967 resultados para stacking faults
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Mode of access: Internet.
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verso: Photograph was made around 1900.
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I present results of my evaluation to identify topographic lineaments that are potentially related to post-glacial faulting using bare-earth LiDAR topographic data near Ridley Island, British Columbia. The purpose of this evaluation has been to review bare-earth LiDAR data for evidence of post-glacial faulting in the area surrounding Ridley Island and provide a map of the potential faults to review and possibly field check. My work consisted of an extensive literature review to understand the tectonic, geologic, glacial and sea level history of the area and analysis of bare-earth LiDAR data for Ridley Island and the surrounding region. Ridley Island and the surrounding north coast of British Columbia have a long and complex tectonic and geologic history. The north coast of British Columbia consists of a series of accreted terranes and some post-accretionary deposits. The accreted terranes were attached to the North American continent during subduction of the Pacific Plate between approximately 200 Ma and 10 Ma. The terrane and post-accretionary deposits are metamorphosed sedimentary, volcanic and intrusive rocks. The rocks have experienced significant deformation and been intruded by plutonic bodies. Approximately 10 Ma subduction of the Pacific Plate beneath the North America Plate ceased along the central and north coast of British Columbia and the Queen Charlotte Fault Zone was formed. The Queen Charlotte Fault Zone is a transform-type fault that separates the Pacific Plate from the North America Plate. Within the past 1 million years, the area has experienced multiple glacial/interglacial cycles. The most recent glacial cycle occurred approximately 23,000 to 13,500 years ago. Few Quaternary deposits have been mapped in the area. The vast majority of seismicity around the northwest coast of British Columbia occurs along the Queen Charlotte Fault Zone. Numerous faults have been mapped in the area, but there is currently no evidence to suggest these faults are active (i.e. have evidence for post-glacial surface displacement or deformation). No earthquakes have been recorded within 50 km of Ridley Island. Several small earthquakes (less than magnitude 6) have been recorded within 100 km of the island. These earthquakes have not been correlated to active faults. GPS data suggests there is ongoing strain in the vicinity of Ridley Island. The strain has the potential to be released along faults, but the calculated strain may be a result of erroneous data or accommodated aseismically. Currently, the greatest known seismic hazard to Ridley Island is the Queen Charlotte Fault Zone. LiDAR data for Ridley Island, Digby Island, Lelu Island and portions of Kaien Island, Smith Island and the British Columbia mainland were reviewed and analyzed for evidence of postglacial faulting. The data showed a strong fabric across the landscape with a northwest-southeast trend that appears to mirror the observed foliation in the area. A total of 80 potential post-glacial faults were identified. Three lineaments are categorized as high, forty-one lineaments are categorized as medium and thirty-six lineaments are categorized as low. The identified features should be examined in the field to further assess potential activity. My analysis did not include areas outside of the LiDAR coverage; however faulting may be present there. LiDAR data analysis is only useful for detecting faults with surficial expressions. Faulting without obvious surficial expressions may be present in the study area.
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Understanding and explaining emergent constitutive laws in the multi-scale evolution from point defects, dislocations and two-dimensional defects to plate tectonic scales is an arduous challenge in condensed matter physics. The Earth appears to be the only planet known to have developed stable plate tectonics as a means to get rid of its heat. The emergence of plate tectonics out of mantle convection appears to rely intrinsically on the capacity to form extremely weak faults in the top 100 km of the planet. These faults have a memory of at least several hundred millions of years, yet they appear to rely on the effects of water on line defects. This important phenomenon was first discovered in laboratory and dubbed ``hydrolytic weakening''. At the large scale it explains cycles of co-located resurgence of plate generation and consumption (the Wilson cycle), but the exact physics underlying the process itself and the enormous spanning of scales still remains unclear. We present an attempt to use the multi-scale non-equilibrium thermodynamic energy evolution inside the deforming lithosphere to move phenomenological laws to laws derived from basic scaling quantities, develop self-consistent weakening laws at lithospheric scale and give a fully coupled deformation-weakening constitutive framework. At meso- to plate scale we encounter in a stepwise manner three basic domains governed by the diffusion/reaction time scales of grain growth, thermal diffusion and finally water mobility through point defects in the crystalline lattice. The latter process governs the planetary scale and controls the stability of its heat transfer mode.
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The research carried out in this thesis was mainly concerned with the effects of large induction motors and their transient performance in power systems. Computer packages using the three phase co-ordinate frame of reference were developed to simulate the induction motor transient performance. A technique using matrix algebra was developed to allow extension of the three phase co-ordinate method to analyse asymmetrical and symmetrical faults on both sides of the three phase delta-star transformer which is usually required when connecting large induction motors to the supply system. System simulation, applying these two techniques, was used to study the transient stability of a power system. The response of a typical system, loaded with a group of large induction motors, two three-phase delta-star transformers, a synchronous generator and an infinite system was analysed. The computer software developed to study this system has the advantage that different types of fault at different locations can be studied by simple changes in input data. The research also involved investigating the possibility of using different integrating routines such as Runge-Kutta-Gill, RungeKutta-Fehlberg and the Predictor-Corrector methods. The investigation enables the reduction of computation time, which is necessary when solving the induction motor equations expressed in terms of the three phase variables. The outcome of this investigation was utilised in analysing an introductory model (containing only minimal control action) of an isolated system having a significant induction motor load compared to the size of the generator energising the system.
