砂土反覆Ko壓縮試驗及其行為模擬

Repeated Ko Compression Tests on Sand and Behavior Modeling

楊朝平(Chau-Ping Yang)

《中華水土保持學報》 31卷2期 (2000/06) Pp. 111-122

https://doi.org/10.29417/JCSWC.200006_31(2).0003

摘要

本文應用倒傳遞類神經網路（BPN）來模擬飽和砂土的壓縮行爲，此法截然不同於傳統的組成律。BPN爲監督式學習網路，可從問題領域的輸入變數值與輸出變數值中學習兩者間的內在映射規則，以應用於新的案例而達模擬預測之效果。模擬資料爲渥太華砂的反覆K_0壓縮試驗結果，此試驗乃是以自行研發之自動化三軸試驗系統施行之。研究結果發現，BPN可適用於土壤承受加壓，解壓，再加壓之複雜應力歷史的應力，應變行爲模擬。

關鍵字

類神經網路 ； 模擬 ； 砂土 ； 壓縮行爲

並列摘要

In this study, an attempt has been made to implement back propagation network (BPN) for modeling the compression behavior of a saturated sand. In the implementation of BPN, data are categorized as input patterns and target patterns. The input patterns are fed to the network, which then performs feed-forward computations to calculate target patterns. A mapping between input patterns and target patterns can be achieved through internal learning algorithms of BPN, resulting in a network capable of simulating the target patterns for a given input patterns. The simulating data are acquired from the repeated Ko compression tests of saturated Ottawa sand performed by automatic triaxial test system, which was developed by author. The work presented in this paper demonstrates that the simulating results agree with measured data.

並列關鍵字

artificial neural network ； modeling ； sand ； compression behavior