{"id":"https://openalex.org/W4391096279","doi":"https://doi.org/10.1109/bigdata59044.2023.10386699","title":"A Deep Learning Pipeline for Optimizing Large-scale Phase Field Simulations","display_name":"A Deep Learning Pipeline for Optimizing Large-scale Phase Field Simulations","publication_year":2023,"publication_date":"2023-12-15","ids":{"openalex":"https://openalex.org/W4391096279","doi":"https://doi.org/10.1109/bigdata59044.2023.10386699"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata59044.2023.10386699","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata59044.2023.10386699","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.osti.gov/servlets/purl/2438977","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014168997","display_name":"Ramakrishnan Kannan","orcid":"https://orcid.org/0000-0002-5852-4806"},"institutions":[{"id":"https://openalex.org/I1289243028","display_name":"Oak Ridge National Laboratory","ror":"https://ror.org/01qz5mb56","country_code":"US","type":"facility","lineage":["https://openalex.org/I1289243028","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I4210159294"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ramakrishnan Kannan","raw_affiliation_strings":["Oak Ridge National Laboratory,Computer Science and Mathematics Division,USA","Computer Science and Mathematics Division, Oak Ridge National Laboratory, USA"],"affiliations":[{"raw_affiliation_string":"Oak Ridge National Laboratory,Computer Science and Mathematics Division,USA","institution_ids":["https://openalex.org/I1289243028"]},{"raw_affiliation_string":"Computer Science and Mathematics Division, Oak Ridge National Laboratory, USA","institution_ids":["https://openalex.org/I1289243028"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086975677","display_name":"Cristina Garc\u00eda\u2013Cardona","orcid":"https://orcid.org/0000-0002-5641-3491"},"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":false,"raw_author_name":"Cristina Garcia-Cardona","raw_affiliation_strings":["Los Alamos National Laboratory,Computer, Computational and Statistical Sciences Division,USA","Computer, Computational and Statistical Sciences Division, Los Alamos National Laboratory, USA"],"affiliations":[{"raw_affiliation_string":"Los Alamos National Laboratory,Computer, Computational and Statistical Sciences Division,USA","institution_ids":["https://openalex.org/I1343871089"]},{"raw_affiliation_string":"Computer, Computational and Statistical Sciences Division, Los Alamos National Laboratory, USA","institution_ids":["https://openalex.org/I1343871089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021028496","display_name":"Balasubramaniam Radhakrishnan","orcid":"https://orcid.org/0000-0002-2672-6235"},"institutions":[{"id":"https://openalex.org/I1289243028","display_name":"Oak Ridge National Laboratory","ror":"https://ror.org/01qz5mb56","country_code":"US","type":"facility","lineage":["https://openalex.org/I1289243028","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I4210159294"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Balasubramaniam Radhakrishnan","raw_affiliation_strings":["Oak Ridge National Laboratory,Computational Sciences and Engineering Division,USA","Computational Sciences and Engineering Division, Oak Ridge National Laboratory, USA"],"affiliations":[{"raw_affiliation_string":"Oak Ridge National Laboratory,Computational Sciences and Engineering Division,USA","institution_ids":["https://openalex.org/I1289243028"]},{"raw_affiliation_string":"Computational Sciences and Engineering Division, Oak Ridge National Laboratory, USA","institution_ids":["https://openalex.org/I1289243028"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039319913","display_name":"Sudip K. Seal","orcid":"https://orcid.org/0000-0003-3233-0656"},"institutions":[{"id":"https://openalex.org/I1289243028","display_name":"Oak Ridge National Laboratory","ror":"https://ror.org/01qz5mb56","country_code":"US","type":"facility","lineage":["https://openalex.org/I1289243028","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I4210159294"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sudip K. Seal","raw_affiliation_strings":["Oak Ridge National Laboratory,Computer Science and Mathematics Division,USA","Computer Science and Mathematics Division, Oak Ridge National Laboratory, USA"],"affiliations":[{"raw_affiliation_string":"Oak Ridge National Laboratory,Computer Science and Mathematics Division,USA","institution_ids":["https://openalex.org/I1289243028"]},{"raw_affiliation_string":"Computer Science and Mathematics Division, Oak Ridge National