{"id":"https://openalex.org/W4289139828","doi":"https://doi.org/10.25080/majora-212e5952-005","title":"Experience report of physics-informed neural networks in fluid simulations: pitfalls and frustration","display_name":"Experience report of physics-informed neural networks in fluid simulations: pitfalls and frustration","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4289139828","doi":"https://doi.org/10.25080/majora-212e5952-005"},"language":"en","primary_location":{"id":"doi:10.25080/majora-212e5952-005","is_oa":true,"landing_page_url":"https://doi.org/10.25080/majora-212e5952-005","pdf_url":"http://conference.scipy.org/proceedings/scipy2022/pdfs/PiYueh_Chuang.pdf","source":{"id":"https://openalex.org/S4220651651","display_name":"Proceedings of the Python in Science Conferences","issn_l":"2575-9752","issn":["2575-9752"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Python in Science Conference","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"http://conference.scipy.org/proceedings/scipy2022/pdfs/PiYueh_Chuang.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088269535","display_name":"Pi-Yueh Chuang","orcid":"https://orcid.org/0000-0001-6330-2709"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Pi-Yueh Chuang","raw_affiliation_strings":["Department of Mechanical and Aerospace Engineering, The George Wash-ington University, Washington, DC 20052, USA"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical and Aerospace Engineering, The George Wash-ington University, Washington, DC 20052, USA","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028603986","display_name":"Lorena A. Barba","orcid":"https://orcid.org/0000-0001-5812-2711"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lorena Barba","raw_affiliation_strings":["Department of Mechanical and Aerospace Engineering, The George Wash-ington University, Washington, DC 20052, USA"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical and Aerospace Engineering, The George Wash-ington University, Washington, DC 20052, USA","institution_ids":["https://openalex.org/I193531525"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5088269535"],"corresponding_institution_ids":["https://openalex.org/I193531525"],"apc_list":null,"apc_paid":null,"fwci":5.4764,"has_fulltext":false,"cited_by_count":46,"citation_normalized_percentile":{"value":0.96775743,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"28","last_page":"36"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12560","display_name":"Nuclear Engineering Thermal-Hydraulics","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10360","display_name":"Fluid Dynamics and Turbulent Flows","score":0.9894000291824341,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.6738756895065308},{"id":"https://openalex.org/keywords/computational-fluid-dynamics","display_name":"Computational fluid dynamics","score":0.5975899696350098},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.5963504910469055},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5640463829040527},{"id":"https://openalex.org/keywords/vortex","display_name":"Vortex","score":0.5426327586174011},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5201845169067383},{"id":"https://openalex.org/keywords/navier\u2013stokes-equations","display_name":"Navier\u2013Stokes equations","score":0.4880274832248688},{"id":"https://openalex.org/keywords/polygon-mesh","display_name":"Polygon mesh","score":0.4413134455680847},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.43937334418296814},{"id":"https://openalex.org/keywords/fluid-dynamics","display_name":"Fluid dynamics","score":0.43256449699401855},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.25376784801483154},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2420775294303894},{"id":"https://openalex.org/keywords/mechanics","display_name":"Mechanics","score":0.1561965048313141},{"id":"https://openalex.org/keywords/compressibility","display_name":"Compressibility","score":0.10372725129127502}],"concepts":[{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.6738756895065308},{"id":"https://openalex.org/C1633027","wikidata":"https://www.wikidata.org/wiki/Q815820","display_name":"Computational fluid dynamics","level":2,"score":0.5975899696350098},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.5963504910469055},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5640463829040527},{"id":"https://openalex.org/C140820882","wikidata":"https://www.wikidata.org/wiki/Q732722","display_name":"Vortex","level":2,"score":0.5426327586174011},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5201845169067383},{"id":"https://openalex.org/C2781278361","wikidata":"https://www.wikidata.org/wiki/Q201321","display_name":"Navier\u2013Stokes equations","level":3,"score":0.4880274832248688},{"id":"https://openalex.org/C31487907","wikidata":"https://www.wikidata.org/wiki/Q1154597","display_name":"Polygon mesh","level":2,"score":0.4413134455680847},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.43937334418296814},{"id":"https://openalex.org/C90278072","wikidata":"https://www.wikidata.org/wiki/Q216320","display_name":"Fluid