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基于Fluent模拟区域水体热污染预测研究
Research on Thermal Pollution Prediction in Regional Water Based on Fluent

DOI: 10.12677/JWRR.2015.46062, PP. 496-505

Keywords: 热污染,区域水体,Fluent,模拟
Thermal Pollution
, Regional Water, Fluent, Simulation

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Abstract:

本文建立了一个用于预测评估电厂温排水对受纳水体水温分布影响情况的数学模型,通过对国内某电厂在河流夏季和冬季两种不利的水文条件下,就电厂运行正常工况和非正常工况两种情况下,对温排水进入水体后的水流运动及温度扩散规律进行了研究。研究发现:总体上,温排水的温升影响区域主要体现在排水口下游250 m以内,在河道中主要沿河道纵向扩散,在250 m后温升效应显著下降,温升影响范围明显变小,温度几乎与河流环境一致;而对不同季节的水文条件下,在温升明显区域影响范围内,夏季的温升影响比冬季温升影响要强,且其横向分布范围变大;就不同工况而言,温升范围影响变化不明显,但对温升范围影响变化而言,非正常工况下的温升影响效果相对较大。最后,通过模拟预测的结果与实测的实际结果对比,验证结果比较理想,说明本模型可以应用于相似的工程和研究,预测结果可以为电厂设计和环境评价提供科学依据。
This paper set up a mathematical model by power plant cooling water used for predicting water temper-ature distribution effect of receiving waters; based on a domestic power plant in the river in summer and winter which are unfavorable hydrological conditions, under the power plant running normal condition and abnormal conditions in both cases, the water movement and diffusion rules of cooling water after entering water temperature were studied. Research found that: overall, the cooling water influence area of the temperature rise is mainly manifested in the downstream port within 250 m, mainly along the river longitudinal dispersion in the river. After 250 m, the temperature rise effect significantly reduces; temperature influence range significantly decreases, and the cooling water temperature is almost con-sistent with the river environment. Under the hydrological conditions of different seasons, in the obvious temperature rise effect region, the influence of the temperature rise of summer is more obvious than winter, and the transverse distribution range of summer is larger. In terms of different working conditions, the temperature rise effect change is not obvious, but for the influence on the temperature range change, the temperature rise effect of the abnormal condition is bigger. Finally, through the actual simulation of the predicted and the measured results, the verification results are more ideal, demonstrating that this model can be applied to similar engineering and research, and prediction results can provide the scientific basis for power plant design and environment evaluation.

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