Studies on Rubber Composition as Passive Acoustic Materials in Underwater Electro Acoustic Tranducer Technology and Their aging Characteristic

The research work has been in the area of compounding and characterization of rubbers for use in under water electro acoustic transducers. The study also covers specific material system such as encapsulation materials, baffle material, seal material, etc. Life prediction techniques of under water rubbers in general have been established with reference to more than one functional property. Ranges of passive materials, besides the active sensing material go into the construction of underwater electro acoustic transducers. Reliability of the transducer is critically dependent on these passive materials. Rubbers are a major class of passive materials. The present work concentrates on these materials. Conventional rubbers are inadequate to meet many of the stringent function specific requirements. There exists a large gap of information in the rubber technology of underwater rubbers, particularly relating to underwater electro acoustic transducers. This study is towards filling up the gaps of information in this crucial area. Water intake into rubber is considered as the single most important issue for the long-term performance of rubbers, especially Neoprene. In this study, the cause and effects of a range of parameters affecting the water absorption by diffusion and permeation have been investigated.

STUDIES ON THE STRESS FLUCTUATIONS IN SHEARED STOKESIAN SUSPENSIONS USING CHAOS THEORY AND NONLINEAR DYNAMICS

The thesis report results obtained from a detailed analysis of the fluctuations of the rheological parameters viz. shear and normal stresses, simulated by means of the Stokesian Dynamics method, of a macroscopically homogeneous sheared suspension of neutrally buoyant non-Brownian suspension of identical spheres in the Couette gap between two parallel walls in the limit of vanishingly small Reynolds numbers using the tools of non-linear dynamics and chaos theory for a range of particle concentration and Couette gaps. The thesis used the tools of nonlinear dynamics and chaos theory viz. average mutual information, space-time separation plots, visual recurrence analysis, principal component analysis, false nearest-neighbor technique, correlation integrals, computation of Lyapunov exponents for a range of area fraction of particles and for different Couette gaps. The thesis observed that one stress component can be predicted using another stress component at the same area fraction. This implies a type of synchronization of one stress component with another stress component. This finding suggests us to further analysis of the synchronization of stress components with another stress component at the same or different area fraction of particles. The different model equations of stress components for different area fraction of particles hints at the possible existence a general formula for stress fluctuations with area fraction of particle as a parameter

Optical and electrical properties of amorphous zinc tin oxide thin films examined for thin film transistor application

Structural, electronic, and optical properties of amorphous and transparent zinc tin oxide films deposited on glass substrates by pulsed laser deposition (PLD) were examined for two chemical compositions of Zn:Sn=1:1 and 2:1 as a function of oxygen partial pressure PO2 used for the film deposition and annealing temperature. Different from a previous report on sputter-deposited films Chiang et al., Appl. Phys. Lett. 86, 013503 2005 , the PLD-deposited films crystallized at a lower temperature 450 °C to give crystalline ZnO and SnO2 phases. The optical band gaps Tauc gaps were 2.80−2.85 eV and almost independent of oxygen PO2 , which are smaller than those of the corresponding crystals 3.35−3.89 eV . Films deposited at low PO2 showed significant subgap absorptions, which were reduced by postthermal annealing. Hall mobility showed steep increases when carrier concentration exceeded threshold values and the threshold value depended on the film chemical composition. The films deposited at low PO2 2 Pa had low carrier concentrations. It is thought that the low PO2 produced high-density oxygen deficiencies and generated electrons, but these electrons were trapped in localized states, which would be observed as the subgap absorptions. Similar effects were observed for 600 °C crystallized films and their resistivities were increased by formation of subgap states due to the reducing high-temperature condition. High carrier concentrations and large mobilities were obtained in an intermediate PO2 region for the as-deposited films.

