{"id":"https://openalex.org/W2092612581","doi":"https://doi.org/10.1137/s1064827503426693","title":"Combining Field Data and Computer Simulations for Calibration and Prediction","display_name":"Combining Field Data and Computer Simulations for Calibration and Prediction","publication_year":2004,"publication_date":"2004-01-01","ids":{"openalex":"https://openalex.org/W2092612581","doi":"https://doi.org/10.1137/s1064827503426693","mag":"2092612581"},"language":"en","primary_location":{"id":"doi:10.1137/s1064827503426693","is_oa":false,"landing_page_url":"https://doi.org/10.1137/s1064827503426693","pdf_url":null,"source":{"id":"https://openalex.org/S165512578","display_name":"SIAM Journal on Scientific Computing","issn_l":"1064-8275","issn":["1064-8275","1095-7197"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Scientific Computing","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/A5020809586","display_name":"Dave Higdon","orcid":null},"institutions":[{"id":"https://openalex.org/I1343871089","display_name":"Los Alamos National Laboratory","ror":"https://ror.org/01e41cf67","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I1343871089","https://openalex.org/I198811213","https://openalex.org/I4210120050"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Dave Higdon","raw_affiliation_strings":["LOS Alamos National Laboratory"],"affiliations":[{"raw_affiliation_string":"LOS Alamos National Laboratory","institution_ids":["https://openalex.org/I1343871089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028735740","display_name":"Marc C. Kennedy","orcid":"https://orcid.org/0000-0001-7497-5394"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marc Kennedy","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027543885","display_name":"James C. Cavendish","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"James C. Cavendish","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091283009","display_name":"John A. Cafeo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"John A. Cafeo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5044559226","display_name":"Robert D. Ryne","orcid":"https://orcid.org/0000-0001-8199-6839"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Robert D. Ryne","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5020809586"],"corresponding_institution_ids":["https://openalex.org/I1343871089"],"apc_list":null,"apc_paid":null,"fwci":12.9762,"has_fulltext":false,"cited_by_count":630,"citation_normalized_percentile":{"value":0.98963169,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"26","issue":"2","first_page":"448","last_page":"466"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13126","display_name":"Scientific Research and Discoveries","score":0.9961000084877014,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/computer-science","display_name":"Computer science","score":0.6346251368522644},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.5864166617393494},{"id":"https://openalex.org/keywords/physical-system","display_name":"Physical system","score":0.5605258941650391},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.5332422256469727},{"id":"https://openalex.org/keywords/uncertainty-analysis","display_name":"Uncertainty analysis","score":0.5306239128112793},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5265218019485474},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5265087485313416},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5200971364974976},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.5176277756690979},{"id":"https://openalex.org/keywords/uncertainty-quantification","display_name":"Uncertainty quantification","score":0.4973914921283722},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.4689936935901642},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.45442771911621094},{"id":"https://openalex.org/keywords/sensitivity-analysis","display_name":"Sensitivity analysis","score":0.4409610331058502},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.43951547145843506},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.43527740240097046},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.43097811937332153},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3647245168685913},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.33405885100364685},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.26195308566093445},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19708868861198425},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1809130311012268},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15871375799179077},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.15738406777381897}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6346251368522644},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.5864166617393494},{"id":"https://openalex.org/C116672817","wikidata":"https://www.wikidata.org/wiki/Q1454986","display_name":"Physical system","level":2,"score":0.5605258941650391},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.5332422256469727},{"id":"https://openalex.org/C177803969","wikidata":"https://www.wikidata.org/wiki/Q29205","display_name":"Uncertainty analysis","level":2,"score":0.5306239128112793},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5265218019485474},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5265087485313416},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5200971364974976},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.5176277756690979},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.4973914921283722},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.4689936935901642},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.45442771911621094},{"id":"https://openalex.org/C176147448","wikidata":"https://www.wikidata.org/wiki/Q1889114","display_name":"Sensitivity