{"id":"https://openalex.org/W7081933544","doi":"https://doi.org/10.5281/zenodo.17142176","title":"Temperature modelling in machine tools","display_name":"Temperature modelling in machine tools","publication_year":2025,"publication_date":"2025-09-17","ids":{"openalex":"https://openalex.org/W7081933544","doi":"https://doi.org/10.5281/zenodo.17142176"},"language":"en","primary_location":{"id":"doi:10.5281/zenodo.17142176","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.17142176","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"dataset"},"type":"dataset","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.5281/zenodo.17142176","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Fern\u00e1ndez, Dar\u00edo","orcid":"https://orcid.org/0009-0001-0688-9862"},"institutions":[{"id":"https://openalex.org/I78650965","display_name":"Technische Universit\u00e4t Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Fern\u00e1ndez, Dar\u00edo","raw_affiliation_strings":["TU Dresden"],"affiliations":[{"raw_affiliation_string":"TU Dresden","institution_ids":["https://openalex.org/I78650965"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hohmann, Michael","orcid":"https://orcid.org/0009-0001-0672-9439"},"institutions":[{"id":"https://openalex.org/I190134885","display_name":"Helmut Schmidt University","ror":"https://ror.org/04e8jbs38","country_code":"DE","type":"education","lineage":["https://openalex.org/I190134885"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Hohmann, Michael","raw_affiliation_strings":["Helmut Schmidt University"],"affiliations":[{"raw_affiliation_string":"Helmut Schmidt University","institution_ids":["https://openalex.org/I190134885"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Coelho, Cec\u00edlia","orcid":"https://orcid.org/0009-0009-4502-937X"},"institutions":[{"id":"https://openalex.org/I190134885","display_name":"Helmut Schmidt University","ror":"https://ror.org/04e8jbs38","country_code":"DE","type":"education","lineage":["https://openalex.org/I190134885"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Coelho, Cec\u00edlia","raw_affiliation_strings":["Helmut Schmidt University"],"affiliations":[{"raw_affiliation_string":"Helmut Schmidt University","institution_ids":["https://openalex.org/I190134885"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Penter, Lars","orcid":"https://orcid.org/0000-0002-1093-2149"},"institutions":[{"id":"https://openalex.org/I4210124503","display_name":"Fraunhofer Institute for Machine Tools and Forming Technology","ror":"https://ror.org/026taa863","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210124503","https://openalex.org/I4923324"]},{"id":"https://openalex.org/I78650965","display_name":"Technische Universit\u00e4t Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Penter, Lars","raw_affiliation_strings":["Fraunhofer Institute for Machine Tools and Forming Technology","TU Dresden"],"affiliations":[{"raw_affiliation_string":"Fraunhofer Institute for Machine Tools and Forming Technology","institution_ids":["https://openalex.org/I4210124503"]},{"raw_affiliation_string":"TU Dresden","institution_ids":["https://openalex.org/I78650965"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ihlenfeldt, Steffen","orcid":"https://orcid.org/0000-0002-9258-5178"},"institutions":[{"id":"https://openalex.org/I78650965","display_name":"Technische Universit\u00e4t Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ihlenfeldt, Steffen","raw_affiliation_strings":["TU Dresden"],"affiliations":[{"raw_affiliation_string":"TU Dresden","institution_ids":["https://openalex.org/I78650965"]}]},{"author_position":"last","author":{"id":null,"display_name":"Niggemann, Oliver","orcid":"https://orcid.org/0000-0001-8747-3596"},"institutions":[{"id":"https://openalex.org/I190134885","display_name":"Helmut Schmidt University","ror":"https://ror.org/04e8jbs38","country_code":"DE","type":"education","lineage":["https://openalex.org/I190134885"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Niggemann, Oliver","raw_affiliation_strings":["Helmut Schmidt University"],"affiliations":[{"raw_affiliation_string":"Helmut Schmidt University","institution_ids":["https://openalex.org/I190134885"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I78650965"],"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":true,"primary_topic":{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.40939998626708984,"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"}},"topics":[{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.40939998626708984,"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"}},{"id":"https://openalex.org/T13177","display_name":"Geological and Geophysical Studies","score":0.04439999908208847,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13067","display_name":"Geological Modeling and Analysis","score":0.031700000166893005,"subfield":{"id":"https://openalex.org/subfields/1906","display_name":"Geochemistry and Petrology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/machine-tool","display_name":"Machine tool","score":0.5378000140190125},{"id":"https://openalex.org/keywords/finite-element-method","display_name":"Finite element method","score":0.5094000101089478},{"id":"https://openalex.org/keywords/compensation","display_name":"Compensation (psychology)","score":0.49459999799728394},{"id":"https://openalex.org/keywords/thermal","display_name":"Thermal","score":0.48019999265670776},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.46309998631477356},{"id":"https://openalex.org/keywords/transient","display_name":"Transient (computer programming)","score":0.4456000030040741},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.40149998664855957},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.37470000982284546},{"id":"https://openalex.org/keywords/preprint","display_name":"Preprint","score":0.3596000075340271},{"id":"https://openalex.org/keywords/temperature-measurement","display_name":"Temperature measurement","score":0.3571000099182129}],"concepts":[{"id":"https://openalex.org/C5941749","wikidata":"https://www.wikidata.org/wiki/Q19768","display_name":"Machine tool","level":2,"score":0.5378000140190125},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5218999981880188},{"id":"https://openalex.org/C135628077","wikidata":"https://www.wikidata.org/wiki/Q220184","display_name":"Finite