Pressure drop prediction in annular two-phase flow in macroscale tubes and channels
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This work proposes a novel physics-based model for the fluid mechanics and heat transfer associated with slug flow boiling in horizontal circular microchannels to update the widely used three-zone model of Thome et al. (2004). The heat transfer model has a ...
This paper proposes a novel concept for a loop thermosyphon cooling system, designed for the transistor module of a transformer. The thermosyphon uses a free convection cooled condenser, making the system completely passive, i.e. no energy consumption is n ...
Predicting the effects of mutations on protein stability is a key problem in fundamental and applied biology, still unsolved even for the relatively simple case of small, soluble, globular, monomeric, two-state-folder proteins. Many articles discuss the li ...
The use of evaporative cooling in the gas diffusion layer (GDL) of polymer electrolyte fuel cells has been proposed as a simple yet impactful solution to simultaneously provide the functionality of cell cooling, thanks to the dissipation of the latent heat ...
Aluminium is a metal sought in the industry because of its various physical properties. It is produced by an electrolysis reduction process in large cells. In these cells, a large electric current goes through the electrolytic bath and the liquid aluminium ...
A test facility to investigate flow pattern transitions of vertical two-phase flow of CO2 has been built within the scope of the high-luminosity detector upgrades at the European Organization for Nuclear Research (CERN). Adiabatic flow pattern observations ...
The global warming potential (GWP) of working fluids in thermodynamic cycles and their environmental impact have been gaining considerable attention within the recent years. The global objectives on climate protection are becoming increasingly ambitious, w ...
This chapter aims to provide an overview of the fatigue life modeling and prediction methods for composite materials and structures, recalling methods used in the past, discovering the present status, and attempting to foresee future trends. ...
Machine learning promises to accelerate materials discovery by allowing computational efficient property predictions from a small number of reference calculations. As a result, the literature has spent a considerable effort in designing representations tha ...
Machine learning promises to accelerate materials discovery by allowing computational efficient property predictions from a small number of reference calculations. As a result, the literature spent a considerable effort in designing representations that ca ...