{"id":2382,"date":"2018-10-03T22:40:50","date_gmt":"2018-10-04T05:40:50","guid":{"rendered":"https:\/\/blogs.plm.automation.siemens.com\/t5\/Simcenter-Blog\/The-fastest-chemistry-solver-on-the-CFD-market\/ba-p\/531014"},"modified":"2026-03-26T06:11:19","modified_gmt":"2026-03-26T10:11:19","slug":"the-fastest-chemistry-solver-on-the-cfd-market","status":"publish","type":"post","link":"https:\/\/blogs.sw.siemens.com\/simcenter\/the-fastest-chemistry-solver-on-the-cfd-market\/","title":{"rendered":"The fastest chemistry solver on the CFD market?!"},"content":{"rendered":"<p><span class=\"TextRun SCXW209712702\"><span class=\"NormalTextRun SCXW209712702\">Designing next generation combustion systems is a true challenge today, with stricter and stricter emission regulations, competitive pressure to deliver shorter time-to-market to stay ahead of competition and the need to adapt to new fuels and fuel compositions.&nbsp;<\/span><\/span><span class=\"TextRun SCXW209712702\"><span class=\"ContextualSpellingAndGrammarError SCXW209712702\">Additionally<\/span><\/span><span class=\"TextRun SCXW209712702\"><span class=\"NormalTextRun SCXW209712702\"><span>&nbsp;<\/span>new technologies such as 3D printing creates vast opportunities to optimize the combustion chamber design for e.g. gas turbine combustors with less constraints, as<span>&nbsp;<\/span><\/span><\/span><a class=\"Hyperlink SCXW209712702\" href=\"http:\/\/meconstructionnews.com\/31438\/siemens-and-e-on-achieve-significant-3d-printing-milestone-for-energy-sector%20.%20http:\/meconstructionnews.com\/31438\/siemens-and-e-on-achieve-significant-3d-printing-milestone-for-energy-sector\" target=\"_blank\" rel=\"noreferrer nofollow noopener\"><span class=\"TextRun Underlined SCXW209712702\"><span class=\"NormalTextRun SCXW209712702\">recently demonstrated by Siemens Industrial Turbomachinery AB<\/span><\/span><\/a><span class=\"TextRun SCXW209712702\"><span class=\"NormalTextRun SCXW209712702\">. Finding the best design among the countless possibilities while ensuring all<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW209712702\"><span class=\"NormalTextRun CommentStart SCXW209712702\">requirements are met demands<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW209712702\"><span class=\"NormalTextRun SCXW209712702\">aggressive usage of the Digital Twin. The digital twin needs to be<span>&nbsp;<\/span><\/span><\/span><strong><span class=\"TextRun SCXW209712702\"><span class=\"NormalTextRun SCXW209712702\">accurate&nbsp;<\/span><\/span><\/strong><span class=\"TextRun SCXW209712702\"><span class=\"NormalTextRun SCXW209712702\">and<span>&nbsp;<\/span><\/span><\/span><strong><span class=\"TextRun SCXW209712702\"><span class=\"NormalTextRun SCXW209712702\">fast&nbsp;<\/span><\/span><\/strong><span class=\"TextRun SCXW209712702\"><span class=\"NormalTextRun SCXW209712702\">to minimize time to market. <\/span><\/span><\/p>\n<p><span class=\"TextRun SCXW209712702\"><span class=\"NormalTextRun SCXW209712702\">New lean-burning combustion systems are typically prone to thermoacoustic instabilities, which need to be avoided. Thermoacoustic instability predictions, accurate emissions as well as re-light simulations (like in the video<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW209712702\"><span class=\"NormalTextRun SCXW209712702\">below<\/span><\/span><span class=\"TextRun SCXW209712702\"><span class=\"NormalTextRun SCXW209712702\">) typically means LES is required. Which means the CPU cost is<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW209712702\"><span class=\"ContextualSpellingAndGrammarError SCXW209712702\">high.<\/span><\/span><span class=\"TextRun SCXW209712702\"><span class=\"NormalTextRun SCXW209712702\"><span>&nbsp;<\/span>Siemens PLM software works hard to bring you as fast and as accurate solutions as possible to help minimize your time-to-market, which is demonstrated again in the upcoming release of Simcenter STAR-CCM+v13.06.