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Study on identification method of heat transfer deterioration of supercritical fluids in vertically heated tubes

机译:垂直加热管中超临界流体传热退化的识别方法研究

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Prediction of the heat transfer of supercritical fluids (SCFs), especially for heat transfer deterioration (HTD), is highly significant to the design and safe operation of supercritical boilers and advanced nuclear systems. To achieve higher predictive accuracy, heat transfer datasets of SCFs are usually classified as HTD cases and non-HTD cases using certain HTD identification methods, and prediction models, including empirical correlations and criteria of HTD occurrence, have been separately developed for HTD cases and non-HTD cases. Therefore, the rationality of HTD identification methods are crucial to the data classification and further development of high-precision prediction models but is seldom discussed in research. This paper first summarizes the existing identification methods of HTD to SCFs, and respective heat transfer datasets of supercritical water (SCW) and CO2(SCCO2) are compiled. Based on these datasets, the accuracy of existing methods in identifying HTD cases and non-HTD cases is evaluated. The results show that, the most common identification method (Nu/Nudb < 0.3) can mistake typical non-HTD case for HTD case and cannot reflect the actual location where HTD occurs. The Lokshin et al. method and Zhang et al. method (htc/htc0 < 1.0) can accurately recognize HTD cases but are prone to error in detecting non-HTD cases. It is believed that the reference value representing normal heat transfer is the key to judging the heat transfer state of SCFs, and should be considered specifically in the pseudo-phase-change influenced region. Finally, an improved identification method of HTD suitable for SCW and SCCO2is proposed. Compared with previous methods, the new method shows favorable accuracy in discerning both HTD cases and non-HTD cases, and is helpful for classifying heat transfer cases and developing precise heat transfer correlations and HTD criteria of SCFs.
机译:超临界流体(SCF)的传热预测,特别是对于传热恶化(HTD)的预测,对于超临界锅炉和先进核系统的设计和安全运行非常重要。为了获得更高的预测精度,通常使用某些HTD识别方法将SCF的传热数据集分为HTD案例和非HTD案例,并且已经针对HTD案例和非HTD案例分别开发了包括经验相关性和HTD发生标准的预测模型。 -HTD案例。因此,HTD识别方法的合理性对于数据分类和高精度预测模型的进一步发展至关重要,但在研究中很少讨论。本文首先总结了现有的HTD对SCF的识别方法,并建立了超临界水(SCW)和CO2(SCCO2)各自的传热数据集。基于这些数据集,评估了现有方法在识别HTD病例和非HTD病例中的准确性。结果表明,最常用的识别方法(Nu / Nudb <0.3)可以将典型的非HTD情况误认为HTD情况,不能反映HTD发生的实际位置。 Lokshin等。方法和张等。方法(htc / htc0 <1.0)可以准确识别HTD病例,但在检测非HTD病例时容易出错。可以认为,代表正常传热的参考值是判断SCF传热状态的关键,应在伪相变影响区域中特别考虑。最后,提出了一种适用于SCW和SCCO2的改进型HTD识别方法。与以前的方法相比,该新方法在区分HTD案例和非HTD案例方面显示出了良好的准确性,并且有助于对传热案例进行分类并开发精确的传热相关性和SCF的HTD标准。

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