Thermodynamics of transfer of polar nonelectrolytes from water to aqueous salt solutions

The Setschenow parameter and thermodynamic parameters of transfer of a number of monosubstituted benzoic acids from water to different salt solutions have been reported. The data have been rationalized by considering the structure breaking effects of the ions of the salts, the localised hydrolysis model, the internal pressure theory and Symons' theory of water structure.

Solubility of 4-Nitrobenzoic Acid in Water & Salt Solutions

Solubilities of 4-nitrobenzoic acid at 25°, 35° and 42°C have been determined in water and in the presence of several concentrations of electrolytes. The free energies, enthalpies and entropies of transfer are also reported. The data have been rationalized by considering the structure-breaking effects of the ions of the salts and the requirement of the localized hydrolysis model. The theory of Symons is not satisfactory to rationalise the experimental data.

Thermodynamic Parameters of Transfer of 2-Nitrobenzoic Acid & 3-Nitrobenzoic Acid from Water to Aqueous Salt Solutions

The Setschenow parameters of solubility in salt solutions and the thermodynamic parameters (25·C) of transfer from aqueous solution to aqueous salt solutions for 2-nitrobenzoic acid and 3-nitrobenzoic acid have been reported. The data have been rationalized on the basis of the localized hydrolysis model and the structure breaking action of ions of the electrolytes.

Thermodynamics of Transfer of Aminobenzoic Acids from Water to Aqueous Salt Solutions

The Setschenow parameter and thermodynamic parameters of transfer of 2- and 4-aminobenzoic acids from water to salt solutions have been reported. The results are discussed in terms of the structure- breaking effects of the ions of the salts, the localized hydrolysis model, and the internal pressure theory.

Investigation of nonlinear absorption and aggregation in aqueous solutions of rhodamine B using thermal lens technique

Thermal lensing effect was studied in aqueous solutions of rhodamine B using 532 nm, 9 ns pulses from a Nd:YAG laser. A low intensity He-Ne laser beam was used for probing the thermal lens. Results obtained show that it is appropriate to use this technique for studying nonlinear absorption processes like two photon absorption or excited state absorption and for analyzing dimerization equilibria.

Studies of nonlinear absorption and aggregation in aqueous solutions of rhodamine 6G using a transient thermal lens technique

Dual-beam transient thermal lens studies were carried out in aqueous solutions of rhodamine 6G using 532 nm pulses from a frequency-doubled Nd:YAG laser. The analysis of the observed data showed that the thermal lens method can effectively be utilized to study the nonlinear absorption and aggregation which are taking place in a dye medium.

Experimental investigation of optical limiting and thermal lensing in toluene solutions of C70

Optical limiting and thermal lensing studies are carried out in C70–toluene solutions. The measurements are performed using 9-ns pulses generated from a frequencydoubled Nd:YAG laser at 532 nm. Optical limiting studies in fullerene molecules lead to the conclusion that reverse saturable absorption is the major mechanism for limiting. Analysis of thermal lensing measurements showed a quadratic dependence of thermal lens signal on incident laser energy, which also supports the view that optical limiting in C70 arises due to sequential two-photon absorption via excited triplet state (reverse saturable absorption).

Characteristics of two-photon absorption in methanol solutions of Rhodamine 6G using laser induced pulsed photoacoustics

Two-photon absorption in methanol solutions of Rhodamine 6G is investigated by photoacoustics using the second harmonic of a pulsed Nd:YAG laser. Competition between one-photon and two-photon processes is observed, depending critically on the sample concentration and input light flux.

Application of laser beam deflection technique to study the diffusion process in electrolyte solutions

A simple method based on laser beam deflection to study the variation of diffusion coefficient with concentration in a solution is presented. When a properly fanned out laser beam is passed through a rectangular cell filled with solution having concentration gradient, the emergent beam traces out a curved pattern on a screen. By taking measurements on the pattern at different concentrations, the variation of diffusion coefficient with concentration can be determined.

Two and Three Photon Absorption in Rhodamine 6G Methanol Solutions Using Pulsed Thermal Lens Technique

Dual beam transient thermal lens studies were carried out in rhodamine 6G methanol solutions using 532 nm pulses from a frequency doubled Nd:YAG laser. Analysis of thermal lens signal shows the existence of different nonlinear processes like two photon absorption and three photon absorption phenomena along with one photon absorption. Concentration of the dye in the solution has been found to influence the occurrence of the different processes in a significant way.

