(SoE) School of Engineering

<p>Shiv Nadar University is a comprehensive, multidisciplinary, research-focused, and student-centric University offering a full range of academic programs at the undergraduate, postgraduate and doctoral level. With state-of-the-art infrastructure, the University comprises of academic wings, sophisticated labs, international standard sports facilities, amphitheaters, auditorium, conference rooms and smart classrooms. The University&rsquo;s goal is to become internationally recognized for the quality of its research and creative endeavors and their applicability to improving quality of life, generating new insights and expanding the boundaries of human knowledge creativity. Committed to excellence in teaching, research and service, the University aims to serve the higher education needs of India and the world beyond.</p>

Shiv Nadar University

This paper describes the development of a nonintrusive flow visualization method for the quantitative study of the dynamic velocity and void profiles across the pipe cross section in slug flow. The method utilizes novel digital image analysis and computer graphics techniques. Slug flow in a 75 mm diameter, 10 m long Plexiglass pipe is recorded on video using super-VHS cameras and an audio-visual mixer. Sixty images are obtained every second and these are digitized and analyzed on a SGI' graphics workstation. Detailed information regarding the local velocity and void distribution is obtained from the analysis and is used to generate velocity and void profiles across the pipe at different distances into the slug. Results show that gas is released into the slug in the form of pulses of bubbles resulting in the existence of large, frothy, highly aerated structures in the mixing zone. The hydrodynamic boundary layer is destroyed at the slug front but begins to redevelop in the mixing zone. It becomes fully developed at the end of the mixing zone and the one-seventh power law profile for velocity profile is applicable. At the end of the mixing zone, the gas moves towards the top of the pipe and the void fraction distribution tends to a steady profile. A process dynamic model is developed to predict the variation of the average liquid holdup within the slug. © 1997 Elsevier Science Ltd.

Electrical Engineering

World University root node

International Journal of Multiphase Flow

Development of digital image analysis techniques for the study of velocity and void profiles in slug flow

This paper investigates the parallel time and processor complexities of several searching problems involving Monge, staircase-Monge, and Monge-composite arrays. We present array-searching algorithms for concurrent-read-exclusive-write (CREW) PRAMs, hypercubes, and several hypercubic networks. All these algorithms run in near-optimal time, and their processor-time products are all within an O(lgn) factor of the worst-case sequential bounds. Several applications of these algorithms are also given. Two applications improve previous results substantially, and the others provide novel parallel algorithms for problems not previously considered. © 1997 Springer-Verlag New York Inc.

Fulltext

Algorithmica (New York)

Parallel searching in generalized Monge arrays

In the present paper the coordinated application of the controlled series compensation (CSC) and the SVS auxiliary controllers has been demonstrated for the dynamic and transient performance enhancement of a series compensated long transmission line. SVS controller, known as the combined reactive power and frequency (CRPF) auxiliary controller, has been developed and incorporated in the SVS control system located at the middle of the transmission line. The application of the auxiliary controllers, considerably, enhances the system damping and the unstable system modes are stabilized. To improve the transient performance, the CSC having bang-bang control characteristics has been incorporated. A digital simulation study, using a nonlinear system model, has been performed to illustrate the comparative effectiveness of the CSC and the SVS auxiliary controllers developed.

Journal of the Institution of Engineers (India): Electrical Engineering Division

Application of CSC and SVS auxiliary controllers for flexible ac transmission systems

Electrochemical Noise(ECN) and Electrochemical Impedance Spectroscope (EIS) measurements were made simultaneously in a 75 mm I.D., 10 m long acrylic pipeline using salt-water/carbon dioxide mixtures. Full pipe flow was studied for liquid velocities of 0.5, 0.75, 1.1, 1.5 m/s and slug flow for Froude numbers 4, 6 and 9. Experiments were carried out at a constant pressure of 136 kPa and temperature of 40°C. ECN data were measured with a fast auto zero resistance ammeter. The ECN technique is able to detect changes in flow regime, showing distinct differences between full pipe flow and siug flow. The choice of sampling rate when using ECN is very important. For slug flows, sampling rates as high as 100 Hz are necessary to include most of the transients in the flow. Distinct differences can be seen in the Fast Fourier Transforms where dominant frequencies exist which correspond to possible bubble action in the slug body. EIS can be used to measure corrosion rate in multiphase flows. It does show an increase in the corrosion rate with liquid flow rates for full pipe flow and Froude numbers for stationary slug flow. A simple statistical analysis of ECN response gives a correlation with corrosion rate. These show ECN could be a very powerful tool for determining corrosion rate and corrosion mechanism in multiphase flow. © 1997 by NACE International.

