Lessons Learnt from a National Competition on Structural Optimization and Additive Manufacturing

2020 ◽  
Vol 1 (1) ◽  
pp. 151-159
Author(s):  
Yulin Xiong ◽  
Dingwen Bao ◽  
Xin Yan ◽  
Tao Xu ◽  
Yi Min Xie
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Structural Optimization ◽  
Optimization Approach ◽  
Loading Test ◽  
Highly Efficient ◽  
Evolutionary Structural Optimization ◽  
National Competition ◽  
Optimal Material ◽  
Manufacturing Technologies

Background:: As an advanced design technique, topology optimization has received much attention over the past three decades. Topology optimization aims at finding an optimal material distribution in order to maximize the structural performance while satisfying certain constraints. It is a useful tool for the conceptional design. At the same time, additive manufacturing technologies have provided unprecedented opportunities to fabricate intricate shapes generated by topology optimization. Objective:: To design a highly efficient structure using topology optimization and to fabricate it using additive manufacturing. Method:: The bi-directional evolutionary structural optimization (BESO) technique provides the conceptional design, and the topology-optimized result is post-processed to obtain smooth structural boundaries. Results:: We have achieved a highly efficient and elegant structural design which won the first prize in a national competition in China on design optimization and additive manufacturing. Conclusion:: In this paper, we present an effective topology optimization approach to maximize the structural load-bearing capacity and establish a procedure to achieve efficient and elegant structural designs. : In the loading test of the final competition, our design carried the highest loading and won the first prize in the competition, which demonstrates the capability of BESO in engineering applications.

Topology Optimization for Constrained Layer Damping Plates Using Evolutionary Structural Optimization Method

2014 ◽  
Vol 894 ◽  
pp. 158-162 ◽  
Author(s):  
Bing Qin Wang ◽  
Bing Li Wang ◽  
Zhi Yuan Huang
Keyword(s):  
Topology Optimization ◽  
Energy Dissipation ◽  
Structural Optimization ◽  
Design Variable ◽  
Loss Factor ◽  
Optimization Approach ◽  
Constrained Layer Damping ◽  
Modal Strain Energy ◽  
Evolutionary Structural Optimization ◽  
Constrained Damping

The evolutionary structural optimization (ESO) is used to optimize constrained damping layer structure. Considering the vibration and energy dissipation mode of the plate with constrained layer damping treatment, the elements of constrained damping layers and modal loss factor are considered as design variable and objective function, while damping material consumption is considered as a constraint. The sensitivity of modal loss factor to design variable is further derived using modal strain energy analysis method. Numerical example is used to demonstrate the effectiveness of the proposed topology optimization approach. The results show that vibration energy dissipation of the plates can be enhanced by the optimal constrained layer damping layout.

Innovative Design, Structural Optimization and Additive Manufacturing of New-Generation Turbine Blades

2021 ◽  
pp. 1-31
Author(s):  
Lorenzo Pinelli ◽  
Andrea Amedei ◽  
Enrico Meli ◽  
Federico Vanti ◽  
Benedetta Romani ◽  
...  
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Structural Optimization ◽  
Turbine Blade ◽  
Turbine Blades ◽  
Topological Optimization ◽  
Mode Shapes ◽  
Structural Topology Optimization ◽  
Structural Topology ◽  
New Generation

Abstract The need for high performances is pushing the complexity of mechanical design at very high levels, especially for turbomachinery components. Structural topology optimization methods together with additive manufacturing techniques for high resistant alloys are considered very promising tools, but their potentialities have not been deeply investigated yet for critical rotating components like new-generation turbine blades. This research work proposes a methodology for the design, the optimization and the additive manufacturing of extremely stressed turbomachinery components like turbine blade-rows. The presented procedure pays particular attention to important aspects of the problems as fluid-structure interactions and fatigue of materials, going beyond the standard structural optimization approaches found in the literature. The numerical procedure shows robustness and efficiency, making the proposed methodology a good tool for rapid design and prototyping, and for reducing the design costs and the time-to-market typical of these mechanical elements. The procedure has been applied to a low-pressure turbine rotor to improve the aeromechanical behavior while keeping the aerodynamic performance. From the original geometry, mode-shapes, forcing functions and aerodynamic damping have been numerically evaluated and are used as input data for the following topological optimization. Finally, the optimized geometry has been verified in order to confirm the improved aeromechanical design. After the structural topology optimization, the final geometries provided by the procedure have been then properly rendered to make them suitable for additive manufacturing. Some prototypes of the new optimized turbine blade have been manufactured to be tested in terms of fatigue.

