考虑高寒低温影响的高心墙堆石坝仓面施工仿真模型研究

低温是影响高寒地区高心墙堆石坝施工的关键因素.然而,目前堆石坝施工仿真主要采用工程经验或者统计分析方法获得有效施工时长等参数从而间接反映气温对施工过程的影响,难以准确量化因高寒低温停工导致的施工进度滞后的影响,且缺乏考虑高寒施工环境下的保温工序,无法满足仓面施工仿真的精细化需求.针对以上问题,本文提出一个考虑高寒低温影...

Study on the simulation model of high-core rockfill dam construction in alpine region considering the influence of low temperature

Low temperature is a key influencing factor that impedes the construction progress of high-core rock-fill dams in alpine region. However,most of the existing simulation models of construction merely consider the effect of temperature on construction indirectly through parameters such as effective construction time which are acquired from engineering experience or statistical analysis methods. As a result, it is difficult to accurately quantify the impact of low temperature on the construction progress. Besides, such models put little consideration on the heat preservation measures in alpine region, which is incapable of meeting the high accuracy demand of the construction simulation of rockfill dam. To solve the above problems, this paper proposes a simulation model of the high-core rockfill dam construction in alpine region considering the influence of low temperature. First,a temperature time series prediction method based on the Particle Swarm Optimization Multilayer Perceptron (PSOMLP) is established. In this process, the hyperparameters of the multilayer perceptron (MLP) are optimized through the Particle Swarm Optimization algorithm (PSO) to solve the problems encountered in traditional MLP training process, including difficult determination of hyperparameters, low training efficiency and poor accuracy. Then, the prediction method is embedded in the construction simulation model to determine the accurate low-temperature shutdown time. Secondly, based on the Bootstrap method, the activity time of heat preservation measures is sampled and used to construct the simulation model of the high-core rockfill dam in alpine region which simultaneously considers the influence of the low-temperature shutdown and the added heat preservation measures. Engineering application results show that the proposed PSOMLP model has higher prediction accuracy than the traditional temperature prediction models, reducing the average error rate from 19.74% to 1.21%, which demonstrates that the qualification of the proposed method in quantifying the influence of low-temperature showdown and added heat preservation measures on construction progress. Therefore, the proposed model provides a new idea for the simulation of high-core rock-fill dam construction in alpine region.