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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Reliability Analysis of Brittle Material Structures - Including MEMS(?) - With the CARES/Life Program

Brittle materials are being used, or considered, for a wide variety of high tech applications that operate in harsh environments, including static and rotating turbine parts. thermal protection systems, dental prosthetics, fuel cells, oxygen transport membranes, radomes, and MEMS. Designing components to sustain repeated load without fracturing while using the minimum amount of material requires the use of a probabilistic design methodology. The CARES/Life code provides a general-purpose analysis tool that predicts the probability of failure of a ceramic component as a function of its time in service. For this presentation an interview of the CARES/Life program will be provided. Emphasis will be placed on describing the latest enhancements to the code for reliability analysis with time varying loads and temperatures (fully transient reliability analysis). Also, early efforts in investigating the validity of using Weibull statistics, the basis of the CARES/Life program, to characterize the strength of MEMS structures will be described as as well as the version of CARES/Life for MEMS (CARES/MEMS) being prepared which incorporates single crystal and edge flaw reliability analysis capability. It is hoped this talk will open a dialog for potential collaboration in the area of MEMS testing and life prediction.

Nemeth, Noel N.↗
NASA NTRS1990

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.↗
NASA NTRS2009

Probabilistic Estimation of Critical Flaw Sizes in the Primary Structure Welds of the Ares I-X Launch Vehicle

The primary structure of the Ares I-X Upper Stage Simulator (USS) launch vehicle is constructed of welded mild steel plates. There is some concern over the possibility of structural failure due to welding flaws. It was considered critical to quantify the impact of uncertainties in residual stress, material porosity, applied loads, and material and crack growth properties on the reliability of the welds during its pre-flight and flight. A criterion--an existing maximum size crack at the weld toe must be smaller than the maximum allowable flaw size--was established to estimate the reliability of the welds. A spectrum of maximum allowable flaw sizes was developed for different possible combinations of all of the above listed variables by performing probabilistic crack growth analyses using the ANSYS finite element analysis code in conjunction with the NASGRO crack growth code. Two alternative methods were used to account for residual stresses: (1) The mean residual stress was assumed to be 41 ksi and a limit was set on the net section flow stress during crack propagation. The critical flaw size was determined by parametrically increasing the initial flaw size and detecting if this limit was exceeded during four complete flight cycles, and (2) The mean residual stress was assumed to be 49.6 ksi (the parent material s yield strength) and the net section flow stress limit was ignored. The critical flaw size was determined by parametrically increasing the initial flaw size and detecting if catastrophic crack growth occurred during four complete flight cycles. Both surface-crack models and through-crack models were utilized to characterize cracks in the weld toe.

Pai, Shantaram S.↗
NASA NTRS2010

JSC Safety and Mission Assurance Data Analysis Overview

These slides describe the data analysis methods that are used to determine inputs for probabilistic risk models supporting the Space Shuttle Program. Other applications can follow a similar path probably using different data sources. Statistical approaches are different and not addressed here. Topics included here: 1) Prior Distribution; 2) Likelihood Data; 3) Bayesian Updating; and 4) Uncertainty and Error. Note: This is a high-level discussion and is not intended to be a tutorial.

Roelant, Henk↗
NASA NTRS2016

[MaRS Project]

The Space Exploration Division of the Safety and Mission Assurances Directorate is responsible for reducing the risk to Human Space Flight Programs by providing system safety, reliability, and risk analysis. The Risk & Reliability Analysis branch plays a part in this by utilizing Probabilistic Risk Assessment (PRA) and Reliability and Maintainability (R&M) tools to identify possible types of failure and effective solutions. A continuous effort of this branch is MaRS, or Mass and Reliability System, a tool that was the focus of this internship. Future long duration space missions will have to find a balance between the mass and reliability of their spare parts. They will be unable take spares of everything and will have to determine what is most likely to require maintenance and spares. Currently there is no database that combines mass and reliability data of low level space-grade components. MaRS aims to be the first database to do this. The data in MaRS will be based on the hardware flown on the International Space Stations (ISS). The components on the ISS have a long history and are well documented, making them the perfect source. Currently, MaRS is a functioning excel workbook database; the backend is complete and only requires optimization. MaRS has been populated with all the assemblies and their components that are used on the ISS; the failures of these components are updated regularly. This project was a continuation on the efforts of previous intern groups. Once complete, R&M engineers working on future space flight missions will be able to quickly access failure and mass data on assemblies and components, allowing them to make important decisions and tradeoffs.

