| URI: | http://dyuthi.cusat.ac.in/purl/5415 |
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| Dyuthi T-2456.pdf | (7.380Mb) |
| Abstract: | In this thesis, the applications of the recurrence quantification analysis in metal cutting operation in a lathe, with specific objective to detect tool wear and chatter, are presented.This study is based on the discovery that process dynamics in a lathe is low dimensional chaotic. It implies that the machine dynamics is controllable using principles of chaos theory. This understanding is to revolutionize the feature extraction methodologies used in condition monitoring systems as conventional linear methods or models are incapable of capturing the critical and strange behaviors associated with the metal cutting process.As sensor based approaches provide an automated and cost effective way to monitor and control, an efficient feature extraction methodology based on nonlinear time series analysis is much more demanding. The task here is more complex when the information has to be deduced solely from sensor signals since traditional methods do not address the issue of how to treat noise present in real-world processes and its non-stationarity. In an effort to get over these two issues to the maximum possible, this thesis adopts the recurrence quantification analysis methodology in the study since this feature extraction technique is found to be robust against noise and stationarity in the signals.The work consists of two different sets of experiments in a lathe; set-I and set-2. The experiment, set-I, study the influence of tool wear on the RQA variables whereas the set-2 is carried out to identify the sensitive RQA variables to machine tool chatter followed by its validation in actual cutting. To obtain the bounds of the spectrum of the significant RQA variable values, in set-i, a fresh tool and a worn tool are used for cutting. The first part of the set-2 experiments uses a stepped shaft in order to create chatter at a known location. And the second part uses a conical section having a uniform taper along the axis for creating chatter to onset at some distance from the smaller end by gradually increasing the depth of cut while keeping the spindle speed and feed rate constant.The study concludes by revealing the dependence of certain RQA variables; percent determinism, percent recurrence and entropy, to tool wear and chatter unambiguously. The performances of the results establish this methodology to be viable for detection of tool wear and chatter in metal cutting operation in a lathe. The key reason is that the dynamics of the system under study have been nonlinear and the recurrence quantification analysis can characterize them adequately.This work establishes that principles and practice of machining can be considerably benefited and advanced from using nonlinear dynamics and chaos theory. |
| Description: | Division of Mechanical Engineering,CUSAT |
| URI: | http://dyuthi.cusat.ac.in/purl/2812 |
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| Dyuthi-T0833.pdf | (3.327Mb) |
| URI: | http://dyuthi.cusat.ac.in/purl/5592 |
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| Dyuthi T-2633.pdf | (7.389Mb) |
| URI: | http://dyuthi.cusat.ac.in/purl/5223 |
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| Dyuthi T-2258.pdf | (2.864Mb) |
| Abstract: | 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. |
| Description: | School of Engineering, Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/2817 |
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| Dyuthi-T0837.pdf | (6.227Mb) |
| URI: | http://dyuthi.cusat.ac.in/purl/5350 |
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| Dyuthi T-2407.pdf | (6.653Mb) |
| Abstract: | Software systems are progressively being deployed in many facets of human life. The implication of the failure of such systems, has an assorted impact on its customers. The fundamental aspect that supports a software system, is focus on quality. Reliability describes the ability of the system to function under specified environment for a specified period of time and is used to objectively measure the quality. Evaluation of reliability of a computing system involves computation of hardware and software reliability. Most of the earlier works were given focus on software reliability with no consideration for hardware parts or vice versa. However, a complete estimation of reliability of a computing system requires these two elements to be considered together, and thus demands a combined approach. The present work focuses on this and presents a model for evaluating the reliability of a computing system. The method involves identifying the failure data for hardware components, software components and building a model based on it, to predict the reliability. To develop such a model, focus is given to the systems based on Open Source Software, since there is an increasing trend towards its use and only a few studies were reported on the modeling and measurement of the reliability of such products. The present work includes a thorough study on the role of Free and Open Source Software, evaluation of reliability growth models, and is trying to present an integrated model for the prediction of reliability of a computational system. The developed model has been compared with existing models and its usefulness of is being discussed. |
| URI: | http://dyuthi.cusat.ac.in/purl/4965 |
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| Dyuthi-T2041.pdf | (3.721Mb) |
| URI: | http://dyuthi.cusat.ac.in/purl/5276 |
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| Dyuthi T-2312.pdf | (8.522Mb) |
| URI: | http://dyuthi.cusat.ac.in/purl/5580 |
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| Dyuthi T-2620.pdf | (8.815Mb) |
