Probabilistic Fatigue/Creep Optimization of Turbine Bladed Disk with Fuzzy Multi-Extremum Response Surface Method
To effectively perform the probabilistic fatigue/creep coupling optimization of a turbine bladed disk, this paper develops the fuzzy multi-extremum response surface method (FMERSM) for the comprehensive probabilistic optimization of multi-failure/multi-component structures, which absorbs the ideas o...
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| Published in | Materials Vol. 12; no. 20; p. 3367 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
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15.10.2019
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| ISSN | 1996-1944 1996-1944 |
| DOI | 10.3390/ma12203367 |
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| Abstract | To effectively perform the probabilistic fatigue/creep coupling optimization of a turbine bladed disk, this paper develops the fuzzy multi-extremum response surface method (FMERSM) for the comprehensive probabilistic optimization of multi-failure/multi-component structures, which absorbs the ideas of the extremum response surface method, hierarchical strategy, and fuzzy theory. We studied the approaches of FMERSM modeling and fatigue/creep damage evaluation of turbine bladed disks, and gave the procedure for the fuzzy probabilistic fatigue/creep optimization of a multi-component structure with FMERSM. The probabilistic fatigue/creep coupling optimization of turbine bladed disks was implemented by regarding the rotor speed, temperature, and density as optimization parameters; the creep stress, creep strain, fatigue damage, and creep damage as optimization objectives; and the reliability and GH4133B fatigue/creep damages as constraint functions. The results show that gas temperature T and rotor speed ω are the key parameters that should be controlled in bladed disk optimization, and respectively reduce by 85 K and 113 rad/s after optimization, which is promising to extend bladed disk life and decrease failure damages. The simulation results show that this method has a higher modeling accuracy and computational efficiency than the Monte Carlo method (MCM). The efforts of this study provide a new useful method for overall probabilistic multi-failure optimization and enrich mechanical reliability theory. |
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| AbstractList | To effectively perform the probabilistic fatigue/creep coupling optimization of a turbine bladed disk, this paper develops the fuzzy multi-extremum response surface method (FMERSM) for the comprehensive probabilistic optimization of multi-failure/multi-component structures, which absorbs the ideas of the extremum response surface method, hierarchical strategy, and fuzzy theory. We studied the approaches of FMERSM modeling and fatigue/creep damage evaluation of turbine bladed disks, and gave the procedure for the fuzzy probabilistic fatigue/creep optimization of a multi-component structure with FMERSM. The probabilistic fatigue/creep coupling optimization of turbine bladed disks was implemented by regarding the rotor speed, temperature, and density as optimization parameters; the creep stress, creep strain, fatigue damage, and creep damage as optimization objectives; and the reliability and GH4133B fatigue/creep damages as constraint functions. The results show that gas temperature T and rotor speed ω are the key parameters that should be controlled in bladed disk optimization, and respectively reduce by 85 K and 113 rad/s after optimization, which is promising to extend bladed disk life and decrease failure damages. The simulation results show that this method has a higher modeling accuracy and computational efficiency than the Monte Carlo method (MCM). The efforts of this study provide a new useful method for overall probabilistic multi-failure optimization and enrich mechanical reliability theory.To effectively perform the probabilistic fatigue/creep coupling optimization of a turbine bladed disk, this paper develops the fuzzy multi-extremum response surface method (FMERSM) for the comprehensive probabilistic optimization of multi-failure/multi-component structures, which absorbs the ideas of the extremum response surface method, hierarchical strategy, and fuzzy theory. We studied the approaches of FMERSM modeling and fatigue/creep damage evaluation of turbine bladed disks, and gave the procedure for the fuzzy probabilistic fatigue/creep optimization of a multi-component structure with FMERSM. The probabilistic fatigue/creep coupling optimization of turbine bladed disks was implemented