<\/span><\/span><\/p>\n<p><span class=\"TextRun SCXW209712702\"><span class=\"NormalTextRun SCXW209712702\"><\/span><\/span><\/p>\n<div class=\"lia-vid-container video-embed-center\">\n<div id=\"lia-vid-g5ZXhjZzE6AjVpKsgkuWdpPboEXWxJPnw596h379r887\" class=\"lia-video-ooyala-player-container\"><\/div>\n<p><script>LITHIUM.OoyalaPlayer.addVideo('https:\/\/player.ooyala.com\/static\/v4\/production\/', 'lia-vid-g5ZXhjZzE6AjVpKsgkuWdpPboEXWxJPnw596h379r887', 'g5ZXhjZzE6AjVpKsgkuWdpPboEXWxJPn', {\"pcode\":\"sxdjkxOluLl_gSQrV57FiGraFE2-\",\"playerBrandingId\":\"ODI0MmQ3NjNhYWVjODliZTgzY2ZkMDdi\",\"width\":\"596px\",\"height\":\"379px\"});<\/script><a class=\"video-embed-link\" href=\"https:\/\/blogs.plm.automation.siemens.com\/t5\/video\/gallerypage\/video-id\/g5ZXhjZzE6AjVpKsgkuWdpPboEXWxJPn\" target=\"_blank\" rel=\"noopener\">(view in My Videos)<\/a><\/p>\n<\/div>\n<p><span>In&nbsp;<\/span><span>this version two major features<\/span><span>&nbsp;are added which make&nbsp;<\/span><span>combustion&nbsp;<\/span><span>simulations both&nbsp;<\/span><strong><span>faster&nbsp;<\/span><\/strong><span>and&nbsp;<\/span><strong><span>more accurate<\/span><\/strong><span>:<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">&nbsp;<\/span><\/p>\n<ol>\n<li data-leveltext=\"%1.\" data-font=\"Calibri, sans-serif\" data-listid=\"1\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span>Faster complex chemistry simulations &#8211; High fidelity calculations are now (much!) faster. Potentially&nbsp;<\/span><strong>the<\/strong><strong>&nbsp;<\/strong><strong>fastest<\/strong>&nbsp;<span>on the CFD market..!?&nbsp;<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">&nbsp;<\/span><\/li>\n<\/ol>\n<ol>\n<li data-leveltext=\"%1.\" data-font=\"Calibri, sans-serif\" data-listid=\"1\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span>Dynamic Thickened Flame Model with complex chemistry and FGM combustion models &#8211; LES combustion simulations are now&nbsp;<\/span><strong><span>more accurate<\/span><\/strong><span>.<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">&nbsp;<\/span><\/li>\n<\/ol>\n<p><span>The complex chemistry model solves all reactions&nbsp;<\/span><span>online, and<\/span><span>&nbsp;is the most suitable model for e.g. CO emissions, low load conditions and ignition driven combustion. Since all reactions are calculated online it is an expensive combustion model. The&nbsp;<\/span><span>chemistry&nbsp;<\/span><span>solver was quick already in Simcenter STAR-CCM+v13.04, using an optimized CVODE implementation and acceleration techniques such as <a href=\"https:\/\/community.plm.automation.siemens.com\/t5\/Simcenter-Blog\/Realistic-Combustion-Simulation-with-STAR-CCM-v12-06\/ba-p\/439623\" target=\"_self\" rel=\"nofollow noopener noreferrer\">Dynamic Mechanism Reduction<\/a><\/span><span>, clustering and ISAT. In this release however, the solver is made even quicker, for some cases&nbsp;<\/span><strong><i><span>much<\/span><\/i><\/strong><strong><span>&nbsp;<\/span><\/strong><span>quicker. A secret sauce (No, we will not tell you the recipe! It\u2019s from grandma!) is implemented which makes&nbsp;<\/span><i><span>all<\/span><\/i><span>&nbsp;simulations faster, regardless of mechanism size, and a sparse solver is introduced which significantly speeds up calculations with more than 100 transported species. See the chart below for examples of CPU time speedup in v13.06 vs v13.04.&nbsp;<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">&nbsp;<\/span><\/p>\n<p><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\"><span class=\"lia-inline-image-display-wrapper lia-image-align-inline\" style=\"width: 999px;\"><img decoding=\"async\" src=\"http:\/\/blogs.sw.siemens.com\/wp-content\/uploads\/sites\/6\/2019\/09\/CPUtimespeedup-1.png\" alt=\"CPUtimespeedup.png\" title=\"CPUtimespeedup.png\"><span class=\"lia-inline-image-caption\" onclick=\"event.preventDefault();\">Speedup of total simulation time STAR-CCM+v13.06 vs v13.04. All cases except the last one were run without chemistry acceleration.      Case description: Sandia Flame D [1]: 5k cells, steady RANS. IFRF glass furnace [2]: 0.64M cells, steady RANS. Flameless combustor [3]: 6.3M cells, unsteady LES. Industrial GT1: Gas Turbine, 10M cells, unsteady LES. Industrial GT2: Gas Turbine, 25M cells, steady RANS. ECN spray H [4]: 92k cells, unsteady RANS. Generic GT: Gas Turbine, 2M cells, steady RANS, clustering acceleration technique.       