SEARCH · Engineering Papers

Results for “fault”

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.

SourceResearch connectionFrom yearThrough year

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

At least 235 records · Page 13

All sources NASA NTRS DOE OSTI

NASA NTRS1993

Analysis of a hardware and software fault tolerant processor for critical applications

Computer systems for critical applications must be designed to tolerate software faults as well as hardware faults. A unified approach to tolerating hardware and software faults is characterized by classifying faults in terms of duration (transient or permanent) rather than source (hardware or software). Errors arising from transient faults can be handled through masking or voting, but errors arising from permanent faults require system reconfiguration to bypass the failed component. Most errors which are caused by software faults can be considered transient, in that they are input-dependent. Software faults are triggered by a particular set of inputs. Quantitative dependability analysis of systems which exhibit a unified approach to fault tolerance can be performed by a hierarchical combination of fault tree and Markov models. A methodology for analyzing hardware and software fault tolerant systems is applied to the analysis of a hypothetical system, loosely based on the Fault Tolerant Parallel Processor. The models consider both transient and permanent faults, hardware and software faults, independent and related software faults, automatic recovery, and reconfiguration.

Dugan, Joanne B.↗

NASA NTRS1995

Earthquake recurrence on the southern San Andreas modulated by fault-normal stress

Earthquake recurrence data from the Pallett Creek and Wrightwood paleoseismic sites on the San Andreas fault appear to show temporal variations in repeat interval. We investigate the interaction between strike-slip faults and auxiliary reverse and normal faults as a physical mechanism capable of producing such variations. Under the assumption that fault strength is a function of fault-normal stress (e.g. Byerlee's Law), failure of an auxiliary fault modifies the strength of the strike-slip fault, thereby modulating the recurrence interval for earthquakes. In our finite element model, auxiliary faults are driven by stress accumulation near restraining and releasing bends of a strike-slip fault. Earthquakes occur when fault strength is exceeded and are incorporated as a stress drop which is dependent on fault-normal stress. The model is driven by a velocity boundary condition over many earthquake cycles. Resulting synthetic strike-slip earthquake recurrence data display temporal variations similar to observed paleoseismic data within time windows surrounding auxiliary fault failures. Our simple model supports the idea that interaction between a strike-slip fault and auxiliary reverse or normal faults can modulate the recurrence interval of events on the strike-slip fault, possibly producing short term variations in earthquake recurrence interval.

Palmer, Randy↗

NASA NTRS2003

Automated Monitoring with a BCP Fault-Decision Test

The Bayesian conditional probability (BCP) technique is a statistical fault-decision technique that is suitable as the mathematical basis of the fault-manager module in the automated-monitoring system and method described in the immediately preceding article. Within the automated-monitoring system, the fault-manager module operates in conjunction with the fault-detector module, which can be based on any one of several fault-detection techniques; examples include a threshold-limit-comparison technique or the BSP or SPRT technique mentioned in the preceding article. The present BCP technique is used to evaluate a series of one or more fault-detection events for the purpose of filtering out occasional false alarms produced by many types of statistical fault-detection procedures. The BCP technique increases the probability that an automated monitoring system produces a correct decision regarding the presence or absence of a fault. Because occasional false alarms are an inevitable consequence of the SPRT, BSP, or any other statistically based fault-detection test, there is a need for a logical procedure to distinguish between true and false alarms. Heretofore, it has been common practice to make a fault decision on an ad hoc basis for example by following a multiple-observation voting strategy in which a signal is declared to be indicative of a fault if m of the last n observations produced a fault-detection alarm. The BCP technique was developed to obtain results more reliable than those afforded by a voting strategy. The BCP technique involves a test in which one applies Bayesian inference techniques to a series of one or more single-observation alarms produced by a fault-detection test. One considers the last n decisions generated by a fault-detection test in order to evaluate the conditional probability that a failure is indicated (see figure). Each new decision reached by a fault-detection test is treated as a new piece of evidence about the state of the monitored asset, and the conditional probability of failure for the system is updated on the basis of this new evidence. The conditional probability of failure is compared with a predefined limit. For a probability below the limit, the asset is declared to be healthy. For a probability above the limit, the asset is declared to be faulty.

