Rotary-scaling fine-tuning (RSFT) method for optimizing railway wheel profiles and its application to a locomotiveOA

作者：Yunguang Ye;Yayun Qi;Dachuan Shi;Yu Sun;Yichang Zhou;Markus Hecht

作者单位：Institute of Land and Sea Transport Systems, TechnicalUniversity of Berlin, 10587 Berlin, GermanyState Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610331, ChinaInstitute of Land and Sea Transport Systems, TechnicalUniversity of Berlin, 10587 Berlin, GermanyState Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610331, ChinaCollege of Transportation Science and Engineering, Nanjing Tech University, Nanjing 210009, ChinaInstitute of Land and Sea Transport Systems, TechnicalUniversity of Berlin, 10587 Berlin, Germany

中文关键词：Wheel profile optimizationWear reductionRotary-scaling fine-tuningParticle swarm optimizationKriging surrogate model

英文关键词：Wheel profile optimizationWear reductionRotary-scaling fine-tuningParticle swarm optimizationKriging surrogate model

刊名：《现代交通学报（英文版）》 2020 (2)

页码/页数：160-183,24

基金：Acknowledgements This work is supported by the Assets4Rail Project which is funded by the Shift2Rail Joint Undertaking under the EU's H2020 program (Grant No. 826250) and the Open Research Fund of State Key Laboratory of Traction Power of Southwest Jiao-tong University (Grant No. TPL2011), and part of the experiment data concerning the railway line is supported by the DynoTRAIN Project, funded by European Commission (Grant No. 234079). The first author is also supported by the China Scholarship Council (Grant No. 201707000113).