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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Main Author:	Noor Aishah, Yumasir
Format:	Undergraduates Project Papers
Language:	English
Published:	2009
Subjects:	TP Chemical technology
Online Access:	http://umpir.ump.edu.my/id/eprint/848/ http://umpir.ump.edu.my/id/eprint/848/ http://umpir.ump.edu.my/id/eprint/848/1/Noor_Aishah_Yumasir.pdf

id	ump-848
recordtype	eprints
spelling	ump-8482015-03-03T07:47:13Z http://umpir.ump.edu.my/id/eprint/848/ Runge Kutta 4th order method and matlab in modeling of biomass growth and product formation in batch fermentation using differential equations Noor Aishah, Yumasir TP Chemical technology 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. 2009-04 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/848/1/Noor_Aishah_Yumasir.pdf Noor Aishah, Yumasir (2009) Runge Kutta 4th order method and matlab in modeling of biomass growth and product formation in batch fermentation using differential equations. Faculty of Chemical & Natural Resources Engineering, Universiti Malaysia Pahang. http://iportal.ump.edu.my/lib/item?id=chamo:45478&theme=UMP2
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TP Chemical technology
spellingShingle	TP Chemical technology Noor Aishah, Yumasir Runge Kutta 4th order method and matlab in modeling of biomass growth and product formation in batch fermentation using differential equations
description	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.
format	Undergraduates Project Papers
author	Noor Aishah, Yumasir
author_facet	Noor Aishah, Yumasir
author_sort	Noor Aishah, Yumasir
title	Runge Kutta 4th order method and matlab in modeling of biomass growth and product formation in batch fermentation using differential equations
title_short	Runge Kutta 4th order method and matlab in modeling of biomass growth and product formation in batch fermentation using differential equations
title_full	Runge Kutta 4th order method and matlab in modeling of biomass growth and product formation in batch fermentation using differential equations
title_fullStr	Runge Kutta 4th order method and matlab in modeling of biomass growth and product formation in batch fermentation using differential equations
title_full_unstemmed	Runge Kutta 4th order method and matlab in modeling of biomass growth and product formation in batch fermentation using differential equations
title_sort	runge kutta 4th order method and matlab in modeling of biomass growth and product formation in batch fermentation using differential equations
publishDate	2009
url	http://umpir.ump.edu.my/id/eprint/848/ http://umpir.ump.edu.my/id/eprint/848/ http://umpir.ump.edu.my/id/eprint/848/1/Noor_Aishah_Yumasir.pdf
first_indexed	2023-09-18T21:53:28Z
last_indexed	2023-09-18T21:53:28Z
_version_	1777413923127951360

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

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