# Collaborative Optimization of Aerodynamics and Wind Turbine Blades
## 1 Introduction
To optimize the aerodynamic shape of blades, [PERSON] et al. [20] focused on the wind turbine blade tip and proposed a surrogate-based optimization scheme to maximize energy production. Combining the lifting surface method with a free-wake model, [PERSON] et al. [21] applied a microgenetic algorithm to optimize the blade chord length and twist angle. Combined with a blade element momentum method, [PERSON] and [PERSON] [22] presented a gradient-based optimization framework for blade profiles to minimize power production losses due to icing. Targeting the maximization of the axial moment, [PERSON] et al. [23] applied the continuous adjoint method to the aerodynamic shape optimization of wind turbine rotor blades. Aiming at diminishing the curse of dimensionality in the design of blade shapes, [PERSON] et al. [24] proposed a deep learning-based optimization of the aerodynamic shape of wind turbine blades. For the structural optimization of wind turbine blades, the materials and lay-up design are of interest. [PERSON] et al. [25] investigated the composite fiber angles throughout the internal structure of the blade and used gradient-based optimization to minimize a scalar stress parameter that correlates with the accumulation of fatigue damage. Regarding the blade chord, twist, layer number, layer location of the spar cap, and the position of the shear web as variables, [PERSON] and [PERSON] [26] investigated the strength, stiffness, and stability of an optimized model of wind turbine blades using an evolutionary algorithm. [PERSON] et al. [27] developed a procedure combining finite element analysis and the particle swarm algorithm to optimize composite structures of the wind turbine blades, which not only allows thickness variation but also permits variation in spar cap location over the structure. [PERSON] and [PERSON] [28] proposed a generic structural optimization procedure for the 2 MW composite wind turbine blade in which the layout thickness of the root is considered. Combined with the finite element method, [PERSON] et al. [29] presented the optimal blade structural configuration in which the skin thickness, thickness, and width of the spar flange, and thickness, location, and length of the front and rear spar web are considered. [PERSON] and [PERSON] [30] addressed a genetic algorithm (GA)-based two-stage design optimization procedure in which the ply lay-up pattern of the spar cap and cross-sectional design optimization at several spanwise locations are investigated. [PERSON] and [PERSON] [31] proposed a GA-based neural network to optimize the ply angle, ply thickness ratio, and ply stacking sequence of the blade and increase the static strength and stiffness of the blade. [PERSON] et al. [32] presented a multi-objective structural optimization framework for a composite wind turbine blade, in which the blade mass, the maximum blade tip displacement, the natural frequencies of vibration, and the critical load factor are considered. Traditionally, the strategy of series design is employed in the process of design of wind turbine blades. At each stage of the design, a single design domain is considered while all other domains are ignored. For instance, the aerodynamics domain is only concerned with obtaining the optimal lines of the blade. Afterward, structure performance is analyzed based on the obtained lines. If the demands of structure performance are not satisfied, the blade lines need to be re-designed. Such a design methodology results in low efficiency and the loss of an overall optimal solution. In fact, in the optimization design of blades, there are coupling relationships between different domains, referring to the design variables, optimization objectives, and constraints. To achieve the best overall performance of a wind turbine blade, both aerodynamic and structural requirements are considered by researchers. For example, [PERSON] et al. [33] presented an aerodynamic/aero-elastic model that includes the structural dynamics of the blades and blade element momentum (BEM) theory.