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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Model Based Engineering for Software Assurance

NASA's successful development of next generation space vehicles, habitats, and robotic systems will require reliable hardware and software systems. The aim of this initiative is to develop modeling methodology and tools to support Model-Based Systems Engineering (MBSE) for software assurance and reliability analysis. This effort expands the Unified Modeling Language (UML) software design models to include fault data for the extraction of Failure Modes and Effects Criticality Analysis (FMECA) and Fault Tree Analysis (FTA) for software. We explored different modeling approaches to integrate the UML software design models with the Systems Modeling Language (SysML) system models to generate an integrated model and reliability tools that take into account software and hardware interfaces.The benefits of this concept directly affect the safety community with quick turnarounds to produce software assurance and reliability analysis artifacts and the ability to visualize failure effects, both hardware and software. The result is enhanced system design integrity and early identification of system risks. This initiative will enable software assurance activities early in the system design lifecycle, facilitating the discovery of design weaknesses and enhancing the capability to produce safe, hazard-free systems

Wang, Lui↗
NASA NTRS2007

Automated Diagnosis and Control of Complex Systems

Livingstone2 is a reusable, artificial intelligence (AI) software system designed to assist spacecraft, life support systems, chemical plants, or other complex systems by operating with minimal human supervision, even in the face of hardware failures or unexpected events. The software diagnoses the current state of the spacecraft or other system, and recommends commands or repair actions that will allow the system to continue operation. Livingstone2 is an enhancement of the Livingstone diagnosis system that was flight-tested onboard the Deep Space One spacecraft in 1999. This version tracks multiple diagnostic hypotheses, rather than just a single hypothesis as in the previous version. It is also able to revise diagnostic decisions made in the past when additional observations become available. In such cases, Livingstone might arrive at an incorrect hypothesis. Re-architecting and re-implementing the system in C++ has increased performance. Usability has been improved by creating a set of development tools that is closely integrated with the Livingstone2 engine. In addition to the core diagnosis engine, Livingstone2 includes a compiler that translates diagnostic models written in a Java-like language into Livingstone2's language, and a broad set of graphical tools for model development.

Kurien, James↗
NASA NTRS2005

Assessing the Relative Risk of Aerocapture Using Probabalistic Risk Assessment

A recent study performed for the Aerocapture Technology Area in the In-Space Propulsion Technology Projects Office at the Marshall Space Flight Center investigated the relative risk of various capture techniques for Mars missions. Aerocapture has been proposed as a possible capture technique for future Mars missions but has been perceived by many in the community as a higher risk option as compared to aerobraking and propulsive capture. By performing a probabilistic risk assessment on aerocapture, aerobraking and propulsive capture, a comparison was made to uncover the projected relative risks of these three maneuvers. For mission planners, this knowledge will allow them to decide if the mass savings provided by aerocapture warrant any incremental risk exposure. The study focuses on a Mars Sample Return mission currently under investigation at the Jet Propulsion Laboratory (JPL). In each case (propulsive, aerobraking and aerocapture), the Earth return vehicle is inserted into Martian orbit by one of the three techniques being investigated. A baseline spacecraft was established through initial sizing exercises performed by JPL's Team X. While Team X design results provided the baseline and common thread between the spacecraft, in each case the Team X results were supplemented by historical data as needed. Propulsion, thermal protection, guidance, navigation and control, software, solar arrays, navigation and targeting and atmospheric prediction were investigated. A qualitative assessment of human reliability was also included. Results show that different risk drivers contribute significantly to each capture technique. For aerocapture, the significant drivers include propulsion system failures and atmospheric prediction errors. Software and guidance hardware contribute the most to aerobraking risk. Propulsive capture risk is mainly driven by anomalous solar array degradation and propulsion system failures. While each subsystem contributes differently to the risk of each technique, results show that there exists little relative difference in the reliability of these capture techniques although uncertainty for the aerocapture estimates remains high given the lack of in-space demonstration.

