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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Probabilistic Finite Element Development

The probabilistic finite element computer program known as Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) is being developed for the analysis of critical structural components for reusable space propulsion systems. First year efforts involve the formulation of the probabilistic analysis strategy and the development of a probabilistic linear analysis code. The ultimate goal of the 3-year program is the development of a finite element code capable of performing nonlinear dynamic analysis of structures having stochastic material properties, geometry, and boundary conditions and subjected to random loading. Three levels of sophistication are envisioned for the stochastic description of the structural problem, namely: (1) homogeneous random variable for stiffness, mass, damping, and external loading; (2) stochastic characterization of variables at the element level, with specified interelement correlations; and (3) stochastic interpolation of variables within a finite element. Two alternative probabilistic analysis methods will be developed, allowing for all three levels of modeling sophistication.

Nagtegaal, J.↗
NASA NTRS1987

Assessment Of Advanced Concentrator Photovoltaic Modules

Computer program developed to estimate probabilistically total and component costs to end users of concentrating photovoltaic arrays in 1990's. Based on modified version of SIMRAND program, Simulation of Research and Development projects, -to estimate total cost of system for large number of module designs. Module design that yields minimum cost for total system then chosen as preferred design. To obtain distribution of expected module costs, simulation performed. Component estimates made by SIMRAND include efficiency of module and costs of cell, assembly of cells, lenses, and modules. Written in FORTRAN 77.

Borden, C. S.↗
NASA NTRS2002

CARES/Life Used for Probabilistic Characterization of MEMS Pressure Sensor Membranes

Microelectromechanical systems (MEMS) devices are typically made from brittle materials such as silicon using traditional semiconductor manufacturing techniques. They can be etched (or micromachined) from larger structures or can be built up with material deposition processes. Maintaining dimensional control and consistent mechanical properties is considerably more difficult for MEMS because feature size is on the micrometer scale. Therefore, the application of probabilistic design methodology becomes necessary for MEMS. This was demonstrated at the NASA Glenn Research Center and Case Western Reserve University in an investigation that used the NASA-developed CARES/Life brittle material design program to study the probabilistic fracture strength behavior of single-crystal SiC, polycrystalline SiC, and amorphous Si3N4 pressurized 1-mm-square thin-film diaphragms. These materials are of interest because of their superior high-temperature characteristics, which are desirable for harsh environment applications such as turbine engine and rocket propulsion system hot sections.

Nemeth, Noel N.↗
NASA NTRS1988

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.↗
NASA NTRS1989

Probabilistic structural analysis: Introductory remarks

The development of probabilistic structural analysis methodology consists of the following program elements: (1) composite load spectra models, (2) computational probabilistic structural analysis methods, and (3) probabilistic constitutive relationships. The development of the probabilistic structural analysis methodology is a joint program of NASA Lewis in-house and sponsored research. The objective of this session is to illustrate recent progress on the application of this methodology to determine the reliability of structural components for rocket propulsion systems. The session contains descriptions of and progress reports on the following specific activities: (1) The NESSUS computer code, (2) approximate methods, (3) advanced methods, (4) composite load spectra applications, (5) probabilistic fracture mechanisms, and (6) probability of failure and risk analysis. Collectively, the progress to date demonstrates that the structural durability of hot engine structural components can be effectively evaluated in a formal probabilistic/reliability framework.

Chamis, Christos C.↗
NASA NTRS1991

Commercialization of NESSUS: Status

A plan was initiated in 1988 to commercialize the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) probabilistic structural analysis software. The goal of the on-going commercialization effort is to begin the transfer of Probabilistic Structural Analysis Method (PSAM) developed technology into industry and to develop additional funding resources in the general area of structural reliability. The commercialization effort is summarized. The SwRI NESSUS Software System is a general purpose probabilistic finite element computer program using state of the art methods for predicting stochastic structural response due to random loads, material properties, part geometry, and boundary conditions. NESSUS can be used to assess structural reliability, to compute probability of failure, to rank the input random variables by importance, and to provide a more cost effective design than traditional methods. The goal is to develop a general probabilistic structural analysis methodology to assist in the certification of critical components in the next generation Space Shuttle Main Engine.

