{"id":"https://openalex.org/W7162012497","doi":"https://doi.org/10.48550/arxiv.2605.20303","title":"AirfoilGen: A valid-by-construction and performance-aware latent diffusion model for airfoil generation","display_name":"AirfoilGen: A valid-by-construction and performance-aware latent diffusion model for airfoil generation","publication_year":2026,"publication_date":"2026-05-19","ids":{"openalex":"https://openalex.org/W7162012497","doi":"https://doi.org/10.48550/arxiv.2605.20303"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.20303","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20303","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.20303","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101838602","display_name":"Zhijie Yang","orcid":"https://orcid.org/0000-0002-0731-303X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Zhijie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136647962","display_name":"Min Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Min","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136690080","display_name":"Qiang Zou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Du, Peng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Zou, Qiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zou, Qiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.6323000192642212,"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":0.6323000192642212,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.09719999879598618,"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"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.08330000191926956,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/airfoil","display_name":"Airfoil","score":0.9484999775886536},{"id":"https://openalex.org/keywords/aerodynamics","display_name":"Aerodynamics","score":0.6545000076293945},{"id":"https://openalex.org/keywords/controllability","display_name":"Controllability","score":0.45969998836517334},{"id":"https://openalex.org/keywords/aerodynamic-center","display_name":"Aerodynamic center","score":0.3864000141620636},{"id":"https://openalex.org/keywords/lift","display_name":"Lift (data mining)","score":0.38600000739097595},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.3644999861717224},{"id":"https://openalex.org/keywords/drag","display_name":"Drag","score":0.329800009727478}],"concepts":[{"id":"https://openalex.org/C112124176","wikidata":"https://www.wikidata.org/wiki/Q4698744","display_name":"Airfoil","level":2,"score":0.9484999775886536},{"id":"https://openalex.org/C13393347","wikidata":"https://www.wikidata.org/wiki/Q8424","display_name":"Aerodynamics","level":2,"score":0.6545000076293945},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.460999995470047},{"id":"https://openalex.org/C48209547","wikidata":"https://www.wikidata.org/wiki/Q1331104","display_name":"Controllability","level":2,"score":0.45969998836517334},{"id":"https://openalex.org/C147334340","wikidata":"https://www.wikidata.org/wiki/Q1229549","display_name":"Aerodynamic center","level":5,"score":0.3864000141620636},{"id":"https://openalex.org/C139002025","wikidata":"https://www.wikidata.org/wiki/Q3001212","display_name":"Lift (data mining)","level":2,"score":0.38600000739097595},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36629998683929443},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.3644999861717224},{"id":"https://openalex.org/C72921944","wikidata":"https://www.wikidata.org/wiki/Q206621","display_name":"Drag","level":2,"score":0.329800009727478},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.32420000433921814},{"id":"https://openalex.org/C60053565","wikidata":"https://www.wikidata.org/wiki/Q1021159","display_name":"Camber (aerodynamics)","level":2,"score":0.31869998574256897},{"id":"https://openalex.org/C107157880","wikidata":"https://www.wikidata.org/wiki/Q845727","display_name":"Lift-to-drag ratio","level":3,"score":0.2996000051498413},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.2874999940395355},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.2727999985218048},{"id":"https://openalex.org/C103838597","wikidata":"https://www.wikidata.org/wiki/Q1579556","display_name":"Transonic","level":3,"score":0.2727999985218048},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2700999975204468},{"id":"https://openalex.org/C111582010","wikidata":"https://www.wikidata.org/wiki/Q7310811","display_name":"Relative wind","level":4,"score":0.2678999900817871},{"id":"https://openalex.org/C72898154","wikidata":"https://www.wikidata.org/wiki/Q458038","display_name":"Flight envelope","level":3,"score":0.25679999589920044},{"id":"https://openalex.org/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"score":0.25220000743865967},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.20303","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20303","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.20303","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20303","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8288748264312744}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Airfoil":[0],"shape":[1],"design":[2],"is":[3,168],"a":[4,11,26,75,87,125,129,139,160],"fundamental":[5],"task":[6],"in":[7,39,124],"aerospace":[8],"engineering,":[9],"with":[10,196,208],"direct":[12],"impact":[13],"on":[14,64],"flight":[15],"stability":[16],"and":[17,43,57,77,119,138,180,201],"fuel":[18],"consumption.":[19],"Deep":[20],"learning":[21],"has":[22],"recently":[23],"emerged":[24],"as":[25],"promising":[27],"tool":[28],"for":[29,82,183],"this":[30,71,157],"task,":[31],"but":[32],"existing":[33],"deep":[34,186],"generative":[35,99,187],"approaches":[36],"remain":[37],"limited":[38],"both":[40],"geometric":[41,199],"validity":[42,200],"physical":[44],"controllability.":[45],"They":[46],"offer":[47],"little":[48],"control":[49,113],"over":[50,114,164],"the":[51,92,98,172],"generated":[52],"shapes,":[53],"yielding":[54],"invalid":[55],"geometries,":[56],"they":[58],"typically":[59],"do":[60],"not":[61],"condition":[62],"effectively":[63],"aerodynamic":[65,115,153,202],"performance.":[66,154],"To":[67],"address":[68],"these":[69,147],"issues,":[70],"paper":[72,158],"proposes":[73],"AirfoilGen,":[74],"valid-by-construction":[76],"performance-aware":[78],"latent":[79,127,148],"diffusion":[80,141],"model":[81,131,142],"airfoil.":[83],"It":[84,109],"first":[85],"introduces":[86],"novel":[88],"airfoil":[89,107,133,176,194],"representation":[90],"scheme,":[91],"circle":[93],"sweeping":[94],"representation,":[95],"to":[96],"constrain":[97],"process":[100],"so":[101],"that":[102,191],"output":[103],"shapes":[104,134],"respect":[105],"essential":[106],"characteristics.":[108],"then":[110],"enables":[111,193],"explicit":[112],"performance":[116,203],"(e.g.,":[117],"lift":[118],"drag":[120],"coefficients)":[121],"by":[122],"operating":[123],"learned":[126],"space:":[128],"transformer":[130],"encodes":[132],"into":[135,146],"vector":[136],"embeddings,":[137],"conditional":[140],"denoises":[143],"Gaussian":[144],"noise":[145],"embeddings":[149],"while":[150],"incorporating":[151],"target":[152],"In":[155],"addition,":[156],"presents":[159],"new":[161],"dataset":[162,177],"of":[163,213],"200,000":[165],"airfoils,":[166],"which":[167],"substantially":[169],"larger":[170],"than":[171,205],"widely":[173],"used":[174],"UIUC":[175],"(1,650":[178],"airfoils)":[179],"more":[181],"suitable":[182],"training":[184],"modern":[185],"models.":[188],"Experiments":[189],"demonstrate":[190],"AirfoilGen":[192],"generation":[195],"far":[197],"greater":[198],"controllability":[204],"previously":[206],"achievable,":[207],"an":[209],"average":[210],"performance-conditioning":[211],"accuracy":[212],"98.41%.":[214]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-22T00:00:00"}