by regarding the rotor speed, temperature, and density as optimization parameters; the creep stress, creep strain, fatigue damage, and creep damage as optimization objectives; and the reliability and GH4133B fatigue/creep damages as constraint functions. The results show that gas temperature T and rotor speed ω are the key parameters that should be controlled in bladed disk optimization, and respectively reduce by 85 K and 113 rad/s after optimization, which is promising to extend bladed disk life and decrease failure damages. The simulation results show that this method has a higher modeling accuracy and computational efficiency than the Monte Carlo method (MCM). The efforts of this study provide a new useful method for overall probabilistic multi-failure optimization and enrich mechanical reliability theory. If we directly establish the reliability optimization design model of an overall structure involving multi-material, multi-disciplinary, and multi-physics structures, the computational burden will become very large in analysis, so that computational efficiency is unacceptable [2]. [...]it is significant to propose an efficient method for an overall reliability optimization design of multi-component and multi-failure modes, to make computational precision and efficiency satisfy engineering requirements. [...]the probabilistic fatigue/creep optimization design of turbine bladed disks involves an obvious fuzziness for design parameters and constraint conditions as well as the coupling among many failure modes such as stress failure, strain failure, creep damage, fatigue damage, and so on [15,16,17,18]. [...]the fuzziness and coupling seriously negatively influence the design precision and efficiency of multi-object optimization when the above methods are directly applied. [...]it is urgent to propose an effective method for multi-object reliability-based optimization, in which the fuzziness for design parameters and constraint conditions as well as the coupling among many failure modes are fully considered in order to improve the modeling accuracy and simulation efficiency. In most of the structural probabilistic designs, in fact, influential parameters and constraint conditions hold obvious fuzziness and seriously influence design precision. [...]it is reasonable to consider the fuzziness of design parameters and constraint conditions to improve the probabilistic design of structures, especially with multi-failure modes or multi-component structures. To effectively perform the probabilistic fatigue/creep coupling optimization of a turbine bladed disk, this paper develops the fuzzy multi-extremum response surface method (FMERSM) for the comprehensive probabilistic optimization of multi-failure/multi-component structures, which absorbs the ideas of the extremum response surface method, hierarchical strategy, and fuzzy theory. We studied the approaches of FMERSM modeling and fatigue/creep damage evaluation of turbine bladed disks, and gave the procedure for the fuzzy probabilistic fatigue/creep optimization of a multi-component structure with FMERSM. The probabilistic fatigue/creep coupling optimization of turbine bladed disks was implemented by regarding the rotor speed, temperature, and density as optimization parameters; the creep stress, creep strain, fatigue damage, and creep damage as optimization objectives; and the reliability and GH4133B fatigue/creep damages as constraint functions. The results show that gas temperature T and rotor speed ω are the key parameters that should be controlled in bladed disk optimization, and respectively reduce by 85 K and 113 rad/s after optimization, which is promising to extend bladed disk life and decrease failure damages. The simulation results show that this method has a higher modeling accuracy and computational efficiency than the Monte Carlo method (MCM). The efforts of this study provide a new useful method for overall probabilistic multi-failure optimization and enrich mechanical reliability theory. To effectively perform the probabilistic fatigue/creep coupling optimization of a turbine bladed disk, this paper develops the fuzzy multi-extremum response surface method (FMERSM) for the comprehensive probabilistic optimization of multi-failure/multi-component structures, which absorbs the ideas of the extremum response surface method, hierarchical strategy, and fuzzy theory. We studied the approaches of FMERSM modeling and fatigue/creep damage evaluation of turbine bladed disks, and gave the procedure for the fuzzy probabilistic fatigue/creep optimization of a multi-component structure with FMERSM. The probabilistic fatigue/creep coupling optimization of turbine bladed disks was implemented by regarding the rotor speed, temperature, and density as optimization parameters; the creep stress, creep strain, fatigue damage, and creep damage as optimization objectives; and the reliability and GH4133B fatigue/creep damages as constraint functions. The results show that gas temperature T and rotor speed ω are the key parameters that should be controlled in bladed disk optimization, and respectively reduce by 85 K and 113 rad/s after optimization, which is promising to extend bladed disk life and decrease failure damages. The simulation results show that this method has a higher modeling accuracy and computational efficiency than the Monte Carlo method (MCM). The efforts of this study provide a new useful method for overall probabilistic multi-failure optimization and enrich mechanical reliability theory. |
| Author | Lu, Cheng Zhang, Chun-Yi Wang, Ze Fei, Cheng-Wei Yuan, Zhe-Shan |
| AuthorAffiliation | 2 Department of Aeronautics and Astronautics, Fudan University, Shanghai 200433, China 1 School of Mechanical and Power Engineering, Harbin University of Science and Technology, Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, Harbin 150080, China; zhangchunyi@hrbust.edu.cn (C.-Y.Z.); yuanzheshan_ma17@hrbust.edu.cn (Z.-S.Y.); wangze_ma17@hrbust.edu.cn (Z.W.) 3 School of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, China; lucheng2013@163.com |
| AuthorAffiliation_xml | – name: 2 Department of Aeronautics and Astronautics, Fudan University, Shanghai 200433, China – name: 1 School of Mechanical and Power Engineering, Harbin University of Science and Technology, Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, Harbin 150080, China; zhangchunyi@hrbust.edu.cn (C.-Y.Z.); yuanzheshan_ma17@hrbust.edu.cn (Z.-S.Y.); wangze_ma17@hrbust.edu.cn (Z.W.) – name: 3 School of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, China; lucheng2013@163.com |
| Author_xml | – sequence: 1 givenname: Chun-Yi surname: Zhang fullname: Zhang, Chun-Yi – sequence: 2 givenname: Zhe-Shan surname: Yuan fullname: Yuan, Zhe-Shan – sequence: 3 givenname: Ze surname: Wang fullname: Wang, Ze – sequence: 4 givenname: Cheng-Wei orcidid: 0000-0001-5333-1055 surname: Fei fullname: Fei, Cheng-Wei – sequence: 5 givenname: Cheng orcidid: 0000-0002-5939-1048 surname: Lu fullname: Lu, Cheng |
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| Cites_doi | 10.1016/j.ijmecsci.2018.04.050 10.1016/j.ast.2015.11.025 10.1016/j.oceaneng.2015.07.032 10.1016/j.ast.2015.12.017 10.1016/j.cja.2016.06.017 10.1016/j.ast.2019.105466 10.1016/B978-0-444-89970-5.50007-8 10.1016/j.engfailanal.2015.04.009 10.1016/j.ast.2018.02.012 10.1016/j.nme.2016.05.017 10.1007/s11771-018-3946-x 10.1016/j.compstruc.2015.09.004 10.1016/j.ymssp.2016.05.026 10.1177/002199838602000202 10.3390/app9173578 10.1016/j.ast.2014.07.003 10.3390/ma12091545 10.1016/j.cma.2008.12.022 10.1016/j.engfracmech.2018.08.009 10.1007/s12666-010-0089-7 10.3390/en12091588 10.4028/www.scientific.net/KEM.697.664 10.1016/j.ast.2018.06.023 10.1016/j.engfailanal.2019.01.015 10.1155/2015/649046 10.1007/s11771-016-3079-z 10.1016/j.applthermaleng.2014.09.065 10.1016/j.ast.2019.06.026 10.1177/0954406214525137 10.1080/00207727308920064 10.1016/j.ijfatigue.2018.10.005 10.1016/j.ast.2017.01.018 10.1016/j.cma.2019.06.036 10.1016/j.ijfatigue.2019.05.005 10.1007/978-81-322-0487-9_74 10.1007/s11771-012-0978-5 10.1002/nme.1883 |
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| Snippet | To effectively perform the probabilistic fatigue/creep coupling optimization of a turbine bladed disk, this paper develops the fuzzy multi-extremum response... If we directly establish the reliability optimization design model of an overall structure involving multi-material, multi-disciplinary, and multi-physics... |
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| StartPage | 3367 |
| SubjectTerms | Accuracy Boundary conditions Collaboration Component reliability Computational efficiency Computer simulation Computing time Coupling Creep (materials) Damage Design optimization Design parameters Disks Efficiency Failure modes Fatigue failure Mathematical models Methods Model accuracy Neural networks Optimization Response surface methodology Turbines |
| Title | Probabilistic Fatigue/Creep Optimization of Turbine Bladed Disk with Fuzzy Multi-Extremum Response Surface Method |
| URI | https://www.proquest.com/docview/2333417127 https://www.proquest.com/docview/2306494489 https://pubmed.ncbi.nlm.nih.gov/PMC6829238 |
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