Lerkkasemsan, Nuttapol

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Lerkkasemsan, Nuttapol
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nuttapol.le@kmitl.ac.th

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    Outer-tubes Falling Film Evaporator with Well-Mixed Surface Renewal
    (2017-01-01)
    Lerkkasemsan, Nuttapol
    ;
    Lerssubsuree, Kuntaphon
    ;
    Chotiviriyavanich, Boonchai
    ;
    Benjangkaprasert, Ruenruedee
    ;
    Kitchaiya, Prakob
    A falling film evaporator with a liquid flowing laminarly outside vertical cylindrical tubes was studied by a mathematical modeling in order to describe the performance of the system and the results are later used for a design of a falling film evaporator. In this study a mathematical model was developed from mass and energy as well as momentum transfer processes in an evaporation of a sugar solution. The equations were solved by using a numerical technique known as implicit method. This model yields the prediction of velocity, temperature and concentration profiles of solution as well as rate of mass evaporation and energy required in this process. Evaporation limitation was disclosed to be based on water mass transfer across the liquid thin film. Renewable surface was proposed to enhance the evaporation by adding a collector for liquid mixing before further evaporation. Adding only one collector at the half height of the evaporation tube could increase water evaporation rate by 1.3 and 2.1 % in case of the liquid perfect mixing, respectively.
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    Kinetic modeling of CO2 gasification reactivity of Palm Kernel Shell (PSK)
    (2017-01-01)
    Lerkkasemsan, Nuttapol
    This research demonstrates the investigation of gasification reactivity behavior of palm kernel shell bio char using thermogravimetric analysis (TGA) at 850, 900 or 950°C under CO<inf>2</inf>. There are three fluid-solid kinetic models used to describe the reaction behavior of palm kernel shell bio char. The three models are volumetric model (VM), grain model (GM), and random pore model (RPM). From model results, the GM model and RPM model describe the reaction quite well. However, the GM model is considered as the best model in all three models to describe the reactivity of palm kernel shell bio char gasification reaction. From the GM model, the reaction starts from the surface and it moves to the core. As time go on, the gasify agent will defuse through the core and it keep the reaction go into the core. The activation energy of gasification reactivity of palm kernel shell bio char are 150kJ/mol for GM model. From the results, the coefficient of determination of GM model are 0.989, 0.989, and 0.961 at 850, 900, 950°C respectively.
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    Kinetic Study of Steam Gasificaiton of Palm Kernel Shell Char
    (2020-05-27)
    Lerkkasemsan, Nuttapol
    In this work, we investigate the reaction mechanism of steam gasification reaction of palm kernel shell char. The experiment results which are used in this work are carried on at temperature of 1123, 1173, and 1223K. The isothermal steam gasification of palm kernel shell char is described by mathematic models including volumetric model (VM), grain model (GM), random pore model (RPM), and modified random pore model (mRPM). From results, we found that the RPM model can predict gasification of palm kernel shell char better than other models. The RPM model considers the overlapping of pore surfaces, which results in the reduction of surface area available for the reaction. The activation energy of gasification reactivity of palm kernel shell char is 152.63 kJ/mol for RPM model. The coefficient of determination of RPM model are 0.9920, 0.9995, and 0.9907 at 1123, 1173, and 1223 K respectively.
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    Predicting Conversion from Pyrolysis of Pongmia
    (2015-01-01)
    Lerkkasemsan, Nuttapol
    This research demonstrates the technique of predicting pyrolysis of lignocellulosic biomass. Modeling of pyrolysis of biomass is complex and challenging because of short reaction times, temperatures as high as a thousand degrees Celsius, and biomass of varying or unknown chemical compositions. As such a deterministic model is not capable of representing the pyrolysis reaction system. To be able to predict a pyrolysis reaction of an unknown lignocellulosic biomass without an experimental data support or data fitting is an even more challenging work. In this research, we are trying to predict pyrolysis of Pongmia in Nitrogen to demonstrate that our technique is useful for predicting pyrolysis reaction of other biomass source. There are three main chemical compositions in lignocellulosic biomass which are cellulose, hemicellulose and lignin. We are considering that the total pyrolysis reaction is affected by the reaction of three main compositions. However, these three main chemical compositions of biomass is vary not only by type of biomass but also by other things such as where it is grown or even which part of biomass since the chemical compositions in the leaf can be different from the trunk. Our propose method is an extending study of our previous paper "pyrolysis of biomass-fuzzy modeling". Our model successfully gives a good predicting result. The result shows that our model can predict 91.82% of pyrolysis of Pongmia in Nitrogen correctly without any data from the experiment. Therefore, we could use this method to predict other lignocellulosic biomass before we perform an experiment.