Aruljothi, Arunvenkatesh↗
NASA NTRS2015

NASA Space Radiation Risk Project: Overview and Recent Results

The NASA Space Radiation Risk project is responsible for integrating new experimental and computational results into models to predict risk of cancer and acute radiation syndrome (ARS) for use in mission planning and systems design, as well as current space operations. The project has several parallel efforts focused on proving NASA's radiation risk projection capability in both the near and long term. This presentation will give an overview, with select results from these efforts including the following topics: verification, validation, and streamlining the transition of models to use in decision making; relative biological effectiveness and dose rate effect estimation using a combination of stochastic track structure simulations, DNA damage model calculations and experimental data; ARS model improvements; pathway analysis from gene expression data sets; solar particle event probabilistic exposure calculation including correlated uncertainties for use in design optimization.

Blattnig, Steve R.↗
NASA NTRS2008

Reliability and Confidence Interval Analysis of a CMC Turbine Stator Vane

High temperature ceramic matrix composites (CMC) are being explored as viable candidate materials for hot section gas turbine components. These advanced composites can potentially lead to reduced weight, enable higher operating temperatures requiring less cooling and thus leading to increased engine efficiencies. However, these materials are brittle and show degradation with time at high operating temperatures due to creep as well as cyclic mechanical and thermal loads. In addition, these materials are heterogeneous in their make-up and various factors affect their properties in a specific design environment. Most of these advanced composites involve two- and three-dimensional fiber architectures and require a complex multi-step high temperature processing. Since there are uncertainties associated with each of these in addition to the variability in the constituent material properties, the observed behavior of composite materials exhibits scatter. Traditional material failure analyses employing a deterministic approach, where failure is assumed to occur when some allowable stress level or equivalent stress is exceeded, are not adequate for brittle material component design. Such phenomenological failure theories are reasonably successful when applied to ductile materials such as metals. Analysis of failure in structural components is governed by the observed scatter in strength, stiffness and loading conditions. In such situations, statistical design approaches must be used. Accounting for these phenomena requires a change in philosophy on the design engineer s part that leads to a reduced focus on the use of safety factors in favor of reliability analyses. The reliability approach demands that the design engineer must tolerate a finite risk of unacceptable performance. This risk of unacceptable performance is identified as a component's probability of failure (or alternatively, component reliability). The primary concern of the engineer is minimizing this risk in an economical manner. The methods to accurately determine the service life of an engine component with associated variability have become increasingly difficult. This results, in part, from the complex missions which are now routinely considered during the design process. These missions include large variations of multi-axial stresses and temperatures experienced by critical engine parts. There is a need for a convenient design tool that can accommodate various loading conditions induced by engine operating environments, and material data with their associated uncertainties to estimate the minimum predicted life of a structural component. A probabilistic composite micromechanics technique in combination with woven composite micromechanics, structural analysis and Fast Probability Integration (FPI) techniques has been used to evaluate the maximum stress and its probabilistic distribution in a CMC turbine stator vane. Furthermore, input variables causing scatter are identified and ranked based upon their sensitivity magnitude. Since the measured data for the ceramic matrix composite properties is very limited, obtaining a probabilistic distribution with their corresponding parameters is difficult. In case of limited data, confidence bounds are essential to quantify the uncertainty associated with the distribution. Usually 90 and 95% confidence intervals are computed for material properties. Failure properties are then computed with the confidence bounds. Best estimates and the confidence bounds on the best estimate of the cumulative probability function for R-S (strength - stress) are plotted. The methodologies and the results from these analyses will be discussed in the presentation.

