Search NASA⌕ Search

SEARCH · Search NASA

Results for “software fault model”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Model Transformation for a System of Systems Dependability Safety Case

Software plays an increasingly larger role in all aspects of NASA's science missions. This has been extended to the identification, management and control of faults which affect safety-critical functions and by default, the overall success of the mission. Traditionally, the analysis of fault identification, management and control are hardware based. Due to the increasing complexity of system, there has been a corresponding increase in the complexity in fault management software. The NASA Independent Validation & Verification (IV&V) program is creating processes and procedures to identify, and incorporate safety-critical software requirements along with corresponding software faults so that potential hazards may be mitigated. This Specific to Generic ... A Case for Reuse paper describes the phases of a dependability and safety study which identifies a new, process to create a foundation for reusable assets. These assets support the identification and management of specific software faults and, their transformation from specific to generic software faults. This approach also has applications to other systems outside of the NASA environment. This paper addresses how a mission specific dependability and safety case is being transformed to a generic dependability and safety case which can be reused for any type of space mission with an emphasis on software fault conditions.

Murphy, Judy↗
DOE OSTI2024

Regional-scale fault-to-structure earthquake simulations with the EQSIM framework: Workflow maturation and computational performance on GPU-accelerated exascale platforms

Continuous advancements in scientific and engineering understanding of earthquake phenomena, combined with the associated development of representative physics-based models, is providing a foundation for high-performance, fault-to-structure earthquake simulations. However, regional-scale applications of high-performance models have been challenged by the computational requirements at the resolutions required for engineering risk assessments. The EarthQuake SIMulation (EQSIM) framework, a software application development under the US Department of Energy (DOE) Exascale Computing Project, is focused on overcoming the existing computational barriers and enabling routine regional-scale simulations at resolutions relevant to a breadth of engineered systems. This multidisciplinary software development—drawing upon expertise in geophysics, engineering, applied math and computer science—is preparing the advanced computational workflow necessary to fully exploit the DOE’s exaflop computer platforms coming online in the 2023 to 2024 timeframe. Achievement of the computational performance required for high-resolution regional models containing upward of hundreds of billions to trillions of model grid points requires numerical efficiency in every phase of a regional simulation. This includes run time start-up and regional model generation, effective distribution of the computational workload across thousands of computer nodes, efficient coupling of regional geophysics and local engineering models, and application-tailored highly efficient transfer, storage, and interrogation of very large volumes of simulation data. This article summarizes the most recent advancements and refinements incorporated in the workflow design for the EQSIM integrated fault-to-structure framework, which are based on extensive numerical testing across multiple graphics processing unit (GPU)-accelerated platforms, and demonstrates the computational performance achieved on the world’s first exaflop computer platform through representative regional-scale earthquake simulations for the San Francisco Bay Area in California, USA.

58 GEOSCIENCES↗
DOE OSTI2016

Power Converter Control Algorithm Design and Simulation for the NREL Next-Generation Drivetrain: July 8, 2013 - January 7, 2016

The National Renewable Energy Laboratory (NREL) and NREL Next-Generation Drivetrain Partners are developing a next-generation drivetrain (NGD) design as part of a Funding Opportunity Announcement award from the U.S. Department of Energy. The proposed NGD includes comprehensive innovations to the gearbox, generator, and power converter that increase the gearbox reliability and drivetrain capacity, while lowering deployment and operation and maintenance costs. A key task within this development effort is the power converter fault control algorithm design and associated computer simulations using an integrated electromechanical model of the drivetrain. The results of this task will be used in generating the embedded control software to be utilized in the power converter during testing of the NGD in the National Wind Technology Center 2.5-MW dynamometer. A list of issues to be addressed with these algorithms was developed by review of the grid interconnection requirements of various North American transmission system operators, and those requirements that presented the greatest impact to the wind turbine drivetrain design were then selected for mitigation via power converter control algorithms.

