ISS: Transient Behavior of Flow Condensation and Its Impacts on Condensation Rate

ISS：流动冷凝的瞬态行为及其对冷凝率的影响

• 批准号: 2224438
• 负责人: Chen Li
• 金额: $ 24万
• 依托单位: University of South Carolina at Columbia
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2224438&HistoricalAwards=false
• 关键词: ISS; Transient; Behavior; Flow; Condensation

Condensers, which are used to reject heat and return/collect liquid to the evaporators/boilers, are essential parts of any liquid-vapor two-phase systems such as heat pipes and vapor chambers, water recovery and harvest, vapor compression systems, and Rankine cycle power systems. However, due to the dominant filmwise condensation mode, where vapors are condensed in the form of a film that covers the surface, in industry practice, condensation heat transfer rate is typically several folds lower than that of boiling or evaporation, leading to oversized- and overweighted-condensers. Highly efficient flow condensation is greatly desirable. Two-phase flow instabilities or oscillations in flow boiling and condensation can have detrimental effects on the system. Although extensive efforts have been taken to understand and manage the two-phase oscillation in flow boiling, only a few studies have been conducted in understanding two-phase condensing flow instabilities. This project would provide valuable knowledge and lead to novel control strategies in achieving the desirable flow pattern. If successful, this research project would improve not only the stability of condenser operations, but also the efficiency if two-phase oscillations can be properly utilized to enhance flow condensation. This project also offers a unique opportunity to promote interdisciplinary collaborations among thermal science, space technology, and machine learning. These types of collaborations would greatly benefit the communities of thermal science, machine learning, space industry, terrestrial water-energy industries, stakeholders, and science and technology education.The research objectives are to understand transient behaviors of flow condensation and their impacts on flow condensation rate in both ground and microgravity environments. New knowledge obtained in this study would advance understandings of operation parameters that govern flow condensation oscillations. The research objectives can be realized in five tasks: (a) systematically characterizing transient behaviors of flow condensation, (b) understanding the dependence of different two-phase flow patterns on the vapor flow changing rate and/or cooling rate, (c) identifying the range of operation conditions that generate intensive two-phase oscillations; (d) characterizing the influence of oscillation modes on flow condensation rate with an emphasis on enhancing flow condensation; and (e) developing machine-learning-based models to accurately predict transient behaviors of flow condensation, flow condensation rate and pressure drop, which are more accessible than the traditional two-phase experiments to research communities, industries, students, and the general public.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

冷凝器用于拒绝热量并将液体返回到蒸发器/锅炉中，是任何液体蒸气两相系统的重要部分，例如热管和蒸气室，水回收和收获，蒸气压缩系统以及兰金循环电力系统。然而，由于胶片的主要凝结模式，在该模式下，蒸气以覆盖表面的膜的形式凝结，在行业实践中，凝结传热速率通常比沸腾或蒸发的频率低几倍，从而导致超大和超重的调节体。高效的流量凝结是非常可取的。流动沸腾和凝结中的两相流量不稳定性或振荡可能对系统产生不利影响。尽管已经采取了广泛的努力来理解和管理流量沸腾的两相振荡，但在理解两相凝结流动不稳定性方面只进行了少量研究。该项目将提供宝贵的知识，并导致实现理想流动模式的新型控制策略。如果成功的话，该研究项目不仅可以提高冷凝器操作的稳定性，而且还会提高效率，如果可以正确利用两阶段振荡来增强流量冷凝。该项目还提供了一个独特的机会来促进热科学，太空技术和机器学习之间的跨学科合作。这些类型的合作将极大地使热科学，机器学习，太空行业，陆地水能产业，利益相关者以及科学技术教育的社区受益。研究目标旨在了解流量凝结的短暂行为及其对地面和微层环境中流量凝结率的影响。在这项研究中获得的新知识将提高对控制流凝结振荡的操作参数的理解。可以在五个任务中实现研究目标：（a）系统地表征流凝结的瞬态行为，（b）了解不同两相流量模式对蒸气流动速率和/或冷却速率的依赖性，（c）识别产生密集的两相振荡范围的范围； （d）表征振荡模式对流凝率的影响，重点是增强流量凝结； （e）开发基于机器学习的模型，以准确预测流动凝结，流凝率和压降的瞬态行为，这些行为比传统的研究社区，行业，学生和公众更容易访问，这一奖项反映了NSF的法定任务，并通过评估了基金会的范围和广泛的影响。