scholarly journals Experimental Observation of the Skeletal Adaptive Repair Mechanism and Bionic Topology Optimization Method

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Kaysar Rahman ◽  
Mamtimin Geni ◽  
Mamatjan Mamut ◽  
Nijat Yusup ◽  
Muhtar Yusup
Keyword(s):  
Topology Optimization ◽  
Bone Remodeling ◽  
External Load ◽  
Optimization Problems ◽  
Reaction Diffusion ◽  
Optimization Method ◽  
Experimental Result ◽  
Spongy Bone ◽  
Ct Data ◽  
Cross Type

Bone adaptive repair theory considers that the external load is the direct source of bone remodeling; bone achieves its maintenance by remodeling some microscopic damages due to external load during the process. This paper firstly observes CT data from the whole self-repairing process in bone defects in rabbit femur. Experimental result shows that during self-repairing process there exists an interaction relationship between spongy bone and enamel bone volume changes of bone defect, that is when volume of spongy bone increases, enamel bone decreases, and when volume of spongy bone decreases, enamel bone increases. Secondly according to this feature a bone remodeling model based on cross-type reaction-diffusion system influenced by mechanical stress is proposed. Finally, this model coupled with finite element method by using the element adding and removing process is used to simulate the self-repairing process and engineering optimization problems by considering the idea of bionic topology optimization.

Non-Probabilistic Based Topology Optimization Under External Load Uncertainty With Eigenvalue-Superposition of Convex Models

2013 ◽  
Author(s):  
Xike Zhao ◽  
Hae Chang Gea ◽  
Wei Song
Keyword(s):  
Topology Optimization ◽  
External Load ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Optimization Method ◽  
Convex Model ◽  
Structure Response ◽  
Gradient Based ◽  
Bounded Convex ◽  
Topology Optimization Method

In this paper the Eigenvalue-Superposition of Convex Models (ESCM) based topology optimization method for solving topology optimization problems under external load uncertainties is presented. The load uncertainties are formulated using the non-probabilistic based unknown-but-bounded convex model. The sensitivities are derived and the problem is solved using gradient based algorithm. The proposed ESCM based method yields the material distribution which would optimize the worst structure response under the uncertain loads. Comparing to the deterministic based topology optimization formulation the ESCM based method provided more reasonable solutions when load uncertainties were involved. The simplicity, efficiency and versatility of the proposed ESCM based topology optimization method can be considered as a supplement to the sophisticated reliability based topology optimization methods.

Structural Topology Optimization Method Based on Bone Remodeling

2013 ◽  
Vol 423-426 ◽  
pp. 1813-1818
Author(s):  
Kaysar Rahman ◽  
Nurmamat Helil ◽  
Rahmatjan Imin ◽  
Mamtimin Geni
Keyword(s):  
Topology Optimization ◽  
Bone Remodeling ◽  
Bone Structure ◽  
Reaction Diffusion ◽  
Optimization Method ◽  
Mechanical Stimulus ◽  
Bone Adaptation ◽  
Reaction Diffusion Equations ◽  
Structural Topology Optimization ◽  
Structural Topology

Bone is a dynamic living tissue that undergoes continuous adaptation of its mass and structure in response to mechanical and biological environment demands. In this paper, we firstly propose a mathematical model based on cross-type reaction diffusion equations of bone adaptation during a remodeling cycle due to mechanical stimulus. The model captures qualitatively very well the bone adaptation and cell interactions during the bone remodeling. Secondly assuming the bone structure to be a self-optimizing biological material which maximizes its own structural stiffness, bone remodeling model coupled with finite element method by using the add and remove element a new topology optimization of continuum structure is presented. Two Numerical examples demonstrate that the proposed approach greatly improves numerical efficiency, compared with the others well known methods for structural topology optimization in open literatures.

