A new 6-component accelerometer force balance for short duration ground testing facilities

A new six-component accelerometer force balance is developed and used in the HST2 shock tunnel of Indian Institute of Science. Aerodynamic forces and moments for a hypersonic slender body measured using this balance system at a free stream Mach number of 5.75 and Reynolds number of 1.5 million and stagnation enthalpy of 1.5 and 2 MJ/kg are presented. These measured values compare well with the theoretical values estimated using modified Newtonian theory.

Torque Angle Loop Analysis of Synchronous Machines

This paper reports the dynamic stability analysis of a single machine infinite bus system through torque angle loop analysis and forms an extension of the work on Block diagrams and torque angle loop analysis of synchronous machines reported by I. Nagy [3]. It aims to incorporate in the machine model, the damper windings (one on each axis) and to compare the dynamic behaviour of the system with and without damper windings. The effect of using different stabilizing signals (viz. active power and speed deviations) on the dynamic performance is analysed and the significant effect of damper windings on the dynamic behaviour of the system is highlighted.

Intelligent Approach for Fault Diagnosis in Power Transmission Systems Using Support Vector Machines

This paper presents an approach for identifying the faulted line section and fault location on transmission systems using support vector machines (SVMs) for diagnosis/post-fault analysis purpose. Power system disturbances are often caused by faults on transmission lines. When fault occurs on a transmission system, the protective relay detects the fault and initiates the tripping operation, which isolates the affected part from the rest of the power system. Based on the fault section identified, rapid and corrective restoration procedures can thus be taken to minimize the power interruption and limit the impact of outage on the system. The approach is particularly important for post-fault diagnosis of any mal-operation of relays following a disturbance in the neighboring line connected to the same substation. This may help in improving the fault monitoring/diagnosis process, thus assuring secure operation of the power systems. In this paper we compare SVMs with radial basis function neural networks (RBFNN) in data sets corresponding to different faults on a transmission system. Classification and regression accuracy is reported for both strategies. Studies on a practical 24-Bus equivalent EHV transmission system of the Indian Southern region is presented for indicating the improved generalization with the large margin classifiers in enhancing the efficacy of the chosen model.

Scheduling identical parallel machines with machine eligibility restrictions to minimize total weighted flowtime in automobile gear manufacturing

In this paper, we address a scheduling problem for minimizing total weighted flowtime, observed in automobile gear manufacturing. Specifically, the bottleneck operation of the pre-heat treatment stage of gear manufacturing process has been dealt with in scheduling. Many real-life scenarios like unequal release times, sequence dependent setup times, and machine eligibility restrictions have been considered. A mathematical model taking into account dynamic starting conditions has been proposed. The problem is derived to be NP-hard. To approach the problem, a few heuristic algorithms have been proposed. Based on planned computational experiments, the performance of the proposed heuristic algorithms is evaluated: (a) in comparison with optimal solution for small-size problem instances and (b) in comparison with the estimated optimal solution for large-size problem instances. Extensive computational analyses reveal that the proposed heuristic algorithms are capable of consistently yielding near-statistically estimated optimal solutions in a reasonable computational time.

Models for the estimation of life of stator insulation in large rotating machines

Epoxy resin bonded mica splitting is the insulation of choice for machine stators. However, this system is seen to be relatively weak under time varying mechanical stress, in particular the vibration causing delamination of mica and deboning of mica from the resin matrix. The situation is accentuated under the combined action of electrical, thermal and mechanical stress. Physical and probabilistic models for failure of such systems have been proposed by one of the authors of this paper earlier. This paper presents a pragmatic accelerated failure data acquisition and analytical paradigm under multi factor coupled stress, Electrical, Thermal. The parameters of the phenomenological model so developed are estimated based on sound statistical treatment of failure data.

Statistical Methods for Accelerated Life Testing with Particular Reference to Resin Impregnated Paper Bushings

Electrical failure of insulation is known to be an extremal random process wherein nominally identical pro-rated specimens of equipment insulation, at constant stress fail at inordinately different times even under laboratory test conditions. In order to be able to estimate the life of power equipment, it is necessary to run long duration ageing experiments under accelerated stresses, to acquire and analyze insulation specific failure data. In the present work, Resin Impregnated Paper (RIP) a relatively new insulation system of choice used in transformer bushings, is taken as an example. The failure data has been processed using proven statistical methods, both graphical and analytical. The physical model governing insulation failure at constant accelerated stress has been assumed to be based on temperature dependent inverse power law model.

Active Sequential Hypothesis Testing with Application to a Visual Search Problem

We consider a visual search problem studied by Sripati and Olson where the objective is to identify an oddball image embedded among multiple distractor images as quickly as possible. We model this visual search task as an active sequential hypothesis testing problem (ASHT problem). Chernoff in 1959 proposed a policy in which the expected delay to decision is asymptotically optimal. The asymptotics is under vanishing error probabilities. We first prove a stronger property on the moments of the delay until a decision, under the same asymptotics. Applying the result to the visual search problem, we then propose a ``neuronal metric'' on the measured neuronal responses that captures the discriminability between images. From empirical study we obtain a remarkable correlation (r = 0.90) between the proposed neuronal metric and speed of discrimination between the images. Although this correlation is lower than with the L-1 metric used by Sripati and Olson, this metric has the advantage of being firmly grounded in formal decision theory.

