Topology optimization subject to additive manufacturing constraints

In topology optimization the goal is to find the ideal material distribution in a domain subject to external forces. The structure is optimal if it has the highest possible stiffness. A volume constraint ensures filigree structures, which are regulated via a Ginzburg–Landau term. During 3D printing overhangs lead to instabilities. As a remedy an additive manufacturing constraint is added to the cost functional. First order optimality conditions are derived using a formal Lagrangian approach. With an Allen-Cahn interface propagation the optimization problem is solved iteratively. At a low computational cost the additive manufacturing constraint brings about support structures, which can be fine tuned according to demands and increase stability during the printing process.

Manufacturable casting parts design with topology optimization of structural assemblies

This paper presents a design method for manufacturable casting parts based on topology optimization of structural assemblies, which considers the geometry requirement and the manufacturing constraint of die-set material cost. The problem formulation follows the previous work presented in multi-component topology optimization for stamped sheet metal assemblies (MTO-S). Based on the vector method combined with Heaviside function, the moldability constraints for casting parts is formulated. As the base structure of component is easily misidentified as an undercut structure by the moldability constraints in the structural assemblies, the component baseline is proposed to realize the automatic filtering of the “fake” undercut structures which can be extended to the parting line to obtain the form of two-mold design. Several numerical examples on compliance minimization of single-mold and two-mold casting parts are conducted to verify the validity of the proposed method. The optimized results show that there is no interior void for each component and the component manufacturability has been improved obviously. The setting of minimum-area bounding box (MABB) area constraint limits and the number of components will have a significant effect on the performance of the optimized structure. Users can achieve the desirable solution based on their actual demand by making trade-offs between the structural performance and manufacturing cost.

A new development of a shadow density filter for manufacturing constraint and its applications to multiphysics topology optimization

The present research develops a new shadow filter and presents its usage for structural topology optimization (TO) considering the molding manufacturability. It is important to consider manufacturing methods in designing products. Some geometrical features not allowing molded parts should be removed. In addition, it has been an important issue to efficiently impose these manufacturing constraints in TO. For this purpose, the present research emulates implementation of shadowing of products and applies the shadow images as pseudodensity variables in TO. The use of this shadow density filter ensures that the optimized layouts comply with the conditions of the manufacturing constraints. Various manufacturing conditions can be imposed depending on the direction and the position of the light. Several numerical examples of compliance minimization problem, conjugate heat transfer problem and fluid-structure interaction problem are solved to demonstrate the validity and effectiveness of the present shadow density filters, and their performances are compared.

Data-Driven Additive Manufacturing Constraints for Topology Optimization

The topology optimization (TO) of structures to be produced using additive manufacturing (AM) is explored using a data-driven constraint function that predicts the minimum producible size of small features in different shapes and orientations. This shape- and orientation-dependent manufacturing constraint, derived from experimental data, is implemented within a TO framework using a modified version of the moving morphable components (MMC) approach. Because the analytic constraint function is fully differentiable, gradient-based optimization can be used. The MMC approach is extended in this work to include a “bootstrapping” step, which provides initial component layouts to the MMC algorithm based on intermediate solid isotropic material with penalization (SIMP) topology optimization results. This “bootstrapping” approach improves convergence compared with reference MMC implementations. Results from two compliance design optimization example problems demonstrate the successful integration of the manufacturability constraint in the MMC approach, and the optimal designs produced show minor changes in topology and shape compared to designs produced using fixed-radius filters in the traditional SIMP approach. The use of this data-driven manufacturability constraint makes it possible to take better advantage of the achievable complexity in additive manufacturing processes, while resulting in typical penalties to the design objective function of around only 2% when compared with the unconstrained case.

Data-Driven Additive Manufacturing Constraints for Topology Optimization

The topology optimization (TO) of structures to be produced using additive manufacturing (AM) is explored using a data-driven constraint function that predicts the minimum producible size of small features in different shapes and orientations. This shape- and orientation-dependent manufacturing constraint, derived from experimental data, is implemented within a TO framework using a modified version of the Moving Morphable Components (MMC) approach. Because the analytic constraint function is fully differentiable, gradient-based optimization can be used. The MMC approach is extended in this work to include a “bootstrapping” step, which provides initial component layouts to the MMC algorithm based on intermediate Solid Isotropic Material with Penalization (SIMP) topology optimization results. This “bootstrapping” approach improves convergence compared to reference MMC implementations. Results from two compliance design optimization example problems demonstrate the successful integration of the manufacturability constraint in the MMC approach, and the optimal designs produced show minor changes in topology and shape compared to designs produced using fixed-radius filters in the traditional SIMP approach. The use of this data-driven manufacturability constraint makes it possible to take better advantage of the achievable complexity in additive manufacturing processes, while resulting in typical penalties to the design objective function of around only 2% when compared to the unconstrained case.

Effect of Spanwise Variation of Chord on the Performance of a Turbine Cascade

This paper compares the aerodynamic performance of two cascade designs, viz.: - constant-chord and varying-chord. The varying-chord design is typical of industrial gas turbines and steam turbine stators in order to reduce manufacturing costs. The present study aims to increase the understanding of the implications of this manufacturing constraint on the aerodynamics of the stator. Experiments are carried out in a linear cascade wind tunnel. Numerical simulations are performed using commercial code CFX. The profile losses and secondary losses in the two designs are compared. The overall total pressure losses indicate better aerodynamic performance of a turbine cascade with constant chord as compared to a turbine cascade of varying-chord design.