| A LSTM surrogate modelling approach for caisson foundations | |
Zhang P1,2 ; Yin ZY1; Zheng YY3,4; Gao FP(高福平)5,6
| |
| Corresponding Author | Yin, Zhen-Yu([email protected]) |
| Source Publication | OCEAN ENGINEERING
 |
| 2020-05-15 | |
| Volume | 204Pages:13 |
| ISSN | 0029-8018 |
| Abstract | This study proposes a hybrid surrogate modelling approach with the integration of deep learning algorithm long short-term memory (LSTM) to identify the mechanical responses of caisson foundations in marine soils. The LSTM based surrogate model is first trained based on limited results generated from the SPH-SIMSAND based numerical simulations with a strong validation, thereafter it is applied to predict the mechanical responses of soil-structure interaction and the failure envelope of unknown caisson foundations with various specifications as testing. The results indicate that the LSTM based model is more flexible than macro-element method, because it can directly learn the failure mechanism of caisson foundation from the raw data, meanwhile guarantees a high computational efficiency and accuracy in comparison with physical and numerical modelling. LSTM based surrogated model shows a great potential of application in engineering practice. |
| Keyword | Caisson foundation Failure envelope Smoothed particle hydrodynamics Long short-term memory |
| DOI | 10.1016/j.oceaneng.2020.107263 |
| Indexed By | SCI ; EI |
| Language | 英语 |
| WOS ID | WOS:000530233700003 |
| WOS Keyword | SUCTION CAISSONS ; HYPOPLASTIC MACROELEMENT ; SHALLOW FOUNDATIONS ; CIRCULAR FOOTINGS ; SAND ; BEHAVIOR ; CAPACITY ; SOIL ; SETTLEMENTS ; PREDICTION |
| WOS Research Area | Engineering ; Oceanography |
| WOS Subject | Engineering, Marine ; Engineering, Civil ; Engineering, Ocean ; Oceanography |
| Funding Project | Research Grants Council (RGC) of Hong Kong Special Administrative Region Government (HKSARG) of China[PolyU R5037-18F] ; Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)[GML2019ZD0503] |
| Funding Organization | Research Grants Council (RGC) of Hong Kong Special Administrative Region Government (HKSARG) of China ; Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) |
| Classification | 一类 |
| Ranking | 4 |
| Contributor | Yin, Zhen-Yu |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://dspace.imech.ac.cn/handle/311007/82019 |
| Collection | 流固耦合系统力学重点实验室 |
| Affiliation | 1.Hong Kong Polytech Univ, Dept Civil & Environm Engn, Hung Hom, Kowloon, Hong Kong, Peoples R China; 2.Southern Marine Sci & Engn Guangdong Lab Guangzho, 1119 Haibin Rd, Guangzhou, Peoples R China; 3.Sun Yat Sen Univ, Sch Civil Engn, Guangzhou 510275, Peoples R China; 4.Southern Marine Sci & Engn Guangdong Lab Zhuahai, Zhuahai, Peoples R China; 5.Chinese Acad Sci, Inst Mech, Key Lab Mech Fluid Solid Coupling Syst, Beijing 100190, Peoples R China; 6.Univ Chinese Acad Sci, Sch Engn Sci, Beijing 100049, Peoples R China |
| Recommended Citation GB/T 7714 | Zhang P,Yin ZY,Zheng YY,et al. A LSTM surrogate modelling approach for caisson foundations[J]. OCEAN ENGINEERING,2020,204:13.Rp_Au:Yin, Zhen-Yu |
| APA | Zhang P,Yin ZY,Zheng YY,&高福平.(2020).A LSTM surrogate modelling approach for caisson foundations.OCEAN ENGINEERING,204,13. |
| MLA | Zhang P,et al."A LSTM surrogate modelling approach for caisson foundations".OCEAN ENGINEERING 204(2020):13. |
| Files in This Item: | Download All | |||||
| File Name/Size | DocType | Version | Access | License | ||
| Jp2020137.pdf（3376KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Download | |
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment