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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Design for testability and diagnosis at the system-level

The growing complexity of full-scale systems has surpassed the capabilities of most simulation software to provide detailed models or gate-level failure analyses. The process of system-level diagnosis approaches the fault-isolation problem in a manner that differs significantly from the traditional and exhaustive failure mode search. System-level diagnosis is based on a functional representation of the system. For example, one can exercise one portion of a radar algorithm (the Fast Fourier Transform (FFT) function) by injecting several standard input patterns and comparing the results to standardized output results. An anomalous output would point to one of several items (including the FFT circuit) without specifying the gate or failure mode. For system-level repair, identifying an anomalous chip is sufficient. We describe here an information theoretic and dependency modeling approach that discards much of the detailed physical knowledge about the system and analyzes its information flow and functional interrelationships. The approach relies on group and flow associations and, as such, is hierarchical. Its hierarchical nature allows the approach to be applicable to any level of complexity and to any repair level. This approach has been incorporated in a product called STAMP (System Testability and Maintenance Program) which was developed and refined through more than 10 years of field-level applications to complex system diagnosis. The results have been outstanding, even spectacular in some cases. In this paper we describe system-level testability, system-level diagnoses, and the STAMP analysis approach, as well as a few STAMP applications.

Simpson, William R.↗
NASA NTRS2010

Risk-Informed Safety Assurance and Probabilistic Assessment of Mission-Critical Software-Intensive Systems

This report validates and documents the detailed features and practical application of the framework for software intensive digital systems risk assessment and risk-informed safety assurance presented in the NASA PRA Procedures Guide for Managers and Practitioner. This framework, called herein the "Context-based Software Risk Model" (CSRM), enables the assessment of the contribution of software and software-intensive digital systems to overall system risk, in a manner which is entirely compatible and integrated with the format of a "standard" Probabilistic Risk Assessment (PRA), as currently documented and applied for NASA missions and applications. The CSRM also provides a risk-informed path and criteria for conducting organized and systematic digital system and software testing so that, within this risk-informed paradigm, the achievement of a quantitatively defined level of safety and mission success assurance may be targeted and demonstrated. The framework is based on the concept of context-dependent software risk scenarios and on the modeling of such scenarios via the use of traditional PRA techniques - i.e., event trees and fault trees - in combination with more advanced modeling devices such as the Dynamic Flowgraph Methodology (DFM) or other dynamic logic-modeling representations. The scenarios can be synthesized and quantified in a conditional logic and probabilistic formulation. The application of the CSRM method documented in this report refers to the MiniAERCam system designed and developed by the NASA Johnson Space Center.

Guarro, Sergio B.↗
NASA NTRS1986

Experiments in software reliability - Life-critical applications

The paper discusses four reliability data gathering experiments which were conducted using a small sample of programs for two problems having ultrareliability requirements, n-version programming for fault detection, and repetitive run modeling for failure and fault rate estimation. The experimental results agree with those of Nagel and Skrivan in that the program error rates suggest an approximate log-linear pattern and the individual faults occurred with significantly different error rates. Additional analysis of the experimental data raises new questions concerning the phenomenon of interacting faults. This phenomenon may provide one explanation for software reliability decay. The fourth experiment underscored the difficulty in distinguishing between observations of deficiencies in the design of the algorithm and observations of software faults for real-time process control software. These experiments are a part of a program of serial experiments being pursued by the System Validation Methods of NASA-Langley Research Center to find a means of credibly performing reliability evaluations of flight control software.

