| 000 | 02322nam a2200241 a 4500 | ||
|---|---|---|---|
| 001 | vtls000045478 | ||
| 003 | KUKTEM | ||
| 005 | 20251114204424.0 | ||
| 008 | 100430t2009 my a f m 000 0 eng d | ||
| 020 | _aTHE0004111(Local) | ||
| 039 | 9 |
_a201905131407 _bfarhana _c201111240945 _dFida _c201107132316 _dVLOAD _c201004301542 _dida _y201004301225 _zida |
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| 040 | _aUMP | ||
| 090 | _aTP156.F4 A37 2009 rs Bc. | ||
| 100 | 0 | _aNoor Aishah Yumasir | |
| 245 | 1 | 0 |
_aRunge Kutta 4th order method and matlab in modeling of biomass growth and product formation in batch fermentation using differential equations / _cNoor Aishah Bt Yumasir |
| 260 |
_aKuantan, Pahang : _bUMP, _c2009 |
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| 300 |
_axiii, 70 p. : _bill. (some col.) ; _c30 cm. + _e1 computer disc |
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| 502 | _aProject paper (Bachelor of Chemical Engineering (Biotechnology)) -- Universiti Malaysia Pahang - 2009 | ||
| 520 | 3 | _aThis 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. | |
| 650 | 0 | _aFermentation | |
| 650 | 0 | _aBiopolymers | |
| 999 |
_aVIRTUA40 _c1760 _d1766 |
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| 999 | _aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5200*6500*6501*9992 | ||