Laboratory, USA","institution_ids":["https://openalex.org/I1289243028"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5014168997"],"corresponding_institution_ids":["https://openalex.org/I1289243028"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13546318,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"20","issue":null,"first_page":"1744","last_page":"1753"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11087","display_name":"Solidification and crystal growth phenomena","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11087","display_name":"Solidification and crystal growth phenomena","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10670","display_name":"Aluminum Alloy Microstructure Properties","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11948","display_name":"Machine Learning in Materials Science","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials 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":0.7569794654846191},{"id":"https://openalex.org/keywords/nucleation","display_name":"Nucleation","score":0.721514105796814},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6434104442596436},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5301538109779358},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5262165069580078},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4843064844608307},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.476953387260437},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44591617584228516},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.440790593624115},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44030168652534485},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4205935597419739},{"id":"https://openalex.org/keywords/computational-science","display_name":"Computational science","score":0.37898552417755127},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3725993037223816},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3432793915271759},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2668156027793884},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10108163952827454},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09469780325889587}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7569794654846191},{"id":"https://openalex.org/C61048295","wikidata":"https://www.wikidata.org/wiki/Q909022","display_name":"Nucleation","level":2,"score":0.721514105796814},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6434104442596436},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5301538109779358},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5262165069580078},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4843064844608307},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.476953387260437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44591617584228516},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.440790593624115},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44030168652534485},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4205935597419739},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.37898552417755127},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3725993037223816},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3432793915271759},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2668156027793884},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10108163952827454},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09469780325889587},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bigdata59044.2023.10386699","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata59044.2023.10386699","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"},{"id":"pmh:oai:osti.gov:2438977","is_oa":true,"landing_page_url":"https://www.osti.gov/biblio/2438977","pdf_url":"https://www.osti.gov/servlets/purl/2438977","source":{"id":"https://openalex.org/S4306402487","display_name":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I139351228","host_organization_name":"Office of Scientific and Technical Information","host_organization_lineage":["https://openalex.org/I139351228"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:osti.gov:2438977","is_oa":true,"landing_page_url":"https://www.osti.gov/biblio/2438977","pdf_url":"https://www.osti.gov/servlets/purl/2438977","source":{"id":"https://openalex.org/S4306402487","display_name":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I139351228","host_organization_name":"Office of Scientific and Technical