Reinforcement Learning Approaches to Power System Scheduling

One major component of power system operation is generation scheduling. The objective of the work is to develop efficient control strategies to the power scheduling problems through Reinforcement Learning approaches. The three important active power scheduling problems are Unit Commitment, Economic Dispatch and Automatic Generation Control. Numerical solution methods proposed for solution of power scheduling are insufficient in handling large and complex systems. Soft Computing methods like Simulated Annealing, Evolutionary Programming etc., are efficient in handling complex cost functions, but find limitation in handling stochastic data existing in a practical system. Also the learning steps are to be repeated for each load demand which increases the computation time.Reinforcement Learning (RL) is a method of learning through interactions with environment. The main advantage of this approach is it does not require a precise mathematical formulation. It can learn either by interacting with the environment or interacting with a simulation model. Several optimization and control problems have been solved through Reinforcement Learning approach. The application of Reinforcement Learning in the field of Power system has been a few. The objective is to introduce and extend Reinforcement Learning approaches for the active power scheduling problems in an implementable manner. The main objectives can be enumerated as:(i) Evolve Reinforcement Learning based solutions to the Unit Commitment Problem.(ii) Find suitable solution strategies through Reinforcement Learning approach for Economic Dispatch. (iii) Extend the Reinforcement Learning solution to Automatic Generation Control with a different perspective. (iv) Check the suitability of the scheduling solutions to one of the existing power systems.First part of the thesis is concerned with the Reinforcement Learning approach to Unit Commitment problem. Unit Commitment Problem is formulated as a multi stage decision process. Q learning solution is developed to obtain the optimwn commitment schedule. Method of state aggregation is used to formulate an efficient solution considering the minimwn up time I down time constraints. The performance of the algorithms are evaluated for different systems and compared with other stochastic methods like Genetic Algorithm.Second stage of the work is concerned with solving Economic Dispatch problem. A simple and straight forward decision making strategy is first proposed in the Learning Automata algorithm. Then to solve the scheduling task of systems with large number of generating units, the problem is formulated as a multi stage decision making task. The solution obtained is extended in order to incorporate the transmission losses in the system. To make the Reinforcement Learning solution more efficient and to handle continuous state space, a fimction approximation strategy is proposed. The performance of the developed algorithms are tested for several standard test cases. Proposed method is compared with other recent methods like Partition Approach Algorithm, Simulated Annealing etc.As the final step of implementing the active power control loops in power system, Automatic Generation Control is also taken into consideration.Reinforcement Learning has already been applied to solve Automatic Generation Control loop. The RL solution is extended to take up the approach of common frequency for all the interconnected areas, more similar to practical systems. Performance of the RL controller is also compared with that of the conventional integral controller.In order to prove the suitability of the proposed methods to practical systems, second plant ofNeyveli Thennal Power Station (NTPS IT) is taken for case study. The perfonnance of the Reinforcement Learning solution is found to be better than the other existing methods, which provide the promising step towards RL based control schemes for practical power industry.Reinforcement Learning is applied to solve the scheduling problems in the power industry and found to give satisfactory perfonnance. Proposed solution provides a scope for getting more profit as the economic schedule is obtained instantaneously. Since Reinforcement Learning method can take the stochastic cost data obtained time to time from a plant, it gives an implementable method. As a further step, with suitable methods to interface with on line data, economic scheduling can be achieved instantaneously in a generation control center. Also power scheduling of systems with different sources such as hydro, thermal etc. can be looked into and Reinforcement Learning solutions can be achieved.

Thermal Conduction in Polymeric Nanofluids and Nanosolids Controlled by Interfacial Scattering:Solutions to Some Selected Problems

Dept.of Instrumentation,Cochin University of Science and Technology

Studies on magnetic monopole solutions of non-abelian gauge theories and related problems

In 1931 Dirac studied the motion of an electron in the field of a magnetic monopole and found that the quantization of electric charge can be explained by postulating the mere existence of a magnetic monopole. Since 1974 there has been a resurgence of interest in magnetic monopole due to the work of ‘t’ Hooft and Polyakov who independently observed that monopoles can exist as finite energy topologically stable solutions to certain spontaneously broken gauge theories. The thesis, “Studies on Magnetic Monopole Solutions of Non-abelian Gauge Theories and Related Problems”, reports a systematic investigation of classical solutions of non-abelian gauge theories with special emphasis on magnetic monopoles and dyons which possess both electric and magnetic charges. The formation of bound states of a dyon with fermions and bosons is also studied in detail. The thesis opens with an account of a new derivation of a relationship between the magnetic charge of a dyon and the topology of the gauge fields associated with it. Although this formula has been reported earlier in the literature, the present method has two distinct advantages. In the first place, it does not depend either on the mechanism of symmetry breaking or on the nature of the residual symmetry group. Secondly, the results can be generalized to finite temperature monopoles.

Stochastic processes and their applications time dependent solutions for some queueing and inventory models

The objective of this thesis is to study the time dependent behaviour of some complex queueing and inventory models. It contains a detailed analysis of the basic stochastic processes underlying these models. In the theory of queues, analysis of time dependent behaviour is an area.very little developed compared to steady state theory. Tine dependence seems certainly worth studying from an application point of view but unfortunately, the analytic difficulties are considerable. Glosod form solutions are complicated even for such simple models as M/M /1. Outside M/>M/1, time dependent solutions have been found only in special cases and involve most often double transforms which provide very little insight into the behaviour of the queueing systems themselves. In inventory theory also There is not much results available giving the time dependent solution of the system size probabilities. Our emphasis is on explicit results free from all types of transforms and the method used may be of special interest to a wide variety of problems having regenerative structure.