Novel algorithms for distributed sequential hypothesis testing

This paper considers sequential hypothesis testing in a decentralized framework. We start with two simple decentralized sequential hypothesis testing algorithms. One of which is later proved to be asymptotically Bayes optimal. We also consider composite versions of decentralized sequential hypothesis testing. A novel nonparametric version for decentralized sequential hypothesis testing using universal source coding theory is developed. Finally we design a simple decentralized multihypothesis sequential detection algorithm.

Proportional resonant controller based circulating power setup for thermal testing of multilevel inverter

A regenerative or circulating-power method is presented in this paper for heat run test on the legs of a three-level neutral point clamped (NPC) inverter. This test ensures that only losses are drawn from the dc supply, while rated power is circulated between the two legs, thus minimising wastage of energy. A proportional-resonant (PR) controller based current control scheme is proposed here for the circulating power test setup in NPC inverter. Simulation and experimental results are presented to validate the controller design at various operating conditions. Results of thermal test on the inverter legs are presented at two different operating conditions.

Safety Assessment of a Masonry Arch Bridge: Field Testing and Simulations

The safety of an in-service brick arch railway bridge is assessed through field testing and finite-element analysis. Different loading test train configurations have been used in the field testing. The response of the bridge in terms of displacements, strains, and accelerations is measured under the ambient and design train traffic loading conditions. Nonlinear fracture mechanics-based finite-element analyses are performed to assess the margin of safety. A parametric study is done to study the effects of tensile strength on the progress of cracking in the arch. Furthermore, a stability analysis to assess collapse of the arch caused by lateral movement at the springing of one of the abutments that is elastically supported is carried out. The margin of safety with respect to cracking and stability failure is computed. Conclusions are drawn with some remarks on the state of the bridge within the framework of the information available and inferred information. DOI: 10.1061/(ASCE)BE.1943-5592.0000338. (C) 2013 American Society of Civil Engineers.

A study on the usefulness of Support Vector Machines for the realtime computational simulation of soft biological organs

Realistic and realtime computational simulation of soft biological organs (e.g., liver, kidney) is necessary when one tries to build a quality surgical simulator that can simulate surgical procedures involving these organs. Since the realistic simulation of these soft biological organs should account for both nonlinear material behavior and large deformation, achieving realistic simulations in realtime using continuum mechanics based numerical techniques necessitates the use of a supercomputer or a high end computer cluster which are costly. Hence there is a need to employ soft computing techniques like Support Vector Machines (SVMs) which can do function approximation, and hence could achieve physically realistic simulations in realtime by making use of just a desktop computer. Present work tries to simulate a pig liver in realtime. Liver is assumed to be homogeneous, isotropic, and hyperelastic. Hyperelastic material constants are taken from the literature. An SVM is employed to achieve realistic simulations in realtime, using just a desktop computer. The code for the SVM is obtained from [1]. The SVM is trained using the dataset generated by performing hyperelastic analyses on the liver geometry, using the commercial finite element software package ANSYS. The methodology followed in the present work closely follows the one followed in [2] except that [2] uses Artificial Neural Networks (ANNs) while the present work uses SVMs to achieve realistic simulations in realtime. Results indicate the speed and accuracy that is obtained by employing the SVM for the targeted realistic and realtime simulation of the liver.

Deformation mechanisms during superplastic testing of Ti-6Al-4V-0.1B alloy

Superplastic tensile tests on warm rolled and optimally annealed boron modified alloy Ti-6Al-4V-0.1B at a temperature of 850 degrees C and initial strain rate of 3 x 10(-4) s(-1) results in a higher elongation (similar to 500%) compared to the base alloy Ti-6Al-4V (similar to 400%). The improvement in superplasticity has been attributed to enhanced contribution from interfacial boundary sliding to the overall deformation for the boron modified alloy. The boundary sliding was facilitated by the starting microstructure which predominantly contains small equiaxed primary a grains with narrow size distribution. Dynamic processes such as coarsening and globularization of primary a phase occur under the test condition but do not significantly contribute to the observed difference in superplasticity between the two alloys. In spite of cavitation takes place around the TiB particles during deformation, they do not cause macroscopic cracking and early fracture by virtue of the cavities being extremely localized. Localized cavitation is found to correlate with increased material transfer due to faster diffusion.

Identification of fault location in power distribution system with distributed generation using support vector machines

This paper presents a multi-class support vector machine (SVMs) approach for locating and diagnosing faults in electric power distribution feeders with the penetration of Distributed Generations (DGs). The proposed approach is based on the three phase voltage and current measurements which are available at all the sources i.e. substation and at the connection points of DG. To illustrate the proposed methodology, a practical distribution feeder emanating from 132/11kV-grid substation in India with loads and suitable number of DGs at different locations is considered. To show the effectiveness of the proposed methodology, practical situations in distribution systems (DS) such as all types of faults with a wide range of varying fault locations, source short circuit (SSC) levels and fault impedances are considered for studies. The proposed fault location scheme is capable of accurately identify the fault type, location of faulted feeder section and the fault impedance. The results demonstrate the feasibility of applying the proposed method in practical in smart grid distribution automation (DA) for fault diagnosis.