Percy, Thomas K.↗
NASA NTRS1994

Software fault tolerance in computer operating systems

This chapter provides data and analysis of the dependability and fault tolerance for three operating systems: the Tandem/GUARDIAN fault-tolerant system, the VAX/VMS distributed system, and the IBM/MVS system. Based on measurements from these systems, basic software error characteristics are investigated. Fault tolerance in operating systems resulting from the use of process pairs and recovery routines is evaluated. Two levels of models are developed to analyze error and recovery processes inside an operating system and interactions among multiple instances of an operating system running in a distributed environment. The measurements show that the use of process pairs in Tandem systems, which was originally intended for tolerating hardware faults, allows the system to tolerate about 70% of defects in system software that result in processor failures. The loose coupling between processors which results in the backup execution (the processor state and the sequence of events occurring) being different from the original execution is a major reason for the measured software fault tolerance. The IBM/MVS system fault tolerance almost doubles when recovery routines are provided, in comparison to the case in which no recovery routines are available. However, even when recovery routines are provided, there is almost a 50% chance of system failure when critical system jobs are involved.

Iyer, Ravishankar K.↗
NASA NTRS2007

A Procedure for Modeling Structural Component/Attachment Failure Using Transient Finite Element Analysis

Structures often comprise smaller substructures that are connected to each other or attached to the ground by a set of finite connections. Under static loading one or more of these connections may exceed allowable limits and be deemed to fail. Of particular interest is the structural response when a connection is severed (failed) while the structure is under static load. A transient failure analysis procedure was developed by which it is possible to examine the dynamic effects that result from introducing a discrete failure while a structure is under static load. The failure is introduced by replacing a connection load history by a time-dependent load set that removes the connection load at the time of failure. The subsequent transient response is examined to determine the importance of the dynamic effects by comparing the structural response with the appropriate allowables. Additionally, this procedure utilizes a standard finite element transient analysis that is readily available in most commercial software, permitting the study of dynamic failures without the need to purchase software specifically for this purpose. The procedure is developed and explained, demonstrated on a simple cantilever box example, and finally demonstrated on a real-world example, the American Airlines Flight 587 (AA587) vertical tail plane (VTP).

Lovejoy, Andrew E.↗
NASA NTRS1992

System for Anomaly and Failure Detection (SAFD) system development

This task specified developing the hardware and software necessary to implement the System for Anomaly and Failure Detection (SAFD) algorithm, developed under Technology Test Bed (TTB) Task 21, on the TTB engine stand. This effort involved building two units; one unit to be installed in the Block II Space Shuttle Main Engine (SSME) Hardware Simulation Lab (HSL) at Marshall Space Flight Center (MSFC), and one unit to be installed at the TTB engine stand. Rocketdyne personnel from the HSL performed the task. The SAFD algorithm was developed as an improvement over the current redline system used in the Space Shuttle Main Engine Controller (SSMEC). Simulation tests and execution against previous hot fire tests demonstrated that the SAFD algorithm can detect engine failure as much as tens of seconds before the redline system recognized the failure. Although the current algorithm only operates during steady state conditions (engine not throttling), work is underway to expand the algorithm to work during transient condition.

Oreilly, D.↗
NASA NTRS1990

DEPEND - A design environment for prediction and evaluation of system dependability

The development of DEPEND, an integrated simulation environment for the design and dependability analysis of fault-tolerant systems, is described. DEPEND models both hardware and software components at a functional level, and allows automatic failure injection to assess system performance and reliability. It relieves the user of the work needed to inject failures, maintain statistics, and output reports. The automatic failure injection scheme is geared toward evaluating a system under high stress (workload) conditions. The failures that are injected can affect both hardware and software components. To illustrate the capability of the simulator, a distributed system which employs a prediction-based, dynamic load-balancing heuristic is evaluated. Experiments were conducted to determine the impact of failures on system performance and to identify the failures to which the system is especially susceptible.

