4 resultados para NOJIMA FAULT
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo
Resumo:
The weakening mechanisms involved in the collapse of complex impact craters are controversial. The Araguainha impact crater, in Brazil, exposes a complex structure of 40 km in diameter, and is an excellent object to address this issue. Its core is dominated by granite. In addition to microstructural observations, magnetic studies reveal its internal fabric acquired during the collapse phase. All granite samples exhibit impact-related planar deformation features (PDFs) and planar fractures (PFs), which were overprinted by cataclasis. Cataclastic deformation has evolved from incipient brittle fracturing to the development of discrete shear bands in the center of the structure. Fracture planes are systematically decorated by tiny grains (<10 mu m) of magnetite and hematite, and the orientation of magnetic lineation and magnetic foliation obtained by the anisotropies of magnetic susceptibility (AMS) and anhysteretic remanence (AAR) are perfectly coaxial in all studied sites. Therefore, we could track the orientation of deformation features which are decorated by iron oxides using the AMS and AAR. The magnetic fabrics show a regular pattern at the borders of the central peak, with orientations consistent with the fabric of sediments at the crater's inner collar and complex in the center of the structure. Both the cataclastic flow revealed from microstructural observations and the structural pattern of the magnetic anisotropy match the predictions from numerical models of complex impact structures. The widespread occurrence of cataclasis in the central peak, and its orientations revealed by magnetic studies indicate that acoustic fluidization likely operates at all scales, including the mineral scales. The cataclastic flow made possible by acoustic fluidization results in an apparent plastic deformation at the macroscopic scale in the core. (C) 2012 Elsevier B.V. All rights reserved.
Resumo:
This paper proposes an evolutionary computing strategy to solve the problem of fault indicator (FI) placement in primary distribution feeders. More specifically, a genetic algorithm (GA) is employed to search for an efficient configuration of FIs, located at the best positions on the main feeder of a real-life distribution system. Thus, the problem is modeled as one of optimization, aimed at improving the distribution reliability indices, while, at the same time, finding the least expensive solution. Based on actual data, the results confirm the efficiency of the GA approach to the FI placement problem.
Resumo:
In this article we propose an efficient and accurate method for fault location in underground distribution systems by means of an Optimum-Path Forest (OPF) classifier. We applied the time domains reflectometry method for signal acquisition, which was further analyzed by OPF and several other well-known pattern recognition techniques. The results indicated that OPF and support vector machines outperformed artificial neural networks and a Bayesian classifier, but OPF was much more efficient than all classifiers for training, and the second fastest for classification.
Resumo:
Network reconfiguration for service restoration (SR) in distribution systems is a complex optimization problem. For large-scale distribution systems, it is computationally hard to find adequate SR plans in real time since the problem is combinatorial and non-linear, involving several constraints and objectives. Two Multi-Objective Evolutionary Algorithms that use Node-Depth Encoding (NDE) have proved able to efficiently generate adequate SR plans for large distribution systems: (i) one of them is the hybridization of the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) with NDE, named NSGA-N; (ii) the other is a Multi-Objective Evolutionary Algorithm based on subpopulation tables that uses NDE, named MEAN. Further challenges are faced now, i.e. the design of SR plans for larger systems as good as those for relatively smaller ones and for multiple faults as good as those for one fault (single fault). In order to tackle both challenges, this paper proposes a method that results from the combination of NSGA-N, MEAN and a new heuristic. Such a heuristic focuses on the application of NDE operators to alarming network zones according to technical constraints. The method generates similar quality SR plans in distribution systems of significantly different sizes (from 3860 to 30,880 buses). Moreover, the number of switching operations required to implement the SR plans generated by the proposed method increases in a moderate way with the number of faults.