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Magnetically Impelled Arc Butt (MIAB) welding is a solid state welding process especially used in circumferential butt welding of tubes in which heat is generated prior to upsetting by an electric arc moving along the peripheral edges of the weldment with the aid of an external magnetic field. This paper aims at studying the formation of Light Band (LB) zone and its effect on the weld properties of MIAB welding of carbon steel tubes. A detailed microstructural analysis has been carried out to understand the microstructural transformations taking place in Thermo-Mechanically Affected Zone leading to formation of LB zone. Welded samples show better tensile properties with higher upset current as it eliminates LB zone formation at weld interface. For lower upset current, width of the LB zone increases with increase in arc rotation current resulting in lower weld tensile strength.

Arithmetic unit is the most important component of modern embedded computer systems. Arithmetic unit generally includes floating point and fixed-point arithmetic operations and trigonometric functions. Multipliers units are the most important hardware structures in a complex arithmetic unit. With increase in chip frequency, the designer must be able to find the best set of trade-offs. The ability for faster computation is essential to achieve high performance in many DSP and Graphic processing algorithms and is why there is at least one dedicated Multiplier unit in all of the modern commercial DSP processors. Tremendous advances in VLSI technology over the past several years resulted in an increased need for high speed multipliers and compelled the designers to go for trade-offs among speed, power consumption and area. A novel modified booth multiplier design for high speed VLSI applications using pre-computation logic has been presented in this paper. The proposed architecture modeled using Verilog HDL, simulated using Cadence NCSIM and synthesized using Cadence RTL Compiler with 65nm TSMC library.The proposed multiplier architecture is compared with the existing multipliers and the results show significant improvement in speed and power dissipation.

Penetration of grid-connected photovoltaic systems can be increased substantially by devising area-specific power output forecasting methods. Meteorological conditions of the area are decisive for solar plant management and electricity generation. This paper estimates and forecasts the profile of power output of a grid-connected 20-kWp solar power plant in a reputed manufacturing industry located in Tiruchirappalli, India, using artificial neural networks (ANNs). A multilayer perceptron-based ANN model is proposed for day-ahead forecasting of the power generation. An experimental database comprising of each day's solar power output and atmospheric temperature for a period of 70 days has been used for training the ANN. Various training algorithms, transfer functions, and learning rules in the hidden layers/output layers were employed on the database of 11,200 patterns in order to obtain the best mapping between the ANN's inputs and outputs. Statistical error analysis in terms of mean absolute percentage error calculated on the 24-h-ahead forecasting results is presented. Analysis of the variations in network forecasting performance caused by changing the neuron functional parameters has been carried out. The results are also utilized for load scheduling operations of the industrial grid for the next day. Reliable area-specific solar power production map can help in power system scheduling and investment productivity.

Model based control algorithms are implemented when traditional control algorithms are inappropriate and fails to produce effective results. Smith predictor is an effective control structure to control process with high dead time. In this work, real time Smith Predictor algorithm is implemented to control a high dead time interacting tank process using LabVIEW. It requires a good knowledge about the process to extract the mathematical model. The model requires to capture the entire dynamics of the process so as to make the control algorithm more effective. In this work, open loop analysis is carried out to understand the dynamics of the plant and the model is extracted using empirical method. A first order plus dead time model (FOPDT) is considered and Smith Predictor structure is implemented to control the process. It is observed that the traditional PID control produces a sustained oscillation because of high dead time and Smith Predictor based control for the same PID parameters produces an effective control of the process.

Magnetically impelled arc butt (MIAB) welding is a pressure welding process used for joining of pipes and tubes with an external magnetic field affecting arc rotation along the tube circumference. In this work, MIAB welding of low alloy steel (T11) tubes were carried out to study the microstructural changes occurring in thermo-mechanically affected zone (TMAZ). To qualify the process for the welding applications where pressure could be up to 300 bar, the MIAB welds are studied with variations of arc current and arc rotation time. It is found that TMAZ shows higher hardness than that in base metal and displays higher weld tensile strength and ductility due to bainitic transformation. The effect of arc current on the weld interface is also detailed and is found to be defect free at higher values of arc currents. The results reveal that MIAB welded samples exhibits good structural property correlation for high pressure applications with an added benefit of enhanced productivity at lower cost. The study will enable the use of MIAB welding for high pressure applications in power and defence sectors.