Thacker, Ben H.↗
NASA NTRS1985

Overview of Structural Response: Probabilistic Structural Analysis

Advanced analysis methods are required to predict accurately the structural response (static, transient, cyclic, etc.) and accompanying local stresses in space propulsion system components operating in a fatigue environment consisting of complex thermal and mechanical load spectra. The probabilistic approach to structural response consists of the following program elements: (1) composite load spectra, (2) probabilistic structural analysis methods development, (3) probabilitic finite element theory, (4) probabilistic structural analysis application, (5) structural tailoring of turbopump blades, (6) unified theory of dynamic creep buckling/ratcheting, (7) creep buckling/ratcheting analyzer, and (8) nonlinear COBSTRAN development. Research activities on all of these program elements (except the creep buckling/ratcheting analyzer) are under way.

Chamis, C. C.↗
NASA NTRS2002

Probabilistic Analysis and Density Parameter Estimation Within Nessus

This NASA educational grant has the goal of promoting probabilistic analysis methods to undergraduate and graduate UTSA engineering students. Two undergraduate-level and one graduate-level course were offered at UTSA providing a large number of students exposure to and experience in probabilistic techniques. The grant provided two research engineers from Southwest Research Institute the opportunity to teach these courses at UTSA, thereby exposing a large number of students to practical applications of probabilistic methods and state-of-the-art computational methods. In classroom activities, students were introduced to the NESSUS computer program, which embodies many algorithms in probabilistic simulation and reliability analysis. Because the NESSUS program is used at UTSA in both student research projects and selected courses, a student version of a NESSUS manual has been revised and improved, with additional example problems being added to expand the scope of the example application problems. This report documents two research accomplishments in the integration of a new sampling algorithm into NESSUS and in the testing of the new algorithm. The new Latin Hypercube Sampling (LHS) subroutines use the latest NESSUS input file format and specific files for writing output. The LHS subroutines are called out early in the program so that no unnecessary calculations are performed. Proper correlation between sets of multidimensional coordinates can be obtained by using NESSUS' LHS capabilities. Finally, two types of correlation are written to the appropriate output file. The program enhancement was tested by repeatedly estimating the mean, standard deviation, and 99th percentile of four different responses using Monte Carlo (MC) and LHS. These test cases, put forth by the Society of Automotive Engineers, are used to compare probabilistic methods. For all test cases, it is shown that LHS has a lower estimation error than MC when used to estimate the mean, standard deviation, and 99th percentile of the four responses at the 50 percent confidence level and using the same number of response evaluations for each method. In addition, LHS requires fewer calculations than MC in order to be 99.7 percent confident that a single mean, standard deviation, or 99th percentile estimate will be within at most 3 percent of the true value of the each parameter. Again, this is shown for all of the test cases studied. For that reason it can be said that NESSUS is an important reliability tool that has a variety of sound probabilistic methods a user can employ; furthermore, the newest LHS module is a valuable new enhancement of the program.

Godines, Cody R.↗
NASA NTRS2008

Injecting Artificial Memory Errors Into a Running Computer Program

Single-event upsets (SEUs) or bitflips are computer memory errors caused by radiation. BITFLIPS (Basic Instrumentation Tool for Fault Localized Injection of Probabilistic SEUs) is a computer program that deliberately injects SEUs into another computer program, while the latter is running, for the purpose of evaluating the fault tolerance of that program. BITFLIPS was written as a plug-in extension of the open-source Valgrind debugging and profiling software. BITFLIPS can inject SEUs into any program that can be run on the Linux operating system, without needing to modify the program s source code. Further, if access to the original program source code is available, BITFLIPS offers fine-grained control over exactly when and which areas of memory (as specified via program variables) will be subjected to SEUs. The rate of injection of SEUs is controlled by specifying either a fault probability or a fault rate based on memory size and radiation exposure time, in units of SEUs per byte per second. BITFLIPS can also log each SEU that it injects and, if program source code is available, report the magnitude of effect of the SEU on a floating-point value or other program variable.