Chemical Mechanisms: GRI 3.0 [5]: 53 species, 325 reactions. Wang [6]: 109 species, 543 reactions. Lu [7]: 188 species, 842 reactions. Ahmed [8]: 246 species, 1284 reactions.<\/span><\/span><\/span><\/p>\n<p><span class=\"TextRun SCXW201681142\"><span class=\"NormalTextRun SCXW201681142\">Note: This is the speedup in<span>&nbsp;<\/span><\/span><\/span><em><span class=\"TextRun SCXW201681142\"><span class=\"NormalTextRun SCXW201681142\">total runtime<\/span><\/span><\/em><span class=\"TextRun SCXW201681142\"><span class=\"NormalTextRun SCXW201681142\">, not just the speedup in chemistry.&nbsp;<span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\">The speedup is ranging from 1.16x faster to 12x(!)<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"ContextualSpellingAndGrammarError SCXW219623687\">faster, and<\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\"><span>&nbsp;<\/span>is very case dependent.<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"ContextualSpellingAndGrammarError SCXW219623687\">Typically<\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\"><span>&nbsp;<\/span>the heavier the chemistry calculation, the higher the<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\">total<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\">speedup. <\/span><\/span><\/span><\/span><span class=\"TextRun SCXW201681142\"><span class=\"NormalTextRun SCXW201681142\"><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\">The<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\">cases represented by the five<\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\"><span>&nbsp;<\/span>left-most bars<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\">were all run with the<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\">GRI3.0 mechanism, with 53 species, and are ordered by mesh size. Note that even for this relatively small chemistry a full scale<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\">25<\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\">M cell<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\">simulation of an industrial gas turbine (denoted GT2 in the graph)<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\">is<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\">more than<\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\"><span>&nbsp;<\/span><\/span><\/span><strong><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\">1.9<\/span><\/span><\/strong><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\"><strong>x faster<\/strong>! The industrial gas turbine<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\">GT1<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\">gives<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\">the least<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\">speedup, indicating that something else than chemistry is probably the bottleneck.<\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\"><span>&nbsp;<\/span>The<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\">three<\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\"><span>&nbsp;<\/span>following bars are all for the same, transient axisymmetric spray bomb case, using different chemistry sizes; Wang = 109 species, Lu = 188 species, Ahmed = 246 species. The speedup is higher the larger the mechanism.<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"ContextualSpellingAndGrammarError SCXW219623687\">Thus<\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\"><span>&nbsp;<\/span>usage of large chemistries is more accessible in v13.06.<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"ContextualSpellingAndGrammarError SCXW219623687\">Finally<\/span><\/span><span class=\"TextRun SCXW219623687\"><span class=\"NormalTextRun SCXW219623687\"><span>&nbsp;<\/span>the last bar shows a RANS simulation of a generic gas turbine with a 188 species mechanism. The massive speedup of 12x in this case indicates that the stiffness of the chemistry for this case is much better handled by the \u201csecret sauce\u201d in the updated solver.