Mold Flow Simulation Pdf 20 !EXCLUSIVE!
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In this study, we propose an integrated particle approach based on the coupling of smoothed particle hydrodynamics (SPH) and discrete element method (DEM) to predict the injection molding process of discrete short fibers. The fibers in the coupled SPH-DEM model are treated as non-rigid bodies to allow deformation and fracture. The interaction between resin and fibers is solved by a physical model to take into consideration of drag forces. Two cases of injection molding process with different volume fractions of short fibers are studied to predict the flow behaviors of fibers and resin. The numerical results qualitatively agree with previous experimental studies. It is found that the velocity contour of resin flow is parabolic in shape due to the velocity gradient near the wall boundaries and consequently the moving direction of fibers is in parallel with the flow direction of resin. Fiber accumulation is found in the case with higher content of short fibers.
There are two main applications for mold-filling simulation. One is in optimizing a new mold design before steel is cut. The second is solving problems with an existing mold. Both can save lots of time and money.
1. Make a list of what is expected of the analysis and decide if the benefits justify the cost. Do you want iterations at different fill times, temperatures, and gate locations Do you want to know the clamp-pressure requirement (Note: When a mold has slides, flow simulation generally does not predict the forces projected against the clamp over the heel blocks.) Want to make sure you know weld-line locations, high-stress areas, venting issues, or pressure distribution Do you need to make sure your equipment has the shot size and injection speed/pressure necessary to mold this part
3. Be prepared for some hard compromises. The filling analysis may identify an ideal location for the gate from a processing viewpoint, but building a mold with that gate location may be impossible or extremely costly, or the gate location may not be not acceptable from a product performance or aesthetics viewpoint. The simulation analyst should have access to sufficient design information to be aware of such restrictions and should have access to the design team to be able to explore any flexibility allowed in part design and application.
Experience counts. Repeat that 10 times. The ideal analyst has years of experience, not only with the software, but also has shop-floor experience in processing, materials, tooling, and part design. Each of these play a role in flow analysis and affect the quality of the results. Finding someone with this diversity of experience is unfortunately rare, so look for a shop that uses a team of these players to do the flow analysis. Try to find a team that will actually test the results on an existing tool. Request, perhaps demand, that they show you a case history where experiments on the tool matched their predictions.
Mold-filling simulation and analysis can tell you a lot about how well and how fast a mold will fill under a given set of conditions. But the accuracy of results depends on many factors, including the accuracy of the material data and the experience of the analyst in plastics materials, molding, and tooling. (Photo: Autodesk Moldflow)
Ansys Polyflow accelerates design time while shrinking energy and raw material demands for manufacturing processes. Polyflow helps to investigate the behavior of new plastics and elastomers. Virtual prototyping enables optimization and design exploration to reduce waste and overdesign.
Performing blow-molding simulation as well as structural analysis provides a method for companies to ensure reliability. Changes made to the manufacturing process can be directly related to final part performance through simulation.
In high-volume manufacturing, such as water containers, a minor reduction in material can drastically reduce costs and improve profit over time. However, reducing material can be risky withou