publication . Article . 2014

Data Mining of the Thermal Performance of Cool-Pipes in Massive Concrete via In Situ Monitoring

Zheng Zuo; Yu Hu; Qingbin Li; Liyuan Zhang;
Open Access English
  • Published: 01 Jan 2014 Journal: Mathematical Problems in Engineering (issn: 1024-123X, eissn: 1563-5147, Copyright policy)
  • Publisher: Hindawi Limited
Abstract
Embedded cool-pipes are very important for massive concrete because their cooling effect can effectively avoid thermal cracks. In this study, a data mining approach to analyzing the thermal performance of cool-pipes via in situ monitoring is proposed. Delicate monitoring program is applied in a high arch dam project that provides a good and mass data source. The factors and relations related to the thermal performance of cool-pipes are obtained in a built theory thermal model. The supporting vector machine (SVM) technology is applied to mine the data. The thermal performances of iron pipes and high-density polyethylene (HDPE) pipes are compared. The data mining ...
Subjects
free text keywords: TA1-2040, Mathematics, Engineering (General). Civil engineering (General), QA1-939, Article Subject
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publication . Article . 2014

Data Mining of the Thermal Performance of Cool-Pipes in Massive Concrete via In Situ Monitoring

Zheng Zuo; Yu Hu; Qingbin Li; Liyuan Zhang;