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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Improving Multiple Fault Diagnosability using Possible Conflicts

Multiple fault diagnosis is a difficult problem for dynamic systems. Due to fault masking, compensation, and relative time of fault occurrence, multiple faults can manifest in many different ways as observable fault signature sequences. This decreases diagnosability of multiple faults, and therefore leads to a loss in effectiveness of the fault isolation step. We develop a qualitative, event-based, multiple fault isolation framework, and derive several notions of multiple fault diagnosability. We show that using Possible Conflicts, a model decomposition technique that decouples faults from residuals, we can significantly improve the diagnosability of multiple faults compared to an approach using a single global model. We demonstrate these concepts and provide results using a multi-tank system as a case study.

multiple faults↗
DOE OSTI2012

Analysis of Fault Permeability Using Mapping and Flow Modeling, Hickory Sandstone Aquifer, Central Texas

Reservoir compartments, typical targets for infill well locations, are commonly created by faults that may reduce permeability. A narrow fault may consist of a complex assemblage of deformation elements that result in spatially variable and anisotropic permeabilities. We report on the permeability structure of a km-scale fault sampled through drilling a faulted siliciclastic aquifer in central Texas. Probe and whole-core permeabilities, serial CAT scans, and textural and structural data from the selected core samples are used to understand permeability structure of fault zones and develop predictive models of fault zone permeability. Using numerical flow simulation, it is possible to predict permeability anisotropy associated with faults and evaluate the effect of individual deformation elements in the overall permeability tensor. We found relationships between the permeability of the host rock and those of the highly deformed (HD) fault-elements according to the fault throw. The lateral continuity and predictable permeability of the HD fault elements enhance capability for estimating the effects of subseismic faulting on fluid flow in low-shale reservoirs.

58 GEOSCIENCES↗
DOE OSTI2020

Automated fault detection of residential air-conditioning systems using thermostat drive cycles

Residential air conditioning equipment comprises a significant portion of the total energy consumption of a home. Unfortunately, air-conditioning systems can be susceptible to faulty operation either from installation errors or faults that accrue over the equipment’s lifetime. This paper presents a novel automated fault detection algorithm for residential air-conditioning systems that can alert the homeowner of the presence of these faults. The proposed algorithm utilizes only the home’s thermostat and outside air temperature to perform automated fault detection over the course of the equipment’s lifetime, including immediately after installation. The algorithm uses an extended Kalman filter approach to identify a three-resistor, two-capacitor (3R2C) electrical equivalent thermodynamic model. The identified 3R2C model is used to predict cooling times during a testing period comprising of a series of thermostat drive-cycle experiments. We tested the algorithm on an EnergyPlus™ model of a typical residential building in Orlando, Florida. Duct faults, indoor airflow faults, and refrigerant undercharge faults were introduced into the building model one at a time. The algorithm was able to accurately determine duct-leak faults, 40% airflow faults, 40% undercharge faults, and no-fault cases with an accuracy of 70%, 77%, 82%, and 87%, respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Dynamic simulation of CO 2 -injection-induced fault rupture with slip-rate dependent friction coefficient

It is known that poro-elastic stress and effective stress reduction associated with deep underground fluid injection can potentially trigger shear rupture along pre-existing faults. We modeled an idealized CO 2 injection scenario, to assess the effects on faults in the first phase of a generic CO 2 aquifer storage operation. We used coupled multiphase fluid flow and geomechanical numerical modeling to evaluate the stress and pressure perturbations induced by fluid injection and the response of a nearby normal fault. Slip-rate dependent friction and inertial effects have been taken into account during rupture. Contact elements have been used to take into account the frictional behavior of the rupture plane. We investigated different scenarios of injection rate to induce rupture on the fault, employing various fault rheologies. Published laboratory data on CO 2 -saturated intact and crushed rock samples, representative of a potential target aquifer, sealing formation and fault gouge, have been used to define a scenario where different fault rheologies apply at different depths. Nucleation of fault rupture takes place at the bottom of the reservoir, in agreement with analytical poro-elastic stress calculations, depending on injection-induced reservoir inflation and the tectonic stress scenario. For the stress state considered here, the first triggered rupture always produces the largest rupture length and slip magnitude, both of which correlate with the fault rheology. Velocity weakening produces larger ruptures and generates larger magnitude seismic events. Heterogeneous faults have been considered including velocity-weakening or velocity strengthening sections inside and below the aquifer, with the upper sections being velocity-neutral. Nucleation of rupture in a velocity-strengthening section results in a limited rupture extension, both in terms of maximum slip and rupture length. For a heterogeneous fault with nucleation in a velocity-weakening section, the rupture may propagate into the overlying velocity-neutral section, if the extent of velocity-weakening and associated friction drop are large enough.