Murthy, Pappu L. N.↗
NASA NTRS2003

Towards a Probabilistic Preliminary Design Criterion for Buckling Critical Composite Shells

A probability-based analysis method for predicting buckling loads of compression-loaded laminated-composite shells is presented, and its potential as a basis for a new shell-stability design criterion is demonstrated and discussed. In particular, a database containing information about specimen geometry, material properties, and measured initial geometric imperfections for a selected group of laminated-composite cylindrical shells is used to calculate new buckling-load "knockdown factors". These knockdown factors are shown to be substantially improved, and hence much less conservative than the corresponding deterministic knockdown factors that are presently used by industry. The probability integral associated with the analysis is evaluated by using two methods; that is, by using the exact Monte Carlo method and by using an approximate First-Order Second- Moment method. A comparison of the results from these two methods indicates that the First-Order Second-Moment method yields results that are conservative for the shells considered. Furthermore, the results show that the improved, reliability-based knockdown factor presented always yields a safe estimate of the buckling load for the shells examined.

Arbocz, Johann↗
NASA NTRS1992

Probabilistic design applications for the Space Transportation Main Engines

All of the current rocket engine designs are based on deterministic design analysis methods. The most recently designed engine, Space Shuttle Main Engines (SSME), was designed and developed using these techniques in the 1970's and 80's. The Space Transportation Main Engine (STME) design objective is to use a robust design methodology and to pro-actively assess and improve the design during the design process. The design approach is a combination of the traditional deterministic methodologies and recently developed probabilistic methodologies. The designer must use a more rigorous structural criteria, conduct pro-active reliability assessments (reliability allocations, failure modes and effects analysis, reliability growth studies, and design reliability assessment), use a damage tolerant design philosophy and perform probabilistic analyses. Rigorous application of this structured methodology will develop a better engine product.

Ohara, Kevin↗
NASA NTRS1990

An improved approach for flight readiness assessment

An improved methodology for quantitatively evaluating failure risk for a spaceflight system in order to assess flight readiness is presented. This methodology is of particular value when information relevant to failure prediction, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is limited. In this approach, engineering analysis models that characterize specific failure modes based on the physics and mechanics of the failure phenomena are used in a prescribed probabilistic structure to generate a failure probability distribution that is modified by test and flight experience in a Bayesian statistical procedure. The probabilistic structure and statistical methodology are generally applicable to any failure mode for which quantitative engineering analysis can be employed to characterize the failure phenomenon and are particularly well suited for use under the constraints on information availability that are typical of such spaceflight systems as the Space Shuttle and planetary spacecraft.

Moore, N. R.↗
NASA NTRS1982

Analysis of backward error recovery for concurrent processes with recovery blocks

Three different methods of implementing recovery blocks (RB's). These are the asynchronous, synchronous, and the pseudo recovery point implementations. Pseudo recovery points so that unbounded rollback may be avoided while maintaining process autonomy are proposed. Probabilistic models for analyzing these three methods under standard assumptions in computer performance analysis, i.e., exponential distributions for related random variables were developed. The interval between two successive recovery lines for asynchronous RB's mean loss in computation power for the synchronized method, and additional overhead and rollback distance in case PRP's are used were estimated.

Shin, K. G.↗
NASA NTRS2014

Aviation Safety Risk Modeling: Lessons Learned From Multiple Knowledge Elicitation Sessions

Aviation safety risk modeling has elements of both art and science. In a complex domain, such as the National Airspace System (NAS), it is essential that knowledge elicitation (KE) sessions with domain experts be performed to facilitate the making of plausible inferences about the possible impacts of future technologies and procedures. This study discusses lessons learned throughout the multiple KE sessions held with domain experts to construct probabilistic safety risk models for a Loss of Control Accident Framework (LOCAF), FLightdeck Automation Problems (FLAP), and Runway Incursion (RI) mishap scenarios. The intent of these safety risk models is to support a portfolio analysis of NASA's Aviation Safety Program (AvSP). These models use the flexible, probabilistic approach of Bayesian Belief Networks (BBNs) and influence diagrams to model the complex interactions of aviation system risk factors. Each KE session had a different set of experts with diverse expertise, such as pilot, air traffic controller, certification, and/or human factors knowledge that was elicited to construct a composite, systems-level risk model. There were numerous "lessons learned" from these KE sessions that deal with behavioral aggregation, conditional probability modeling, object-oriented construction, interpretation of the safety risk results, and model verification/validation that are presented in this paper.

