Multi-objective optimization of the design and operation for snow-melting pavement with electric heating pipes. (25th July 2017)

• Record Type: Journal Article
• Authors: Liu, Kai; Huang, Silu; Xie, Hongzhou; Wang, Fang
• Is Part Of: Applied thermal engineering. Volume 122(2017)
• Page Start: 359
• Page End: 367
• Publication Date: 2017-07-25
• Subjects: Snow-melting pavement -- Thermal simulation -- Response surface methodology -- Prediction model -- Energy utilization analysis -- Multi-objective optimization; Heat engineering -- Periodicals; Heating -- Equipment and supplies -- Periodicals; Periodicals; 621.40205
• DOI: 10.1016/j.applthermaleng.2017.05.033
• Languages: English
• ISSNs: 1359-4311

Abstract

Highlights: The operation of SMP-EHP is simulated by the numerical model. The prediction models for THT and LER of SMP-EHP are proposed by RSM. The effects of different parameters on THT and LER are analyzed and compared. The optimization parameters for the SMP-EHP are obtained by multi-objective optimization. The optimization targets are heating time saving and energy saving. Abstract: Snow-melting pavement with electric heating pipes (SMP-EHP) is used to mitigate the accumulated snow problem for large longitudinal slopes or slippery roads. To improve its operation efficiency, the structural model and thermal simulations of the SMP-EHP were studied. The electric heating pipe's embedded spacing ( s ) and embedded depth ( d ), the heating power ( P ) and the wind velocity ( v ) were considered as the input parameters. The total heating time (THT) and the lost energy rate (LER) for the melting process were considered as the prediction responses. The prediction models for THT and LER were proposed by using Response Surface Methodology (RSM). The single input parameter's effects on prediction responses and the interactions between them were analyzed by the assisted thermal simulation. The rationality of the prediction models and simulations were validated by statistical analysis and experiments. Additionally, for decreasing THT, LER, a multi-objective optimization on THT and the lost energy (LE) was built through the genetic algorithm. Through optimization, the recommended parameters are proposed. The results and suggestions could efficiently guide the operation of SMP-EHP.