Topology Optimization of Fluidic Pressure Loaded Structures and Compliant Mechanisms using the Darcy Method

Abstract

In various applications, design problems involving structures and compliant mechanisms experience fluidic pressure loads. During topology optimization of such design problems, these loads adapt their direction and location with the evolution of the design, which poses various challenges. A new density-based topology optimization approach using Darcy's law in conjunction with a drainage term is presented to provide a continuous and consistent treatment of design-dependent fluidic pressure loads. The porosity of each finite element and its drainage term are related to its density variable using a Heaviside function, yielding a smooth transition between the solid and void phases. A design-dependent pressure field is established using Darcy's law and the associated PDE is solved using the finite element method. Further, the obtained pressure field is used to determine the consistent nodal loads. The approach provides a computationally inexpensive evaluation of load sensitivities using the adjoint-variable method. To show the efficacy and robustness of the proposed method, numerical examples related to fluidic pressure loaded stiff structures and small-deformation compliant mechanisms are solved. For the structures, compliance is minimized, whereas for the mechanisms a multi-criteria objective is minimized with given resource constraints.

arXiv comment29 pages, 18 figures

Cited by in corpus (10)

• Topology optimization of stiff structures under self-weight for given volume using a smooth Heaviside function
• HoneyTop90: A 90-line MATLAB code for topology optimization using honeycomb tessellation
• TOPress: a MATLAB implementation for topology optimization of structures subjected to design-dependent pressure loads
• Topological synthesis of fluidic pressure-actuated robust compliant mechanisms
• Tree Reconstruction using Topology Optimisation
• SoRoTop: a hitchhiker's guide to topology optimization MATLAB code for design-dependent pneumatic-driven soft robots
• An improved Material Mask Overlay Strategy for the desired discreteness of pressure-loaded optimized topologies
• Towards topology optimization of pressure-driven soft robots
• TOaCNN: Adaptive Convolutional Neural Network for Multidisciplinary Topology Optimization
• Soft Pneumatic Grippers: Topology optimization, 3D-printing and Experimental validation