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論文中文名稱:使用粒子群演算法優化邊坡穩定分析 [以論文名稱查詢館藏系統]
論文英文名稱:Optimization of Slope Stability Analysis using Particle Swarm Optimization [以論文名稱查詢館藏系統]
院校名稱:臺北科技大學
學院名稱:工程學院
系所名稱:工程科技研究所
畢業學年度:102
出版年度:103
中文姓名:沈哲平
英文姓名:Zhe-Ping Shen
研究生學號:99679005
學位類別:博士
語文別:中文
口試日期:2013-05-10
論文頁數:247
指導教授中文名:陳偉堯
口試委員中文名:蔡富安;陳木松;朱子偉;張國楨
中文關鍵詞:三維雷射掃描儀粒子群演算法邊坡穩定分析
英文關鍵詞:3D laser scannerParticle swarm optimizationslope stability analysis
論文中文摘要:本研究以臺北市猴山岳崩塌處為研究區域,使用三維雷射掃描儀和高解析度環場影像紀錄地滑案例和地貌演變情形,使用工程領域廣泛運用的邊坡穩定分析軟體(STABL),透過粒子群演算法優化邊坡穩定分析,以尋找邊坡臨界滑動面,發展邊坡穩定分析評估流程。首先進行現地邊坡掃描,建置點雲資料生成數值高程模型,運用環場影像紀錄地貌變化與植生叢聚分布,經粒子群演算法優化邊坡穩定分析以搜尋較低安全因子,結合高精度數值高程模型及多重邊坡剖面的邊坡穩定分析,而得各邊坡剖面之潛在臨界滑動面。
邊坡穩定分析可評估現地邊坡的安穩情形,使用安全因子和邊坡臨界滑動面顯示潛在地滑風險,而高精度的地形資訊影響分析可靠度,透過粒子群演算法可快速於所有安全因子可能解中搜尋較佳解(由經典邊坡案例驗證,可搜尋到理論最佳解與相關文獻最優者;真實邊坡剖面分析顯示皆較無優化者為佳,平均優化效益為2.99%,最高為8.14%),而得對應的較高風險滑動面。
針對研究區域由2011年數值地形模型經GIS萃取之邊坡土體,切分多組邊坡剖面藉由STABL與PSO計算邊坡穩定性,在以0度方位角垂直切分DEM方面,平均優化效益為5.73%,最高為10.25%;在以45度方位角平行切分DEM方面,平均優化效益為6.85%,最高為11.11%;在使用0-359度方位角由最高點切分DEM方面,平均優化效益為4.36%,最高為20.05%,PSO皆能針對三種相異切分模式之邊坡剖面找到更小FS,且能修正無STABL初始解的問題,可顯著提升STABL對於較低FS和邊坡滑動面的搜尋成效。
論文英文摘要:This study used a 3-D laser scanner to scan landslides at Houshanyue in the Wenshan District of Taipei city. Using STABL and Particle Swarm Optimization (PSO) to find the critical slip surfaces of the slope under study. First, the slope was scanned to generate point cloud data, which in terms were used to create the Digital Elevation Model (DEM). Then, the slope analysis was optimized by PSO in order to calculate the lowest Factor of Safety (FS). In this study, the DEM was analyzed in many 2-D profiles of different orientations in order to find the most critical slip surface of each profile.
STABL is a computer program developed in FORTRAN for the general solutions of slope stability problems using 2-D limiting equilibrium methods. The slip surfaces with the smallest FS are the most critical slip surfaces. In such analyses, precise topographic profiles of the slope impact the stability analysis greatly. That’s why 3-D laser scanner was used in this research. The proposed approach was verified by the classic slope in the literature and the actual slope at Houshanyue. For the classic slope, the proposed approach found the best solution (same as the best solution in the literature). For the actual slope, the proposed method found better solutions for all profiles.
The DEM used in this study was scanned and created in 2011. The slope was first cut in parallel to generate many profiles with an azimeth of zero degree (due north). The average improvement of these profiles was 5.73%. Then, the slope was cut in 45-degree angles. The average improvement of the profiles became 6.85%. Finally, the slope was cut in radial directions from 0 to 359 degrees. The average improvement was 4.36%. These results proved that the proposed method could significantly improve the slope stability analysis, and the proposed method could discover better solutions in a very short amount of time for all profiles analyzed using the PSO.
論文目次:摘 要 i
ABSTRACT iii
誌 謝 v
目 錄 vii
表目錄 xi
圖目錄 xiii
第一章 緒論 1
1.1 前言 1
1.2 研究目的 2
1.3 研究方法 3
1.4 研究架構 4
第二章 文獻回顧 7
2.1 新興測量技術 8
2.1.1 三維雷射掃描儀 8
2.1.2 環場影像 10
2.2. 邊坡穩定之力學分析 10
2.2.1 極限平衡法 11
2.2.2 Ordinary Method of Slices 12
2.2.3 Simplified Janbu Method 12
2.2.4 Simplified Bishop Method 13
2.2.5 Spencer Method of Slices 14
2.2.6 塊體法 14
2.3 邊坡穩定之GIS分析 15
2.4 人工智慧 16
2.4.1 類神經網路 16
2.4.2 粒子群演算法 17
第三章 邊坡地滑量測分析 21
3.1 研究區域介紹 21
3.2 環境地質彙整 28
3.3 歷史地滑災害 30
3.4 三維雷射掃描儀量測 33
3.5 地形模型建置 36
3.6 環場影像拍攝 38
第四章 使用粒子群演算法與二維力學分析模式進行邊坡穩定分析 39
4.1 相異時期地形剖面線建置 39
4.2 STABL介紹 39
4.2.1 邊坡資料輸入格式 41
4.2.2 分析結果判讀 42
4.3 使用PSO優化STABL 44
4.3.1 經典邊坡測試案例之STABL分析 44
4.3.2 經典邊坡測試案例之窮舉法結合STABL分析 45
4.3.3 PSO優化潛在滑動面之求解空間 47
4.3.4 經典邊坡測試案例之PSO結合STABL分析 48
4.3.5 經典邊坡測試案例之PSO結合STABL分析結果 51
4.3.6 經典邊坡測試案例之前人研究成果比較 56
4.4 猴山岳的實例分析 58
4.4.1 現地邊坡概況 59
4.4.2 現地邊坡之三維雷射掃描儀監測 61
4.4.3 點雲資料之地表覆蓋物濾除 62
4.4.4 真實邊坡測試案例之PSO結合STABL分析 64
4.4.5 真實邊坡測試案例之PSO結合STABL分析結果 65
第五章 使用數值地形模型與二維力學分析模式進行邊坡穩定分析 77
5.1 使用三維雷射掃描儀與GIS計算邊坡剖面 77
5.2 相異地區之地形剖面線自動劃分 81
5.3 邊坡剖面結合STABL進行邊坡穩定分析 82
5.4 PSO結合STABL尋求各地形剖面最小安全因子 84
5.4.1 以0度方位角垂直切分DEM 86
5.4.2 以45度方位角平行切分DEM 89
5.4.3 以0-359度方位角由最高點切分DEM 91
第六章 結論與建議 103
6.1 結論 104
6.2 建議 105
參考文獻 107
附錄A: PSO結合STABL之臨界滑動面分析結果(以0度方位角垂直切分DEM) 119
附錄B: PSO結合STABL之臨界滑動面分析結果(以45度方位角平行切分DEM) 143
附錄C: PSO結合STABL之臨界滑動面分析結果(以0-359度方位角由最高點切分DEM) 155
附錄D: PSO結合STABL之臨界滑動面分析結果(微調求解空間邊界限制之分析) 239
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