&nbsp;<\/span><\/span><span class=\"EOP SCXW219623687\" data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">&nbsp;<\/span><\/span><\/span><\/p>\n<p><span class=\"TextRun SCXW230977860\"><span class=\"NormalTextRun SCXW230977860\">With these updates,<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW230977860\"><span class=\"NormalTextRun SCXW230977860\">specifically thanks to the secret sauce added,<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW230977860\"><span class=\"NormalTextRun SCXW230977860\">we believe<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW230977860\"><span class=\"SpellingError SCXW230977860\">Simcenter<\/span><\/span><span class=\"TextRun SCXW230977860\"><span class=\"NormalTextRun SCXW230977860\"><span>&nbsp;<\/span>STAR-CCM+<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW230977860\"><span class=\"NormalTextRun SCXW230977860\">now<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW230977860\"><span class=\"NormalTextRun SCXW230977860\">has<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW230977860\"><span class=\"NormalTextRun SCXW230977860\">the <strong>fastest complex chemistry solver on the market<\/strong>..<\/span><\/span><span class=\"TextRun SCXW230977860\"><span class=\"NormalTextRun SCXW230977860\">!<\/span><\/span><span class=\"TextRun SCXW230977860\"><span class=\"NormalTextRun SCXW230977860\"><span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW230977860\"><span class=\"NormalTextRun SCXW230977860\">Be my guest and prove me wrong! Or right&#8230;<\/span><\/span>&nbsp;<\/p>\n<p><span class=\"TextRun SCXW208195287\"><span class=\"ContextualSpellingAndGrammarError SCXW208195287\">Of course<\/span><\/span><span class=\"TextRun SCXW208195287\"><span class=\"NormalTextRun SCXW208195287\"><span>&nbsp;<\/span>the new solver is verified to be as accurate (or even more accurate) than the previous version, as demonstrated in the plots below for ECN spray H.<\/span><\/span><\/p>\n<p><span class=\"EOP SCXW208195287\" data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\"><span class=\"lia-inline-image-display-wrapper lia-image-align-inline\" style=\"width: 966px;\"><img decoding=\"async\" src=\"http:\/\/blogs.sw.siemens.com\/wp-content\/uploads\/sites\/6\/2019\/09\/ECNresults2-1.png\" alt=\"ECNresults2.png\" title=\"ECNresults2.png\"><span class=\"lia-inline-image-caption\" onclick=\"event.preventDefault();\">Verification of results in v13.04 vs v13.06 for ECN spray H. Transient temperature trace as well as CO and n-heptane mass fraction profiles at a line 3.5 mm off axis at t=1ms are consistent.<\/span><\/span><\/span><\/p>\n<p><span class=\"EOP SCXW208195287\" data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\"><span class=\"TextRun SCXW97895273\"><span class=\"NormalTextRun SCXW97895273\">And\u2026 now you can even use<span>&nbsp;<\/span><\/span><\/span><em><span class=\"TextRun SCXW97895273\"><span class=\"NormalTextRun SCXW97895273\">huge<\/span><\/span><\/em><span class=\"TextRun SCXW97895273\"><span class=\"NormalTextRun SCXW97895273\"><span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW97895273\"><span class=\"NormalTextRun SCXW97895273\">chemistries<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW97895273\"><span class=\"NormalTextRun SCXW97895273\">in your CFD calculations, as demonstrated by the axisymmetric RANS of the ECN spray bomb below. This case was run with a<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW97895273\"><span class=\"NormalTextRun SCXW97895273\">detailed<\/span><\/span><span class=\"TextRun SCXW97895273\"><span class=\"NormalTextRun SCXW97895273\"><span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW97895273\"><span class=\"NormalTextRun SCXW97895273\">n-heptane chemistry from<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW97895273\"><span class=\"ContextualSpellingAndGrammarError SCXW97895273\">LLNL<\/span><\/span><span class=\"TextRun SCXW97895273\"><span class=\"ContextualSpellingAndGrammarError SCXW97895273\">[<\/span><\/span><span class=\"TextRun SCXW97895273\"><span class=\"NormalTextRun SCXW97895273\">9]<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW97895273\"><span class=\"NormalTextRun SCXW97895273\">of 697 species and 2987 reactions(!), using DMR as acceleration technique.