Goswami, Kumar K.↗
DOE OSTI2022

GridDS: Data Science Toolkit for Energy Grid Data

According to the U.S. Energy Information Administration (EIA), the demand for energy is expected to increase 50% by the year 20501. While energy standards, such as the Institute of Electrical and Electronics Engineers (IEEE) Standard 1547, (Basso 2015) and monitoring with wide area management systems (WAMS) (Liu 2017, Zhou 2016) have enabled large scale data collection and storage, the application of this data in mitigating costs associated with increased consumer demand is an ongoing focus for energy research. This ubiquitous data collection presents a promising opportunity for machine learning and data science to improve efficiency of distributed energy resources (DERs). The GridDS software toolkit is designed to leverage advanced metering infrastructure (AMI), outage management systems data (OMS), Supervisory control Data Acquisition (SCADA), and geographic information systems (GIS) to forecast future energy demands and detect incipient grid failures. GridDS is a python software library designed to be modular and generalizable to data recorded by DERs. In adapting to disparate datasets recorded by various WAMS, GridDS provides a range of unique functionality not presently implemented in current WAMS which have highly specific software infrastructure by design. GridDS functionality ranges from data specification and preparation, to training and validation for state of the art machine learning, to interactive data visualization. For data intake, GridDS combines: Pandera: a library for creating data specifications. TimeScaleDB: a postgresSQL database infrastructure for efficient storage of timeseries data. Dataset class: A custom dataset class / interface that ensures modularity between a range of synthetic and live recorded datasets. Is

Ladd, Alexander↗
DOE OSTI2021

Concurrent Optimization of Capital Cost and Expected O&M

Concentrating solar power (CSP) technologies can utilize heat from concentrated sunlight from a field of tracking mirrors to generate electricity, reform fuel, provide process heat, or augment fossil plant heat sources. Electricity-generating power tower systems focus light from thousands of independent heliostats onto a thermal receiver, which uses the focused light to warm a heat transfer fluid (HTF), typically, a molten nitrate salt. The HTF is then sent to a power generation cycle or diverted into thermal energy storage (TES) for later use. Thermal storage is – in principle – a straightforward proposition. However, optimal utilization of a TES resource is complex and multi-faceted: thermal energy may be dispatched to produce electricity immediately upon first availability, or thermal energy may be reserved for next-day peak periods at risk of filling storage and dumping energy, or a portion of the thermal energy can be reserved to maintain equipment temperatures, reducing power cycle startup time, etc. Many possible dispatch permutations variously emphasize producing peak power, operating through transients, expediting daily startup, etc. The best operation strategy can change day-to-day throughout the year, depending on the weather and market pricing forecasts. The project we describe in this report develops a software package that allows users to explore design optimization, operations decisions, and performance characterization of concentrating solar power tower plants. Users interface with the tool through a scripting language, and results are reported in time series tables, plots, runtime logs, and design outputs. Users choose from a list of variables such as tower height, solar multiple, design-point irradiance, thermal storage size, etc., and specify information about the system using a list of parameters. The software can then optimize the specified variables to reduce the cost of energy produced by the system while meeting certain production requirements, accounting for uncertain weather and electricity price forecasts, and correcting for equipment failures or repair time. The software we develop is the first comprehensive design tool of its kind to incorporate all of these aspects while being deployed as open source.

14 SOLAR ENERGY↗
NASA NTRS2008

Information Extraction for System-Software Safety Analysis: Calendar Year 2007 Year-End Report

This annual report describes work to integrate a set of tools to support early model-based analysis of failures and hazards due to system-software interactions. The tools perform and assist analysts in the following tasks: 1) extract model parts from text for architecture and safety/hazard models; 2) combine the parts with library information to develop the models for visualization and analysis; 3) perform graph analysis on the models to identify possible paths from hazard sources to vulnerable entities and functions, in nominal and anomalous system-software configurations; 4) perform discrete-time-based simulation on the models to investigate scenarios where these paths may play a role in failures and mishaps; and 5) identify resulting candidate scenarios for software integration testing. This paper describes new challenges in a NASA abort system case, and enhancements made to develop the integrated tool set.

