{"id":"https://openalex.org/W7224464718","doi":"https://doi.org/10.69644/ivk-2026-sia-0023","title":"Machine learning-based prediction of W\u00f6hler curves for Ck35 steel","display_name":"Machine learning-based prediction of W\u00f6hler curves for Ck35 steel","publication_year":2026,"publication_date":"2026-10-28","ids":{"openalex":"https://openalex.org/W7224464718","doi":"https://doi.org/10.69644/ivk-2026-sia-0023"},"language":"en","primary_location":{"id":"doi:10.69644/ivk-2026-sia-0023","doi":"https://doi.org/10.69644/ivk-2026-sia-0023","is_oa":true,"landing_page_url":"https://doi.org/10.69644/ivk-2026-sia-0023","pdf_url":"https://doi.org/10.69644/ivk-2026-sia-0023","source":{"id":"https://openalex.org/S2739268444","display_name":"Integritet i vek konstrukcija","issn_l":"1451-3749","issn":["1451-3749","1820-7863"],"is_oa":true,"is_in_doaj":true,"is_core":false,"listed_in":["ddh","doaj","poland-40","russia-white-list-2"],"host_organization":"https://openalex.org/P4310321131","host_organization_name":"Society for Structural Integrity and Life, Institute for Material Testing","host_organization_lineage":["https://openalex.org/P4310321131"],"host_organization_lineage_names":["Society for Structural Integrity and Life, Institute for Material Testing"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Structural Integrity and Life","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.69644/ivk-2026-sia-0023","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5116026913","display_name":"Milica Ivi\u0107 Nikoli\u0107","orcid":"https://orcid.org/0009-0007-6217-4929","observed_orcids":["https://orcid.org/0009-0007-6217-4929"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Milica Ivi\u0107 Nikoli\u0107","raw_affiliation_strings":["Technical Test Centre, Military Scientific Research Institution of the Serbian Army, Belgrade, Serbia"],"raw_orcid":"https://orcid.org/0009-0007-6217-4929","affiliations":[{"raw_affiliation_string":"Technical Test Centre, Military Scientific Research Institution of the Serbian Army, Belgrade, Serbia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046893594","display_name":"Branislav Djordjevi\u0107","orcid":"https://orcid.org/0000-0001-8595-6930","observed_orcids":["https://orcid.org/0000-0001-8595-6930"]},"institutions":[{"id":"https://openalex.org/I4068193","display_name":"University of Belgrade","ror":"https://ror.org/02qsmb048","country_code":"RS","type":"education","lineage":["https://openalex.org/I4068193"]}],"countries":["RS"],"is_corresponding":false,"raw_author_name":"Branislav \u0110or\u0111evi\u0107","raw_affiliation_strings":["University of Belgrade, Innovation Centre of the Faculty of Mechanical Engineering, Belgrade, Serbia"],"raw_orcid":"https://orcid.org/0000-0001-8595-6930","affiliations":[{"raw_affiliation_string":"University of Belgrade, Innovation Centre of the Faculty of Mechanical Engineering, Belgrade, Serbia","institution_ids":["https://openalex.org/I4068193"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043473300","display_name":"Aleksandar Sedmak","orcid":"https://orcid.org/0000-0002-5438-1895","observed_orcids":["https://orcid.org/0000-0002-5438-1895"]},"institutions":[{"id":"https://openalex.org/I4068193","display_name":"University of Belgrade","ror":"https://ror.org/02qsmb048","country_code":"RS","type":"education","lineage":["https://openalex.org/I4068193"]}],"countries":["RS"],"is_corresponding":false,"raw_author_name":"Aleksandar Sedmak","raw_affiliation_strings":["University of Belgrade, Faculty of Mechanical Engineering, Belgrade, Serbia"],"raw_orcid":"https://orcid.org/0000-0002-5438-1895","affiliations":[{"raw_affiliation_string":"University of Belgrade, Faculty of Mechanical Engineering, Belgrade, Serbia","institution_ids":["https://openalex.org/I4068193"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019939040","display_name":"Sreten Mastilovi\u0107","orcid":"https://orcid.org/0000-0002-1856-626X","observed_orcids":["https://orcid.org/0000-0002-1856-626X"]},"institutions":[{"id":"https://openalex.org/I4068193","display_name":"University