Topology Optimization and Design for Additive Manufactured Supporting Structure of Vehicle Rudder

Abstract The object investigated in this work is a design method for the supporting structure of vehicle rudders, which are the crucial components in flight control system. As a practical application of topology optimization for additive manufacture, the design process was presented in this article. To obtain the optimal material distribution, topology optimization based on SIMP method was applied, with compliance minimization as the optimization objective. A numerical optimization model was built and calculated in Inspire, and the result in an equivalent load scheme of 30 percent point load and 70 percent uniform pressure was adopted to be the initial geometry for the subsequent design. Concentrating on realizing the optimized geometry, this design took a series of technical constrains for additive manufacture and mass requirements into consideration. Notably, the FEM simulation for the supporting structure is necessary, which consist of stress analysis and mode analysis. And the technical feasibility was verified in its practical manufacturing process. Finally, by the experiment about dynamic characteristic, it is verified that the lightweight rudder designed in this work can satisfy all the requirements for flight control.

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A Comprehensive Review of Isogeometric Topology Optimization: Methods, Applications and Prospects

Chinese Journal of Mechanical Engineering ◽

10.1186/s10033-020-00503-w ◽

2020 ◽

Vol 33 (1) ◽

Author(s):

Jie Gao ◽

Mi Xiao ◽

Yan Zhang ◽

Liang Gao

Keyword(s):

Topology Optimization ◽

Computer Aided Design ◽

Numerical Technique ◽

Optimization Methods ◽

Negative Influence ◽

Comprehensive Overview ◽

Promising Alternative ◽

Computer Aided ◽

Optimal Material ◽

Material Layout

AbstractTopology Optimization (TO) is a powerful numerical technique to determine the optimal material layout in a design domain, which has accepted considerable developments in recent years. The classic Finite Element Method (FEM) is applied to compute the unknown structural responses in TO. However, several numerical deficiencies of the FEM significantly influence the effectiveness and efficiency of TO. In order to eliminate the negative influence of the FEM on TO, IsoGeometric Analysis (IGA) has become a promising alternative due to its unique feature that the Computer-Aided Design (CAD) model and Computer-Aided Engineering (CAE) model can be unified into a same mathematical model. In the paper, the main intention is to provide a comprehensive overview for the developments of Isogeometric Topology Optimization (ITO) in methods and applications. Finally, some prospects for the developments of ITO in the future are also presented.

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A Shape Optimization Method for Part Design Derived from the Buildability Restrictions of the Directed Energy Deposition Additive Manufacturing Process

Designs ◽

10.3390/designs4030019 ◽

2020 ◽

Vol 4 (3) ◽

pp. 19

Author(s):

Andreas K. Lianos ◽

Harry Bikas ◽

Panagiotis Stavropoulos

Keyword(s):

Topology Optimization ◽

Additive Manufacturing ◽

Energy Deposition ◽

Design Method ◽

Current Trend ◽

Internal Stresses ◽

Material Distribution ◽

Load Case ◽

Design Elements ◽

Industrial Sectors

The design methodologies and part shape algorithms for additive manufacturing (AM) are rapidly growing fields, proven to be of critical importance for the uptake of additive manufacturing of parts with enhanced performance in all major industrial sectors. The current trend for part design is a computationally driven approach where the parts are algorithmically morphed to meet the functional requirements with optimized performance in terms of material distribution. However, the manufacturability restrictions of AM processes are not considered at the primary design phases but at a later post-morphed stage of the part’s design. This paper proposes an AM design method to ensure: (1) optimized material distribution based on the load case and (2) the part’s manufacturability. The buildability restrictions from the direct energy deposition (DED) AM technology were used as input to the AM shaping algorithm to grant high AM manufacturability. The first step of this work was to define the term of AM manufacturability, its effect on AM production, and to propose a framework to estimate the quantified value of AM manufacturability for the given part design. Moreover, an AM design method is proposed, based on the developed internal stresses of the build volume for the load case. Stress tensors are used for the determination of the build orientation and as input for the part morphing. A top-down mesoscale geometric optimization is used to realize the AM part design. The DED Design for Additive Manufacturing (DfAM) rules are used to delimitate the morphing of the part, representing at the same time the freeform mindset of the AM technology. The morphed shape of the part is optimized in terms of topology and AM manufacturability. The topology optimization and AM manufacturability indicator (TMI) is introduced to screen the percentage of design elements that serve topology optimization and the ones that serve AM manufacturability. In the end, a case study for proof of concept is realized.

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The Study on Fatigue Life of Interconnect with Respect to Geometrical Shape of Supporting Structure and Load Conditions in MEMS

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.297-300.539 ◽

2005 ◽

Vol 297-300 ◽

pp. 539-544

Author(s):

Jae Joon Shim ◽

Geun Jo Han ◽

Kwang Young Kim ◽

Doo Pyo Yun ◽

Chul Ho Ok ◽

...

Keyword(s):

Fatigue Life ◽

Critical Temperature ◽

Thermal Load ◽

Fem Simulation ◽

Geometrical Shape ◽

Operating Life ◽

Batch Production ◽

Supporting Structure ◽

External Conditions ◽

Load Conditions

Recently, application of semiconductor sensors has widely spreaded into various industries becasuse those have several merits like easy miniaturization and batch production etc. But external conditions such as thermal and repetitive load have a bad effect on sensors’s lifetime. Therefore, lots of studies related with the fatigue of microelectromechnical systems (MEMS) have been conducted. Especially, this paper was focused on fatigue life of aluminum interconnect in the supporting structure of sensor under cyclic thermal load and on the approximation equation defining the critical temperature to ensure required operating life using FEM simulation.

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Structural topology optimization of bridge girders in cable supported bridges

IABSE Conference, Kuala Lumpur 2018: Engineering the Developing World ◽

10.2749/kualalumpur.2018.0975 ◽

2018 ◽

Author(s):

Mads Baandrup ◽

Ole Sigmund ◽

Niels Aage

Keyword(s):

Topology Optimization ◽

Large Scale ◽

Design Method ◽

Optimization Method ◽

Bridge Girders ◽

Structural Topology ◽

Box Girders ◽

Box Girder ◽

Fine Mesh ◽

Further Development

This work applies a ultra large scale topology optimization method to study the optimal structure of bridge girders in cable supported bridges.The current classic orthotropic box girder designs are limited in further development and optimiza tion, and suffer from substantial fatigue issues. A great disadvantage of the orthotropic girder is the loads being carried one direction at a time, thus creating stress hot spots and fatigue problems. Hence, a new design concept has the potential to solve many of the limitations in the current state of-the-art.We present a design method based on ultra large scale topology optimization. The highly detailed structures and fine mesh-discretization permitted by ultra large scale topology optimization reveal new design features and previously unseen eff ects. The results demonstrate the potential of gener ating completely different design solutions for bridge girders in cable supported bridges, which dif fer significantly from the classic orthotropic box girders.The overall goal of the presented work is to identify new and innovative, but at the same time con structible and economically reasonable, solutions tobe implemented into the design of future cable supported bridges.

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Topology Optimization of Dynamic Systems Under Uncertain Loads: An H∞-Norm-Based Approach

Journal of Computational and Nonlinear Dynamics ◽

10.1115/1.4042140 ◽

2019 ◽

Vol 14 (2) ◽

Author(s):

Paolo Venini

Keyword(s):