Malin, Jane T.↗
NASA NTRS1984

A Fault Tolerant System for an Integrated Avionics Sensor Configuration

An aircraft sensor fault tolerant system methodology for the Transport Systems Research Vehicle in a Microwave Landing System (MLS) environment is described. The fault tolerant system provides reliable estimates in the presence of possible failures both in ground-based navigation aids, and in on-board flight control and inertial sensors. Sensor failures are identified by utilizing the analytic relationships between the various sensors arising from the aircraft point mass equations of motion. The estimation and failure detection performance of the software implementation (called FINDS) of the developed system was analyzed on a nonlinear digital simulation of the research aircraft. Simulation results showing the detection performance of FINDS, using a dual redundant sensor compliment, are presented for bias, hardover, null, ramp, increased noise and scale factor failures. In general, the results show that FINDS can distinguish between normal operating sensor errors and failures while providing an excellent detection speed for bias failures in the MLS, indicated airspeed, attitude and radar altimeter sensors.

Caglayan, A. K.↗
NASA NTRS1993

Enhanced methods for determining operational capabilities and support costs of proposed space systems

This report documents the work accomplished during the first two years of research to provide support to NASA in predicting operational and support parameters and costs of proposed space systems. The first year's research developed a methodology for deriving reliability and maintainability (R & M) parameters based upon the use of regression analysis to establish empirical relationships between performance and design specifications and corresponding mean times of failure and repair. The second year focused on enhancements to the methodology, increased scope of the model, and software improvements. This follow-on effort expands the prediction of R & M parameters and their effect on the operations and support of space transportation vehicles to include other system components such as booster rockets and external fuel tanks. It also increases the scope of the methodology and the capabilities of the model as implemented by the software. The focus is on the failure and repair of major subsystems and their impact on vehicle reliability, turn times, maintenance manpower, and repairable spares requirements. The report documents the data utilized in this study, outlines the general methodology for estimating and relating R&M parameters, presents the analyses and results of application to the initial data base, and describes the implementation of the methodology through the use of a computer model. The report concludes with a discussion on validation and a summary of the research findings and results.

Ebeling, Charles↗
NASA NTRS1990

PIE: A Dynamic Failure-Based Technique

This paper presents a dynamic technique for statistically estimating three program characteristics that affect a program's computational behavior: (1) the probability that a particular section of a program is executed, (2) the probability that the particular section affects the data state, and (3) the probability that a data state produced by that section has an effect on program output. These three characteristics can be used to predict whether faults are likely to be uncovered by software testing. Index Terms: Software testing, data state, fault, failure, testability. 1 Introduction

Voas, Jeffrey M.↗
NASA NTRS1989

NASA-LaRc Flight-Critical Digital Systems Technology Workshop

The outcome is documented of a Flight-Critical Digital Systems Technology Workshop held at NASA-Langley December 13 to 15 1988. The purpose of the workshop was to elicit the aerospace industry's view of the issues which must be addressed for the practical realization of flight-critical digital systems. The workshop was divided into three parts: an overview session; three half-day meetings of seven working groups addressing aeronautical and space requirements, system design for validation, failure modes, system modeling, reliable software, and flight test; and a half-day summary of the research issues presented by the working group chairmen. Issues that generated the most consensus across the workshop were: (1) the lack of effective design and validation methods with support tools to enable engineering of highly-integrated, flight-critical digital systems, and (2) the lack of high quality laboratory and field data on system failures especially due to electromagnetic environment (EME).

