Fatigue-resistance topology optimization of continuum structure by penalizing the cumulative fatigue damage

This paper aims to collect in a structured manner different computer-aided engineering (CAE) tools especially developed for additive manufacturing (AM) that maximize the capabilities of this technology regarding product development. The flexibility of the AM process allows the manufacture of highly complex shapes that are not possible to produce by any other existing technology. This fact enables the use of some existing design tools like topology optimization that has already existed for decades and is used in limited cases, together with other novel developments like lattice design tools. These two technologies or design approaches demand a highly flexible manufacturing system to be applied and could not be used before, due to the conventional industrial process limitations. In this paper, these technologies will be described and combined together with other generic or specific design tools, introducing the study case of an additive manufactured mechanical design of a bicycle stem.

Design for Additive Manufacturing: Tool Review and a Case Study

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

Abstract The aim of this paper is to integrate the reliability-based analysis into topology optimization problems. Consequently, reliability-based topology optimization (RBTO) of geometrically nonlinear elasto-plastic models is presented. For purpose of performing (RBTO), the volume fraction is considered reliable since that the application of (RBTO) gives different topology in comparison to the deterministic topology optimization. The effects of changing the prescribed total structural volume constraint for deterministic designs and changing the reliability index for probabilistic designs are considered. Reliability index works as a constraint which is related to reliability condition added into the volume fraction and it is calculated using the Monte-Carlo simulation approach in the case of probabilistic design. In addition, bi-directional evolutionary structural optimization (BESO) method is utilized to study the effect of geometrically nonlinear elasto-plastic design. The plastic behavior can be controlled by defining a limit on the plastic limit load multipliers. The suggested work's efficiency is demonstrated via a 2D benchmark problem. In case of elastic material, a 2D model of U-shape plate is used for probabilistic design of linear and geometrically nonlinear topology optimizations. Furthermore, a 2D elasto-plastic model is considered for reliability-based design to demonstrate that the suggested approach can determine the best topological solution. 

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Reliability based geometrically nonlinear bi-directional evolutionary structural optimization of elasto-plastic material

This paper presents a computationally efficient multi-resolution topology optimization framework by establishing a novel bi-directional evolutionary structure optimization (BESO) method based on extended finite element method (XFEM). In the proposed framework, the high-resolution designs preserving the topological complexity can be obtained with low degree of freedoms (DOFs). The implementation of the presented multi-resolution optimization framework takes good use of the ability of XFEM at accurately modeling material discontinuities within one element. On the basis of XFEM, a strategy of triangulated partition and a new material interpolation model are introduced to represent the finer material distribution. We employ the coarser finite element (FE) mesh to perform the finite element analysis, the sub-parts partitioned from finite elements to describe material properties and the nodal design variables to perform the optimization. To circumvent artificially stiff patterns, a modified sensitivity filter is applied to regularize the solution. The effectiveness and high efficiency of the presented approach are highlighted by typical 2D and 3D examples.

An efficient evolutionary structural optimization method for multi-resolution designs

A novel minimum weight formulation of topology optimization implemented with reanalysis approach

Topological index sometimes called molecular descriptor is a numerical value which associates a chemical composition for correlating chemical structure with numerous physical properties, chemical reactivity, or biological activity. In this paper, we study some topological indices of boron and try to correlate the physicochemical properties such as freezing points, boiling points, melting points, infrared spectrum, electronic parameters, viscosity, and density of chemical graphs. We discuss these topological indices, and some of them are mentioned here such as Randic index, the first general Zagreb index, the general sum connectivity index, hyper-Zagreb index (HM), the atom-bond connectivity index (ABC), the geometric-arithmetic index (GA), the harmonic index (H), and the forgotten index (F).

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Degree-Based Topological Indices of Boron B12

This article presents a novel formulation for geometric nonlinear topology optimization problems. In practical engineering, maximum deflection is frequently used to quantify the stiffness of contin...

A new geometrically nonlinear topology optimization formulation for controlling maximum displacement

This paper proposes a novel method for the continuum topology optimization of transient vibration problem with maximum dynamic response constraint. An aggregated index in the form of an integral function is presented to cope with the maximum response constraint in the time domain. The density filter solid isotropic material with penalization method combined with threshold projection is developed. The sensitivities of the proposed index with respect to design variables are conducted. To reduce computational cost, the second-order Arnoldi reduction (SOAR) scheme is employed in transient analysis. Influences of aggregate parameter, duration of loading period, interval time, and number of basis vectors in the SOAR scheme on the final designs are discussed through typical examples while unambiguous configuration can be achieved. Through comparison with the corresponding static response from the final designs, the optimized results clearly demonstrate that the transient effects cannot be ignored in structural topology optimization.

Topology optimization of transient problem with maximum dynamic response constraint using SOAR scheme

Scientists and researchers are focusing on generation electrical energy using maximum share of renewable energy resources. Wind turbines possess crucial part in generation of electrical energy from renewable energy sources. A lot of research work has been carried out to find out optimum mechanical design of wind turbines specially focused on reduction in weight of turbine blades. This research work presents an extensive review for existing topology optimization techniques specially used for wind turbine blades. At first an indepth review for solid isotropic material with penalization (SIMP) techniques including optimal criteria and filter sensitivity has been presented. After that a comparative analysis focusing advantages and disadvantages of latest optimization techniques that evolutionary structural optimization (ESO) and bidirectional evolutionary structural optimization (BESO) is presented.

Nouman Saeed

Papers

A novel minimum weight formulation of topology optimization implemented with reanalysis approach

Degree-Based Topological Indices of Boron B12

A new geometrically nonlinear topology optimization formulation for controlling maximum displacement

Topology optimization of transient problem with maximum dynamic response constraint using SOAR scheme

A Review of Structural Optimization Techniques for Wind Turbines