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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Simulations of CO 2 injection into fractures and faults for improving their geophysical characterization at EGS sites

Here, we propose the use of CO 2 in push-pull well tests to improve geophysical identification and characterization of fractures and faults at enhanced geothermal system (EGS) sites. Using TOUGH2/ECO2N, we carried out numerical experiments of push-pull injection-production cycling of CO 2 into idealized vertical fractures and faults to produce pressure-saturation-temperature conditions that can be analyzed for their geophysical response. Our results show that there is a strong difference between injection and production mainly because of CO 2 buoyancy. While the CO 2 -plume grows laterally and upward during injection, not all CO 2 is recovered during the subsequent production phase. Even under the best conditions for recovery, at least 10% of the volume of the pores still remains filled with CO 2 . To improve EGS characterization, comparisons can be made of active seismic methods carried out before and after (time lapse mode) CO 2 injection into the fracture or fault. Here we find that across the CO 2 saturation range, C11 (the normal stiffness in the horizontal direction perpendicular to the fracture plane) varies between maximum and minimum values by about 15%. It reaches a maximum at around 6% gas saturation, decreasing exponentially to a minimum at higher saturations. Finally, our results suggest that CO 2 injection can be effectively used to infiltrate fault and fracture zones reaching about optimal saturation values in order to enhance seismic imaging at EGS sites.

58 GEOSCIENCES↗
DOE OSTI2019

Single-Submodule Open-Circuit Fault Diagnosis for a Modular Multi-level Converter Using Artificial Intelligent-based Techniques

Modular multi-level converters (MMCs) are one of the promising topologies in recent years for medium or high voltage applications. They are considered as the next generation DC/AC converters for medium/high voltage (MV/HV) motor drive applications due to their transform-less structures, high efficiency and modularity. Reliability is one of the most important challenges in MMCs, since a large number of power switching devices are used and each of these devices can be considered as a potential failure point. It is significant to detect and locate the fault accurately and apply appropriate protections in a timely manner. This paper investigates the behavior of the failure submodules and healthy submodules and use artificial neural network (ANN) classification algorithms for singlesubmodule open-circuit fault diagnosis. The ANN algorithm is implemented in field programmable gate array (FPGA) and the ANN parameters training is completed offline in Matlab. Experimental results of the proposed fault diagnosis for a singlemodule open-circuit fault are presented in this paper.

artificial intelligent↗
DOE OSTI2014

Characteristic investigation and control of a modular multilevel converter-based HVDC system under single-line-to-ground fault conditions

This paper presents the analysis and control of a multilevel modular converter (MMC)-based HVDC transmission system under three possible single-line-to-ground fault conditions, with special focus on the investigation of their different fault characteristics. Considering positive-, negative-, and zero-sequence components in both arm voltages and currents, the generalized instantaneous power of a phase unit is derived theoretically according to the equivalent circuit model of the MMC under unbalanced conditions. Based on this model, a novel double-line frequency dc-voltage ripple suppression control is proposed. This controller, together with the negative-and zero-sequence current control, could enhance the overall fault-tolerant capability of the HVDC system without additional cost. To further improve the fault-tolerant capability, the operation performance of the HVDC system with and without single-phase switching is discussed and compared in detail. Lastly, simulation results from a three-phase MMC-HVDC system generated with MATLAB/Simulink are provided to support the theoretical analysis and proposed control schemes.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Behavior of Single-Line-Ground Faults in Inverter-Based Resource Dominated Grids Explained

It has been observed by protection engineers that it is difficult for a protective relay to identify the faulted phase during a single-line-ground (SLG) fault in a power system with a high ingression of inverter-based resources (IBR) using currents (phase or sequence). Further studies using electromagnetic transient (EMT) simulation show that the initial operating conditions of the IBRs influence the response of phase currents during an SLG fault. In this letter, we conduct a quantitative analysis using sequence components. We find that the pre-fault condition determines the relative position of the current contributed by the grid versus that from the IBR, and further dictates which phase has the largest magnitude during an SLG condition. Finally, this finding is further verified by the EMT simulation results.

electromagnetic transient simulation↗
DOE OSTI2015

A Framework For Evaluating Comprehensive Fault Resilience Mechanisms In Numerical Programs

As HPC systems approach Exascale, their circuit feature will shrink, while their overall size will grow, all at a fixed power limit. These trends imply that soft faults in electronic circuits will become an increasingly significant problem for applications that run on these systems, causing them to occasionally crash or worse, silently return incorrect results. This is motivating extensive work on application resilience to such faults, ranging from generic techniques such as replication or checkpoint/restart to algorithm-specific error detection and resilience techniques. Effective use of such techniques requires a detailed understanding of (1) which vulnerable parts of the application are most worth protecting (2) the performance and resilience impact of fault resilience mechanisms on the application. This paper presents FaultTelescope, a tool that combines these two and generates actionable insights by presenting in an intuitive way application vulnerabilities and impact of fault resilience mechanisms on applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

