Multiscale surface structures offer the opportunity to combine the heat transfer enhancement provided by microscale structures with the dryout benefits provided by some nanostructures, which is particularly attractive for falling film evaporators, who have ...
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 r ...
The heat transfer performance of commercially produced micro-enhanced tubes with and without a nanocoating was investigated under pool boiling of saturated refrigerant. These multiscale enhancements were on the outside of 19 mm horizontal copper tubes heat ...
This article describes a study of beam radiation striking particle beds of randomly packed, spherical par-ticles. The current study is focused on concentrating solar power receivers which use solid particles as a heat transfer medium, but results are appli ...
As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, health monitoring, decision- and policy-making, and more, by comprehensively m ...
Within the context of contemporary machine learning problems, efficiency of optimization process depends on the properties of the model and the nature of the data available, which poses a significant problem as the complexity of either increases ad infinit ...
This work presents a new computational optimization framework for the robust control of parks of Wave Energy Converters (WEC) in irregular waves. The power of WEC parks is maximized with respect to the individual control damping and stiffness coefficients ...
In Process Systems Engineering, computationally-demanding models are frequent and plentiful. Handling such complexity in an optimization framework in a fast and reliable way is essential, not only for generating meaningful solutions but also for providing ...
Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...
There are various possibilities to realize coil winding designs for an inductive power transfer system. In order to achieve high power transfer efficiency and power density and explore trade-offs between the two, design optimization around the coil link is ...
