| Abstract: | Modeling of chaotic systems, based on the output time series, is quite promising since the output often represents the characteristic behaviour of the total system. It has been an interesting topic for researchers over the past few years. So far, some methods are developed for the identification of chaotic systems. Because of the intense complexity of chaotic systems, the performance of existing algorithms is not always satisfactory. Application of chaotic system theory to socially relevant problems like environmental studies is the need of the hour Neural networks have the required self-learning capability to tune the network parameters (i.e. weights) for identifying highly non-linear and chaotic systems. In the present work, effectiveness of modeling a chaotic system using dynamic neural networks has been demonstrated. From the rich literature available for non-linear modeling with neural networks, the Recurrent Neural Network (RNN) structure is selected. The Extended Kalman Filter (EKF) algorithm is used to train the RNN. Further, the Expectation Maximization algorithm is used to effectively arrive at the initial states and the state covariance. Particle filter algorithm with its two important variants namely Sampling Importance Resampling (SIR) and Rao Blackwellised algorithms are also used for training the given RNN. Four standard chaotic systems, Lorenz, Rossler, Chua and Chen, are modelled with the three algorithms. The best algorithm is found to be EKF-EM based on the least mean square error criterion. Validation of RNN model with EKFEM algorithm is done in time domain by Estimation of embedding dimension, Phase plots, Lyapunov Exponents, Kaplan -Yorke dimension and Bifurcation diagrams. Analysis of the chaotic systems is also performed in the transform domain using Fourier, Wavelet and Mapped Real Transforms. viii Natural chaotic systems are analyzed based on the selected model structure and training algorithm, taken for analysis. Sunspot, Venice Lagoon and North Atlantic oscillations are the three of the natural chaotic systems modelled with the selected RNN model structure and EKF-EM algorithm. |
| URI: | http://dyuthi.cusat.ac.in/purl/5162 |
| Files | Size |
|---|---|
| Dyuthi-T2196.pdf | (6.188Mb) |
| 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 |
| Files | Size |
|---|---|
| Dyuthi-T2195.pdf | (5.865Mb) |
| Abstract: | Electrocardiogram gives the information regarding the health of the patients by monitoring the bioelectric potentials generated by the sinoatrial node in the heart. These signals can be collected by using electrodes suitably placed on the body of a patient. The normal human ECG lie in the frequency range of 0.05-100 Hz and the most useful information is contained in the range of 0.5-45 Hz. Even though a large amount of work has already been done in the field of ECG classification, no classification system has made an attempt in identifying the isolated abnormalities which pose a silent threat to patients. An adaptive filtering technique for denoising the ECG which is based on Genetic Algorithm (GA) tuned Sign-Data Least Mean Square (SD-LMS) algorithm is proposed. This algorithm gave an average signal to noise ratio improvement of 10.75 dB for baseline wander and 24.26 dB for power line interference. It is seen that the step size ‘μ’ optimized with GA helps in obtaining better SNR value without causing any damage to the information content in the ECG. A new wavelet for automatic classification of arrhythmias from electrocardiogram is proposed. This new wavelet is formed as a sum of shifted Gaussians so that it resembles a normal ECG. This shape has been chosen with the aim of extracting maximum information from the ECG under analysis. The classification performance was studied using the most commonly used database, the MIT-BIH Arrhythmia database. The shifted and summed Gaussian wavelet was then optimized using GA. The optimum wavelet for classification was obtained after several runs of the GA algorithm. The ECG class labeling was done according to the Association for the Advancement of Medical Instrumentation (AAMI). The wavelet scales corresponding to the different frequency levels giving maximum classification performance were identified by selecting finer scales. Probabilistic Neural Network classifier was used for classification purpose. The proposed classification system offered better results than that reported in literature by giving an overall sensitivity of 97.01% for Normal beats, 75.20% for Supraventricular beats and 93.06% for Ventricular beats. As mentioned above this technique could exclusively identify some of the isolated abnormalities present in the patient records. |
| URI: | http://dyuthi.cusat.ac.in/purl/5143 |
| Files | Size |
|---|---|
| Dyuthi-T2177.pdf | (4.847Mb) |