<\/span><\/span><\/span><\/p>\n<p><span class=\"EOP SCXW208195287\" data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\"><span class=\"EOP SCXW97895273\" data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\"><\/span><\/span><\/p>\n<div class=\"lia-vid-container video-embed-center\">\n<div id=\"lia-vid-dmd3hjZzE6HfJQ1c1eq6mHUKV2s_N4E2w596h313r868\" class=\"lia-video-ooyala-player-container\"><\/div>\n<p><script>LITHIUM.OoyalaPlayer.addVideo('https:\/\/player.ooyala.com\/static\/v4\/production\/', 'lia-vid-dmd3hjZzE6HfJQ1c1eq6mHUKV2s_N4E2w596h313r868', 'dmd3hjZzE6HfJQ1c1eq6mHUKV2s_N4E2', {\"pcode\":\"sxdjkxOluLl_gSQrV57FiGraFE2-\",\"playerBrandingId\":\"ODI0MmQ3NjNhYWVjODliZTgzY2ZkMDdi\",\"width\":\"596px\",\"height\":\"313px\"});<\/script><a class=\"video-embed-link\" href=\"https:\/\/blogs.plm.automation.siemens.com\/t5\/video\/gallerypage\/video-id\/dmd3hjZzE6HfJQ1c1eq6mHUKV2s_N4E2\" target=\"_blank\" rel=\"noopener\">(view in My Videos)<\/a><\/p>\n<\/div>\n<p><span class=\"EOP SCXW208195287\" data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\"><span class=\"TextRun SCXW161312714\"><span class=\"NormalTextRun SCXW161312714\">And\u2026 As if that wasn\u2019t enough\u2026 The combustion table generation time for<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW161312714\"><span class=\"SpellingError SCXW161312714\">flamelet<\/span><\/span><span class=\"TextRun SCXW161312714\"><span class=\"NormalTextRun SCXW161312714\"><span>&nbsp;<\/span>combustion models is also significantly faster<\/span><\/span><span class=\"TextRun SCXW161312714\"><span class=\"NormalTextRun SCXW161312714\"><span>&nbsp;<\/span>in v13.06<\/span><\/span><span class=\"TextRun SCXW161312714\"><span class=\"NormalTextRun SCXW161312714\">, which makes usage of large chemistries more accessible. See the chart below for table generation times for 0D and 1D<span>&nbsp;<\/span><\/span><\/span><span class=\"TextRun SCXW161312714\"><span class=\"SpellingError SCXW161312714\">flamelet<\/span><\/span><span class=\"TextRun SCXW161312714\"><span class=\"NormalTextRun SCXW161312714\"><span>&nbsp;<\/span>tables for FGM. The table generation time for the 163 species mechanism has shrunk from the order of hours to the order of ten minutes!<\/span><\/span><\/span><\/p>\n<p><span class=\"EOP SCXW208195287\" data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\"><span class=\"EOP SCXW161312714\" data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\"><span class=\"lia-inline-image-display-wrapper lia-image-align-inline\" style=\"width: 874px;\"><img decoding=\"async\" src=\"http:\/\/blogs.sw.siemens.com\/wp-content\/uploads\/sites\/6\/2019\/09\/TableGenTimes-1.png\" alt=\"TableGenTimes.png\" title=\"TableGenTimes.png\"><span class=\"lia-inline-image-caption\" onclick=\"event.preventDefault();\">Speedup of FGM table generation in v13.06 vs v13.04<\/span><\/span><\/span><\/span><\/p>\n<p><span>So, now you can achieve more at the same time. But that\u2019s not it\u2026 To support the increasing need for LES combustion for accurate prediction of e.g.&nbsp;<\/span><span>thermoacoustic<\/span><span>&nbsp;instabilities and emissions, we have extended the Dynamic Thickened Flame model (TFM) in STAR-CCM+ to be compatible with complex chemistry as well as the efficient and accurate FGM&nbsp;<\/span><span>flamelet<\/span><span>&nbsp;combustion model.<\/span><\/p>\n<p><span>The FGM kinetic rate model and&nbsp;<\/span><span>c<\/span><span>omplex&nbsp;<\/span><span>c<\/span><span>hemistry are both most accurate when resolving the flame front on the CFD grid.