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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 199 records · Page 11

Engine System Model Development for Nuclear Thermal Propulsion

In order to design, analyze, and evaluate conceptual Nuclear Thermal Propulsion (NTP) engine systems, an improved NTP design and analysis tool has been developed. The NTP tool utilizes the Rocket Engine Transient Simulation (ROCETS) system tool and many of the routines from the Enabler reactor model found in Nuclear Engine System Simulation (NESS). Improved non-nuclear component models and an external shield model were added to the tool. With the addition of a nearly complete system reliability model, the tool will provide performance, sizing, and reliability data for NERVA-Derived NTP engine systems. A new detailed reactor model is also being developed and will replace Enabler. The new model will allow more flexibility in reactor geometry and include detailed thermal hydraulics and neutronics models. A description of the reactor, component, and reliability models is provided. Another key feature of the modeling process is the use of comprehensive spreadsheets for each engine case. The spreadsheets include individual worksheets for each subsystem with data, plots, and scaled figures, making the output very useful to each engineering discipline. Sample performance and sizing results with the Enabler reactor model are provided including sensitivities. Before selecting an engine design, all figures of merit must be considered including the overall impacts on the vehicle and mission. Evaluations based on key figures of merit of these results and results with the new reactor model will be performed. The impacts of clustering and external shielding will also be addressed. Over time, the reactor model will be upgraded to design and analyze other NTP concepts with CERMET and carbide fuel cores.

Nelson, Karl W.↗

Design Strategy for a Formally Verified Reliable Computing Platform

This paper presents a high-level design for a reliable computing platform for real-time control applications. The design tradeoffs and analyses related to the development of a formally verified reliable computing platform are discussed. The design strategy advocated in this paper requires the use of techniques that can be completely characterized mathematically as opposed to more powerful or more flexible algorithms whose performance properties can only be analyzed by simulation and testing. The need for accurate reliability models that can be related to the behavior models is also stressed. Tradeoffs between reliability and voting complexity are explored. In particular, the transient recovery properties of the system are found to be fundamental to both the reliability analysis as well as the "correctness" models.

Butler, Ricky W.↗

Method of Testing and Predicting Failures of Electronic Mechanical Systems

A method employing a knowledge base of human expertise comprising a reliability model analysis implemented for diagnostic routines is disclosed. The reliability analysis comprises digraph models that determine target events created by hardware failures human actions, and other factors affecting the system operation. The reliability analysis contains a wealth of human expertise information that is used to build automatic diagnostic routines and which provides a knowledge base that can be used to solve other artificial intelligence problems.

Iverson, David L.↗

Statistical modelling of software reliability

During the six-month period from 1 April 1991 to 30 September 1991 the following research papers in statistical modeling of software reliability appeared: (1) A Nonparametric Software Reliability Growth Model; (2) On the Use and the Performance of Software Reliability Growth Models; (3) Research and Development Issues in Software Reliability Engineering; (4) Special Issues on Software; and (5) Software Reliability and Safety.

Miller, Douglas R.↗

Computer Reliability

Using a NASA developed program, Dr. J. Walter Bond is creating a course in computer reliability modeling. The course will examine three different computer programs, one of them NASA's Care III, the others UCLA's Aries 78 and Aries 82. All three are designed to help estimate the reliability of complex, redundant, fault tolerant system. In computer design, software of this kind can predict or model the effects of various hardware or software failures, a process called reliability modeling.

Source record↗

Automated ultrareliability models - A review

Analytic models are required to assess the reliability of systems designed to ultrareliability requirements. This paper reviews the capabilities and limitations of five currently available automated reliability models which are applicable to fault-tolerant flight control systems. 'System' includes sensors, computers, and actuators. A set of review criteria including validation, configuration adaptability, and resource requirements for model evaluation are described. Five models, ARIES, CARE II, CARE III, CARSRA, and CAST, are assessed against the criteria, thereby characterizing their capabilities and limitations. This review should be helpful to potential users of the models.