NACE - International Corrosion Conference Series

Comparison of ECN and EIS measurement for corrosion monitoring under multiphase flow conditions

The steady state and dynamic performance of a flexible AC transmission system (FACTS) with midpoint located SVS has been presented with and without series compensation. The maximum capacitor of SVS branch in case of line without series compensation, is split into two locations. Two third of it is at the sending end for the purpose of series compensation and one third remains at SVS branch. This has the advantage of reduced ‘δ’ without upsetting greatly the cost economy of equipment. The degree of series compensation thus obtained is used to evaluate the steady state and dynamic performance of series compensated transmission line. The results are then compared over a wide operating range. The line reactive power auxiliary controller and bus frequency auxiliary controller are employed in the SVS control system to stabilize the unstable system modes and the performance of the two auxiliary controllers is also compared over wide operating conditions. It has been established here that such a series capacitor compensated line can give improved static and dynamic performance at a reduced value of δ. © 1996 Taylor & Francis.

Electric Machines and Power Systems

A flexible ac transmission system “steady state and dynamic performance analysis”

This paper presents a robust artificial neural network technique to assess the on-line dynamic stability of power system. Efforts have been made to minimize the error in dynamic stability assessment by optimising the size and introducing more sensitive information in training vector. The problem has been attempted with Kohonen's self-organising feature map (SOFM) to classify the states of power system. The main reason which inspired the authors to apply Kohonen's SOFM technique is to avoid local minima that saturate the learning process in back-propagation algorithm. Conventional QR algrithm in conjunction with S-matrix method is used to allocate dynamic stability indices to output neurons. © 1996 Taylor & Francis.

A robust artificial neural network technique for dynamic stability assessment

The paper is concerned with the design of a hybrid controller structure, consisting of the adaptive control law and a neural-network-based learning scheme for adaptation of time-varying controller parameters. The target error vector for weight adaptation of the neural networks is derived using the Lyapunov-function approach. The global stability of the closed-loop feedback system is guaranteed, provided the structure of the robot-manipulator dynamics model is exact. Generalisation of the controller over the desired trajectory space has been established using an online weight-learning scheme. Model learning, using a priori knowledge of a robot arm model, has been shown to improve tracking accuracy. The proposed control scheme has been implemented using both MLN and RBF networks. Faster convergence, better generalisation and superior tracking accuracy have been achieved in the case of the RBF network. © IEE, 1996.

IEE Proceedings: Control Theory and Applications

Neuro-adaptive hybrid controller for robot-manipulator tracking control

A robust hybrid control method that integrates a neural controller, and a H∞ controller is proposed. The neural controller is designed for feedback linearization and the H∞ controller is used to minimize the effect of parameter uncertainties of the model on the tracking performance. Simulations are provided to show that the disturbances generated from the model error will be quickly compensated and hence more robust performance can be achieved.

IEEE International Conference on Neural Networks - Conference Proceedings

Robust hybrid controller for robotic manipulators using neural and H∞ techniques

This paper is concerned with the design of a neuroadaptive trajectory tracking controller. The paper presents a new control scheme based on inversion of a feedforward neural model of a robot arm. The proposed control scheme requires two modules. The first module consists of an appropriate feedforward neural model of forward dynamics of the robot arm that continuously accounts for the changes in the robot dynamics. The second module implements an efficient network inversion algorithm that computes the control action by inverting the neural model. In this paper, a new extended Kalman filter (EKF) based network inversion scheme is proposed. The scheme is evaluated through comparison with two other schemes of network inversion: gradient search in input space and Lyapunov function approach. Using these three inversion schemes the proposed controller was implemented for trajectory tracking control of a two-link manipulator. Simulation results in all cases confirm the efficacy of control input prediction using network inversion. Comparison of the inversion algorithms in terms of tracking accuracy showed the superior performance of the EKF based inversion scheme over others. © 1996 IEEE.

IEEE Transactions on Neural Networks

On adaptive trajectory tracking of a robot manipulator using inversion of its neural emulator

A query based learning algorithm is proposed in this paper to obtain a valid neural emulator of the robot manipulator using radial basis function networks. This algorithm is centred around the concept of network inversion for which we have proposed an extended Kalman filtering (EKF) based algorithm. Initially the training data set is generated by tracking various random trajectories in robot work space. During this process, control input (or joint actuating torque) vector is computed using a fixed PD control scheme with added dither signal. The RBF network thus learned is tested for its validity using the inversion based recall process. In case the neural network is partially trained, additional input/output data pairs are generated. The data so generated are used to retrain the RBFN model of the robot manipulator. Experiments showed significant improvement in the neural model after retraining. © 1996 Taylor & Francis Group, LLC.