Innovative Design, Structural Optimization and Additive Manufacturing of New-Generation Turbine Blades

2020 ◽  
Author(s):  
Andrea Amedei ◽  
Enrico Meli ◽  
Andrea Rindi ◽  
Benedetta Romani ◽  
Lorenzo Pinelli ◽  
...  
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Structural Optimization ◽  
Turbine Blade ◽  
Turbine Blades ◽  
Forced Response ◽  
Mode Shapes ◽  
Structural Topology Optimization ◽  
Structural Topology ◽  
New Generation

Abstract The need for high performances is pushing the complexity of mechanical design at very high levels, especially for turbomachinery components. In this field, structural topology optimization methods together with additive manufacturing techniques for high resistant alloys are considered very promising tools, but their potentialities have not been deeply investigated yet for critical rotating components like new-generation turbine blades. In this framework, this research work proposes a methodology for the design, the optimization and the additive manufacturing of extremely stressed turbomachinery components like turbine blade-rows. The presented procedure pays particular attention to important aspects of the problems as fluid-structure interactions (forced response and flutter phenomena) and fatigue of materials, going beyond the standard structural optimization approaches found in the literature. The new design strategy enables a substantial reduction of the component mass, limiting the maximum stress and improving the vibrational behaviour of the system in terms of eigenfrequencies, modal shapes and fatigue life. Furthermore, the numerical procedure shows robustness and efficiency, making the proposed methodology a good tool for rapid design and prototyping, and for reducing the design costs and the time-to-market typical of this kind of mechanical elements. The procedure has been applied to a low-pressure turbine rotor to improve the aeromechanical behavior while keeping the aerodynamic performance. From the original geometry, mode-shapes, forcing functions (due to rotor/stator interactions) and aerodynamic damping have been numerically evaluated and are used as input data for the following topological optimization. Finally, the optimized geometry has been verified in order to confirm the improved aeromechanical design. After the structural topology optimization, the final geometries provided by the procedure have been then properly rendered to make them suitable for additive manufacturing. Some prototypes of the new optimized turbine blade have been manufactured from aluminum to be tested mechanically and in terms of fatigue.

Boundary Slope Control in Topology Optimization for Additive Manufacturing: For Self-Support and Surface Roughness

2019 ◽  
Vol 141 (9) ◽  
Author(s):  
Cunfu Wang ◽  
Xiaoping Qian ◽  
William D. Gerstler ◽  
Jeff Shubrooks
Keyword(s):  
Heat Transfer ◽  
Surface Roughness ◽  
Topology Optimization ◽  
Additive Manufacturing ◽  
Density Gradient ◽  
Transfer Efficiency ◽  
Global Constraints ◽  
Optimization Approach ◽  
Heat Transfer Efficiency ◽  
Boundary Slope

This paper studies how to control boundary slope of optimized parts in density-based topology optimization for additive manufacturing (AM). Boundary slope of a part affects the amount of support structure required during its fabrication by additive processes. Boundary slope also has a direct relation with the resulting surface roughness from the AM processes, which in turn affects the heat transfer efficiency. By constraining the minimal boundary slope, support structures can be eliminated or reduced for AM, and thus, material and postprocessing costs are reduced; by constraining the maximal boundary slope, high-surface roughness can be attained, and thus, the heat transfer efficiency is increased. In this paper, the boundary slope is controlled through a constraint between the density gradient and the given build direction. This allows us to explicitly control the boundary slope through density gradient in the density-based topology optimization approach. We control the boundary slope through two single global constraints. An adaptive scheme is also proposed to select the thresholds of these two boundary slope constraints. Numerical examples of linear elastic problem, heat conduction problem, and thermoelastic problems demonstrate the effectiveness and efficiency of the proposed formulation in controlling boundary slopes for additive manufacturing. Experimental results from metal 3D printed parts confirm that our boundary slope-based formulation is effective for controlling part self-support during printing and for affecting surface roughness of the printed parts.

