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At least 73 records · Page 4

Probabilistic structural analysis methods development for SSME

The development of probabilistic structural analysis methods is a major part of the SSME Structural Durability Program and consists of three program elements: composite load spectra, probabilistic finite element structural analysis, and probabilistic structural analysis applications. Recent progress includes: (1) the effects of the uncertainties of several factors on the HPFP blade temperature pressure and torque, (2) the evaluation of the cumulative distribution function of structural response variables based on assumed uncertainties on primitive structural variables, and (3) evaluation of the failure probability. Collectively, the results obtained demonstrate that the structural durability of critical SSME components can be probabilistically evaluated.

Chamis, C. C.↗

Probabilistic structural analysis methods of hot engine structures

Development of probabilistic structural analysis methods for hot engine structures is a major activity at Lewis Research Center. Recent activities have focused on extending the methods to include the combined uncertainties in several factors on structural response. This paper briefly describes recent progress on composite load spectra models, probabilistic finite element structural analysis, and probabilistic strength degradation modeling. Progress is described in terms of fundamental concepts, computer code development, and representative numerical results.

Chamis, C. C.↗

Probabilistic structural analysis methods of hot engine structures

Development of probabilistic structural analysis methods for hot engine structures at Lewis Research Center is presented. Three elements of the research program are: (1) composite load spectra methodology; (2) probabilistic structural analysis methodology; and (3) probabilistic structural analysis application. Recent progress includes: (1) quantification of the effects of uncertainties for several variables on high pressure fuel turbopump (HPFT) turbine 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; and (3) evaluation of the failure probability. Collectively, the results demonstrate that the structural durability of hot engine structural components can be effectively evaluated in a formal probabilistic/reliability framework.

Chamis, C. C.↗

An advanced probabilistic structural analysis method for implicit performance functions

In probabilistic structural analysis, the performance or response functions usually are implicitly defined and must be solved by numerical analysis methods such as finite element methods. In such cases, the most commonly used probabilistic analysis tool is the mean-based, second-moment method which provides only the first two statistical moments. This paper presents a generalized advanced mean value (AMV) method which is capable of establishing the distributions to provide additional information for reliability design. The method requires slightly more computations than the second-moment method but is highly efficient relative to the other alternative methods. In particular, the examples show that the AMV method can be used to solve problems involving non-monotonic functions that result in truncated distributions.

Wu, Y.-T.↗

Certification of damage tolerant composite structure

A reliability based certification testing methodology for impact damage tolerant composite structure was developed. Cocured, adhesively bonded, and impact damaged composite static strength and fatigue life data were statistically analyzed to determine the influence of test parameters on the data scatter. The impact damage resistance and damage tolerance of various structural configurations were characterized through the analysis of an industry wide database of impact test results. Realistic impact damage certification requirements were proposed based on actual fleet aircraft data. The capabilities of available impact damage analysis methods were determined through correlation with experimental data. Probabilistic methods were developed to estimate the reliability of impact damaged composite structures.

Rapoff, Andrew J.↗

NESSUS/expert and NESSUS/FPI in the Probabilistic Structural Analysis Methods (PSAM) program

The Numerical Evaluation of Stochastic Structures under Stress (NESSUS) is the primary computer code being developed in the NASA Probabilistic Structural Analysis Methods (PSAM) project. It consists of four modules NESSUS/EXPERT, NESSUS/FPI, NESSUS/PRE and NESSUS/FEM. This presentation concentrates on EXPERT and FPI. To provide an effective interface between NESSUS and the user, an expert system module called NESSUS/EXPERT is being developed. That system uses the CLIPS artificial intelligence code developed to NASA-JSC. The code is compatible with FORTRAN, the standard language for codes in PSAM. The user interacts with the CLIPS inference engine, which is linked to the knowledge database. The perturbation database generated by NESSUS/FEM and managed in EXPERT is used to develop the so-called response or performance model in the random variables. Two independent probabilistic methods are available in PSAM for the computation of the probabilistic structural response. These are the Fast Probability Integration (FPI) method and Monte Carlo simulation. FPI is classified as an advanced reliability method and has been developed over the past ten years by researchers addressing the reliability of civil engineering structures. Monte Carlo is a well-established technique for computing probabilities by conducting a number of deterministic analyses with specified input distributional information.

