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commit 8ee98c7eae7d8551477ac8077d41df8a48f47acc
parent e4ee05fd5a4492aae835d3da3ebfbb713a9d32d2
Author: Christophe Coustet <christophe.coustet@meso-star.com>
Date:   Tue,  5 Dec 2017 16:01:05 +0100

Add information on linear and propagator.

Diffstat:
Mstardis.html.in | 19+++++++++++--------
1 file changed, 11 insertions(+), 8 deletions(-)

diff --git a/stardis.html.in b/stardis.html.in @@ -3,11 +3,12 @@ </header> <p>Stardis computes the <b>propagator</b> (aka the <b>Green function</b>) of -coupled thermal systems under the linear assumption. Here <b>coupled</b> -refers to conductive, convective and radiative transfers. Stardis can deal -with complex geometries as well as high-frequency external solicitations -over very long period of time, relative to the characteristic time of the -system.</p> +coupled thermal systems under the linear assumption. Here <b>coupled</b> refers +to conductive, convective and radiative transfers, and linear means that each +modeled phenomena is represented using a model that is linear with temperature. +Stardis can deal with complex geometries as well as high-frequency external +solicitations over a very long period of time, relative to the characteristic +time of the system.</p> <p>Stardis does not compute temperature fields as a whole. It is designed to compute specific observables such as temperatures at probe points / dates or @@ -49,9 +50,11 @@ device):</p> <li> the value of interest is the core temperature (semiconductor junction) in the red-colored region of the IGBT which is also the source of dissipated power (see figure below),</li> - <li> the propagator has been <b>precomputed</b> using the Stardis Monte-Carlo - solver from the 3D description of the model and the materials' properties - (see figure below),</li> + <li> an estimate of the propagator has been <b>precomputed</b> using the + Stardis Monte-Carlo solver from the 3D description of the model and the + materials' properties (see figure below); the estimate is based on 10,000 + paths and the resulting statistical uncertainty could be reduced by just + sampling additional paths,</li> <li> on request, the propagator is applied to the user-provided temperatures and dissipated power; it acts as a <b>super-fast direct model</b> to compute the value of the core temperature together with its statistical uncertainty