Bornstein, Benjamin J.↗
NASA NTRS2003

Advanced Software for Analysis of High-Speed Rolling-Element Bearings

COBRA-AHS is a package of advanced software for analysis of rigid or flexible shaft systems supported by rolling-element bearings operating at high speeds under complex mechanical and thermal loads. These loads can include centrifugal and thermal loads generated by motions of bearing components. COBRA-AHS offers several improvements over prior commercial bearing-analysis programs: It includes innovative probabilistic fatigue-life-estimating software that provides for computation of three-dimensional stress fields and incorporates stress-based (in contradistinction to prior load-based) mathematical models of fatigue life. It interacts automatically with the ANSYS finite-element code to generate finite-element models for estimating distributions of temperature and temperature-induced changes in dimensions in iterative thermal/dimensional analyses: thus, for example, it can be used to predict changes in clearances and thermal lockup. COBRA-AHS provides an improved graphical user interface that facilitates the iterative cycle of analysis and design by providing analysis results quickly in graphical form, enabling the user to control interactive runs without leaving the program environment, and facilitating transfer of plots and printed results for inclusion in design reports. Additional features include roller-edge stress prediction and influence of shaft and housing distortion on bearing performance.

Poplawski, J. V.↗
NASA NTRS1986

Automatic probabilistic knowledge acquisition from data

A computer program for extracting significant correlations of attributes from masses of data is outlined. This information can then be used to develop a knowledge base for a probabilistic expert system. The method determines the best estimate of joint probabilities of attributes from data put into contingency table form. A major output from the program is a general formula for calculating any probability relation associated with the data. These probability relations can be utilized to form IF-THEN rules with associated probability, useful for expert systems.

Gevarter, W. B.↗
NASA NTRS1985

Protecting intellectual property in space; Proceedings of the Aerospace Computer Security Conference, McLean, VA, March 20, 1985

The primary purpose of the Aerospace Computer Security Conference was to bring together people and organizations which have a common interest in protecting intellectual property generated in space. Operational concerns are discussed, taking into account security implications of the space station information system, Space Shuttle security policies and programs, potential uses of probabilistic risk assessment techniques for space station development, key considerations in contingency planning for secure space flight ground control centers, a systematic method for evaluating security requirements compliance, and security engineering of secure ground stations. Subjects related to security technologies are also explored, giving attention to processing requirements of secure C3/I and battle management systems and the development of the Gemini trusted multiple microcomputer base, the Restricted Access Processor system as a security guard designed to protect classified information, and observations on local area network security.

Source record↗
NASA NTRS1986

Probabilistic structural analysis methods for space propulsion system components

The development of a three-dimensional inelastic analysis methodology for the Space Shuttle main engine (SSME) structural components is described. The methodology is composed of: (1) composite load spectra, (2) probabilistic structural analysis methods, (3) the probabilistic finite element theory, and (4) probabilistic structural analysis. The methodology has led to significant technical progress in several important aspects of probabilistic structural analysis. The program and accomplishments to date are summarized.

Chamis, C. C.↗
NASA NTRS1987

Probabilistic structural analysis methods for space propulsion system components

The development of a three-dimensional inelastic analysis methodology for the Space Shuttle main engine (SSME) structural components is described. The methodology is composed of: (1) composite load spectra, (2) probabilistic structural analysis methods, (3) the probabilistic finite element theory, and (4) probabilistic structural analysis. The methodology has led to significant technical progress in several important aspects of probabilistic structural analysis. The program and accomplishments to date are summarized.

