Tropical Mesoscale Convective Systems and Associated Energetics : Observational and Modeling Studies

The main purpose of the thesis is to improve the state of knowledge and understanding of the physical structure of the TMCS and its short range prediction. The present study principally addresses the fine structure, dynamics and microphysics of severe convective storms.The structure and dynamics of the Tropical cloud clusters over Indian region is not well understood. The observational cases discussed in the thesis are limited to the temperature and humidity observations. We propose a mesoscale observational network along with all the available Doppler radars and other conventional and non—conventional observations. Simultaneous observations with DWR, VHF and UHF radars of the same cloud system will provide new insight into the dynamics and microphysics of the clouds. More cases have to be studied in detail to obtain climatology of the storm type passing over tropical Indian region. These observational data sets provide wide variety of information to be assimilated to the mesoscale data assimilation system and can be used to force CSRM.The gravity wave generation and stratosphere troposphere exchange (STE) processes associated with convection gained a great deal of attention to modem science and meteorologist. Round the clock observations using VHF and UHF radars along with supplementary data sets like DWR, satellite, GPS/Radiosondes, meteorological rockets and aircrafl observations is needed to explore the role of convection and associated energetics in detail.

ARMA modeling of time series based on rational approximation of spectral density function

This study is concerned with Autoregressive Moving Average (ARMA) models of time series. ARMA models form a subclass of the class of general linear models which represents stationary time series, a phenomenon encountered most often in practice by engineers, scientists and economists. It is always desirable to employ models which use parameters parsimoniously. Parsimony will be achieved by ARMA models because it has only finite number of parameters. Even though the discussion is primarily concerned with stationary time series, later we will take up the case of homogeneous non stationary time series which can be transformed to stationary time series. Time series models, obtained with the help of the present and past data is used for forecasting future values. Physical science as well as social science take benefits of forecasting models. The role of forecasting cuts across all fields of management-—finance, marketing, production, business economics, as also in signal process, communication engineering, chemical processes, electronics etc. This high applicability of time series is the motivation to this study.

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.

Mesozooplankton of the Arabian Sea and the Bay of Bengal with special reference to planktonic ostracods

The Arabian Sea and the Bay of Bengal are both highly dynamic ecosystems, due to the seasonally reversing monsoon winds, but the processes affecting the mesozooplankton community remain poorly understood. These are important basins exhibiting enhanced biological production as a result of upwelling, winter cooling and other episodic events such as eddies and gyres. Zooplankters are primarily the prey for almost all fish larvae. Seasonal changes in the biogeochemical processes can strongly affect zooplankton density and distribution, which in turn, strongly affect the larval growth, and consequently, the pelagic fish recruitment. It is clear that plankton biomass and biogeochemical fluxes are not in steady state. Acoustic data on mesozooplankton abundance suggests that they also exist in the mesopelagic zone. Earlier studies were confined only to the upper 200 m and hence the structure of mesozooplankton community in the deeper layers was not well known. Copepods are the dominant mesoplankton group, and therefore the majority of the studies were focused on them. The planktonic ostracods are the second major crustacean group and at times, their swarms can outnumber all other planktonic groups. The understanding of the community structure of the ostracods is essential to establish their role in the marine food web. Mesozooplankton is responsible for the vertical flux of organic matter produced by phytoplankton and is assumed to be equivalent to new production (Eppley & Peterson, 1979). Since the fate of newly produced organic matter depends upon their consumers, the zooplankton biomass must be estimated in size fractions or taxonomic components to understand the vertical flux of organic carbon. It is thus important to update our knowledge on different groups of zooplankton on the basis of seasonal and temporal distribution. The distribution in space and time is essential for modeling the carbon cycling that structure the marine ecosystems

Modeling Of Work-Related Musculoskeletal Disorders In Chemical Process Industry In India

