{"id":"https://openalex.org/W7168256185","doi":"https://doi.org/10.48550/arxiv.2607.10412","title":"Machine Learning-based Correlation of Charpy Impact Properties Between Sub-sized and Standard-sized Specimens for Nuclear Structural Materials","display_name":"Machine Learning-based Correlation of Charpy Impact Properties Between Sub-sized and Standard-sized Specimens for Nuclear Structural Materials","publication_year":2026,"publication_date":"2026-07-11","ids":{"openalex":"https://openalex.org/W7168256185","doi":"https://doi.org/10.48550/arxiv.2607.10412"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.10412","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.10412","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.10412","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5140675584","display_name":"Yugandhar Kasala Sreenivasulu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sreenivasulu, Yugandhar Kasala","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140677825","display_name":"Isshu Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Isshu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140606909","display_name":"John W. Merickel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Merickel, John W.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140605177","display_name":"Fei Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Fei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140735501","display_name":"Yalei Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Yalei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140590944","display_name":"Joshua E. Rittenhouse","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rittenhouse, Joshua E.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140610873","display_name":"Aleksandar Vakanski","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vakanski, Aleksandar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5140666222","display_name":"Rongjie Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Rongjie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"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/T11699","display_name":"High-Velocity Impact and Material Behavior","score":0.26499998569488525,"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/T11699","display_name":"High-Velocity Impact and Material Behavior","score":0.26499998569488525,"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/T10396","display_name":"Fatigue and fracture mechanics","score":0.09139999747276306,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/T10840","display_name":"High Temperature Alloys and Creep","score":0.08780000358819962,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/charpy-impact-test","display_name":"Charpy impact test","score":0.9915000200271606},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6424000263214111},{"id":"https://openalex.org/keywords/tangent","display_name":"Tangent","score":0.574400007724762},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.4108000099658966},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.3986000120639801},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.3666999936103821},{"id":"https://openalex.org/keywords/residual-stress","display_name":"Residual stress","score":0.3052999973297119},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.2987000048160553}],"concepts":[{"id":"https://openalex.org/C127205250","wikidata":"https://www.wikidata.org/wiki/Q653604","display_name":"Charpy impact test","level":3,"score":0.9915000200271606},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6424000263214111},{"id":"https://openalex.org/C138187205","wikidata":"https://www.wikidata.org/wiki/Q131251","display_name":"Tangent","level":2,"score":0.574400007724762},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.5055000185966492},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.4108000099658966},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.3986000120639801},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.3666999936103821},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.3140000104904175},{"id":"https://openalex.org/C37292000","wikidata":"https://www.wikidata.org/wiki/Q1257918","display_name":"Residual stress","level":2,"score":0.3052999973297119},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.2987000048160553},{"id":"https://openalex.org/C99595764","wikidata":"https://www.wikidata.org/wiki/Q486802","display_name":"Toughness","level":2,"score":0.2953000068664551},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.2906999886035919},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.2858999967575073},{"id":"https://openalex.org/C2992524093","wikidata":"https://www.wikidata.org/wiki/Q486802","display_name":"Impact energy","level":2,"score":0.27799999713897705},{"id":"https://openalex.org/C2984185122","wikidata":"https://www.wikidata.org/wiki/Q1309431","display_name":"Structural integrity","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.27639999985694885},{"id":"https://openalex.org/C2780841128","wikidata":"https://www.wikidata.org/wiki/Q5073781","display_name":"Characterization (materials science)","level":2,"score":0.2727999985218048},{"id":"https://openalex.org/C31555180","wikidata":"https://www.wikidata.org/wiki/Q3523867","display_name":"Material properties","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C56529433","wikidata":"https://www.wikidata.org/wiki/Q626700","display_name":"Nondestructive testing","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.25440001487731934}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.10412","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.10412","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.10412","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.10412","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.4747985601425171,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Reliable":[0],"correlations":[1],"of":[2,189],"Charpy":[3,89,167,207,227],"impact":[4,90,168,228],"test":[5,121],"results":[6],"between":[7],"sub-sized":[8,120,164],"and":[9,25,38,46,63,74,139,165,193,222],"full-sized":[10,124,166,206],"specimens":[11],"are":[12,144],"essential":[13],"for":[14,87,134,191,195,215],"structural":[15],"integrity":[16],"assessments,":[17],"particularly":[18],"in":[19,54],"nuclear":[20],"applications,":[21],"where":[22],"spatial":[23],"constraints":[24],"limited":[26,61],"material":[27,216],"volume":[28],"restrict":[29],"specimen":[30,75,93],"size.":[31],"Although":[32],"standards":[33],"such":[34],"as":[35],"ASTM":[36],"A370":[37],"BS":[39],"7910":[40],"provide":[41],"guidance":[42],"on":[43,170],"conversion":[44],"methodologies,":[45],"numerous":[47],"analytical":[48,184],"correlation":[49,179],"methods":[50],"have":[51,60],"been":[52],"proposed":[53,86,96],"prior":[55],"studies,":[56],"these":[57],"approaches":[58],"generally":[59],"accuracy":[62],"their":[64],"applicability":[65],"is":[66,85,156],"often":[67],"constrained":[68],"to":[69,118,182,205],"specific":[70],"materials,":[71],"treatment":[72],"conditions,":[73],"geometries.":[76],"In":[77],"this":[78,212],"study,":[79],"a":[80,110,150,159],"Machine":[81],"Learning":[82],"(ML)-based":[83],"framework":[84,155],"correlating":[88],"properties":[91],"across":[92,102],"sizes.":[94],"The":[95,154,197],"approach":[97,175,213],"maps":[98],"absorbed":[99],"energy":[100,137],"values":[101,133,188],"the":[103,127,131],"full":[104],"ductile-to-brittle":[105,140],"transition":[106,141],"region":[107],"by":[108,146],"applying":[109],"temperature":[111,142],"shift":[112],"combined":[113],"with":[114,123,149],"scaled":[115],"residual":[116],"projection,":[117],"align":[119],"data":[122,148,208],"response.":[125],"From":[126],"resulting":[128],"temperature-energy":[129],"profiles,":[130],"correlated":[132],"upper":[135],"shelf":[136],"(USE)":[138],"(DBTT)":[143],"extracted":[145],"fitting":[147],"hyperbolic":[151],"tangent":[152],"model.":[153],"validated":[157],"using":[158],"dataset":[160],"comprising":[161],"389":[162],"matched":[163],"tests":[169],"SA533B":[171],"steel.":[172],"This":[173],"ML-based":[174],"demonstrates":[176],"an":[177],"improved":[178],"performance":[180],"relative":[181],"conventional":[183],"methods,":[185],"achieving":[186],"R2":[187],"0.942":[190],"USE":[192],"0.892":[194],"DBTT.":[196],"trained":[198],"ML":[199],"models":[200],"do":[201],"not":[202],"require":[203],"access":[204],"during":[209],"inference,":[210],"making":[211],"suitable":[214],"surveillance":[217],"programs,":[218],"accelerated":[219],"irradiation":[220],"testing,":[221],"other":[223],"applications":[224],"involving":[225],"small-size":[226],"testing.":[229]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-15T00:00:00"}