Investigations on Ultrasonic Transducer Array Systems for NDE of Underwater Pipelines

The main objective of carrying out this investigation is to develop suitable transducer array systems so that underwater pipeline inspection could be carried out in a much better way, a focused beam and electronic steering can reduce inspection time as well. Better results are obtained by optimizing the array parameters. The spacing between the elements is assumed to be half the wavelength so that the interelement interaction is minimum. For NDT applications these arrays are operated at MHz range. The wavelengths become very small in these frequency ranges. Then the size of the array elements becomes very small, requiring hybrid construction techniques for their fabrication. Transducer elements have been fabricated using PVDF as the active, mild steel as the backing and conducting silver preparation as the bonding materials. The transducer is operated in the (3,3) mode. The construction of a high frequency array is comparatively complicated. The interelement spacing between the transducer elements becomes considerably small when high frequencies are considered. It becomes very difficult to construct the transducer manually. The electrode connections to the elements can produce significant loading effect. The array has to be fabricated using hybrid construction techniques. The active materials has to be deposited on a proper substrate and etching techniques are required to fabricate the array. The annular ring, annular cylindrical or other similar structural forms of arrays may also find applications in the near future in treatments were curved contours of the human body are affected.

Comparison Study of Pattern Synthesis Techniques Using Neural Networks

In this paper, a comparison study among three neuralnetwork algorithms for the synthesis of array patterns is presented. The neural networks are used to estimate the array elements' excitations for an arbitrary pattern. The architecture of the neural networks is discussed and simulation results are presented. Two new neural networks, based on radial basis functions (RBFs) and wavelet neural networks (WNNs), are introduced. The proposed networks offer a more efficient synthesis procedure, as compared to other available techniques

Qualitative Air Flow Modelling and Analysis of Data Centre Air Conditioning as Multiple Jet Array

Data centre is a centralized repository,either physical or virtual,for the storage,management and dissemination of data and information organized around a particular body and nerve centre of the present IT revolution.Data centre are expected to serve uniinterruptedly round the year enabling them to perform their functions,it consumes enormous energy in the present scenario.Tremendous growth in the demand from IT Industry made it customary to develop newer technologies for the better operation of data centre.Energy conservation activities in data centre mainly concentrate on the air conditioning system since it is the major mechanical sub-system which consumes considerable share of the total power consumption of the data centre.The data centre energy matrix is best represented by power utilization efficiency(PUE),which is defined as the ratio of the total facility power to the IT equipment power.Its value will be greater than one and a large value of PUE indicates that the sub-systems draw more power from the facility and the performance of the data will be poor from the stand point of energy conservation. PUE values of 1.4 to 1.6 are acievable by proper design and management techniques.Optimizing the air conditioning systems brings enormous opportunity in bringing down the PUE value.The air conditioning system can be optimized by two approaches namely,thermal management and air flow management.thermal management systems are now introduced by some companies but they are highly sophisticated and costly and do not catch much attention in the thumb rules.

Development of a Fully Automated Image Analysis Method for High Density cDNA and array CGH Microarray Based Genomic Studies

In this thesis, different techniques for image analysis of high density microarrays have been investigated. Most of the existing image analysis techniques require prior knowledge of image specific parameters and direct user intervention for microarray image quantification. The objective of this research work was to develop of a fully automated image analysis method capable of accurately quantifying the intensity information from high density microarrays images. The method should be robust against noise and contaminations that commonly occur in different stages of microarray development.