[Scilab-users] ode, speed issue or tips to speed up ?

[Stéphane Mottelet]

Hi,

The "fix" solver is the classical Runge-Kutta-Fehlberg scheme, hence an 
*explicit* scheme. So, your Jacobian is just ignored in the 
computations. If you guessed that some stiffness may occur, e.g. if you 
ode is a discretized pde, then you should force the "stiff" solver 
instead. In that case the Jacobian will be used. If you want to speed up 
things and if your Jacobian is  banded, using %ODEOPTIONS allows to do so.

S.

Le 02/09/2021 à 18:03, CHEZE David 227480 a écrit :
>
> Dear all,
>
> In experimental work, I’m comparing dynamic model of a thermal system 
> with measurements. I’m using function ode, “fix” solver (continuous 
> time, lowest accuracy requirement is applying in my case at this 
> stage) and Jacobian ( to try to speed up the calculation but not 
> sensitive as for now) to get the solution of the equation,  a single 
> temperature node, at 240 times (time vector), default rtol=1.d-3 and 
> atol=1.d-4. The system inputs are available as vector of reals , size 
> is 240 and inputs are passed to the ode function as inputs functions 
> by interpolating (interp1) the inputs vectors. It is issuing correct 
> temperature solutions but is very slow, ~40s for 240 times, while the 
> variable inputs vector are actually not varying a lot and thus I would 
> expect very short calculation time.
>
> WIN10-64bits Intel i7 2,6GHz, Scilab 6.1.1
>
> Is there any tips to speed up the calculation , advanced example 
> documentation about ODEOPTIONS or ode_optional_output ? I guess it’s 
> the same underlying code that is used in Xcos isn’t it ?
>
> Thank you for advising,
>
> David
>
>
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-- 
Stéphane Mottelet
Ingénieur de recherche
EA 4297 Transformations Intégrées de la Matière Renouvelable
Département Génie des Procédés Industriels
Sorbonne Universités - Université de Technologie de Compiègne
CS 60319, 60203 Compiègne cedex
Tel : +33(0)344234688
http://www.utc.fr/~mottelet

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