Ahmad Barari PhD, PE, Assistant Professor, University of Ontario Institute of Technology
Amirali Lalehpour, PhD Student, University of Ontario Institute of Technology
Additive manufacturing (AM) since its emergence and development into a manufacturing process, has made it possible to manufacture lots of complicated designs, such as Topology Optimization (TO), which where unfeasible by the traditional methods. However, there are limitations on the way of manufacturing the TO results with AM, making it crucial to develop an algorithm that takes AM restriction into account. This research intends to introduce a new paradigm to identify the unfeasible areas and modify them to make them feasible by AM. The areas with angles less than 45 degrees and the bridges are considered unfeasible. The new paradigm operates as a filter and a threshold is defined for it based on the volume fraction of the iteration and the geometric area of the section to be added to the structure in order to make it feasible. The closer the current volume fraction gets to the target volume and the larger gets the unfeasible section, the more sensitive gets the filter. When it is close enough to the target, the filter becomes more sensitive and changes the unfeasible areas to feasible ones. The results of this methodology are found to be manufacturable by AM while were not before being modified by the new paradigm.