溪洛渡拱坝施工期混凝土中期降温速率与通水冷却参数关系的数据挖掘模型
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摘要
针对现场施工数据冗余对日降温速率与通水参数的关联关系分析产生干扰的问题,建立了中期通水冷却参数关联规则挖掘的模型。首先确定日降温速率的主要影响因素,然后通过该模型从大坝温度历史监测数据中挖掘出定量的关联规则,确定主要调控的参数从而优化调整中期通水冷却措施。结果表明:为达到中期降温阶段日降温速率的要求,通水温度宜控制在(14.6,14.8]℃内,混凝土初始温度宜控制在(17.7,18.5]℃内,通水流量宜控制在(15.0,22.5]L/min内;并应该重点调控通水流量,在设置冷却通水流量的初始值时可将其预先设定在(15.0,22.5] L/min范围内。研究成果对于制定中期冷却通水措施具有指导价值。
A model of association rule mining for the mid-term water cooling parameters is established to tackle the interference of redundant construction data on analyzing the correlation between daily cooling rate and water-cooling parameters. First, the main factors affecting the daily cooling rate are determined, and then the quantitative association rules are extracted from the history monitoring data of dam temperature. On such basis, the main control parameters are determined so as to optimize the mid-term water cooling measures. Results suggest that the water-cooling temperature should be controlled within(14.6,14.8]℃ so as to meet requirements, the initial temperature of concrete should be in(17.7,18.5]℃, and water flow rate between(15.0,22.5] L/min. Water flow rate should be regarded as control focus, so the initial value of cooling flow rate can be preset as within(15.0,22.5] L/min. The research finding is of guiding significance for deciding mid-term cooling measures.
A model of association rule mining for the mid-term water cooling parameters is established to tackle the interference of redundant construction data on analyzing the correlation between daily cooling rate and water-cooling parameters. First, the main factors affecting the daily cooling rate are determined, and then the quantitative association rules are extracted from the history monitoring data of dam temperature. On such basis, the main control parameters are determined so as to optimize the mid-term water cooling measures. Results suggest that the water-cooling temperature should be controlled within(14.6,14.8]℃ so as to meet requirements, the initial temperature of concrete should be in(17.7,18.5]℃, and water flow rate between(15.0,22.5] L/min. Water flow rate should be regarded as control focus, so the initial value of cooling flow rate can be preset as within(15.0,22.5] L/min. The research finding is of guiding significance for deciding mid-term cooling measures.
引文
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[2] 朱伯芳.混凝土坝理论与技术新进展[M].北京:中国水利水电出版社,2009.
[3] 付学奎,周宜红,黄耀英,等.基于BP神经网络的坝体混凝土二期通水冷却分析[J].水利水电技术,2012,43(2):50-53.
[4] 周艳国,王江,徐晗.小湾拱坝二期冷却方案温控措施对比分析[J].长江科学院院报,2009,26(7):48-51.
[5] 黄耀英,周绍武,付学奎,等.中后期冷却期间混凝土浇筑仓温度动态预测模型[J].四川大学学报(工程科学版),2013,45(4):34-38.
[6] 黄耀英,周绍武,郑东健,等.混凝土坝中后期通水快速调控研究 [J].长江科学院院报,2014,31(12):92-96.
[7] OLIINYK A,SUBBOTIN S A.A Stochastic Approach for Association Rule Extraction[J].Pattern Recognition and Image Analysis,2016,26(2):419-426.
[8] AFSHARI M H,DEHKORDI M N,AKBARI M.Association Rule Hiding Using Cuckoo Optimization Algorithm[J].Expert Systems with Applications,2016,64:340-351.
[9] 李洋波,黄达海.高拱坝施工的温控数据库系统 [J].武汉大学学报(工学版),2008,41(4):52-55.
[10] 李洋波,黄达海,黄玮,等.溪洛渡拱坝温控数据库的功能[J].水电站设计,2008,(4):105-107.
[11] 刘德福,黄达海,田斌.拱坝封拱温度场及温控优化[M].北京:中国水利水电出版社,2008.
[12] 张锐,李庆中,周伟.几个参数对拱坝温度及应力影响的研究[J].长江科学院院报,2009,26(3):44-48.
[13] 朱优平,李同春,冯树荣,等.大体积混凝土温控通水参数优选数学模型[J].长江科学院院报,2015,32(8):126-130.
[14] 张宇鑫.大体积混凝土温度应力仿真分析与反分析[D].大连:大连理工大学,2002.