58 GEOSCIENCES↗
DOE OSTI2021

Fault Detection on Seismic Structural Images Using a Nested Residual U-Net

Automatic identification of faults on seismic structural images is a challenging yet crucial task in quantitative seismic interpretation. Human picking or attribute-based fault detection methods may misidentify faults on noisy, complex seismic images. In this work, we develop a new automatic fault detection method using a nested residual U-shaped convolutional neural network. Each of the encoders and decoders in this neural network is a residual U-Net, leading to a nested architecture. The final fault map results from the fusion of three fault maps with low, medium, and high fault resolutions. We demonstrate the excellent fault-detection capability of our nested neural network using a series of synthetic and field seismic images. We find that our approach produces clearer and more interpretable fault maps than the current state-of-the-art U-Net fault detection method, particularly on noisy seismic images. Our new automatic fault detection method can facilitate reliable quantitative seismic interpretation on field seismic images.

58 GEOSCIENCES↗
DOE OSTI2022

Barriers to Broader Utilization of Fault Detection Technologies for Improving Residential HVAC Equipment Efficiency

Faults in residential heating, ventilating, and air conditioning (HVAC) equipment may occur due to poor installation practices or develop over time, and these faults can negatively impact system efficiency, thermal comfort, and equipment lifespan. Automated fault detection and diagnostic (AFDD) technologies identify energy wasting HVAC faults, such as low indoor airflow and improper refrigerant charge, and guide technicians in improving system efficiency. For residential HVAC, AFDD consists of a range of fault detecting and diagnostic capabilities, sensor configurations, and target applications. AFDD technology can either be permanently installed by the original equipment manufacturer (OEM) using embedded sensors or as an add-on product either during or after installation. Additionally, several advanced installation tools and refrigerant gauge sets include AFDD features for temporary use during equipment installation and tune-ups. Some technologies can detect a fault but have limited diagnostic capabilities. For example, a single-point measurement from the home's thermostat or energy monitor can provide certain fault detection capability by analyzing the equipment runtime or energy consumption. These technologies, though limited at determining the cause of a given fault, may have significant energy savings potential due to their low cost and prevalence in the residential HVAC market. Despite the potential benefits, fault detection technologies face many technical and market barriers preventing broad adoption. Beyond the cost barriers due to the added sensor requirements and technology development, fault detection technologies face many implementation and adoption barriers such as installer training, customer awareness, standardized communication protocols, and methods of test for evaluating accuracy. The purpose of this whitepaper is to characterize market and technical barriers impeding broader utilization of fault detection technology for residential HVAC energy efficiency applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Random Forest Regressor-Based Approach for Detecting Fault Location and Duration in Power Systems