IoT-Based Comfort Control and Fault Diagnostics System for Energy-Efficient Homes

This project studies an Internet of Things (IoT)-based comfort control and fault diagnostics system (referred as iComfort in this report) for energy-efficient homes. The system delivers an occupant-comfort-oriented thermal environment adaptive to fault scenarios and achieves HVAC energy savings in a cost-effective and straightforward way. This smart iComfort home system consists of the following key features. 1) Cost-effectiveness and scalability of the entire hardware and software system: The system includes low-cost temperature, humidity, and airflow sensors, and a Raspberry Pi-based local hub that interfaces with the cloud and IoT-enabled devices. The cost is low, not only for sensors, but also the costs associated with sensor installation, system setup and commissioning, data communication and storage, and data analytics (e.g., the development of automated fault detection and diagnosis (AFDD), as well as adaptive control strategies that are both computationally efficient and practical to implement). 2) Energy performance and user satisfaction: The system delivers user satisfaction and energy savings. This includes a) ease of use, b) optimal occupant thermal comfort, and c) accurate system feedback (e.g., low false alarm of AFDD strategies). 3) Favorable demonstrated prototype performance: The prototype tested at the Pacific Northwest National Laboratory (PNNL) Lab Homes demonstrates the accuracy of fault detections and diagnoses and shows thermal comfort improvement and energy savings through adaptive and optimal HVAC operations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Representing Small Commercial Building Faults in EnergyPlus, Part I: Model Development

Small commercial buildings (those with less than approximately 1000 m2 of total floor area) often do not have access to cost-effective automated fault detection and diagnosis (AFDD) tools for maintaining efficient building operations. AFDD tools based on machine-learning algorithms hold promise for lowering cost barriers for AFDD in small commercial buildings; however, such algorithms require access to high-quality training data that is often difficult to obtain. To fill the gap in this research area, this study covers the development (Part I) and validation (Part II) of fault models that can be used with the building energy modeling software EnergyPlus® and OpenStudio® to generate a cost-effective training data set for developing AFDD algorithms. Part I (this paper) presents a library of fault models, including detailed descriptions of each fault model structure and their implementation with EnergyPlus. This paper also discusses a case study of training data set generation, representing an actual building.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Permeability Variations Associated With Fault Reactivation in a Claystone Formation Investigated by Field Experiments and Numerical Simulations

We studied the relation between rupture and changes in permeability within a fault zone intersecting the Opalinus Clay formation at 300 m depth in the Mont Terri Underground Research Laboratory (Switzerland). A series of water injection experiments were performed in a borehole straddle interval set within the damage zone of the main fault. A three-component displacement sensor allowed an estimation of the displacement of a minor fault plane reactivated during a succession of step rate pressure tests. The experiment reveals that the fault hydromechanical (HM) behavior is different from one test to the other with varying pressure levels needed to trigger rupture and different slip behavior under similar pressure conditions. Numerical simulations were performed to better understand the reason for such different behavior and to investigate the relation between rupture nucleation, permeability change, pressure diffusion, and rupture propagation. Here, our main findings are as follows: (i) a rate frictional law and a rate-and-state permeability law can reproduce the first test, but it appears that the rate constitutive parameters must be pressure dependent to reproduce the complex HM behavior observed during the successive injection tests; (ii) almost similar ruptures can create or destroy the fluid diffusion pathways; (iii) a too high or too low diffusivity created by the main rupture prevents secondary rupture events from occurring whereas “intermediate” diffusivity favors the nucleation of a secondary rupture associated with the fluid diffusion. However, because rupture may in certain cases destroy permeability, this succession of ruptures may not necessarily create a continuous hydraulic pathway.

58 GEOSCIENCES↗
DOE OSTI2019

Fabrication and Tests of a Resistive-Type Superconducting Fault Current Limiter Module Based on Coated Conductors

The resistivetype superconducting fault current limiter (R-SFCL) is simple in structure, near zero impedance at normal state and can be quickly triggered by the fault current. Thus, it is a possible solution to limit the fault current in the power grid. In this paper, we report the fabrication and test for an R-SFCL module The R-SFCL module consists of seven bifilar coils connected in parallel, which were wound with two parallel 2G tapes. A 5mm spacer was co-wound between adjacent turns to act as the highvoltage insulation. In the tests, we test the current distribution among the bifilar coils, and then simulated short-circuit tests were conducted on the module to obtain its performance under fault current surge.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Local lattice distortion mediated formation of stacking faults in Mg alloys