In this modern complex world, stress at work is found to be increasingly a common feature in day to day life. For the same reason, job stress is one of the active areas in occupational health and safety research for over last four decades and is continuing to attract researchers in academia and industry. Job stress in process industries is of concern due to its influence on process safety, and worker‘s safety and health. Safety in process (chemical and nuclear material) industry is of paramount importance, especially in a thickly populated country like India. Stress at job is the main vector in inducing work related musculoskeletal disorders which in turn can affect the worker health and safety in process industries. In view of the above, the process industries should try to minimize the job stress in workers to ensure a safe and healthy working climate for the industry and the worker. This research is mainly aimed at assessing the influence of job stress in inducing work related musculoskeletal disorders in chemical process industries in India

Numerical Simulation of Two-Part Underwater Towing System

The motion instability is an important issue that occurs during the operation of towed underwater vehicles (TUV), which considerably affects the accuracy of high precision acoustic instrumentations housed inside the same. Out of the various parameters responsible for this, the disturbances from the tow-ship are the most significant one. The present study focus on the motion dynamics of an underwater towing system with ship induced disturbances as the input. The study focus on an innovative system called two-part towing. The methodology involves numerical modeling of the tow system, which consists of modeling of the tow-cables and vehicles formulation. Previous study in this direction used a segmental approach for the modeling of the cable. Even though, the model was successful in predicting the heave response of the tow-body, instabilities were observed in the numerical solution. The present study devises a simple approach called lumped mass spring model (LMSM) for the cable formulation. In this work, the traditional LMSM has been modified in two ways. First, by implementing advanced time integration procedures and secondly, use of a modified beam model which uses only translational degrees of freedoms for solving beam equation. A number of time integration procedures, such as Euler, Houbolt, Newmark and HHT-α were implemented in the traditional LMSM and the strength and weakness of each scheme were numerically estimated. In most of the previous studies, hydrodynamic forces acting on the tow-system such as drag and lift etc. are approximated as analytical expression of velocities. This approach restricts these models to use simple cylindrical shaped towed bodies and may not be applicable modern tow systems which are diversed in shape and complexity. Hence, this particular study, hydrodynamic parameters such as drag and lift of the tow-system are estimated using CFD techniques. To achieve this, a RANS based CFD code has been developed. Further, a new convection interpolation scheme for CFD simulation, called BNCUS, which is blend of cell based and node based formulation, was proposed in the study and numerically tested. To account for the fact that simulation takes considerable time in solving fluid dynamic equations, a dedicated parallel computing setup has been developed. Two types of computational parallelisms are explored in the current study, viz; the model for shared memory processors and distributed memory processors. In the present study, shared memory model was used for structural dynamic analysis of towing system, distributed memory one was devised in solving fluid dynamic equations.

‘Modeling and Analysis of Competing Risks Data’

there has been much research on analyzing various forms of competing risks data. Nevertheless, there are several occasions in survival studies, where the existing models and methodologies are inadequate for the analysis competing risks data. ldentifiabilty problem and various types of and censoring induce more complications in the analysis of competing risks data than in classical survival analysis. Parametric models are not adequate for the analysis of competing risks data since the assumptions about the underlying lifetime distributions may not hold well. Motivated by this, in the present study. we develop some new inference procedures, which are completely distribution free for the analysis of competing risks data.

Analyzing and Modeling a Multiparty Outsourcing Environment.

This paper discusses the complexities involved in managing and monitoring the delivery of IT services in a multiparty outsourcing environment. The complexities identified are grouped into four categories and are tabulated. A discussion on an attempt to model a multiparty outsourcing scenario using UML is also presented and explained using an illustration. Such a model when supplemented by a performance evaluation tool can enable an organization to manage the provision of IT services in a multiparty outsourcing environment more effectively

Acoustic Structure Interaction For Floating Structure Under Moving Load

The present thesis concentrates largely on sound radiation from floating structure due to moving load

RMAC-M: Extending the R-MAC Protocol for an Energy Efficient, Delay Tolerant Underwater Acoustic Sensor Network application with a mobile data mule node

