岩性Markov预测下的长隧洞TBM施工进度随机仿真分析  

Stochastic Simulation and Risk Analysis of Water Tunnel TBM Construction Scheduling Based on Geologic Prediction Using Markov Process

作　　者：刘东海[1] 周云晴[1] 王帅[1] 章跃林[2] 

机构地区：[1]天津大学建筑工程学院,天津300072 [2]中水北方勘测设计有限责任公司,天津300222

出　　处：《系统仿真学报》2009年第2期558-562,共5页Journal of System Simulation

基　　金：国家自然科学基金(50709024)

摘　　要：长距离输水隧洞的TBM施工技术复杂,工序繁多,且受到众多不确定性因素(尤其是地质条件)的影响,给工程施工进度的安排及计划带来了相当的风险。在分析围岩岩性分布随机特性的基础上,提出了基于Markov过程的地质岩性风险预测方法,确定了沿隧洞轴线上岩性的分布概率,克服了以往方法难以量化地质风险的弊端,为定量分析地质风险提供了新的途径。在顾及岩性不确定性和工作活动时间随机性条件下,建立了针对不同岩性的TBM施工随机循环网络仿真模型,采用Monte-Carlo方法,对工程工期、完工概率以及资源利用情况进行了风险分析。工程实例应用表明本方法的可行性及有效性。There are many obstacles during the tunnel boring machine （TBM） construction of long water tunnel, which consist of complex construction techniques, various working procedures, and being affected by many uncertain factors, especially the geologic uncertainty. These would cause great risk for project planning and construction scheduling. Analyzing on the stochastic characteristics of the geologic spatial tendency, a method of geologic prediction was based on Markov process. With this method, the geologic state probabilities along the horizontal alignment of the tunnel could be determined. This is a new approach to quantitative analyses of the geological risk which the traditional methods have difficulty in measuring. Under consideration of the uncertainties of the geology and work activities duration, the models of stochastic cyclic network simulation （CYCLONE） for different geologic states were built. Using the Monte-Carlo simulation, the schedule risks, such as the reliability of project completion and the utilization rate of working resources, were obtained. The application of practical project shows that the method is feasible and effective.

关 键 词：TBM施工 施工进度 风险分析 随机循环网络仿真 地质预测 MARKOV过程 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]