Topology Optimization ◽

Structural Parameters ◽

Goal Function ◽

Dynamic Compliance ◽

Case Scenario ◽

Worst Case ◽

Original Definition ◽

Optimal Material ◽

The One ◽

Definition Of

An innovative approach to topology optimization of dynamic system is introduced that is based on the system transfer-function H∞-norm. As for the structure, the proposed strategy allows to determine the optimal material distribution that ensures the minimization of a suitable goal function, such as (an original definition of) the dynamic compliance. Load uncertainty is accounted for by means of a nonprobabilistic convex-set approach (Ben-Haim and Elishakoff, 1990, Convex Models of Uncertainty in Applied Mechanics, Elsevier Science, Amsterdam). At each iteration, the worst load is determined as the one that maximizes the current dynamic compliance so that the proposed strategy fits the so-called worst case scenario (WCS) approach. The overall approach consists of the repeated solution of the two steps (minimization of the dynamic compliance with respect to structural parameters and maximization of the dynamic compliance with respect to the acting load) until convergence is achieved. Results from representative numerical studies are eventually presented along with extensions to the proposed approach that are currently under development.

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Multiscale, thermomechanical topology optimization of self-supporting cellular structures for porous injection molds

Rapid Prototyping Journal ◽

10.1108/rpj-09-2017-0190 ◽

2019 ◽

Vol 25 (9) ◽

pp. 1482-1492

Author(s):

Tong Wu ◽

Andres Tovar

Keyword(s):

Topology Optimization ◽

Mechanical Performance ◽

Mechanical Load ◽

Design Method ◽

Three Dimensional ◽

Optimization Method ◽

Cellular Structures ◽

Injection Mold ◽

Computationally Efficient ◽

Content Type

Purpose This paper aims to establish a multiscale topology optimization method for the optimal design of non-periodic, self-supporting cellular structures subjected to thermo-mechanical loads. The result is a hierarchically complex design that is thermally efficient, mechanically stable and suitable for additive manufacturing (AM). Design/methodology/approach The proposed method seeks to maximize thermo-mechanical performance at the macroscale in a conceptual design while obtaining maximum shear modulus for each unit cell at the mesoscale. Then, the macroscale performance is re-estimated, and the mesoscale design is updated until the macroscale performance is satisfied. Findings A two-dimensional Messerschmitt Bolkow Bolhm (MBB) beam withstanding thermo-mechanical load is presented to illustrate the proposed design method. Furthermore, the method is implemented to optimize a three-dimensional injection mold, which is successfully prototyped using 420 stainless steel infiltrated with bronze. Originality/value By developing a computationally efficient and manufacturing friendly inverse homogenization approach, the novel multiscale design could generate porous molds which can save up to 30 per cent material compared to their solid counterpart without decreasing thermo-mechanical performance. Practical implications This study is a useful tool for the designer in molding industries to reduce the cost of the injection mold and take full advantage of AM.

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Optimisation of Springback Predicted by Experimental and Numerical Approach by Using Response Surface Methodology

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.6-8.753 ◽

2005 ◽

Vol 6-8 ◽

pp. 753-762

Author(s):

R. Bahloul ◽

Phillippe dal Santo ◽

Ali Mkaddem ◽

A. Potiron

Keyword(s):

Response Surface ◽

Sheet Metal ◽

Design Method ◽

Fem Simulation ◽

Numerical Approach ◽

Tool Geometry ◽

Nose Radius ◽

Element Analysis ◽

Metal Parts ◽

Sheet Metal Parts

Bending has significant importance in the sheet metal product industry. Moreover, the springback of sheet metal should be taken into consideration in order to produce bent sheet metal parts within acceptable tolerance limits and to solve geometrical variation for the control of manufacturing process. Nowadays, the importance of this problem increases because of the use of sheet-metal parts with high mechanical characteristics (High Strength Low Alloy steel). This work describes robust methods of predicting springback of parts in 3D modelling subjected to bending and unbending deformations. Also the effects of tool geometry in the final shape after springback are discussed. The first part of this paper presents the laboratory experiments in wiping die bending, in which the influence of process variables, such as die shoulder radius, punch-die clearance, punch nose radius and materials properties were discussed. The second part summarises the finite element analysis by using ABAQUS software and compares these results with some experimental data. It appeared that the final results of the FEM simulation are in good agreement with the experimental ones. An optimisation methodology based on the use of experimental design method and response surface technique is proposed in the third part of this paper. That makes it possible to obtain the optimum values of clearance between the punch and the die and the optimum die radius which can reduce the springback without cracking and damage of product.

