{"id":"https://openalex.org/W4414397405","doi":"https://doi.org/10.2514/1.i011638","title":"System Identification of an Advanced Geared Turbofan Model Using Neural Networks","display_name":"System Identification of an Advanced Geared Turbofan Model Using Neural Networks","publication_year":2025,"publication_date":"2025-09-22","ids":{"openalex":"https://openalex.org/W4414397405","doi":"https://doi.org/10.2514/1.i011638"},"language":"en","primary_location":{"id":"doi:10.2514/1.i011638","is_oa":false,"landing_page_url":"https://doi.org/10.2514/1.i011638","pdf_url":null,"source":{"id":"https://openalex.org/S4210240151","display_name":"Journal of Aerospace Information Systems","issn_l":"2327-3097","issn":["2327-3097"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315709","host_organization_name":"American Institute of Aeronautics and Astronautics","host_organization_lineage":["https://openalex.org/P4310315709"],"host_organization_lineage_names":["American Institute of Aeronautics and Astronautics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Aerospace Information Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036780186","display_name":"Gabriel Adriano de Melo","orcid":"https://orcid.org/0000-0001-5878-7967"},"institutions":[{"id":"https://openalex.org/I107428990","display_name":"Instituto Tecnol\u00f3gico de Aeron\u00e1utica","ror":"https://ror.org/05vh67662","country_code":"BR","type":"education","lineage":["https://openalex.org/I107428990"]},{"id":"https://openalex.org/I13805885","display_name":"Vaughn College of Aeronautics and Technology","ror":"https://ror.org/056e22e24","country_code":"US","type":"education","lineage":["https://openalex.org/I13805885"]}],"countries":["BR","US"],"is_corresponding":false,"raw_author_name":"Gabriel A. Melo","raw_affiliation_strings":["Aeronautics Institute of Technology"],"raw_orcid":"https://orcid.org/0000-0001-5878-7967","affiliations":[{"raw_affiliation_string":"Aeronautics Institute of Technology","institution_ids":["https://openalex.org/I107428990","https://openalex.org/I13805885"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018345920","display_name":"Joaquim N. Dias","orcid":"https://orcid.org/0000-0002-6495-4263"},"institutions":[{"id":"https://openalex.org/I82497590","display_name":"Auburn University","ror":"https://ror.org/02v80fc35","country_code":"US","type":"education","lineage":["https://openalex.org/I82497590"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joaquim N. Dias","raw_affiliation_strings":["Auburn University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Auburn University","institution_ids":["https://openalex.org/I82497590"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17548131,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":"12","first_page":"1043","last_page":"1065"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11372","display_name":"Hydraulic and Pneumatic Systems","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11372","display_name":"Hydraulic and Pneumatic Systems","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T10117","display_name":"Advanced Combustion Engine Technologies","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/1507","display_name":"Fluid Flow and Transfer Processes"},"field":{"id":"https://openalex.org/fields/15","display_name":"Chemical Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11202","display_name":"Cavitation Phenomena in Pumps","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/turbofan","display_name":"Turbofan","score":0.9362999796867371},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7279999852180481},{"id":"https://openalex.org/keywords/throttle","display_name":"Throttle","score":0.6549000144004822},{"id":"https://openalex.org/keywords/turbine","display_name":"Turbine","score":0.5831999778747559},{"id":"https://openalex.org/keywords/system-identification","display_name":"System identification","score":0.5454000234603882},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.47940000891685486},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.45249998569488525}],"concepts":[{"id":"https://openalex.org/C110050840","wikidata":"https://www.wikidata.org/wiki/Q654051","display_name":"Turbofan","level":2,"score":0.9362999796867371},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7279999852180481},{"id":"https://openalex.org/C72971556","wikidata":"https://www.wikidata.org/wiki/Q961356","display_name":"Throttle","level":2,"score":0.6549000144004822},{"id":"https://openalex.org/C2778449969","wikidata":"https://www.wikidata.org/wiki/Q130760","display_name":"Turbine","level":2,"score":0.5831999778747559},{"id":"https://openalex.org/C119247159","wikidata":"https://www.wikidata.org/wiki/Q1366192","display_name":"System identification","level":3,"score":0.5454000234603882},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.491100013256073},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.48010000586509705},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.47940000891685486},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.4595000147819519},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.45249998569488525},{"id":"https://openalex.org/C2780799671","wikidata":"https://www.wikidata.org/wiki/Q17087362","display_name":"Transient (computer programming)","level":2,"score":0.40529999136924744},{"id":"https://openalex.org/C77405623","wikidata":"https://www.wikidata.org/wiki/Q598451","display_name":"System dynamics","level":2,"score":0.3537999987602234},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.34459999203681946},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3037000000476837},{"id":"https://openalex.org/C107645828","wikidata":"https://www.wikidata.org/wiki/Q12070446","display_name":"System model","level":2,"score":0.2944999933242798},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28459998965263367},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2766000032424927},{"id":"https://openalex.org/C93226319","wikidata":"https://www.wikidata.org/wiki/Q193137","display_name":"Differential (mechanical device)","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.2547999918460846},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.25060001015663147}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2514/1.i011638","is_oa":false,"landing_page_url":"https://doi.org/10.2514/1.i011638","pdf_url":null,"source":{"id":"https://openalex.org/S4210240151","display_name":"Journal of Aerospace Information Systems","issn_l":"2327-3097","issn":["2327-3097"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315709","host_organization_name":"American Institute of Aeronautics and Astronautics","host_organization_lineage":["https://openalex.org/P4310315709"],"host_organization_lineage_names":["American Institute of Aeronautics and Astronautics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Aerospace Information Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W26752759","https://openalex.org/W1988101164","https://openalex.org/W2009061689","https://openalex.org/W2019428117","https://openalex.org/W2023861497","https://openalex.org/W2042743986","https://openalex.org/W2054073919","https://openalex.org/W2064675550","https://openalex.org/W2076063813","https://openalex.org/W2077144648","https://openalex.org/W2110996650","https://openalex.org/W2145629157","https://openalex.org/W2728711348","https://openalex.org/W2919115771","https://openalex.org/W2954561314","https://openalex.org/W2963587345","https://openalex.org/W2990138404","https://openalex.org/W3008968441","https://openalex.org/W3044794661","https://openalex.org/W3177828909","https://openalex.org/W3187020323","https://openalex.org/W4229368250","https://openalex.org/W4231552808","https://openalex.org/W4295298952","https://openalex.org/W4299733614","https://openalex.org/W4321106573","https://openalex.org/W4362470436"],"related_works":[],"abstract_inverted_index":{"Gas":[0],"turbines":[1],"exhibit":[2],"nonlinearities":[3],"in":[4,63,198],"both":[5,155],"steady-state":[6],"and":[7,37,104,125,132,141,160,190],"transient":[8],"operations,":[9],"which":[10],"also":[11],"vary":[12],"throughout":[13],"the":[14,20,64,79,88,114,149,156,165,174,186],"flight":[15,199],"envelope.":[16],"This":[17,183],"work":[18,184],"addresses":[19],"challenge":[21],"of":[22,81,117,168,188],"obtaining":[23],"a":[24,59,68,99,105],"high-fidelity":[25,60],"simulation":[26,200],"model":[27,50,70,181],"without":[28],"requiring":[29],"detailed":[30],"knowledge":[31],"about":[32],"individual":[33],"gas":[34,195],"turbine":[35,123,196],"components":[36],"assumes":[38],"that":[39,148],"only":[40,137],"input\u2013output":[41],"data":[42,57],"are":[43],"available.":[44],"Two":[45],"approaches":[46],"were":[47,95],"employed":[48],"to":[49],"an":[51],"advanced":[52],"geared":[53],"turbofan":[54],"engine":[55],"using":[56,73,136],"from":[58],"simulation.":[61],"First,":[62],"system":[65,157,176],"identification":[66,158,177],"approach,":[67,90],"quasi-steady":[69],"was":[71,111],"derived":[72],"multivariate":[74],"orthogonal":[75],"functions,":[76],"followed":[77],"by":[78,170],"estimation":[80],"dynamic":[82],"parameters":[83],"during":[84],"throttle":[85,142],"transients.":[86],"In":[87],"second":[89],"different":[91],"neural":[92,106,150,162],"network":[93],"architectures":[94],"tested:":[96],"feed-forward":[97],"layers,":[98],"long":[100],"short-term":[101],"memory":[102],"architecture,":[103],"differential":[107,151],"architecture.":[108],"Model":[109],"performance":[110],"quantified":[112],"through":[113],"prediction":[115],"accuracy":[116],"five":[118],"outputs":[119],"(fuel":[120],"flow,":[121],"thrust,":[122],"temperature,":[124],"shaft":[126],"rotational":[127],"speeds":[128],"[Formula:":[129,133],"see":[130,134],"text]":[131],"text])":[135],"altitude,":[138],"Mach":[139],"number,":[140],"as":[143],"inputs.":[144],"The":[145],"results":[146],"demonstrate":[147],"architecture":[152],"significantly":[153],"outperforms":[154],"method":[159,178],"other":[161],"approaches,":[163],"reducing":[164],"standard":[166],"deviations":[167],"residuals":[169],"80%\u201390%":[171],"compared":[172],"with":[173],"conventional":[175],"across":[179],"all":[180],"outputs.":[182],"advances":[185],"understanding":[187],"classical":[189],"deep":[191],"learning":[192],"methodologies":[193],"for":[194],"modeling":[197],"applications.":[201]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