Long periodic stacking ordered phases (LPSOs), consisting of various configurations of stacking faults, play an important role in developing ultrastrong Mg alloys with moderate ductility. However, their formation mechanisms are far from clear as no apparent defects are introduced during their formation as it is commonly believed that stacking faults are induced by defects. Here, we present the atomic and electronic basis for lattice-distortion-mediated formation of stacking faults, i.e., localized face-centredcubic (FCC) structures, within a Mg-Zn-Y alloy with a hexagonal close-packed (HCP) structure. The atomic motion trajectories from ab-initio molecular dynamic simulations show that the Mg atoms occupying the nearest neighbour positions of Zn and Y solute atoms undergo a local HCP-to-FCC transition. It is revealed that a local lattice distortion caused by the solute atoms enables the Mg atoms to move and rearrange into a local FCC configuration, which is validated by high resolution scanning transmission microscopy and in-situ synchrotron X-ray diffraction. Our simulations provide profound insight into the formation mechanism of stacking faults in HCP Mg and their physical nature of phase transformations. This is not only critically important because conventional defects, such as dislocations and vacancies, are important to deformation for Mg and its alloys, but also because they serve as a potential new approach to the design of advanced Mg alloys when defects could be used to facilitate

36 MATERIALS SCIENCE↗
DOE OSTI2021

Crack fault diagnosis of rotating machine in nuclear power plant based on ensemble learning

Crack faults in rotating machines can cause machine shutdown or scrapping, endangering the normal operation and safety of nuclear power plants. Intelligent diagnostic techniques based on machine learning have the potential to diagnose crack faults. However, problems such as scarcity of field fault data and high noise of plant measurements pose challenges to the application of machine learning. Here this study proposes an ensemble learning approach to mitigate the negative impacts of the problems. Ensemble learning is a strategy for combining multiple machine learning models into a composite model. The basic idea of ensemble learning is that even if one model makes a mistake, other models can correct it. Case studies based on bearing and gear system fault experiments show that the proposed ensemble learning models have better diagnostic results than the single model in the presence of noise and small data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Design of machine learning models with domain experts for automated sensor selection for energy fault detection

Data-driven techniques that extract insights from sensor data reduce the cost of improving system energy performance through fault detection and system health monitoring. To lower cost barriers to widespread deployment, a methodology is proposed that takes advantage of existing sensor data, encodes expert knowledge about the application system to create ‘virtual sensors’ and applies statistical and mathematical methods to reduce the time required for manual configurations. The approach combines sensor data points with encoded expert knowledge that is generic to the application system but independent of a particular deployment, thereby reducing the need to tailor to individual deployments. Additionally, this paper not only presents a method that detects faults from measured energy data, but also (1) describes an engagement method with experts in the energy system domain to identify data, (2) integrates domain knowledge with the data, (3) automatically selects from among the large pool of potential input data, and (4) uses machine learning to automatically build a data-driven fault detection model. Demonstration on a commercial building chiller plant shows that only a small number of virtual sensors is necessary for fault detection with high accuracy rates. This corresponds to the use of only five out of 52 original sensor data points features. With as few as four features, classification F1 scores exceed 90% on the training set and 80% on the testing set. The results are implementable and realizable using off-the-shelf tools. The goal is to design with domain experts an energy monitoring system that can be configured once and then widely deployed with little additional cost or effort.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Feedback-Based Fault-Tolerant and Health-Adaptive Optimal Charging of Batteries

The key technology barriers that hinder the growth of Electric Vehicles (EVs) are long charging time, the shorter life-time of EV batteries, and battery safety. Specifically, EV charging protocols have significant effects on battery lifetime and safety. If not charged properly, the battery could end up with shorter life, and more importantly, improper charging can cause battery faults leading to catastrophic failures. To overcome these barriers, we propose a closed-loop feedback based approach, that enables real-time optimal fast charging protocol adaptation to battery health and possess active diagnostic capabilities in the sense that, during charging, it detects real-time faults and takes corrective action to mitigate such fault effects. We utilize battery electrical-thermal model, explicit battery capacity and power fade aging models, and thermal fault model to capture battery behavior. In conjunction with the models, we adopt linear quadratic optimal control techniques to realize the feedback-based control algorithm. Simulation studies are presented to illustrate the effectiveness of the proposed scheme.

