Recently developed physics-informed deep learning is regarded as a transformative
learning philosophy that has been applied in many scientific domains, but such applications …

Crude oil scheduling plays an important role in reducing production cost of refineries.
However, fluctuations in operation conditions in crude distillation units (CDUs) and quality of …

This study proposes a new inverse design method that utilizes a physics-informed neural
network (PINN) to parameterize the geometric and operating inputs, enabling the …

The inhibition performance of three amino acid-based amphoteric surfactants disodium-N-
alkyliminodiacetate was investigated by the weight-loss and electrochemical methods. XPS …

A fast and accurate representation of the complex heat and mass transfer processes of
closed-wet cooling tower (CWCT) systems for optimal design and management is …

As large water-using systems in chemical industries, cooling water systems (CWSs)
consume a large amount of water and power. Up to now, most research on the cooling water …

This research explored the intricacies of water consumption and energy requirements within
cooling systems designed for concentrated solar power plants. In the present work, an …

In the present study, an evaporative cooling test system consisting of an elliptical-heat
exchanger was examined. Tests were conducted for various airflow rates of 52, 68, 81, 96 …

Cooling water systems (CWSs) are extensively utilized in various industries to eliminate the
excess heat and converse energy. Studies on CWSs mainly concentrated on finding the …

In this study, a computational strategy is proposed for geometric design and prioritization of
wave-plate mist eliminators by combining the Taguchi experimental design, CFD modelling …