长江科学院院报 ›› 2022, Vol. 39 ›› Issue (2): 141-146.DOI: 10.11988/ckyyb.20201119

• 水工结构与材料 • 上一篇    下一篇

高拱坝混凝土一期控温阶段温度变化动态预测方法

黄建文1,2, 李飞翔1, 袁华3, 王兴霞1,2, 江谊园4, 叶林华4   

  1. 1.三峡大学 水利与环境学院,湖北 宜昌 443002;
    2.三峡大学 水电工程施工与管理湖北省重点实验室,湖北 宜昌 443002;
    3.中水北方勘测设计研究有限责任公司,天津 300222;
    4.中国葛洲坝集团三峡建设工程有限公司,湖北 宜昌 443000
  • 收稿日期:2020-11-02 修回日期:2021-03-05 出版日期:2022-02-01 发布日期:2022-02-01
  • 作者简介:黄建文(1977-),男,湖北黄陂人,教授,博士,硕士生导师,主要从事水电工程施工组织管理与系统仿真研究。E-mail: jwhuang@ctgu.edu.cn
  • 基金资助:
    国家自然科学基金项目(51879147,52009069);水电工程施工与管理湖北省重点实验室开放基金项目(2019KSD03)

Dynamically Predicting Temperature Change in the First Phase Temperature Control Stage for High Arch Dam Concrete

HUANG Jian-wen1,2, LI Fei-xiang1, YUAN Hua3, WANG Xing-xia1,2, JIANG Yi-yuan4, YE Lin-hua4   

  1. 1. College of Hydraulic and Environmental Engineering, China Three Gorges University, Yichang 443002, China;
    2. Hubei Key Laboratory of Construction and Management in Hydropower Engineering, China Three Gorges University, Yichang 443002, China;
    3. China Water Resources Beifang Investigation, Design and Research Co., Ltd., Tianjin 300222, China;
    4. China Gezhouba Group Three Gorges Construction Engineering Co., Ltd., Yichang 443000, China
  • Received:2020-11-02 Revised:2021-03-05 Published:2022-02-01 Online:2022-02-01

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摘要： 为了能够提前获知一期控温阶段混凝土短期内温度变化趋势,及时采取相应温控措施,防止温度裂缝产生,以高拱坝施工期浇筑仓混凝土为研究对象,分析初始温度、通水冷却、绝热温升、环境气温及层面散热等因素对浇筑仓混凝土温度的综合影响,建立适时动态更新初温的高拱坝混凝土一期控温阶段温度变化动态预测模型。同时,考虑不同浇筑仓混凝土的差异性,运用非线性优化法对模型的重要参数进行优化求解,并运用最大绝对误差、平均绝对误差、相对误差等评价指标检验预测模型的精度。最后结合工程实例,以2 d为步长更新初始温度并优化参数,以12 d为龄期,对浇筑仓混凝土温度进行预测,结果表明模型预测值与实测值的最大绝对误差在0.6 ℃以内,平均绝对误差在0.2 ℃以内,相对误差在0.9%以内,预测精度满足施工现场需求。

关键词: 混凝土, 一期控温, 通水冷却, 绝热温升, 动态预测, 非线性优化

Abstract: The aim of this research is to obtain in advance the short-term temperature change trend of concrete in the first stage of temperature control, and take corresponding temperature control measures in time to prevent from temperature cracks. With high arch dam concrete in construction period as the research object, we examined the comprehensive influences of initial temperature, water cooling, adiabatic temperature rise, environmental temperature and layer heat dissipation on the concrete temperature of pouring warehouse, and then established a dynamic prediction model of temperature change in the first stage temperature control stage of high arch dam concrete by timely updating the initial temperature. Furthermore, in view of the difference of concrete in different pouring warehouses, we adopted the nonlinear optimization method to optimize the important parameters of the model, and verified the accuracy of the model using such indicators as maximum absolute error (MAE), average absolute error (AAE) and relative error (RE). With engineering practice as case study, we updated the initial temperature with 2 days as the step and optimized the model parameters, and predicted the concrete temperature of the pouring warehouse with 12 days as the age of concrete. The maximum absolute error (MAE) between predicted value and measured value is within 0.6 ℃, the average absolute error (AAE) within 0.2 ℃, and the relative error (RE) within 0.9%. The prediction accuracy of the model meets the requirements of the construction site.

Key words: concrete, first stage of temperature control, water cooling, adiabatic temperature rise, dynamic prediction, nonlinear optimization

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