Optimum supply for an inverter-fed cage induction motor at different load conditions

The effects of power supply on the energy efficiency of a form-wound cage induction motor are studied when the motor operates under light loads. The cage induction motor is modelled with the space and time discretized finite-element analysis. The resistive losses are taken into account accurately by modelling eddy currents in the form-wound multi-conductor stator winding and the rotor cage. The core losses are considered with conventional empirical equations. A pulse-width-modulated (PWM) voltage is used to supply the motor. The fundamental harmonic (FH) terminal voltage is decreased from its rated value and the slip is adjusted to achieve a particular load condition. The variation of the total electromagnetic as well as the stator resistive losses are analyzed to find the optimum supply.reviewe

Modelling and Multi-objective Optimization of Continuous Protein Recovery in Liquid-Solid Circulating Fluidized Bed (LSCFB)

In recent years, liquid-solid circulating fluidized beds (LSCFBs) are being applied as a reactor system in a number of new applications. This study focused on the modelling and multi-objective optimization of LSCFB system for continuous protein recovery process. A mathematical model was developed considering the protein adsorption and desorption characteristics, liquid-solid mass transfer and the hydrodynamics of the LSCFB, to predict the protein adsorption and desorption performance of the LSCFB system. The simulation results showed good agreement with available experimental data. Parametric sensitivity analysis showed complex interplay of various operational parameters over the system performance indicators. Moreover, the change in operating conditions in one column affects the performance of the other column as the two columns are interlinked. Multi-objective optimization of the LSCFB system at both the operation and the design stage were carried out using the model developed to determine the range of optimal solutions. Elitist nondominate sorting genetic algorithm with its jumping gene adaptation (NSGA-II-aJG) was used to solve a number of two- and three- objective function optimization problems. The optimization resulted in Pareto optimal solutions, which provides a broad range of non-dominated solutions due to conflicting behaviour of the operating and design parameters on the system performance indicators such as the protein production rate, the percent recovery and the amount of ion exchange particles required. Significant improvements were achieved, for example, for the same recovery level, the production rate at optimal operation increased by 33%, using 11% less solids compared to experimental results. In the design stage optimization, the performance of the system was further improved. This modelling and multi-objective optimization study is very general and can be easily extended for the improvement of LSCFB in other applications

Steam Gasification of Biomass Surrogates: Catalyst Development and Kinetic Modelling

This study reports a new fluidizable La2O3 promoted Ni/γ-Al2O3 catalyst. Prepared catalysts are characterized using BET specific surface area, XRD, TPR, TPO, H2-pulse chemisorptions, Pyridine FTIR, NH3-TPD and CO2-TPD. Catalytic steam gasification of biomass surrogates (glucose and 2-methoxy-4-methylphenol) are conducted in a CREC Riser Simulator under the expected conditions of a twin circulating fludized bed gasifier. Catalyst structure-property and structure-reactivity relationships are established using characterization and gasification results. Gasification performance of a catalyst is found to be well-correlated as a function of its Ni dispersion and basicity/acidity ratio. It is hypothesized that acid sites of γ-Al2O3 are responsible for coke deposition via hydrocarbon cracking, whereas basic sites facilitated coke reforming. The relative proportion of octahedral and tetrahedral sites in γ-Al2O3, which is a main determinant of metal-support interaction and acid-base properties, is assessed using H2 TPR and NH3-TPD. A 20% Ni/5% La2O3-γAl2O3 catalyst is developed, in this study, optimizing catalyst formulation and preparation conditions. This catalyst yields a 98.3% carbon conversion of glucose to permanent gases with no tar formation and negligible coke deposition. In the case of 2-methoxy-4-methylphenol gasification, a 89.8% carbon conversion with tar formation reduced to only 5.7% is achieved using this catalyst. The developed catalyst yields a high quality synthesis gas (H2/CO \u3e 2) performing very close of the equilibrium. A mechanistic based kinetic model with statistically significant intrinsic kinetic parameters is also developed and validated using an independent set of experimental results

Estimation of biodiesel properties from chemical composition – an artificial neural network (ANN) approach

Biodiesel, produced from renewable feedstock represents a more sustainable source of energy and will therefore play a significant role in providing the energy requirements for transportation in the near future. Chemically, all biodiesels are fatty acid methyl esters (FAME), produced from raw vegetable oil and animal fat. However, clear differences in chemical structure are apparent from one feedstock to the next in terms of chain length, degree of unsaturation, number of double bonds and double bond configuration-which all determine the fuel properties of biodiesel. In this study, prediction models were developed to estimate kinematic viscosity of biodiesel using an Artificial Neural Network (ANN) modelling technique. While developing the model, 27 parameters based on chemical composition commonly found in biodiesel were used as the input variables and kinematic viscosity of biodiesel was used as output variable. Necessary data to develop and simulate the network were collected from more than 120 published peer reviewed papers. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture and learning algorithm were optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the coefficient of determination (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found high predictive accuracy of the ANN in predicting fuel properties of biodiesel and has demonstrated the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties. Therefore the model developed in this study can be a useful tool to accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests

