A Conditional Simulation Method for Predicting Wind Pressure Fields of Large-Span Spatial Structures
Wind load is among the control loads for large-span spatial structures. Wind tunnel test is one of the commonly used methods for measuring wind pressure fields of different kinds of structures. However, due to the limited wind pressure data obtained from wind tunnel testing, it is quite meaningful t...
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Hindawi Limited
2021-01-01
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Series: | Shock and Vibration |
Online Access: | http://dx.doi.org/10.1155/2021/8829509 |
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doaj-fe41ca375cea48f69d74d8241621ac8f2021-07-19T01:03:40ZengHindawi LimitedShock and Vibration1875-92032021-01-01202110.1155/2021/8829509A Conditional Simulation Method for Predicting Wind Pressure Fields of Large-Span Spatial StructuresFangjin Sun0Tiantian Liu1Daming Zhang2Zhonghao Xu3 Guangxi Key Laboratory of New Energy and Building Energy SavingCollege of Civil EngineeringGuangxi Key Laboratory of Embedded Technology and IntelligenceCollege of Civil EngineeringWind load is among the control loads for large-span spatial structures. Wind tunnel test is one of the commonly used methods for measuring wind pressure fields of different kinds of structures. However, due to the limited wind pressure data obtained from wind tunnel testing, it is quite meaningful to employ the limited measured data to predict the unknown wind pressure at target points. Considering the complexity of wind pressure fields of large-span spatial structures, a simplified nonparametric method based on conditional simulation is proposed to predict the unknown pressures using the existing data. The Karhunen–Loève (KL for short) expansion is employed to represent wind pressure random variants as eigenfunctions of the covariance operator. To reduce the variant dimensionality, the nearest neighboring estimator is given for the transition distribution of the KL expansion. The targeted wind pressure fields are obtained by expanding the Fourier basis of the eigenfunction and estimating its expansion coefficients. The proposed method is applied to estimate wind pressures on a gable roof building. The relevant parameters of the wind pressure field are obtained, and the results compare well with those from wind tunnel testing, with higher efficiency. The proposed method effectively reduces the dimensionality of the predicted wind pressures, with reduced errors, higher accuracy, and increased efficiency.http://dx.doi.org/10.1155/2021/8829509 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Fangjin Sun Tiantian Liu Daming Zhang Zhonghao Xu |
spellingShingle |
Fangjin Sun Tiantian Liu Daming Zhang Zhonghao Xu A Conditional Simulation Method for Predicting Wind Pressure Fields of Large-Span Spatial Structures Shock and Vibration |
author_facet |
Fangjin Sun Tiantian Liu Daming Zhang Zhonghao Xu |
author_sort |
Fangjin Sun |
title |
A Conditional Simulation Method for Predicting Wind Pressure Fields of Large-Span Spatial Structures |
title_short |
A Conditional Simulation Method for Predicting Wind Pressure Fields of Large-Span Spatial Structures |
title_full |
A Conditional Simulation Method for Predicting Wind Pressure Fields of Large-Span Spatial Structures |
title_fullStr |
A Conditional Simulation Method for Predicting Wind Pressure Fields of Large-Span Spatial Structures |
title_full_unstemmed |
A Conditional Simulation Method for Predicting Wind Pressure Fields of Large-Span Spatial Structures |
title_sort |
conditional simulation method for predicting wind pressure fields of large-span spatial structures |
publisher |
Hindawi Limited |
series |
Shock and Vibration |
issn |
1875-9203 |
publishDate |
2021-01-01 |
description |
Wind load is among the control loads for large-span spatial structures. Wind tunnel test is one of the commonly used methods for measuring wind pressure fields of different kinds of structures. However, due to the limited wind pressure data obtained from wind tunnel testing, it is quite meaningful to employ the limited measured data to predict the unknown wind pressure at target points. Considering the complexity of wind pressure fields of large-span spatial structures, a simplified nonparametric method based on conditional simulation is proposed to predict the unknown pressures using the existing data. The Karhunen–Loève (KL for short) expansion is employed to represent wind pressure random variants as eigenfunctions of the covariance operator. To reduce the variant dimensionality, the nearest neighboring estimator is given for the transition distribution of the KL expansion. The targeted wind pressure fields are obtained by expanding the Fourier basis of the eigenfunction and estimating its expansion coefficients. The proposed method is applied to estimate wind pressures on a gable roof building. The relevant parameters of the wind pressure field are obtained, and the results compare well with those from wind tunnel testing, with higher efficiency. The proposed method effectively reduces the dimensionality of the predicted wind pressures, with reduced errors, higher accuracy, and increased efficiency. |
url |
http://dx.doi.org/10.1155/2021/8829509 |
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