of Belgrade","ror":"https://ror.org/02qsmb048","country_code":"RS","type":"education","lineage":["https://openalex.org/I4068193"]},{"id":"https://openalex.org/I4400008997","display_name":"Institute for Multidisciplinary Research","ror":"https://ror.org/045kr1469","country_code":"RS","type":"education","lineage":["https://openalex.org/I4068193","https://openalex.org/I4400008997"]}],"countries":["RS"],"is_corresponding":false,"raw_author_name":"Sreten Mastilovi\u0107","raw_affiliation_strings":["University of Belgrade, Institute for Multidisciplinary Research, National Institute of the Republic of Serbia"],"raw_orcid":"https://orcid.org/0000-0002-1856-626X","affiliations":[{"raw_affiliation_string":"University of Belgrade, Institute for Multidisciplinary Research, National Institute of the Republic of Serbia","institution_ids":["https://openalex.org/I4068193","https://openalex.org/I4400008997"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028465097","display_name":"Aleksandar Dimi\u0107","orcid":"https://orcid.org/0000-0001-5495-0763","observed_orcids":["https://orcid.org/0000-0001-5495-0763"]},"institutions":[{"id":"https://openalex.org/I4068193","display_name":"University of Belgrade","ror":"https://ror.org/02qsmb048","country_code":"RS","type":"education","lineage":["https://openalex.org/I4068193"]}],"countries":["RS"],"is_corresponding":false,"raw_author_name":"Aleksandar Dimi\u0107","raw_affiliation_strings":["University of Belgrade, Faculty of Mechanical Engineering, Belgrade, Serbia"],"raw_orcid":"https://orcid.org/0000-0001-5495-0763","affiliations":[{"raw_affiliation_string":"University of Belgrade, Faculty of Mechanical Engineering, Belgrade, Serbia","institution_ids":["https://openalex.org/I4068193"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"26","issue":"Special Issue A","first_page":"S23","last_page":"S29"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10396","display_name":"Fatigue and fracture mechanics","score":0.9810000061988831,"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"}},"topics":[{"id":"https://openalex.org/T10396","display_name":"Fatigue and fracture mechanics","score":0.9810000061988831,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.014600000344216824,"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/T13213","display_name":"Mechanical Failure Analysis and Simulation","score":0.0006000000284984708,"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/s-n-curves","display_name":"S-N curves","score":0.9290000200271606},{"id":"https://openalex.org/keywords/fatigue-life-prediction","display_name":"fatigue life prediction","score":0.8899999856948853},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.6869999766349792},{"id":"https://openalex.org/keywords/gaussian-process-regression","display_name":"Gaussian process regression","score":0.9160000085830688},{"id":"https://openalex.org/keywords/linear-regression","display_name":"linear regression","score":0.9980000257492065},{"id":"https://openalex.org/keywords/stress-amplitude","display_name":"stress amplitude","score":0.5429999828338623},{"id":"https://openalex.org/keywords/number-of-cycles-to-failure","display_name":"number of cycles to failure","score":0.8140000104904175}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6718000173568726},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5467000007629395},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5461999773979187},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.5320000052452087},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5148000121116638},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.4957999885082245},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47909998893737793},{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.44920000433921814},{"id":"https://openalex.org/C14948415","wikidata":"https://www.wikidata.org/wiki/Q7310972","display_name":"Relevance vector