Bickford, Randall L.↗

DOE OSTI2022

Using discrete Bayesian networks for diagnosing and isolating cross-level faults in HVAC systems

Fault detection and diagnosis (FDD) technologies are critical to ensure satisfactory building performance, such as reducing energy wastes and negative impacts on occupant comfort and productivity. Existing FDD technologies mainly focus on component-level FDD solutions, which could lead to mis-diagnosis of cross-level faults in heating, ventilating, and air-conditioning (HVAC) systems. Cross-level faults are those faults that occur in one component or subsystem, but cause operational abnormalities in other components or subsystems, and result in a building level performance degradation. How to effectively diagnose the root cause of a cross-level fault is the focus of this study. Here, this paper presents a novel discrete Bayesian Network (DisBN)-based method for diagnosing cross-level faults in an HVAC system commonly used in commercial buildings. A two-level DisBN structure model is developed in this study. The parameters used in the DisBN model are obtained either from expert knowledge or through machine-learning strategies from normal system operation data. Meanwhile, the probability parameters are discretized to incorporate the uncertainties associated with typical expert knowledge. Thus, the developed DisBN method addresses the challenges many other BN based FDD methods face, i.e., the lack of fault data for BN parameter training. The developed DisBN represents causal relationships between a fault and its cross-level system impacts (i.e., fault symptoms or fault indicators) by considering how fault impacts propagate across different levels in an HVAC system. A weather and schedule information-based Pattern Matching (WPM) method is employed to automatically create WPM baseline data sets for each incoming real time snapshot data from the building systems. Consequently, BN inference and real-time diagnostics are achieved by comparing incoming snapshot data and the WPM baseline data set. The proposed method is evaluated using experimental fault data collected in a campus building. Fault diagnosis results demonstrate that the WPM-DisBN method is effective at locating the root causes of cross-level faults in an HVAC system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2014

CO 2 storage and potential fault instability in the St. Lawrence Lowlands sedimentary basin (Quebec, Canada): Insights from coupled reservoir-geomechanical modeling

In this paper, coupled reservoir-geomechanical (TOUGH-FLAC) modeling is applied for the first time to the St. Lawrence Lowlands region to evaluate the potential for shear failure along pre-existing high-angle normal faults, as well as the potential for tensile failure in the caprock units (Utica Shale and Lorraine Group). This activity is part of a general assessment of the potential for safe CO 2 injection into a sandstone reservoir (the Covey Hill Formation) within an Early Paleozoic sedimentary basin. Field and subsurface data are used to estimate the sealing properties of two reservoir-bounding faults (Yamaska and Champlain faults). The spatial variations in fluid pressure, effective minimum horizontal stress, and shear strain are calculated for different injection rates, using a simplified 2D geological model of the Becancour area, located ~110 km southwest of Quebec City. The simulation results show that initial fault permeability affects the timing, localization, rate, and length of fault shear slip. Contrary to the conventional view, our results suggest that shear failure may start earlier for a permeable fault than for a sealing fault, depending on the site-specific geologic setting. In simulations of a permeable fault, shear slip is nucleated along a 60 m long fault segment in a thin and brittle caprock unit (Utica Shale) trapped below a thicker and more ductile caprock unit (Lorraine Group) – and then subsequently progresses up to the surface. In the case of a sealing fault, shear failure occurs later in time and is localized along a fault segment (300 m) below the caprock units. The presence of the inclined low-permeable Yamaska Fault close to the injection well causes asymmetric fluid-pressure buildup and lateral migration of the CO 2 plume away from the fault, reducing the overall risk of CO 2 leakage along faults. Finally, fluid-pressure-induced tensile fracturing occurs only under extremely high injection rates and is localized below the caprock units, which remain intact, preventing upward CO 2 migration.