Direct Calophyllum oil extraction and resin separation with a binary solvent of n-hexane and methanol mixture

This study investigated the use of a mixture of n-hexane and methanol as a binary solvent for the direct oil extraction and resin separation from Calophyllum seeds, in a single step. Optimal oil and resin yields and physicochemical properties were determined by identifying the best extraction conditions. The solvent mixture tested extracted oil and resin effectively from Calophyllum seeds, and separated resin from oil. Extraction conditions affected oil and resin yields and their physicochemical properties, with the n-hexane-to-methanol ratio being the most critical factor. Oil yield improved as n-hexane-to-methanol ratio increased from 0.5:1 to 2:1, and resin yield increased as methanol-to-n-hexane ratio increased from 0.5:1 to 2:1. Physicochemical properties of oil and resin, particularly for acid value and impurity content, improved as the n-hexane-to-methanol ratio decreased from 2:1 to 0.5:1. The best oil (51% with more than 95% triglycerides) and resin (18% with more than 5% polyphenols) yields were obtained with n-hexane-to-methanol ratios of 2:1 and 0.5:1, respectively, at a temperature of 50 °C, with an extraction time of 5 h. The best values for physicochemical property of oil were a density of 0.885 g/cm3, a viscosity of 26.0 mPa.s, an acid value of 13 mg KOH/g, an iodine value of 127 g/100 g, an unsaponifiable content of 1.5%, a moisture content of 0.8% and an ash content of 0.04%

Optimisation of bio-oil extraction process from Beauty Leaf (Calophyllum inophyllum) oil seed as a second generation biodiesel source

The Beauty Leaf tree (Calophyllum inophyllum) is a potential source of non-edible vegetable oil for producing future generation biodiesel because of its ability to grow in a wide range of climate conditions, easy cultivation, high fruit production rate, and the high oil content in the seed. This plant naturally occurs in the coastal areas of Queensland and the Northern Territory in Australia, and is also widespread in south-east Asia, India and Sri Lanka. Although Beauty Leaf is traditionally used as a source of timber and orientation plant, its potential as a source of second generation biodiesel is yet to be exploited. In this study, the extraction process from the Beauty Leaf oil seed has been optimised in terms of seed preparation, moisture content and oil extraction methods. The two methods that have been considered to extract oil from the seed kernel are mechanical oil extraction using an electric powered screw press, and chemical oil extraction using nhexane as an oil solvent. The study found that seed preparation has a significant impact on oil yields, especially in the screw press extraction method. Kernels prepared to 15% moisture content provided the highest oil yields for both extraction methods. Mechanical extraction using the screw press can produce oil from correctly prepared product at a low cost, however overall this method is ineffective with relatively low oil yields. Chemical extraction was found to be a very effective method for oil extraction for its consistence performance and high oil yield, but cost of production was relatively higher due to the high cost of solvent. However, a solvent recycle system can be implemented to reduce the production cost of Beauty Leaf biodiesel. The findings of this study are expected to serve as the basis from which industrial scale biodiesel production from Beauty Leaf can be made

Energy and electricity consumption analysis of Malaysian industrial sector

Malaysia has been experiencing strong economic growth through the last decade. Energy has been a key input in the development and growth of the country. The industrial sector is the second largest consumers of energy in Malaysia. In the present work sixty-four (64) factories in seven different manufacturing sectors were audited within the four regions of east-coast of Malaysia. In this audit, the most important parameters that have been collected are; power rating and operation time of energy consuming equipment/machinery; fossil fuel and other sources of energy consumption; production figure; peak and off peak tariff usage behavior; and power factor. These data were analyzed to investigate the breakdown of end-use equipment/machinery, the peak and off peak usage behavior, power factor trend, specific energy consumption and specific electricity consumption. The result of the energy audit shows that the highest energy consuming equipment is electric motor followed by liquid pumps and air compressor. The highest specific total energy (fossil fuel and electricity) consumption among the industrial sub-sectors is found in the rubber producing industries followed by fabricated metal industries, while the highest specific electrical energy consumption was found in the fabricated metal industries followed by rubber producing industries. The specific energy and electricity consumptions found in the present study are compared with Indonesian industrial sectors and presented in thin paper. The study also found that the 64% electrical energy was consumed in peak hours by the industries and average power factor ranged from 0.88 to 0.91. The energy audit in this study can be important tools and approaches for the policy maker to get insight into the energy and electricity uses pattern of Malaysian industrial sector