| Abstract: | Production Planning and Control (PPC) systems have grown and changed because of the developments in planning tools and models as well as the use of computers and information systems in this area. Though so much is available in research journals, practice of PPC is lagging behind and does not use much from published research. The practices of PPC in SMEs lag behind because of many reasons, which need to be explored. This research work deals with the effect of identified variables such as forecasting, planning and control methods adopted, demographics of the key person, standardization practices followed, effect of training, learning and IT usage on firm performance. A model and framework has been developed based on literature. Empirical testing of the model has been done after collecting data using a questionnaire schedule administered among the selected respondents from Small and Medium Enterprises (SMEs) in India. Final data included 382 responses. Hypotheses linking SME performance with the use of forecasting, planning and controlling were formed and tested. Exploratory factor analysis was used for data reduction and for identifying the factor structure. High and low performing firms were classified using a Logistic Regression model. A confirmatory factor analysis was used to study the structural relationship between firm performance and dependent variables. |
| URI: | http://dyuthi.cusat.ac.in/purl/5105 |
| Files | Size |
|---|---|
| Dyuthi-T 2171.pdf | (2.649Mb) |
| Abstract: | The hazards associated with major accident hazard (MAH) industries are fire, explosion and toxic gas releases. Of these, toxic gas release is the worst as it has the potential to cause extensive fatalities. Qualitative and quantitative hazard analyses are essential for the identitication and quantification of the hazards associated with chemical industries. This research work presents the results of a consequence analysis carried out to assess the damage potential of the hazardous material storages in an industrial area of central Kerala, India. A survey carried out in the major accident hazard (MAH) units in the industrial belt revealed that the major hazardous chemicals stored by the various industrial units are ammonia, chlorine, benzene, naphtha, cyclohexane, cyclohexanone and LPG. The damage potential of the above chemicals is assessed using consequence modelling. Modelling of pool fires for naphtha, cyclohexane, cyclohexanone, benzene and ammonia are carried out using TNO model. Vapor cloud explosion (VCE) modelling of LPG, cyclohexane and benzene are carried out using TNT equivalent model. Boiling liquid expanding vapor explosion (BLEVE) modelling of LPG is also carried out. Dispersion modelling of toxic chemicals like chlorine, ammonia and benzene is carried out using the ALOHA air quality model. Threat zones for different hazardous storages are estimated based on the consequence modelling. The distance covered by the threat zone was found to be maximum for chlorine release from a chlor-alkali industry located in the area. The results of consequence modelling are useful for the estimation of individual risk and societal risk in the above industrial area.Vulnerability assessment is carried out using probit functions for toxic, thermal and pressure loads. Individual and societal risks are also estimated at different locations. Mapping of threat zones due to different incident outcome cases from different MAH industries is done with the help of Are GIS.Fault Tree Analysis (FTA) is an established technique for hazard evaluation. This technique has the advantage of being both qualitative and quantitative, if the probabilities and frequencies of the basic events are known. However it is often difficult to estimate precisely the failure probability of the components due to insufficient data or vague characteristics of the basic event. It has been reported that availability of the failure probability data pertaining to local conditions is surprisingly limited in India. This thesis outlines the generation of failure probability values of the basic events that lead to the release of chlorine from the storage and filling facility of a major chlor-alkali industry located in the area using expert elicitation and proven fuzzy logic. Sensitivity analysis has been done to evaluate the percentage contribution of each basic event that could lead to chlorine release. Two dimensional fuzzy fault tree analysis (TDFFTA) has been proposed for balancing the hesitation factor invo1ved in expert elicitation . |
| Description: | Division of Safety and Fire Engineering, School of Engineering, Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/2650 |
| Files | Size |
|---|---|
| Dyuthi-T0710.pdf | (2.149Mb) |
| Abstract: | The thesis presented here unveils an experimental study of the hydrodynamic characteristics of swirling fluidized bed viz. pressure drop across the distributor and the bed, minimum fluidizing velocity, bed behaviour and angle of air injection. In swirling fluidized bed the air is admitted to the bed at an angle 'Ѳ' to the horizontal. The vertical component of the velocity v sin Ѳ causes fluidization and the horizontal component v cos Ѳ contributes to swirl motion of the bed material.The study was conducted using spherical particles having sizes 3.2 mm, 5.5 mm & 7.4 mm as the bed materials. Each of these particles was made from high density polyethylene, nylon and acetal having relative densities of 0.93, 1.05 and 1.47 respectively.The experiments were conducted