| 刘桦,朱其萍,谢晓翠,何畅,张冰剑,潘明,陈清林.考虑环境参数不确定性的闭式冷却塔随机模拟研究[J].,2019,59(3):244-250 |
| 考虑环境参数不确定性的闭式冷却塔随机模拟研究 |
| Study of stochastic modeling of closed cooling tower considering uncertainty of ambient parameters |
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| DOI：10.7511/dllgxb201903004 |
| 中文关键词: 闭式冷却塔 随机模拟 不确定性 采样方案 CFD模型 |
| 英文关键词: closed cooling tower stochastic modeling uncertainty sampling strategy CFD model |
| 基金项目:国家自然科学基金资助项目(21606261,51776228). |
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| 摘要点击次数: 863 |
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| 中文摘要: |
| 利用随机模拟的方法探讨了地理位置和季节性环境参数的变化对闭式冷却塔热效率的潜在影响.首先,通过试验设计对不确定性随机变量进行量化和表征以确定合理的采样方案.以北京和广州为例,统计了当地各季有代表性的环境温度和相对湿度数据,结合核密度估计和皮尔逊积矩相关系数法来计算原始数据的累积概率分布函数以及相关系数矩阵,再利用哈默斯利序列采样将随机变量离散化以确定样本方案.接下来,将生成的样本方案传递到闭式冷却塔的过程模型中,使用COMSOL软件实现对其热质传递过程的三维严格模拟,并得到采样空间内的热效率概率分布模型.随机模拟结果显示,使用现有确定性设计方法有较大概率导致闭式冷却塔处于设计不足的状态,不同城市间环境参数不确定性的差异会对闭式冷却塔热效率概率分布有较大影响,这表明需要对闭式冷却塔进行详细的柔性设计. |
| 英文摘要: |
| The implying impacts of plant locations and season-related environmental parameters on the thermal efficiency of a closed cooling tower are systematically investigated using stochastic modeling. The first step is experimental design in which the uncertain random variables are characterized and quantified to determine an appropriate sampling strategy. Taking Beijing and Guangzhou as examples, the representative statistics of ambient temperature and relative humidity in each season are collected and processed to determine their cumulative distribution functions and correlation coefficient matrix by combining kernel density estimation with Pearson product-moment correlation coefficient methods. Hammersley sequence sampling is used to discretize the random values and sample from these probability distributions that generates a set of scenarios. Thereafter, the sampled scenarios can be passed through the rigorous three-dimensional modeling of the closed cooling tower with COMSOL software so that the heat-mass transfer process can be simulated and the probability distribution of thermal efficiency in the input space can be obtained. The stochastic modeling results show that the existing deterministic design methods for the closed cooling tower have a relatively high probability of being under designed. The differences in environmental parameters between cities have a great influence on the probability distribution of thermal efficiency, which highlights the necessity of flexible design for the closed cooling tower. |
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