17 WIND ENERGY↗
NASA NTRS1990

A Thermal Expert System (TEXSYS) development overview - AI-based control of a Space Station prototype thermal bus

A knowledge-based control system for real-time control and fault detection, isolation and recovery (FDIR) of a prototype two-phase Space Station Freedom external thermal control system (TCS) is discussed in this paper. The Thermal Expert System (TEXSYS) has been demonstrated in recent tests to be capable of both fault anticipation and detection and real-time control of the thermal bus. Performance requirements were achieved by using a symbolic control approach, layering model-based expert system software on a conventional numerical data acquisition and control system. The model-based capabilities of TEXSYS were shown to be advantageous during software development and testing. One representative example is given from on-line TCS tests of TEXSYS. The integration and testing of TEXSYS with a live TCS testbed provides some insight on the use of formal software design, development and documentation methodologies to qualify knowledge-based systems for on-line or flight applications.

Glass, B. J.↗
NASA NTRS2008

Processing LiDAR Data to Predict Natural Hazards

ELF-Base and ELF-Hazards (wherein 'ELF' signifies 'Extract LiDAR Features' and 'LiDAR' signifies 'light detection and ranging') are developmental software modules for processing remote-sensing LiDAR data to identify past natural hazards (principally, landslides) and predict future ones. ELF-Base processes raw LiDAR data, including LiDAR intensity data that are often ignored in other software, to create digital terrain models (DTMs) and digital feature models (DFMs) with sub-meter accuracy. ELF-Hazards fuses raw LiDAR data, data from multispectral and hyperspectral optical images, and DTMs and DFMs generated by ELF-Base to generate hazard risk maps. Advanced algorithms in these software modules include line-enhancement and edge-detection algorithms, surface-characterization algorithms, and algorithms that implement innovative data-fusion techniques. The line-extraction and edge-detection algorithms enable users to locate such features as faults and landslide headwall scarps. Also implemented in this software are improved methodologies for identification and mapping of past landslide events by use of (1) accurate, ELF-derived surface characterizations and (2) three LiDAR/optical-data-fusion techniques: post-classification data fusion, maximum-likelihood estimation modeling, and hierarchical within-class discrimination. This software is expected to enable faster, more accurate forecasting of natural hazards than has previously been possible.

Fairweather, Ian↗
NASA NTRSDate not supplied

Fault Management Algorithm Risk Assessment for the NASA Space Launch System

This presentation describes the false positive (FP) and false negative (FN) risk assessment process currently being conducted for the Space Launch System (SLS) Artemis II Fault Management (FM) detection functions. The analysis scope, general assumptions and guide rules, and key modeling concepts were discussed to establish the basis of the risk assessments conducted. Initial analyses indicated a dominance in the total risk by software and firmware failures. This paper presents efforts applied to refine the software risks and the overall impact of implementing those modifications. Current analyses conducted on the detection functions implemented for the SLS Artemis II mission indicate primary risk drivers for the individual FM detection functions are flight software failures, firmware design failures, and hardware Common Cause Failures (CCFs). There still remains issues of how to account for time and redundancy in the software risk estimations.

probability risk analysis↗
NASA NTRSDate not supplied

Fault Management Algorithm Risk Assessment for the NASA Space Launch System

This paper presents the false positive (FP) and false negative (FN) risk assessment process currently being conducted for the Space Launch System (SLS) Artemis II Fault Management (FM) detection functions. The analysis scope, general assumptions and guide rules, and key modeling concepts were discussed to establish the basis of the risk assessments conducted. Initial analyses indicated a dominance in the total risk by software and firmware failures. This paper presents efforts applied to refine the software risks and the overall impact of implementing those modifications. Current analyses conducted on the detection functions implemented for the SLS Artemis II mission indicate primary risk drivers for the individual FM detection functions are flight software failures, firmware design failures, and hardware Common Cause Failures (CCFs). There still remains issues of how to account for time and redundancy in the software risk estimations.