using conidour type distributors having four rows of slits. Altogether four distributors having angles of air injection (Φ)- 0°, 5°, 10° & 15° were designed and fabricated for the study. The total number of slits in each distributor was 144. The area of opening was 6220 mm2 making the percentage area of opening to 9.17. But the percentage useful area of opening of the distributor was 96.The experiments on the variation of distributor pressure drop with superficial velocity revealed that the distributor pressure drop decreases with angle of air injection. Investigations related to bed hydrodynamics were conducted using 2.5 kg of bed material. The bed pressure drop measurements were made along the radial direction of the distributor at distances of 60 mm, 90 mm, 120 mm & 150 mm from the centre of the distributor. It was noticed that after attaining minimum fluidizing velocity, the bed pressure drop increases along the radial direction of the distributor. But at a radial distance of 90 mm from the distributor centre, after attaining minimum fluidizing velocity the bed pressure drop remains almost constant. It was also observed that the bed pressure drop varies inversely with particle size as well as particle density.An attempt was made to determine the effect of various parameters on minimum fluidizing velocity. It was noticed that the minimum fluidizing velocity varies directly with angle of air injection (Φ), particle size and particle density.The study on the bed behaviour showed that the superficial velocity required for initiating various bed phenomena (such as swirl motion and separation of particles from the cone at the centre) increase with increase in particle size as well as particle density. It was also observed that the particle size and particle density directly influence the superficial velocity required for various regimes of bed behaviour such as linear variation of bed pressure drop, constant bed pressure drop and sudden increase or decrease in bed pressure drop.Experiments were also performed to study the effect of angle of air injection (Φ). It was noticed that the bed pressure drop decreases with angle of air injection. It was also noticed that the angle of air injection directly influence the superficial velocity required for initiating various bed phenomena as well as the various regimes of bed behaviour. |
| Description: | Division of Mechanical Engineering, Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/2626 |
| Files | Size |
|---|---|
| Dyuthi-T0705.pdf | (9.679Mb) |
| Abstract: | Investigations on the fracture behaviour of polymer blends is the topic of this thesis. The blends selected are PP/HDPE and PS/HIPS. PP/HDPE blend is chosen due to its commercial importance and PS/HIPS blend is selected to study the transition from brittle fracture to ductile fracture.PP/HDPE blends were prepared at different compositions by melt blending at 180°C and fracture failure process was investigated by conducting notch sensitivity test and tensile test at different strain rates. The effects of two types of modifiers (particulate and elastomer) on the fracture behaviour and notch sensitivity of PP/HDPE blends were studied. The modifiers used are calcium carbonate, a hard particulate filler commonly used in plastics and Ethylene Propylene Diene Monomer (EPDM). They were added in 2%, 4% and 6% by weight of the blends.The study shows that the mechanical properties of PP/HDPE blends can be optimized by selecting proper blend compositions. The selected modifiers are found to alter and improve the fracture behaviour and notch sensitivity of the blends. Particulate fillers like calcium carbonate can be used for making the mechanical behaviour more stable at the various blend compositions. The resistance to notch sensitivity of the blends is found to be marginally lower in the presence of calcium carbonate. The elastomeric modifier EPDM produces a better stability of the mechanical behaviour. A low concentration of EPDM is sufficient to effect such a change. EPDM significantly improves the resistance to notch sensitivity of the blends. The study shows that judicious selection of modifiers can improve the fracture behaviour and notch sensitivity of PP/HDPE blends and help these materials to be used for critical applications.For investigating the transition in fracture behaviour and failure modes, PS/HIPS blends were selected. The blends were prepared by melt mixing followed by injection moulding to prepare the specimens for conducting tensile, impact and flexure tests. These tests were used to simulate the various conditions which promote failure.The tensile behaviour of unnotched and notched PS/HIPS blend samples were evaluated at slow speeds. Tensile strengths and moduli were found to increase at the higher testing speed for all the blend combinations whereas maximum strain at break was found to decrease. For a particular speed of testing, the tensile strength and modulus show only a very slight decrease as HIPS content is increased up to about 40%. However, there is a drastic decrease on increasing the HIPS content thereafter.The maximum strain at break shows only a very slight change