Seismic hazard map of Coimbatore using subsurface fault rupture

This study presents the future seismic hazard map of Coimbatore city, India, by considering rupture phenomenon. Seismotectonic map for Coimbatore has been generated using past earthquakes and seismic sources within 300 km radius around the city. The region experienced a largest earthquake of moment magnitude 6.3 in 1900. Available earthquakes are divided into two categories: one includes events having moment magnitude of 5.0 and above, i.e., damaging earthquakes in the region and the other includes the remaining, i.e., minor earthquakes. Subsurface rupture character of the region has been established by considering the damaging earthquakes and total length of seismic source. Magnitudes of each source are estimated by assuming the subsurface rupture length in terms of percentage of total length of sources and matched with reported earthquake. Estimated magnitudes match well with the reported earthquakes for a RLD of 5.2% of the total length of source. Zone of influence circles is also marked in the seismotectonic map by considering subsurface rupture length of fault associated with these earthquakes. As earthquakes relive strain energy that builds up on faults, it is assumed that all the earthquakes close to damaging earthquake have released the entire strain energy and it would take some time for the rebuilding of strain energy to cause a similar earthquake in the same location/fault. Area free from influence circles has potential for future earthquake, if there is seismogenic source and minor earthquake in the last 20 years. Based on this rupture phenomenon, eight probable locations have been identified and these locations might have the potential for the future earthquakes. Characteristic earthquake moment magnitude (M-w) of 6.4 is estimated for the seismic study area considering seismic sources close to probable zones and 15% increased regional rupture character. The city is divided into several grid points at spacing of 0.01 degrees and the peak ground acceleration (PGA) due to each probable earthquake is calculated at every grid point in city by using the regional attenuation model. The maximum of all these eight PGAs is taken for each grid point and the final PGA map is arrived. This map is compared to the PGA map developed based on the conventional deterministic seismic hazard analysis (DSHA) approach. The probable future rupture earthquakes gave less PGA than that of DSHA approach. The occurrence of any earthquake may be expected in near future in these eight zones, as these eight places have been experiencing minor earthquakes and are located in well-defined seismogenic sources.

Fault-tolerant characteristics and topological properties of a hierarchical network of hypercubes

We analyse the fault-tolerant parameters and topological properties of a hierarchical network of hypercubes. We take a close look at the Extended Hypercube (EH) and the Hyperweave (HW) architectures and also compare them with other popular architectures. These two architectures have low diameter and constant degree of connectivity making it possible to expand these networks without affecting the existing configuration. A scheme for incrementally expanding this network is also presented. We also look at the performance of the ASCEND/DESCEND class of algorithms on these architectures.

Fault tolerance in multiprocessor systems

Multiprocessor systems which afford a high degree of parallelism are used in a variety of applications. The extremely stringent reliability requirement has made the provision of fault-tolerance an important aspect in the design of such systems. This paper presents a review of the various approaches towards tolerating hardware faults in multiprocessor systems. It. emphasizes the basic concepts of fault tolerant design and the various problems to be taken care of by the designer. An indepth survey of the various models, techniques and methods for fault diagnosis is given. Further, we consider the strategies for fault-tolerance in specialized multiprocessor architectures which have the ability of dynamic reconfiguration and are suited to VLSI implementation. An analysis of the state-óf-the-art is given which points out the major aspects of fault-tolerance in such architectures.

Performance modelling of a fault-tolerant real-time multiprocessor using stochastic Petri nets

The fault-tolerant multiprocessor (ftmp) is a bus-based multiprocessor architecture with real-time and fault- tolerance features and is used in critical aerospace applications. A preliminary performance evaluation is of crucial importance in the design of such systems. In this paper, we review stochastic Petri nets (spn) and developspn-based performance models forftmp. These performance models enable efficient computation of important performance measures such as processing power, bus contention, bus utilization, and waiting times.

Evidence of episodic brittle faulting in the cratonic part of the Peninsular India and its implications for seismic hazard in slow deforming regions

The region around Waclakkancheri, in the province of Kerala, India, which lies in the vicinity of Palghat-Cauvery ;hear zone (within the Precambrian crystalline terrain), has been a site of microseismic activity since 1989. Earlier studies had identified a prominent WNW-ESE structure overprinting on the E-W trending lineaments associated with Palghat-Cauvery shear zone. We have mapped this structure, located in a chamockite quarry near Desamangalam, Waclakkancheri, which we identify as a ca. 30 km-long south dipping reverse fault. This article presents the characteristics of this fault zone exposed on the exhumed crystalline basement and discusses its significance in understanding the earthquake potential of the region. This brittle deformation zone consists of fracture sets with small-scale displacement and slip planes with embedded fault gouges. The macroscopic as well as the microscopic studies of this fault zone indicate that it evolved through different episodes of faulting in the presence of fluids. The distinct zones within consolidated gouge and the cross cutting relationship of fractures indicate episodic fault activity. At least four faulting episodes can be recognized based on the sequential development of different structural elements in the fault rocks. The repeated ruptures are evident along this shear zone and the cyclic behavior of this fault consists of co-seismic ruptures alternating with inter-seismic periods, which is characterized by the sealed fractures and consolidated gouge. The fault zone shows a minimum accumulated dip/oblique slip of 2.1 m in the reverse direction with a possible characteristic slip of 52 cm (for each event). The ESR dating of fault gouge indicates that the deformation zone records a major event in the Middle Quaternary. The empirical relationships between fault length and slip show that this fault may generate events M >= 6. The above factors suggest that this fault may be characterized as potentially active. Our study offers some new pointers that can be used in other slow deforming cratonic hinterlands in exploring the discrete active faults.

