Batch reactor - Revision history

SebastianSager at 12:10, 16 April 2026

2026-04-16T12:10:55Z

← Older revision		Revision as of 12:10, 16 April 2026
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	<math>		<math>
	\begin{array}{llcl}		\begin{array}{llcl}
	\displaystyle \max_{x, u} & x_2(t_f) \\[1.5ex]		\displaystyle \max_{x, T} & x_2(t_f) \\[1.5ex]
	\mbox{s.t.} & \dot{x}_1 & = & -k_1 x_1^2.\\		\mbox{s.t.} & \dot{x}_1 & = & -k_1 x_1^2.\\
	& \dot{x}_2 & = & k_1 x_1^2 - k_2 x_2,\\		& \dot{x}_2 & = & k_1 x_1^2 - k_2 x_2,\\
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	This solution was computed using JuMP with a collocation method and 300 discretization points. The differential equations were solved using the explicit Euler Method. The source code can be found at [[Batch reactor (JuMP)]].		This solution was computed using JuMP with a collocation method and 300 discretization points. The differential equations were solved using the explicit Euler Method. The source code can be found at [[Batch reactor (JuMP)]].

	The optimal objective value of the problem is x2(tf) = 0.611715.		The optimal objective value of the problem is <math>x_2(t_f) = 0.611715</math>.

	<gallery caption="Reference solution plots" widths="180px" heights="140px" perrow="2">		<gallery caption="Reference solution plots" widths="180px" heights="140px" perrow="2">

2019-04-11T13:42:22Z

<math> </math> rendering appears to be broken

← Older revision		Revision as of 13:42, 11 April 2019
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	This solution was computed using JuMP with a collocation method and 300 discretization points. The differential equations were solved using the explicit Euler Method. The source code can be found at [[Batch reactor (JuMP)]].		This solution was computed using JuMP with a collocation method and 300 discretization points. The differential equations were solved using the explicit Euler Method. The source code can be found at [[Batch reactor (JuMP)]].

	The optimal objective value of the problem is ~~<math> x_2~~(~~t_f~~) = 0.611715 ~~</math>~~.		The optimal objective value of the problem is x2(tf) = 0.611715.

	<gallery caption="Reference solution plots" widths="180px" heights="140px" perrow="2">		<gallery caption="Reference solution plots" widths="180px" heights="140px" perrow="2">

2019-04-11T13:41:03Z

Add link to GEKKO solution

← Older revision		Revision as of 13:41, 11 April 2019
Line 40:		Line 40:
	This solution was computed using JuMP with a collocation method and 300 discretization points. The differential equations were solved using the explicit Euler Method. The source code can be found at [[Batch reactor (JuMP)]].		This solution was computed using JuMP with a collocation method and 300 discretization points. The differential equations were solved using the explicit Euler Method. The source code can be found at [[Batch reactor (JuMP)]].

	The optimal objective value of the problem is <math> x_2(t_f) = -0.611715 </math>.		The optimal objective value of the problem is <math> x_2(t_f) = 0.611715 </math>.

	<gallery caption="Reference solution plots" widths="180px" heights="140px" perrow="2">		<gallery caption="Reference solution plots" widths="180px" heights="140px" perrow="2">
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	Model descriptions are available in		Model descriptions are available in
			* [[:Category:Gekko \| GEKKO Python code]] at [[Batch reactor (GEKKO)]]
	* [[:Category: Julia/JuMP \| JuMP code]] at [[Batch reactor (JuMP)]]		* [[:Category: Julia/JuMP \| JuMP code]] at [[Batch reactor (JuMP)]]

2016-07-27T08:42:58Z

← Older revision		Revision as of 08:42, 27 July 2016
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	[[Category:ODE model]]		[[Category:ODE model]]
	[[Category:Chemical engineering]]		[[Category:Chemical engineering]]
	~~[[Category:Path-constrained arcs]]~~

2016-07-27T08:28:09Z

2016-07-27T08:24:57Z

2016-06-27T22:08:00Z

Mathematical formulation

2016-06-27T22:07:49Z

Mathematical formulation

2016-06-27T22:07:41Z

Mathematical formulation

2016-06-27T22:01:30Z

← Older revision		Revision as of 22:01, 27 June 2016
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	[[Category:MIOCP]]		[[Category:MIOCP]]
	[[Category:ODE model]]		[[Category:ODE model]]
	[[Chemical engineering]]		[[Category:Chemical engineering]]
	[[Path-constrained arcs]]		[[Category:Path-constrained arcs]]