{"id":6990,"date":"2012-01-21T23:29:08","date_gmt":"2012-01-21T21:29:08","guid":{"rendered":"http:\/\/hgpu.org\/?p=6990"},"modified":"2012-01-21T23:29:08","modified_gmt":"2012-01-21T21:29:08","slug":"a-practical-visualization-strategy-for-large-scale-supernovae-cfd-simulations","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=6990","title":{"rendered":"A Practical Visualization Strategy for Large-Scale Supernovae CFD Simulations"},"content":{"rendered":"<p>Simulating the expansion of a Type II supernova using an adaptive computational fluid dynamics (CFD) engine yields a complex mixture of turbulent flow with dozens of physical properties. The dataset shown in this sketch was initially simulated on iVEC&#8217;s EPIC supercomputer (a 9600 core Linux cluster) using FLASH [Fryxell et al. 2000] to model the thermonuclear explosion, and later post-processed using a novel integration technique to derive the radio frequency emission spectra of the expanding shock-wave front [Potter et al. 2011]. Model parameters have been chosen to simulate the asymmetric properties of the SN 1987A remnant [Potter et al. 2009].<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Simulating the expansion of a Type II supernova using an adaptive computational fluid dynamics (CFD) engine yields a complex mixture of turbulent flow with dozens of physical properties. The dataset shown in this sketch was initially simulated on iVEC&#8217;s EPIC supercomputer (a 9600 core Linux cluster) using FLASH [Fryxell et al. 2000] to model the [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[104,90,3],"tags":[7,1270,1795,1793,182,134],"class_list":["post-6990","post","type-post","status-publish","format-standard","hentry","category-fluid-dynamics","category-opencl","category-paper","tag-ati","tag-ati-radeon-hd-6750-m","tag-fluid-dynamics","tag-opencl","tag-opengl","tag-visualization"],"views":2062,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/6990","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=6990"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/6990\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=6990"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=6990"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=6990"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}