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An Artificial Intelligence–Assisted Design Method for Topology Optimization without Pre-Optimized Training Data

Applied Sciences ◽

10.3390/app11199041 ◽

2021 ◽

Vol 11 (19) ◽

pp. 9041

Author(s):

Alex Halle ◽

Lucio Flavio Campanile ◽

Alexander Hasse

Keyword(s):

Topology Optimization ◽

Input Data ◽

Design Method ◽

Design Procedure ◽

Computational Effort ◽

Training Data ◽

Geometry Design ◽

Random Input Data ◽

Degree Of Filling ◽

Initial Process

Engineers widely use topology optimization during the initial process of product development to obtain a first possible geometry design. The state-of-the-art method is iterative calculation, which requires both time and computational power. This paper proposes an AI-assisted design method for topology optimization, which does not require any optimized data. An artificial neural network—the predictor—provides the designs on the basis of boundary conditions and degree of filling as input data. In the training phase, the so-called evaluators evaluate the generated geometries on the basis of random input data with respect to given criteria. The results of those evaluations flow into an objective function, which is minimized by adapting the predictor’s parameters. After training, the presented AI-assisted design procedure generates geometries that are similar to those of conventional topology optimizers, but require only a fraction of the computational effort. We believe that our work could be a clue for AI-based methods that require data that are difficult to compute or unavailable.

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Modelling, Design and Validation of a Parallel Kinematic Robot for Additive Manufacture Applications

10.17352/ara.000009 ◽

2021 ◽

pp. 019-029

Author(s):

Lahoud Marcel ◽

Melendez Leonardo ◽

Gil Arturo

Keyword(s):

Additive Manufacturing ◽

Open Source Software ◽

Design Method ◽

Kinematic Model ◽

Additive Manufacture ◽

Parallel Kinematics ◽

Cartesian Space ◽

Parallel Kinematic ◽

Manufacturing Applications ◽

Design Construction

The additive manufacture is a fabrication process that has taken huge steps in the last decade, even though the first researches and prototypes are around since almost forty years ago. In this article, a design method for a Parallel Kinematics Robot for Additive Manufacturing Applications is proposed. A numerical model is obtained from the kinematics of the robot for which the design, construction and assembly are planned using recycled materials and equipment. The control of the robot is done using open source software, allowing the planning of trajectories in the Cartesian space on a maximum designed cylindrical workspace of 300mm in diameter by 300mm high. At the end of the work the robot was identified, the kinematic model was validated and considerations for future works were given.

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Microstructural Topology Optimization of Constrained Layer Damping on Plates for Maximum Modal Loss Factor of Macrostructures

Shock and Vibration ◽

10.1155/2020/8837610 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13

Author(s):

Zhanpeng Fang ◽

Lei Yao ◽

Shuxia Tian ◽

Junjian Hou

Keyword(s):

Topology Optimization ◽

Loss Factor ◽

Strain Energy ◽

Design Method ◽

Optimization Method ◽

Constrained Layer Damping ◽

Viscoelastic Materials ◽

Modal Strain Energy ◽

Design Variables ◽

Microstructural Topology Optimization

This paper presents microstructural topology optimization of viscoelastic materials for the plates with constrained layer damping (CLD) treatments. The design objective is to maximize modal loss factor of macrostructures, which is obtained by using the Modal Strain Energy (MSE) method. The microstructure of the viscoelastic damping layer is composed of 3D periodic unit cells. The effective elastic properties of the unit cell are obtained through the strain energy-based method. The density-based topology optimization is adopted to find optimal microstructures of viscoelastic materials. The design sensitivities of modal loss factor with respect to the design variables are analyzed and the design variables are updated by Method of Moving Asymptotes (MMA). Numerical examples are given to demonstrate the validity of the proposed optimization method. The effectiveness of the optimal design method is illustrated by comparing a solid and an optimized cellular viscoelastic material as applied to the plates with CLD treatments.

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