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Reduced order analysis of flow and heat transfer for air-cooled condenser of power generating unit

机译:发电机组风冷冷凝器流动与传热的降阶分析

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The flow and heat transfer exhibit complex non-linear characteristics for the air-cooled condenser (ACC) of power generating unit because numerous factors, including the meteorological and the geographic conditions, as well as the configurations of wavy finned tube bundles, can affect its performances. In order to quickly and accurately predict the air side velocity and temperature fields of ACC, the reduced order models (ROMs) based proper orthogonal decomposition (POD) method were established, by which the previous 10~5 DOF in CFD model was reduced to 10~1 DOF for new case prediction. The weight coefficients for POD modes were obtained by cubic spline interpolation and flux matching procedure (FMP). The air flow fields and correlating temperature fields influenced by environmental natural winds were revealed. It is found that accuracies of the POD solution with cubic spline interpolation are better than that of FMP. However, the FMP procedure, which can extract flow and thermal information from fewer observations, has better robustness than interpolation method. Hence, it is more appropriate for the POD solution of extrapolated cases. The present research may provide a rapid and reliable approach for the optimization of real-time operation of air-cooled power generating units.
机译:流动和传热对于发电机组的风冷冷凝器(ACC)表现出复杂的非线性特性,因为气象和地理条件以及波浪状翅片管束的配置等多种因素都会影响其性能,表演。为了快速准确地预测ACC的空气流速和温度场,建立了基于降阶模型(ROM)的适当正交分解(POD)方法,从而将CFD模型中以前的10〜5 DOF减少到10约1个自由度用于新病例预测。通过三次样条插值和磁通匹配程序(FMP)获得POD模式的权重系数。揭示了自然环境风影响下的空气流场和相关温度场。发现三次样条插值的POD解的精度优于FMP。但是,FMP程序可以从较少的观测值中提取流量和热量信息,比插值方法具有更好的鲁棒性。因此,它更适合外推案例的POD解决方案。本研究可以为风冷发电机组实时运行的优化提供一种快速可靠的方法。

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