Power system failures or outages due to short-circuits or “faults” can result in long service interruptions leading to significant socio-economic consequences. It is critical for electrical utilities to quickly ascertain fault characteristics, including location, type, and duration, to reduce the service time of an outage. Existing fault detection mechanisms (relays and digital fault recorders) are slow to communicate the fault characteristics upstream to the substations and control centers for action to be taken quickly. Fortunately, due to availability of high-resolution phasor measurement units (PMUs), more event-driven solutions can be captured in real time. In this paper, we propose a data-driven approach for determining fault characteristics using samples of fault trajectories. A random forest regressor (RFR)-based model is used to detect real-time fault location and its duration simultaneously. This model is based on combining multiple uncorrelated trees with state-of-the-art boosting and aggregating techniques in order to obtain robust generalizations and greater accuracy without overfitting or underfitting. Four cases were studied to evaluate the performance of RFR: 1. Detecting fault location (case 1), 2. Predicting fault duration (case 2), 3. Handling missing data (case 3), and 4. Identifying fault location and length in a real-time streaming environment (case 4). A comparative analysis was conducted between the RFR algorithm and state-of-the-art models, including deep neural network, Hoeffding tree, neural network, support vector machine, decision tree, naive Bayesian, and K-nearest neighborhood. Experiments revealed that RFR consistently outperformed the other models in detection accuracy, prediction error, and processing time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Development of Asset Fault Signatures for Prognostic and Health Management in the Nuclear Industry

Proactive online monitoring in the nuclear industry is being explored using the Electric Power Research Institute’s Fleet-Wide Prognostic and Health Management (FW-PHM) Suite software. The FW-PHM Suite is a set of web-based diagnostic and prognostic tools and databases that serves as an integrated health monitoring architecture. The FW-PHM Suite has four main modules: Diagnostic Advisor, Asset Fault Signature (AFS) Database, Remaining Useful Life Advisor, and Remaining Useful Life Database. This paper focuses on development of asset fault signatures to assess the health status of generator step-up generators and emergency diesel generators in nuclear power plants. Asset fault signatures describe the distinctive features based on technical examinations that can be used to detect a specific fault type. At the most basic level, fault signatures are comprised of an asset type, a fault type, and a set of one or more fault features (symptoms) that are indicative of the specified fault. The AFS Database is populated with asset fault signatures via a content development exercise that is based on the results of intensive technical research and on the knowledge and experience of technical experts. The developed fault signatures capture this knowledge and implement it in a standardized approach, thereby streamlining the diagnostic and prognostic process. This will support the automation of proactive online monitoring techniques in nuclear power plants to diagnose incipient faults, perform proactive maintenance, and estimate the remaining useful life of assets.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Fault Current Control and Protection in a Standalone DC Microgrid Using Adaptive Droop and Current Derivative

This report presents a novel fault detection, characterization, and fault current control algorithm for a standalone solar-photovoltaic (PV) based dc microgrids. The protection scheme is based on the current derivative algorithm. The overcurrent and current directional/differential comparison based protection schemes are incorporated for the dc microgrid fault characterization. For a low impedance fault, the fault current is controlled based on the current/voltage thresholds and current direction. Generally, the droop method is used to control the power-sharing between the converters by controlling the reference voltage. In this article, an adaptive droop scheme is also proposed to control the fault current by calculating a virtual resistance R droop , and to control the converter output reference voltage. For a high impedance fault, differential comparison method is used to characterize the fault. These algorithms effectively control the converter pulsewidth and reduce the flow of source current from a particular converter, which helps to increase the fault clearing time. Additionally, a trip signal is sent to the corresponding dc circuit breaker (DCCB), to isolate the faulted converter, feeder or a dc bus. The dc microgrid protection design procedure is detailed, and the performance of the proposed method is verified by simulation analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Evaluation of HVAC & refrigeration system fault behaviors and impacts: A systematic review

Achieving the goals of green buildings critically depends on the fault-free operation of heating, ventilation and air conditioning and refrigeration (HVAC&R) systems. However, faults frequently occur in these systems, causing a range of negative consequences, including increased energy consumption, diminished operational performance, compromised indoor environmental quality, higher operational costs, and shortened system lifespan. The evaluation of fault behaviors and impacts plays a critical role in revealing fault characteristics and consequently supports many research areas, including the design of the high-performance equipment, development of fault detection and diagnostics (FDD) and robust control approaches, as well as the enhancement of maintenance decision-making activities. This paper systematically reviews 112 research publications that reported the analysis and evaluation of fault behaviors and impacts in HVAC&R systems over the past thirty years. Here, we designed a review approach to address five crucial research questions, namely: 1) the objectives of analysis and evaluation of fault behaviors and impacts, 2) data sources, 3) equipment/system types and fault types, 4) evaluation methods including evaluation measures and associated metrics, and 5) challenges and future directions in the research on evaluating of fault behaviors and impacts. In-depth discussions on these questions help bridge the gap between the evaluation of fault behaviors and impacts and their practical applications, such as the development of high-performance systems, fault models, FDD methods, and maintenance decision-making tools within the HVAC&R FDD domain.

