We propose a new deterministic robust design optimization method for composite laminate structures under worst-case material uncertainty. The method is based on a simultaneous parametrization of topology and material and combines a design problem and a material uncertainty problem into a single min–max optimization problem which provides an efficient approach to handle variation of material properties in stiffness driven design optimization problems. An analysis is performed using a design problem based on a failure criterion formulation to evaluate the ability of the proposed method to generate robust composite designs. The design problem is solved using various loads, boundary conditions and manufacturing constraints. The designs generated with the proposed method have improved objective responses compared to the worst-case response of designs generated with nominal material properties and are less sensitive to the variation of material properties. The analysis indicates that the proposed method can be efficiently applied in a robust structural optimization framework. © 2023 The Author(s)

We propose a method to analyze effects of material uncertainty in composite laminate structures optimized using a simultaneous topology and material optimization approach. The method is based on computing worst -case values for the material properties and provides an efficient way of handling variation in material properties of composites for stiffness driven optimization problems. An analysis is performed to evaluate the impact of material uncertainty on designs from two design problems: Maximization of stiffness and minimization of a failure criteria index, respectively. The design problems are solved using different loads, boundary conditions and manufacturing constraints. The analysis indicates that the influence of material uncertainty is dependent on the type of optimization problem. For compliance problems the impact on the objective value is proportional to the changes of the constitutive properties and the effect of material uncertainty is consistent and predictable for the generated designs. The strength-based problem shows that material uncertainty has a significant impact on the response, and the effects of material uncertainty is not consistent and changes for different design requirements. In addition, the results show an increase of up to 25% of the maximum failure index when considering the worst-case deviation of the constitutive properties from their nominal values.

This paper presents a new discrete parametrization method for simultaneous topology and material optimization of composite laminate structures, referred to as Hyperbolic Function Parametrization (HFP). The novelty of HFP is the way the candidate materials are parametrized in the optimization problem. In HFP, a filtering technique based on hyperbolic functions is used, such that only one design variable is used for any given number of material candidates. Compared to state-of-the-art methods such Discrete Material and Topology Optimization (DMTO) and Shape Function with Penalization (SFP), HFP has much fewer optimization variables and constraints but introduces additional non-linearity in the optimization problems. A comparative analysis of HFP, DMTO and SFP are performed based on the problem of maximizing the stiffness of composite plates under a total volume constraint and multiple manufacturing constraints using various loads, boundary conditions and input parameters. The comparison shows that all three methods are highly sensitive to the choice of input parameters for the optimization problem, although the performance of HFP is overall more consistent. HFP method performs similarly to DMTO and SFP in terms of the designs obtained and computational cost. However, HFP obtains similar or better objective function values compared to the DMTO and SFP methods.

The increasing use of bre-reinforced composite materials in the manufacturing of high performance structures is primarily driven by their superior strength-toweight ratio when compared to traditional metallic alloys. This provides the ability to design and manufacture lighter structures with improved mechanical properties. However, the specic manufacturing process of composite structures, along with the orthotropic material properties exhibited by bre-reinforced composite materials, result in a complex structural design process where a number of dierent design parameters and manufacturing issues, which aect the mechanical properties of the composite structure, have to be considered. An ecient way to do this is to implement structural optimization techniques in the structural design process thus improving the ability of the design process to nd design solutions which satisfy the structural requirements imposed on the composite structure.

This thesis describes a two phase composite structure optimization method based on a novel material homogenization approach. The proposed method consists of a stiness optimization problem and a lay-up optimization problem, respectively, with the aim to obtain a manufacturable composite structure with maximized stiness properties. The homogenization material approach is applied in both optimization problems, such that the material properties of the composite structure are homogenized. In the proposed method the stiness optimization problem provides a composite structure with maximized stiness properties by nding the optimal distribution of composite material across the design domain. The aim of the lay-up optimization problem is to obtain a manufacturable lay-up sequence of bre-reinforced composite plies for the composite structure which, as far as possible, retains the stiness properties given by the stiness optimization problem. The ability of the composite structure optimization method to obtain manufacturable composite structures is tested and conrmed by a number of numerical tests.

The homogenized material optimization (HMO) problem is a novel structural optimization problem that we have developed for optimization of fiber reinforced composite structures. In the HMO problem we apply a smeared-out approach to model the material properties of fiber reinforced composite materials. The objective of the HMO problem is to maximize the stiffness of a composite structure by means of finding the optimal distribution of composite material, belonging to a fixed set of fiber orientations, across the design domain. In order to obtain manufacturable solutions, we have introduced a linear density filter as a restriction method to control the thickness variation across the design domain. To examine the effect of the density filter on the thickness variation and the objective function value of composite structures, obtained in the HMO problem, we have performed numerical tests for different load cases, mesh densities and range of the filter radius.

It is observed that for the present problem the thickness variation was mesh-independent. Both the thickness variation and objective function value depend on the load case used in the HMO problem. For all load cases the thickness variations exhibits an approximately piece-wise linear behaviour for increased filter radius. Furthermore, it was observed that an increase of filter radius would result in an moderate increase in objective function value for the solutions obtained from the HMO problem. From these results we conclude that by using a density filter, the HMO problem can be used to obtain manufacturable designs for composite structures.

In the present work we propose a two phase composite structure optimization method based on a novel material homogenization approach. It consists of a stiffness and a lay-up optimization problem, respectively, with the aim of obtaining manufacturable composite structures with maximized stiffness properties. The method is applied to a cantilever plate, and numerical tests were performed for three load cases and for a number of parameters settings. The results show that the proposed method can obtain manufacturable composite structures with maximized stiffness properties. In the first phase of the method, the stiffness optimization problem provides an optimal distribution of the composite material, such that the stiffness properties of the structureare maximized. The second phase, the lay-up optimization problem, provides a manufacturable lay-up sequence of discrete plies which attempts to retain the stiffness properties of the structure from the first phase.