Structural Topology Optimization Using Turing Model

2014 ◽  
Vol 889-890 ◽  
pp. 595-599
Author(s):  
Kaysar Rahman ◽  
Azhar Halik ◽  
Kahar Samsak ◽  
Nurmamat Helil
Keyword(s):  
Topology Optimization ◽  
Bone Remodeling ◽  
Reaction Diffusion ◽  
Optimization Method ◽  
Reaction Diffusion Equations ◽  
Structural Topology Optimization ◽  
Structural Topology ◽  
Hypothetical Model ◽  
Continuum Structures ◽  
Material Formation

In this paper firstly a new hypothetical model of bone remodeling based on bone bioactivity mechanism and Turing reaction-diffusion equations is presented. Secondly this model of bone remodeling is translated to material formation and resorption process of continuum structures, a new heuristic structural topology optimization is presented. Finally short cantilever beam problem, one of the widely used examples in structural topology optimization are carried out by using present method to confirm the validity of the proposed topology optimization method.

A NEW ELEMENT-BASED METHOD FOR SOLVING STRUCTURAL TOPOLOGY OPTIMIZATION PROBLEMS WITH NON-UNIFORM MESHES

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Kuang-Wu Chou ◽  
Chang-Wei Huang
Keyword(s):  
Topology Optimization ◽  
Optimization Problems ◽  
Optimization Method ◽  
Optimal Topology ◽  
Evolutionary Stage ◽  
Structural Topology Optimization ◽  
Volume Constraint ◽  
Structural Topology ◽  
Exchange Method ◽  
Python Scripting

This study proposes a new element-based method to solve structural topology optimization problems with non-uniform meshes. The objective function is to minimize the compliance of a structure, subject to a volume constraint. For a structure of a fixed volume, the method is intended to find a topology that could almost conform to the compliance minimum. The method is refined from the evolutionary switching method, whose policy of exchanging elements is improved by replacing some empirical decisions with ones according to optimization theories. The method has the evolutionary stage and the element exchange stage to conduct topology optimization. The evolutionary stage uses the evolutionary structural optimization method to remove inefficient elements until the volume constraint is satisfied. The element exchange stage performs a procedure refined from the element exchange method. Notably, the procedures of both stages are refined to conduct non-uniform finite element meshes. The proposed method was implemented to use the Abaqus Python scripting interface to call the services of Abaqus such as running analysis and retrieving the output database of an analysis. Numerical examples demonstrate that the proposed optimization method could determine the optimal topology of a structure that is subject to a volume constraint and whose mesh is non-uniform.

Topology Optimization of Rigid-Body Systems Considering Collision Avoidance

2020 ◽  
Vol 142 (8) ◽  
Author(s):  
Fritz Stöckli ◽  
Kristina Shea
Keyword(s):  
Topology Optimization ◽  
Rigid Body ◽  
Collision Avoidance ◽  
Optimization Problems ◽  
Computational Design ◽  
Optimization Method ◽  
The Body ◽  
Graph Grammar ◽  
Automated Synthesis ◽  
Inertia Properties

Abstract Passive dynamic mechanisms can perform simple robotic tasks without requiring actuators and control. In previous research, a computational design method was introduced that integrates dynamic simulation to evaluate and evolve configurations of such mechanisms. It was shown to find multiple solutions of passive dynamic brachiating robots (Stöckli and Shea, 2017, “Automated Synthesis of Passive Dynamic Brachiating Robots Using a Simulation-Driven Graph Grammar Method,” J. Mech. Des. 139(9), p. 092301). However, these solutions are limited, since bodies are modeled only by their inertia properties and thus lack a shape embodiment. This paper presents a method to generate rigid-body topologies based on given inertia properties. The rule-based topology optimization method presented guarantees that the topology is manifold, meaning that it has no disconnected parts, while still connecting all joints that need to be part of the body. Furthermore, collisions with the environment, as well as with other bodies, during their predefined motion trajectories are avoided. A collision matrix enables efficient collision detection as well as the calculation of the swept area of one body in the design space of another body by only one matrix–vector multiplication. The presented collision avoidance method proves to be computationally efficient and can be adopted for other topology optimization problems. The method is shown to solve different tasks, including a reference problem as well as passive dynamic brachiating mechanisms. Combining the presented methods with the simulation-driven method from Stöckli and Shea (2017, “Automated Synthesis of Passive Dynamic Brachiating Robots Using a Simulation-Driven Graph Grammar Method,” J. Mech. Des. 139(9), p. 092301), the computational design-to-fabrication of passive dynamic systems is now possible and solutions are provided as STL files ready to be 3D-printed directly.