Chen, Yimin [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2018

Interseismic Ground Deformation and Fault Slip Rates in the Greater San Francisco Bay Area From Two Decades of Space Geodetic Data

The detailed spatial variations of strain accumulation and creep on major faults in the northern San Francisco Bay Area (North Bay), which are important for seismic potential and evaluation of natural hazards, remain poorly understood. We combine interferometric synthetic aperture radar data from the ERS-1/2 and Envisat satellites between 1992 and 2010 with continuous and campaign GPS data to obtain a high spatial and temporal coverage of ground deformation of the North Bay. The SAR data from both ascending and descending orbits are combined to separate horizontal and vertical components of the deformation. We jointly invert the horizontal component of the mean velocities derived from these data to infer the deep strike-slip rates on major locked faults. We use the estimated deep rates to simulate the long-wavelength deformation due to interseismic elastic strain accumulation along these locked faults. After removing the long-wavelength signal from the InSAR horizontal mean velocity field, we estimate fault-parallel surface creep rates of up to 2 mm/year along the central section of the Rodgers Creek fault and surface creep rates ranging between 2 and 4 mm/year along the Concord fault. No surface creep is geodetically resolved along the West Napa and Green Valley fault zones. We identified characteristically repeating earthquakes on the Rodgers Creek fault, the West Napa fault, the Green Valley fault, and the Concord fault. Finally, nontectonic deformation in the Geysers geothermal field and in Late Cenozoic basins (Rohnert Park and Sonoma basins) are also observed, likely due to hydrological and sediment-compaction processes, respectively.

58 GEOSCIENCES↗
DOE OSTI2017

Internal structure of the San Jacinto fault zone at Blackburn Saddle from seismic data of a linear array

Local and teleseismic earthquake waveforms recorded by a 180-m-long linear array (BB) with seven seismometers crossing the Clark fault of the San Jacinto fault zone northwest of Anza are used to image a deep bimaterial interface and core damage structure of the fault. Delay times of P waves across the array indicate an increase in slowness from the southwest most (BB01) to the northeast most (BB07) station. Automatic algorithms combined with visual inspection and additional analyses are used to identify local events generating fault zone head and trapped waves. The observed fault zone head waves imply that the Clark fault in the area is a sharp bimaterial interface, with lower seismic velocity on the southwest side. The moveout between the head and direct P arrivals for events within ~40 km epicentral distance indicates an average velocity contrast across the fault over that section and the top 20 km of 3.2 per cent. A constant moveout for events beyond ~40 km to the southeast is due to off-fault locations of these events or because the imaged deep bimaterial interface is discontinuous or ends at that distance. The lack of head waves from events beyond ~20 km to the northwest is associated with structural complexity near the Hemet stepover. Events located in a broad region generate fault zone trapped waves at stations BB04–BB07. Waveform inversions indicate that the most likely parameters of the trapping structure are width of ~200 m, S velocity reduction of 30–40 per cent with respect to the bounding blocks, Q value of 10–20 and depth of ~3.5 km. The trapping structure and zone with largest slowness are on the northeast side of the fault. The observed sense of velocity contrast and asymmetric damage across the fault suggest preferred rupture direction of earthquakes to the northwest. This inference is consistent with results of other geological and seismological studies.

