共查询到18条相似文献,搜索用时 78 毫秒
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大唐国际王滩电厂位于渤海湾西侧,排水口附近有河口、潟湖以及港口等地貌和工程,温排水在此复杂水域的输运特征具有典型的研究价值。该文以此电厂温排水为研究对象,采用MIKE 3软件和双重嵌套网格技术建立三维水动力及温度耦合模型,利用2017年5月和8月实测潮流及温度数据对模型进行合理性验证。模拟和分析了不同潮流动力、风作用以及温排水条件下温升效应特征。结果表明:温排水条件对温升起控制作用,排水量和排水温度是影响温升分布的二个关键要素;风动力作用对于温升影响较大,风生流对温升平面分布产生重要影响;由于该海域为弱潮区,不同潮流作用造成的温升差异较小。 相似文献
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采用平面二维水流、温度扩散数学模型研究了中山燃气电厂的温排水扩散规律、温升变化和影响范围,为该电厂的建设提供依据。 相似文献
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滨海电厂温排水三维数值模拟研究 总被引:1,自引:0,他引:1
针对传统温排水平面二维数学模型的不足,采用三维斜压水流数学模型来模拟温排水的运动,建立了某电厂温排水工程近区和远区耦合的数学模型,得到了计算域内的三维潮流场与温升场。研究结果表明MIKE3软件能较好的模拟出实测潮流的流速场。海湾内温排水三维分层现象显著,温排水温升包络范围以表层温升分布为主。 相似文献
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数值模拟是开展温排水研究工作的重要手段。主要对国内滨海电厂温排水数值模拟研究进行了回顾,分别就控制方程离散方法、网格设计、模型空间维度、是否考虑了斜压效应、参数选取、开边界处理方式、波浪影响等方面进行了讨论。应开展满足温排水影响后评估要求的实时预报模型的研发工作,为电厂温排水影响后评估工作提供技术基础;并探索温排水实时预报模型与数据同化方法相结合的技术手段,进一步提高温排水数值预报的技术水平。 相似文献
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潮流河段温排水影响的平面二维数值模拟 总被引:6,自引:2,他引:6
为研究电厂温排水对受纳水体的温升影响,基于无结构的三角形网格,采用有限元算法,建立了平面二维非恒定流温排水数学模型。该模型建立在非恒定水动力学模型基础上,考虑了源汇项的作用,因此能适应于各种恒定与非恒定河道水流中的温排水计算,并能适应于喇叭形和蘑菇头形等多种排水形式。该模型在多项电厂程温排水问题研究中得到了成功应用,以位于长江下游感潮河段中的南京马渡电厂为例进行了计算分析,并采用实体模型试验成果对数学模型计算结果进行了对比检验。开发研制了数学模型的后处理软件,实现了温排水运动过程的动态演示。 相似文献
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为研究温排水对长江安徽段水温的影响,建立长江干流安庆至芜湖段三维水动力温度输运模型,根据水文实测数据对模型参数进行率定及验证,分别在纵、横断面上预测分析了不利条件下两种排放工况(减排前、减排后)对周边水域温度的影响范围及程度.结果表明:在两种排放工况下,保护目标水温均未受影响;水体温升分布有显著垂向差异,随着水深增加,... 相似文献
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建设项目温排水对水环境影响分析初探 总被引:3,自引:0,他引:3
杨柳俊 《水资源与水工程学报》2005,16(4):78-80
建设项目水资源论证分析工作需要科学、实用的数学模型进行退水对水环境的影响分析计算,当前相继立项建设的电厂、热电厂都将产生大量的温排水,其稀释扩散规律与普通污染物扩散规律有一定的相似性。本文通过实例,采用二维对流扩散模型分析探讨温排水对水环境的影响程度。 相似文献
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Al Mahdi Saadi Amina Msilini Christian Charron Andr St-Hilaire Taha B. M. J. Ouarda 《河流研究与利用》2022,38(1):23-35
Thermal refuges in rivers are becoming a critical habitat for ectotherm fish, including Atlantic salmon (Salmo salar). In this study, two statistical modelling approaches were used to estimate the areas of potential thermal refuges: generalized additive models (GAM) and multivariate adaptive regression splines (MARS). This allowed for the first development of a reliable statistical model that uses a few relevant predictors (air temperature, river discharge, main river, and tributary temperatures) to estimate tributary plume thermal refuge surface areas. GAM and MARS models were fitted independently for four sites on the Ste-Marguerite River, (Quebec, Canada). Model performances were evaluated using the leave-one-out cross validation (LOOCV) approach and the following criteria: the Akaike information criterion (AIC), root-mean-square error (RMSE), relative root-mean-square error (rRMSE), Nash-Sutcliffe efficiency coefficient (NASH), and finally the bias (BIAS). Using an array of thermographs deployed at the confluence of a cold tributary and the warmer main river stem, refuges were delineated at a daily time step. Model results indicate that the estimated areas are similar to the refuge surfaces interpolated using temperature measurements, with both models and for all sites. Results suggest that MARS performs better than GAM in terms of forecasting and estimating the variability of the area of thermal refuges at all study-stations. This relatively simple approach will be of use to water resources managers faced with the challenge of protecting thermal refuges for fish. 相似文献
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To understand the temporal and spatial variability of thermal refuges, this study focused on modeling potential thermal refuge area (PTRA) at a sub-daily time-step in two tributary confluences of the Sainte-Marguerite River (Canada) during the summers of 2020 and 2021. Aquatic ectotherm species, such as Atlantic salmon (Salmo salar), seek these refuges to avoid heat stress during high summer river temperatures. To investigate the temporal variability of these PTRA, we employed inverse weighted distance interpolation to delineate the hourly area available at both confluences. We then analyzed the impact of the atypical low flow conditions of summer 2021 on the diel cycle of PTRA extremes using the coefficient of variation and the generalized additive model (GAM). Finally, we used four supervised machine-learning regression models and three to five hydrometeorological predictors to estimate hourly PTRA availability: multivariate adaptive splines regression (MARS), GAM, support vector machine regression (SVM), and random forest regression (RF). The results showed that tree-based and kernel-based regression models, RF and SVM, outperformed GAM and MARS. RF had the highest accuracy at both sites, with a relative root mean square error and Nash–Sutcliffe efficiency coefficient (Nash) of 13% and 93%, respectively. Our study discovered that under warm conditions in August 2021, small perennial tributary inflows in combination with low mainstem discharge could create high and constant PTRA at confluences, potentially providing vital thermal refuges for cold-water taxa. These refuges may be especially important at the local level, within a specific stretch or section of the river. Given the decreasing availability of thermal refuges for salmonids, it is crucial to monitor stream temperatures at small spatial and temporal scales using data-driven techniques in order to understand stream temperature heterogeneity at tributary confluences. 相似文献