Master of Science in Sustainable Process Development

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Browsing Master of Science in Sustainable Process Development by Author "Gunarathne D"

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    Kinetic modeling of tar formation in an updraft biomass gasifier
    (2020) Jayathilake GKM; Gunarathne D
    As the depreciation of the fossil fuels in the world, it is obligatory to discover new fuels to the highly industrialized society. With increasing requirements of the energy, it is globally focused on the use of renewable energy. Biomass can be used as an alternative energy source to replace fossil fuels, which contribute to the greenhouse gas emission. Therefore, biomass is a major renewable energy source as of today. Nowadays, converting biomass into biofuel is a major goal. So, the gasification process can be used as such an effective way to convert biomass into syngas. Even if the major goal of the gasification is to produce syngas such as H2, CO, intermittently, many byproducts are generated such as NOx, SO2, fly ash and tar. The formation of tar in the gasifier is a problematic situation. The formation of tar mainly depends on temperature, residence time, type of biomass and gasifying medium. Modeling is an effective method to optimize the gasifier operation. Also, it can be used to determine the relationship between operational parameter limits and explain trends in output products. By using Aspen Plus process simulation tool, a kinetic model was developed to predict the tar formation of updraft gasifier considering the main chemical phenomena biomass pyrolysis, reduction and combustion. The results were compared with the experimental data from the literature to validate the model. According to the developed model, the tar content and the composition could be estimated with respect to the equivalence ratio (ER) and pyrolysis zone bed height. When the ER is increasing the formation of tar is trending to decrease. The pyrolysis zone bed height beyond 1.3 cm does not show a significant impact on the tar content. It is possible to use the developed model to minimize tar content by operating at a suitable temperature (by controlling the ER) and by keeping an applicable residence time (by maintaining a suitable bed height). Further, this model can be used to optimize the tar formation with different biomass types and gasifying mediums when the temperature profile of the gasifier is available.
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    Process parameter optimization of washing pretreatment for inorganic removal from rice husk
    (2020) Peiris DMA; Gunarathne D
    Rice husk is particularly known as one of the most common agricultural waste and the usage of rice husk in energy applications is typically via the combustion process. Using agricultural waste for combustion application can lead to slagging, corrosion and fouling of boilers due to some problematic elements such as K and Cl. Water washing removes those problematic elements from rice husk and hot water washing treatment improves the removal efficiency of those alkali oxides, halides and total ash content. Further, hot water washing pretreatment has been identified as an effective method compared to acid treatment and alkali treatment. This study is aimed at optimizing the washing parameters; washing temperature, time and water to biomass ratio. Effectiveness of washing was directly evaluated by conductivity measurements and the removal of inorganic elements. The second order kinetic model was successfully applied for the leaching of K and Cl species and the kinetic parameters were obtained. Washing temperature has significant effect on Si removal, a considerable effect on K removal and a very weak effect of Cl removal. Moreover, water/biomass ratio has an appreciable effect on K removal, a very weak effect on Cl removal whereas almost no effect of Si removal. Washing temperature of 65 ⁰C and water to biomass ratio of 100 was selected as the optimum process conditions. At the selected optimum conditions, about 84% of K and 81% of Cl can be removed while Si removal is insignificant. Within 10 minutes leaching time, 97% of leachable Cl and 81% leachable K can be removed.