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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/34563

    Title: 基因演算法應用於衝擊性撓度儀回算之研究
    Other Titles: Backcalculation for FWD deflections of pavements using genetic algorithm
    Authors: 江克培;Jiang, Ke-pei
    Contributors: 淡江大學土木工程學系碩士班
    張德文;Chang, Der-wen
    Keywords: 動態回算;基因遺傳演算法;初始族群;突變率;dynamic backcalculation;Genetic Algorithm;initialization population;mutation
    Date: 2005
    Issue Date: 2010-01-11 05:23:15 (UTC+8)
    Abstract: 傳統的試驗數據回算一般多以靜態方式完成,但由實務及研究經驗顯示,靜態回算無法有效地模擬動態試驗,更無法穩定的處理觀測數據,致使撓度法於鋪面工程中之運用常止於觀摩與比較,肇於此,本研究使用格林柔度方程式解模擬鋪面動態應力波行為,並結合基因遺傳演算法發展動態回算分析,以擴充撓度法試驗的應用範圍。研究另蒐集國內落重儀現地試驗,以迭代法、資料庫法、基因遺傳算法和MODULUS回算程式所得與實驗室試驗數據比較,確定各項分析法之可信度。

    Conventional data interpretation of the deflection test on pavements is mostly accomplished using the static analysis. However according to the practice and the study experiences, the static analysis could not accurately model the dynamic testing and stably handle the predictions. The deflection test needs to be analyzed carefully in order to provide reliable information of the pavements. This study uses the dynamic Green’s functions to model the stress waves propagating along the pavements. The Genetic Algorithms (GA) is incorporated with the program to develop the dynamic backcalculation analysis of the Falling Weight Deflectometer (FWD) test. In-situ deflection data of the FWD test were collected and analyzed. Comparison and validation were carried for dynamic backcalculation programs using the iterative, data bank and this method with the static backcalculation program MODULUS. The laboratory results were also used for comparisons.

    Results of this study indicate that the dynamic backcalculation can reflect the pavement structure more truthfully than the static conventional analysis. A dynamic backcalculation program UTFWD-GA is thus suggested to evaluate the pavements for the FWD test. According to the parametric studies, the backcalculation time would increase with the number of populations and generations. The optimized results could be found for the GA method of the four layered flexible pavement structures, where the initialization populations is 140, and mutation is 0.1. The associated RMS errors of the moduli and the deflections were found less than 2%. Although the dynamic backcalculation results were found agreeable with each other, they would be different from static backcalculation and lab data. Nevertheless, the predictions on the same road were varied at different sections. The applications need to be restudied carefully.
    Appears in Collections:[Graduate Institute & Department of Civil Engineering] Thesis

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