probability risk analysis↗
NASA NTRS2009

Applying Model-based Diagnosis to a Rapid Propellant Loading System

The overall objective of the US Air Force Research Laboratory (AFRL) Rapid Propellant Loading (RPL) Program is to develop a launch vehicle, payload and ground support equipment that can support a rapid propellant load and launch within one hour. NASA Kennedy Space Center (KSC) has been funded by AFRL to develop hardware and software to demonstrate this capability. The key features of the software would be the ability to recognize and adapt to failures in the physical hardware components, advise operators of equipment faults and workarounds, and put the system in a safe configuration if unable to fly. In December 2008 NASA KSC and NASA Ames Research Center (ARC) demonstrated model based simulation and diagnosis capabilities for a scaled-down configuration of the RPL hardware. In this paper we present a description of the model-based technologies that were included as part of this demonstration and the results that were achieved. In continuation of this work we are currently testing the technologies on a simulation of the complete RPL system. Later in the year, when the RPL hardware is ready, we will be integrating these technologies with the real-time operation of the system to provide live state estimates. In future years we will be developing the capability to recover from faulty conditions via redundancy and reconfiguration.

Goodrich, Charlie H.↗
NASA NTRS2009

Rover Attitude and Pointing System Simulation Testbed

The MER (Mars Exploration Rover) Attitude and Pointing System Simulation Testbed Environment (RAPSSTER) provides a simulation platform used for the development and test of GNC (guidance, navigation, and control) flight algorithm designs for the Mars rovers, which was specifically tailored to the MERs, but has since been used in the development of rover algorithms for the Mars Science Laboratory (MSL) as well. The software provides an integrated simulation and software testbed environment for the development of Mars rover attitude and pointing flight software. It provides an environment that is able to run the MER GNC flight software directly (as opposed to running an algorithmic model of the MER GNC flight code). This improves simulation fidelity and confidence in the results. Further more, the simulation environment allows the user to single step through its execution, pausing, and restarting at will. The system also provides for the introduction of simulated faults specific to Mars rover environments that cannot be replicated in other testbed platforms, to stress test the GNC flight algorithms under examination. The software provides facilities to do these stress tests in ways that cannot be done in the real-time flight system testbeds, such as time-jumping (both forwards and backwards), and introduction of simulated actuator faults that would be difficult, expensive, and/or destructive to implement in the real-time testbeds. Actual flight-quality codes can be incorporated back into the development-test suite of GNC developers, closing the loop between the GNC developers and the flight software developers. The software provides fully automated scripting, allowing multiple tests to be run with varying parameters, without human supervision.

Vanelli, Charles A.↗
NASA NTRS1993

A fault-tolerant intelligent robotic control system

This paper describes the concept, design, and features of a fault-tolerant intelligent robotic control system being developed for space and commercial applications that require high dependability. The comprehensive strategy integrates system level hardware/software fault tolerance with task level handling of uncertainties and unexpected events for robotic control. The underlying architecture for system level fault tolerance is the distributed recovery block which protects against application software, system software, hardware, and network failures. Task level fault tolerance provisions are implemented in a knowledge-based system which utilizes advanced automation techniques such as rule-based and model-based reasoning to monitor, diagnose, and recover from unexpected events. The two level design provides tolerance of two or more faults occurring serially at any level of command, control, sensing, or actuation. The potential benefits of such a fault tolerant robotic control system include: (1) a minimized potential for damage to humans, the work site, and the robot itself; (2) continuous operation with a minimum of uncommanded motion in the presence of failures; and (3) more reliable autonomous operation providing increased efficiency in the execution of robotic tasks and decreased demand on human operators for controlling and monitoring the robotic servicing routines.