58 GEOSCIENCES↗

DOE OSTI2017

Novel Coupled Thermochronometric and Geochemical Investigation of Blind Geothermal Resources in Fault-Controlled Dilational Corners

Geothermal plays in extensional and transtensional tectonic environments have long been a major target in the exploration of geothermal resources and the Dixie Valley area has served as a classic natural laboratory for this type of geothermal plays. In recent years, the interactions between normal faults and strike-slip faults, acting either as strain relay zones have attracted significant interest in geothermal exploration as they commonly result in fault-controlled dilational corners with enhanced fracture permeability and thus have the potential to host blind geothermal prospects. Structural ambiguity, complications in fault linkage, etc. often make the selection for geothermal exploration drilling targets complicated and risky. Though simplistic, the three main ingredients of a viable utility-grade geothermal resource are heat, fluids, and permeability. Our new geological mapping and fault kinematic analysis derived a structural model suggest a two-stage structural evolution with (a) middle Miocene N -S trending normal faults (faults cutting across the modern range), - and tiling Olio-Miocene volcanic and sedimentary sequences (similar in style to East Range and S Stillwater Range). NE-trending range-front normal faulting initiated during the Pliocene and are both truncating N-S trending normal faults and reactivating some former normal faults in a right-lateral fashion. Thus the two main fundamental differences to previous structural models are (1) N-S trending faults are pre-existing middle Miocene normal faults and (2) these faults are reactivated in a right-later fashion (NOT left-lateral) and kinematically linked to the younger NE-trending range-bounding normal faults (Pliocene in age). More importantly, this study provides the first constraints on transient fluid flow through the novel application of apatite (U-Th)/He (AHe) and 4 He/ 3 He thermochronometry in the geothermally active Dixie Valley area in Nevada.

(U-Th)/He↗

DOE OSTI2019

Pajarito Fault System Paleoseismic Trenching Project: Phase 1 Report

The Pajarito fault system (PFS) is a late Quaternary, 50-km-long fault system that bounds the western margin of the Rio Grande rift and crosses the western margin of Los Alamos National Laboratory (LANL) in Los Alamos, NM. As currently interpreted, the PFS is the largest contributing seismic source to ground motion hazard at LANL (Wong et al., 2007). Thus, understanding the fault system’s paleoseismic history is important for characterizing seismic hazard at LANL. The PFS consists of several distinct fault sections, from south to north, the Pajarito fault (PF), Guaje Mountain fault (GMF), Rendija Canyon fault (RCF) and Santa Clara Canyon fault (SCCF) (Wong et al., 2007). In the 2007 seismic source model for the LANL PSHA (Wong et al., 2007), the PFS is interpreted to be a single segmented rupture source. An earthquake recurrence model for the PFS was developed for the PSHA based primarily on the results of previous paleoseismic studies performed on the PF, RCF, and GMF (no detailed paleoseismic studies have been performed on the SCCF). LANL’s 2007 updated probabilistic seismic hazard analysis heavily favored the three Holocene event paleoearthquake model, despite having no single subsurface trenching investigation yield evidence for multiple earthquakes in the Holocene. Sensitivity analyses from the most recent PSHA update (Wong et al., 2007) and subsequent review by the LANL Update Steering Committee (USC, 2013) show that the recurrence of earthquakes within the Holocene epoch (~11,700 years ago to the present) along the PFS is significant to hazard. The USC (2013) recommended additional paleoseismic information be collected on the Pajarito fault section of the PFS to test recurrence models presented by Wong et al. (2007) and Lewis et al. (2009). To address the USC (2013) recommendations, a multi-year paleoseismic investigation of the PFS was conceived consisting of several field phases to evaluate the Holocene earthquake history of the PFS. This report presents the results from the initial Phase 1 paleoseismic investigation of the Pajarito fault. Phase 1 included the excavation and interpretation of six paleoseismic trenches, two each at three separate locations on the Pajarito fault - Sites A, B, and C. Sites B and C were located on the primary trace of the Pajarito fault, and Site A was located on an antithetic trace of the Pajarito fault east of the main fault.

58 GEOSCIENCES↗

DOE OSTI2024

Adaptive Fault Current-Limiting Control of MMC for Protection of Multiterminal HVDC Systems