analysis","level":3,"score":0.4409610331058502},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.43951547145843506},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.43527740240097046},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.43097811937332153},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3647245168685913},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.33405885100364685},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.26195308566093445},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19708868861198425},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1809130311012268},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15871375799179077},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.15738406777381897},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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:10.1137/s1064827503426693","is_oa":false,"landing_page_url":"https://doi.org/10.1137/s1064827503426693","pdf_url":null,"source":{"id":"https://openalex.org/S165512578","display_name":"SIAM Journal on Scientific Computing","issn_l":"1064-8275","issn":["1064-8275","1095-7197"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Scientific Computing","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":32,"referenced_works":["https://openalex.org/W55912154","https://openalex.org/W1973333099","https://openalex.org/W1977046327","https://openalex.org/W1984550626","https://openalex.org/W1985093013","https://openalex.org/W1988446510","https://openalex.org/W1988684120","https://openalex.org/W2018044188","https://openalex.org/W2018840457","https://openalex.org/W2026170388","https://openalex.org/W2030033341","https://openalex.org/W2038669746","https://openalex.org/W2049588492","https://openalex.org/W2053934160","https://openalex.org/W2056760934","https://openalex.org/W2069993596","https://openalex.org/W2077428996","https://openalex.org/W2083027289","https://openalex.org/W2100320591","https://openalex.org/W2116413426","https://openalex.org/W2126453481","https://openalex.org/W2130416410","https://openalex.org/W2167928328","https://openalex.org/W2168464387","https://openalex.org/W2786093300","https://openalex.org/W2795739367","https://openalex.org/W2904816695","https://openalex.org/W4239273814","https://openalex.org/W4251644969","https://openalex.org/W4253525948","https://openalex.org/W4292403327","https://openalex.org/W4292890447"],"related_works":["https://openalex.org/W2116089868","https://openalex.org/W4249135812","https://openalex.org/W93577605","https://openalex.org/W1991803138","https://openalex.org/W2033170585","https://openalex.org/W4387046439","https://openalex.org/W3128892391","https://openalex.org/W1983007452","https://openalex.org/W2115703496","https://openalex.org/W2124353633"],"abstract_inverted_index":{"We":[0,147],"develop":[1],"a":[2,17,27,32,73,149,172,185,190],"statistical":[3],"approach":[4,77],"for":[5,81,90,142],"characterizing":[6],"uncertainty":[7,68,91,115],"in":[8,116],"predictions":[9,135],"that":[10,69,100,120],"are":[11],"made":[12],"with":[13,72],"the":[14,22,48,58,67,82,96,107,111,117,122,127,163],"aid":[15],"of":[16,34,44,98,145,162],"computer":[18,23],"simulation":[19,24,108],"model.":[20],"Typically,":[21],"code":[25,109],"models":[26,157],"physical":[28,50,113,129],"system":[29,51],"and":[30,37,61,110,136,152,189],"requires":[31],"set":[33],"inputs---some":[35],"known":[36],"specified,":[38],"others":[39],"unknown.":[40],"A":[41],"limited":[42],"amount":[43],"field":[45,124],"data":[46,125],"from":[47],"true":[49,128],"is":[52,70,168,180],"available":[53],"to":[54,63,93,158,182],"inform":[55,64],"us":[56,65],"about":[57,66],"unknown":[59,160],"inputs":[60,86],"also":[62],"associated":[71,138],"simulation-based":[74],"prediction.":[75],"The":[76,131,166],"given":[78],"here":[79],"allows":[80],"following:uncertainty":[83],"regarding":[84],"model":[85,159,164],"(i.e.,":[87],"calibration);":[88],"accounting":[89,141],"due":[92],"limitations":[94],"on":[95,126,154],"number":[97],"simulations":[99],"can":[101],"be":[102],"carried":[103,169],"out;":[104],"discrepancy":[105],"between":[106],"actual":[112,123],"system;":[114],"observation":[118],"process":[119,156],"yields":[121,134],"system.":[130],"resulting":[132],"analysis":[133],"their":[137],"uncertainties":[139],"while":[140],"multiple":[143],"sources":[144],"uncertainty.":[146],"use":[148],"Bayesian":[150],"formulation":[151],"rely":[153],"Gaussian":[155],"functions":[161],"inputs.":[165],"estimation":[167],"out":[170],"using":[171],"Markov":[173],"chain":[174],"Monte":[175],"Carlo":[176],"method.":[177],"This":[178],"methodology":[179],"applied":[181],"two":[183],"examples:":[184],"charged":[186],"particle":[187],"accelerator":[188],"spot":[191],"welding":[192],"process.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":12},{"year":2025,"cited_by_count":23},{"year":2024,"cited_by_count":30},{"year":2023,"cited_by_count":38},{"year":2022,"cited_by_count":37},{"year":2021,"cited_by_count":36},{"year":2020,"cited_by_count":38},{"year":2019,"cited_by_count":37},{"year":2018,"cited_by_count":52},{"year":2017,"cited_by_count":50},{"year":2016,"cited_by_count":33},{"year":2015,"cited_by_count":36},{"year":2014,"cited_by_count":43},{"year":2013,"cited_by_count":32},{"year":2012,"cited_by_count":36}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}