| Abstract: | The service quality of any sector has two major aspects namely technical and functional. Technical quality can be attained by maintaining technical specification as decided by the organization. Functional quality refers to the manner which service is delivered to customer which can be assessed by the customer feed backs. A field survey was conducted based on the management tool SERVQUAL, by designing 28 constructs under 7 dimensions of service quality. Stratified sampling techniques were used to get 336 valid responses and the gap scores of expectations and perceptions are analyzed using statistical techniques to identify the weakest dimension. To assess the technical aspects of availability six months live outage data of base transceiver were collected. The statistical and exploratory techniques were used to model the network performance. The failure patterns have been modeled in competing risk models and probability distribution of service outage and restorations were parameterized. Since the availability of network is a function of the reliability and maintainability of the network elements, any service provider who wishes to keep up their service level agreements on availability should be aware of the variability of these elements and its effects on interactions. The availability variations were studied by designing a discrete time event simulation model with probabilistic input parameters. The probabilistic distribution parameters arrived from live data analysis was used to design experiments to define the availability domain of the network under consideration. The availability domain can be used as a reference for planning and implementing maintenance activities. A new metric is proposed which incorporates a consistency index along with key service parameters that can be used to compare the performance of different service providers. The developed tool can be used for reliability analysis of mobile communication systems and assumes greater significance in the wake of mobile portability facility. It is also possible to have a relative measure of the effectiveness of different service providers. |
| Description: | School of Engineering, Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/3155 |
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| Dyuthi-T1129.pdf | (2.500Mb) |
| URI: | http://dyuthi.cusat.ac.in/purl/5481 |
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| Dyuthi T-2523.pdf | (13.04Mb) |
| URI: | http://dyuthi.cusat.ac.in/purl/5267 |
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| Dyuthi T-2303.pdf | (15.46Mb) |
| Abstract: | In case of novel products with short shelf life, sales data was either unavailable or scarcely available. The available methods for the estimation of demand of such products were direct survey methods, collection of opinion or indirect survey methods, comparison with established products and limited market trial. From literature review it was concluded that existing literature for predicting the demand of novel and short life products were scarce. This led to identification of problem namely demand forecast of relatively novel and short life products. Initially conventional methods like naive, exponential smoothing and moving average methods were used to predict the demand. Markov based model was then applied to forecast errors of the conventional methods. This model or algorithm requires only demand data of two consecutive months and hence is suited for demand forecast of novel products.This algorithm was then applied to two novel baked products, one of relatively large quantity and another of relatively small quantity. Naive, exponential smoothing and moving average methods were applied to this data and the forecasts as well as error for all the working days of two consecutive months were estimated. Markov based algorithm was then applied for these errors and the steady state probability was determined for each state of demand. A state of a system is where the system was at a point of time. The demand corresponding to the state with maximum probability was selected and the corresponding profit was estimated. The obtained profits were then compared and the combination with maximum profit was identified and the method is validated by estimating the annual savings that this method will bring to the firm when compared to existing methods in case of products A and BThe suitability of the model was validated by the fact that its implementation on product A and product B fetched more annual savings when compared to existing practice. Return on investment increased for product A and product B when compared to existing methods. Thus it was concluded that a firm can further enhance its profit by implementing this model or algorithm for more number of products. Further the model can be generalized by applying it to more types of novel products with short shelf life. The forecasting of novel and short life products was not much explored in previous research works. This model can act as the benchmark for future researches in forecasting of novel and short life products |
| URI: | http://dyuthi.cusat.ac.in/purl/5161 |
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| Dyuthi-T2195.pdf | (5.865Mb) |
