Improved Waste Heat Management and Energy Integration in an Aluminum Annealing Continuous Furnace Using a Machine Learning Approach.

Annealing furnaces are critical for achieving the desired material properties in the production of high-quality aluminum products. In addition, energy efficiency has become more and more important in industrial processes due to increasing decarbonization regulations and the price of natural gas. Thus, the current study aims to determine the opportunities to reduce energy consumption in an annealing continuous furnace and the associated emissions. To this end, the heat transfer phenomenon is modeled and solutions for the decreasing fuel consumption are evaluated so that the overall performance of the process is enhanced. A heat transfer model is developed using the finite difference method, and the heat transfer coefficient is calculated using machine learning regression models. The heat transfer model is able to predict the heat transfer coefficient and calculate the aluminum temperature profile along the furnace and the fuel consumption for any given operating condition. Two solutions for boosting the furnace exergy efficiency are evaluated, including the modulation of the furnace temperature profiles and the energy integration by the recycling of exhaust flue gases. The results show that the advanced energy integration approach significantly reduces fuel consumption by up to 20.7%. Sensitivity analysis demonstrates that the proposed strategy can effectively reduce fuel consumption compared with the business-as-usual scenario for a range of sheet thicknesses and sheet velocities.

Multiphysics Analysis of Ultrasonic Shock Wave Lithotripsy and Side Effects on Surrounding Tissues.

BACKGROUND: Today, the most common method for kidney stone therapy is extracorporeal shock wave lithotripsy. Current research is a numerical simulation of kidney stone fragmentation via ultrasonic shock waves. Most numerical studies in lithotripsy have been carried out using the elasticity or energy method and neglected the dissipation phenomenon. In the current study, it is solved by not only the linear acoustics equation, but also the Westervelt acoustics equation which nonlinearity and dissipation are involved. OBJECTIVE: This study is to compare two methods for simulation of shock wave lithotripsy, clarifying the effect of shock wave profiles and stones' material, and investigating side effects on surrounding tissues. MATERIAL AND METHODS: Computational study is done using COMSOL Multiphysics, commercial software based on the finite element method. Nonlinear governing equations of acoustics, elasticity and bioheat-transfer are coupled and solved. RESULTS: A decrease in the rise time of shock wave leads to increase the produced acoustic pressure and enlarge focus region. The shock wave damages kidney tissues in both linear and nonlinear simulation but the damage due to high temperature is very negligible compared to the High Intensity Focused Ultrasound (HIFU). CONCLUSION: Disaffiliation of wave nonlinearity causes a high incompatibility with reality. Stone's material is an important factor, affecting the fragmentation.