Periodic Reporting for period 1 - SURFING (Flow on thin fluid sheets)
Período documentado: 2020-11-01 hasta 2022-10-31
The general topic of this project is the development of improved mathematical models for thin film flow modelling. The study of such thin fluid layers is an integral part of many flow problems, ranging from gear lubrication and cleaning simulations, through automotive water management and spray coating. While specialized thin film solvers have been developed to model these thin fluid layers, there exists no method to detect their formation, or to couple surface and bulk flow.
This project developed a new computational framework to model thin film flow. Unlike existing methods, the proposed method is not just able to model not just the evolution of thin fluid films, but it can also predict the formation and break up of thin fluid sheets. A further advantage of the new framework, referred to as the Discrete Droplet Method (DDM), is that it can predict the evolution of thin fluid films on moving surfaces of any shape. Proof-of-concept applications have shown that this method can significantly benefit rain-on-car applications in the automotive industry to track how rainwater moves over a car, and where it collects.
We further developed a model adaptive framework to couple surface and bulk flow. The newly developed DDM for modelling surface flow was coupled with an existing and popular Navier-Stokes solver for bulk fluid flow. Through various examples, we showed that the newly developed model adaptive framework can significantly speed up simulations of coupled bulk surface flow, with one application showing an almost 20x speed-up.
This project developed a new computational framework to model thin film flow. Unlike existing methods, the proposed method is not just able to model not just the evolution of thin fluid films, but it can also predict the formation and break up of thin fluid sheets. A further advantage of the new framework, referred to as the Discrete Droplet Method (DDM), is that it can predict the evolution of thin fluid films on moving surfaces of any shape. Proof-of-concept applications have shown that this method can significantly benefit rain-on-car applications in the automotive industry to track how rainwater moves over a car, and where it collects.
We further developed a model adaptive framework to couple surface and bulk flow. The newly developed DDM for modelling surface flow was coupled with an existing and popular Navier-Stokes solver for bulk fluid flow. Through various examples, we showed that the newly developed model adaptive framework can significantly speed up simulations of coupled bulk surface flow, with one application showing an almost 20x speed-up.
The first part of the project was to develop a new mathematical model to simulate thin fluid films. For this, we considered a Cauchy momentum equation, and averaged the velocity in the direction normal to the fluid surface. The fluid film was discretized using Lagrangian fluid droplets moving over the surface. Derivative computation was done using a SPH type integral kernel approximation. A velocity filtering approach was then developed to stabilize the numerical solutions.
One of the key challenges solved during this project was determining the appropriate coupling and conservation constraints for data transfer between the thin film and bulk flow models. For this, we developed a new framework for volume and mass conservation in meshfree methods, followed by a new paradigm to couple meshfree and particle methods.
The results of this project have been disseminated through peer-reviewed journal articles and talks at international conferences and workshops.
One of the key challenges solved during this project was determining the appropriate coupling and conservation constraints for data transfer between the thin film and bulk flow models. For this, we developed a new framework for volume and mass conservation in meshfree methods, followed by a new paradigm to couple meshfree and particle methods.
The results of this project have been disseminated through peer-reviewed journal articles and talks at international conferences and workshops.
The newly developed computational methods have shown to be able to predict a multiple of applications of fluid flowing in thin layers which was not possible in the past. This includes flow on arbitrarily moving curved surfaces, partially wetted surfaces, and the formation of thin liquid films. Furthermore, the novel coupled framework investigated in this project has been shown to significantly speed up applications such as cleaning and rain-on-car simulations, which used to rely on excessively fine resolutions of bulk flow solvers.
From a wider perspective, the work of this project has shown, for the first time, how different computational models can be adaptively coupled. Here, the coupling interface was determined automatically within the simulations. This work has established the guidelines for adaptive coupling between two computational models, and has the potential to be extended to a wide variety of applications.
One of the benefits of this project is that it established a close collaboration between the University of Luxembourg, the Justus Leibig University of Giessen in Germany and the Fraunhofer institute of industrial mathematics ITWM in Germany. This ensures that the results of the project can be exploited in both scientific and industrial avenues in the future.
From a wider perspective, the work of this project has shown, for the first time, how different computational models can be adaptively coupled. Here, the coupling interface was determined automatically within the simulations. This work has established the guidelines for adaptive coupling between two computational models, and has the potential to be extended to a wide variety of applications.
One of the benefits of this project is that it established a close collaboration between the University of Luxembourg, the Justus Leibig University of Giessen in Germany and the Fraunhofer institute of industrial mathematics ITWM in Germany. This ensures that the results of the project can be exploited in both scientific and industrial avenues in the future.