Design and Fabrication of Structural Connections Using Bi-Directional Evolutionary Structural Optimization and Additive Manufacturing

2016 ◽  
Vol 846 ◽  
pp. 571-576 ◽  
Author(s):  
Hamed Seifi ◽  
Mike Xie ◽  
James O’Donnell ◽  
Nicholas Williams
Keyword(s):  
Additive Manufacturing ◽  
Structural Optimization ◽  
Large Scale ◽  
Limited Area ◽  
Complex Structures ◽  
Evolutionary Structural Optimization ◽  
3D Printed ◽  
Structural Connections ◽  
Definition Of ◽  
Processing Steps

The need to simplify the construction issues of complex structures leads to definition of SmartNodes project as a research which aims to confine the complexity of structure to a limited area (nodes) in order to decrease processing steps and labor intensity by application of additive manufacturing (AM) techniques. Bi-Directional Evolutionary Structural Optimization (BESO) is used to design efficient and elegant nodal connections of large scale spatial structures and minimise the volume of nodes to be printed and to ultimately replace welded, forged and cast connections by 3D printed connections. The prototypes discussed in this paper demonstrate BESO design process through two generic cases.

scholarly journals Continuous Fiber Angle Topology Optimization for Polymer Composite Deposition Additive Manufacturing Applications

Fibers ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 14 ◽  
Author(s):  
Delin Jiang ◽  
Robert Hoglund ◽  
Douglas Smith
Keyword(s):  
Mechanical Properties ◽  
Topology Optimization ◽  
Additive Manufacturing ◽  
Carbon Fiber ◽  
Polymer Composite ◽  
Fiber Reinforcement ◽  
Fiber Direction ◽  
Optimization Approach ◽  
Continuous Fiber ◽  
Fiber Angle

Mechanical properties of parts produced with polymer deposition additive manufacturing (AM) depend on the print bead direction, particularly when short carbon-fiber reinforcement is added to the polymer feedstock. This offers a unique opportunity in the design of these structures since the AM print path can potentially be defined in a direction that takes advantage of the enhanced stiffness gained in the bead and, therefore, fiber direction. This paper presents a topology optimization approach for continuous fiber angle optimization (CFAO), which computes the best layout and orientation of fiber reinforcement for AM structures. Statically loaded structures are designed for minimum compliance where the adjoint variable method is used to compute design derivatives, and a sensitivity filter is employed to reduce the checkerboard effect. The nature of the layer-by-layer approach in AM is given special consideration in the algorithm presented. Examples are provided to demonstrate the applicability of the method in both two and three dimensions. The solution to our two dimensional problem is then printed with a fused filament fabrication (FFF) desktop printer using the material distribution results and a simple infill method which approximates the optimal fiber angle results using a contour-parallel deposition strategy. Mechanical stiffness testing of the printed parts shows improved results as compared to structures designed without accounting for the direction of the composite structure. Results show that the mechanical properties of the final FFF carbon fiber/polymer composite printed parts are greatly influenced by the print direction, and optimized material orientation tends to align with the imposed force direction to minimize the compliance.

A Multi-Scale Topology Optimization Approach for Optimal Macro-Layout and Local Grading of TPMS-Based Lattices

2021 ◽  
Author(s):  
Niclas Strömberg
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Local Density ◽  
Bulk Material ◽  
Transversely Isotropic ◽  
Benchmark Problems ◽  
Optimization Approach ◽  
Lattice Structures ◽  
Efficient Design ◽  
Multi Scale

Abstract The use of lattice structures in design for additive manufacturing has quickly emerged as a popular and efficient design alternative for creating innovative multifunctional lightweight solutions. In particular, the family of triply periodic minimal surfaces (TPMS) studied in detail by Schoen for generating frame-or shell-based lattice structures seems extra promising. In this paper a multi-scale topology optimization approach for optimal macro-layout and local grading of TPMS-based lattice structures is presented. The approach is formulated using two different density fields, one for identifying the macro-layout and another one for setting the local grading of the TPMS-based lattice. The macro density variable is governed by the standard SIMP formulation, but the local one defines the orthotropic elasticity of the element following material interpolation laws derived by numerical homogenization. Such laws are derived for frame- and shell-based Gyroid, G-prime and Schwarz-D lattices using transversely isotropic elasticity for the bulk material. A nice feature of the approach is that the lower and upper additive manufacturing limits on the local density of the TMPS-based lattices are included properly. The performance of the approach is excellent, and this is demonstrated by solving several three-dimensional benchmark problems, e.g., the optimal macro-layout and local grading of Schwarz-D lattice for the established GE-bracket is identified using the presented approach.

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