A crucial requirement of the protection system for multi-terminal high-voltage DC (MTDC) transmission is that it is capable of selectively isolating the faulty area from the healthy part of the network using DC circuit breakers (DCCBs), while ensuring continuous operation of converter stations in the healthy part of the network. But in the half-bridge modular multilevel converters (HB-MMCs) based MTDC system, since HB-MMCs do not have fault current absorption capability, when a DC fault occurs, the rising fault currents can quickly reach the blocking threshold within a few milliseconds and disrupt the operation of the MMCs in the healthy part. To facilitate fault-ride-through capability of MTDC system, large DC reactors are often considered in series with DCCBs to reduce the rate of rise of the fault current and prevent blocking the MMCs in the healthy part of the DC networks; however, large DC reactors prohibitively increase the cost of the system, introduce stability issues and can create post-fault oscillations. This paper presents an adaptive fault current-limiting control method for MMCs to avoid their blocking and enable the continuous operation of the healthy part of MTDC systems. The method contains two parts: The first part is based on circulating current feedforward control, which emulates virtual reactors in each arm of an MMC, and is immediately activated when the fault current starts to increase to reduce the rate of rise of the fault current. The second part temporarily bypasses all the submodules when the fault current exceeds a preset threshold, complementing the fault current-limiting effect of the first part. Neither part requires fault detection signals, and they are automatically activated during faults. Simulation case studies of a four-terminal bipolar MMC-based high-voltage DC system are presented to demonstrate the effectiveness of the proposed control methods.

active fault current limiting↗

DOE OSTI2016

Contrasts in compliant fault zone properties inferred from geodetic measurements in the San Francisco Bay area

In crustal fault zones, regions of damaged rock characterized by reduced elastic shear modulus can influence patterns of near-field interseismic deformation. In order to study these compliant fault zones (CFZs) and how they might develop over the lifetimes of faults, we compare two fault segments with contrasting fault age and lithology along the San Andreas Fault in the San Francisco Bay Area. New geodetic measurements of the interseismic velocity fields at each location are used to constrain fault zone parameters through a Markov chain Monte Carlo method. At Black Mountain, in the Santa Cruz Mountains of the San Francisco Peninsula, we do not find evidence for a compliant fault zone; instead, we find that the geodetic data are more consistent with a model of a single fault in a homogeneous elastic half-space. At Lake San Andreas, a younger fault segment 35 km farther north, we find evidence for a compliant fault zone about 3.4 +1.1/-1.4 km wide, containing a shear modulus of about 40% of the shear modulus of the surrounding rock. We also find that the best fitting CFZ model at this location, unlike the best fitting homogeneous half-space model, has a locking depth that agrees well with the observed depth of microseismicity. Based on differences in fault age, cumulative displacement, and lithology between Black Mountain and Lake San Andreas, we infer that lithology plays an important and, in this case, perhaps a dominant role in the accumulation of fault zone damage structures and the development of CFZs over the lifetime of a fault.

58 GEOSCIENCES↗

DOE OSTI2019

Basement Fault Reactivation by Fluid Injection Into Sedimentary Reservoirs: Poroelastic Effects

Abstract To investigate mechanisms of seismic fault reactivation in crystalline basement in response to fluid injection in overlying sedimentary reservoirs, we conducted three‐dimensional finite element simulations to assess the effects of direct pore pressure communication and indirect poroelastic stress transfer on the change in Coulomb failure stress of favorably oriented faults of varying permeability structure in normal, strike‐slip, and reverse faulting stress regimes. We demonstrate that the direct pore pressure effect transmitted along a hydraulically conductive fault exceeds the indirect poroelastic effect, but alone is insufficient for fault reactivation in the basement. The poroelastic effect on the Coulomb failure stress results from induced normal tractions and, to a lesser extent, from induced shear tractions that relate to the flexing of the fault as the reservoir expands poroelastically with fluid injection. Assuming a higher Biot coefficient for reservoir over basement rock as previously reported, the combined direct pore pressure and indirect poroelastic effects result in reactivation of hydraulically conductive faults in the basement in normal and strike‐slip faulting stress regimes and in the reservoir in reverse faulting regimes. Sealing normal faults that are not preferentially conductive also preferentially reactivate in the reservoir. These findings apply to injection in either hanging or footwall of normal and reverse faults. Reducing the contrast in Biot coefficient between reservoir and basement favors fault reactivation in the reservoir for injection in the footwall in normal faulting stress regimes. These simulations demonstrate that geomechanical models without coupled poroelasticity underestimate the potential of fault reactivation in crystalline basement.

Fan, Zhiqiang↗

NASA NTRS1991

A distributed fault-detection and diagnosis system using on-line parameter estimation

The development of a model-based fault-detection and diagnosis system (FDD) is reviewed. The system can be used as an integral part of an intelligent control system. It determines the faults of a system from comparison of the measurements of the system with a priori information represented by the model of the system. The method of modeling a complex system is described and a description of diagnosis models which include process faults is presented. There are three distinct classes of fault modes covered by the system performance model equation: actuator faults, sensor faults, and performance degradation. A system equation for a complete model that describes all three classes of faults is given. The strategy for detecting the fault and estimating the fault parameters using a distributed on-line parameter identification scheme is presented. A two-step approach is proposed. The first step is composed of a group of hypothesis testing modules, (HTM) in parallel processing to test each class of faults. The second step is the fault diagnosis module which checks all the information obtained from the HTM level, isolates the fault, and determines its magnitude. The proposed FDD system was demonstrated by applying it to detect actuator and sensor faults added to a simulation of the Space Shuttle Main Engine. The simulation results show that the proposed FDD system can adequately detect the faults and estimate their magnitudes.

Guo, T.-H.↗

NASA NTRS2018

Optimization of Second Fault Detection Thresholds to Maximize Mission POS

In order to support manned spaceflight safety requirements, the Space Launch System (SLS) has defined program-level requirements for key systems to ensure successful operation under single fault conditions. To accommodate this with regards to Navigation, the SLS utilizes an internally redundant Inertial Navigation System (INS) with built-in capability to detect, isolate, and recover from first failure conditions and still maintain adherence to performance requirements. The unit utilizes multiple hardware- and software-level techniques to enable detection, isolation, and recovery from these events in terms of its built-in Fault Detection, Isolation, and Recovery (FDIR) algorithms. Successful operation is defined in terms of sufficient navigation accuracy at insertion while operating under worst case single sensor outages (gyroscope and accelerometer faults at launch). In addition to first fault detection and recovery, the SLS program has also levied requirements relating to the capability of the INS to detect a second fault, tracking any unacceptable uncertainty in knowledge of the vehicle's state. This detection functionality is required in order to feed abort analysis and ensure crew safety. Increases in navigation state error and sensor faults can drive the vehicle outside of its operational as-designed environments and outside of its performance envelope causing loss of mission, or worse, loss of crew. The criteria for operation under second faults allows for a larger set of achievable missions in terms of potential fault conditions, due to the INS operating at the edge of its capability. As this performance is defined and controlled at the vehicle level, it allows for the use of system level margins to increase probability of mission success on the operational edges of the design space. Due to the implications of the vehicle response to abort conditions (such as a potentially failed INS), it is important to consider a wide range of failure scenarios in terms of both magnitude and time. As such, the Navigation team is taking advantage of the INS's capability to schedule and change fault detection thresholds in flight. These values are optimized along a nominal trajectory in order to maximize probability of mission success, and reducing the probability of false positives (defined as when the INS would report a second fault condition resulting in loss of mission, but the vehicle would still meet insertion requirements within system-level margins). This paper will describe an optimization approach using Genetic Algorithms to tune the threshold parameters to maximize vehicle resilience to second fault events as a function of potential fault magnitude and time of fault over an ascent mission profile. The analysis approach, and performance assessment of the results will be presented to demonstrate the applicability of this process to second fault detection to maximize mission probability of success.

Anzalone, Evan↗

DOE OSTI2022

A phase-field model for quasi-dynamic nucleation, growth, and propagation of rate-and-state faults

Despite its critical role in the study of earthquake processes, numerical simulation of the entire stages of fault rupture remains a formidable task. The main challenges in simulating a fault rupture process include the complex evolution of fault geometry, frictional contact, and off-fault damage over a wide range of spatial and temporal scales. Here, in this paper, we develop a phase-field model for quasi-dynamic fault nucleation, growth, and propagation, which features two standout advantages: (i) it does not require any sophisticated algorithms to represent fault geometry and its evolution; and (ii) it allows for modeling fault nucleation, propagation, and off-fault damage processes with a single formulation. Built on a recently developed phase-field framework for shear fractures with frictional contact, the proposed formulation incorporates rate- and state-dependent friction, radiation damping, and their impacts on fault mechanics and off-fault damage. We show that the numerical results of the phase-field model are consistent with those obtained from well-verified approaches that model the fault as a surface of discontinuity, without suffering from the mesh convergence issue in the existing continuous approaches to fault rupture (e.g., the stress glut method). Further, through numerical examples of fault propagation in various settings, we demonstrate that the phase-field approach may open new opportunities for investigating complex earthquake processes that have remained overly challenging for the existing numerical methods.