machine","level":3,"score":0.44359999895095825},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42500001192092896},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.4072999954223633},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.40700000524520874},{"id":"https://openalex.org/C46889948","wikidata":"https://www.wikidata.org/wiki/Q2755024","display_name":"Nonlinear regression","level":3,"score":0.4027000069618225},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.39169999957084656},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.36489999294281006},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.3619999885559082},{"id":"https://openalex.org/C150217764","wikidata":"https://www.wikidata.org/wiki/Q6803607","display_name":"Mean absolute percentage error","level":3,"score":0.33739998936653137},{"id":"https://openalex.org/C184389593","wikidata":"https://www.wikidata.org/wiki/Q603159","display_name":"Curve fitting","level":2,"score":0.33570000529289246},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.33230000734329224},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3321000039577484},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.3296999931335449},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.31940001249313354},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.3138999938964844},{"id":"https://openalex.org/C55037315","wikidata":"https://www.wikidata.org/wiki/Q5421151","display_name":"Experimental data","level":2,"score":0.3068000078201294},{"id":"https://openalex.org/C145828037","wikidata":"https://www.wikidata.org/wiki/Q17086219","display_name":"Least squares support vector machine","level":3,"score":0.29809999465942383},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.2955000102519989},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C180205008","wikidata":"https://www.wikidata.org/wiki/Q159190","display_name":"Amplitude","level":2,"score":0.26930001378059387},{"id":"https://openalex.org/C2775846686","wikidata":"https://www.wikidata.org/wiki/Q643012","display_name":"Condition monitoring","level":2,"score":0.25529998540878296},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.2524999976158142}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.69644/ivk-2026-sia-0023","doi":"https://doi.org/10.69644/ivk-2026-sia-0023","is_oa":true,"landing_page_url":"https://doi.org/10.69644/ivk-2026-sia-0023","pdf_url":"https://doi.org/10.69644/ivk-2026-sia-0023","source":{"id":"https://openalex.org/S2739268444","display_name":"Integritet i vek konstrukcija","issn_l":"1451-3749","issn":["1451-3749","1820-7863"],"is_oa":true,"is_in_doaj":true,"is_core":false,"listed_in":["ddh","doaj","poland-40","russia-white-list-2"],"host_organization":"https://openalex.org/P4310321131","host_organization_name":"Society for Structural Integrity and Life, Institute for Material Testing","host_organization_lineage":["https://openalex.org/P4310321131"],"host_organization_lineage_names":["Society for Structural Integrity and Life, Institute for Material Testing"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Structural Integrity and Life","raw_type":"journal-article"},{"id":"pmh:oai:machinery.mas.bg.ac.rs:123456789/8997","doi":null,"is_oa":true,"landing_page_url":"https://machinery.mas.bg.ac.rs/handle/123456789/8997","pdf_url":null,"source":{"id":"https://openalex.org/S4377196545","display_name":"MACHINERY - Repository of the Faculty of Mechanical Engineering (University of Belgrade)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4068193","host_organization_name":"University of Belgrade","host_organization_lineage":["https://openalex.org/I4068193"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Structural Integrity and Life","raw_type":"article"}],"best_oa_location":{"id":"doi:10.69644/ivk-2026-sia-0023","doi":"https://doi.org/10.69644/ivk-2026-sia-0023","is_oa":true,"landing_page_url":"https://doi.org/10.69644/ivk-2026-sia-0023","pdf_url":"https://doi.org/10.69644/ivk-2026-sia-0023","source":{"id":"https://openalex.org/S2739268444","display_name":"Integritet i vek