58 GEOSCIENCES↗
DOE OSTI2016

Late Quaternary slip-rate along the central Bangong-Chaxikang segment of the Karakorum fault, western Tibet

Insight into the spatial and temporal changes of slip-rate is essential to understand the kinematic role of large strike-slip faults in continental collision zones. Geodetic and geologic rates from present to several million years ago along the Karakorum fault range from 0 to 11 mm/yr. Here, we determine the first late Quaternary slip-rate at the southern end of the linear Bangong-Chaxikang segment of the Karakorum fault, using cumulative offsets (20–200 m) of fans and terraces at three sites, as well as 74 new 10 Be surface-exposure ages to constrain the age of these offset geomorphic markers. The rate is >3 mm/yr at sites Gun and Chaxikang, and it is >1.7–2.2 mm/yr at the Gar fan site. Together with rates obtained along the southernmost Menshi-Kailas segment, the Karakorum fault slip-rate seems to increase southeastward from south of Bangong Lake to Kailas (from >3 to >8 mm/yr). These Karakorum fault slip-rate data (>3–8 mm/yr), together with the total length of the fault (>1000 km) and its initiation age (>13–23 Ma), confirm that the Karakorum fault is the major fault accommodating dextral strike-slip motion NE of the western Himalayas. Furthermore, the dextral Karakorum fault in the south and the conjugate left-lateral Longmu Co–Altyn Tagh fault system in the north are thus the major strike-slip faults of western Tibet, which contribute to eastward extrusion of Tibet.

58 GEOSCIENCES↗
DOE OSTI2017

What does fault tolerant Deep Learning need from MPI?

Deep Learning (DL) algorithms have become the {\em de facto} Machine Learning (ML) algorithm for large scale data analysis. DL algorithms are computationally expensive -- even distributed DL implementations which use MPI require days of training (model learning) time on commonly studied datasets. Long running DL applications become susceptible to faults -- requiring development of a fault tolerant system infrastructure, in addition to fault tolerant DL algorithms. This raises an important question: {\em What is needed from MPI for designing fault tolerant DL implementations?} In this paper, we address this problem for permanent faults. We motivate the need for a fault tolerant MPI specification by an in-depth consideration of recent innovations in DL algorithms and their properties, which drive the need for specific fault tolerance features. We present an in-depth discussion on the suitability of different parallelism types (model, data and hybrid); a need (or lack thereof) for check-pointing of any critical data structures; and most importantly, consideration for several fault tolerance proposals (user-level fault mitigation (ULFM), Reinit) in MPI and their applicability to fault tolerant DL implementations. We leverage a distributed memory implementation of Caffe, currently available under the Machine Learning Toolkit for Extreme Scale (MaTEx). We implement our approaches by extending MaTEx-Caffe for using ULFM-based implementation. Our evaluation using the ImageNet dataset and AlexNet neural network topology demonstrates the effectiveness of the proposed fault tolerant DL implementation using OpenMPI based ULFM.

Amatya, Vinay C.↗
DOE OSTI2016

OpenStudio® Fault Models Gem [SWR-15-23]

Overview of the OpenStudio® Fault Models Gem: Creating a comprehensive library of OpenStudio® fault models. Features: - Physics-based fault impact simulation within the capability of EnergyPlus®/OpenStudio® - Fault intensity implementation simulating how severe faults are (e.g., how much portion is fouled in the condenser heat exchanger) and estimating the impact of a fault in different fault intensities. - Fault evolution implementation simulating evolving/increasing fault intensity through certain period of time. Future goals: - what are common/typical faults in different sample spaces (e.g., HVAC system type, building operation type, building location etc.)? - how often (e.g., incidence and prevalence) faults occur in different sample spaces (e.g., HVAC system type, building operation type, building location etc.)?

Frank, Stephen↗
DOE OSTI2013

Series and parallel arc-fault circuit interrupter tests.