Meissner, C. W., Jr.↗
DOE OSTI2014

Workshop on Software Productivity for Extreme-scale Science, January 13-14, 2014, Hilton Hotel, Rockville, MD

While emerging extreme-scale computing systems provide unprecedented resources for scientific discovery, DOE’s scientific communities now face a crisis in extreme-scale scientific software productivity due to a powerful confluence of factors: ongoing disruptive changes in computer architectures and new frontiers in modeling, simulation, and analysis of complex multiscale and multiphysics phenomena. Research in mission-critical science and energy problems has become increasingly dependent on high-performance computing, but productivity in extreme-scale scientific application development has not kept pace. The principal issues are (1) a significant lag between extreme-scale hardware and algorithmic innovations and their effective use in applications, leading to poorly scaling codes; (2) obstacles in the combined use of independently developed software components; (3) lack of agile yet rigorous software engineering practices for high-performance computing; and (4) failure to consider the entire lifecycle of large scientific software efforts, leading to fragile, complicated application codes that are increasingly difficult to enhance.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2001

[Low Fidelity Simulation of a Zero-Y Robot]

The item to be cleared is a low-fidelity software simulation model of a hypothetical freeflying robot designed for use in zero gravity environments. This simulation model works with the HCC simulation system that was developed by Xerox PARC and NASA Ames Research Center. HCC has been previously cleared for distribution. When used with the HCC software, the model computes the location and orientation of the simulated robot over time. Failures (such as a broken motor) can be injected into the simulation to produce simulated behavior corresponding to the failure. Release of this simulation will allow researchers to test their software diagnosis systems by attempting to diagnose the simulated failure from the simulated behavior. This model does not contain any encryption software nor can it perform any control tasks that might be export controlled.

Sweet, Adam↗
NASA NTRS2001

Evolution of safety-critical requirements post-launch

This paper reports the results of a small study of requirements changes to the onboard software of three spacecraft subsequent to launch. Only those requirement changes that resulted from post-launch anoma-lies (i.e., during operations) were of interest here, since the goal was to better understand the relation-ship between critical anomalies during operations and how safety-critical requirements evolve. The results of the study were surprising in that anomaly-driven, post-launch requirements changes were rarely due to previous requirements having been incorrect. Instead, changes involved new requirements (1) for the software to handle rare events or (2) for the software to compensate for hardware failures or limitations. The prevalence of new requirements as a result of post-launch anomalies suggests a need for increased requirements-engineering support of maintenance activities in these systems. The results also confirm both the difficulty and the benefits of pursuing requirements completeness, especially in terms of fault tolerance, during development of critical systems.

Software requirements↗
DOE OSTI2019

Analyzing a Five-Year Failure Record of a Leadership-Class Supercomputer

Extreme-scale computing systems are required to solve some of the grand challenges in science and technology. From astrophysics to molecular biology, supercomputers are an essential tool to accelerate scientific discovery. However, large computing systems are prone to failures due to their complexity. It is crucial to develop an understanding of how these systems fail to design reliable supercomputing platforms for the future. This paper examines a five-year failure and workload record of a leadership-class supercomputer. To the best of our knowledge, five years represents the vast majority of the lifespan of a supercomputer. This is the first time such analysis is performed on a top 10 modern supercomputer. We performed a failure categorization and found out that: i) most errors are GPU-related, with roughly 37% of them being double-bit errors on the cards; ii) failures are not evenly spread across the physical machine, with room temperature presumably playing a major role; and iii) software errors of the system bring down several nodes concurrently. Our failure rate analysis unveils that: i) the system consistently degrades, being at least twice as reliable at the beginning, compared to the end of the period; ii) Weibull distribution closely fits the mean-time-between-failure data; and iii) hardware and software errors show a markedly different pattern. Finally, we correlated failure and workload records to reveal that: i) failure and workload records are weakly correlated, except for certain types of failures when segmented by the hours of the day; ii) several categories of failures make jobs crash within the first minutes of execution; and iii) a significant fraction of failed jobs exhaust the requested time with a disregard of when the failure occurred during execution.

Rojas, Elvis↗