Analysis on frosting of heat exchanger and numerical simulation of heat transfer characteristics using BP neural network learning algorithm.

The study is aimed at the frosting problem of the air source heat pump in the low temperature and high humidity environment, which reduces the service life of the system. First, the frosting characteristics at the evaporator side of the air source heat pump system are analyzed. Then, a new defrost technology is proposed, and dimensional theory and neural network are combined to predict the transfer performance of the new system. Finally, an adaptive network control algorithm is proposed to predict the frosting amount. This algorithm optimizes the traditional neural network algorithm control process, and it is more flexible, objective, and reliable in the selection of the hidden layer, the acquisition of the optimal function, and the selection of the corresponding learning rate. Through model performance, regression analysis, and heat transfer characteristics simulation, the effectiveness of this method is further confirmed. It is found that, the new air source heat pump defrost system can provide auxiliary heat, effectively regulating the temperature and humidity. The mean square error is 0.019827, and the heat pump can operate efficiently under frosting conditions. The defrost system is easy to operate, and facilitates manufactures designing for different regions under different conditions. This research provides reference for energy conservation, emission reduction, and sustainable economic development.

Study of the upper airway of obstructive sleep apnea patient using fluid structure interaction.

Up to 14% of the U.S. population is estimated to have obstructive sleep apnea (OSA), while the outcomes of the treatments have variable results. In the current study, a three-dimensional fluid-structure interaction modeling was applied to simulate the upper airway to identify the precise location, severity, and characteristic of airway collapse. This was accomplished using Simpleware® and ANSYS® software applied to a 3-D rendering of the airway in a real patient with severe OSA. During this simulation, areas which are prone to collapse and precipitate apneic episodes were identified at the tip of the soft palate and the base of the tongue, with intrathoracic pressure as low as -1370 Pa. These results are consistent with anatomical structures currently indicated and targeted in the treatment of OSA. This improved FSI modeling simulation, which is the first to completely model the whole upper airway without consideration of the nasal cavity in OSA, and can allow virtual modification of the airway prior to actual treatment by doctors.