One of the major applications of underwater acoustic sensor networks (UWASN) is ocean environment monitoring. Employing data mules is an energy efficient way of data collection from the underwater sensor nodes in such a network. A data mule node such as an autonomous underwater vehicle (AUV) periodically visits the stationary nodes to download data. By conserving the power required for data transmission over long distances to a remote data sink, this approach extends the network life time. In this paper we propose a new MAC protocol to support a single mobile data mule node to collect the data sensed by the sensor nodes in periodic runs through the network. In this approach, the nodes need to perform only short distance, single hop transmission to the data mule. The protocol design discussed in this paper is motivated to support such an application. The proposed protocol is a hybrid protocol, which employs a combination of schedule based access among the stationary nodes along with handshake based access to support mobile data mules. The new protocol, RMAC-M is developed as an extension to the energy efficient MAC protocol R-MAC by extending the slot time of R-MAC to include a contention part for a hand shake based data transfer. The mobile node makes use of a beacon to signal its presence to all the nearby nodes, which can then hand-shake with the mobile node for data transfer. Simulation results show that the new protocol provides efficient support for a mobile data mule node while preserving the advantages of R-MAC such as energy efficiency and fairness.

Modeling of ALFA Programs Using PVS Theorem Prover

In Safety critical software failure can have a high price. Such software should be free of errors before it is put into operation. Application of formal methods in the Software Development Life Cycle helps to ensure that the software for safety critical missions are ultra reliable. PVS theorem prover, a formal method tool, can be used for the formal verification of software in ADA Language for Flight Software Application (ALFA.). This paper describes the modeling of ALFA programs for PVS theorem prover. An ALFA2PVS translator is developed which automatically converts the software in ALFA to PVS specification. By this approach the software can be verified formally with respect to underflow/overflow errors and divide by zero conditions without the actual execution of the code.

A facile and single pot strategy for the synthesis of novel naphthyridine derivatives under microwave irradiation conditions using ZnCl2 as catalyst, evaluation of AChE inhibitory activity, and molecular modeling studies

A series of novel naphthyridine derivatives 3 and 4 was prepared from substituted pyridine 2 and ketones using ZnCl2 as catalyst under microwave irradiation conditions. All the compounds were evaluated for AChE inhibitory activity and promising compounds 3d, 3e, 4b, and 4g was identified. Representative compounds 3d and 3e were found to show insignificant THLE-2 liver cell viability/toxicity. The binding mode between X-ray crystal structure of human AChE and compounds was studied using molecular docking method and fitness scores were found to be in good correlation with the activity data.

Modeling of ALFA Programs Using PVS Theorem Prover

In Safety critical software failure can have a high price. Such software should be free of errors before it is put into operation. Application of formal methods in the Software Development Life Cycle helps to ensure that the software for safety critical missions are ultra reliable. PVS theorem prover, a formal method tool, can be used for the formal verification of software in ADA Language for Flight Software Application (ALFA.). This paper describes the modeling of ALFA programs for PVS theorem prover. An ALFA2PVS translator is developed which automatically converts the software in ALFA to PVS specification. By this approach the software can be verified formally with respect to underflow/overflow errors and divide by zero conditions without the actual execution of the code

Artificial neural network modeling for surface roughness prediction in cylindrical grinding of Al‐SiCp metal matrix composites and ANOVA analysis

Metal matrix composites (MMC) having aluminium (Al) in the matrix phase and silicon carbide particles (SiCp) in reinforcement phase, ie Al‐SiCp type MMC, have gained popularity in the re‐cent past. In this competitive age, manufacturing industries strive to produce superior quality products at reasonable price. This is possible by achieving higher productivity while performing machining at optimum combinations of process variables. The low weight and high strength MMC are found suitable for variety of components

The role of lower partial moments in stochastic modeling

Lower partial moments plays an important role in the analysis of risks and in income/poverty studies. In the present paper, we further investigate its importance in stochastic modeling and prove some characterization theorems arising out of it. We also identify its relationships with other important applied models such as weighted and equilibrium models. Finally, some applications of lower partial moments in poverty studies are also examined