Bridgman, M. S.↗

Design for Reliability (DfR) in Space Life Support

The engineering process of Design for Reliability (DfR) is well established in the automotive and aerospace industries. DfR should be useful in the future development of space life support systems. DfR is a sequence of tasks that develop system requirements and plan reliability analysis and testing. First and fundamentally, the reliability requirement is defined. Next the system reliability model is developed, often using a reliability block diagram. The overall system reliability requirement is allocated to the subsystems and an estimate of the attainable reliability is made. This expected reliability can be improved by simplifying the design by removing components or by replacing less reliable components. Improving reliability can require difficult compromises, such as reducing performance requirements, increasing budget, or extending testing. The actual system reliability can be determined only by testing, which should continue long enough to provide the required confidence in the measured value. New systems often have unexpected design errors that cause failures in early testing. The usual reliability improvement process of testing, finding the failure modes, and redesigning to remove them reduces the failure rate and is referred to as “reliability growth.” After redesign has been completed, the system should be further tested to determine the actual achieved reliability more accurately. If the final system failure rate is too high, redundant systems can be used to improve overall operational reliability. Adding redundancy simply to increase the one- or two-fault tolerance metric may sometimes reduce reliability. Reliability can be improved in three ways: redesigning the system to include more reliable subsystems and components, reliability growth testing and failure mode removal, and by using parallel redundant systems. DfR should combine these approaches to achieve the required reliability while managing performance, cost, and schedule.

Reliability↗

Design for Reliability (DfR) in Space Life Support

The engineering process of Design for Reliability (DfR) is well established in the automotive and aerospace industries. DfR should be useful in the future development of space life support systems. DfR is a sequence of tasks that develop system requirements and plan reliability analysis and testing. First and fundamentally, the reliability requirement is defined. Next the system reliability model is developed, often using a reliability block diagram. The overall system reliability requirement is allocated to the subsystems and an estimate of the attainable reliability is made. This expected reliability can be improved by simplifying the design by removing components or by replacing less reliable components. Improving reliability can require difficult compromises, such as reducing performance requirements, increasing budget, or extending testing. The actual system reliability can be determined only by testing, which should continue long enough to provide the required confidence in the measured value. New systems often have unexpected design errors that cause failures in early testing. The usual reliability improvement process of testing, finding the failure modes, and redesigning to remove them reduces the failure rate and is referred to as “reliability growth.” After redesign has been completed, the system should be further tested to determine the actual achieved reliability more accurately. If the final system failure rate is too high, redundant systems can be used to improve overall operational reliability. Adding redundancy simply to increase the one- or two-fault tolerance metric may sometimes reduce reliability. Reliability can be improved in three ways: redesigning the system to include more reliable subsystems and components, reliability growth testing and failure mode removal, and by using parallel redundant systems. DfR should combine these approaches to achieve the required reliability while managing performance, cost, and schedule.

Reliability↗

Loss Landscape Analysis for Reliable Quantized ML Models for Scientific Sensing

In this paper, we propose a method to perform empirical analysis of the loss landscape of machine learning (ML) models. The method is applied to two ML models for scientific sensing, which necessitates quantization to be deployed and are subject to noise and perturbations due to experimental conditions. Our method allows assessing the robustness of ML models to such effects as a function of quantization precision and under different regularization techniques -- two crucial concerns that remained underexplored so far. By investigating the interplay between performance, efficiency, and robustness by means of loss landscape analysis, we both established a strong correlation between gently-shaped landscapes and robustness to input and weight perturbations and observed other intriguing and non-obvious phenomena. Our method allows a systematic exploration of such trade-offs a priori, i.e., without training and testing multiple models, leading to more efficient development workflows. This work also highlights the importance of incorporating robustness into the Pareto optimization of ML models, enabling more reliable and adaptive scientific sensing systems.

Baldi, Tommaso [Pisa, Scuola Normale Superiore]↗

An Improved Model of the Crustal Structure of Mars

The first reliable model of the structure of the crust and upper mantle of Mars from remote observations was produced using data from the Mars Orbiter Laser Altimeter (MOLA) and the Radio Science investigation of Mars Global Surveyor (MGS). That model assumed a uniform crustal density and solved for the global variations in crustal thickness using a gravity field derived from preliminary MGS tracking. In that study, spherical harmonic potential coefficients were derived to degree and order 80, but crustal structure was interpreted cautiously to degree 60, or 360 km wavelength, owing to the presence of noise. Tracking normal equations have since been generated to degree 75, to degree 80 (supplemented by altimetric crossovers), and recently to degree 90, using new constants for the orientation of the spin pole and the rotation rate of Mars provided by the IAU2000 rotation model. Gravity models now incorporate tracking data coverage from the Primary and Extended MGS missions and the early phases of the Mars Odyssey mission. In the present study we exploit these advances in gravity modeling to present a refined crustal inversion, which we also interpret in the context of Mars' internal structure and thermal evolution.