| Abstract: | Pollution of water with pesticides has become a threat to the man, material and environment. The pesticides released to the environment reach the water bodies through run off. Industrial wastewater from pesticide manufacturing industries contains pesticides at higher concentration and hence a major source of water pollution. Pesticides create a lot of health and environmental hazards which include diseases like cancer, liver and kidney disorders, reproductive disorders, fatal death, birth defects etc. Conventional wastewater treatment plants based on biological treatment are not efficient to remove these compounds to the desired level. Most of the pesticides are phyto-toxic i.e., they kill the microorganism responsible for the degradation and are recalcitrant in nature. Advanced oxidation process (AOP) is a class of oxidation techniques where hydroxyl radicals are employed for oxidation of pollutants. AOPs have the ability to totally mineralise the organic pollutants to CO2 and water. Different methods are employed for the generation of hydroxyl radicals in AOP systems. Acetamiprid is a neonicotinoid insecticide widely used to control sucking type insects on crops such as leafy vegetables, citrus fruits, pome fruits, grapes, cotton, ornamental flowers. It is now recommended as a substitute for organophosphorous pesticides. Since its use is increasing, its presence is increasingly found in the environment. It has high water solubility and is not easily biodegradable. It has the potential to pollute surface and ground waters. Here, the use of AOPs for the removal of acetamiprid from wastewater has been investigated. Five methods were selected for the study based on literature survey and preliminary experiments conducted. Fenton process, UV treatment, UV/ H2O2 process, photo-Fenton and photocatalysis using TiO2 were selected for study. Undoped TiO2 and TiO2 doped with Cu and Fe were prepared by sol-gel method. Characterisation of the prepared catalysts was done by X-ray diffraction, scanning electron microscope, differential thermal analysis and thermogravimetric analysis. Influence of major operating parameters on the removal of acetamiprid has been investigated. All the experiments were designed using central compoiste design (CCD) of response surface methodology (RSM). Model equations were developed for Fenton, UV/ H2O2, photo-Fenton and photocatalysis for predicting acetamiprid removal and total organic carbon (TOC) removal for different operating conditions. Quality of the models were analysed by statistical methods. Experimental validations were also done to confirm the quality of the models. Optimum conditions obtained by experiment were verified with that obtained using response optimiser. Fenton Process is the simplest and oldest AOP where hydrogen peroxide and iron are employed for the generation of hydroxyl radicals. Influence of H2O2 and Fe2+ on the acetamiprid removal and TOC removal by Fenton process were investigated and it was found that removal increases with increase in H2O2 and Fe2+ concentration. At an initial concentration of 50 mg/L acetamiprid, 200 mg/L H2O2 and 20 mg/L Fe2+ at pH 3 was found to be optimum for acetamiprid removal. For UV treatment effect of pH was studied and it was found that pH has not much effect on the removal rate. Addition of H2O2 to UV process increased the removal rate because of the hydroxyl radical formation due to photolyis of H2O2. An H2O2 concentration of 110 mg/L at pH 6 was found to be optimum for acetamiprid removal. With photo-Fenton drastic reduction in the treatment time was observed with 10 times reduction in the amount of reagents required. H2O2 concentration of 20 mg/L and Fe2+ concentration of 2 mg/L was found to be optimum at pH 3. With TiO2 photocatalysis improvement in the removal rate was noticed compared to UV treatment. Effect of Cu and Fe doping on the photocatalytic activity under UV light was studied and it was observed that Cu doping enhanced the removal rate slightly while Fe doping has decreased the removal rate. Maximum acetamiprid removal was observed for an optimum catalyst loading of 1000 mg/L and Cu concentration of 1 wt%. It was noticed that mineralisation efficiency of the processes is low compared to acetamiprid removal efficiency. This may be due to the presence of stable intermediate compounds formed during degradation Kinetic studies were conducted for all the treatment processes and it was found that all processes follow pseudo-first order kinetics. Kinetic constants were found out from the experimental data for all the processes and half lives were calculated. The rate of reaction was in the order, photo- Fenton>UV/ H2O2>Fenton> TiO2 photocatalysis>UV. Operating cost was calculated for the processes and it was found that photo-Fenton removes the acetamiprid at lowest operating cost in lesser time. A kinetic model was developed for photo-Fenton process using the elementary reaction data and mass balance equations for the species involved in the process. Variation of acetamiprid concentration with time for different H2O2 and Fe2+ concentration at pH 3 can be found out using this model. The model was validated by comparing the simulated concentration profiles with that obtained from experiments. This study established the viability of the selected AOPs for the removal of acetamiprid from wastewater. Of the studied AOPs photo- Fenton gives the highest removal efficiency with lowest operating cost within shortest time. |
| Description: | Division of Safety and Fire Engineering, School of Engineering |
| URI: | http://dyuthi.cusat.ac.in/purl/5023 |
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| Dyuthi-2089.pdf | (4.491Mb) |