Real-time PCR assay and rapid diagnostic tests for the diagnosis of clinically suspected malaria patients in Bangladesh

<p>Abstract</p> <p>Background</p> <p>More than 95% of total malaria cases in Bangladesh are reported from the 13 high endemic districts. <it>Plasmodium falciparum </it>and <it>Plasmodium vivax </it>are the two most abundant malaria parasites in the country. To improve the detection and management of malaria patients, the National Malaria Control Programme (NMCP) has been using rapid diagnostic test (RDT) in the endemic areas. A study was conducted to establish a SYBR Green-based modified real-time PCR assay as a gold standard to evaluate the performance of four commercially-available malaria RDTs, along with the classical gold standard- microscopy.</p> <p>Methods</p> <p>Blood samples were collected from 338 febrile patients referred for the diagnosis of malaria by the attending physician at Matiranga</p> <p>Upazila Health Complex (UHC) from May 2009 to August 2010. Paracheck RDT and microscopy were performed at the UHC. The blood samples were preserved in EDTA tubes. A SYBR Green-based real-time PCR assay was performed and evaluated. The performances of the remaining three RDTs (Falcivax, Onsite Pf and Onsite Pf/Pv) were also evaluated against microscopy and real-time PCR using the stored blood samples.</p> <p>Result</p> <p>In total, 338 febrile patients were enrolled in the study. Malaria parasites were detected in 189 (55.9%) and 188 (55.6%) patients by microscopy and real-time PCR respectively. Among the RDTs, the highest sensitivity for the detection of <it>P. falciparum </it>(including mixed infection) was obtained by Paracheck [98.8%, 95% confidence interval (CI) 95.8-99.9] and Falcivax (97.6%, 95% CI 94.1-99.4) compared to microscopy and real-time PCR respectively. Paracheck and Onsite Pf/Pv gave the highest specificity (98.8%, 95% CI 95.7-99.9) compared to microscopy and Onsite Pf/Pv (98.8, 95% CI 95.8-99.9) compared to real-time PCR respectively for the detection of <it>P. falciparum</it>. On the other hand Falcivax and Onsite Pf/Pv had equal sensitivity (90.5%, 95% CI 69.6-98.8) and almost 100% specificity compared to microscopy for the detection of <it>P. vivax</it>. However, compared to real-time PCR assay RDTs and microscopy gave low sensitivity (76.9%, 95% CI 56.4-91) in detecting of <it>P. vivax </it>although a very high specificity was obtained (99- 100%).</p> <p>Conclusion</p> <p>The results of this study suggest that the SYBR Green-based real-time PCR assay could be used as an alternative gold standard method in a reference setting. Commercially-available RDTs used in the study are quite sensitive and specific in detecting <it>P. falciparum</it>, although their sensitivity in detecting <it>P. vivax </it>was not satisfactory compared to the real-time PCR assay.</p

Effects of pretreatments of Napier Grass with deionized water, sulfuric acid and sodium hydroxide on pyrolysis oil characteristics

The depletion of fossil fuel reserves has led to increasing interest in liquid bio-fuel from renewable biomass. Biomass is a complex organic material consisting of different degrees of cellulose, hemicellulose, lignin, extractives and minerals. Some of the mineral elements tend to retard conversions, yield and selectivity during pyrolysis processing. This study is focused on the extraction of mineral retardants from Napier grass using deionized water, dilute sodium hydroxide and sulfuric acid and subsequent pyrolysis in a fixed bed reactor. The raw biomass was characterized before and after each pretreatment following standard procedure. Pyrolysis study was conducted in a fixed bed reactor at 600 o�C, 30 �C/min and 30 mL/min N2 flow. Pyrolysis oil (bio-oil) collected was analyzed using standard analytic techniques. The bio-oil yield and characteristics from each pretreated sample were compared with oil from the non-pretreated sample. Bio-oil yield from the raw sample was 32.06 wt% compared to 38.71, 33.28 and 29.27 wt% oil yield recorded from the sample pretreated with sulfuric acid, deionized water and sodium hydroxide respectively. GC–MS analysis of the oil samples revealed that the oil from all the pretreated biomass had more value added chemicals and less ketones and aldehydes. Pretreatment with neutral solvent generated valuable leachate, showed significant impact on the ash extraction, pyrolysis oil yield, and its composition and therefore can be regarded as more appropriate for thermochemical conversion of Napier grass