Information","host_organization_lineage":["https://openalex.org/I139351228"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320316892","display_name":"UT-Battelle","ror":"https://ror.org/04nza6677"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391096279.pdf"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W2002230881","https://openalex.org/W2063606786","https://openalex.org/W2091212299","https://openalex.org/W2335044697","https://openalex.org/W2884610413","https://openalex.org/W2906423938","https://openalex.org/W2919115771","https://openalex.org/W2971515228","https://openalex.org/W3008213669","https://openalex.org/W3139362221","https://openalex.org/W4206325529","https://openalex.org/W4238393424","https://openalex.org/W4283319085","https://openalex.org/W4283331992","https://openalex.org/W4286905150","https://openalex.org/W4311768005","https://openalex.org/W4318148169","https://openalex.org/W4391954212","https://openalex.org/W6739901393","https://openalex.org/W6861842597"],"related_works":["https://openalex.org/W4313886759","https://openalex.org/W2014598323","https://openalex.org/W3196590631","https://openalex.org/W4289780727","https://openalex.org/W2189903790","https://openalex.org/W2334739780","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983"],"abstract_inverted_index":{"Phase":[0],"field":[1],"(PF)":[2],"simulations":[3,75,97,203],"are":[4,67,76],"computationally":[5],"expensive":[6],"but":[7],"remain":[8],"a":[9,70,134,146,156,163,207,219,225,240,245,265,271],"key":[10],"analysis":[11,26,104,211],"tool":[12],"to":[13,78,125,132,176,231,243,250,280,301],"understand":[14],"the":[15,37,44,50,56,89,96,138,141,152,167,171,180,201,216,252,260,282,297,302],"complex":[16],"mechanisms":[17],"of":[18,29,36,40,46,58,81,91,95,112,121,140,143,159,162,218,254,296],"additive":[19],"manufacturing":[20],"(AM)":[21],"processes.":[22],"Each":[23],"PF":[24,74,135,202],"simulation-aided":[25],"requires":[27],"thousands":[28],"node":[30],"hours":[31],"on":[32,151],"leadership-class":[33],"supercomputers.":[34],"One":[35],"main":[38],"goals":[39],"these":[41],"analyses":[42],"is":[43,124,174,186,236,268],"study":[45],"microstructure":[47],"evolution":[48],"during":[49],"build":[51,244],"process":[52],"which":[53,66,235],"begins":[54],"with":[55,239,270],"onset":[57,90],"nucleation.":[59,92,255],"Nucleation":[60],"occurs":[61],"under":[62],"certain":[63],"thermomechanical":[64],"conditions":[65],"not":[68,99],"known":[69],"priori":[71],"and":[72,127],"many":[73,94],"required":[77],"identify":[79],"ranges":[80],"input":[82,261],"thermo-mechanical":[83],"parameters":[84,262],"that":[85,170,223,274],"can":[86],"result":[87,100],"in":[88,101,145,179,191,194,206,264,294],"Since":[93],"do":[98],"nucleation,":[102],"an":[103,233,276],"campaign":[105],"often":[106],"ends":[107],"up":[108],"wasting":[109],"tremendous":[110],"amounts":[111],"precious":[113],"computing":[114],"resources":[115],"executing":[116],"nucleation-absent":[117],"simulations.":[118],"The":[119,213,256],"goal":[120],"this":[122],"work":[123],"design":[126],"train":[128],"deep":[129,247],"learning":[130,221,248],"models":[131,299],"inform":[133],"simulation":[136,148,173],"about":[137],"likelihood":[139,253],"occurrence":[142],"nucleation":[144,178],"future":[147],"time-step":[149],"based":[150],"state":[153],"summary":[154],"over":[155,199],"finite":[157],"number":[158],"past":[160],"time-steps":[161],"running":[164,172],"simulation.":[165,266],"If":[166],"prediction":[168],"determines":[169],"unlikely":[175],"reach":[177],"allotted":[181],"time,":[182],"then":[183,237],"its":[184],"execution":[185],"stopped":[187],"immediately":[188],"ultimately":[189],"resulting":[190],"vast":[192],"reduction":[193],"wasted":[195],"computations":[196],"when":[197],"accrued":[198],"all":[200],"typically":[204],"performed":[205],"single":[208],"or":[209],"multiple":[210],"campaign(s).":[212],"paper":[214],"presents":[215],"performance":[217,289],"machine":[220],"pipeline":[222,273],"uses":[224,275],"convolutional":[226],"neural":[227],"network":[228,242],"(CNN)":[229],"model":[230,249,257,279],"learn":[232,281],"embedding":[234],"used":[238,263],"self-attention":[241],"multi-task":[246],"predict":[251],"also":[258],"predicts":[259],"Performance":[267],"compared":[269,300],"baseline":[272,304],"off-the-shelf":[277],"LeNet-5":[278],"initial":[283],"embedding.":[284],"Despite":[285],"their":[286],"smaller":[287],"size,":[288],"results":[290],"indicate":[291],"significant":[292],"improvement":[293],"accuracy":[295],"proposed":[298],"larger":[303],"models.":[305]},"counts_by_year":[],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}