&nbsp;<\/span><span>However<\/span><span>&nbsp;since the laminar flame thickness is typically in the order of 1 mm or less, this means impractically fine grids. The Dynamic Thickened Flame model (TFM) is a well-established technique to remedy this problem by artificially thickening the flame to be resolved on the actual grid. This typically gives a better flame position for premixed and partially premixed flames. The model is made compatible with both FGM and complex chemistry, to enable maximum impact at minimum time for the problem at hand. As a user you select the number of grid cells you want the flame to be refined on, and the model does the rest. For an example see&nbsp;<\/span><span>the LES simulation of&nbsp;<\/span><span>the Chen flame 3<\/span><span>&nbsp;[10]&nbsp;<\/span><span>below<\/span><span>,<\/span><span>&nbsp;using FGM kinetic rate vs FGM TFM.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">&nbsp;<\/span><\/p>\n<p><span class=\"EOP SCXW208195287\" data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\"><span class=\"EOP SCXW161312714\" data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">&nbsp;<\/span><\/span><\/p>\n<p><span class=\"EOP SCXW208195287\" data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\"><span class=\"EOP SCXW161312714\" data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\"><span class=\"lia-inline-image-display-wrapper lia-image-align-inline\" style=\"width: 999px;\"><img decoding=\"async\" src=\"http:\/\/blogs.sw.siemens.com\/wp-content\/uploads\/sites\/6\/2019\/09\/Chen-1.png\" alt=\"Chen.png\" title=\"Chen.png\"><span class=\"lia-inline-image-caption\" onclick=\"event.preventDefault();\">LES simulations of Chen Flame 3 [10], FGM kinetic rate vs FGM with dynamic thickened flame model<\/span><\/span><\/span><\/span><\/p>\n<p><span>Chen Flame 3<\/span><span>&nbsp;is a premixed methane lab flame with a pilot flame igniting the main fuel\/air mixture. The plots show temperature over radial direction for 4 measurement stations. As can be noted by measurement station 3 and 4, the flame length is better captured in TFM: The temperature at the axis is too high when using FGM Kinetic rate, meaning the flame is too short. In TFM the temperature profiles are very well captured.<\/span><\/p>\n<p><span>We hope these enhancements will help you become more efficient and effective in your design work. We want to learn whether these enhancements help you, so please don\u2019t hesitate to reach out to give feedback, or use the <em>Reactions, Combustion<\/em>&nbsp;Technical Forum group at the Steve Portal to tell us how it goes. Your input guides our future direction.<\/span><\/p>\n<p><span>Ps. Don\u2019t miss our recent blog on design&nbsp;<\/span><span>optimization<\/span><span>&nbsp;of rotary kilns and SNCR systems<\/span><span>&nbsp;<\/span><a href=\"https:\/\/community.plm.automation.siemens.com\/t5\/Simcenter-Blog\/Cementing-the-future-of-rotary-kilns-through-simulation-and\/ba-p\/528237\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"><span>here<\/span><\/a><span>.<\/span><\/p>\n<p><span>[1]&nbsp;<\/span><a href=\"http:\/\/www.sandia.gov\/TNF\/DataArch\/FlameD.html\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"><span>http:\/\/www.sandia.gov\/TNF\/DataArch\/FlameD.html<\/span><\/a><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:40,&quot;335559740&quot;:240}\">&nbsp;<\/span><\/p>\n<p><span>[2] Nakamura, T.,&nbsp;<\/span><span>Vandecamp<\/span><span>, W. L., Smart, J. P. Technical report, IFRF Doc No F 90\/Y\/7, 1990.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:40,&quot;335559740&quot;:240}\">&nbsp;<\/span><\/p>\n<p><span>[3]&nbsp;<\/span><span>Ver\u00edssimo<\/span><span>&nbsp;A. S., Rocha A. M. A., and Costa M, Energy &amp; Fuels 25 (6), pp 2469\u20132480 (2011)<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:40,&quot;335559740&quot;:240}\">&nbsp;<\/span><\/p>\n<p><a href=\"http:\/\/www.engr.uconn.edu\/~tlu\/mechs\/mechs.htm\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"><span>[4]&nbsp;<\/span><\/a><a href=\"http:\/\/www.engr.uconn.edu\/~tlu\/mechs\/mechs.htm\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"><span>https:\/\/ecn.sandia.gov\/<\/span><\/a><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:40,&quot;335559740&quot;:240}\">&nbsp;<\/span><\/p>\n<p><span>[5]&nbsp;<\/span><a