up to about 40% HIPS content and thereafter shows a remarkable increase. The notched specimens also follow a comparable trend even though the notch sensitivity is seen high for PS rich blends containing up to 40% HIPS. The notch sensitivity marginally decreases with increase in HIPS content. At the same time, it is found to increase with the increase in strain rate. It is observed that blends containing more than 40% HIPS fail in ductile mode.The impact characteristics of PSIHIPS blends studied were impact strength, the energy absorbed by the test specimen and impact toughness. Remarkable increase in impact strength is observed as HIPS content in the blend exceeds 40%. The energy absorbed by the test specimens and the impact toughness also show a comparable trend.Flexural testing which helps to characterize the load bearing capacity was conducted on PS/HIPS blend samples at the two different testing speeds of 5mmlmin and 10 mm/min. The flexural strength increases with increase in testing speed for all the blend compositions. At both the speeds, remarkable reduction in flexural strength is observed as HIPS content in the blend exceeds 40%. The flexural strain and flexural energy absorbed by the specimens are found to increase with increase in HIPS content. At both the testing speeds, brittle fracture is observed for PS rich blends whereas HIPS rich blends show ductile mode of failure.Photoelastic investigations were conducted on PS/HIPS blend samples to analyze their failure modes. A plane polariscope with a broad source of light was utilized for the study. The coloured isochromatic fringes formed indicate the presence of residual stress concentration in the blend samples. The coverage made by the fringes on the test specimens varies with the blend composition and it shows a reducing trend with the increase in HIPS content. This indicates that the presence of residual stress is a contributing factor leading to brittle fracture in PS rich blends and this tendency gradually falls with increase in HIPS content and leads to their ductile mode of failure. |
| Description: | School of Engineering, Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/2625 |
| Files | Size |
|---|---|
| Dyuthi-T0704.pdf | (5.609Mb) |
| Abstract: | Soil moisture plays a cardinal role in sustaining eclological balance and agricultural development – virtually the very existence of life on earth. Because of the growing shortage of water resources, we have to use the available water most efficiently by proper management. Better utilization of rainfall or irrigation management depends largely on the water retention characteristics of the soil.Soil water retention is essential to life and it provides an ongoing supply of water to plants between periods of irrigation so as to allow their continued growth and survival.It is essential to maintain readily available water in the soil if crops are to sustain satisfactory growth. The plant growth may be retarded if the soil moisture is either deficient or excessive. The optimum moisture content is that moisture which leads to optimum growth of plant. When watering is done, the amount of water supplied should be such that the water content is equal to the field capacity that is the water remained in the saturated soil after gravitational drainage. Water will gradually be utilized consumptively by plants after the water application, and the soil moisture will start falling. When the water content in the soil reaches the value known as permanent wilting point (when the plant starts wilting) fresh dose of irrigation may be done so that water content is again raised to the field capacity of soil.Soil differ themselves in some or all the properties depending on the difference in the geotechnical and environmental factors. Soils serve as a reservoir of the nutrients and water required for crops.Study of soil and its water holding capacity is essential for the efficient utilization of irrigation water. Hence the identification of the geotechnical parameters which influence the water retention capacity, chemical properties which influence the nutrients and the method to improve these properties have vital importance in irrigation / agricultural engineering. An attempt in this direction has been made in this study by conducting the required tests on different types of soil samples collected from various locations in Trivandrum district Kerala, with and without admixtures like coir pith, coir pith compost and vermi compost. Evaluation of the results are presented and a design procedure has been proposed for a better irrigation scheduling and management. |
| Description: | Division of Civil Engineering, Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/2361 |
| Files | Size |
|---|---|
| Dyuthi-T0633.pdf | (5.314Mb) |
| Description: | Faculty of Engineering. Cochin University of Science and Technology |
| URI: | http://dyuthi.cusat.ac.in/purl/2358 |
| Files | Size |
|---|---|
| Dyuthi-T0630.pdf | (3.053Mb) |
Dyuthi Digital Repository Copyright © 2007-2011 Cochin University of Science and Technology. Items in Dyuthi are protected by copyright, with all rights reserved, unless otherwise indicated.