Growth of zinc oxide thin films for optoelectronic application by pulsed laser deposition

Zinc oxide (ZnO) thin films were deposited on quartz, silicon, and polymer substrates by pulsed laser deposition (PLD) technique at different oxygen partial pressures (0.007 mbar to 0.003 mbar). Polycrystalline ZnO films were obtained at room temperature when the oxygen pressure was between 0.003 mbar and .007 mbar, above and below this pressure the films were amorphous as indicated by the X-ray diffraction (XRD). ZnO films were deposited on Al2O3 (0001) at different substrate temperatures varying from 400oC to 600oC and full width half maximum (FWHM) of XRD peak is observed to decrease as substrate temperature increases. The optical band gaps of these films were nearly 3.3 eV. A cylindrical Langmuir probe is used for the investigation of plasma plume arising from the ZnO target. The spatial and temporal variations in electron density and electron temperature are studied. Optical emission spectroscopy is used to identify the different ionic species in the plume. Strong emission lines of neutral Zn, Zn+ and neutral oxygen are observed. No electronically excited O+ cations are identified, which is in agreement with previous studies of ZnO plasma plume.

Studies on Heat Diffusion in Selected Conducting Polymers using Probe Beam Deflection and Photoacoustic Techniques

In the present study, radio frequency plasma polymerization technique is used to prepare thin films of polyaniline, polypyrrole, poly N-methyl pyrrole and polythiophene. The thermal characterization of these films is carried out using transverse probe beam deflection method. Electrical conductivity and band gaps are also determined. The effect of iodine doping on electrical conductivity and the rate of heat diffusion is explored.Bulk samples of poyaniline and polypyrrole in powder form are synthesized by chemical route. Open photoacoustic cell configuration is employed for the thermal characterization of these samples. The effect of acid doping on heat diffusion in these bulk samples of polyaniline is also investigated. The variation of electrical conductivity of doped polyaniline and polypyrrole with temperature is also studied for drawing conclusion on the nature of conduction in these samples. In order to improve the processability of polyaniline and polypyrrole, these polymers are incorporated into a host matrix of poly vinyl chloride. Measurements of thermal diffusivity and electrical conductivity of these samples are carried out to investigate the variation of these quantities as a function of the content of polyvinyl chloride.

Analysis and Optimization of Machining Process Using Evolutionary Algorithms

To ensure quality of machined products at minimum machining costs and maximum machining effectiveness, it is very important to select optimum parameters when metal cutting machine tools are employed. Traditionally, the experience of the operator plays a major role in the selection of optimum metal cutting conditions. However, attaining optimum values each time by even a skilled operator is difficult. The non-linear nature of the machining process has compelled engineers to search for more effective methods to attain optimization. The design objective preceding most engineering design activities is simply to minimize the cost of production or to maximize the production efficiency. The main aim of research work reported here is to build robust optimization algorithms by exploiting ideas that nature has to offer from its backyard and using it to solve real world optimization problems in manufacturing processes.In this thesis, after conducting an exhaustive literature review, several optimization techniques used in various manufacturing processes have been identified. The selection of optimal cutting parameters, like depth of cut, feed and speed is a very important issue for every machining process. Experiments have been designed using Taguchi technique and dry turning of SS420 has been performed on Kirlosker turn master 35 lathe. Analysis using S/N and ANOVA were performed to find the optimum level and percentage of contribution of each parameter. By using S/N analysis the optimum machining parameters from the experimentation is obtained.Optimization algorithms begin with one or more design solutions supplied by the user and then iteratively check new design solutions, relative search spaces in order to achieve the true optimum solution. A mathematical model has been developed using response surface analysis for surface roughness and the model was validated using published results from literature.Methodologies in optimization such as Simulated annealing (SA), Particle Swarm Optimization (PSO), Conventional Genetic Algorithm (CGA) and Improved Genetic Algorithm (IGA) are applied to optimize machining parameters while dry turning of SS420 material. All the above algorithms were tested for their efficiency, robustness and accuracy and observe how they often outperform conventional optimization method applied to difficult real world problems. The SA, PSO, CGA and IGA codes were developed using MATLAB. For each evolutionary algorithmic method, optimum cutting conditions are provided to achieve better surface finish.The computational results using SA clearly demonstrated that the proposed solution procedure is quite capable in solving such complicated problems effectively and efficiently. Particle Swarm Optimization (PSO) is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. From the results it has been observed that PSO provides better results and also more computationally efficient.Based on the results obtained using CGA and IGA for the optimization of machining process, the proposed IGA provides better results than the conventional GA. The improved genetic algorithm incorporating a stochastic crossover technique and an artificial initial population scheme is developed to provide a faster search mechanism. Finally, a comparison among these algorithms were made for the specific example of dry turning of SS 420 material and arriving at optimum machining parameters of feed, cutting speed, depth of cut and tool nose radius for minimum surface roughness as the criterion. To summarize, the research work fills in conspicuous gaps between research prototypes and industry requirements, by simulating evolutionary procedures seen in nature that optimize its own systems.