Dunham, J. R.↗
DOE OSTI2019

Test-Based Modeling of Photovoltaic Inverter Impact on Distribution Systems

Distributed PV has important effects on overcurrent, overvoltage and islanding protection. These effects are more difficult to analyze because the faulted behavior of PV inverters is less well understood than for rotating machines. Full transient models of the inverter can be accurate, but that approach requires inverter design details and simulation software that doesn’t easily interoperate with utility protection system software. Further, anomalous model behaviors often emerge at different grid conditions, and these are difficult to fix in a proprietary model. Testing provides another approach to characterize inverters, validate models or answer questions of application. This earlier work found major impacts from the inverter design, firmware, operating point and balance-of-system components. Our objective is to characterize PV inverters from black-box testing, leading to standard test reports that could provide parameter sets for widely-implemented models in software tools. The tool vendors can then develop standard inverter models, as they did for rotating machines and exciters. Besides fully detailed transient models, inverters can be represented with steady-state current sources, dynamically controlled current sources or non-linear frequency-dependent black boxes. Type-test data could support the last three kinds of model. Short circuit and sag tests would encompass the basic fault types, reporting the maximum transient and rms currents over all power levels and points-on-wave within four time ranges : 1) 0 to 1 cycles, for close and latch consideration 2) 1 to 4 cycles, for equipment withstand 3) 4 to 30 cycles, for interrupt ratings 4) 30 cycles and beyond, for backup protection analysis Open circuit tests would vary output power and power factor, and report the maximum rms voltage from 1 to 10 cycles after the event. Without models, the type-test data could also provide upper limits on the expected overvoltages and overcurrents.

Wieserman, Laura M.↗
DOE OSTI2022

A Hybrid DC Fault Primary Protection Algorithm for Multi-Terminal HVdc Systems

Protection against dc faults is one of the main technical hurdles faced when operating converter-based HVdc systems. Protection becomes even more challenging for multi-terminal dc (MTdc) systems with more than two terminals/converter stations. In this paper, a hybrid primary fault detection algorithm for MTdc systems is proposed to detect a broad range of failures. Sensor measurements, i.e., line currents and dc reactor voltages measured at local terminals, are first processed by a top-level context clustering algorithm. For each cluster, the best fault detector is selected among a detector pool according to a rule resulting from a learning algorithm. The detector pool consists of several existing detection algorithms, each performing differently across fault scenarios. The proposed hybrid primary detection algorithm: i) offers superior performance compared to an individual detector through a data-driven approach; ii) detects all major fault types including pole-to-pole (P2P), pole-to-ground (P2G), and external dc faults; iii) identifies faults with various fault locations and impedances; iv) is more robust to noisy sensor measurements compared to existing methods; v) does not require exhaustive simulation and sampling for training the model. Performance and effectiveness of the proposed algorithm are evaluated and verified based on time-domain simulations in the PSCAD/EMTDC software environment. The results confirm satisfactory operation, accuracy, and detection speed of the proposed algorithm under various fault scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Reliable edge machine learning hardware for scientific applications

Extreme data rate scientific experiments create massive amounts of data that require efficient ML edge processing. This leads to unique validation challenges for VLSI implementations of ML algorithms: enabling bit-accurate functional simulations for performance validation in experimental software frameworks, verifying those ML models are robust under extreme quantization and pruning, and enabling ultra-fine-grained model inspection for efficient fault tolerance. We discuss approaches to developing and validating reliable algorithms at the scientific edge under such strict latency, resource, power, and area requirements in extreme experimental environments. We study metrics for developing robust algorithms, present preliminary results and mitigation strategies, and conclude with an outlook of these and future directions of research towards the longer-term goal of developing autonomous scientific experimentation methods for accelerated scientific discovery.

Baldi, Tommaso↗
NASA NTRS1982

Production of Reliable Flight Crucial Software: Validation Methods Research for Fault Tolerant Avionics and Control Systems Sub-Working Group Meeting

The state of the art in the production of crucial software for flight control applications was addressed. The association between reliability metrics and software is considered. Thirteen software development projects are discussed. A short term need for research in the areas of tool development and software fault tolerance was indicated. For the long term, research in format verification or proof methods was recommended. Formal specification and software reliability modeling, were recommended as topics for both short and long term research.

Dunham, J. R.↗
NASA NTRS1985

Systems approach to software fault tolerance

Computing systems are employed for aerospace applications with high reliability requirements. In order to provide the needed reliability, it was necessary to make use of computing systems with fault-tolerance characteristics. Traditionally, fault tolerance is achieved through the use of hardware redundance. However, fault-tolerant techniques based on suitable software design considerations have also been developed. The present paper is concerned with the major issues arising in the context of an application of fault-tolerant software techniques to dynamic systems. Attention is given to fault-tolerant flight software, software component stability, system stability with fault-tolerant software, the preservation of functional performance, N-version vs. recovery blocks in flight software, systems-based software, static and dynamic models, static and dynamic consistency tests, and recovery block initialization.

