Recyclable Short Fibre Reinforced Plastics PP/Nylon and HDPE/Nylon composites

The study shows that standard plastics like polypropylene and high density polyethylene can be reinforced by adding nylon short fibres. Compared to the conventional glass reinforced thermoplastics this novel class of reinforced thermoplastics has the major advantage of recyclability. Hence such composites represent a new spectrum of recyclable polymer composites. The fibre length and fibre diameter used for reinforcement are critical parameters While there is a critical fibre length below which no effective reinforcement takes place, the reinforcement improves when the fibre diameter decreases due to increased surface area.While the fibres alone give moderate reinforcement, chemical modification of the matrix can further improve the strength and modulus of the composites. Maleic anhydride grafting in presence of styrene was found to be the most efficient chemical modification. While the fibre addition enhances the viscosity of the melt at lower shear rates, the enhancement at higher shear rate is only marginal. This shows that processing of the composite can be done in a similar way to that of the matrix polymer in high shear operations such as injection moulding. Another significant observation is the decrease in melt viscosity of the composite upon grafting. Thus chemical modification of matrix makes processing of the composite easier in addition to improving the mechanical load bearing capacity.For the development of a useful short fibre composite, selection of proper materials, optimum design with regard to the particular product and choosing proper processing parameters are most essential. Since there is a co-influence of many parameters, analytical solutions are difficult. Hence for selecting proper processing parameters 'rnold flow' software was utilized. The orientation of the fibres, mechanical properties, temperature profile, shrinkage, fill time etc. were determined using the software.Another interesting feature of the nylon fibre/PP and nylon fibre/HDPE composites is their thermal behaviour. Both nylon and PP degrade at the same temperature in single steps and hence the thermal degradation behaviour of the composites is also being predictable. It is observed that the thermal behaviour of the matrix or reinforcement does not affect each other. Almost similar behaviour is observed in the case of nylon fibre/HDPE composites. Another equally significant factor is the nucleating effect of nylon fibre when the composite melt cools down. In the presence of the fibre the onset of crystallization occurs at slightly higher temperature.When the matrix is modified by grafting, the onset of crystallization occurs at still higher temperature. Hence it may be calculated that one reason for the improvement in mechanical behaviour of the composite is the difference in crystallization behaviour of the matrix in presence of the fibre.As mentioned earlier, a major advantage of these composites is their recyclability. Two basic approaches may be employed for recycling namely, low temperature recycling and high temperature recycling. In the low temperature recycling, the recycling is done at a temperature above the melting point of the matrix, but below that of the fibres while in the high temperature route. the recycling is done at a temperature above the melting points of both matrix and fibre. The former is particularly interesting in that the recycled material has equal or even better mechanical properties compared to the initial product. This is possible because the orientation of the fibre can improve with successive recycling. Hence such recycled composites can be used for the same applications for which the original composite was developed. In high temperature recycling, the composite is converted into a blend and hence the properties will be inferior to that of the original composite, but will be higher than that of the matrix material alone.

Studies on the fracture behaviour of polymer blends with special reference to PP/HDPE and PS/HIPS blends

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.

A Comparative Study Of Tensile And Microstructural Characteristics Of Friction Welded Joints And Conventionally Welded Joints Of Aluminium Alloy 6061

Welding of high strength and low weight materials like Aluminium Alloys without any defects by conventional welding techniques is a major challenge in industries. Hence research on solid state welding techniques like Friction stir welding and Friction welding techniques have got much importance in joining of Aluminium alloys. However most of the industries are not changing conventional techniques as skilled workers are available on that area. Most common conventional welding techniques used for joining of Aluminium alloys are Gas welding and Arc welding. Friction welding is a solid-state welding process that generates heat through mechanical friction between a moving and a stationary component with the addition of a lateral force called “upset” to plast ically displace and fuse the materials. In this work, experimental study on tensile and micro structural characteristics of welded joints formed from conventional welding techniques and Rotary friction welding(suitable for weld specimens with circular cross section) has been carried out and the same were compared. The process parameters for arc welding used was 50-70 Amp reverse polarity DC and electrodes of 2.3mm diameter. In Gas welding, the parameters were oxy acetylene neural flame at 3200°C and 3mm electrodes . In the case of friction welding an axial pressure loading of 3Mpa with 5 MPa as upsetting pressure and 500 rpm were used to obtain good welded joints. Tensile characteristic studies of Arc welded joints and Gas welded joints showed 48% and 60 % variations respectively from the maximum load bearing characteristics of parent metal. In the case of friction welded joint, the variation was found to 46%. Micro structural evaluation of conventionally welded joints exhibited clear distinct zones of various weld regions. In the case of friction welded joint micro structural photographs showed comparable features both in parent metal and welded region. Thus the tensile characteristic study and microstructure evaluations proved that friction welded joints are good in both aspects compared to conventionally welded joints.

