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系統識別號 U0026-0309201414461900
論文名稱(中文) 應用間接量測方法於橋樑沖刷預測與安全評估
論文名稱(英文) Proxy-Based Models for Bridge Scour Prediction and Safety Evaluation
校院名稱 成功大學
系所名稱(中) 土木工程學系
系所名稱(英) Department of Civil Engineering
學年度 102
學期 2
出版年 103
研究生(中文) 黃薰毅
研究生(英文) Hsun-Yi Huang
學號 n68961157
學位類別 博士
語文別 英文
論文頁數 109頁
口試委員 指導教授-馮重偉
口試委員-朱聖浩
口試委員-曾惠斌
口試委員-鄭道明
口試委員-黃盈樺
口試委員-楊亦東
中文關鍵字 橋梁沖刷  間接測量  基因演算法  類神經網路  蒙地卡羅模擬  自然震動頻率  有限元素法 
英文關鍵字 Bridge Scour  Genetic algorithms  Artificial neural networks  Monte Carlo method  Bridge natural frequency  Finite element method 
學科別分類
中文摘要   河水沖刷致使橋基裸露已業經調查為橋梁致災最重要原因之一,橋梁基礎沖刷行為是一個長期的過程,由於平時沖刷的累積,在汛期來臨,尤其遭受颱風侵襲時,致使橋梁基礎無法承受瞬間過大的沖刷而傾倒斷裂,進而造成重大的災害。由於橋梁基礎沖刷通常位於水面之下,不若其他橋梁構件可以目視檢測法初步判別橋損狀況,在基礎沖刷量測不易下,沖刷橋梁造成無預警的損壞倒塌,對用路人生命財產產生相當大的風險。
  防範未然,對橋梁沖刷狀況進行預測,事先掌握橋梁長期安全狀況的變化,適時進行補強工作為重要課題,然而預測的工作需要長期的資料記錄,由於量測的不易,大多數的橋梁並沒有相關的沖刷記錄,因此本研究透過分析提出具有描述沖刷過程的間接性指標:降雨事件、河床高層變化,來彌補橋梁沖刷資料不足的問題,透過基因演算法對事件進行程度分級並整合類神經網路與蒙地卡羅模擬法對未來橋梁安全進行預測,並考量極端氣候的情形,提出不同模擬情境,以提供橋梁管理單位參考。
  為解決橋梁沖刷量測不易的問題,本研究亦提出以間接性指標-橋梁自然頻率,來衡量橋梁基礎沖刷狀況。透過有限元素法以電腦模擬橋梁結構,計算在各種沖刷深度下自然頻率的變化,分析沖刷情形與頻率變化及各式橋梁環境因子的關係,透過支撐向量機建構各因子之間的關係,判別橋梁安全等級,降低沖刷量測與橋梁安全判別的困難度,亦有助於在橋梁沖刷方面的長期記錄參考。
英文摘要   In this thesis, two models were developed for the bridge scour issue: a bridge scour prediction model and a safety evaluation model. Bridge scour is a long-term process that occurs under water and cannot be observed directly. This results in sudden bridge failures and disasters.
  A reasonable model for predicting bridge scour and preventing bridge failures is important. However, because measuring scour is a difficult task, there is a shortage of scour records. Therefore, to establish a bridge scour prediction model, this thesis uses rainfall events and variance in riverbed elevations extracted from the literature as proxy indexes, and integrates genetic algorithms, artificial neural networks, and the Monte Carlo method. A real case is illustrated, and can provide a reference for bridge management authorities.
  Scouring around bridge piers is an important safety issue of bridge management since it can lead to bridge slanting and collapse. Since the water flow mechanism around a pier structure is complicated, it is very difficult to develop a generic model to determine the scour depth. Many researchers have tried to estimate the scour depth around bridge piers by simulating a bridge model with a consideration of various factors such as the depth of the water, the average flow velocity, and the diameter of the sand. However, most models require predefined conditions and can only be applied to certain types of bridges.
  In addition, the bridge natural frequency as another proxy index is introduced to evaluate the bridge scour conditions and reduce the difficulty in measuring the bridge scour. A complicated finite element model and a simple soil spring model, which is an improved form of the complicated finite element model, are implemented to simulate the bridge structure and compute the bridge natural frequency along the scour depth when considering various environmental variables. The complex relationship among factors is modeled using support vector machine and the level of safety can be efficiently determined.
  The results of this study will provide bridge management authorities with efficient and effective methods to predict bridge scour and evaluate the bridge status using proxy indexes to reduce the rate of disaster occurrence from bridge failures.
論文目次 中文摘要 i
Abstract ii
誌謝 iv
CONTENTS v
LIST OF TABLES viii
LIST OF FIGURES ix
Chapter 1 Introduction 1
1.1 Research background 1
1.2 Research objectives 3
1.3 Research scope 4
1.4 Research flowchart 5
1.5 Thesis organization 6
Chapter 2 Problem Statement and Literature Review 8
2.1 Problem statement 8
2.2 Mechanics of bridge scour 10
2.2.1 Introduction to bridge scour behavior, types, and factors 10
2.2.2 Literature review of bridge scour mechanics 13
2.2.3 Literature review of bridge scour depth analyses 14
2.2.4 Literature review of bridge safety prediction 16
2.3 Bridge scour field measurements 18
2.4 Evaluation of bridge conditions in Taiwan 21
2.5 Summary 23
Chapter 3 Methodology 25
3.1 Genetic Algorithms 25
3.1.1 Introduction 25
3.1.2 Chromosome Representation, Fitness Computation and Termination Procedure 27
3.1.3 Crossover, Mutation and Selection Schemes 28
3.1.4 GA features 32
3.2 Artificial Neural Networks 32
3.2.1 Overview of ANNs 33
3.2.2 Feed-forward back-propagation neural networks 35
3.2.3 Activation function 38
3.2.4 ANN features 40
3.3 Monte Carlo Method 41
3.4 Bridge Natural Frequency 43
3.4.1 Calculation of natural frequency 43
3.4.2 Effective mass and parallel subspace iteration methods 45
3.4.3 Complicated finite element model and simple soil spring model 46
3.5 Support vector machine 49
3.5.1 Introduction of support vector machine 50
3.5.2 Optimal parameter selection technique 53
3.6 Summary 54
Chapter 4 Proxy-based evaluation models for bridge scour 56
4.1 Model I: proxy-based scour bridge safety prediction 56
4.1.1 Crucial factors for extraction 57
4.1.2 Level determination for proxy index 61
4.1.3 Application of artificial neural networks 63
4.1.4 Monte Carlo simulation for rainfall events 65
4.2 Model II: proxy-based bridge scour condition evaluation 67
4.2.1 Programs for the bridge modeling 67
4.2.2 Environmental factors of bridge structure 69
4.2.3 Application of support vector machine 71
4.3 Summary 72
Chapter 5 Case study 74
5.1 Predicting level of bridge scour according to rainfall events 74
5.1.1 Case bridge information and data setting 74
5.1.2 Level determination of rainfall events using genetic algorithms 76
5.1.3 Simulation results 80
5.2 Scour condition estimation using bridge natural frequency 82
5.2.1 Case bridge information 82
5.2.2 Examination of the proposed approach 83
5.2.3 Analysis of bridge natural frequency and bridge foundation scour 85
5.2.4 Bridge scour safety level judgment using a support vector machine 94
5.3 Summary 98
Chapter 6 Conclusions and future research 100
6.1 Conclusions 100
6.2 Future research 102
Reference 104
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