Runge Kutta 4th order method and matlab in modeling of biomass growth and product formation in batch fermentation using differential equations

This study is about the modeling of biomass growth and PHB production in batch fermentation by using the numerical integration Runge Kutta 4th Order Method. The data is obtained from two sources which are from Valappil et. al, 2007[1] and data from the experiment of Hishafi, 2009 [2]. In order to si...

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Bibliographic Details
Main Author: Noor Aishah, Yumasir
Format: Undergraduates Project Papers
Language:English
Published: 2009
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/848/1/Noor_Aishah_Yumasir.pdf
http://umpir.ump.edu.my/id/eprint/848/
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Summary:This study is about the modeling of biomass growth and PHB production in batch fermentation by using the numerical integration Runge Kutta 4th Order Method. The data is obtained from two sources which are from Valappil et. al, 2007[1] and data from the experiment of Hishafi, 2009 [2]. In order to simulate the process, the method of ordinary differential equation, ode45 in MATLAB software was used. The ode45 provides an essential tool that will integrate a set of ordinary differential equations numerically. The calculation method of ode45 uses Runge Kutta 4th Order numerical integration. The values of the parameters of the models are determined by selecting the value that will give the least square error between the predicted model and the actual data. After the modeling process, a linear regression between the parameters of the ode(as the dependent variable) and the manipulated control variable agitation rate and initial concentration of glucose (as the independent variables) is made in order to study the effect of the manipulated variables. From the simulation, it’s found that the model for both of biomass and PHB fit the data satisfactorily. After the linear regression, it is found that the agitation rate gives more influence than initial concentration of glucose.