Zuber, M. T.↗

The conservativeness of reliability estimates based on instantaneous coverage

Reliability modeling must take into account two different types of phenomena, including the fault-occurrence behavior and the fault/error-handling behavior of a system. The effectiveness of the fault/error-handling behavior can be captured by instantaneous coverage probabilities. This paper has the objective to show that the assumption of instantaneous coverage leads to conservative predictions of system reliability for systems characterized by relatively long interevent times for fault occurrences and relatively short interevent times for fault/error-handling actions. The importance of this result is related to the fact that it can now be shown that model predictions based on instantaneous coverage are lower bounds on the true system reliability. Attention is given to a semi-Markov reliability model, instantaneous coverage approximations, the proof of conservative prediction, and the computation of coverage probabilities.

Mcgough, J.↗

Reliability and availability modeling of coupled communication networks - A simplified modeling approach

The network-complexity of LANs and of LANs that are interconnected by bridges and routers poses a challenging reliability-modeling problem. The present effort toward these problems' solution attempts to simplify them by reducing their number of states through truncation and state merging, as suggested by Shooman and Laemmel (1990). Through the use of state merging, it becomes possible to reduce the Bateman-Cortes 161 state model to a two state model with a closed-form solution. In the case of coupled networks, a technique which allows for problem-decomposition must be used.

Shooman, Martin L.↗

Reliability and Maintainability model (RAM) user and maintenance manual

This report documents the procedures for utilizing and maintaining the Reliability and Maintainability Model (RAM) developed by the University of Dayton for the NASA Langley Research Center (LaRC). The RAM model predicts reliability and maintainability (R&M) parameters for conceptual space vehicles using parametric relationships between vehicle design and performance characteristics and subsystem mean time between maintenance actions (MTBM) and manhours per maintenance action (MH/MA). These parametric relationships were developed using aircraft R&M data from over thirty different military aircraft of all types. This report describes the general methodology used within the model, the execution and computational sequence, the input screens and data, the output displays and reports, and study analyses and procedures. A source listing is provided.

Ebeling, Charles E.↗

A study of fault prediction and reliability assessment in the SEL environment

An empirical study on estimation and prediction of faults, prediction of fault detection and correction effort, and reliability assessment in the Software Engineering Laboratory environment (SEL) is presented. Fault estimation using empirical relationships and fault prediction using curve fitting method are investigated. Relationships between debugging efforts (fault detection and correction effort) in different test phases are provided, in order to make an early estimate of future debugging effort. This study concludes with the fault analysis, application of a reliability model, and analysis of a normalized metric for reliability assessment and reliability monitoring during development of software.

Basili, Victor R.↗

Thermophysical Property Measurements of Molten Semiconductors in 1-g and Reduced-g Condition

Understanding and controlling the formation kinetics of varieties of crystal imperfections such as point defects, non uniform distribution of doping atoms, and impurity atoms in growing crystals are very important. Theoretical (numerical) modeling of the crystal growth process is an essential step to achieving these objectives. In order to obtain reliable modeling results, input parameters, i.e. various thermophysical parameters, must be accurate. The importance of accurate thermophysical properties of semiconductors in crystal growth cannot be overly emphasized. The total hemispherical emissivity, for instance, has a dramatic impact on the thermal environment. It determines the radiative emission from the surface of the melt which determines to a large extent the profile of the solidified crystal. In order to understand the convection and the turbulence in a melt, viscosity becomes an important parameter. The liquid surface tension determines the shape of the liquid-atmosphere interface near the solid-liquid-atmosphere triple point. Currently used values for these parameters are rather inaccurate, and this program intends to provide more reliable measurements of these thermophysical properties. Thus, the objective of this program is in the accurate measurements of various thermophysical properties which can be reliably used in the modeling of various crystal growth processes. In this program, thermophysical properties of molten semiconductors, such as Si, Ge, Si-Ge, and InSb will be measured as a function of temperature using the High Temperature Electrostatic Levitator at JPL. Each material will be doped by different kinds of impurities at various doping levels. Thermophysical properties which will be measured include: density, thermal expansion coefficient, surface tension, viscosity, specific heat, hemispherical total emissivity, and perhaps electrical and thermal conductivities. Many molten semiconductors are chemically reactive with crucibles. As a result, these dispersed impurities in the melts tend to substantially modify the properties of pure semiconductors. Sample levitation done in a vacuum clearly helps maintain the sample purity. However, in the 1-g environment, all gravity caused effects such as convection, sedimentation and buoyancy are still present in the sample. In addition, large forces needed to levitate a sample in the presence of the gravity can cause additional flows in the melt. The use of the High Temperature Electrostatic Levitator (HTESL) for the present research is a recent development and little is known about the flows induced by the electrostatic forces. In this ground base program, we will define the limits of HTESL technology as various thermophysical properties of molten semiconductors are measured.

