{"id":"https://openalex.org/W7155030458","doi":"https://doi.org/10.48550/arxiv.2604.18438","title":"Scalable Physics-Informed Neural Differential Equations and Data-Driven Algorithms for HVAC Systems","display_name":"Scalable Physics-Informed Neural Differential Equations and Data-Driven Algorithms for HVAC Systems","publication_year":2026,"publication_date":"2026-04-20","ids":{"openalex":"https://openalex.org/W7155030458","doi":"https://doi.org/10.48550/arxiv.2604.18438"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.18438","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.18438","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.2604.18438","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016292174","display_name":"Hanfeng Zhai","orcid":"https://orcid.org/0000-0003-1511-7597"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhai, Hanfeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134165703","display_name":"Hongtao Qiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiao, Hongtao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134134868","display_name":"Hassan Mansour","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mansour, Hassan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5069430909","display_name":"Christopher R. Laughman","orcid":"https://orcid.org/0000-0002-8540-2249"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Laughman, Christopher","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":0.9848999977111816,"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":0.9848999977111816,"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/T11416","display_name":"Numerical methods for differential equations","score":0.0019000000320374966,"subfield":{"id":"https://openalex.org/subfields/2612","display_name":"Numerical Analysis"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.0008999999845400453,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.692300021648407},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5828999876976013},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5813000202178955},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5286999940872192},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.5027999877929688},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.47440001368522644},{"id":"https://openalex.org/keywords/ordinary-differential-equation","display_name":"Ordinary differential equation","score":0.453900009393692},{"id":"https://openalex.org/keywords/hvac","display_name":"HVAC","score":0.43799999356269836},{"id":"https://openalex.org/keywords/differential-equation","display_name":"Differential equation","score":0.39320001006126404}],"concepts":[{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.692300021648407},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6525999903678894},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5828999876976013},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5813000202178955},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5432000160217285},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5286999940872192},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.5027999877929688},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.47440001368522644},{"id":"https://openalex.org/C51544822","wikidata":"https://www.wikidata.org/wiki/Q465274","display_name":"Ordinary differential equation","level":3,"score":0.453900009393692},{"id":"https://openalex.org/C122346748","wikidata":"https://www.wikidata.org/wiki/Q1798773","display_name":"HVAC","level":3,"score":0.43799999356269836},{"id":"https://openalex.org/C78045399","wikidata":"https://www.wikidata.org/wiki/Q11214","display_name":"Differential equation","level":2,"score":0.39320001006126404},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.3691999912261963},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.35989999771118164},{"id":"https://openalex.org/C50897621","wikidata":"https://www.wikidata.org/wiki/Q2665508","display_name":"Hybrid system","level":2,"score":0.35089999437332153},{"id":"https://openalex.org/C133512626","wikidata":"https://www.wikidata.org/wiki/Q787371","display_name":"Automatic differentiation","level":3,"score":0.3449000120162964},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3343000113964081},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.3149000108242035},{"id":"https://openalex.org/C93226319","wikidata":"https://www.wikidata.org/wiki/Q193137","display_name":"Differential (mechanical device)","level":2,"score":0.3009999990463257},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.3005000054836273},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2872999906539917},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.27549999952316284},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.2687999904155731},{"id":"https://openalex.org/C186219872","wikidata":"https://www.wikidata.org/wiki/Q955889","display_name":"Differential algebraic equation","level":4,"score":0.2630000114440918},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.258899986743927},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.25060001015663147},{"id":"https://openalex.org/C77405623","wikidata":"https://www.wikidata.org/wiki/Q598451","display_name":"System dynamics","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.18438","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.18438","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.2604.18438","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.18438","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":[{"score":0.6933297514915466,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2,122,152],"scalable,":[3],"data-driven":[4],"simulation":[5,145],"framework":[6],"for":[7,112],"large-scale":[8],"heating,":[9],"ventilation,":[10],"and":[11,49,76,91,100,103,133,155],"air":[12],"conditioning":[13],"(HVAC)":[14],"systems":[15,158],"that":[16,42,93],"couples":[17],"physics-informed":[18,56],"neural":[19],"ordinary":[20],"differential":[21],"equations":[22],"(PINODEs)":[23],"with":[24,73,87,159],"differential-algebraic":[25],"equation":[26],"(DAE)":[27],"solvers.":[28],"At":[29,79],"the":[30,80,137],"component":[31],"level,":[32,82],"we":[33,83,104,120],"learn":[34],"heat-exchanger":[35],"dynamics":[36],"using":[37],"an":[38],"implicit":[39],"PINODE":[40],"formulation":[41],"predicts":[43],"conserved":[44],"quantities":[45],"(refrigerant":[46],"mass":[47],"$M_r$":[48],"internal":[50],"energy":[51],"$E_\\text{hx}$)":[52],"as":[53],"outputs,":[54],"enabling":[55],"training":[57],"via":[58],"automatic":[59],"differentiation":[60],"of":[61],"mass/energy":[62],"balances.":[63],"Stable":[64],"long-horizon":[65],"prediction":[66],"is":[67],"achieved":[68],"through":[69],"gradient-stabilized":[70],"latent":[71],"evolution":[72],"gated":[74],"architectures":[75],"layer":[77],"normalization.":[78],"system":[81],"integrate":[84],"learned":[85],"components":[86],"DAE":[88],"solvers":[89],"(IDA":[90],"DASSL)":[92],"explicitly":[94],"enforce":[95],"junction":[96],"constraints":[97],"(pressure":[98],"equilibrium":[99],"mass-flow":[101],"consistency),":[102],"use":[105],"Bayesian":[106],"optimization":[107],"to":[108,157,161],"tune":[109],"solver":[110],"parameters":[111],"accuracy--efficiency":[113],"trade-offs.":[114],"To":[115],"reduce":[116],"residual":[117],"system-level":[118],"bias,":[119],"introduce":[121],"lightweight":[123],"corrector":[124],"network":[125,135],"trained":[126],"on":[127],"short":[128],"trajectory":[129],"segments.":[130],"Across":[131],"dual-compressor":[132],"scaled":[134],"studies,":[136],"proposed":[138],"approach":[139],"attains":[140],"multi-fold":[141],"speedups":[142],"over":[143],"high-fidelity":[144],"while":[146],"keeping":[147],"errors":[148],"low":[149],"(MAPE":[150],"below":[151],"few":[153],"percent)":[154],"scales":[156],"up":[160],"16":[162],"compressor-condenser":[163],"pairs.":[164]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-22T00:00:00"}