scholarly journals Size and Topology Optimization for Trusses with Discrete Design Variables by Improved Firefly Algorithm

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Yue Wu ◽  
Qingpeng Li ◽  
Qingjie Hu ◽  
Andrew Borgart
Keyword(s):  
Topology Optimization ◽  
Firefly Algorithm ◽  
Optimization Problems ◽  
Optimization Method ◽  
Structural Topology ◽  
Discrete Variables ◽  
And Topology ◽  
Design Variables ◽  
Improved Firefly Algorithm ◽  
Discrete Design Variables

Firefly Algorithm (FA, for short) is inspired by the social behavior of fireflies and their phenomenon of bioluminescent communication. Based on the fundamentals of FA, two improved strategies are proposed to conduct size and topology optimization for trusses with discrete design variables. Firstly, development of structural topology optimization method and the basic principle of standard FA are introduced in detail. Then, in order to apply the algorithm to optimization problems with discrete variables, the initial positions of fireflies and the position updating formula are discretized. By embedding the random-weight and enhancing the attractiveness, the performance of this algorithm is improved, and thus an Improved Firefly Algorithm (IFA, for short) is proposed. Furthermore, using size variables which are capable of including topology variables and size and topology optimization for trusses with discrete variables is formulated based on the Ground Structure Approach. The essential techniques of variable elastic modulus technology and geometric construction analysis are applied in the structural analysis process. Subsequently, an optimization method for the size and topological design of trusses based on the IFA is introduced. Finally, two numerical examples are shown to verify the feasibility and efficiency of the proposed method by comparing with different deterministic methods.

Analogy of Strain Energy Density Based Bone-Remodeling Algorithm and Structural Topology Optimization

2008 ◽  
Vol 131 (1) ◽  
Author(s):  
In Gwun Jang ◽  
Il Yong Kim ◽  
Byung Man Kwak
Keyword(s):  
Topology Optimization ◽  
Energy Density ◽  
Bone Remodeling ◽  
Strain Energy Density ◽  
Strain Energy ◽  
Optimization Method ◽  
Bone Adaptation ◽  
Structural Topology Optimization ◽  
Structural Topology ◽  
Topology Optimization Method

In bone-remodeling studies, it is believed that the morphology of bone is affected by its internal mechanical loads. From the 1970s, high computing power enabled quantitative studies in the simulation of bone remodeling or bone adaptation. Among them, Huiskes et al. (1987, “Adaptive Bone Remodeling Theory Applied to Prosthetic Design Analysis,” J. Biomech. Eng., 20, pp. 1135–1150) proposed a strain energy density based approach to bone remodeling and used the apparent density for the characterization of internal bone morphology. The fundamental idea was that bone density would increase when strain (or strain energy density) is higher than a certain value and bone resorption would occur when the strain (or strain energy density) quantities are lower than the threshold. Several advanced algorithms were developed based on these studies in an attempt to more accurately simulate physiological bone-remodeling processes. As another approach, topology optimization originally devised in structural optimization has been also used in the computational simulation of the bone-remodeling process. The topology optimization method systematically and iteratively distributes material in a design domain, determining an optimal structure that minimizes an objective function. In this paper, we compared two seemingly different approaches in different fields—the strain energy density based bone-remodeling algorithm (biomechanical approach) and the compliance based structural topology optimization method (mechanical approach)—in terms of mathematical formulations, numerical difficulties, and behavior of their numerical solutions. Two numerical case studies were conducted to demonstrate their similarity and difference, and then the solution convergences were discussed quantitatively.

