{"id":"https://openalex.org/W4411101374","doi":"https://doi.org/10.32604/cmc.2025.065648","title":"Physics-Informed Gaussian Process Regression with Bayesian Optimization for Laser Welding Quality Control in Coaxial Laser Diodes","display_name":"Physics-Informed Gaussian Process Regression with Bayesian Optimization for Laser Welding Quality Control in Coaxial Laser Diodes","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4411101374","doi":"https://doi.org/10.32604/cmc.2025.065648"},"language":"en","primary_location":{"id":"doi:10.32604/cmc.2025.065648","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.065648","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.32604/cmc.2025.065648","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100348411","display_name":"Ziyang Wang","orcid":"https://orcid.org/0000-0003-3452-9167"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ziyang Wang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070210507","display_name":"Lian Duan","orcid":"https://orcid.org/0000-0003-2750-0972"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lian Duan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033704273","display_name":"Lei Kuang","orcid":"https://orcid.org/0000-0002-3415-3748"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lei Kuang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101909512","display_name":"Haibo Zhou","orcid":"https://orcid.org/0000-0002-9571-1416"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haibo Zhou","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5025725446","display_name":"Ji\u2019an Duan","orcid":"https://orcid.org/0000-0001-5104-3148"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ji\u2019an Duan","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100348411"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4595,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.80878045,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"84","issue":"2","first_page":"2587","last_page":"2604"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10834","display_name":"Welding Techniques and Residual Stresses","score":0.9902999997138977,"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/T10834","display_name":"Welding Techniques and Residual Stresses","score":0.9902999997138977,"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/T11583","display_name":"Advanced Measurement and Metrology Techniques","score":0.9793000221252441,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9736999869346619,"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/coaxial","display_name":"Coaxial","score":0.678575336933136},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.5766925811767578},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5467343330383301},{"id":"https://openalex.org/keywords/laser","display_name":"Laser","score":0.5449491739273071},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5412826538085938},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.5206438899040222},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4958232343196869},{"id":"https://openalex.org/keywords/welding","display_name":"Welding","score":0.4564502239227295},{"id":"https://openalex.org/keywords/diode","display_name":"Diode","score":0.4362153112888336},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.43556904792785645},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.43206435441970825},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3636539578437805},{"id":"https://openalex.org/keywords/optoelectronics","display_name":"Optoelectronics","score":0.3320167660713196},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.31237247586250305},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.25945258140563965},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.24380365014076233},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1959930658340454},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.13425812125205994},{"id":"https://openalex.org/keywords/quantum-mechanics","display_name":"Quantum mechanics","score":0.11079758405685425},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.09378895163536072}],"concepts":[{"id":"https://openalex.org/C51221625","wikidata":"https://www.wikidata.org/wiki/Q1751466","display_name":"Coaxial","level":2,"score":0.678575336933136},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.5766925811767578},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5467343330383301},{"id":"https://openalex.org/C520434653","wikidata":"https://www.wikidata.org/wiki/Q38867","display_name":"Laser","level":2,"score":0.5449491739273071},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5412826538085938},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.5206438899040222},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4958232343196869},{"id":"https://openalex.org/C19474535","wikidata":"https://www.wikidata.org/wiki/Q131172","display_name":"Welding","level":2,"score":0.4564502239227295},{"id":"https://openalex.org/C78434282","wikidata":"https://www.wikidata.org/wiki/Q11656","display_name":"Diode","level":2,"score":0.4362153112888336},