Rhim, Won-Kyu↗

Automated model generation for reliability analysis programs

Semi-Markov models (a generalization of Markov models) can be used to calculate the reliability of virtually any fault-tolerant system. However, the process of delineating all of the states and transitions in the model of a complex system can be devastatingly tedious and error-prone. The ASSIST program allows the user to describe the semi-Markov model in a high-level language. Instead of specifying the individual states of the model, the user specifies the rules governing the behavior of the system, and these are used by ASSIST to automatically generate the model. A small number of statements in the abstract language can be used to describe a very large, complex model. Because no assumptions are made about the system being modeled, the ASSIST program can be used to generate models describing the behavior of any type of system. The ASSIST program and its input language are described and illustrated by examples.

Johnson, Sally C.↗

Composite Overwrapped Pressure Vessels (COPV): Flight Rationale for the Space Shuttle Program

Each Orbiter Vehicle (Space Shuttle Program) contains up to 24 Kevlar49/Epoxy Composite Overwrapped Pressure Vessels (COPV) for storage of pressurized gases. In the wake of the Columbia accident and the ensuing Return To Flight (RTF) activities, Orbiter engineers reexamined COPV flight certification. The original COPV design calculations were updated to include recently declassified Kevlar COPV test data from Lawrence Livermore National Laboratory (LLNL) and to incorporate changes in how the Space Shuttle was operated as opposed to orinigially envisioned. 2005 estimates for the probability of a catastrophic failure over the life of the program (from STS-1 through STS-107) were one-in-five. To address this unacceptable risk, the Orbiter Project Office (OPO) initiated a comprehensive investigation to understand and mitigate this risk. First, the team considered and eventually deemed unfeasible procuring and replacing all existing flight COPVs. OPO replaced the two vessels with the highest risk with existing flight spare units. Second, OPO instituted operational improvements in ground procedures to signficiantly reduce risk, without adversely affecting Shuttle capability. Third, OPO developed a comprehensive model to quantify the likelihood of occurrance. A fully-instrumented burst test (recording a lower burst pressure than expected) on a flight-certified vessel provided critical understanding of the behavior of Orbiter COPVs. A more accurate model was based on a newly-compiled comprehensive database of Kevlar data from LLNL and elsewhere. Considering hardware changes, operational improvements and reliability model refinements, the mean reliability was determined to be 0.998 for the remainder of the Shuttle Program (from 2007, for STS- 118 thru STS-135). Since limited hardware resources precluded full model validation through multiple tests, additional model confidence was sought through the first-ever Accelerated Stress Rupture Test (ASRT) of a flown flight article. A Bayesian statistical approach was developed to interpret possible test results. Since the lifetime observed in the ASRT exceeded initial estimates by one to two orders of magnitude, the Space Shuttle Program deemed there was significant conservatism in the model and accepted continued operation with existing flight hardware. Given the variability in tank-to-tank original prooftest response, a non-destructive evaluation (NDE) technique utilizing Raman Spectroscopy was developed to directly measure COPV residual stress state. Preliminary results showed that patterns of low fiber elastic strains over the outside vessel surface, together with measured permanent volume growth during proof, could be directly correlated to increased fiber stress ratios on the inside fibers adjacent to the liner, and thus reduced reliability.

Kezirian, Michael T.↗