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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Latent-Space Dynamics for Prediction and Fault Detection in Geothermal Power Plant Operations

This paper presents a latent-space dynamic neural network (LSDNN) model for the multi-step-ahead prediction and fault detection of a geothermal power plant’s operation. The model was trained to learn the dynamics of the power generation process from multivariate time-series data and the effects of exogenous variables, such as control adjustment and ambient temperature. In the LSDNN model, an encoder–decoder architecture was designed to capture cross-correlation among different measured variables. In addition, a latent space dynamic structure was proposed to propagate the dynamics in the latent space to enable prediction. The prediction power of the LSDNN was utilized for monitoring a geothermal power plant and detecting abnormal events. The model was integrated with principal component analysis (PCA)-based process monitoring techniques to develop a fault-detection procedure. The performance of the proposed LSDNN model and fault detection approach was demonstrated using field data collected from a geothermal power plant.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Adaptive Fault Detection Based on Neural Networks and Multiple Sampling Points for Distribution Networks and Microgrids

Smart networks such as microgrid (MG) and active distribution networks (ADN) have been recently playing an important role in power system operation. The design and implementation of appropriate protection systems for such networks must be addressed, which imposes new technical challenges. This paper presents the implementation and validation aspects of an adaptive fault detection strategy based on neural networks (NNs) and multiple sampling points for ADN and MG. The solution is implemented on an edge device. Artificial NNs are used to derive a data-driven model that uses only local measurements to detect fault states of the network without the need for communication infrastructure. Multiple sampling points are used to derive a data-driven model, which allows the generalization considering the implementation in physical systems. The adaptive fault detector model is implemented on a Jetson Nano system, which is a single-board computer (SBC) with a small Graphic Processing Unit (GPU) intended to run machine learning loads at the edge. The proposed method is tested in a physical, real-life, low-voltage network located at Universidad del Norte, Colombia. This testing network is based on the IEEE-13 Node Test Feeder scaled down to 220 V. The validation in a simulation environment shows the accuracy and dependability above 99.6%, while the real-time tests show the accuracy and dependability of 95.5% and 100%, respectively. Without hard-to-derive parameters, the easy-to-implement embedded model highlights the potential for real-life applications.

42 ENGINEERING↗
DOE OSTI2025

Eucalyptus – An Analysis Suite for Fault Trees with Uncertainty Quantification

Eucalyptus is a novel code developed at Lawrence Livermore National Laboratory to incorporate uncertainty quantification into Fault Tree Analysis (FTA). This tool addresses the challenge of imperfect knowledge in “grey-box” systems by allowing analysts to incorporate and propagate uncertainty from component-level assessments to system-level effects. Eucalyptus facilitates a consistent evaluation of the impact of subject matter expert judgment and knowledge gaps on overall system response by Monte Carlo generation of possible system fault trees, sampling probabilities of the existence of subsystems and components. Here, the code supports the specification of fault trees through text and allows export to various formats, including auto-generated images, easing analysis and reducing errors. It has undergone extensive verification testing, demonstrating its reliability and readiness for deployment, and leverages on-node parallelism for rapid analysis. Example analyses are shown that include the identification of system failure paths and quantification of the value of further information about system components.

Fault Tree Analysis↗
NASA NTRS2004

The 2003 Bam (Iran) earthquake: Rupture of a blind strike-slip fault

A magnitude 6.5 earthquake devastated the town of Bam in southeast Iran on 26 December 2003. Surface displacements and decorrelation effects, mapped using Envisat radar data, reveal that over 2 m of slip occurred at depth on a fault that had not previously been identified. It is common for earthquakes to occur on blind faults which, despite their name, usually produce long-term surface effects by which their existence may be recognised. However, in this case there is a complete absence of morphological features associated with the seismogenic fault that destroyed Bam.

earthquakes blind faults Bam Envisat radar remote ↗
NASA NTRS2003

Developing fault models for space mission software

Over the past several years, we have focused on developing fault models for space mission software. In general, these models use measurable attributes of a software system and its development process to estimate the number of faults inserted into the system during its development; their outputs can be used to better estimate the resources to be allocated to fault identification and removal for all system components.

fault models software development software archite↗
NASA NTRS1998

Estimating Rates of Fault Insertion and Test Effectiveness in Software Systems

In developing a software system, we would like to estimate the total number of faults inserted into a software system, the residual fault content of that system at any given time, and the efficacy of the testing activity in executing the code containing the newly inserted faults.

fault insertion software systems test effectivenes↗
NASA NTRS2006

A dynamic fault tree model of a propulsion system

We present a dynamic fault tree model of the benchmark propulsion system, and solve it using Galileo. Dynamic fault trees (DFT) extend traditional static fault trees with special gates to model spares and other sequence dependencies. Galileo solves DFT models using a judicious combination of automatically generated Markov and Binary Decision Diagram models. Galileo easily handles the complexities exhibited by the benchmark problem. In particular, Galileo is designed to model phased mission systems.