konstrukcija","issn_l":"1451-3749","issn":["1451-3749","1820-7863"],"is_oa":true,"is_in_doaj":true,"is_core":false,"listed_in":["ddh","doaj","poland-40","russia-white-list-2"],"host_organization":"https://openalex.org/P4310321131","host_organization_name":"Society for Structural Integrity and Life, Institute for Material Testing","host_organization_lineage":["https://openalex.org/P4310321131"],"host_organization_lineage_names":["Society for Structural Integrity and Life, Institute for Material Testing"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Structural Integrity and Life","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7224464718.pdf","grobid_xml":"https://content.openalex.org/works/W7224464718.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W1988335915","https://openalex.org/W2028928669","https://openalex.org/W2052804863","https://openalex.org/W2139212933","https://openalex.org/W2145992718","https://openalex.org/W2167267506","https://openalex.org/W2672330039","https://openalex.org/W4205247343","https://openalex.org/W4220946698","https://openalex.org/W4281760806","https://openalex.org/W4391661843","https://openalex.org/W4402309281","https://openalex.org/W4403089631","https://openalex.org/W4408406144","https://openalex.org/W4409445463","https://openalex.org/W4412436668","https://openalex.org/W7117720925"],"related_works":["https://openalex.org/W7114832693","https://openalex.org/W4405355703","https://openalex.org/W4417200602","https://openalex.org/W7167612434","https://openalex.org/W4362640732","https://openalex.org/W4405829642","https://openalex.org/W4366985501","https://openalex.org/W4285174546","https://openalex.org/W4406734724","https://openalex.org/W4409445463"],"abstract_inverted_index":{"Machine":[0,52],"learning":[1,12,48,182],"has":[2],"become":[3],"a":[4,114,127],"powerful":[5],"tool":[6],"for":[7,161],"prediction":[8,35],"and":[9,26,57,93,105,132,141,149,168],"discovery":[10],"by":[11],"patterns":[13],"from":[14,69],"observations,":[15],"although":[16],"its":[17],"reliability":[18],"depends":[19],"on":[20],"appropriate":[21],"model":[22,118],"selection,":[23],"rigorous":[24],"evaluation,":[25],"awareness":[27],"of":[28,36,39,107,129,180,188,195],"inherent":[29],"limitations.":[30],"This":[31],"study":[32],"investigates":[33],"the":[34,76,98,178,186,193],"S-N":[37,100,170],"behaviour":[38],"Ck35":[40],"steel":[41],"(DIN":[42],"EN":[43],"10083)":[44],"using":[45,136],"three":[46],"machine":[47,181],"models:":[49],"Support":[50],"Vector":[51],"(SVM),":[53],"Linear":[54],"Regression":[55,60],"(LR),":[56],"Gaussian":[58],"Process":[59],"(GPR),":[61],"implemented":[62],"in":[63,86],"MATLAB\u00ae.":[64],"A":[65],"material":[66],"identifier":[67],"extracted":[68],"sample":[70],"codes":[71],"is":[72,119,134],"used":[73],"to":[74,109,113,122,157,174,184],"partition":[75],"experimental":[77,169,189],"dataset":[78],"into":[79,91],"distinct":[80],"groups,":[81],"with":[82],"available":[83],"fatigue":[84,124,190],"data":[85,163],"each":[87],"group":[88,167],"alternately":[89],"divided":[90],"training":[92],"test":[94],"sets.":[95],"To":[96],"capture":[97],"expected":[99],"relationship,":[101],"both":[102],"stress":[103],"amplitude":[104],"number":[106],"cycles":[108],"failure":[110],"are":[111,172],"transformed":[112],"logarithmic":[115],"space.":[116],"Each":[117,165],"trained":[120],"separately":[121],"predict":[123],"life":[125],"as":[126],"function":[128],"applied":[130],"stress,":[131],"performance":[133,155],"evaluated":[135],"Mean":[137,143],"Absolute":[138],"Percentage":[139],"Error":[140,145],"Root":[142],"Square":[144],"metrics.":[146],"The":[147],"SVM":[148],"GPR":[150],"models":[151],"demonstrate":[152],"better":[153],"predictive":[154],"compared":[156,173],"classical":[158],"LR,":[159],"particularly":[160],"nonlinear":[162],"groups.":[164],"predicted":[166],"curve":[171],"assess":[175],"accuracy,":[176],"illustrating":[177],"potential":[179],"approaches":[183],"reduce":[185],"scope":[187],"testing":[191],"through":[192],"application":[194],"intelligent":[196],"algorithms.":[197]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2026-10-30T00:00:00"}