{"id":"https://openalex.org/W4226227621","doi":"https://doi.org/10.1109/tase.2022.3158204","title":"A Deep-Learning-Based Surrogate Model for Thermal Signature Prediction in Laser Metal Deposition","display_name":"A Deep-Learning-Based Surrogate Model for Thermal Signature Prediction in Laser Metal Deposition","publication_year":2022,"publication_date":"2022-03-28","ids":{"openalex":"https://openalex.org/W4226227621","doi":"https://doi.org/10.1109/tase.2022.3158204"},"language":"en","primary_location":{"id":"doi:10.1109/tase.2022.3158204","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2022.3158204","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Automation Science and Engineering","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/A5010845074","display_name":"Shenghan Guo","orcid":"https://orcid.org/0000-0002-2159-6128"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shenghan Guo","raw_affiliation_strings":["School of Manufacturing Systems and Networks, Arizona State University, Mesa, AZ, USA"],"affiliations":[{"raw_affiliation_string":"School of Manufacturing Systems and Networks, Arizona State University, Mesa, AZ, USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054810335","display_name":"Weihong Guo","orcid":"https://orcid.org/0000-0001-8433-6326"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weihong Guo","raw_affiliation_strings":["Department of Industrial and Systems Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038634061","display_name":"Linkan Bian","orcid":"https://orcid.org/0000-0002-5057-6599"},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Linkan Bian","raw_affiliation_strings":["Department of Industrial and Systems Engineering, Mississippi State University, Starkville, MS, USA"],"affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, Mississippi State University, Starkville, MS, USA","institution_ids":["https://openalex.org/I99041443"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017592135","display_name":"Y. B. Guo","orcid":"https://orcid.org/0000-0001-9497-6802"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Y. B. Guo","raw_affiliation_strings":["Department of Mechanical and Aerospace Engineering and the New Jersey Advanced Engineering Institute, Rutgers, The State University of New Jersey, Piscataway, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical and Aerospace Engineering and the New Jersey Advanced Engineering Institute, Rutgers, The State University of New Jersey, Piscataway, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5010845074"],"corresponding_institution_ids":["https://openalex.org/I55732556"],"apc_list":null,"apc_paid":null,"fwci":2.3876,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.8817157,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"20","issue":"1","first_page":"482","last_page":"494"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10705","display_name":"Additive Manufacturing Materials and Processes","score":0.9998999834060669,"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/T10705","display_name":"Additive Manufacturing Materials and Processes","score":0.9998999834060669,"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/T10783","display_name":"Additive Manufacturing and 3D Printing Technologies","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9876999855041504,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/transient","display_name":"Transient (computer programming)","score":0.6576223969459534},{"id":"https://openalex.org/keywords/thermal","display_name":"Thermal","score":0.5967943668365479},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5627773404121399},{"id":"https://openalex.org/keywords/signature","display_name":"Signature (topology)","score":0.5571392774581909},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5494638085365295},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5428824424743652},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5046678781509399},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.4714330732822418},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.45673489570617676},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.45365893840789795},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4331439435482025},{"id":"https://openalex.org/keywords/deposition","display_name":"Deposition (geology)","score":0.43245142698287964},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42888689041137695},{"id":"https://openalex.org/keywords/nanotechnology","display_name":"Nanotechnology","score":0.23329243063926697},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2173101007938385},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.13557446002960205},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.11007201671600342},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0976424515247345}],"concepts":[{"id":"https://openalex.org/C2780799671","wikidata":"https://www.wikidata.org/wiki/Q17087362","display_name":"Transient (computer programming)","level":2,"score":0.6576223969459534},{"id":"https://openalex.org/C204530211","wikidata":"https://www.wikidata.org/wiki/Q752823","display_name":"Thermal","level":2,"score":0.5967943668365479},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5627773404121399},{"id":"https://openalex.org/C2779696439","wikidata":"https://www.wikidata.org/wiki/Q7512811","display_name":"Signature (topology)","level":2,"score":0.5571392774581909},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5494638085365295},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5428824424743652},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5046678781509399},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.4714330732822418},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.45673489570617676},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.45365893840789795},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4331439435482025},{"id":"https://openalex.org/C64297162","wikidata":"https://www.wikidata.org/wiki/Q1987070","display_name":"Deposition (geology)","level":3,"score":0.43245142698287964},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42888689041137695},{"id":"https://openalex.org/C171250308","wikidata":"https://www.wikidata.org/wiki/Q11468","display_name":"Nanotechnology","level":1,"score":0.23329243063926697},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2173101007938385},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.13557446002960205},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.11007201671600342},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0976424515247345},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C2816523","wikidata":"https://www.wikidata.org/wiki/Q180184","display_name":"Sediment","level":2,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tase.2022.3158204","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2022.3158204","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Automation Science and Engineering","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":60,"referenced_works":["https://openalex.org/W292268285","https://openalex.org/W1522301498","https://openalex.org/W1969831389","https://openalex.org/W1997733123","https://openalex.org/W2079451707","https://openalex.org/W2099471712","https://openalex.org/W2125389028","https://openalex.org/W2146149961","https://openalex.org/W2147632348","https://openalex.org/W2159218886","https://openalex.org/W2293174830","https://openalex.org/W2337490972","https://openalex.org/W2342910067","https://openalex.org/W2381790605","https://openalex.org/W2416486912","https://openalex.org/W2587706859","https://openalex.org/W2593414223","https://openalex.org/W2606292481","https://openalex.org/W2610394307","https://openalex.org/W2734129016","https://openalex.org/W2762092659","https://openalex.org/W2772940940","https://openalex.org/W2782924686","https://openalex.org/W2787223504","https://openalex.org/W2798706078","https://openalex.org/W2808062989","https://openalex.org/W2886032578","https://openalex.org/W2895008327","https://openalex.org/W2898116879","https://openalex.org/W2915627018","https://openalex.org/W2949939488","https://openalex.org/W2950776302","https://openalex.org/W2952745707","https://openalex.org/W2956238283","https://openalex.org/W2963021791","https://openalex.org/W2963163163","https://openalex.org/W2963306805","https://openalex.org/W2963584589","https://openalex.org/W2963768110","https://openalex.org/W2963784072","https://openalex.org/W2963800363","https://openalex.org/W2986485969","https://openalex.org/W2997893499","https://openalex.org/W2999509561","https://openalex.org/W3025171962","https://openalex.org/W3027367393","https://openalex.org/W3138753100","https://openalex.org/W3159275571","https://openalex.org/W4213251304","https://openalex.org/W4249968406","https://openalex.org/W4294596616","https://openalex.org/W4320013936","https://openalex.org/W6631190155","https://openalex.org/W6678815747","https://openalex.org/W6720691552","https://openalex.org/W6729482032","https://openalex.org/W6734209382","https://openalex.org/W6743259963","https://openalex.org/W6748086406","https://openalex.org/W7053616676"],"related_works":["https://openalex.org/W3000097931","https://openalex.org/W2354322770","https://openalex.org/W4237547500","https://openalex.org/W1570848052","https://openalex.org/W2373192430","https://openalex.org/W4239268388","https://openalex.org/W1537496349","https://openalex.org/W2379407973","https://openalex.org/W4243305035","https://openalex.org/W2125195795"],"abstract_inverted_index":{"Laser":[0],"metal":[1,10],"deposition":[2,123],"(LMD)":[3],"is":[4,87,155,228,294,303],"an":[5,134,287],"additive":[6],"manufacturing":[7],"method":[8,180,219,367],"for":[9,53,68,79,113,133,170,223,302,323],"parts":[11],"by":[12,261,353],"using":[13],"focused":[14],"thermal":[15,27,33,49,69,105,115,131,141,224,240,244,276,284,314,321,350,358,393],"energy":[16],"to":[17,99,159,195,274,299,312],"fuse":[18],"materials":[19],"as":[20,30],"they":[21,72],"are":[22,76,181],"deposited.":[23],"During":[24],"LMD,":[25,148],"transient":[26,48,104,167],"signatures":[28,50,106,132,241,245,277,285,315,322,351],"such":[29,47],"the":[31,103,114,122,145,161,171,178,188,211,235,255,268,296,304,327,336,339,349,356,365,373,380,385,389],"in-situ":[32],"images":[34,112],"of":[35,46,62,117,129,166,177,190,238,258,286,379],"melt":[36,118,168,381],"pool,":[37,382],"contain":[38],"rich":[39],"information":[40,209],"about":[41,210,267],"process":[42,54,204,212,369,391],"performance.":[43],"Early":[44],"prediction":[45,128],"provides":[51],"opportunities":[52],"monitoring":[55],"and":[56,75,101,175,214,242,392],"defect":[57],"prevention.":[58],"While":[59],"physics-based":[60],"models":[61],"LMD":[63,189,200,390],"have":[64,73,202,344],"been":[65],"conventionally":[66],"used":[67],"signature":[70,225],"prediction,":[71],"limitations":[74],"computationally":[77],"expensive":[78],"real-time":[80,203],"prediction.":[81,226],"A":[82],"scalable,":[83],"efficient":[84],"data-science-based":[85],"model":[86,110,232],"therefore":[88],"needed.":[89],"This":[90],"paper":[91],"develops":[92],"a":[93,149,184,229],"deep-learning-based":[94,230],"surrogate":[95,231],"model,":[96],"called":[97],"LMD-cGAN,":[98],"predict":[100,275],"emulate":[102,313],"in":[107,147,183,252,278,316],"LMD.":[108],"The":[109,173,217,248],"generates":[111,243],"dynamics":[116],"pool":[119,169],"conditionally":[120],"on":[121,138,187,282],"layer.":[124],"It":[125],"enables":[126],"early":[127],"future-layer":[130],"in-process":[135,288,297],"part":[136,215,289,298,337],"based":[137,281],"its":[139],"early-layer":[140,283,374],"signatures.":[142,394],"To":[143,319],"respect":[144],"physics":[146],"physics-guided":[150],"image":[151],"selection":[152],"(PGIS)":[153],"mechanism":[154,251],"integrated":[156],"with":[157,333,361],"LMD-cGAN":[158,227,253,270,307,354],"calibrate":[160],"predictions":[162,260],"against":[163,264],"physical":[164,256,265,363],"benchmarks":[165],"process.":[172,269],"effectiveness":[174],"efficiency":[176],"proposed":[179,218,249,366],"demonstrated":[182],"case":[185],"study":[186],"Ti-4Al-6V":[191],"thin-walled":[192],"structures.":[193],"Note":[194],"Practitioners\u2014With":[196],"online":[197],"sensing,":[198],"many":[199],"applications":[201],"data":[205,222,329,340],"that":[206,233,295],"convey":[207],"valuable":[208],"status":[213],"quality.":[216],"leverages":[220],"these":[221,259],"learns":[234],"population":[236],"profile":[237],"real":[239],"from":[246,372],"there.":[247],"PGIS":[250],"ensures":[254],"validity":[257],"benchmarking":[262],"them":[263],"insights":[266],"can":[271,308],"be":[272,300,310,331],"applied":[273,311],"future":[279],"layers":[280],"(an":[290],"implicit":[291],"assumption":[292],"here":[293],"predicted":[301],"same":[305],"type).":[306],"also":[309],"specific":[317],"layers.":[318],"generate":[320],"generic,":[324],"non-defect":[325],"parts,":[326],"training":[328],"should":[330,343],"selected":[332],"caution":[334],"\u2013":[335],"where":[338],"were":[341],"collected":[342],"no":[345],"obvious":[346],"defects,":[347],"so":[348],"generated":[352],"show":[355],"regular":[357],"dynamics.":[359],"Compared":[360],"pure":[362],"models,":[364],"incorporates":[368],"uncertainties":[370],"captured":[371],"data,":[375],"hence":[376],"\u201con-the-fly\u201d":[377],"emulation":[378],"while":[383],"characterizing":[384],"inherent":[386],"relationship":[387],"between":[388]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}