propulsion system↗
NASA NTRS2005

Fault protection techniques in JPL Spacecraft

While every JPL spacecraft requires some unique mission specific fault protection, there are many requirements which are common to all spacecraft configurations. These consist of protecting command and data processing & attitude control computers, protection against communication loss with the spacecraft, ensuring that safe external and internal temperature levels are maintained, and recovery from power overloads. Additionally, most JPL spacecraft are equipped with a general-purpose 'Safe Mode' response algorithm which configures the spacecraft to a lower power state which is safe and predictable so that diagnosis of more complex faults can be addressed by the Operations Team. This paper details the generic application of fault protection techniques which are implemented into most JPL spacecraft designs.

fault protection↗
NASA NTRS2004

Using the GeoFEST Faulted Region Simulation System

GeoFEST (the Geophysical Finite Element Simulation Tool) simulates stress evolution, fault slip and plastic/elastic processes in realistic materials, and so is suitable for earthquake cycle studies in regions such as Southern California. Many new capabilities and means of access for GeoFEST are now supported. New abilities include MPI-based cluster parallel computing using automatic PYRAMID/Parmetis-based mesh partitioning, automatic mesh generation for layered media with rectangular faults, and results visualization that is integrated with remote sensing data. The parallel GeoFEST application has been successfully run on over a half-dozen computers, including Intel Xeon clusters, Itanium II and Altix machines, and the Apple G5 cluster. It is not separately optimized for different machines, but relies on good domain partitioning for load-balance and low communication, and careful writing of the parallel diagonally preconditioned conjugate gradient solver to keep communication overhead low. Demonstrated thousand-step solutions for over a million finite elements on 64 processors require under three hours, and scaling tests show high efficiency when using more than (order of) 4000 elements per processor. The source code and documentation for GeoFEST is available at no cost from Open Channel Foundation. In addition GeoFEST may be used through a browser-based portal environment available to approved users. That environment includes semi-automated geometry creation and mesh generation tools, GeoFEST, and RIVA-based visualization tools that include the ability to generate a flyover animation showing deformations and topography. Work is in progress to support simulation of a region with several faults using 16 million elements, using a strain energy metric to adapt the mesh to faithfully represent the solution in a region of widely varying strain.

Geophyical Finite Element Simulation Tool (GeoFEST↗
NASA NTRS2013

A System for Fault Management for NASA's Deep Space Habitat

NASA's exploration program envisions the utilization of a Deep Space Habitat (DSH) for human exploration of the space environment in the vicinity of Mars and/or asteroids. Communication latencies with ground control of as long as 20+ minutes make it imperative that DSH operations be highly autonomous, as any telemetry-based detection of a systems problem on Earth could well occur too late to assist the crew with the problem. A DSH-based development program has been initiated to develop and test the automation technologies necessary to support highly autonomous DSH operations. One such technology is a fault management tool to support performance monitoring of vehicle systems operations and to assist with real-time decision making in connection with operational anomalies and failures. Toward that end, we are developing Advanced Caution and Warning System (ACAWS), a tool that combines dynamic and interactive graphical representations of spacecraft systems, systems modeling, automated diagnostic analysis and root cause identification, system and mission impact assessment, and mitigation procedure identification to help spacecraft operators (both flight controllers and crew) understand and respond to anomalies more effectively. In this paper, we describe four major architecture elements of ACAWS: Anomaly Detection, Fault Isolation, System Effects Analysis, and Graphic User Interface (GUI), and how these elements work in concert with each other and with other tools to provide fault management support to both the controllers and crew. We then describe recent evaluations and tests of ACAWS on the DSH testbed. The results of these tests support the feasibility and strength of our approach to failure management automation and enhanced operational autonomy.

Fault management↗
NASA NTRS2013

V&V of Fault Management: Challenges and Successes

This paper describes the results of a special breakout session of the NASA Independent Verification and Validation (IV&V) Workshop held in the fall of 2012 entitled "V&V of Fault Management: Challenges and Successes." The NASA IV&V Program is in a unique position to interact with projects across all of the NASA development domains. Using this unique opportunity, the IV&V program convened a breakout session to enable IV&V teams to share their challenges and successes with respect to the V&V of Fault Management (FM) architectures and software. The presentations and discussions provided practical examples of pitfalls encountered while performing V&V of FM including the lack of consistent designs for implementing faults monitors and the fact that FM information is not centralized but scattered among many diverse project artifacts. The discussions also solidified the need for an early commitment to developing FM in parallel with the spacecraft systems as well as clearly defining FM terminology within a project.

Verification↗
NASA NTRSDate not supplied

Design and Testing of a Hard-Fault Protection Circuit for a 1 kV SiC MOSFET Inverter

Due to increasingly high DC link voltages and further advancements in the current density of silicon carbide (SiC) MOSFETs, it has become evident that conventional IGBT protection methods are not sufficient to prevent exceeding the current rating of these devices during low-inductance fault events. This paper explores the use of an air core Rogowski coil topology to mitigate these hard fault events. The design of this circuit resulted in safe shutdown of a low impedance phase-to-phase fault in under one microsecond, tested up to DC link voltages of 1 kV. This paper details the theory, design, simulation, and successful test results of this method.

hard fault protection↗
NASA NTRSDate not supplied

Hard Fault Protection for a Silicon Carbide-Based Aerospace Motor Drive

Due to increasingly high DC link voltages and further advancements in the current density of silicon carbide (SiC) MOSFETs, it has become evident that conventional IGBT protection methods are not sufficient to protect these devices from overcurrent during low-inductance fault events. The use of an air core Rogowski coil topology was explored to see if it could mitigate these hard fault events. The design of this circuit resulted in safe shutdown of a low impedance phase-tophase fault, tested up to DC link voltages of 1 kV.