Studies on Thermal structure in the seas around in India

The thesis entitled Studies on Thermal Structure in the Seas Around India. An attempt is made in this study to document the observed variability of thermal structure, both on seasonal and short-term scales, in the eastern Arabian Sea and southwestern Bay of Bengal, from the spatial and time series data sets from a reasonably strong data base. The present study has certain limitations. The mean temperatures are based on an uneven distribution of data in space and time. Some of the areas, although having a ‘full annual coverage, do not have adequate data for some months. Some portions in the area under study are having data gaps. The consistency and the coherence in the internal wave characteristics could not be examined due to non-availability of adequate data sets. The influence of generating mechanisms; other than winds and tides on the observed internal wave fields could not be ascertained due to lack of data. However, a comprehensive and intensive data collection can overcome these limitations. The deployment of moored buoys with arrays of sensors at different depths at some important locations for about 5 to 10 years can provide intensive and extensive data sets. This strong data base can afford to address the short-term and seasonal variability of thermal field and understand in detail the individual and collective influences of various physical and dynamical mechanisms responsible for such variability.

Studies on rubber compositions as passive acoustic materials in underwater electro acoustic transducer technology-and their aging characteristics

Rubber has become an indispensable material in Ocean technology. Rubber components play critical roles such as sealing, damping, environmental protection, electrical insulation etc. in most under water engineering applications. Technology driven innovations in electro acoustic transducers and other sophisticated end uses have enabled quantum jump in the quality and reliability of rubber components. Under water electro acoustic transducers use rubbers as a critical material in their construction. Work in this field has lead to highly reliable and high performance materials which has enhanced service life of transducers to the extent of 1015 years. Present work concentrates on these materials. Conventional rubbers are inadequate to meet many of the stringent functional of the requirements. There exists large gap of information in the rubber technology of under water rubbers, particularly in the context of under water electro acoustic transducers. Present study is towards filling up the gaps of information in this crucial area. The research work has been in the area of compounding and characterisation of rubbers for use in under water electro acoustic transducers. The study also covers specific material system such as encapsulation material, baffle material, seal material, etc. Life prediction techniques of under water rubbers in general has been established with reference to more than one functional property. This thesis is divided into 6 chapters.

Bionomics, Resource Characteristics And Distribution Of The Threatened Freshwater Fishes Of Kerala

The previous faunistic studies were concentrated.on the taxonomical and zoogeo— graphical aspects. These studies contributed to many new additions to the fish fauna of Kerala meanwhile many species described earlier are reported missing in recent years. Many fish species were collected only once or twice by scientists. Detailed information on distribution, habitat, feeding habits, reproduction, population size, etc. are available only with regard to a very few fish species. A meaningful assessment on the biodiversity status of the majority of freshwater fishes cannot be done for want of sufficient data base and therefore, no suitable conservation and management programmes are forthcoming for the protection and preservation of the unique fish germplasm resources of Kerala. The present study was conceptualised and undertaken mostly aiming at bridging these gaps by generating an authentic data base on the distribution, resource characteristics and bionomics of the threatened fishes inhabiting the rivers of Kerala. Osteobrama bakeri (Day) is an endemic fish having a very highly restricted and fragmented distribution in Periyar, Chalakudy, Kabini, Kallada and Meenachil rivers of Kerala. This belongs to vulnerable category and is locally known as Mullanpaval which is valued as food fish. Besides, due to its vibrant and attractive colouration and easiness for domestication, it has great potential for being propagated as an ornamental fish. Hitherto, no information is available on the bionomics and resource characteristics of this species. Studies on detailed life history traits are indispensable for fishery management, development of captive breeding technique and implementation of various conservation programmes. In the present study, a pioneer attempt is also made to investigate the life history traits, resource characteristics, proximate composition, etc. of O.baken'.

