A novel approach to the calculation and optimization methodology of repairable elements of unmanned aerial vehicle (UAV) structures using pre-cured composite patches is proposed. These patches are glued to the damaged structure with adhesives filled with short fibers or particulate fillers. Compared with conventional repair procedures (in which composite prepregs or wet lay-up are used), the suggested method allows damaged UAV structures to be repaired relatively quickly in field conditions without the need for a vacuum or special equipment. In most scientific studies on this problem, significant attention is devoted to the investigation of rectangular patches used for reinforcing plates that have defects such as cracks and damage. This study focuses on the potential application of circular patches for reinforcing plates with defects or damage and includes further parametric optimization of the geometric parameters of the patch. A fundamental approach to the topological and structural optimization of adhesive bonding, along with an experimental study of adhesive properties, has been combined into a single model. This model includes the optimization of the shape and structure of patches for bonded repair, allowing for changes in adhesive thickness to restore the load-carrying capacity of the structure. The simulation and analysis of the results of the renovation of damaged structures for double-sided and single-sided repaired elements of the UAV structure were performed.

The subject of this study is a topological optimization algorithm for a lapped symmetric adhesive joint. The purpose of this research is to create a hybrid optimization algorithm that combines the advantages of a genetic algorithm and a particle swarm algorithm and, at the same time, reduces the time required to solve the problem. Task: to create a methodology for solving the optimization problem for a symmetric double-sided lapped adhesive joint, which consists of a main plate and two patches (the main plate has a constant thickness, and the thickness of the patches varies along the length of the joint, this is required to reduce the stress concentration in the joint and reduce its weight) with satisfaction of the optimality criterion, namely, to minimize the mass of the structure with the strength and thickness restrictions for the patch. The optimization problem is that we must find the optimal patch form, namely, the length of the patch and the thickness-on-length dependence for the patch. Methods: the modified Goland-Reissner model was used to describe the deflected mode of the joint. The finite difference method was used to solve the direct stress state problem for the structure. For the numerical solution of the optimization problem, a combination of the multi-population model of the genetic optimization algorithm and the particle swarm algorithm was used. To improve the performance of the genetic algorithm, a multi-population model with migration of the best individuals between populations was applied. The introduction of individuals from other populations into the population avoids homogenization of the genotype in a separate population and premature stopping of the optimization process. To describe the shape of the patch, the Fourier series expansion of the patch thickness dependence was used. Results: A hybrid algorithm is proposed based on the sequential application of a genetic algorithm and a particle swarm algorithm for three populations of solutions. The particle swarm algorithm makes it possible to improve the value of the objective function achieved at the previous stage by 20%. Conclusions: the scientific novelty lies in the improvement of the optimization algorithm compared with the known ones. To reduce the calculation time, a one-dimensional adhesive joint stress state mathematical model was used in this paper. The methods used made it possible to create a combined topological optimization algorithm that combines the advantages of both methods and allows us to find a solution to the problem quite quickly. The Python program run time is only a few minutes.

A method for selecting mechanical properties and geometry of reinforcing overlays to increase the strength of composite structural elements with holes has been developed. The method is based on the developed algorithm for calculating stress concentration near holes reinforced with inserted rings or glued composite reinforcing overlays. The determination of stresses near holes and overlays is reduced to solving a system of singular integral equations. The kernels of these equations are constructed using Green’s solution, which allows a reduction in the number of equations to four. It is shown that the stress concentration near holes can be significantly reduced by optimizing the thickness, elastic properties, and shape of the overlays. The stress calculations performed based on the three-dimensional theory of elasticity confirmed the reliability of the results obtained within the framework of the plane problem of an anisotropic body. The results obtained, in accordance with the concept of sustainable development, enable the develop simple methods for increasing reliability, reducing material consumption, and reducing the manufacturing and operating costs of composite structures in the aerospace and mechanical engineering industries.

This paper investigates approaches to improving the energy efficiency of the manufacturing process of thermosetting polymer composites through optimization of curing parameters. It is shown that the isothermal dwell stage is the longest and most energy-intensive phase of the technological cycle, while curing schedules commonly used in industrial practice and often based on averaged datasheet properties of the resin are not always rational when the part geometry, composite lay-up structure, and heat transfer conditions are taken into account.Within the study, two principal approaches to determining optimal technological parameters are analysed: the experimental approach and the online method. The experimental approach involves selecting curing schedules based on a series of tests for a specific structure, which ensures compliance with the required material properties but is associated with significant time and energy costs. The online method is based on continuous monitoring of parameters characterising the degree of completion of chemical reactions in the resin and enables adaptive adjustment of temperature–time profiles during the forming process without the need for additional experiments.To analyse the curing process, well-established physical and mathematical models of heat transfer and polymerisation kinetics are employed, allowing prediction of the spatial–temporal distributions of temperature and degree of cure within the composite laminate. Particular attention is paid to the investigation of the stress–strain state formed as a result of the combined effects of thermal, shrinkage, and relaxation processes. It is demonstrated that the level of residual stresses can be reduced by ensuring a uniform temperature field, applying double-sided heating, optimising tooling design, and exploiting the relaxation properties of the material.As a result of curing schedule optimisation for a given composite laminate configuration, the duration of the isothermal dwell was reduced by a factor of 1.7, leading to a decrease in energy consumption of the forming process from 40 to 23 kWh without deterioration of processing conditions or product quality. The obtained results are methodological in nature and can be applied in the development of energy-efficient manufacturing technologies for polymer composite structures and in the creation of computer-integrated process control systems.