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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