Regularization Scheme for Controlling Length Scale in Topology Optimization Based on Bacterial Quemotaxis

In order to avoid numerical problems in topological optimization such as checkerboards or mesh dependence, different regularization schemes have been used including penalization, continuation and filtering [24]. This research shows a new regularization scheme to avoid these problems in the Bacterial Chemotaxis Based Topology Optimization Algorithm- BCBTOA [23]. This algorithm simulates the behavior of marine bacteria that forms honeycomb patterns to represent the distribution of material in a domain [23], The original algorithm suffered from a faulty tuning of parameters [23] And after making some modifications we have obtained two fundamental parameters that control the algorithm, these parameters are the radius of action of the chemotactic model of communication between bacteria, (parameter R) and the desired volume fraction (parameter f) [21]. When the parameter R changes it restricts the size of the cavities and solid zones in the structure, the solid zones being larger as R increases and retaining the desired volume fraction f. From the above we deduce that the parameter R functions as a regularization parameter to control the size of the structural members. As a result, we obtained several layouts for different topology optimization problems of continuous bi-dimensional structures.