commit 6cbd1d854e0c2b2004ac16e5a277209324125598
parent f6fa38ee14eaa4ce4f719d7bfffec2994579db53
Author: Vincent Forest <vincent.forest@meso-star.com>
Date: Mon, 4 Dec 2017 11:50:59 +0100
Merge remote-tracking branch 'origin/master'
Diffstat:
1 file changed, 24 insertions(+), 26 deletions(-)
diff --git a/stardis.html.in b/stardis.html.in
@@ -20,19 +20,21 @@ Propagators seamlessly agregate all the provided geometrical and physical
information on the system in an unbiased and very-fast statistical model.</p>
<p>Stardis' algorithms are based on state-of-the-art Monte-Carlo method applied
-to radiative transfer physics (Delatorre [1]) combined with conduction's
-statistical formulation (Kac [2] and Muller [3]). Thanks to recent advances in
-computer graphics technology which has already been a game changer in the
-cinema industry (FX and animated movies), this theoritical framework can now
-be practically used on the most geometrically complex models.</p>
+to radiative transfer physics (Delatorre [<a href="#1">1</a>]) combined with
+conduction's statistical formulation (Kac [<a href="#2">2</a>] and Muller [<a
+href="#3">3</a>]). Thanks to recent advances in computer graphics technology
+which has already been a game changer in the cinema industry (FX and animated
+movies), this theoritical framework can now be practically used on the most
+geometrically complex models.</p>
<p>Everytime the linear assumption is relevant, this theoritical framework
-allows to encompass all the heat transfer mecanisms (conductive-convective-
-radiative) in an <b>unified statistical model</b>. Such models can be solved by
-a <b>Monte-Carlo approach</b> just by sampling <b>thermal paths</b>. This can
-be seen as an extension of Monte-Carlo algorithms that solve radiative transfer
-by sampling optical paths. A main property of this approach is that the
-resulting algorithms does not rely on a volume mesh of the system.</p>
+allows to encompass all the heat transfer mecanisms
+(conductive-convective-radiative) in an <b>unified statistical model</b>. Such
+models can be solved by a <b>Monte-Carlo approach</b> just by sampling
+<b>thermal paths</b>. This can be seen as an extension of Monte-Carlo
+algorithms that solve radiative transfer by sampling optical paths. A main
+property of this approach is that the resulting algorithms does not rely on a
+volume mesh of the system.</p>
<h2>An example of propagator use</h2>
@@ -124,21 +126,17 @@ you are always going to talk to someone that knows what they are doing.</p>
<p>Our commercial offer is versatile:</p>
<ul>
<li>we provide software developers with a Stardis SDK,</li>
- <li>we <a href=#syrthes>assist users</a> in integrating Stardis in their workflow,</li>
- <li>we propose bot theoretical and technical trainings and support,</li>
+ <li>we <a href=#syrthes>assist users</a> in integrating Stardis in their
+ workflow,</li>
+ <li>we propose both theoretical and technical training and support,</li>
<li>we develop <a href=#optisol>custom software</a> from / on top of
- Stardis.</li>
+ Stardis,</li>
+ <li>we have a study service based on the method implemented in Stardis.</li>
</ul>
To get access to Stardis and for more informations on our offer, please <a
href="mailto:contact@meso-star.com">contact us</a>.
-<!--p>Depending on your status (industry or academic) and development constraints
-(open or closed source, ...) Stardis can be made available under the adequate
-license. Of course, both theoritical and software development training is
-proposed on a regular basis as well as on demand to help you master all the
-power of our innovative approach.</p-->
-
<h2>Examples of integration and development</h2>
<h3 id="syrthes"> EDF R&D - SYRTHES </h3>
@@ -192,15 +190,15 @@ and initial conditions, Star-Therm can compute the temperature at any position
within the solid.</p>
<h2>References</h2>
-<p>
+<div id=1>
[1] Delatorre et al., <i>Monte Carlo advances and concentrated solar
applications</i>, <b>Solar Energy</b>, 2014
-</p>
-<p>
+</div>
+<div id=2>
[2] Kac, <i>On Distributions of Certain Wiener Functionals</i>.
<b>The Annals of Mathematical Statistics</b>, 1949.
-</p>
-<p>
+</div>
+<div id=3>
[3] Muller, <i>Some continuous Monte-Carlo Methods for the Dirichlet Problem"
</i>, <b>Transactions of the American Mathematical Society</b>, 1956.
-</p>
+</div>
