非高斯风场作用下桥梁抖振响应研究

罗颖; 任达程; 韩艳; 董国朝

doi:10.7638/kqdlxxb-2022.0085

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非高斯风场作用下桥梁抖振响应研究

研究论文 | 更新时间：2026-05-28

- 非高斯风场作用下桥梁抖振响应研究
- Study on buffeting response of bridge under non-Gaussian wind field
- 空气动力学学报 2023年41卷第8期页码：107-116
- 作者机构：
  
  长沙理工大学土木工程学院,长沙,410114
- 作者简介：
  
  罗颖*（1990-），男，湖南人，讲师，研究方向：结构风荷载及桥梁风致振动. E-mail：luoying20080138@163.com
- 基金信息：
  
  国家自然科学基金（51908074，52178452，52178451）;湖南省教育厅科学研究项目（20C0055）;长沙理工大学土木工程优势特色重点学科创新性项目（18ZDXK16）
- DOI：10.7638/kqdlxxb-2022.0085
  中图分类号： U441+.3
- 纸质出版：2023
- 稿件说明：
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罗颖, 任达程, 韩艳, 等. 非高斯风场作用下桥梁抖振响应研究[J]. 空气动力学学报, 2023, 41(8): 107−116.

LUO Ying, REN Dacheng, HAN Yan, et al. Study on buffeting response of bridge under non-Gaussian wind field[J]. 2023, 41(8): 107-116.
罗颖, 任达程, 韩艳, 等. 非高斯风场作用下桥梁抖振响应研究[J]. 空气动力学学报, 2023, 41(8): 107−116. DOI： 10.7638/kqdlxxb-2022.0085

LUO Ying, REN Dacheng, HAN Yan, et al. Study on buffeting response of bridge under non-Gaussian wind field[J]. 2023, 41(8): 107-116. DOI： 10.7638/kqdlxxb-2022.0085.

摘要

为研究非高斯风场作用下桥梁结构的抖振响应特性，以太洪长江大桥为例，基于Hermite多项式模型，模拟了非高斯脉动风场时程，计算了不同平均风速下不同非高斯特性脉动风场的抖振响应。结果表明：非高斯风场作用下结构响应的幅值和均方根值均比高斯风场更大，非高斯特性越强，均方根值越大；随着平均风速的增加，风场峰度对结构响应均方根的影响逐渐明显。因此，对于非高斯风场，高斯过程假定低估了实际的响应情况。此外，不同非高斯特性脉动风场作用下，结构响应的偏度和峰度均趋近高斯过程的结果。

Abstract

Taking Taihong Yangtze River Bridge as an example

the buffeting response of the bridge under non-Gaussian wind field is studied. Firstly

based on Hermite polynomial model

the time history of the non-Gaussian fluctuating wind field is simulated. Subsequently

the corresponding wind load time history is calculated

and the time domain analysis of the buffeting response of the bridge is carried out. Finally

by comparing the response results of fluctuating wind fields with different non-Gaussian characteristics under various mean wind speeds

the influence of non-Gaussian characteristics of wind field on the buffeting response of the bridge structure is discussed. The results show that the amplitude and root mean square (RMS) of the buffeting response under non-Gaussian wind field are larger than the counterparts under Gaussian wind field

and stronger non-Gaussian characteristics correspond to larger RMS. With the increase of mean wind speed

the influence of kurtosis of the wind field on the RMS of the response becomes more obvious. Therefore

the Gaussian process assumption underestimates the actual response of a non-Gaussian wind field. In addition

the skewness and kurtosis of the buffeting response under fluctuating wind field with different non-Gaussian characteristics are similar to the results of the Gaussian process.

关键词

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references

Davenport A G. Buffetting of a suspension bridge by storm winds[J]. Journal of the Structural Division, 1962, 88(3): 233-270.https://ascelibrary.org/doi/abs/10.1061/JSDEAG.0000773

DAVENPORT A G. The response of slender, line-like structures to a gusty wind[C]// Proceedings of the Institution of Civil Engineers, 1962, 23(3): 389-408. doi: 10.1680/iicep.1962.10876

DING Q S. Refinement of coupled flutter and buffeting analysis for long-span bridges[M]. Shanghai: Tongji University Press, 2007(in Chinese).

ZHAO L, WU F Y, PAN J J, et al. Wind field characteristics and wind-induced buffeting response of a long-span bridge during the landing of a strong typhoon[J]. Acta Aerodynamica Sinica, 2021, 39(4): 85-97(in Chinese). [万方]

HU X H, YANG S Y, LI Y L, et al. Study of buffeting response and suppression measures for composite girder cable-stayed bridge in longest cantilever state during construction[J]. Bridge Construction, 2021, 51(1): 21-28(in Chinese). [万方]

HAN Y, LIU Y F, LIU Z W, et al. The wind-induced buffeting response and fatigue damage analysis of the cables of Jiang-shun bridge[J]. Journal of Changsha University of Science and Technology (Natural Science), 2016, 13(3): 50-57 (in Chinese).