58 GEOSCIENCES↗

DOE OSTI2022

Multiple simultaneous faults’ impacts on air-conditioner behavior and performance of a charge diagnostic method

Although there have been several studies that have focused on the effects of faults on the performance and on the characteristic features that could be used to detect faults, almost none of the research has studied the effects of multiple simultaneous faults. Existing fault detection and diagnosis approaches that have been developed based on single faults may struggle with simultaneous faults. Here, this paper is part of a series that present a methodology and comprehensive measurement data from a battery of laboratory tests on an air-conditioner with combinations of common faults (refrigerant charge, evaporator airflow, non-condensable gas, and liquid line restrictions) imposed, to show how the indicator variables and overall performance are impacted. The system has a microtube condenser and a fixed-orifice (FXO) expansion device, which are found to affect the features’ fault sensitivity. This experiment is the first to test these combined faults in an FXO-equipped system, so comparisons are made to a previously studied thermostatic expansion valve-equipped system. Finally, a promising charge diagnostic technology is assessed, to see how it is impacted by other faults. The faults reduced capacity by up to 42%, and efficiency by up to 39%. The charge diagnostic performed well, even with multiple faults present.

42 ENGINEERING↗

DOE OSTI2022

Use of Machine Learning on PMU Data for Transmission System Fault Analysis

Synchrophasor technology has been used for monitoring, control, and protection of bulk power system for over 10 years. Deployment of phasor measurement units (PMUs) in the USA power system has surpassed 3000 units installed in the transmission substations as stand-alone intelligent electronic devices (IEDs) or as a software add-on to other devices such as digital protective relays (DPRs) or digital fault recorders (DFRs). By now, thousands of terabytes of PMU data may have been captured and stored by various transmission system operators (TSOs) and independent system operators (ISOs). This creates an opportunity to deploy advanced machine learning (ML) techniques to detect and classify faults recorded by PMUs automatically to be used by the system operators for rapid, critical decision-making when manual analysis of the past or unfolding events is not feasible. In this paper we offer a brief background on how the automated fault analysis may be done using DPR and/or DFR data, and compare some of the legacy approaches to the new ML approaches in the context of the system-wide PMU recordings. We then offer insights from developing practical ML solutions that have been applied on field recordings captured by close to 450 PMUs from all three US interconnections (Western, Eastern and ERCOT) over two years (2016-2017). We identify and illustrate ML challenges we addressed: inaccurate data, data with scarce and temporally imprecise fault labels, data recorded by PMUs sparsely located at substations resulting in the fault records taken afar from the ends of the faulted lines, data containing only positive sequence values, and data taken at different voltage levels. We then illustrate the ML model results for fault analysis under different application scenarios. The novelty of this study is not only in the design, implementation, and performance analysis of the ML algorithms, but also in the use of advanced fault modelling and simulation approaches to improve the training results when developing supervised ML models for fault detection and classification. Extensive simulations of faults were conducted on a 14-bus power system to create a training dataset with over 1400 accurately labelled faults. This dataset was applied to enhance the accuracy of fault detection and classification of machine learning-based models trained with small number of labelled faults in large datasets recorded in the grid interconnections ranging from 5,000 to 70,000 buses.

Synchrophasors, Machine Learning, Fault Analysis, ↗

DOE OSTI2024

Adaptive Fault Current-Limiting Control of MMC for Protection of Multiterminal HVDC Systems: Preprint