element method","level":2,"score":0.5094000101089478},{"id":"https://openalex.org/C2780023022","wikidata":"https://www.wikidata.org/wiki/Q1338171","display_name":"Compensation (psychology)","level":2,"score":0.49459999799728394},{"id":"https://openalex.org/C204530211","wikidata":"https://www.wikidata.org/wiki/Q752823","display_name":"Thermal","level":2,"score":0.48019999265670776},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.46309998631477356},{"id":"https://openalex.org/C2780799671","wikidata":"https://www.wikidata.org/wiki/Q17087362","display_name":"Transient (computer programming)","level":2,"score":0.4456000030040741},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.40149998664855957},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38199999928474426},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.37470000982284546},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37389999628067017},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3709000051021576},{"id":"https://openalex.org/C43169469","wikidata":"https://www.wikidata.org/wiki/Q580922","display_name":"Preprint","level":2,"score":0.3596000075340271},{"id":"https://openalex.org/C72293138","wikidata":"https://www.wikidata.org/wiki/Q909741","display_name":"Temperature measurement","level":2,"score":0.3571000099182129},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.3538999855518341},{"id":"https://openalex.org/C159188206","wikidata":"https://www.wikidata.org/wiki/Q1478382","display_name":"Heat flux","level":3,"score":0.3449999988079071},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.34470000863075256},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.34299999475479126},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3269999921321869},{"id":"https://openalex.org/C55037315","wikidata":"https://www.wikidata.org/wiki/Q5421151","display_name":"Experimental data","level":2,"score":0.3246000111103058},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.31700000166893005},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.3160000145435333},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.3012999892234802},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.296999990940094},{"id":"https://openalex.org/C182310444","wikidata":"https://www.wikidata.org/wiki/Q1332643","display_name":"Boundary value problem","level":2,"score":0.2937000095844269},{"id":"https://openalex.org/C50517652","wikidata":"https://www.wikidata.org/wiki/Q179635","display_name":"Heat transfer","level":2,"score":0.28940001130104065},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.2793999910354614},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.27549999952316284},{"id":"https://openalex.org/C169222746","wikidata":"https://www.wikidata.org/wiki/Q4116558","display_name":"Factorial experiment","level":2,"score":0.271699994802475},{"id":"https://openalex.org/C129446986","wikidata":"https://www.wikidata.org/wiki/Q542419","display_name":"Thermal analysis","level":3,"score":0.2671999931335449},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2565000057220459},{"id":"https://openalex.org/C132459708","wikidata":"https://www.wikidata.org/wiki/Q744069","display_name":"Extrapolation","level":2,"score":0.25209999084472656},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.25200000405311584},{"id":"https://openalex.org/C199639397","wikidata":"https://www.wikidata.org/wiki/Q1788588","display_name":"Engineering drawing","level":1,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5281/zenodo.17142176","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.17142176","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"dataset"}],"best_oa_location":{"id":"doi:10.5281/zenodo.17142176","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.17142176","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"dataset"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4175702929496765}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"If":[0],"you":[1],"use":[2],"this":[3],"please":[4],"cite:":[5],"'''@article{coelho2025open,":[6],"title={An":[7],"Open":[8],"Dataset":[9],"for":[10,47,156],"Temperature":[11],"Modelling":[12],"in":[13,153,165],"Machine":[14],"Tools},":[15],"author={Coelho,":[16],"C":[17],"and":[18,21,24,27,30,62,100,113,121,135,149,159,168],"Fern{\\'a}ndez,":[19],"D":[20],"Hohmann,":[22],"M":[23],"Penter,":[25],"L":[26],"Ihlenfeldt,":[28],"S":[29],"Niggemann,":[31],"O},":[32],"journal={arXiv":[33],"preprint":[34],"arXiv:2509.16222},":[35],"year={2025}}'''":[36],"We":[37],"introduce":[38],"a":[39,48,52,79,88,93,136],"structured,":[40],"high-resolution":[41],"dataset":[42,125],"of":[43,51,161],"transient":[44],"thermal":[45,129,154],"simulations":[46],"vertical":[49],"axis":[50],"machine":[53,147],"tool":[54],"test":[55],"rig.":[56],"The":[57,140],"data":[58,141],"set":[59,142],"includes":[60],"temperature":[61],"heat":[63],"flux":[64],"values":[65],"recorded":[66],"at":[67,71],"29":[68],"probe":[69],"locations":[70],"1800":[72],"time":[73],"steps,":[74],"sampled":[75],"every":[76],"second":[77],"over":[78],"30-minute":[80],"range,":[81],"across":[82],"17":[83],"simulation":[84,179],"runs":[85],"derived":[86],"from":[87],"fractional":[89],"factorial":[90],"design.":[91],"First,":[92],"computer-aided":[94],"design":[95],"model":[96,122],"was":[97],"de-featured,":[98],"segmented,":[99],"optimized,":[101],"followed":[102],"by":[103,176],"finite":[104],"element":[105],"(FE)":[106],"modelling.":[107],"Detailed":[108],"information":[109],"on":[110],"material,":[111],"mesh,":[112],"boundary":[114],"conditions":[115],"is":[116,143],"included.":[117],"To":[118],"support":[119,146,171],"research":[120],"development,":[123],"the":[124],"provides":[126],"summary":[127],"statistics,":[128],"evolution":[130],"plots,":[131],"correlation":[132],"matrix":[133],"analyses,":[134],"reproducible":[137],"Jupyter":[138],"notebook.":[139],"designed":[144],"to":[145,170],"learning":[148,151],"deep":[150],"applications":[152],"modelling":[155],"prediction,":[157],"correction,":[158],"compensation":[160],"thermally":[162],"induced":[163],"deviations":[164],"mechanical":[166],"systems,":[167],"aims":[169],"researchers":[172],"without":[173],"FE":[174],"expertise":[175],"providing":[177],"ready-to-use":[178],"data.":[180]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}