{"id":"https://openalex.org/W135841311","doi":null,"title":"Uncertainty quantification with experimental data and complex system models","display_name":"Uncertainty quantification with experimental data and complex system models","publication_year":2010,"publication_date":"2010-01-01","ids":{"openalex":"https://openalex.org/W135841311","mag":"135841311"},"language":"en","primary_location":{"id":"pmh:qt5d01s25c","doi":null,"is_oa":true,"landing_page_url":"http://www.escholarship.org/uc/item/5d01s25c","pdf_url":"http://www.escholarship.org/uc/item/5d01s25c","source":{"id":"https://openalex.org/S4306400115","display_name":"eScholarship (California Digital Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2801248553","host_organization_name":"California Digital Library","host_organization_lineage":["https://openalex.org/I2801248553"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Russi, Trent Michael. (2010). Uncertainty Quantification with Experimental Data and Complex System Models. UC Berkeley: Mechanical Engineering. Retrieved from: http://www.escholarship.org/uc/item/5d01s25c","raw_type":"dissertation"},"volume":null,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://www.escholarship.org/uc/item/5d01s25c","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017044098","display_name":"Trent Russi","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Trent Russi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5017044098"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":80,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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":0.8047000169754028,"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":0.8047000169754028,"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/T11236","display_name":"Control Systems and Identification","score":0.07400000095367432,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.025699999183416367,"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/uncertainty-quantification","display_name":"uncertainty quantification","score":0.9909999966621399},{"id":"https://openalex.org/keywords/parameter-estimation","display_name":"parameter estimation","score":0.4740000069141388},{"id":"https://openalex.org/keywords/lagrangian-dual","display_name":"Lagrangian dual","score":0.7319999933242798},{"id":"https://openalex.org/keywords/sensitivity-analysis","display_name":"sensitivity analysis","score":0.8429999947547913},{"id":"https://openalex.org/keywords/active-subspaces","display_name":"active subspaces","score":0.7770000100135803},{"id":"https://openalex.org/keywords/surrogate-modeling","display_name":"surrogate models","score":0.8289999961853027},{"id":"https://openalex.org/keywords/experimental-design","display_name":"experimental design","score":0.7350000143051147},{"id":"https://openalex.org/keywords/polynomial-optimization","display_name":"polynomial optimization","score":0.7960000038146973},{"id":"https://openalex.org/keywords/combustion-chemistry","display_name":"combustion chemistry","score":0.6819999814033508},{"id":"https://openalex.org/keywords/biological-models","display_name":"biological models","score":0.593999981880188}],"concepts":[{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5881205201148987},{"id":"https://openalex.org/C73684929","wikidata":"https://www.wikidata.org/wiki/Q598870","display_name":"Lagrange multiplier","level":2,"score":0.5277020931243896},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.49736812710762024},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4775027632713318},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.4754970967769623},{"id":"https://openalex.org/C81845259","wikidata":"https://www.wikidata.org/wiki/Q290117","display_name":"Quadratic programming","level":2,"score":0.4623938798904419},{"id":"https://openalex.org/C87117476","wikidata":"https://www.wikidata.org/wiki/Q362383","display_name":"Cardinality (data modeling)","level":2,"score":0.4376002848148346},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4237411618232727},{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.41523319482803345},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4116678833961487},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38461166620254517},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.21458464860916138},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.11405405402183533},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"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/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:qt5d01s25c","doi":null,"is_oa":true,"landing_page_url":"http://www.escholarship.org/uc/item/5d01s25c","pdf_url":"http://www.escholarship.org/uc/item/5d01s25c","source":{"id":"https://openalex.org/S4306400115","display_name":"eScholarship (California Digital Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2801248553","host_organization_name":"California Digital Library","host_organization_lineage":["https://openalex.org/I2801248553"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Russi, Trent Michael. (2010). Uncertainty Quantification with Experimental Data and Complex System Models. UC Berkeley: Mechanical Engineering. Retrieved from: http://www.escholarship.org/uc/item/5d01s25c","raw_type":"dissertation"},{"id":"pmh:oai:escholarship.org/ark:/13030/qt5d01s25c","doi":null,"is_oa":false,"landing_page_url":"https://escholarship.org/uc/item/5d01s25c","pdf_url":null,"source":{"id":"https://openalex.org/S4306400115","display_name":"eScholarship (California Digital Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2801248553","host_organization_name":"California Digital Library","host_organization_lineage":["https://openalex.org/I2801248553"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"etd"},{"id":"mag:135841311","doi":null,"is_oa":false,"landing_page_url":"https://escholarship.org/content/qt5d01s25c/qt5d01s25c.pdf?t=mtgrkf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:qt5d01s25c","doi":null,"is_oa":true,"landing_page_url":"http://www.escholarship.org/uc/item/5d01s25c","pdf_url":"http://www.escholarship.org/uc/item/5d01s25c","source":{"id":"https://openalex.org/S4306400115","display_name":"eScholarship (California Digital Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2801248553","host_organization_name":"California Digital Library","host_organization_lineage":["https://openalex.org/I2801248553"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Russi, Trent Michael. (2010). Uncertainty Quantification with Experimental Data and Complex System Models. UC Berkeley: Mechanical Engineering. Retrieved from: http://www.escholarship.org/uc/item/5d01s25c","raw_type":"dissertation"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G2420593118","display_name":"Collaborative Research:  Cyberinfrastructure and Research Facilities:  Process Informatics for Chemical Reaction Systems","funder_award_id":"0535542","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7594817094","display_name":"ITR/AP: Realistic Uncertainty Bounds for Complex Dynamic Models","funder_award_id":"0113985","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337393","display_name":"Division of Chemistry","ror":"https://ror.org/01ar8dr59"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W135841311.pdf","grobid_xml":"https://content.openalex.org/works/W135841311.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7055629950","https://openalex.org/W2973566697","https://openalex.org/W2027249688","https://openalex.org/W3123855726","https://openalex.org/W2102117606","https://openalex.org/W3129396314","https://openalex.org/W7097573053","https://openalex.org/W2086858915","https://openalex.org/W6891289112","https://openalex.org/W6926642670"],"abstract_inverted_index":{"This":[0,190,218,424],"dissertation":[1],"discusses":[2],"uncertainty":[3,66,151,159],"quantication":[4],"as":[5,62,64,117,119,125,193,392],"posed":[6,192],"in":[7,67,152,160,226],"the":[8,55,68,76,99,106,114,129,134,139,148,153,161,184,194,198,224,229,236,248,251,289,310,319,325,339,345,350,369,380,398,408,420],"Data":[9,12,80,370],"Collaboration":[10,13,81,371],"framework.":[11],"is":[14,36,82,167,178,191,220,238,355,415,425],"a":[15,28,71,173,296,334,384,404,413],"methodology":[16],"for":[17,275,303,305],"combining":[18],"experimental":[19,164,215,395],"data":[20,59,216],"and":[21,42,50,60,95,163,181,188,283,312,363],"system":[22,32,252],"models":[23,61,253,267,277],"to":[24,53,91,113,133,146,150,158,171,210,246,255,294,324,378,403,419],"induce":[25],"constraints":[26],"on":[27,98,138,235,318,357,427],"set":[29,388,400,414],"of":[30,40,57,70,75,79,85,105,131,169,175,183,196,201,228,281,288,291,309,348,368,382,389,411],"uncertain":[31],"parameters.":[33],"The":[34,44,102,329,353],"framework":[35,372],"summarized,":[37],"including":[38],"outlines":[39],"notation":[41],"techniques.":[43],"main":[45,77],"techniques":[46,84,300],"include":[47],"polynomial":[48],"optimization":[49],"surrogate":[51,266,351],"modeling":[52,271],"ascertain":[54],"consistency":[56],"all":[58,214],"well":[63,118],"propagate":[65],"form":[69],"model":[72],"prediction.":[73],"One":[74],"methods":[78],"using":[83,223],"nonconvex":[86],"quadratically":[87],"constrained":[88,393],"quadratic":[89,257,264],"programming":[90],"provide":[92,147],"both":[93,109,179],"lower":[94,233,337],"upper":[96],"bounds":[97,137],"various":[100],"objectives.":[101],"Lagrangian":[103],"dual":[104],"NQCQP":[107,242,249],"provides":[108],"an":[110,241,306,315,428],"outer":[111],"bound":[112,234],"optimal":[115,140],"objective":[116,237],"Lagrange":[120],"multipliers.":[121],"These":[122,142],"multipliers":[123,143],"act":[124],"sensitivity":[126,149],"measures":[127],"relaying":[128],"effects":[130],"changes":[132],"parameter":[135,327,341,390],"constraint":[136],"objective.":[141],"are":[144,268,301,373,376],"rewritten":[145],"response":[154],"prediction":[155],"with":[156,213,278],"respect":[157],"parameters":[162,176,202,282],"data.":[165,396],"It":[166],"often":[168],"interest":[170],"find":[172],"vector":[174],"that":[177,203,322],"feasible":[180,387,399,422],"representative":[182],"current":[185],"community":[186],"work":[187],"knowledge.":[189],"problem":[195,219],"finding":[197],"minimal":[199],"number":[200],"must":[204],"deviate":[205],"from":[206,360,430],"their":[207],"literature":[208],"value":[209],"achieve":[211],"concurrence":[212],"constraints.":[217,328],"heuristically":[221],"solved":[222],"l1-norm":[225],"place":[227],"cardinality":[230],"function.":[231],"A":[232],"provided":[239],"through":[240],"formulation.":[243],"In":[244],"order":[245],"use":[247],"techniques,":[250],"need":[254],"have":[256,263,333],"forms.":[258],"When":[259],"they":[260],"do":[261],"not":[262],"forms,":[265],"fitted.":[269],"Surrogate":[270],"can":[272,332,401],"be":[273],"difficult":[274],"complex":[276],"large":[279],"numbers":[280],"long":[284],"simulation":[285],"times":[286],"because":[287],"amount":[290],"evaluation-time":[292],"required":[293],"make":[295],"good":[297],"fit.":[298],"New":[299],"developed":[302],"searching":[304],"active":[307,320,330],"subspace":[308,321,331],"parameters,":[311],"subsequently":[313],"creating":[314],"experiment":[316],"design":[317],"adheres":[323],"original":[326,340],"dimension":[335,342],"signicantly":[336],"than":[338],"thereby":[343],"reducing":[344],"computational":[346],"complexity":[347,381],"generating":[349],"model.":[352],"technique":[354],"demonstrated":[356,426],"several":[358],"examples":[359],"combustion":[361,431],"chemistry":[362],"biology.":[364],"Several":[365],"other":[366],"applications":[367],"presented.":[374],"They":[375],"used":[377],"demonstrate":[379],"describing":[383],"high":[385],"dimensional":[386],"values":[391],"by":[394],"Approximating":[397],"lead":[402],"simple":[405],"description,":[406],"but":[407],"predictive":[409],"capability":[410],"such":[412],"significantly":[416],"reduced":[417],"compared":[418],"actual":[421],"set.":[423],"example":[429],"chemistry.":[432]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":8},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":2}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}