We present a physically-based flow simulation which supports complex boundary conditions running on the graphics processing unit (GPU). We employ the Lattice Boltzmann Method (LBM), a relatively new discrete-space discrete-time method, for computing the flow field. To handle complex, moving and deformable boundaries, we propose a generic voxelization algorithm of the boundaries using depth peeling, and extend it to a dynamic boundary generation method that converts any geometric boundary to LBM boundary nodes on-the-fly. Our implementation incorporates various optimizations to fully exploit the computation power of the GPU. As a result, the GPU-based simulation can be an order of magnitude faster than the CPU version, while generating simulation results with the same accuracy.<\/p>\n","protected":false},"excerpt":{"rendered":"
We present a physically-based flow simulation which supports complex boundary conditions running on the graphics processing unit (GPU). We employ the Lattice Boltzmann Method (LBM), a relatively new discrete-space discrete-time method, for computing the flow field. To handle complex, moving and deformable boundaries, we propose a generic voxelization algorithm of the boundaries using depth peeling, […]<\/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":[104,3],"tags":[444,1795,121,108,20,408,182],"class_list":["post-1630","post","type-post","status-publish","format-standard","hentry","category-fluid-dynamics","category-paper","tag-cg","tag-fluid-dynamics","tag-fluid-simulation","tag-lattice-boltzmann-model","tag-nvidia","tag-nvidia-geforce-fx-5900-ultra","tag-opengl"],"views":2254,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/1630","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=1630"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/1630\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1630"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1630"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1630"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}