href=\"http:\/\/combustion.berkeley.edu\/gri-mech\/version30\/text30.html\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"><span>http:\/\/combustion.berkeley.edu\/gri-mech\/version30\/text30.html<\/span><\/a><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:40,&quot;335559740&quot;:240}\">&nbsp;<\/span><\/p>\n<p><span>[6] Wang, H. Yao, M. Yue, Z. Jia, M. and Reitz, R. D. Combust. and Flame 162, pp. 2390 \u2013 2404 (2015)<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:40,&quot;335559740&quot;:240}\">&nbsp;<\/span><\/p>\n<p><span>[7]&nbsp;<\/span><a href=\"http:\/\/www.engr.uconn.edu\/~tlu\/mechs\/mechs.htm\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"><span>http:\/\/www.engr.uconn.edu\/~tlu\/mechs\/mechs.htm<\/span><\/a><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:40,&quot;335559740&quot;:240}\">&nbsp;<\/span><\/p>\n<p><span>[8] Ahmed, S.S.,&nbsp;<\/span><span>Mau\u00df<\/span><span>. F.,&nbsp;<\/span><span>Mor\u00e9ac<\/span><span>, G.,&nbsp;<\/span><span>Zeuch<\/span><span>, T., Phys. Chem. Chem. Phys., 9, 1107 \u2013 1126 (2007)<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:40,&quot;335559740&quot;:240}\">&nbsp;<\/span><\/p>\n<p><span>[9]&nbsp;<\/span><a href=\"https:\/\/combustion.llnl.gov\/mechanisms\/alkanes\/n-heptane-detailed-mechanism-version-3\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"><span>https:\/\/combustion.llnl.gov\/mechanisms\/alkanes\/n-heptane-detailed-mechanism-version-3<\/span><\/a><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:40,&quot;335559740&quot;:240}\">&nbsp;<\/span><\/p>\n<p><span>[10] Chen, Y. C., Peters, N., Schneemann, G. A., Wruck, N., Renz, U. Mansour, M. S., Combustion and Flame, 107:223-244 (1996)<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:40,&quot;335559740&quot;:240}\">&nbsp;<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Designing next generation combustion systems is a true challenge today, with stricter and stricter emission regulations, competitive pressure to deliver shorter time-to-market to stay ahead of compet&#8230;<\/p>\n","protected":false},"author":48653,"featured_media":2395,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"spanish_translation":"","french_translation":"","german_translation":"","italian_translation":"","polish_translation":"","japanese_translation":"","chinese_translation":"","footnotes":""},"categories":[1],"tags":[5,242],"industry":[89,150],"product":[],"coauthors":[],"class_list":["post-2382","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","tag-cae-simulation","tag-computational-fluid-dynamics-cfd","industry-automotive-transportation","industry-energy-utilities"],"featured_image_url":"https:\/\/blogs.sw.siemens.com\/wp-content\/uploads\/sites\/6\/2019\/09\/Chen-1.png","_links":{"self":[{"href":"https:\/\/blogs.sw.siemens.com\/simcenter\/wp-json\/wp\/v2\/posts\/2382","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.sw.siemens.com\/simcenter\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.sw.siemens.com\/simcenter\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/simcenter\/wp-json\/wp\/v2\/users\/48653"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/simcenter\/wp-json\/wp\/v2\/comments?post=2382"}],"version-history":[{"count":5,"href":"https:\/\/blogs.sw.siemens.com\/simcenter\/wp-json\/wp\/v2\/posts\/2382\/revisions"}],"predecessor-version":[{"id":19926,"href":"https:\/\/blogs.sw.siemens.com\/simcenter\/wp-json\/wp\/v2\/posts\/2382\/revisions\/19926"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/simcenter\/wp-json\/wp\/v2\/media\/2395"}],"wp:attachment":[{"href":"https:\/\/blogs.sw.siemens.com\/simcenter\/wp-json\/wp\/v2\/media?parent=2382"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/simcenter\/wp-json\/wp\/v2\/categories?post=2382"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/simcenter\/wp-json\/wp\/v2\/tags?post=2382"},{"taxonomy":"industry","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/simcenter\/wp-json\/wp\/v2\/industry?post=2382"},{"taxonomy":"product","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/simcenter\/wp-json\/wp\/v2\/product?post=2382"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/simcenter\/wp-json\/wp\/v2\/coauthors?post=2382"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}