High Voltage↗
DOE OSTI2019

Is it Worth Relaxing Fault Tolerance to Speed Up Decommission in Distributed Storage Systems?

Efficient resource utilization is a major concern for large-scale computer platforms. One method used to lower energy consumption and operational cost is to reduce the amount of idle resources. This can be achieved by using malleability, namely, the possibility for resource managers to dynamically increase or decrease the amount of resources of jobs while they are running. Decommissioning (i.e., removing from the cluster) the idle nodes as soon as possible allows the resource manager to quickly reallocate those nodes to other jobs. Challenges appear when such nodes host part of a distributed storage system. Such storage systems may need to transfer large amounts of data before releasing the nodes, in order to ensure data availability and a certain level of fault tolerance. In this paper, we model and evaluate the performance of the decommission operation when relaxing the level of fault tolerance (i.e., the number of replicas) during this operation. Intuitively, this is expected to reduce the amount of data transfers needed before nodes are released, and thus allow nodes to be returned to the resource manager faster. We quantify theoretically how much time and resources are saved by such a fast decommission strategy compared with a standard decommission that does not temporarily reduce the fault-tolerance level. We establish lower bounds for the duration of the different phases of a fast decommission. We use the lower bounds to estimate when fast decommission would be useful to reduce the usage of core-hours and when not. We implement a prototype for fast decommission and experimentally validate the lower bounds on the duration of the operation and confirm in practice our theoretical findings.

Decommission↗
DOE OSTI2018

Commercial Fault Detection and Diagnostics Tools: What They Offer, How They Differ, and What's Still Needed

It is estimated that 5%-30% energy use in commercial buildings is wasted due to faults and errors in operations. Automated fault detection and diagnostics (AFDD) technologies can address this waste by identifying (detecting) deviations from normal or expected operation (faults), and resolving (diagnosing) the type of problem or its location, minimizing the need for complex manual analysis of operational data. Although currently underutilized, AFDD is a powerful approach to ensuring efficient building operations. AFDD offers the potential to greatly improve performance, and to do so cost effectively. There is currently a diverse landscape of AFDD technologies on the market, but no common framework exists to characterize such tools, or distinguish one offering from another. It is difficult to determine from vendor websites and marketing materials key technology features and capabilities, or the overall state of the technology. In this paper, we present an AFDD characterization framework, and findings from applying the framework to survey over a dozen technologies from today's market. This paper outlines the current state of the market, as well as outstanding needs in the industry, derived from direct engagement of, and technical assistance provided to users of AFDD technology. A core set of interrelated informational, organizational, and technical needs and barriers that must be addressed to realize the full potential of AFDD at scale are identified. Lastly, based on information gathered through a survey and discussion with both vendors and users, several opportunities to further advance the technology are discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Measuring during a fault

Measuring instruments used in power systems will continue to report their results, even when there is a fault in the system. At such a time, the quality of the measurement is decreased, and the uncertainty of the value is increased. The uncertainty should be reported, but it rarely is. While power engineers have seemingly come to trust the results of such measurements without an uncertainty statement, in any case there is a fundamental problem with quantifying the uncertainty. The problem is not limited to power systems, though faults make it more evident. Uncertainty of the kind caused by a faulted power system can be considered definitional uncertainty, and that is normally evaluated statistically. It is not possible to perform statistics unless the measurement can be repeated at least a few times, and that is not an option outside the laboratory. This paper examines the matter from the viewpoint of measurement theory, and suggests a direction for some future work.

measurement, uncertainty, goodness of fit, degrees↗
DOE OSTI2024

A Data-Driven Approach for High-Impedance Fault Localization in Distribution Systems: Preprint

Accurate and quick identification of high-impedance faults (HIFs) is critical for the reliable operation of distribution systems. Unlike other faults in power grids, HIFs are very difficult to detect by conventional overcurrent relays due to the low fault current. Although HIFs can be affected by various factors, the voltage-current characteristics can substantially imply how the system responds to the disturbance and thus provides opportunities to effectively localize HIFs. In this work, we propose a data-driven approach for the identification of HIF events. To tackle the nonlinearity of the voltage-current trajectory, first, we formulate optimization problems to approximate the trajectory with piecewise functions. Then we collect the function features of all segments as inputs and use the support vector machine approach to efficiently identify HIFs at different locations. Numerical studies on the IEEE 123-node test feeder demonstrate the validity and accuracy of the proposed approach for real-time HIF identification.

explainable artificial intelligence↗