Burnside, O. H.↗

Probabilistic structural analysis methods for select space propulsion system components

The Probabilistic Structural Analysis Methods (PSAM) project developed at the Southwest Research Institute integrates state-of-the-art structural analysis techniques with probability theory for the design and analysis of complex large-scale engineering structures. An advanced efficient software system (NESSUS) capable of performing complex probabilistic analysis has been developed. NESSUS contains a number of software components to perform probabilistic analysis of structures. These components include: an expert system, a probabilistic finite element code, a probabilistic boundary element code and a fast probability integrator. The NESSUS software system is shown. An expert system is included to capture and utilize PSAM knowledge and experience. NESSUS/EXPERT is an interactive menu-driven expert system that provides information to assist in the use of the probabilistic finite element code NESSUS/FEM and the fast probability integrator (FPI). The expert system menu structure is summarized. The NESSUS system contains a state-of-the-art nonlinear probabilistic finite element code, NESSUS/FEM, to determine the structural response and sensitivities. A broad range of analysis capabilities and an extensive element library is present.

Millwater, H. R.↗

Application of the Probabilistic Dynamic Synthesis Method to the Analysis of a Realistic Structure

The Probabilistic Dynamic Synthesis method is a new technique for obtaining the statistics of a desired response engineering quantity for a structure with non-deterministic parameters. The method uses measured data from modal testing of the structure as the input random variables, rather than more "primitive" quantities like geometry or material variation. This modal information is much more comprehensive and easily measured than the "primitive" information. The probabilistic analysis is carried out using either response surface reliability methods or Monte Carlo simulation. A previous work verified the feasibility of the PDS method on a simple seven degree-of-freedom spring-mass system. In this paper, extensive issues involved with applying the method to a realistic three-substructure system are examined, and free and forced response analyses are performed. The results from using the method are promising, especially when the lack of alternatives for obtaining quantitative output for probabilistic structures is considered.

Brown, Andrew M.↗

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

The fourth year of technical developments on the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) system for Probabilistic Structural Analysis Methods is summarized. The effort focused on the continued expansion of the Probabilistic Finite Element Method (PFEM) code, the implementation of the Probabilistic Boundary Element Method (PBEM), and the implementation of the Probabilistic Approximate Methods (PAppM) code. The principal focus for the PFEM code is the addition of a multilevel structural dynamics capability. The strategy includes probabilistic loads, treatment of material, geometry uncertainty, and full probabilistic variables. Enhancements are included for the Fast Probability Integration (FPI) algorithms and the addition of Monte Carlo simulation as an alternate. Work on the expert system and boundary element developments continues. The enhanced capability in the computer codes is validated by applications to a turbine blade and to an oxidizer duct.

Source record↗

Probabilistic structural analysis methods for space transportation propulsion systems

Information on probabilistic structural analysis methods for space propulsion systems is given in viewgraph form. Information is given on deterministic certification methods, probability of failure, component response analysis, stress responses for 2nd stage turbine blades, Space Shuttle Main Engine (SSME) structural durability, and program plans. .

Chamis, C. C.↗

Probabilistic Aeroelastic Analysis of Turbomachinery Components

A probabilistic approach is described for aeroelastic analysis of turbomachinery blade rows. Blade rows with subsonic flow and blade rows with supersonic flow with subsonic leading edge are considered. To demonstrate the probabilistic approach, the flutter frequency, damping and forced response of a blade row representing a compressor geometry is considered. The analysis accounts for uncertainties in structural and aerodynamic design variables. The results are presented in the form of probabilistic density function (PDF) and sensitivity factors. For subsonic flow cascade, comparisons are also made with different probabilistic distributions, probabilistic methods, and Monte-Carlo simulation. The approach shows that the probabilistic approach provides a more realistic and systematic way to assess the effect of uncertainties in design variables on the aeroelastic instabilities and response.

