This paper presents a synthesis approach in a density-based topology optimization setting to design large deformation compliant mechanisms for inducing desired strains in biological tissues. The modelling is based on geometrical nonlinearity together with a suitably chosen hypereleastic material model, wherein the mechanical equilibrium equations are solved using the total Lagrangian finite element formulation. An objective based on least-square error with respect to target strains is formulated and minimized with the given set of constraints and the appropriate surroundings of the tissues. To circumvent numerical instabilities arising due to large deformation in low stiffness design regions during topology optimization, a strain-energy based interpolation scheme is employed. The approach uses an extended robust formulation i.e. the eroded, intermediate and dilated projections for the design description as well as variation in tissue stiffness. Efficacy of the synthesis approach is demonstrated by designing various compliant mechanisms for providing different target strains in biological tissue constructs. Optimized compliant mechanisms are 3D-printed and their performances are recorded in a simplified experiment and compared with simulation results obtained by a commercial software.
翻译:本文介绍了在基于密度的地形优化环境中设计大规模畸形适应机制以诱导生物组织所需菌株的大规模畸形适应性机制的综合方法,模型以几何非线性为基础,并采用适当选择的超电子材料模型,其中机械平衡方程式使用总Lagrangian有限元素配方来解决,根据目标菌株方面最差的差错制定目标,并用给定的制约和组织的适当环境来尽量减少目标菌株;为避免因低僵化设计区在地形优化期间发生大规模变形而产生的数字不稳定,采用了基于压力能源的内推法;该方法使用一种扩大的稳健配方,即对设计描述以及组织僵硬度的变异进行侵蚀、中间和变异的预测。通过设计各种兼容机制,在生物组织构造中提供不同的目标菌株,可以证明合成方法的有效性。优化的遵守机制是3D打印的,其性能记录在简化的实验中,并与商业软件取得的模拟结果进行比较。