化工进展2024，Vol.43Issue(z1)：1-12,12.DOI:10.16085/j.issn.1000-6613.2024-0375
机器学习在喷射器研究中的应用进展
Process in the application of machine learning in ejector research
摘要
Abstract
The ejector is a widely used mechanical device with advantages such as simple structure,low initial cost,easy maintenance,and reliable operation.It is widely applied in fields such as refrigeration,desalination,chemical engineering,fuel cells,aerospace,etc.The ejector does not directly consume mechanical energy,which allows for energy-saving purposes,making it more important and attractive with the national goals of"carbon peaking and carbon neutrality"in China.Machine learning methods,as a data-driven automated analysis approach,can be used for analyzing the internal flow characteristics of ejectors and optimizing ejector performance.In recent years,a small number of scholars have already applied machine learning methods to the study of ejectors in various applications,aiming at improving the ejector performance and the system performance.But the research in the open literature is currently scattered,and the state of the art is not yet clear.The present work comprehensively reviewed the literature on the application of machine learning methods in the study of ejectors for different applications,analyzed the current research status,summarized the machine learning methods utilized in the open literature,and pointed out that in the future machine learning methods can be applied to the study of internal flow characteristics of ejectors,providing a basis and guidance for improving the efficiency and performance of ejectors.Machine learning methods can be applied to the study of ejector performance under variable operating conditions,constructing a pathway from automated design to real-world application of ejectors.Constructing more suitable algorithms and proposing a series of targeted solutions.关键词
喷射制冷/喷射器/机器学习/人工神经网络/预测/优化Key words
ejector refrigeration/ejector/machine learning/artificial neural network/prediction/optimization分类
通用工业技术引用本文复制引用
戴征舒,左元浩,陈孝罗,张犁,赵根,张学军,张华..机器学习在喷射器研究中的应用进展[J].化工进展,2024,43(z1):1-12,12.基金项目
国家自然科学基金(51906152) （51906152）
上海市浦江人才计划(22PJ1411200) （22PJ1411200）
浙江省"领雁"研发攻关计划(2024C03117). （2024C03117）