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Diagnosing faults in wastewater treatment, like diagnosis of most problems, requires bi-directional plausible reasoning. This means that both predictive (from causes to symptoms) and diagnostic (from symptoms to causes) inferences have to be made, depending on the evidence available, in reasoning for the final diagnosis. The use of computer technology for the purpose of diagnosing faults in the wastewater process has been explored, and a rule-based expert system was initiated. It was found that such an approach has serious limitations in its ability to reason bi-directionally, which makes it unsuitable for diagnosing tasks under the conditions of uncertainty. The probabilistic approach known as Bayesian Belief Networks (BBNS) was then critically reviewed, and was found to be well-suited for diagnosis under uncertainty. The theory and application of BBNs are outlined. A full-scale BBN for the diagnosis of faults in a wastewater treatment plant based on the activated sludge system has been developed in this research. Results from the BBN show good agreement with the predictions of wastewater experts. It can be concluded that the BBNs are far superior to rule-based systems based on certainty factors in their ability to diagnose faults and predict systems in complex operating systems having inherently uncertain behaviour.
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Reliability of power converters is of crucial importance in switched reluctance motor drives used for safety-critical applications. Open-circuit faults in power converters will cause the motor to run in unbalanced states, and if left untreated, they will lead to damage to the motor and power modules, and even cause a catastrophic failure of the whole drive system. This study is focused on using a single current sensor to detect open-circuit faults accurately. An asymmetrical half-bridge converter is considered in this study and the faults of single-phase open and two-phase open are analysed. Three different bus positions are defined. On the basis of a fast Fourier transform algorithm with Blackman window interpolation, the bus current spectrums before and after open-circuit faults are analysed in details. Their fault characteristics are extracted accurately by the normalisations of the phase fundamental frequency component and double phase fundamental frequency component, and the fault characteristics of the three bus detection schemes are also compared. The open-circuit faults can be located by finding the relationship between the bus current and rotor position. The effectiveness of the proposed diagnosis method is validated by the simulation results and experimental tests.
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Photovoltaic (PV) solar power generation is proven to be effective and sustainable but is currently hampered by relatively high costs and low conversion efficiency. This paper addresses both issues by presenting a low-cost and efficient temperature distribution analysis for identifying PV module mismatch faults by thermography. Mismatch faults reduce the power output and cause potential damage to PV cells. This paper first defines three fault categories in terms of fault levels, which lead to different terminal characteristics of the PV modules. The investigation of three faults is also conducted analytically and experimentally, and maintenance suggestions are also provided for different fault types. The proposed methodology is developed to combine the electrical and thermal characteristics of PV cells subjected to different fault mechanisms through simulation and experimental tests. Furthermore, the fault diagnosis method can be incorporated into the maximum power point tracking schemes to shift the operating point of the PV string. The developed technology has improved over the existing ones in locating the faulty cell by a thermal camera, providing a remedial measure, and maximizing the power output under faulty conditions.
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This paper presents a diagnostic and prognostic condition monitoring method for insulated-gate bipolar transistor (IGBT) power modules for use primarily in electric vehicle applications. The wire-bond-related failure, one of the most commonly observed packaging failures, is investigated by analytical and experimental methods using the on-state voltage drop as a failure indicator. A sophisticated test bench is developed to generate and apply the required current/power pulses to the device under test. The proposed method is capable of detecting small changes in the failure indicators of the IGBTs and freewheeling diodes and its effectiveness is validated experimentally. The novelty of the work lies in the accurate online testing capacity for diagnostics and prognostics of the power module with a focus on the wire bonding faults, by injecting external currents into the power unit during the idle time. Test results show that the IGBT may sustain a loss of half the bond wires before the impending fault becomes catastrophic. The measurement circuitry can be embedded in the IGBT drive circuits and the measurements can be performed in situ when the electric vehicle stops in stop-and-go, red light traffic conditions, or during routine servicing.
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Ecosystems can provide many services. Wetlands, for example, can help mitigate water pollution from point sources as well as non-point sources, serve as habitat for wildlife, sequester carbon and serve as a place for recreation. Studies have found that these services can have substantial value to society. The sale of ecosystem credits has been found to be a possible way to finance construction investments in wetlands and easements to farmers to take their land out of production. At the same time, selling one ecosystem service credit may not always be enough to justify the investment. Traditionally market participants have only been allowed to sell a single credit from one piece of land, but recently there have been discussions about the possibility of selling more than one credit from a piece of land because it potentially could lead to more efficient ecosystem service provision. Selling multiple credits is sometimes referred to as credit stacking. This paper is an empirical study of the potential for credit stacking applied to the services provided by wetlands in the Upper Mississippi River Basin, specifically nitrogen, phosphorus and wildlife credits. In the setting of our study where costs are discrete rather than continuous we found that wetlands are a cost-effective way to reduce the nitrogen loads from wastewater treatment plants and that stacking nitrogen, phosphorus and wildlife credits may improve social welfare while leading to a higher level of ecosystem services. However, for credit stacking to be welfare improving we found that there needs to be a substantial demand for the credit that covers the majority of the investment in wetlands, while the credit aggregator has a choice between what ecosystem projects to undertake. If the credit that covers the majority of investment is sold first and is the sole basis of the investment decision and the objective is to improve welfare, a sequential implementation of ecosystem credits is not recommended; it would not lead to an increase in the total amount of ecosystem services provided though it would increase profit for the credit producer.
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This paper presents our approach of identifying the profile of an unknown user based on the activities of known users. The aim of author profiling task of PAN@CLEF 2016 is cross-genre identification of the gender and age of an unknown user. This means training the system using the behavior of different users from one social media platform and identifying the profile of other user on some different platform. Instead of using single classifier to build the system we used a combination of different classifiers, also known as stacking. This approach allowed us explore the strength of all the classifiers and minimize the bias or error enforced by a single classifier.