On Wind-Induced Fatigue of Curtain Wall Supporting Structure of a High-Rise Building
Due to the soft stiffness of high-rise buildings in the horizontal direction, strong wind will cause a strenuous structural response. Wind load is one key control load in the design of high-rise buildings. This study analyzes wind-induced fatigue of curtain wall supporting structure of a high-rise b...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/5/2547 |
| _version_ | 1797475596481069056 |
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| author | Haiyin Luo Zhengnong Li |
| author_facet | Haiyin Luo Zhengnong Li |
| author_sort | Haiyin Luo |
| collection | DOAJ |
| description | Due to the soft stiffness of high-rise buildings in the horizontal direction, strong wind will cause a strenuous structural response. Wind load is one key control load in the design of high-rise buildings. This study analyzes wind-induced fatigue of curtain wall supporting structure of a high-rise building in accordance with dynamic pressure measurement data of wind tunnel, acquiring wind pressure in each part of the structure. The finite element model is established for the curtain wall supporting structure, and the fatigue of corresponding nodes is discussed. Moreover, RBF (radial basis function) neural network regression is introduced to predict the fatigue life of unknown working conditions. Based on the joint distribution model of wind velocity and direction, this study explores the distribution law of fatigue life of supporting structure nodes, proposes a hypothesis of life distribution, and conducts a test. Moreover, working conditions with higher probability life are collected to provide a basis for practical engineering applications. The results show that the average deviation is below 10% by using RBF neural network and the probability life of the sample nodes is between 0 and 10<sup>16</sup>. Wind velocity is 8~15 m/s and azimuth angles of 50°~100°, 120°~200°, and 260°~300° are found in working conditions with low probability life; about 95% of the fatigue damage takes place in the first 30 conditions, and their fatigue damage values are between 3.5 × 10<sup>−3</sup>~9.36 × 10<sup>−2</sup>. |
| first_indexed | 2024-03-09T20:47:23Z |
| format | Article |
| id | doaj.art-284de3ff9d9f4c48a9380c3a669fcdfd |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T20:47:23Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-284de3ff9d9f4c48a9380c3a669fcdfd2023-11-23T22:42:32ZengMDPI AGApplied Sciences2076-34172022-02-01125254710.3390/app12052547On Wind-Induced Fatigue of Curtain Wall Supporting Structure of a High-Rise BuildingHaiyin Luo0Zhengnong Li1Key Laboratory of Building Safety and Efficiency of the Ministry of Education, Hunan University, Changsha 410082, ChinaKey Laboratory of Building Safety and Efficiency of the Ministry of Education, Hunan University, Changsha 410082, ChinaDue to the soft stiffness of high-rise buildings in the horizontal direction, strong wind will cause a strenuous structural response. Wind load is one key control load in the design of high-rise buildings. This study analyzes wind-induced fatigue of curtain wall supporting structure of a high-rise building in accordance with dynamic pressure measurement data of wind tunnel, acquiring wind pressure in each part of the structure. The finite element model is established for the curtain wall supporting structure, and the fatigue of corresponding nodes is discussed. Moreover, RBF (radial basis function) neural network regression is introduced to predict the fatigue life of unknown working conditions. Based on the joint distribution model of wind velocity and direction, this study explores the distribution law of fatigue life of supporting structure nodes, proposes a hypothesis of life distribution, and conducts a test. Moreover, working conditions with higher probability life are collected to provide a basis for practical engineering applications. The results show that the average deviation is below 10% by using RBF neural network and the probability life of the sample nodes is between 0 and 10<sup>16</sup>. Wind velocity is 8~15 m/s and azimuth angles of 50°~100°, 120°~200°, and 260°~300° are found in working conditions with low probability life; about 95% of the fatigue damage takes place in the first 30 conditions, and their fatigue damage values are between 3.5 × 10<sup>−3</sup>~9.36 × 10<sup>−2</sup>.https://www.mdpi.com/2076-3417/12/5/2547curtain wall supporting structurewind tunnel testfinite element analysisregression analysiswind-induced fatigue analysis |
| spellingShingle | Haiyin Luo Zhengnong Li On Wind-Induced Fatigue of Curtain Wall Supporting Structure of a High-Rise Building Applied Sciences curtain wall supporting structure wind tunnel test finite element analysis regression analysis wind-induced fatigue analysis |
| title | On Wind-Induced Fatigue of Curtain Wall Supporting Structure of a High-Rise Building |
| title_full | On Wind-Induced Fatigue of Curtain Wall Supporting Structure of a High-Rise Building |
| title_fullStr | On Wind-Induced Fatigue of Curtain Wall Supporting Structure of a High-Rise Building |
| title_full_unstemmed | On Wind-Induced Fatigue of Curtain Wall Supporting Structure of a High-Rise Building |
| title_short | On Wind-Induced Fatigue of Curtain Wall Supporting Structure of a High-Rise Building |
| title_sort | on wind induced fatigue of curtain wall supporting structure of a high rise building |
| topic | curtain wall supporting structure wind tunnel test finite element analysis regression analysis wind-induced fatigue analysis |
| url | https://www.mdpi.com/2076-3417/12/5/2547 |
| work_keys_str_mv | AT haiyinluo onwindinducedfatigueofcurtainwallsupportingstructureofahighrisebuilding AT zhengnongli onwindinducedfatigueofcurtainwallsupportingstructureofahighrisebuilding |