The Indian power generation market is moving towards deregulation. Deregulation forces the utilities to operate the plant efficiently and economically with reduced in-house auxiliary power consumption. The increase in auxiliary power consumption increases the operation cost of the plant. In future utilities have to correctly predict the power consumption at in-plant auxiliaries to arrive at the total capacity available for selling and to estimate the operational cost. Auxiliary power consumption is an important index that describes how well a thermal power plant is operating. Induced draft (ID) fan power consumption is almost one-third of the total power consumption by in-house auxiliaries. This paper details the methodology adopted for prediction of ID fan power consumption by artificial neural network. Operational parameters from fifty number of boilers have been collected and used for the analysis. Nine influential parameters that accurately describe the power consumption at ID fan are identified. The identified influential parameters are used in the Artificial Neural Network model for predicting the ID fan power consumption. The proposed methodology can be used by power plant operator and designers for effectively predicting the power consumption by ID fan.

Induced Draft (ID) fans have been employed in power plants for evacuating the flue gas from the furnace and send it through the chimney. Power consumption by ID fan power accounts for one-third of the total power consumption by all the in-house auxiliaries. In future, utilities have to correctly predict the power consumed by the in-plant auxiliaries to arrive at the total capacity available for selling and to estimate the operational cost. In this paper, an Artificial Neural Network (ANN) model has been created for prediction of ID fan power consumption. Operational data from fifty number of steam generators has been collected. The collected data have been utilised for the training and testing of the ANN model. The developed model shall help the plant operators and designers in accurately predicting the power consumed by ID fan

High speed and efficient multipliers are essential components in today’s computational circuits like digital signal processing, algorithms for cryptography and high performance processors. Invariably, almost all processing units will contain hardware multipliers based on some algorithm that fits the application requirement. Tremendous advances in VLSI technology over the past several years resulted in an increased need for high speed multipliers and compelled the designers to go for trade-offs among speed, power consumption and area. Amongst various methods of multiplication, Vedic multipliers are gaining ground due to their expected improvement in performance. A novel multiplier design for high speed VLSI applications using Urdhva-Tiryagbhyam sutra of Vedic Multiplication has been presented in this paper. The proposed architecture modeled using Verilog HDL, simulated using Cadence NCSIM and synthesized using Cadence RTL Compiler with 65nm TSMC library.The proposed multiplier architecture is compared with the existing multipliers and the results show significant improvement in speed and power dissipation.

The VLSI binary adder is the basic building block in any computation unit. It is widely used in the arithmetic logic unit, memory addressing computation and in many other places. In this paper the binary adder is presented with keeping in mind speed, power and finally area. In this paper the BCD adder is designed using the mixed approach such as hierarchical, muxing and variable grouping techniques. The design and result are presented in this paper

High speed and efficient multipliers are essential components in today’s computational circuits like digital signal processing, algorithms for cryptography and high performance processors. Invariably, almost all processing units will contain hardware multipliers based on some algorithm that fits the application requirement. Tremendous advances in VLSI technology over the past several years resulted in an increased need for high speed multipliers and compelled the designers to go for trade-offs among speed, power consumption and area. Amongst various methods of multiplication, Vedic multipliers are gaining ground due to their expected improvement in performance. A novel multiplier design for high speed VLSI applications using Urdhva-Tiryagbhyamsutra of Vedic Multiplication has been presented in this paper. The multiplier architecture is implemented using Verilog coding and synthesise during Cadence RTL Compiler. Physical design is implemented using Cadence Encounter RTL-to-GDSII System using standard 180nm technology. The proposed multiplier architecture is compared with the conventional multiplier and the results show significant improvement in speed and power dissipation.

An increase in environmental awareness, renewable energy usage and concern for energy security have resulted in the advent of Solar Photovoltaic (PV) systems as a sustainable form of alternative energy. Lack of area-specific forecasts for the power output of grid-connected photovoltaic system hinders in tapping the full potential of abundant solar power. The objective of this paper is to estimate the profile of power output of a grid connected 20kW p solar power plant in a reputed manufacturing industry located in Tiruchirappalli, India [10° 44' 42.3816" N, 78° 47' 9.4524" E] using artificial intelligence techniques. An Artificial Neural Network (ANN) based model is proposed as a prediction model in this paper. An experimental database comprising of each day's solar power output and atmospheric temperature (from 31st May 2014 to 31st July 2014) has been used for training the ANN. The regression mapping of the neural network was carried out with the Neural Network Fitting Toolbox of MATLAB and simulated with Neuro Solutions development environment. Statistical error analysis in terms of Mean Squared Error (MSE) was calculated on the Day-Ahead Forecasting results and was found to be in the range of 0.019 to 0.025, signifying good accuracy and efficiency. Reliable area-specific solar power production map can provide better utilization of solar energy resource and help in power system management.

Solar photovoltaic (PV) system are attaining world wide popularity due to their clean generation mechanism and energy security. The dc voltage obtained from PV system is usually lower than the peak value of the required output voltage of inverter and varies in a wide range. A power transformer is required to step-up the output voltage or a dc-dc converter is required to boost the input dc voltage, in addition to the dc-ac inverter, which increase cost and circuit complexity. Z-source single stage inverters with bulk inductors and capacitors are used in some topologies, but the harmonic content in the output is relatively high. In this paper, a solar photovoltaic (PV) fed single stage boost inverter feeding a three phase induction motor is explained with mathematical expressions and computer simulations. A time independent pulse width modulation technique is adopted in this system, which generates symmetrical gate pulse pattern resulting in smooth output waveforms. The dc link inductor can be kept very low as the inductor current is maintained constant by this discrete switching control strategy. This system is simple, cost effective and can be used for stand-alone solar applications. Results obtained from this system confirm the effectiveness of new discrete switching strategy and prove its capability to perform real time.

In recent trends managing, using and processing a high volume of data has become part of real time computation. As the importance of decimal arithmetic is growing in all financial, internet-based and commercial applications, more attention has to be paid for fast decimal data processing. Despite the widespread use of binary arithmetic, decimal computation remains essential for many applications, Decimal numbers are not only required whenever numbers are presented for human inspection, but also often used when fractions are involved. In this paper new design of high speed Binary Coded Decimal (BCD) addition is discussed.

Hybrid systems are systems in which the discrete dynamics and the continuous dynamics not only coexist but also interact with each other. The modeling of such hybrid systems is different from the convention modeling techniques followed for purely discrete or purely continuous systems. Development of techniques for Modeling, system identification and controller synthesis of hybrid systems is an upcoming research area. In this paper a three tank benchmark system is modeled using hybrid modeling technique and the modeled system is simulated using SIMULINK and a controller is designed for the hybrid system using STATEFLOW in MATLAB.

Current trends in the academia and industry is managing and processing a high volume of data. Most of the time is spend on converting the data from decimal to binary, processing and converting back to decimal. The direct production of decimal sum offers a significant improvement in addition over methods requiring decimal correction. Here is the proposition which will reduce the conversion and processing time. This work is the extension of Alp Arslan Bayracci and Ahmet Akkas et al of reduced delay Binary Coded Decimal (BCD) adder. In some corner case, adder design was misbehaving and has been corrected and presented.

An open loop interferometric Fiber Optic Gyro (IFOG) has been designed,developed,tested and demonstrated at LEOS.This Gyro is of all fiber construction,using polarisation maintaining components, an integrated optic phase modulator and a superluminescent diode as light source. The interferometer uses 400m long polarisation maintaining fiber wound in Quadruple configuration on a 100 mm diameter Aluminium former. The coil and former weight 400 gms. An inhouse built processing electronics, consisting of a Lock-in-Amplifier, superluminescent diode driver with photodiode feedback, a Thermoelectric cooler controller for wavelength stabilization, a pulse suppression logic and regulated power supplies have been used for meeting signal processing requirements. The total power consumption of Gyro is 5 watts. Weight (including all electronics and sensor) is 1.5 Kg. Gyro drift was measured to be 0.07 deg./hr. and random walk 0.006hr. Scale factor stability was 200 ppm.

Systems in which the dynamical behaviour evolves based on the interaction between the continuous dynamics and the discrete dynamics, present in the system, are called hybrid systems. Traditionally such systems were analysed either as purely continuous or purely discrete systems. The interactions between discrete and continuous systems in today’s technological problems have become so important that hybrid modelling of such systems is called for. In this paper a discrete controller is designed for such a hybrid system. Hybrid modelling technique is used to model the hybrid three tank systems. The hybrid model is simulated in SIMULINK and STATEFLOW is used to design the discrete controller.

Aryabhata was a spin-stabilised satellite. Attitude determination was required for the evaluation of the stabilisation system and for scientific experiments. Temperature sensors were required for the performance evaluation of the onboard systems and of the thermal control system. A detailed description of the sensors used for these functions inAryabhata is given.

In recent years, tremendous interest has been evoked in the development of fibre optic inertial systems. Apart from this, the optical fibre systems are proving their might in the areas of monitoring of the environmental parameters. In addition to this, optical fibre systems find extensive applications in satellite and rocket based systems. In this paper, the highlights of these new technologies have been presented with special emphasis on communication aspects between satellite check-out and data reception communication links between ground station and tracking antenna. Also, few other possible applications of fibre based instrumentation onâ€"board satellites are dealt with.