For the development of multi-terminal high voltage DC (MTDC) transmission, it is critical to design the protection system that can selectively isolate the faulty area from the healthy part of the dc grid using DC circuit breakers (DCCBs) while ensuring continuous operation of converter stations in the healthy part. However, because of the lack of fault current blocking capability in half-bridge (HB) modular multilevel converters (MMCs), when a dc fault occurs, the rising fault currents can quickly reach the blocking threshold within a few milliseconds and disrupt the operation of MMCs in the healthy part. Large DC reactors are often considered in series with DCCBs to reduce the rate of rise of fault currents and prevent blocking of MMCs in the healthy part of the grid. However, large DC reactors can prohibitively increase the cost of the system, particularly when they are considered in an offshore environment, for instance in offshore wind projects. Large dc reactors can also introduce stability issues and create post-fault oscillations. This paper presents an adaptive fault current limiting control method for MMCs to avoid their blocking and enable continuous operation of MTDC systems. It contains two parts: The first part is based on circulating current feedforward control that emulates virtual reactors in each arm of an MMC, which is immediately activated when the fault current starts to increase, to reduce the rate of rise of the fault current; the second part is triggered when the fault current exceeds a preset threshold by temporarily bypassing the SMs, serving as a complement to the fault current limiting effect of the first part. Both parts do not require fault detection signal and they are activated automatically during faults. Simulation case studies of a four-terminal bipolar MMC-HVDC system are presented to demonstrate the effectiveness of the proposed control methods.

active fault current limiting↗

DOE OSTI2015

In situ observations on the coupling between hydraulic diffusivity and displacements during fault reactivation in shales

Key questions in fault reactivation in shales relate to the potential for enhanced fluid transport through previously low-permeability aseismic formations. Here, we explore the behavior of a 20 m long N0-to-170°, 75-to-80°W fault in shales that is critically stressed under a strike-slip regime (σ 1 = 4 ± 2 MPa, horizontal and N162° ± 15°E, σ 2 = 3.8 ± 0.4 MPa and σ 3 = 2.1 ± 1 MPa, respectively 7-8° inclined from vertical and horizontal and N72°). The fault was reactivated by fluid pressurization in a borehole using a straddle packer system isolating a 2.4 m long injection chamber oriented-subnormal to the fault surface at a depth of 250 m. A three-dimensional displacement sensor attached across the fault allowed monitoring fault movements, injection pressure and flow rate. Pressurization induced a hydraulic diffusivity increase from ~2 × 10 -9 to ~10 3 m 2 s -1 associated with a complex three-dimensional fault movement. The shear (x-, z-) and fault-normal (y-) components (U x , U y , and U z ) = (44.0 × 10 -6 m, 10.5 × 10 -6 m, and 20.0 × 10 -6 m) are characterized by much larger shear displacements than the normal opening. Numerical analyses of the experiment show that the fault permeability evolution is controlled by the fault reactivation in shear related to Coulomb failure. The large additional fault hydraulic aperture for fluid flow is not reflected in the total normal displacement that showed a small partly contractile component. This suggests that complex dilatant effects estimated to occur in a plurimeter radius around the injection source affect the flow and slipping patch geometries during fault rupture, controlling the initial slow slip and the strong back slip of the fault following depressurization.

58 GEOSCIENCES↗

DOE OSTI2019

Dynamics, Radiation, and Overall Energy Budget of Earthquake Rupture With Coseismic Off-Fault Damage

Earthquake ruptures dynamically activate coseismic off–fault damage around fault cores. Systematic field observation efforts have shown the distribution of off–fault damage around main faults, while numerical modeling using elastic–plastic off–fault material models have demonstrated the evolution of coseismic off–fault damage during earthquake ruptures. Laboratory–scale microearthquake experiments have pointed out the enhanced high–frequency radiation due to the coseismic off–fault damage. However, the detailed off–fault fracturing mechanisms, subsequent radiation, and its contribution to the overall energy budget remain to be fully understood because of limitations of current observational techniques and model formulations. Here, we constructed a new physics–based dynamic earthquake rupture modeling framework, based on the combined finite–discrete element method, to investigate the fundamental mechanisms of coseismic off–fault damage, and its effect on the rupture dynamics, the radiation and the overall energy budget. We conducted a 2–D systematic case study with depth and showed the mechanisms of dynamic activation of the coseismic off–fault damage. We found the decrease in rupture velocity and the enhanced high–frequency radiation in near field due to the coseismic off–fault damage. We then evaluated the overall energy budget, which shows a significant contribution of the coseismic off–fault damage to the overall energy budget even at depth, where the damage zone width becomes narrower. Here, the present numerical framework for the dynamic earthquake rupture modeling thus provides new insights into earthquake rupture dynamics with the coseismic off–fault damage.

58 GEOSCIENCES↗