properties, fabrication variables, structural geometry, service environments, etc.), which result in the uncertain behavior in the composite structural responses, are included in the assessment. The probabilistic assessment consists of design criteria, modeling of composite structures and uncertainties, simulation methods, and the decision making process. A sample case is presented to illustrate the formal procedure and to demonstrate that composite structural designs can be probabilistically assessed with accuracy and efficiency.

Shiao, Michael C.↗

Rocket engine system reliability analyses using probabilistic and fuzzy logic techniques

The reliability of rocket engine systems was analyzed by using probabilistic and fuzzy logic techniques. Fault trees were developed for integrated modular engine (IME) and discrete engine systems, and then were used with the two techniques to quantify reliability. The IRRAS (Integrated Reliability and Risk Analysis System) computer code, developed for the U.S. Nuclear Regulatory Commission, was used for the probabilistic analyses, and FUZZYFTA (Fuzzy Fault Tree Analysis), a code developed at NASA Lewis Research Center, was used for the fuzzy logic analyses. Although both techniques provided estimates of the reliability of the IME and discrete systems, probabilistic techniques emphasized uncertainty resulting from randomness in the system whereas fuzzy logic techniques emphasized uncertainty resulting from vagueness in the system. Because uncertainty can have both random and vague components, both techniques were found to be useful tools in the analysis of rocket engine system reliability.

Hardy, Terry L.↗

Probabilistic risk assessment of the Space Shuttle. Phase 3: A study of the potential of losing the vehicle during nominal operation. Volume 5: Auxiliary shuttle risk analyses

Volume 5 is Appendix C, Auxiliary Shuttle Risk Analyses, and contains the following reports: Probabilistic Risk Assessment of Space Shuttle Phase 1 - Space Shuttle Catastrophic Failure Frequency Final Report; Risk Analysis Applied to the Space Shuttle Main Engine - Demonstration Project for the Main Combustion Chamber Risk Assessment; An Investigation of the Risk Implications of Space Shuttle Solid Rocket Booster Chamber Pressure Excursions; Safety of the Thermal Protection System of the Space Shuttle Orbiter - Quantitative Analysis and Organizational Factors; Space Shuttle Main Propulsion Pressurization System Probabilistic Risk Assessment, Final Report; and Space Shuttle Probabilistic Risk Assessment Proof-of-Concept Study - Auxiliary Power Unit and Hydraulic Power Unit Analysis Report.

Fragola, Joseph R.↗