batteries↗
DOE OSTI2016

Ab initio study of point defects near stacking faults in 3C-SiC

Interactions between point defects and stacking faults in 3C-SiC are studied using an ab initio method based on density functional theory. The results show that the discontinuity of the stacking sequence considerably affects the configurations and behavior of intrinsic defects, especially in the case of silicon interstitials. The existence of an intrinsic stacking fault (missing a C-Si bilayer) shortens the distance between the tetrahedral-center site and its second-nearest-neighboring silicon layer, making the tetrahedral silicon interstitial unstable. Instead of a tetrahedral configuration with four C neighbors, a pyramid-like interstitial structure with a defect state within the band gap becomes a stable configuration. In addition, orientation rotation occurs in the split interstitials that has diverse effects on the energy landscape of silicon and carbon split interstitials in the stacking fault region. Moreover, our analyses of ionic relaxation and electronic structure of vacancies show that the built-in strain field, owing to the existence of the stacking fault, makes the local environment around vacancies more complex than that in the bulk.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Dynamic modeling of injection-induced fault reactivation and ground motion and impact on surface structures and human perception

We summarize recent modeling studies of injection-induced fault reactivation, seismicity, and its potential impact on surface structures and nuisance to the local human population. We used coupled multiphase fluid flow and geomechanical numerical modeling, dynamic wave propagation modeling, seismology theories, and empirical vibration criteria from mining and construction industries. We first simulated injection-induced fault reactivation, including dynamic fault slip, seismic source, wave propagation, and ground vibrations. From co-seismic average shear displacement and rupture area, we determined the moment magnitude to about M w = 3 for an injection-induced fault reactivation at a depth of about 1000 m. We then analyzed the ground vibration results in terms of peak ground acceleration (PGA), peak ground velocity (PGV), and frequency content, with comparison to the U.S. Bureau of Mines’ vibration criteria for cosmetic damage to buildings, as well as human-perception vibration limits. For the considered synthetic M w = 3 event, our analysis showed that the short duration, high frequency ground motion may not cause any significant damage to surface structures, and would not cause, in this particular case, upward CO 2 leakage, but would certainly be felt by the local population.

58 GEOSCIENCES↗
DOE OSTI2017

Numerical modeling of fluid flow in a fault zone: a case of study from Majella Mountain (Italy)

We present the preliminary results of a numerical model of fluid flow in a fault zone, based on field data acquired at the Majella Mountain, (Italy). The fault damage zone is described as a discretely fractured medium, and the fault core as a porous medium. Our model utilizes dfnWorks, a parallelized computational suite, developed at Los Alamos National Laboratory to model the damage zone and characterizes its hydraulic parameters. We present results from the field investigations and the basic computational workflow, along with preliminary results of fluid flow simulations at the scale of the fault.

58 GEOSCIENCES↗
DOE OSTI2025

Active multi-mode data analysis to improve fault diagnosis in AHUs

Faults in heating, ventilation and air conditioning systems can lead to increased energy consumption, occupant comfort issues, and reduced equipment lifetime. Commercial fault detection and diagnosis (FDD) tools has been increasingly deployed in U.S. commercial buildings. While they are helping to achieve energy efficiency and operational reliability, there remain gaps in their fault diagnostic capabilities. The diagnostic results often contain multiple distinct candidate root causes (CRCs) or offer no insight into CRCs. This study developed a novel active rule-based multi-mode data analysis method to enhance diagnostic resolution by applying proven rule sets and additional new rules to data from multiple known operational modes. The proposed method was demonstrated using enhanced air handling unit performance assessment rule sets and validated with the simulated data of two air handling units. New metrics, namely, reduced number of CRCs and improvement ratio, were developed to quantify the improvement of fault diagnostic resolution. The validation results showed that the proposed method effectively reduced the number of CRCs in contrast to analyzing data solely for a single mode of operation. It achieved a median improvement ratio of 80% in 19 test cases.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Cooperative fault management for resilient integration of renewable energy

Cooperative fault management (CFM) is designed herein to control different types of renewable energy resources cooperatively during electrical faults. This paper studies systems with a high penetration of photovoltaic (PV) energy and wind energy. First, CFM leverages power converters of PV farms to boost the ride-through capability of nearby doubly-fed induction generators (DFIGs). By controlling PV farms’ output voltages to change smoothly during both fault initiation and fault clearance, the widely used crowbar in DFIGs is less likely to be activated. Crowbar activation adversely makes DFIGs lose controllability and absorb reactive power. The second contribution is the development of a software-defined CFM controller and a controller in-the-loop demonstration of the real-time performance of this optimization-based CFM. CFM capitalizes on distributed optimization formulation to enable flexibility, plug-and-play, and privacy-preserving. Computation time, however, is a major concern for optimization-based dynamics control. Here, real-time controller-in-the-loop simulation results show optimization-based CFM can output reference values around 60 ms and is quick enough for dynamic control.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