Caglayan, A. K.↗
NASA NTRS1993

Semi-Markov Unreliability Range Evaluator

Semi-Markov Unreliability Range Evaluator, SURE, computer program is software tool for analysis of reconfigurable, fault-tolerant systems. Traditional reliability analyses based on aggregates of fault-handling and fault-occurrence models. SURE provides efficient means for calculating accurate upper and lower bounds for probabilities of death states for large class of semi-Markov mathematical models, and not merely those reduced to critical-pair architectures.

Butler, Ricky W.↗
NASA NTRS2013

Automated Generation of Fault Management Artifacts from a Simple System Model

Our understanding of off-nominal behavior - failure modes and fault propagation - in complex systems is often based purely on engineering intuition; specific cases are assessed in an ad hoc fashion as a (fallible) fault management engineer sees fit. This work is an attempt to provide a more rigorous approach to this understanding and assessment by automating the creation of a fault management artifact, the Failure Modes and Effects Analysis (FMEA) through querying a representation of the system in a SysML model. This work builds off the previous development of an off-nominal behavior model for the upcoming Soil Moisture Active-Passive (SMAP) mission at the Jet Propulsion Laboratory. We further developed the previous system model to more fully incorporate the ideas of State Analysis, and it was restructured in an organizational hierarchy that models the system as layers of control systems while also incorporating the concept of "design authority". We present software that was developed to traverse the elements and relationships in this model to automatically construct an FMEA spreadsheet. We further discuss extending this model to automatically generate other typical fault management artifacts, such as Fault Trees, to efficiently portray system behavior, and depend less on the intuition of fault management engineers to ensure complete examination of off-nominal behavior.

Spinup and Orient↗
NASA NTRS2017

Radiation Hardening by Software Techniques on FPGAs: Flight Experiment Evaluation and Results

We present our work on implementing Radiation Hardening by Software (RHBSW) techniques on the Xilinx Virtex5 FPGAs PowerPC 440 processors on the SpaceCube 2.0 platform. The techniques have been matured and tested through simulation modeling, fault emulation, laser fault injection and now in a flight experiment, as part of the Space Test Program- Houston 4-ISS SpaceCube Experiment 2.0 (STP-H4-ISE 2.0). This work leverages concepts such as heartbeat monitoring, control flow assertions, and checkpointing, commonly used in the High Performance Computing industry, and adapts them for use in remote sensing embedded systems. These techniques are extremely low overhead (typically <1.3%), enabling a 3.3x gain in processing performance as compared to the equivalent traditionally radiation hardened processor. The recently concluded STP-H4 flight experiment was an opportunity to upgrade the RHBSW techniques for the Virtex5 FPGA and demonstrate them on-board the ISS to achieve TRL 7. This work details the implementation of the RHBSW techniques, that were previously developed for the Virtex4-based SpaceCube 1.0 platform, on the Virtex5-based SpaceCube 2.0 flight platform. The evaluation spans the development and integration with flight software, remotely uploading the new experiment to the ISS SpaceCube 2.0 platform, and conducting the experiment continuously for 16 days before the platform was decommissioned. The experiment was conducted on two PowerPCs embedded within the Virtex5 FPGA devices and the experiment collected 19,400 checkpoints, processed 253,482 status messages, and incurred 0 faults. These results are highly encouraging and future work is looking into longer duration testing as part of the STP-H5 flight experiment.

Hybrid Flight Architectures↗
DOE OSTI2026

Generation of random geological models using multi-randomization for machine learning