Luxhoj, J. T.↗
NASA NTRS1992

Space transportation architecture: Reliability sensitivities

A sensitivity analysis is given of the benefits and drawbacks associated with a proposed Earth to orbit vehicle architecture. The architecture represents a fleet of six vehicles (two existing, four proposed) that would be responsible for performing various missions as mandated by NASA and the U.S. Air Force. Each vehicle has a prescribed flight rate per year for a period of 31 years. By exposing this fleet of vehicles to a probabilistic environment where the fleet experiences failures, downtimes, setbacks, etc., the analysis involves determining the resiliency and costs associated with the fleet of specific vehicle/subsystem reliabilities. The resources required were actual observed data on the failures and downtimes associated with existing vehicles, data based on engineering judgement for proposed vehicles, and the development of a sensitivity analysis program.

Williams, A. M.↗
NASA NTRSDate not supplied

Spaceflight Over the Last Ten Years: Failures and Fix-ups 2013 - 2022 RAMS XV Conference

This project is an overview and analysis of the past ten years (2013 – present) in global spaceflight, highlighting the orbital launches of countries, particularly the failures that occurred, the reasons they occurred, and a breakdown of the related statistics and background information. The analysis is conducted from a perspective of reliability and maintainability engineering and Probabilistic Risk Assessment (PRA) to formulate a quantifiable understanding of the data and how it is pertinent to Safety and Mission Assurance (SMA) in spaceflight. There is a breakdown by country or group, timelines, and number of launches. The failures over the years are categorized, all given a broad analysis of subsystem failures and details of events. A few failures are given a more in-depth analysis of root causes and failure modes determined by their unique or common nature. The data is retrieved from online, publicly available sources.

Quinn Slaugenhoupt↗
DOE OSTI2025

Probabilistic Predictions for Fastener Failure in the Sandia Mechanics Challenge Using the Discrete-Direct Uncertainty Quantification Approach

This paper documents the blind and post-blind analysis predictions for the 2023 Sandia Mechanics Challenge (SMC), which involved predicting the behavior of a threaded fastener joint structure subjected to shock loading. Utilizing repeat sets of fastener calibration data from various experimental configurations including tension, double shear, and joint tension, we developed a library of calibrated models which were propagated through the application model using the Discrete-Direct (DD) uncertainty quantification (UQ) approach. Although the initial blind predictions did not incorporate spare-sample processing to quantify fastener failure probabilities, the analyses yielded reasonable conclusions aligned with experimental results. In the post-blind analysis phase, we focused on enhancing the fidelity of the aluminum constitutive model and innovating the DD approach to obtain probabilistic predictions for fastener failure, particularly when quantities of interest (QoIs) approach their bounds. The improved aluminum model captures the behavior of the cantilever under shock loading more accurately, predicting both partial and complete cracks, although it tends to underpredict failure propagation. The enhanced DD approach facilitates probabilistic predictions that reflect the interdependent failure mechanisms of the fasteners and the cantilever, revealing that while certain fasteners are more likely to fail, the failure does not necessarily follow a progressive pattern. Overall, the post-blind analyses significantly improved the predictive capabilities of the model, providing valuable insights into the SMC application and establishing a robust foundation for informed engineering decisions. The methodology demonstrates a cost-effective and extensible approach suitable for a wide range of applications, highlighting the importance of uncertainty quantification to provide context for engineering decision making.