Modification of Polypropylene/High Density Polyethylene Blend Using Nanokaolinite Clay and E-Glass Fibre: Preparation, Characterization and Micromechanical Modelling

Upgrading two widely used standard plastics, polypropylene (PP) and high density polyethylene (HDPE), and generating a variety of useful engineering materials based on these blends have been the main objective of this study. Upgradation was effected by using nanomodifiers and/or fibrous modifiers. PP and HDPE were selected for modification due to their attractive inherent properties and wide spectrum of use. Blending is the engineered method of producing new materials with tailor made properties. It has the advantages of both the materials. PP has high tensile and flexural strength and the HDPE acts as an impact modifier in the resultant blend. Hence an optimized blend of PP and HDPE was selected as the matrix material for upgradation. Nanokaolinite clay and E-glass fibre were chosen for modifying PP/HDPE blend. As the first stage of the work, the mechanical, thermal, morphological, rheological, dynamic mechanical and crystallization characteristics of the polymer nanocomposites prepared with PP/HDPE blend and different surface modified nanokaolinite clay were analyzed. As the second stage of the work, the effect of simultaneous inclusion of nanokaolinite clay (both N100A and N100) and short glass fibres are investigated. The presence of nanofiller has increased the properties of hybrid composites to a greater extent than micro composites. As the last stage, micromechanical modeling of both nano and hybrid A composite is carried out to analyze the behavior of the composite under load bearing conditions. These theoretical analyses indicate that the polymer-nanoclay interfacial characteristics partially converge to a state of perfect interfacial bonding (Takayanagi model) with an iso-stress (Reuss IROM) response. In the case of hybrid composites the experimental data follows the trend of Halpin-Tsai model. This implies that matrix and filler experience varying amount of strain and interfacial adhesion between filler and matrix and also between the two fillers which play a vital role in determining the modulus of the hybrid composites.A significant observation from this study is that the requirement of higher fibre loading for efficient reinforcement of polymers can be substantially reduced by the presence of nanofiller together with much lower fibre content in the composite. Hybrid composites with both nanokaolinite clay and micron sized E-glass fibre as reinforcements in PP/HDPE matrix will generate a novel class of high performance, cost effective engineering material.

Short-Term Load Forecast Of A Low Loadfactor Power System For Optimization Of Merit Order Dispatch Using Adaptive Learning Algorithm

Short term load forecasting is one of the key inputs to optimize the management of power system. Almost 60-65% of revenue expenditure of a distribution company is against power purchase. Cost of power depends on source of power. Hence any optimization strategy involves optimization in scheduling power from various sources. As the scheduling involves many technical and commercial considerations and constraints, the efficiency in scheduling depends on the accuracy of load forecast. Load forecasting is a topic much visited in research world and a number of papers using different techniques are already presented. The accuracy of forecast for the purpose of merit order dispatch decisions depends on the extent of the permissible variation in generation limits. For a system with low load factor, the peak and the off peak trough are prominent and the forecast should be able to identify these points to more accuracy rather than minimizing the error in the energy content. In this paper an attempt is made to apply Artificial Neural Network (ANN) with supervised learning based approach to make short term load forecasting for a power system with comparatively low load factor. Such power systems are usual in tropical areas with concentrated rainy season for a considerable period of the year

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.

An Alternative Approach To Computer System Security Monitoring And Enhancement Through System Call Sequence Analysis

Modern computer systems are plagued with stability and security problems: applications lose data, web servers are hacked, and systems crash under heavy load. Many of these problems or anomalies arise from rare program behavior caused by attacks or errors. A substantial percentage of the web-based attacks are due to buffer overflows. Many methods have been devised to detect and prevent anomalous situations that arise from buffer overflows. The current state-of-art of anomaly detection systems is relatively primitive and mainly depend on static code checking to take care of buffer overflow attacks. For protection, Stack Guards and I-leap Guards are also used in wide varieties.This dissertation proposes an anomaly detection system, based on frequencies of system calls in the system call trace. System call traces represented as frequency sequences are profiled using sequence sets. A sequence set is identified by the starting sequence and frequencies of specific system calls. The deviations of the current input sequence from the corresponding normal profile in the frequency pattern of system calls is computed and expressed as an anomaly score. A simple Bayesian model is used for an accurate detection.Experimental results are reported which show that frequency of system calls represented using sequence sets, captures the normal behavior of programs under normal conditions of usage. This captured behavior allows the system to detect anomalies with a low rate of false positives. Data are presented which show that Bayesian Network on frequency variations responds effectively to induced buffer overflows. It can also help administrators to detect deviations in program flow introduced due to errors.

Toxic Metal Distribution in the Core Sediment of Cochin Estuarine System (CES)

This article present the result from a study of two sediment cores collected from the environmentally distinct zones of CES. Accumulation status of five toxic metals: Cadmium (Cd), Chromium (Cr), Cobalt (Co), Copper (Cu) and Lead (Pb) were analyzed. Besides texture and CHNS were determined to understand the composition of the sediment. Enrichment Factor (EF) and Anthropogenic Factor (AF) were used to differentiate the typical metal sources. Metal enrichment in the cores revealed heavy load at the northern (NS1 ) region compared with the southern zone (SS1). Elevation of metal content in core NS1 showed the industrial input. Statistical analyses were employed to understand the origin of metals in the sediment samples. Principal Component Analysis (PCA) distinguishes the two zones with different metal accumulation capacity: highest at NS1 and lowest at SS1. Correlation analysis revealed positive significant relation only in core NS1, adhering to the exposition of the intensified industrial pollution