Generating high-fidelity geological models is essential for advancing machine learning (ML) methods in automated seismic interpretation. For instance, seismic images paired with corresponding fault labels are foundational for ML-based fault detection from seismic migration sections. While several open-access datasets of random geological models exist, open-source tools specifically designed to produce large volumes of such models for ML applications remain scarce. To address this gap, we present RGM (Random Geological Model), an open-source software package for efficiently generating 2D and 3D synthetic geological models tailored for ML workflows. RGM supports the creation of diverse model components, including medium property distributions (P-/S-wave velocities and density), seismic reflectivity images (i.e., synthetic migration sections), relative geological time, and discrete fault attributes such as probability, dip, strike, rake, and displacement. It also accommodates the creation of complex geological features such as salt bodies and unconformities. The model generation algorithm employs a multi-randomization strategy, yielding an effectively infinite-dimensional model space that encompasses a wide range of geological scenarios and associated seismic features. Furthermore, RGM incorporates a method to generate synthetic elastic migration images using analytical elastic reflection coefficients combined with frequency-dependent scaling. This functionality enables the creation of training datasets for ML models that leverage elastic seismic images. RGM is implemented in modern object-oriented Fortran, allowing users to flexibly control statistical parameters governing model variability. We demonstrate the capability, performance, and geological realism of the package through comprehensive 2D and 3D examples.

58 GEOSCIENCES↗
NASA NTRS1984

Development and analysis of the Software Implemented Fault-Tolerance (SIFT) computer

SIFT (Software Implemented Fault Tolerance) is an experimental, fault-tolerant computer system designed to meet the extreme reliability requirements for safety-critical functions in advanced aircraft. Errors are masked by performing a majority voting operation over the results of identical computations, and faulty processors are removed from service by reassigning computations to the nonfaulty processors. This scheme has been implemented in a special architecture using a set of standard Bendix BDX930 processors, augmented by a special asynchronous-broadcast communication interface that provides direct, processor to processor communication among all processors. Fault isolation is accomplished in hardware; all other fault-tolerance functions, together with scheduling and synchronization are implemented exclusively by executive system software. The system reliability is predicted by a Markov model. Mathematical consistency of the system software with respect to the reliability model has been partially verified, using recently developed tools for machine-aided proof of program correctness.

Goldberg, J.↗
NASA NTRS1997

Diagnostic Analyzer for Gearboxes (DAG): User's Guide

This documentation describes the Diagnostic Analyzer for Gearboxes (DAG) software for performing fault diagnosis of gearboxes. First, the user would construct a graphical representation of the gearbox using the gear, bearing, shaft, and sensor tools contained in the DAG software. Next, a set of vibration features obtained by processing the vibration signals recorded from the gearbox using a signal analyzer is required. Given this information, the DAG software uses an unsupervised neural network referred to as the Fault Detection Network (FDN) to identify the occurrence of faults, and a pattern classifier called Single Category-Based Classifier (SCBC) for abnormality scaling of individual vibration features. The abnormality-scaled vibration features are then used as inputs to a Structure-Based Connectionist Network (SBCN) for identifying faults in gearbox subsystems and components. The weights of the SBCN represent its diagnostic knowledge and are derived from the structure of the gearbox graphically presented in DAG. The outputs of SBCN are fault possibility values between 0 and 1 for individual subsystems and components in the gearbox with a 1 representing a definite fault and a 0 representing normality. This manual describes the steps involved in creating the diagnostic gearbox model, along with the options and analysis tools of the DAG software.

Jammu, Vinay B.↗
NASA NTRS2020

Hardware Verification and Validation for a Navigation Sensor Software Model in Support of Flight Vehicle Performance Analysis

… or, “It’s in the details, how to make complicated software perform like complicated hardware.” In attempts to minimize development time and quickly build an operational vehicle, NASA’s Space Launch System (SLS) has had to be intentional about integrated testing. Constraints on budget and schedule have required balance between testing needs and the desire for an integrated flight vehicle as soon as possible. To provide key insights early in design and analysis cycles, a large amount of effort has shifted into maturing and validating models at the component level with integrated testing as a means to validate their integration. In terms of SLS Navigation, this, and the model-based design approach have pushed explicit requirements for sensor models to be validated against flight hardware to high precision. This paper covers the approach taken to verify and validate the models for the two key navigation sensors on the SLS vehicle, the Redundant Inertial Navigation Sensor and the Rate Gyro Assembly. These models are used in performance evaluation, fault detection, and operations development extensively. Using a mix of data from hardware vendor documentation and testing reports, limited in-house testing, and integration activities, these models were able to be validated against flight hardware at multiple levels, from the internal software design to statistical behavior at the raw sensor and integrated box levels. The high level of insight into the hardware elements is instrumental to support flight certification activities and building confidence in SLS Navigation capability. Focused testing enabled additional insight and validation that proved invaluable and the resulting insights were used to focus and mature models. Additionally, of having validated performance-based hardware models enables a wide breadth of activities including detailed fault detection studies and integration into future vehicle frameworks, such as an upper stage and provide a valuable asset to continued SLS analysis and design.

