The analysis evaluate the convergence and efficiency of each methodology for the different problems which are solved. The achieved goal is not the definition of an ever valid mathematical strategy, but here focus is given on the parallel application of a detailed fluid dynamic analysis and automated...
Nature has been perfecting flight much longer than any human. By studying the myriad of ways these creatures achieve this, engineers can build more efficient and dynamic flying—or even swimming—drones. These drones may one day deliver groceries to your front door or plumb the depths to study ...
this approach is commonly used to estimate the photobioreactor's hydrodynamics for large-scale operation. In the case of bubble size distribution, the population balance technique along with Eulerian-Eulerian method is used. This method uses a set of conservation equations for each bubble class, acco...
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12 May 2025|Open Access Gas–liquid two-phase bubble flow spinning for hydrovoltaic flexible electronics Precise control of fiber morphology remains challenging. This study develops bioinspired gas-liquid spinning to create programmable microstructured fibers and reveals a bubble-mediated dynamic interface ad...
Investigating and tailoring the thermodynamic properties of different fluids is crucial to many fields. For example, the efficiency, operation range, and environmental safety of applications in energy and refrigeration cycles are highly affected by the p
Fluid dynamic simulation using RANS models can be conducted within hours on a local workstation for fixed beds with a few thousand of particles. The idea behind that class of turbulence model is that a property can be decomposed into its time-aver- aged value and a fluctuating component: φ...
Cavitation is undesirable because it produces extensive erosion of the rotating blades, additional noise from the resultant knocking and vibrations, and a significant reduction of efficiency because it distorts the flow pattern. The cavities form when the pressure of the liquid has been reduced to ...
Physics-informed neural networks (PINNs), another class of algorithm, are gaining ground since they add physical intuition in common NNs, and can bind experimental data with Navier–Stokes equations for fluid mechanics [140,141,148,149,150]. Algorithms based on genetic programming (GP) are best...
For this particular class of multi-phase flows, we consider the solid particles and gas bubbles as being the discrete constituents of the dispersed phase co-flowing with the continuous liquid phase. The co-existence of three phases considerably complicates the fluid flow due to an array of ...