Leveraging Partially Enhanced Scan for Improved Observability in Delay Fault Testing

Enhanced Scan design can significantly improve the fault coverage for two pattern delay tests at the cost of exorbitantly high area overhead. The redundant flip-flops introduced in the scan chains have traditionally only been used to launch the two-pattern delay test inputs, not to capture tests results. This paper presents a new, much lower cost partial Enhanced Scan methodology with both improved controllability and observability. Facilitating observation of some hard to observe internal nodes by capturing their response in the already available and underutilized redundant flip-flops improves delay fault coverage with minimal or almost negligible cost. Experimental results on ISCAS'89 benchmark circuits show significant improvement in TDF fault coverage for this new partial enhance scan methodology.

Data mining approaches to software fault diagnosis

Automatic identification of software faults has enormous practical significance. This requires characterizing program execution behavior and the use of appropriate data mining techniques on the chosen representation. In this paper, we use the sequence of system calls to characterize program execution. The data mining tasks addressed are learning to map system call streams to fault labels and automatic identification of fault causes. Spectrum kernels and SVM are used for the former while latent semantic analysis is used for the latter The techniques are demonstrated for the intrusion dataset containing system call traces. The results show that kernel techniques are as accurate as the best available results but are faster by orders of magnitude. We also show that latent semantic indexing is capable of revealing fault-specific features.

On the stacking fault energies of some close-packed hexagonal metals

It is now realised (1,2,3) that a knowledge of stacking fault energy is fundamental for an understanding of the mechanical behaviour of metals. There are several processes in which the imperfect dislocations have to recombine locally to form an unextended dislocation . For intersection of two dislocations it is, for example, necessary to form 'constrictions'. Cross slip of extended dislocations also involves constriction. The onset of stage llI work hardening in a crystal with close-packed structure is attributed to cross slip and hence is controlled by the stacking fault energy (SPE). Methods of estimation of SFE are based on either the direct observation of stacking faults in an electron microscope or their effects on the deformation processes.

Comparison of Multiclass SVM Classification Methods to Use in a Supportive System for Distance Relay Coordination

This paper aims at evaluating the methods of multiclass support vector machines (SVMs) for effective use in distance relay coordination. Also, it describes a strategy of supportive systems to aid the conventional protection philosophy in combating situations where protection systems have maloperated and/or information is missing and provide selective and secure coordinations. SVMs have considerable potential as zone classifiers of distance relay coordination. This typically requires a multiclass SVM classifier to effectively analyze/build the underlying concept between reach of different zones and the apparent impedance trajectory during fault. Several methods have been proposed for multiclass classification where typically several binary SVM classifiers are combined together. Some authors have extended binary SVM classification to one-step single optimization operation considering all classes at once. In this paper, one-step multiclass classification, one-against-all, and one-against-one multiclass methods are compared for their performance with respect to accuracy, number of iterations, number of support vectors, training, and testing time. The performance analysis of these three methods is presented on three data sets belonging to training and testing patterns of three supportive systems for a region and part of a network, which is an equivalent 526-bus system of the practical Indian Western grid.

A new approach for fault location identification in transmission system using stability analysis and SVMs

This paper presents a new approach to the location of fault in the high voltage power transmission system using Support Vector Machines (SVMs). A knowledge base is developed using transient stability studies for apparent impedance swing trajectory in the R-X plane. SVM technique is applied to identify the fault location in the system. Results are presented on sample 3-power station, a 9-bus system illustrate the implementation of the proposed method.

Neural network approach for fault location in unbalanced distribution networks with limited measurements

This paper presents an Artificial Neural Network (ANN) approach for locating faults in distribution systems. Different from the traditional Fault Section Estimation methods, the proposed approach uses only limited measurements. Faults are located according to the impedances of their path using a Feed Forward Neural Networks (FFNN). Various practical situations in distribution systems, such as protective devices placed only at the substation, limited measurements available, various types of faults viz., three-phase, line (a, b, c) to ground, line to line (a-b, b-c, c-a) and line to line to ground (a-b-g, b-c-g, c-a-g) faults and a wide range of varying short circuit levels at substation, are considered for studies. A typical IEEE 34 bus practical distribution system with unbalanced loads and with three- and single- phase laterals and a 69 node test feeder with different configurations are considered for studies. The results presented show that the proposed approach of fault location gives close to accurate results in terms of the estimated fault location.

Actuator fault detection and isolation in linear systems

A scheme for the detection and isolation of actuator faults in linear systems is proposed. A bank of unknown input observers is constructed to generate residual signals which will deviate in characteristic ways in the presence of actuator faults. Residual signals are unaffected by the unknown inputs acting on the system and this decreases the false alarm and miss probabilities. The results are illustrated through a simulation study of actuator fault detection and isolation in a pilot plant doubleeffect evaporator.