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In the last years the limitation of resources and rising environmental pollution at the same time caused a rethinking in society. Careful handling of raw materials gets more and more important. These circumstances in combination with more severe legislative boundary conditions have big influences on the automotive industry. The acceptance of vehicles with high fuel consumption decreases from year to year. “Green” vehicles driven by alternative propulsion concepts reach increased market penetrations. Among other measures, the potential of aerodynamics has to be tapped to reduce the fuel...
With the experimental data from a road test with a full-size tractor-trailer configuration, I am to recreate the experiment within STAR-CCM+ and compare the solution to the given data. For realistic conditions the simulation will include the rotation of the tires, the relative translation of the road and a detailed volume mesh, which all will be implemented directly via STAR_CCM+.
How Do You Consider Surface Tension Effects Between Particles When Using DEM? In STAR-CCM+, we can model the effect of the presence of the liquid film on the surface of DEM particles in the approximation of liquid bridge model. The capillary force resulting from the surface tension and the pressure difference inside the liquid bridge has known dependence on the wetting angle, liquid surface tension, particle size, etc. If one assumes particular shape of liquid bridge, the solution of Laplace-Young equation provides the solution for hydrostatic pressure within liquid bridge. This gives the analytical solution for the maximum force needed to separate two particles connected with liquid bridge (lots of literature is available on this, including using liquid bridge model with DEM). Now, you just need to equate the liquid bridge force with STAR-CCM+ expression for linear cohesion force and voilà! - obtain the value of STAR-CCM+ cohesion parameter. Using cohesion model this way should account for the surface tension effect on the bulk flow of wet grains.
After explaining why simulating a pool break is so difficult in my last blog post, I couldn't resist actually performing the simulation using Discrete Element Modelling in STAR-CCM+ .
A DEM simulation of a pool break. This simulation does not include the influence of the gravitional pull of the big guy leaning against the bar, or of every single particle in the universe (see this blog post for more information )
CD-adapco today announced a partnership with USA Luge. Together with Panther Racing, the company will provide guidance and technical assistance to USA Luge in an effort to increase aerodynamic efficiency of the team's sleds and racers.
Simulation with STAR-CCM+ showing velocity magnitude contours around a work station with the personal breeze fan turned on.
Pressure contours around the Taj Mahal. Results were obtained from a pollutant dispersion analysis using STAR-CCM+.
I've always been a terrible pool player. Until recently, I attributed this complete lack of talent to my abysmal hand-eye coordination skills. As it turns out, I may have been too hard on myself in that my inability is almost entirely due to the fact that I generally fail to properly take account of all the physical phenomena that influence the pool table when making a shot. More specifically, it's because I usually neglect to to take account the gravitational attraction of the big dude sitting at the opposite corner of the bar. In the past few blog posts we've talked about the importance of 'simulating the system', the process by which we try to account for all the factors that are likely to significantly influence the performance of a design in operation, and how failing to account for some of those physics can reduce the accuracy of your prediction. Exactly the same principles apply when lining up a pool shot! On paper at least, calculating the elastic collision of two pool balls is a relatively trivial task. Let me explain…