{"id":"https://openalex.org/W2043790261","doi":"https://doi.org/10.2514/6.2006-1997","title":"Statistical Methods for Model Validation under Uncertainty","display_name":"Statistical Methods for Model Validation under Uncertainty","publication_year":2006,"publication_date":"2006-05-01","ids":{"openalex":"https://openalex.org/W2043790261","doi":"https://doi.org/10.2514/6.2006-1997","mag":"2043790261"},"language":"en","primary_location":{"id":"doi:10.2514/6.2006-1997","doi":"https://doi.org/10.2514/6.2006-1997","is_oa":false,"landing_page_url":"https://doi.org/10.2514/6.2006-1997","pdf_url":null,"source":{"id":"https://openalex.org/S4306499481","display_name":"AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference (SDM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"47th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference&amp;lt;BR&amp;gt; 14th AIAA/ASME/AHS Adaptive Structures Conference&amp;lt;BR&amp;gt; 7th","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5049537061","display_name":"Ramesh Rebba","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I118136607","display_name":"General Motors (United States)","ror":"https://ror.org/05addee68","country_code":"US","type":"company","lineage":["https://openalex.org/I118136607"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ramesh Rebba","raw_affiliation_strings":["GM R&D","General Motors,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"GM R&D","institution_ids":[]},{"raw_affiliation_string":"General Motors,","institution_ids":["https://openalex.org/I118136607"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089894989","display_name":"Sankaran Mahadevan","orcid":"https://orcid.org/0000-0003-1969-2388","observed_orcids":["https://orcid.org/0000-0003-1969-2388"]},"institutions":[{"id":"https://openalex.org/I200719446","display_name":"Vanderbilt University","ror":"https://ror.org/02vm5rt34","country_code":"US","type":"education","lineage":["https://openalex.org/I200719446"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sankaran Mahadevan","raw_affiliation_strings":["Vanderbilt University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Vanderbilt University","institution_ids":["https://openalex.org/I200719446"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.1842,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.83636364,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"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/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9487000107765198,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9487000107765198,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10780","display_name":"Reliability and Maintenance Optimization","score":0.011599999852478504,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T11890","display_name":"Scientific Measurement and Uncertainty Evaluation","score":0.004600000102072954,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/model-validation","display_name":"model validation","score":0.996999979019165},{"id":"https://openalex.org/keywords/model-uncertainty","display_name":"model uncertainty","score":0.949999988079071},{"id":"https://openalex.org/keywords/bayesian-hypothesis-testing","display_name":"Bayesian hypothesis testing","score":0.843999981880188},{"id":"https://openalex.org/keywords/reliability-estimation","display_name":"reliability estimation","score":0.7260000109672546},{"id":"https://openalex.org/keywords/limited-experimental-data","display_name":"limited experimental data","score":0.6919999718666077}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6379290819168091},{"id":"https://openalex.org/C3019813237","wikidata":"https://www.wikidata.org/wiki/Q65089264","display_name":"Model validation","level":2,"score":0.5139948725700378},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.44678887724876404},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3223334550857544},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.26409488916397095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26173174381256104},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13209927082061768}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2514/6.2006-1997","doi":"https://doi.org/10.2514/6.2006-1997","is_oa":false,"landing_page_url":"https://doi.org/10.2514/6.2006-1997","pdf_url":null,"source":{"id":"https://openalex.org/S4306499481","display_name":"AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference (SDM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"47th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference&amp;lt;BR&amp;gt; 14th AIAA/ASME/AHS Adaptive Structures Conference&amp;lt;BR&amp;gt; 7th","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320338291","display_name":"Sandia National Laboratories","ror":"https://ror.org/01apwpt12"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W26653269","https://openalex.org/W101144848","https://openalex.org/W642357447","https://openalex.org/W1533179050","https://openalex.org/W1977505379","https://openalex.org/W1990010868","https://openalex.org/W1993725118","https://openalex.org/W2005913644","https://openalex.org/W2006650224","https://openalex.org/W2019420194","https://openalex.org/W2028963199","https://openalex.org/W2045816034","https://openalex.org/W2076930812","https://openalex.org/W2086083509","https://openalex.org/W2092612581","https://openalex.org/W2126163471","https://openalex.org/W2286788253","https://openalex.org/W4238306122","https://openalex.org/W4299431800"],"related_works":["https://openalex.org/W2027873958","https://openalex.org/W2231949697","https://openalex.org/W2321165763","https://openalex.org/W2962732683","https://openalex.org/W7204960807","https://openalex.org/W2045816034","https://openalex.org/W2317295776","https://openalex.org/W7163152987","https://openalex.org/W91654077","https://openalex.org/W31324185"],"abstract_inverted_index":{"*\u2020":[0],"Model":[1],"uncertainties":[2],"and":[3,53,95],"limited":[4],"experimental":[5],"data":[6],"in":[7],"many":[8],"engineering":[9],"applications":[10],"make":[11],"the":[12,30,34],"model":[13,71,79],"validation":[14,72],"essentially":[15],"a":[16,63,74],"statistical":[17,23,55],"exercise.":[18],"This":[19],"paper":[20],"investigates":[21],"various":[22],"methods":[24,92],"to":[25,33,41],"quantitatively":[26],"assess":[27],"how":[28],"close":[29],"prediction":[31],"is":[32,39,67,82],"observation.":[35],"Interval-based":[36],"hypothesis":[37,49],"testing":[38],"found":[40],"be":[42],"more":[43,64],"practically":[44],"useful":[45],"than":[46],"point":[47],"null":[48],"testing.":[50],"Both":[51],"classical":[52],"Bayesian":[54],"techniques":[56],"are":[57,93],"implemented":[58],"for":[59,84],"this":[60],"purpose.":[61],"Also,":[62],"direct":[65],"approach":[66],"proposed":[68,91],"by":[69],"formulating":[70],"as":[73],"reliability":[75,80],"estimation":[76],"problem.":[77],"The":[78,90],"metric":[81],"extended":[83],"validating":[85],"models":[86],"with":[87],"multivariate":[88],"outputs.":[89],"illustrated":[94],"compared":[96],"using":[97],"numerical":[98],"examples.":[99]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-10-06T10:28:23.643775","created_date":"2016-06-24T00:00:00"}