Marzwell, Neville I.↗
NASA NTRS2002

The NASA Integrated Vehicle Health Management Technology Experiment for X-37

The NASA Integrated Vehicle Health Management (IVHM) Technology Experiment for X-37 was intended to run IVHM software on-board the X-37 spacecraft. The X-37 is intended to be an unpiloted vehicle that would orbit the Earth for up to 21 days before landing on a runway. The objectives of the experiment were to demonstrate the benefits of in-flight IVHM to the operation of a Reusable Launch Vehicle, to advance the Technology Readiness Level of this IVHM technology within a flight environment, and to demonstrate that the IVHM software could operate on the Vehicle Management Computer. The scope of the experiment was to perform real-time fault detection and isolation for X-37's electrical power system and electro-mechanical actuators. The experiment used Livingstone, a software system that performs diagnosis using a qualitative, model-based reasoning approach that searches system-wide interactions to detect and isolate failures. Two of the challenges we faced were to make this research software more efficient so that it would fit within the limited computational resources that were available to us on the X-37 spacecraft, and to modify it so that it satisfied the X-37's software safety requirements. Although the experiment is currently unfunded, the development effort had value in that it resulted in major improvements in Livingstone's efficiency and safety. This paper reviews some of the details of the modeling and integration efforts, and some of the lessons that were learned.

Schwabacher, Mark↗
DOE OSTI2020

Fault Response of Distributed Energy Resources Considering the Requirements of IEEE 1547-2018

Inverter-based DER responses to faults on the electric power system are different than those of conventional generators and are often poorly understood. Inverter fault responses are largely software-defined, within physics-based constraints. DERs are regulated by standards and grid codes that also constrain their responses. Though fault response of DERs will vary widely, for any DER following any particular standard, a pattern of fault response can be synthesized by observing that particular standard. In this paper, the recently published IEEE 1547-2018 is examined to explore the general fault response of any DER that follows IEEE 1547-2018. Additionally, an IEEE 1547-2018 compliant inverter model is developed and tested in simulation to find the fault response, and that response is compared with the fault response of a commercial off-the-shelf inverter.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2021

Development of a Unified Taxonomy for HVAC System Faults

Detecting and diagnosing HVAC faults is critical for maintaining building operation performance, reducing energy waste, and ensuring indoor comfort. An increasing deployment of commercial fault detection and diagnostics (FDD) software tools in commercial buildings in the past decade has significantly increased buildings’ operational reliability and reduced energy consumption. A massive amount of data has been generated by the FDD software tools. However, efficiently utilizing FDD data for ‘big data’ analytics, algorithm improvement, and other data-driven applications is challenging because the format and naming conventions of those data are very customized, unstructured, and hard to interpret. This paper presents the development of a unified taxonomy for HVAC faults. A taxonomy is an orderly classification of HVAC faults according to their characteristics and causal relations. The taxonomy includes fault categorization, physical hierarchy, fault library, relation model, and naming/tagging scheme. The taxonomy employs both a physical hierarchy of HVAC equipment and a cause-effect relationship model to reveal the root causes of faults in HVAC systems. A structured and standardized vocabulary library is developed to increase data representability and interpretability. The developed fault taxonomy can be used for HVAC system ‘big data’ analytics such as HVAC system fault prevalence analysis or the development of an HVAC FDD software standard. A common type of HVAC equipment-packaged rooftop unit (RTU) is used as an example to demonstrate the application of the developed fault taxonomy. Two RTU FDD software tools are used to show that after mapping FDD data according to the taxonomy, the meta-analysis of the multiple FDD reports is possible and efficient.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

IBR Short Circuit Modeling in ETAP

Mohammad Zadeh from ETAP presented various modeling improvements that included the following: • Address convergence issues by using complete Norton Equivalent model including the IBR series filter impedance. • Fault ride through identification within iterations while short circuit results have not been converged and how that may impact final SC results. • Options for FRT curve 1- using a timer to lock FRT logic vs a hysteresis in FRT curve to avoid unwanted toggling. • Report recent co-operation between software vendors (Aspen, CAPE and ETAP) for adopting a C++ interface for IBR blackbox SC modeling. There was lot of interest to know about the model improvements that are being considered.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1988

A method of measuring fault latency in a digital flight control system

This paper describes the motivation, conduct, and analysis of some 2500 low-level hardware fault cases applied in automated testing at the NASA Ames Reconfigurable Digital Flight Control System Facility. Fault detection was correlated with hardware and software fault monitoring and, in limited cases, with sensitivity to flight program execution modes. The results are statistically assessed to ascertain system-level reliability implications based on a single-fault model. Extension to multiple-fault models is addressed. The overall methodology/facility itself is judged to be a promising enhancement to current practice.

