<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Using Machine Learning to Augment Coarse-Grid Computational Fluid Dynamics Simulations · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2010.00072/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2010.00072/feed.xml" rel="self" type="application/rss+xml" /><item><title>Using Machine Learning to Augment Coarse-Grid Computational Fluid Dynamics Simulations — mentioned by naasking</title><link>https://news.ycombinator.com/item?id=34338168</link><guid isPermaLink="false">urn:hackerpapers:mention:2010.00072:34338168</guid><pubDate>Wed, 11 Jan 2023 13:30:33 GMT</pubDate><description>&lt;p&gt;&amp;gt; The interesting question is indeed &amp;quot;augmentation&amp;quot;: can we use ML models to improve the efficiency of first principles simulations via some sort of feedback process. Using Machine Learning to Augment Coarse-Grid Computational Fluid Dynamics Simulations, https://arxiv.org/abs/2010.00072&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2010.00072/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>physics.comp-ph</category></item></channel></rss>