While the 2011 National Electrical Codeª (NEC) only requires series arc-fault protection, some arc-fault circuit interrupter (AFCI) manufacturers are designing products to detect and mitigate both series and parallel arc-faults. Sandia National Laboratories (SNL) has extensively investigated the electrical differences of series and parallel arc-faults and has offered possible classification and mitigation solutions. As part of this effort, Sandia National Laboratories has collaborated with MidNite Solar to create and test a 24-string combiner box with an AFCI which detects, differentiates, and de-energizes series and parallel arc-faults. In the case of the MidNite AFCI prototype, series arc-faults are mitigated by opening the PV strings, whereas parallel arc-faults are mitigated by shorting the array. A range of different experimental series and parallel arc-fault tests with the MidNite combiner box were performed at the Distributed Energy Technologies Laboratory (DETL) at SNL in Albuquerque, NM. In all the tests, the prototype de-energized the arc-faults in the time period required by the arc-fault circuit interrupt testing standard, UL 1699B. The experimental tests confirm series and parallel arc-faults can be successfully mitigated with a combiner box-integrated solution.

Johnson, Jay Dean↗
DOE OSTI2013

Award ER25750: Coordinated Infrastructure for Fault Tolerance Systems Indiana University Final Report

The main purpose of the Coordinated Infrastructure for Fault Tolerance in Systems initiative has been to conduct research with a goal of providing end-to-end fault tolerance on a systemwide basis for applications and other system software. While fault tolerance has been an integral part of most high-performance computing (HPC) system software developed over the past decade, it has been treated mostly as a collection of isolated stovepipes. Visibility and response to faults has typically been limited to the particular hardware and software subsystems in which they are initially observed. Little fault information is shared across subsystems, allowing little flexibility or control on a system-wide basis, making it practically impossible to provide cohesive end-to-end fault tolerance in support of scientific applications. As an example, consider faults such as communication link failures that can be seen by a network library but are not directly visible to the job scheduler, or consider faults related to node failures that can be detected by system monitoring software but are not inherently visible to the resource manager. If information about such faults could be shared by the network libraries or monitoring software, then other system software, such as a resource manager or job scheduler, could ensure that failed nodes or failed network links were excluded from further job allocations and that further diagnosis could be performed. As a founding member and one of the lead developers of the Open MPI project, our efforts over the course of this project have been focused on making Open MPI more robust to failures by supporting various fault tolerance techniques, and using fault information exchange and coordination between MPI and the HPC system software stack from the application, numeric libraries, and programming language runtime to other common system components such as jobs schedulers, resource managers, and monitoring tools.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A strainmeter array as the fulcrum of novel observatory sites along the Alto Tiberina Near Fault Observatory

Fault slip is a complex natural phenomenon involving multiple spatiotemporal scales from seconds to days to weeks. To understand the physical and chemical processes responsible for the full fault slip spectrum, a multidisciplinary approach is highly recommended. The Near Fault Observatories (NFOs) aim at providing high-precision and spatiotemporally dense multidisciplinary near-fault data, enabling the generation of new original observations and innovative scientific products. The Alto Tiberina Near Fault Observatory is a permanent monitoring infrastructure established around the Alto Tiberina fault (ATF), a 60 km long low-angle normal fault (mean dip 20°), located along a sector of the Northern Apennines (central Italy) undergoing an extension at a rate of about 3 mm yr –1 . The presence of repeating earthquakes on the ATF and a steep gradient in crustal velocities measured across the ATF by GNSS stations suggest large and deep (5–12 km) portions of the ATF undergoing aseismic creep. Both laboratory and theoretical studies indicate that any given patch of a fault can creep, nucleate slow earthquakes, and host large earthquakes, as also documented in nature for certain ruptures (e.g., Iquique in 2014, Tōhoku in 2011, and Parkfield in 2004). Nonetheless, how a fault patch switches from one mode of slip to another, as well as the interaction between creep, slow slip, and regular earthquakes, is still poorly documented by near-field observation. With the strainmeter array along the Alto Tiberina fault system (STAR) project, we build a series of six geophysical observatory sites consisting of 80–160 m deep vertical boreholes instrumented with strainmeters and seismometers as well as meteorological and GNSS antennas and additional seismometers at the surface. By covering the portions of the ATF that exhibits repeated earthquakes at shallow depth (above 4 km) with these new observatory sites, we aim to collect unique open-access data to answer fundamental questions about the relationship between creep, slow slip, dynamic earthquake rupture, and tectonic faulting.

58 GEOSCIENCES↗