42 ENGINEERING↗
NASA NTRS1990

EDNA: Expert fault digraph analysis using CLIPS

Traditionally fault models are represented by trees. Recently, digraph models have been proposed (Sack). Digraph models closely imitate the real system dependencies and hence are easy to develop, validate and maintain. However, they can also contain directed cycles and analysis algorithms are hard to find. Available algorithms tend to be complicated and slow. On the other hand, the tree analysis (VGRH, Tayl) is well understood and rooted in vast research effort and analytical techniques. The tree analysis algorithms are sophisticated and orders of magnitude faster. Transformation of a digraph (cyclic) into trees (CLP, LP) is a viable approach to blend the advantages of the representations. Neither the digraphs nor the trees provide the ability to handle heuristic knowledge. An expert system, to capture the engineering knowledge, is essential. We propose an approach here, namely, expert network analysis. We combine the digraph representation and tree algorithms. The models are augmented by probabilistic and heuristic knowledge. CLIPS, an expert system shell from NASA-JSC will be used to develop a tool. The technique provides the ability to handle probabilities and heuristic knowledge. Mixed analysis, some nodes with probabilities, is possible. The tool provides graphics interface for input, query, and update. With the combined approach it is expected to be a valuable tool in the design process as well in the capture of final design knowledge.

Dixit, Vishweshwar V.↗
NASA NTRS1997

Probabilistic Micromechanics and Macromechanics for Ceramic Matrix Composites

The properties of ceramic matrix composites (CMC's) are known to display a considerable amount of scatter due to variations in fiber/matrix properties, interphase properties, interphase bonding, amount of matrix voids, and many geometry- or fabrication-related parameters, such as ply thickness and ply orientation. This paper summarizes preliminary studies in which formal probabilistic descriptions of the material-behavior- and fabrication-related parameters were incorporated into micromechanics and macromechanics for CMC'S. In this process two existing methodologies, namely CMC micromechanics and macromechanics analysis and a fast probability integration (FPI) technique are synergistically coupled to obtain the probabilistic composite behavior or response. Preliminary results in the form of cumulative probability distributions and information on the probability sensitivities of the response to primitive variables for a unidirectional silicon carbide/reaction-bonded silicon nitride (SiC/RBSN) CMC are presented. The cumulative distribution functions are computed for composite moduli, thermal expansion coefficients, thermal conductivities, and longitudinal tensile strength at room temperature. The variations in the constituent properties that directly affect these composite properties are accounted for via assumed probabilistic distributions. Collectively, the results show that the present technique provides valuable information about the composite properties and sensitivity factors, which is useful to design or test engineers. Furthermore, the present methodology is computationally more efficient than a standard Monte-Carlo simulation technique; and the agreement between the two solutions is excellent, as shown via select examples.

Murthy, Pappu L. N.↗
NASA NTRS2007

Accounting for Uncertainties in Strengths of SiC MEMS Parts

A methodology has been devised for accounting for uncertainties in the strengths of silicon carbide structural components of microelectromechanical systems (MEMS). The methodology enables prediction of the probabilistic strengths of complexly shaped MEMS parts using data from tests of simple specimens. This methodology is intended to serve as a part of a rational basis for designing SiC MEMS, supplementing methodologies that have been borrowed from the art of designing macroscopic brittle material structures. The need for this or a similar methodology arises as a consequence of the fundamental nature of MEMS and the brittle silicon-based materials of which they are typically fabricated. When tested to fracture, MEMS and structural components thereof show wide part-to-part scatter in strength. The methodology involves the use of the Ceramics Analysis and Reliability Evaluation of Structures Life (CARES/Life) software in conjunction with the ANSYS Probabilistic Design System (PDS) software to simulate or predict the strength responses of brittle material components while simultaneously accounting for the effects of variability of geometrical features on the strength responses. As such, the methodology involves the use of an extended version of the ANSYS/CARES/PDS software system described in Probabilistic Prediction of Lifetimes of Ceramic Parts (LEW-17682-1/4-1), Software Tech Briefs supplement to NASA Tech Briefs, Vol. 30, No. 9 (September 2006), page 10. The ANSYS PDS software enables the ANSYS finite-element-analysis program to account for uncertainty in the design-and analysis process. The ANSYS PDS software accounts for uncertainty in material properties, dimensions, and loading by assigning probabilistic distributions to user-specified model parameters and performing simulations using various sampling techniques.

Nemeth, Noel↗