Evan J Anzalone↗
NASA NTRS2020

Hardware Verification and Validation for a Navigation Sensor Software Model in Support of Flight Vehicle Performance Analysis

… or, “It’s in the details, how to make complicated software perform like complicated hardware.” In attempts to minimize development time and quickly build an operational vehicle, NASA’s Space Launch System (SLS) has had to be intentional about integrated testing. Constraints on budget and schedule have required balance between testing needs and the desire for an integrated flight vehicle as soon as possible. To provide key insights early in design and analysis cycles, a large amount of effort has shifted into maturing and validating models at the component level with integrated testing as a means to validate their integration. In terms of SLS Navigation, this, and the model-based design approach have pushed explicit requirements for sensor models to be validated against flight hardware to high precision. This paper covers the approach taken to verify and validate the models for the two key navigation sensors on the SLS vehicle, the Redundant Inertial Navigation Sensor and the Rate Gyro Assembly. These models are used in performance evaluation, fault detection, and operations development extensively. Using a mix of data from hardware vendor documentation and testing reports, limited in-house testing, and integration activities, these models were able to be validated against flight hardware at multiple levels, from the internal software design to statistical behavior at the raw sensor and integrated box levels. The high level of insight into the hardware elements is instrumental to support flight certification activities and building confidence in SLS Navigation capability. Focused testing enabled additional insight and validation that proved invaluable and the resulting insights were used to focus and mature models. Additionally, of having validated performance-based hardware models enables a wide breadth of activities including detailed fault detection studies and integration into future vehicle frameworks, such as an upper stage and provide a valuable asset to continued SLS analysis and design.

Thomas Park↗
DOE OSTI2015

Analysis of rupture area of aftershocks caused by twin earthquakes (Case study: 11 April 2012 earthquakes of Aceh-North Sumatra)

The 11 April 2012 earthquakes off-shore Aceh-North Sumatra are unique events for the history of Indonesian earthquake. It is unique because that they have similar magnitude, 8.5 Mw and 8.1 Mw; close to epicenter distance, similar strike-slip focal mechanism, and occuring in outer rise area. The purposes of this research are: (1) comparing area of earthquakes base on models and that of calculation, (2) fitting the shape and the area of earthquake rupture zones, (3) analyzing the relationship between rupture area and magnitude of the earthquakes. Rupture area of the earthquake fault are determined by using 4 different formulas, i.e. Utsu and Seki (1954), Wells and Coppersmith (1994), Ellsworth (2003), and Christophersen and Smith (2000). The earthquakes aftershock parameters are taken from PGN (PusatGempabumiNasional or National Earthquake Information Center) of BMKG (Indonesia Agency Meteorology Climatology and Geophysics). The aftershock epicenters are plotted by GMT’s software. After that, ellipse and rectangular models of aftershock spreading are made. The results show that: (1) rupture areas were calculated using magnitude relationship which are larger than the the aftershock distributions model, (2) the best fitting model for that earthquake aftershock distribution is rectangular associated with Utsu and Seki (1954) formula, (3) the larger the magnitude of the earthquake, the larger area of the fault.

58 GEOSCIENCES↗
NASA NTRS1989

CONFIG - Adapting qualitative modeling and discrete event simulation for design of fault management systems

CONFIG is a modeling and simulation tool prototype for analyzing the normal and faulty qualitative behaviors of engineered systems. Qualitative modeling and discrete-event simulation have been adapted and integrated, to support early development, during system design, of software and procedures for management of failures, especially in diagnostic expert systems. Qualitative component models are defined in terms of normal and faulty modes and processes, which are defined by invocation statements and effect statements with time delays. System models are constructed graphically by using instances of components and relations from object-oriented hierarchical model libraries. Extension and reuse of CONFIG models and analysis capabilities in hybrid rule- and model-based expert fault-management support systems are discussed.

Malin, Jane T.↗