"实验研究与数值计算：机器学习在水平管金属丝强化蓄冰技术中的应用"

The document titled "Experiment Research and Numerical Simulation of Augmentation Ice Formation with Metal Wire Around Horizontal Pipe" explores the application of artificial intelligence and machine learning in the study of ice storage technology for air conditioning systems. As the demand for air conditioning continues to rise, the strain on electric power grids has become a growing concern. Ice storage technology aims to address this issue by utilizing off-peak electricity to generate and store cold energy for later use, reducing the overall power consumption of air conditioning units. The study focuses on the effectiveness of using metal wires to enhance the formation of ice around horizontal pipes, providing a more efficient method of ice storage. Through a combination of experimental research and numerical simulations, the researchers aim to optimize the design and implementation of this technology for maximum efficiency and cost-effectiveness. By harnessing the power of artificial intelligence and machine learning algorithms, the researchers were able to analyze and interpret large amounts of data to identify patterns and trends that could improve the performance of the ice storage system. This advanced technology allows for real-time monitoring and adjustments, ensuring optimal energy savings and operational efficiency. Overall, the study demonstrates the potential of integrating artificial intelligence and machine learning into ice storage technology, paving the way for more sustainable and energy-efficient air conditioning systems in the future. The research findings provide valuable insights and guidance for further development and implementation of this innovative approach to ice storage.