dynamics","level":2,"score":0.43256449699401855},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.25376784801483154},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2420775294303894},{"id":"https://openalex.org/C57879066","wikidata":"https://www.wikidata.org/wiki/Q41217","display_name":"Mechanics","level":1,"score":0.1561965048313141},{"id":"https://openalex.org/C84655787","wikidata":"https://www.wikidata.org/wiki/Q8067817","display_name":"Compressibility","level":2,"score":0.10372725129127502},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.25080/majora-212e5952-005","is_oa":true,"landing_page_url":"https://doi.org/10.25080/majora-212e5952-005","pdf_url":"http://conference.scipy.org/proceedings/scipy2022/pdfs/PiYueh_Chuang.pdf","source":{"id":"https://openalex.org/S4220651651","display_name":"Proceedings of the Python in Science Conferences","issn_l":"2575-9752","issn":["2575-9752"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Python in Science Conference","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.25080/majora-212e5952-005","is_oa":true,"landing_page_url":"https://doi.org/10.25080/majora-212e5952-005","pdf_url":"http://conference.scipy.org/proceedings/scipy2022/pdfs/PiYueh_Chuang.pdf","source":{"id":"https://openalex.org/S4220651651","display_name":"Proceedings of the Python in Science Conferences","issn_l":"2575-9752","issn":["2575-9752"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Python in Science Conference","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4289139828.pdf","grobid_xml":"https://content.openalex.org/works/W4289139828.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W1490180844","https://openalex.org/W1634261337","https://openalex.org/W1970454553","https://openalex.org/W1988115241","https://openalex.org/W2006309046","https://openalex.org/W2027570878","https://openalex.org/W2036000326","https://openalex.org/W2062864628","https://openalex.org/W2065462230","https://openalex.org/W2072844193","https://openalex.org/W2085623372","https://openalex.org/W2158985775","https://openalex.org/W2749028154","https://openalex.org/W2806521165","https://openalex.org/W2899283552","https://openalex.org/W2899663614","https://openalex.org/W3014009018","https://openalex.org/W3118248754","https://openalex.org/W3133319347","https://openalex.org/W3200673624","https://openalex.org/W3203542838","https://openalex.org/W3205073660","https://openalex.org/W4220717841","https://openalex.org/W4286980132"],"related_works":["https://openalex.org/W3006027083","https://openalex.org/W2352639646","https://openalex.org/W2809988020","https://openalex.org/W4253695312","https://openalex.org/W2265619912","https://openalex.org/W2360943024","https://openalex.org/W2556915148","https://openalex.org/W204964826","https://openalex.org/W2146338266","https://openalex.org/W2990747292"],"abstract_inverted_index":{"Though":[0],"PINNs":[1],"(physics-informed":[2],"neural":[3],"networks)":[4],"are":[5,72],"now":[6],"deemed":[7],"as":[8,50,113],"a":[9,20,51,136,156,164,190],"complement":[10],"to":[11,24,53,131,182,207],"traditional":[12,54],"CFD":[13],"(computational":[14],"fluid":[15],"dynamics)":[16],"solvers":[17],"rather":[18],"than":[19,142],"replacement,":[21],"their":[22],"ability":[23],"solve":[25],"the":[26,45,65,100,127,133,150,171,185],"Navier-Stokes":[27,46],"equations":[28,47],"without":[29,199],"given":[30,201],"data":[31],"is":[32,188,205],"still":[33,189],"of":[34,43,122,135,195],"great":[35],"interest.":[36],"This":[37],"report":[38],"presents":[39],"our":[40,60,177],"not-so-successful":[41],"experiments":[42],"solving":[44,196],"with":[48,59,105],"PINN":[49,97,128,160,186,209],"replacement":[52],"solvers.":[55],"We":[56],"aim":[57],"to,":[58],"experiments,":[61],"prepare":[62],"readers":[63],"for":[64,126,211],"challenges":[66],"they":[67,71],"may":[68],"face":[69],"if":[70],"interested":[73],"in":[74,193,214],"data-free":[75],"PINN.":[76],"In":[77],"this":[78,111],"work,":[79],"we":[80,109,179],"used":[81,110],"two":[82],"standard":[83],"flow":[84,93,112,197],"problems:":[85],"2D":[86,91,101,146],"Taylor-Green":[87,102],"vortex":[88,103,172],"at":[89,94],"and":[90,108,116,167],"cylinder":[92,147],".":[95],"The":[96,145,159],"method":[98,161,187],"solved":[99],"problem":[104],"acceptable":[106],"results,":[107],"an":[114],"accuracy":[115,130,134],"performance":[117],"benchmark.":[118],"About":[119],"32":[120],"hours":[121],"training":[123],"were":[124],"required":[125],"method's":[129],"match":[132],"finite-difference":[137],"simulation,":[138],"which":[139],"took":[140],"less":[141],"20":[143],"seconds.":[144],"flow,":[148],"on":[149],"other":[151],"hand,":[152],"did":[153,168],"not":[154,169],"produce":[155],"physical":[157],"solution.":[158],"behaved":[162],"like":[163,181],"steady-flow":[165],"solver":[166],"capture":[170],"shedding":[173],"phenomenon.":[174],"By":[175],"sharing":[176],"experience,":[178],"would":[180],"emphasize":[183],"that":[184],"work-in-progress,":[191],"especially":[192],"terms":[194],"problems":[198,213],"any":[200],"data.":[202],"More":[203],"work":[204],"needed":[206],"make":[208],"feasible":[210],"real-world":[212],"such":[215],"applications.":[216],"(Reproducibility":[217],"package:":[218],"pi\\_yueh\\_chuang\\_2022\\_6592457.)":[219]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}