{"id":5299,"date":"2021-12-15T04:00:00","date_gmt":"2021-12-08T13:21:35","guid":{"rendered":"https:\/\/www.ibs.re.kr\/bimag\/?post_type=tribe_events&#038;p=5299"},"modified":"2021-12-14T16:09:33","modified_gmt":"2021-12-14T07:09:33","slug":"2021-12-15","status":"publish","type":"tribe_events","link":"https:\/\/www.ibs.re.kr\/bimag\/event\/2021-12-15\/","title":{"rendered":"Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics"},"content":{"rendered":"<p>We will discuss about \u201cStiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics\u201d, Ji et al., <em>The Journal of Physical Chemistry A<\/em>, 2020<\/p>\n<p>The recently developed physics-informed neural network (PINN) has achieved success in many science and engineering disciplines by encoding physics laws into the loss functions of the neural network such that the network not only conforms to the measurements and initial and boundary conditions but also satisfies the governing equations. This work first investigates the performance of the PINN in solving stiff chemical kinetic problems with governing equations of stiff ordinary differential equations (ODEs). The results elucidate the challenges of utilizing the PINN in stiff ODE systems. Consequently, we employ quasi-steady-state assumption (QSSA) to reduce the stiffness of the ODE systems, and the PINN then can be successfully applied to the converted non-\/mild-stiff systems. Therefore, the results suggest that stiffness could be the major reason for the failure of the regular PINN in the studied stiff chemical kinetic systems. The developed stiff-PINN approach that utilizes QSSA to enable the PINN to solve stiff chemical kinetics shall open the possibility of applying the PINN to various reaction-diffusion systems involving stiff dynamics.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We will discuss about \u201cStiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics\u201d, Ji et al., The Journal of Physical Chemistry A, 2020 The recently developed physics-informed neural network (PINN) has &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/www.ibs.re.kr\/bimag\/event\/2021-12-15\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics&#8221;<\/span><\/a><\/p>\n","protected":false},"author":3,"featured_media":0,"template":"","meta":{"_editorskit_title_hidden":false,"_editorskit_reading_time":0,"_editorskit_is_block_options_detached":false,"_editorskit_block_options_position":"{}","_uag_custom_page_level_css":"","_tribe_events_status":"","_tribe_events_status_reason":"","footnotes":""},"tags":[],"tribe_events_cat":[219],"class_list":["post-5299","tribe_events","type-tribe_events","status-publish","hentry","tribe_events_cat-journal-club","cat_journal-club"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics - Biomedical Mathematics Group<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.ibs.re.kr\/bimag\/event\/2021-12-15\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics - Biomedical Mathematics Group\" \/>\n<meta property=\"og:description\" content=\"We will discuss about \u201cStiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics\u201d, Ji et al., The Journal of Physical Chemistry A, 2020 The recently developed physics-informed neural network (PINN) has &hellip; 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Continue reading \"Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics\"","og_url":"https:\/\/www.ibs.re.kr\/bimag\/event\/2021-12-15\/","og_site_name":"Biomedical Mathematics Group","article_modified_time":"2021-12-14T07:09:33+00:00","twitter_card":"summary_large_image","twitter_misc":{"Est. reading time":"1 minute"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/www.ibs.re.kr\/bimag\/event\/2021-12-15\/","url":"https:\/\/www.ibs.re.kr\/bimag\/event\/2021-12-15\/","name":"Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics - Biomedical Mathematics Group","isPartOf":{"@id":"https:\/\/www.ibs.re.kr\/bimag\/#website"},"datePublished":"2021-12-08T13:21:35+00:00","dateModified":"2021-12-14T07:09:33+00:00","breadcrumb":{"@id":"https:\/\/www.ibs.re.kr\/bimag\/event\/2021-12-15\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.ibs.re.kr\/bimag\/event\/2021-12-15\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/www.ibs.re.kr\/bimag\/event\/2021-12-15\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/www.ibs.re.kr\/bimag\/"},{"@type":"ListItem","position":2,"name":"Events","item":"https:\/\/www.ibs.re.kr\/bimag\/events\/"},{"@type":"ListItem","position":3,"name":"Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics"}]},{"@type":"WebSite","@id":"https:\/\/www.ibs.re.kr\/bimag\/#website","url":"https:\/\/www.ibs.re.kr\/bimag\/","name":"Biomedical Mathematics Group","description":"\uae30\ucd08\uacfc\ud559\uc5f0\uad6c\uc6d0 \uc758\uc0dd\uba85\uc218\ud559\uadf8\ub8f9","publisher":{"@id":"https:\/\/www.ibs.re.kr\/bimag\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.ibs.re.kr\/bimag\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/www.ibs.re.kr\/bimag\/#organization","name":"IBS Biomedical Mathematics Group","url":"https:\/\/www.ibs.re.kr\/bimag\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.ibs.re.kr\/bimag\/#\/schema\/logo\/image\/","url":"https:\/\/www.ibs.re.kr\/bimag\/cms\/wp-content\/uploads\/2021\/02\/ibs-circle-1.png","contentUrl":"https:\/\/www.ibs.re.kr\/bimag\/cms\/wp-content\/uploads\/2021\/02\/ibs-circle-1.png","width":250,"height":250,"caption":"IBS Biomedical Mathematics Group"},"image":{"@id":"https:\/\/www.ibs.re.kr\/bimag\/#\/schema\/logo\/image\/"}}]}},"uagb_featured_image_src":{"full":false,"thumbnail":false,"medium":false,"medium_large":false,"large":false,"1536x1536":false,"2048x2048":false,"dimag-thumbnail":false,"twentyseventeen-featured-image":false,"twentyseventeen-thumbnail-avatar":false},"uagb_author_info":{"display_name":"BIMAG","author_link":"https:\/\/www.ibs.re.kr\/bimag\/author\/hphongblog\/"},"uagb_comment_info":0,"uagb_excerpt":"We will discuss about \u201cStiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics\u201d, Ji et al., The Journal of Physical Chemistry A, 2020 The recently developed physics-informed neural network (PINN) has &hellip; 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