| Abstract: | Leachate from an untreated landfill or landfill with damaged liners will cause the pollution of soil and ground water. Here an attempt was made to generate knowledge on concentrations of all relevant pollutants in soil due to municipal solid waste landfill leachate and its migration through soil and also to study the effect of leachate on the engineering properties of soil. To identify the pollutants in soil due to the leachate generated from municipal solid waste landfill site, a case study on an unlined municipal solid waste landfill at Kalamassery has been done. Soil samples as well as water samples were collected from the site and analysed to identify the pollutants and its effect on soil characteristics. The major chemicals in the soil were identified as Ammonia, Chloride, Nitrate, Iron, Nickel, Chromium, Cadmium etc.. Engineering properties of field soil samples show that the chemicals from the leachate of landfill may have effect on the engineering properties of soil. Laboratory experiments were formulated to model the field around an unlined MSW landfill using two different soils subjected to a synthetic leachate. The Maximum change in chemical concentration and engineering property was observed on soil samples at a radial distance of 0.2 m and at a depth of 0.3 m. The pollutant (chemicals) transport pattern through the soil was also studied using synthetic leachate. To establish the effect of pollutants (chemicals) on engineering properties of soil, experiments were conducted on two types soils treated with the synthetic chemicals at four different concentrations. Analyses were conducted after maturing periods of 7, 50, 100 and 150 days. Test soils treated with maximum chemical concentration and matured for 150 days were showing major change in the properties. To visualize the flow of pollutants through soil in a broader sense, the transportation of pollutants through soil was modeled using software ‘Visual MODFLOW’. The actual field data collected for the case study was used to calibrate the modelling and thus simulated the flow pattern of the pollutants through soil around Kalamassery municipal solid waste landfill for an extent of 4 km2. Flow was analysed for a time span of 30 years in which the landfill was closed after 20 years. The concentration of leachate beneath the landfill was observed to be reduced considerably within one year after closure of landfill and within 8 years, it gets lowered to a negligible level. As an environmensstal management measure to control the pollution through leachate, permeable reactive barriers are used as an emerging technology. Here the suitability of locally available materials like coir pith, rice husk and sugar cane bagasse were investigated as reactive media in permeable reactive barrier. The test results illustrates that, among these, coir pith was showing better performance with maximum percentage reduction in concentration of the filtrate. All these three agricultural wastes can be effectively utilized as a reactive material. This research establishes the influence of leachate of municipal solid waste landfill on the engineering properties of soil. The factors such as type of the soil, composition of leachate, infiltration rate, aquifers, ground water table etc., will have a major role on the area of influence zone of the pollutants in a landfill. Software models of the landfill area can be used to predict the extent and the time span of pollution of a landfill, by inputting the accurate field parameters and leachate characteristics. The present study throws light on the role of agro waste materials on the reduction of the pollution in leachate and thus prevents the groundwater and soil from contamination |
| URI: | http://dyuthi.cusat.ac.in/purl/4948 |
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| Dyuthi-T2024.pdf | (11.45Mb) |
| URI: | http://dyuthi.cusat.ac.in/purl/5394 |
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| Dyuthi T-2430.pdf | (11.71Mb) |
| Abstract: | The present study aimed at critically looking at the current practice of the installation of compacted clay liner using bentonite enhanced sand (BES). The application of bentonite is currently the most accepted practice for lining purposes. The ideal bentonite sand combination, which satisfies the liner requirements is 20% bentonite and 80% sand, was selected as one of the liner materials for the investigation of development of desiccation cracks. Locally available sundried marine clay and its combination with bentonite were also included in the study. The desiccation tests on liner materials were conducted for wet/dry cycles to simulate the seasonal variations. Digital image processing techniques were used to measure the crack intensity factor (CIF), a useful and effective parameter for quantification of desiccation cracking. The repeatability of the tests could be well established, as the variation in CIF values of identical samples had a very narrow range of 0 to 2%. The studies on the development of desiccation cracks showed that the CIF of bentonite enhanced sand mixture (BES) was 18.09%, 39.75% and 21.22% for the first, second and third cycles respectively, while it was only 9.83%, 7.52% and 4.58% respectively for sun dried marine clay (SMC). Thus the locally available, alternate liner material suggested, viz SMC, is far superior to BES, when subjected to alternate wet/dry cycles. Further, the improvement of these liner materials when amended with randomly distributed fibre reinforcements was also investigated. Three types of fibres ,namely nylon fibre, polypropylene monofilament and polypropylene fibre mesh were used for the study of fibre amended BES and SMC.The influence of these amendments on the properties of the above liner materials is also studied. The results showed that there is definite improvement in the properties of the liner materials when it is reinforced with discrete random fibres. The study also proved that the desiccation cracks could be controlled with the help of fibre reinforcement. |
| Description: | School of Engineering, Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/xmlui/purl/1944 |
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| Dyuthi-T0471.pdf | (9.205Mb) |
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