Reddy, T. S. R.↗

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 Structural Analysis Methods (PSAM) for select space propulsion system structural components

The objective is the development of several modular structural analysis packages capable of predicting the probabilistic response distribution for key structural variables such as maximum stress, natural frequencies, transient response, etc. The structural analysis packages are to include stochastic modeling of loads, material properties, geometry (tolerances), and boundary conditions. The solution is to be in terms of the cumulative probability of exceedance distribution (CDF) and confidence bounds. Two methods of probability modeling are to be included as well as three types of structural models - probabilistic finite-element method (PFEM); probabilistic approximate analysis methods (PAAM); and probabilistic boundary element methods (PBEM). The purpose in doing probabilistic structural analysis is to provide the designer with a more realistic ability to assess the importance of uncertainty in the response of a high performance structure. Probabilistic Structural Analysis Method (PSAM) tools will estimate structural safety and reliability, while providing the engineer with information on the confidence that should be given to the predicted behavior. Perhaps most critically, the PSAM results will directly provide information on the sensitivity of the design response to those variables which are seen to be uncertain.

Cruse, T. A.↗

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

The objective is the development of several modular structural analysis packages capable of predicting the probabilistic response distribution for key structural variables such as maximum stress, natural frequencies, transient response, etc. The structural analysis packages are to include stochastic modeling of loads, material properties, geometry (tolerances), and boundary conditions. The solution is to be in terms of the cumulative probability of exceedance distribution (CDF) and confidence bounds. Two methods of probability modeling are to be included as well as three types of structural models - probabilistic finite-element method (PFEM); probabilistic approximate analysis methods (PAAM); and probabilistic boundary element methods (PBEM). The purpose in doing probabilistic structural analysis is to provide the designer with a more realistic ability to assess the importance of uncertainty in the response of a high performance structure. Probabilistic Structural Analysis Method (PSAM) tools will estimate structural safety and reliability, while providing the engineer with information on the confidence that should be given to the predicted behavior. Perhaps most critically, the PSAM results will directly provide information on the sensitivity of the design response to those variables which are seen to be uncertain.

Cruse, T. A.↗

NASA Overview

This viewgraph presentation provides information on computer programs for the application of probabilistics in aerospace design. The presentation defines risk, and lists probabilistic tools which can take risk into account. It then lists current and future examples of NASA aerospace technology program support which utilize probabilistic methods. Current examples include turbofan engines, combustor liners, life estimation, the analysis of rotors and blades, and shuttle ground operations. The 2nd Generation Reusable Launch Vehicle is one of the future areas of support. The presentation also suggests other future uses of probabilistic tools in aerospace design, and optimal methods for their implementation.

Rusick, Jeff↗

NESSUS/EXPERT - An expert system for probabilistic structural analysis methods

An expert system (NESSUS/EXPERT) is presented which provides assistance in using probabilistic structural analysis methods. NESSUS/EXPERT is an interactive menu-driven expert system that provides information to assist in the use of the probabilistic finite element code NESSUS/FEM and the fast probability integrator. NESSUS/EXPERT was developed with a combination of FORTRAN and CLIPS, a C language expert system tool, to exploit the strengths of each language.

Millwater, H.↗

Composite Loads Spectra for Select Space Propulsion Structural Components: Probabilistic Load Model Development

This effort is in support of the development of the expert system of computer codes to predict the loads on select structural components of a space propulsion engine. The development will be based primarily on the space shuttle main engine (SSME) test data base. Because of random variations of the many different sources of the loadings on the selected structural components and transients, a probabilistic approach to the problems was adopted. The goal of this task is to characterize all of the individual sources of loads at critical structural locations, such as the turbine blades, the transfer ducts, and liquid oxygen posts, using state-of-the-art probabilistic methods with varying levels of sophistication. The second phase of this work is the development of a composite load model based on a probabilistic synthesis of the individual load model previously developed. This model will be based on the stochastic combination of the load variables and not on the physical process for the combination of the individual loads to the composite load seen by the selected structural components.

Kurth, R.↗