Chamis, Christos C.↗
NASA NTRSDate not supplied

Proof-of-Concept for a Long-Term Health Metric to Quantify End of Mission Health Status in Astronauts

NASA has long used Probabilistic Risk Assessment (PRA) when high-stakes decisions need to be made about complex systems. For spaceflight medical risk, the Human Research Program’s Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is a significant step towards robustly quantifying the risk to crew health during exploration missions. However, there remains a significant gap in the ability to comprehensively characterize and assess risk across the disparate functionalities and capabilities which comprise the entire Crew Health and Performance (CHP) system. To fill this gap, the Crew Health and Performance – Probabilistic Risk Assessment (CHP-PRA) project aims to perform risk characterization for the CHP system by assessing performance risk in addition to medical risk. This effort also includes quantifying Long-Term Health (LTH) risk in addition to in-mission risk outcomes within the CHP-PRA results. LTH risk encompasses the timeframe from immediately post-flight, through the rest of an astronaut’s career, through retirement, and until death. A proof-of-concept LTH risk metric is based on medical condition end-state, as defined by the Evidence Library, capturing the spaceflight specific medical impacts persisting into post-flight[1]. Condition outcomes in the Evidence Library progress through three Clinical Phases (CP): the diagnostic phase (CP1), the treatment/convalescent phase (CP2), and the end-state phase (CP3) which represents the detrimental effects of the condition after the crew member has recovered to the maximal extent. Each CP has an associated Task Impairment (TI), defined as the degree of crew incapacity due to experiencing the condition, and is quantified with a 0-1 range. Conditions with an associated CP3 (e.g. Sepsis, Traumatic Hypovolemic Shock, Sudden Cardiac Arrest, etc.) typically have serious consequences that can cause an astronaut to be fully or partially debilitated throughout the remainder of the mission. Consequently, the Cumulative CP3 TI End-of-Mission Health Status Metric is developed by CHP-PRA to quantify the cumulative effects of all conditions which progressed to the CP3 state throughout the entirety of the mission. Hence, this End-of-Mission Health Status Metric attempts to serve as an indicator of an astronaut’s health state at the time of landing. The severity of the lingering effects of in-mission medical events are dependent on mission activities and the level of available in-mission medical care. This allows the associated cumulative TI metric to be used in comparison with the crew’s end of mission health status for different levels of in-mission resources. This presentation provides the strategy for using CP3 as an LTH metric component, as well as a proof-of-concept demonstration of LTH risk characterization using this component.

long term health↗
NASA NTRS1987

Probabilistic structural analysis to evaluate the structural durability of SSME critical components

NASA Lewis Research Center is currently developing probabilistic structural analysis methods for select Space Shuttle Main Engine (SSME) structural components. Briefly, the deterministic, three-dimensional, inelastic analysis methodology developed under the Hot Section Technology (HOST) and R and T Base Programs is being augmented to accommodate the complex probabilistic loading spectra, the thermoviscoplastic material behavior, and the material degradation associated with the environment of space propulsion system structural components representative of the SSME such as turbine blades, transfer ducts, and liquid-oxygen posts. The development of probabilistic structural analysis methodology consists of the following program elements: (1) composite load spectra; (2) probabilistic structural analysis methods; (3) probabilistic finite element theory - new variational principles; and (4) probabilistic structural analysis application. In addition, the program includes deterministic analysis elements: (1) development of structural tailoring computer codes (SSME/STAEBL); (2) development of dynamic creep buckling/ratcheting theory; (3) evaluation of the dynamic characteristics of single-crystal SSME blades; (4) development of SSME blade damper technology; and (5) development of integrated boundary elements for hotfluid structure interaction.

Chamis, Christos C.↗
NASA NTRS1989

Fatigue crack growth model RANDOM2 user manual. Appendix 1: Development of advanced methodologies for probabilistic constitutive relationships of material strength models

FORTRAN program RANDOM2 is presented in the form of a user's manual. RANDOM2 is based on fracture mechanics using a probabilistic fatigue crack growth model. It predicts the random lifetime of an engine component to reach a given crack size. Details of the theoretical background, input data instructions, and a sample problem illustrating the use of the program are included.

Boyce, Lola↗