Modeling of Breakdown voltage of Solid Insulating Materials Using Soft Computing Techniques

The voids or cavities within the solid insulating material during manufacturing are potential sources of electrical trees which can lead to continuous degradation and breakdown of insulating material due to Partial Discharge (PD). To determine the suitability of use and acquire the data for the dimensioning of electrical insulation systems breakdown voltage of insulator should be determined. A major field of Artificial Neural Networks (ANN) and Least Square Support Vector Machine (LS-SVM) application is function estimation due to its useful features, they are, non-linearity and adaptively. In this project, the breakdown voltage due to PD in cavities for five insulating materials under AC conditions has been predicted as a function of different input parameters, such as, the insulating sample thickness ‘t,’ the thickness of the void ‘t1’ diameter of the void ‘d’ and relative permittivity of materials by using two different models. The requisite training data are obtained from experimental studies performed on a Cylinder-Plane Electrode system. Different dimensioned voids are artificially created.. On completion of training, it is found that the ANN and LS-SVM models are capable of predicting the breakdown voltage Vb = f (t, t1, d, ) very efficiently and with a small value of Mean Absolute Error. The system has been predicted using MATLAB

Separation of Carboxylic Acids From Aqueous Fraction of Fast Pyrolysis Bio-Oils Using Nanofiltration and Reverse Osmosis Membranes

There has been a growing interest in renewable sources of energy due to an increase in demand and potential shortages and environmental problems associated with fossil fuels. Bio-oils, complex liquid fuels produced from fast pyrolysis of biomass, have been recognized as one potential source of renewable energy. However, they cannot be utilized directly due to their high viscosity, corrosiveness, and high char content. Bio-oils readily phase separate into aqueous phase and organic phase upon addition of water. The aqueous fraction of bio oil (AFBO) is convenient to process and contains sugars, organic acids, hydroxyacetone, hydroxyacetaldehyde, furfural, phenols and other organic species that can potentially be converted to hydrogen, alkanes, aromatics, or olefins. However, the acidity of AFBO (pH ~2.5) is relatively high due to the presence of organic acids which can impose more demands on construction equipment of the vessels and the upgrading process. Removal of acids is essential to use AFBO as a commercial fuel or further upgrading into fuels or chemicals. Traditional separation techniques for the removal of acids from AFBO, like ion exchange and distillation are not attractive due to practical limitations. Membrane-based separations have been increasingly employed due to their inherent advantages over conventional separations methods. Pressure driven membrane processes like nanofiltration (NF) and reverse osmosis (RO) have been used in chemical, electronics, textile, petrochemical, pulp and paper, and food industries as well as for the treatment of municipal wastewater and landfill leachates. However, these processes are targeted for aqueous systems containing little or no organic solvents. The use of membranes to separate organic solvent solutions or organic-rich aqueous solutions is still at a very early stage. The feasibility of removing small organic acids from the AFBO using NF and RO membranes was studied. Experiments were conducted with commercially available polymeric NF and RO membranes and aqueous solutions of increasing complexity, i.e. single solute solutions of acetic acid and glucose, binary solute solutions containing both acetic acid and glucose, and a model AFBO containing acetic acid, glucose, formic acid, hydroxyacetone, furfural, guaiacol, and catechol. Feed concentrations (up to 34 % solute by weight) close to those in real AFBO were chosen. These were generally at least an order of magnitude higher than previously studied in the literature for related membrane separations. Retention factors for single and binary solutions of acetic acid and glucose were promising so that the separation was expected to be feasible. However, all the membranes were irreversibly damaged when experiments were conducted with the model AFBO due to the presence of guaiacol in the feed solution. Experiments with model AFBO excluding guaiacol were also conducted. NF membranes showed retention factors of glucose greater than 80% and of acetic acid less than -15% when operated at transmembrane pressures near 60 bar. Finally, the solution-diffusion (SD) model was applied to predict the permeate flux and solute retention and compared to the experimental results. In another study, we explored the potential of nanocomposite membranes in gas separations. Solubility based membrane gas separation, in which the more soluble (and perhaps slower-diffusing) species preferentially permeates through the membranes, has received considerable attention due to both economic and environmental concerns. In this work, we synthesized organic-inorganic nanocomposite membranes by decorating the surfaces of commercially available alumina substrates with a selective organic material that is physically or chemically anchored to the porous surfaces. Hyperbranched melamine-based dendrimers and polydimethylsiloxane (PDMS) were used as filling agents. Separation factors for propane/nitrogen and carbon dioxide/methane were obtained for modified membranes. The separation performance of PDMS-alumina composite membranes was comparable to the currently best known polymers being used for this type of application