RICE S O. Mathematical analysis of random noise[J]. Bell System Technical Journal, 1944, 23(3): 282-332. DOI:10.1002/j.1538-7305.1944.tb00874.x[LinkOut]

DEODATIS G. Simulation of ergodic multivariate stochastic processes[J]. Journal of Engineering Mechanics, 1996, 122(8): 778-787. DOI: 10.1061/(ASCE)0733-9399(1996)122:8(778)[LinkOut]

YANG X J, HUANG J S, ZHANG J G, et al. Effective simulation of stochastic fluctuating wind field of transmission tower-line system based on interpolation and dimension reduction method[J]. Journal of Vibration and Shock, 2021, 40(9): 77-83 (in Chinese).

NIELSEN M, LARSEN G C, MANN J, et al. Wind simulation for extreme and fatigue loads[R ] . Ris∅ -R-1437(EN), 2004: 1-104. https://www.osti.gov/etdeweb/servlets/purl/20435973

DU X Q, JIN X Y, XU H L, et al. Uniform flow mechanism of non-Gaussian features of pressure on square cylinder[J]. Journal of Tongji University (Natural Science), 2020, 48(2): 191-199 (in Chinese).

MA X L. Research of non-Gaussian characteristics of bridge wind loads[D]. Dalian: Dalian University of Technology, 2015 (in Chinese).

YAMAZAKI F, SHINOZUKA M. Digital generation of non-Gaussian stochastic fields[J]. Journal of Engineering Mechanics, 1988, 114(7): 1183-1197. DOI:10.1061/(asce)0733-9399(1988)114:7(1183)[LinkOut]

KARMAKAR D, RAY-CHAUDHURI S, SHINOZUKA M. Conditional simulation of non-Gaussian wind velocity profiles: application to buffeting response of Vincent Thomas suspension bridge[J]. Probabilistic Engineering Mechanics, 2012, 29: 167-175. DOI:10.1016/j.probengmech.2011.11.005[LinkOut]

LI J H, LI C X, DENG Y, et al. Simulation of multivariate non-Gaussian fluctuating wind pressure based on AR and ARMA models[J]. Journal of Vibration and Shock, 2017, 36(24): 103-107, 123 (in Chinese).

WEN Q. Simulation of non-Gaussian stochastic process based on spectral representation method[D]. Shenzhen: Shenzhen University, 2020 (in Chinese).

GUSELLA V, MATERAZZI A L. Non-Gaussian along-wind response analysis in time and frequency domains[J]. Engineering Structures, 2000, 22(1): 49-57. DOI:10.1016/S0141-0296(98)00074-1

CHANG G C. Extreme response analysis of transmission tower under non-Gaussian wind[D]. Chengdu: Southwest Jiaotong University, 2015 (in Chinese).

CUI W, ZHAO L, GE Y J. Non-Gaussian turbulence induced buffeting responses of long-span bridges[J]. Journal of Bridge Engineering, 2021, 26(8): 04021057. DOI:10.1061/(asce)be.1943-5592.0001747[LinkOut]

CUI W, ZHAO L, GE Y J. Non-Gaussian turbulence induced buffeting responses of long-span bridges based on state augmentation method[J]. Engineering Structures, 2022, 254: 113774. DOI:10.1016/j.engstruct.2021.113774[LinkOut]

GRIGORIU M. Crossings of non-Gaussian translation processes[J]. Journal of Engineering Mechanics, 1984, 110(4): 610-620. DOI:10.1061/(asce)0733-9399(1984)110: 4(610)[LinkOut]

ABRAMSON N. Nonlinear transformations of random processes[J]. IEEE Transactions on Information Theory, 1967, 13(3): 502-505Doi:10.1109/TIT.1967.1054033

WINERSTEIN S R. Nonlinear vibration models for extremes and fatigue[J]. Journal of Engineering Mechanics, 1988, 114(10): 1772-1790. DOI:10.1061/(asce)0733-9399(1988)114: 10(1772)[LinkOut]

GURLEY K R, KAREEM A, TOGNARELLI M A. Simulation of a class of non-normal random processes[J]. International Journal of Non-Linear Mechanics, 1996, 31(5): 601-617. DOI:10.1016/0020-7462(96)00025-X[LinkOut]

YANG L P, GURLEY K R. Efficient stationary multivariate non-Gaussian simulation based on a Hermite PDF model[J]. Probabilistic Engineering Mechanics, 2015, 42: 31-41. DOI:10.1016/j.probengmech.2015.09.006[LinkOut]

LI Q C, LIN Y K. New stochastic theory for bridge stability in turbulent flow. II[J]. Journal of Engineering Mechanics, 1995, 121(1): 102-116. DOI:10.1061/(asce)0733-9399(1995)121:1(102)[LinkOut]

HUANG G Q, PENG L L, LIAO H L, et al. Field measurement study on wind characteristics at puli great bridge site in mountainous area[J]. Journal of Southwest Jiaotong University, 2016, 51(2): 349-356 (in Chinese).

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