高海峰

教授

电子邮箱:gaohaifeng@shu.edu.cn



l 个人简介

1066vip威尼斯机自学院副教授、硕士生导师,中国机械工程学会高级会员,上海市科技专家库专家,上海市教育评估协会专家,多个国际期刊编委、学术编辑、审稿人。

长期从事航空航天可靠性工程,主要致力于航空发动机结构强度、振动及其可靠性设计与多学科优化的研究工作。博士毕业于北京航空航天大学航空宇航推进理论与工程专业,博士后工作于上海交通大学和意大利米兰理工大学,并继续保持紧密合作。主持和参与了国家自然科学基金、“两机专项”、先进航空发动机协同创新、博士后基金、北航博士研究生创新基金等多项国家级和省部级项目;以第一/通讯作者发表SCI学术论文10余篇,参编外文专著1部。

l 主要研究领域

1多物理场耦合动力学分析

2多源不确定性建模与分析

3、高温结构疲劳寿命预测与多目标优化

4、基于人工智能算法的可靠性与故障评估



l 代表性成果

以第一/通讯作者在《Reliability Engineer & System Safety》、Aerospace Science and Technology》、《Engineering Failure Analysis》等国内外学术期刊发表SCI论文10余篇。


著作

1Gao H F, Zio E, Bai G C. Low-cycle fatigue damage assessment of turbine blades using a substructure-based reliability approach. In: Stochastic Models in Reliability Engineering. CRC Press, 2020.


论文

1Gao H F, Wang A, Zio E, Bai G C. An integrated reliability approach with improved importance sampling for low-cycle fatigue damage prediction of turbine disks. Reliability Engineering & System Safety, 2020, 199.

2Gao H F, Zio E, Wang A, Bai G C, Fei C W. Probabilistic-based combined high and low cycle fatigue assessment for turbine blades using a substructure-based kriging surrogate model. Aerospace Science and Technology, 2020, 104.

3Gao H F, Zio E, Guo J J, Bai G C, Fei C W. Dynamic probabilistic- based LCF damage assessment of turbine blades regarding time-varying multi-physical field loads. Engineering Failure Analysis, 2020, 108.

4Gao H F, Wang A, Bai G C, Wei C M, Fei C W. Substructure-based distributed collaborative probabilistic analysis method for low-cycle fatigue damage assessment of turbine blade-disk. Aerospace Science and Technology, 2018, 79(08): 636-646.

5Gao H F, Fei C W, Bai G C, Ding L. Reliability-based low-cycle fatigue damage analysis for turbine blade with thermo-structural interaction. Aerospace Science and Technology, 2016(02), 49: 289-300.



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