Topology optimization for 3D microstructures of viscoelastic composite materials

Materials with high stiffness and good vibration damping properties are of great industrial interest. In this paper, a topology optimization algorithm based on the BESO method is applied to design viscoelastic composite material by adjusting its 3D microstructures. The viscoelastic composite material is assumed to be composed of a non-viscoelastic material with high stiffness and a viscoelastic material with good vibration damping. The 3D microstructures of the composite are uniformly represented by corresponding periodic unit cells (PUCs). The effective properties of the 3D PUC are extracted by the homogenization theory. The optimized properties of the composites and the optimal microscopic layout of the two materials phases under the conditions of maximum stiffness and maximum damping are given by several numerical examples.

Evolutionary Topology Optimization of Spatial Steel-Concrete Structures

Topology optimization techniques based on finite element analysis have been widely used in many fields, but most of the research and applications are based on single-material structures. Extended from the bi-directional evolutionary structural optimization (BESO) method, a new topology optimization technique for 3D structures made of multiple materials is presented in this paper. According to the sum of each element's principal stresses in the design domain, a material more suitable for this element would be assigned. Numerical examples of a steel- concrete cantilever, two different bridges and four floor systems are provided to demonstrate the effectiveness and practical value of the proposed method for the conceptual design of composite structures made of steel and concrete.

A Hole Nucleation Method Combining BESO and Topological Sensitivity for Level Set Topology Optimization

As is known to all, the incapacity to nucleate holes automatically in the design domain is one of the main issues of the classical level set topology optimization method. To solve the issue of hole nucleation, this paper employs the bi-directional evolutionary structural optimization (BESO) method based on the material removal scheme and the frequently used topological sensitivity and proposes the combining BESO and topological sensitivity (CBT) method for level set topology optimization. This method can replace the existing hole nucleation method for level set topology optimization. First, the topological sensitivity is combined with BESO, and the BESO method based on topological sensitivity is proposed. Second, the method is integrated into level set topology optimization to solve the issue of hole nucleation. Two sensitivity thresholds are defined depending on the evolutionary volume ratio and boundary topological sensitivity, respectively, and the smaller one is used as the sensitivity threshold for hole nucleation. The material is removed from the design domain to nucleate holes based on this threshold. Three classical two-dimensional numerical examples are used to validate the proposed hole nucleation method.

Multi-level objective optimization method for high rise frame shear wall structure

<p>Automatic optimum design is the future development trend of structural design. The main purpose of this study is to propose an automatic optimum design method for building structures. Based on the Bidirectional Evolutionary Structural Optimization(BESO) method, this paper introduces the concept of multi-level objective, and proposes Multi-level objective Optimization Method(MLOOM). By reducing the constraint redundancy of structural members, this method can reduce the structural cost as much as possible and allocate the structural materials reasonably. MLOOM is close to the practical engineering experience, and improves the efficiency and effect of optimization based traditional algorithm. Taking two story and ten story steel frame shear wall structure as examples, the efficiency and economy of the optimization method are illustrated.</p>