Speaker identification using models for phonemes

Motivation for Speaker recognition work is presented in the first part of the thesis. An exhaustive survey of past work in this field is also presented. A low cost system not including complex computation has been chosen for implementation. Towards achieving this a PC based system is designed and developed. A front end analog to digital convertor (12 bit) is built and interfaced to a PC. Software to control the ADC and to perform various analytical functions including feature vector evaluation is developed. It is shown that a fixed set of phrases incorporating evenly balanced phonemes is aptly suited for the speaker recognition work at hand. A set of phrases are chosen for recognition. Two new methods are adopted for the feature evaluation. Some new measurements involving a symmetry check method for pitch period detection and ACE‘ are used as featured. Arguments are provided to show the need for a new model for speech production. Starting from heuristic, a knowledge based (KB) speech production model is presented. In this model, a KB provides impulses to a voice producing mechanism and constant correction is applied via a feedback path. It is this correction that differs from speaker to speaker. Methods of defining measurable parameters for use as features are described. Algorithms for speaker recognition are developed and implemented. Two methods are presented. The first is based on the model postulated. Here the entropy on the utterance of a phoneme is evaluated. The transitions of voiced regions are used as speaker dependent features. The second method presented uses features found in other works, but evaluated differently. A knock—out scheme is used to provide the weightage values for the selection of features. Results of implementation are presented which show on an average of 80% recognition. It is also shown that if there are long gaps between sessions, the performance deteriorates and is speaker dependent. Cross recognition percentages are also presented and this in the worst case rises to 30% while the best case is 0%. Suggestions for further work are given in the concluding chapter.

Gap Analysis For Implementing Tqm In Seafood Exporting Firms

Gap analysis is a very useful tool for firms contemplating adoption of a new system. This paper envisages the use of the gap analysis tool as a precursor for Indian seafood exporting firms to adopt total quality management. Total quality management (TQM) is a management philosophy which strives to put quality at the forefront of all its decision-making, thereby satisfying customers. We therefore recommend that firms adopt the TQM system for better alignment of management goals. The gap analysis tool serves as a roadmap for TQM implementation, by showing the management where they actually are and where they want to be. The main gaps were found to be in the areas of usage of SPC tools (66.7%), benchmarking (65.6%), top management commitment (56.25%) and customer focus (48.1%).

Challenges Faced by Kerala Tourism Industry

Tourism being a smokeless industry is now a multi-billion, multi-sectoral and multi-dimensional activity in the world. Twenty first century tourism has reached up to space when a Russian rocket carried the space vehicle of Dennis Tito, an American businessman and the world’s first space tourist, to the space station. Time is not too far to carry tourists to moon and other planets in specially launched vehicles. Tourism is being considered as an agent of social change bridging gaps among nations, regions and people and helping them to open up. It is a promoter of development-material and spiritual both at macro and micro level. The General Assembly of the United Nations, in designating the year 1967 as ‘International Tourism Year’ recognized the importance of international travel as a means of fostering understanding among people, and giving them a knowledge of the rich heritage of the past civilizations, a better appreciation of the values of different cultures, thus contributing to the strengthening of world peace. It adopted the theme “Tourism-Passport to peace”. Our veteran national leader and the first Prime Minister of India, Jawaharlal Nehru had said” welcome a tourist and send back a friend” which indicates the need for extending friendly hospitality to the in bound tourists. Modern transportation has removed the obstacles of distance enabling people to appreciate each other engage in the exchange of ideas and commerce. Tourism can help overcome real prejudices and foster bonds. Tourism can be a real force of world peace. Considering the vast and varied potential of tourism in the state and its impact on the economic, social and cultural environment of the state, a detailed study is found to be relevant and imperative

Study on period search methods of variable stars: Application to ASAS and CRTS databases

Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.