scholarly journals An Efficient and High-Resolution Topology Optimization Method Based on Convolutional Neural Networks

2019 ◽  
Author(s):  
Liang Xue ◽  
Jie Liu ◽  
Guilin Wen ◽  
Hongxin Wang
Keyword(s):  
Topology Optimization ◽  
High Resolution ◽  
High Efficiency ◽  
Optimization Problems ◽  
Combined Treatment ◽  
Computational Cost ◽  
Optimization Method ◽  
Element Analysis ◽  
Arbitrary Boundary ◽  
Topology Optimization Method

Topology optimization is a pioneering design method that can provide various candidates with high mechanical properties. However, the high-resolution for the optimum structures is highly desired, normally in turn leading to computationally intractable puzzle, especially for the famous Solid Isotropic Material with Penalization (SIMP) method. In this paper, an efficient and high-resolution topology optimization method is proposed based on the Super-Resolution Convolutional Neural Network (SRCNN) technique in the framework of SIMP. The SRCNN includes four processes, i.e. refining, path extraction & representation, non-linear mapping, and reconstruction. The high computational efficiency is achieved by a pooling strategy, which can balance the number of finite element analysis (FEA) and the output mesh in optimization process. To further reduce the high computational cost of 3D topology optimization problems, a combined treatment method using 2D SRCNN is built as another speeding-up strategy. A number of typical examples justify that the high-resolution topology optimization method adopting SRCNN has excellent applicability and high efficiency for 2D and 3D problems with arbitrary boundary conditions, any design domain shape, and varied load.

Buckling Topology Optimization of Laminated Multi-Material Composite Structures

2006 ◽  
Author(s):  
Erik Lund
Keyword(s):  
Topology Optimization ◽  
Composite Structures ◽  
Optimization Problems ◽  
Combinatorial Problem ◽  
Optimization Method ◽  
Load Factor ◽  
Material Optimization ◽  
Material Stiffness ◽  
Gradient Based ◽  
Material Composite

The design problem of maximizing the buckling load factor of laminated multi-material composite shell structures is investigated using the so-called Discrete Material Optimization (DMO) approach. The design optimization method is based on ideas from multi-phase topology optimization where the material stiffness is computed as a weighted sum of candidate materials, thus making it possible to solve discrete optimization problems using gradient based techniques and mathematical programming. The potential of the DMO method to solve the combinatorial problem of proper choice of material and fiber orientation simultaneously is illustrated for a multilayered plate example and a simplified shell model of a spar cap of a wind turbine blade.

scholarly journals Efficient, high-resolution topology optimization method based on convolutional neural networks

2021 ◽  
Author(s):  
Liang Xue ◽  
Jie Liu ◽  
Guilin Wen ◽  
Hongxin Wang
Keyword(s):  
Topology Optimization ◽  
High Resolution ◽  
High Efficiency ◽  
Optimization Problems ◽  
Combined Treatment ◽  
Computational Cost ◽  
Treatment Method ◽  
Optimization Method ◽  
Arbitrary Boundary ◽  
Topology Optimization Method

AbstractTopology optimization is a pioneer design method that can provide various candidates with high mechanical properties. However, high resolution is desired for optimum structures, but it normally leads to a computationally intractable puzzle, especially for the solid isotropic material with penalization (SIMP) method. In this study, an efficient, high-resolution topology optimization method is developed based on the superresolution convolutional neural network (SRCNN) technique in the framework of SIMP. SRCNN involves four processes, namely, refinement, path extraction and representation, nonlinear mapping, and image reconstruction. High computational efficiency is achieved with a pooling strategy that can balance the number of finite element analyses and the output mesh in the optimization process. A combined treatment method that uses 2D SRCNN is built as another speed-up strategy to reduce the high computational cost and memory requirements for 3D topology optimization problems. Typical examples show that the high-resolution topology optimization method using SRCNN demonstrates excellent applicability and high efficiency when used for 2D and 3D problems with arbitrary boundary conditions, any design domain shape, and varied load.

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