教師資料查詢 | 類別: 期刊論文 | 教師: 張正興 Cheng-hsin Chang (瀏覽個人網頁)

標題:Predicting Peak Pressures from Computed CFD Data and Artificial Neural Networks Algorithm
學年96
學期1
出版(發表)日期2008/01/01
作品名稱Predicting Peak Pressures from Computed CFD Data and Artificial Neural Networks Algorithm
作品名稱(其他語言)
著者Chang, Cheng‐Hsin; Shang, Neng‐Chou; Wu, Cho‐Sen; Chen, Chern‐Hwa
單位淡江大學土木工程學系
出版者Abingdon: Taylor & Francis
著錄名稱、卷期、頁數Journal of the Chinese Institute of Engineers=中國工程學刊 31(1), pp.95-103
摘要The goal of this paper is to predict the peak pressure coefficients by combining two simulation models, steady‐state Reynolds averaged CFD model and Artificial Neural Networks (ANN). Many previous studies have shown that CFD can predict mean pressure coefficients, Cp well if inlet profiles, grid adaptation and the turbulent model are well chosen. However, the design codes for wind loads are based on peak pressure coefficients in wind tunnel experiments. The combination of two simulation methods, CFD and ANN, allows us to predict the peak pressure coefficients. The peak surface pressure values on master WERFL models inside urban street canyons are determined by the prognostic model FLUENT using the k‐epsilon turbulence model and Artificial Neural Networks algorithm. The results are compared against fluid modeling from wind tunnel tests.
關鍵字CFD;artific neural networks;wind loads;wind tunnel
語言英文
ISSN0253-3839;2158-7299
期刊性質國外
收錄於EI
產學合作
通訊作者Chang, Cheng‐hsin
審稿制度
國別英國
公開徵稿
出版型式紙本;電子版
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