Simulation of stationary non-Gaussian multivariate wind pressures using moment-based piecewise Hermite polynomial model

被引:27
作者
Liu, Min [1 ]
Peng, Liuliu [1 ]
Huang, Guoqing [1 ]
Yang, Qingshan [1 ]
Jiang, Yan [2 ]
机构
[1] Chongqing Univ, Sch Civil Engn, Chongqing 400044, Peoples R China
[2] Southwest Univ, Coll Engn & Technol, Chongqing 400715, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Simulation; Stationary; Non-Gaussian; Wind pressures; Multivariate random processes; Piecewise Hermite polynomial model; EFFICIENT METHODOLOGY; STOCHASTIC-PROCESS; EXPANSION; APPROXIMATE; DENSITY; FIELD; TIME;
D O I
10.1016/j.jweia.2019.104041
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The wind pressure at the flow separation region of building surfaces generally exhibits non-Gaussian characteristics and is modeled as a non-Gaussian random process. To evaluate the structural response under this non-Gaussian excitation, the time-domain response analysis is commonly used, especially in order to take into account the structural and aerodynamics nonlinearity. This makes the simulation of stationary non-Gaussian multivariate random processes becomes an essential task. The traditional correlation distortion simulation method based on the Hermite polynomial model (HPM) is widely used because it has relatively satisfactory simulation efficiency and is easy for the use. Nonetheless, its application range and simulation accuracy are restricted by the effective zone and modeling accuracy of the moment-based HPM. In this study, a novel correlation distortion simulation method using moment-based piecewise HPM (PHPM) is proposed, where the formulas of the PHPM corresponding to four cases, correlation distortion relationship and simulation scheme are developed. In comparison with the method using HPM, the proposed method has not only wider application range, but also higher simulation accuracy. To demonstrate the effectiveness of the proposed method, the simulations of measured univariate and multivariate non-Gaussian wind pressure data are conducted. Results show that for the example of wind pressures out of the monotonic region, which cannot be simulated by the method using HPM, the PDF and PSD of the simulated samples by the proposed method agree with the targets well. For the other examples, the simulation accuracy of the proposed method is overall higher than that of the simulation method using the moment-based HPM. These verify that the proposed method has larger applicability and higher accuracy than the simulation method using the HPM. Note that the proposed method can also be applied to simulate other non-Gaussian excitations such as the wind speed in the complex area.
引用
收藏
页数:14
相关论文
共 51 条
[1]  
[Anonymous], [No title captured]
[2]   Geometrically nonlinear cantilever under stochastic loading vectors [J].
Antonini, A ;
Gioffrè, M ;
Gusella, V .
NONLINEAR DYNAMICS, 2002, 28 (01) :83-102
[3]   Critical review and latest developments of a class of simulation algorithms for strongly non-Gaussian random fields [J].
Bocchini, Paolo ;
Deodatis, George .
PROBABILISTIC ENGINEERING MECHANICS, 2008, 23 (04) :393-407
[4]   The Hermite Moment Model for Highly Skewed Response With Application to Tension Leg Platforms [J].
Choi, Myoungkeun ;
Sweetman, Bert .
JOURNAL OF OFFSHORE MECHANICS AND ARCTIC ENGINEERING-TRANSACTIONS OF THE ASME, 2010, 132 (02) :1-8
[5]   Simulation of highly skewed non-Gaussian stochastic processes [J].
Deodatis, G ;
Micaletti, RC .
JOURNAL OF ENGINEERING MECHANICS-ASCE, 2001, 127 (12) :1284-1295
[6]   Simulation of ergodic multivariate stochastic processes [J].
Deodatis, G .
JOURNAL OF ENGINEERING MECHANICS, 1996, 122 (08) :778-787
[7]   Simulation of non-Gaussian field applied to wind pressure fluctuations [J].
Gioffrè, M ;
Gusella, V ;
Grigoriu, M .
PROBABILISTIC ENGINEERING MECHANICS, 2000, 15 (04) :339-345
[8]   Peak response of a nonlinear beam [J].
Gioffre, Massimiliano ;
Gusella, Vittorio .
JOURNAL OF ENGINEERING MECHANICS, 2007, 133 (09) :963-969
[9]   Influence of non-Gaussian wind characteristics on wind turbine extreme response [J].
Gong, Kuangmin ;
Chen, Xinzhong .
ENGINEERING STRUCTURES, 2014, 59 :727-744
[10]   Existence and construction of translation models for stationary non-Gaussian processes [J].
Grigoriu, M. .
PROBABILISTIC ENGINEERING MECHANICS, 2009, 24 (04) :545-551