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.43556904792785645},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.43206435441970825},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3636539578437805},{"id":"https://openalex.org/C49040817","wikidata":"https://www.wikidata.org/wiki/Q193091","display_name":"Optoelectronics","level":1,"score":0.3320167660713196},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.31237247586250305},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.25945258140563965},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.24380365014076233},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1959930658340454},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.13425812125205994},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.11079758405685425},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.09378895163536072},{"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:10.32604/cmc.2025.065648","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.065648","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32604/cmc.2025.065648","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.065648","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.6399999856948853,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1970280031","https://openalex.org/W1996181848","https://openalex.org/W2018670577","https://openalex.org/W2019371381","https://openalex.org/W2091651498","https://openalex.org/W2769791151","https://openalex.org/W2783796248","https://openalex.org/W2791109005","https://openalex.org/W2807172002","https://openalex.org/W3082409364","https://openalex.org/W4214869066","https://openalex.org/W4224238278","https://openalex.org/W4283791637","https://openalex.org/W4308994170","https://openalex.org/W4367186520","https://openalex.org/W4380244364","https://openalex.org/W4389113435","https://openalex.org/W4390536085","https://openalex.org/W4390699022","https://openalex.org/W4391573224","https://openalex.org/W4393948775","https://openalex.org/W4397290534","https://openalex.org/W4399504798","https://openalex.org/W4399842555"],"related_works":["https://openalex.org/W3104422856","https://openalex.org/W4206864338","https://openalex.org/W4287867179","https://openalex.org/W566010457","https://openalex.org/W2600092203","https://openalex.org/W4293503520","https://openalex.org/W4300066510","https://openalex.org/W4406204722","https://openalex.org/W2056958800","https://openalex.org/W4210726438"],"abstract_inverted_index":{"The":[0,188],"packaging":[1,23],"quality":[2],"of":[3,31,88,102],"coaxial":[4],"laser":[5,26],"diodes":[6],"(CLDs)":[7],"plays":[8],"a":[9,62,111,152],"pivotal":[10],"role":[11],"in":[12],"determining":[13],"their":[14],"optical":[15,36,48,107,147,185,193],"performance":[16],"and":[17,47,56,65,184,201],"long-term":[18],"reliability.":[19],"As":[20],"the":[21,40,86,100,127,142,173],"core":[22],"process,":[24],"high-precision":[25,146],"welding":[27,45,70,89,182,190],"requires":[28],"precise":[29],"control":[30],"process":[32,113],"parameters":[33,46,90,183,191],"to":[34,84,91,106],"suppress":[35],"power":[37,49,108,148,186,194],"loss.":[38,109,187],"However,":[39],"complex":[41],"nonlinear":[42],"relationship":[43],"between":[44,181],"loss":[50,149,195],"renders":[51],"traditional":[52],"trial-and-error":[53],"methods":[54],"inefficient":[55],"imprecise.":[57],"To":[58],"address":[59],"this":[60],"challenge,":[61],"physics-informed":[63,132],"(PI)":[64],"data-driven":[66],"collaboration":[67],"approach":[68],"for":[69,164,204],"parameter":[71,166],"optimization":[72,154],"is":[73],"proposed.":[74],"First,":[75],"thermal-fluid-solid":[76],"coupling":[77],"finite":[78,118],"element":[79,119],"method":[80,175],"(FEM)":[81],"was":[82,123,162],"employed":[83],"quantify":[85],"sensitivity":[87],"physical":[92,179],"characteristics,":[93],"including":[94],"residual":[95],"stress.":[96],"This":[97],"analysis":[98],"facilitated":[99],"identification":[101],"critical":[103],"factors":[104],"contributing":[105],"Subsequently,":[110],"Gaussian":[112],"regression":[114],"(GPR)":[115],"model":[116],"incorporating":[117],"simulation":[120],"prior":[121],"knowledge":[122],"constructed":[124],"based":[125],"on":[126],"selected":[128],"features.":[129],"By":[130],"introducing":[131],"kernel":[133],"(PIK)":[134],"functions,":[135],"stress":[136],"distribution":[137],"patterns":[138],"were":[139],"embedded":[140],"into":[141],"prediction":[143],"model,":[144],"achieving":[145],"prediction.":[150],"Finally,":[151],"Bayesian":[153],"(BO)":[155],"algorithm":[156],"with":[157],"an":[158],"adaptive":[159],"sampling":[160],"strategy":[161],"implemented":[163],"efficient":[165],"space":[167],"exploration.":[168],"Experimental":[169],"results":[170],"demonstrate":[171],"that":[172],"proposed":[174],"effectively":[176],"establishes":[177],"explicit":[178],"correlations":[180],"optimized":[189],"reduced":[192],"by":[196],"34.1%,":[197],"providing":[198],"theoretical":[199],"guidance":[200],"technical":[202],"support":[203],"reliable":[205],"CLD":[206],"packaging.":[207]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-02-28T09:26:25.869077","created_date":"2025-10-10T00:00:00"}