Mcgough, John↗
NASA NTRS1994

Program Finds Minimal Cut Sets

CUTSETS computer program identifies all minimal cut sets for given node. Software package contains subprograms that solve for minimal cut sets of fault trees and digraphs by use of object-oriented programming techniques. Cut-set codes used to solve graph models for reliability analysis and identify potential single-point failures in modeled system. Includes utility subprogram that converts popular COD-format diagraph-model-description files into text input files suitable for use with other CUT-SETS subprograms. FEAT (MSC-21873) and FIRM (MSC-21860). Written in C language.

Iverson, D. L.↗
NASA NTRS2006

Trade Studies of Space Launch Architectures using Modular Probabilistic Risk Analysis

A top-down risk assessment in the early phases of space exploration architecture development can provide understanding and intuition of the potential risks associated with new designs and technologies. In this approach, risk analysts draw from their past experience and the heritage of similar existing systems as a source for reliability data. This top-down approach captures the complex interactions of the risk driving parts of the integrated system without requiring detailed knowledge of the parts themselves, which is often unavailable in the early design stages. Traditional probabilistic risk analysis (PRA) technologies, however, suffer several drawbacks that limit their timely application to complex technology development programs. The most restrictive of these is a dependence on static planning scenarios, expressed through fault and event trees. Fault trees incorporating comprehensive mission scenarios are routinely constructed for complex space systems, and several commercial software products are available for evaluating fault statistics. These static representations cannot capture the dynamic behavior of system failures without substantial modification of the initial tree. Consequently, the development of dynamic models using fault tree analysis has been an active area of research in recent years. This paper discusses the implementation and demonstration of dynamic, modular scenario modeling for integration of subsystem fault evaluation modules using the Space Architecture Failure Evaluation (SAFE) tool. SAFE is a C++ code that was originally developed to support NASA s Space Launch Initiative. It provides a flexible framework for system architecture definition and trade studies. SAFE supports extensible modeling of dynamic, time-dependent risk drivers of the system and functions at the level of fidelity for which design and failure data exists. The approach is scalable, allowing inclusion of additional information as detailed data becomes available. The tool performs a Monte Carlo analysis to provide statistical estimates. Example results of an architecture system reliability study are summarized for an exploration system concept using heritage data from liquid-fueled expendable Saturn V/Apollo launch vehicles.

Mathias, Donovan L.↗
NASA NTRS2008

Advanced Diagnostic and Prognostic Testbed (ADAPT) Testability Analysis Report

As system designs become more complex, determining the best locations to add sensors and test points for the purpose of testing and monitoring these designs becomes more difficult. Not only must the designer take into consideration all real and potential faults of the system, he or she must also find efficient ways of detecting and isolating those faults. Because sensors and cabling take up valuable space and weight on a system, and given constraints on bandwidth and power, it is even more difficult to add sensors into these complex designs after the design has been completed. As a result, a number of software tools have been developed to assist the system designer in proper placement of these sensors during the system design phase of a project. One of the key functions provided by many of these software programs is a testability analysis of the system essentially an evaluation of how observable the system behavior is using available tests. During the design phase, testability metrics can help guide the designer in improving the inherent testability of the design. This may include adding, removing, or modifying tests; breaking up feedback loops, or changing the system to reduce fault propagation. Given a set of test requirements, the analysis can also help to verify that the system will meet those requirements. Of course, a testability analysis requires that a software model of the physical system is available. For the analysis to be most effective in guiding system design, this model should ideally be constructed in parallel with these efforts. The purpose of this paper is to present the final testability results of the Advanced Diagnostic and Prognostic Testbed (ADAPT) after the system model was completed. The tool chosen to build the model and to perform the testability analysis with is the Testability Engineering and Maintenance System Designer (TEAMS-Designer). The TEAMS toolset is intended to be a solution to span all phases of the system, from design and development through health management and maintenance. TEAMS-Designer is the model-building and testability analysis software in that suite.

Ossenfort, John↗