A Review of Microstructure Control and Mechanical Performance Optimization of γ-TiAl Alloys

Effect of printing direction and thickness on the mechanical behaviour of SLM fabricated Hastelloy-X

Multiscale plasticity behavior and fatigue performance of laser melting multi-layer nickel-based superalloys upon heat treatments

In some specific conditions, UAVs are required to obtain comprehensive information of an area or to operate in the area in an all-round way. In this case, the coverage path planning (CPP) is required. This paper proposes a solution to solve the problem of short endurance time in the coverage path planning (CPP) problem of multi-solar unmanned aerial vehicles (UAVs). Firstly, the energy flow efficiency based on the energy model is proposed to evaluate the energy utilization efficiency during the operation. Moreover, for the areas with and without obstacles, the coverage path optimization model is proposed based on the undirected graph search method. The constraint equation is defined to restrict the UAV from accessing the undirected graph according to certain rules. A mixed integer linear programming (MILP) model is proposed to determine the flight path of each UAV with the objective of minimizing operation time. Through the simulation experiment, compared with the Boustrophedon Cellular Decomposition method for coverage path planning, it is seen that the completion time is greatly improved. In addition, considering the impact of the attitude angle of the solar powered UAV when turning, the operation time and the total energy flow efficiency are defined as the optimization objective. The bi-objective model equation is established to solve the problem of the CPP. A large number of simulation experiments show that the optimization model in this paper selects different optimization objectives and applies to different shapes of areas to be covered, which has wide applicability and strong feasibility.

https://www.mdpi.com/2504-446X/6/8/203/pdf?version=1660989955

Coverage Path Planning Based on the Optimization Strategy of Multiple Solar Powered Unmanned Aerial Vehicles

The effects of different heat treatments on the microstructure and mechanical properties of the laser melting nickel-based superalloys were systematically investigated. The strength improvement of the heat-treated material was mainly derived from the aging treatment, which converted the γ matrix together with Niobium to the strengthening phases γ′′ and γ′. The solution treatment dissolved partial Laves phases to form the short-acicular δ phases in the remelting zone (RZ), whereas the homogenization treatment dissolved most precipitates including the Laves phase and δ phase, leading to significant grain coarsening in the multi-layer material. Moreover, based on the instrumented indentation reverse analysis, RZ shows consistent stress–strain relationships after the heat treatments, reaching the same level as the heat-treated base material (BM). The remelting-affected zone (RAZ) reveals more outstanding mechanical properties after the direct aging (DA) treatment for the work hardening contributed by dislocation strengthening. Additionally, the residual stresses and deformations in RAZ provide an extra thermodynamic driving force for the grain recrystallization and the formation of the short-clavate δ phase in the solution-treated RAZ. The remaining large grains and small Taylor factor in RZ are considered to lead to a reduction of the mesoscopic yield strength, which cannot be identified in microscopic indentation analysis. The DA heat treatment is recommended for the strength improvement of the laser melting materials. 

Effects of heat treatments on microstructure and mechanical properties of laser melting multi-layer materials

A comprehensive study of the anisotropic tensile properties of laser additive manufactured Ni-based superalloy after heat treatment

When performing area coverage tasks in some special scenarios, fixed-wing aircraft conventionally adopt the scan-type of path planning, where the distance between two adjacent tracks is usually less than the minimum turning radius of the aircraft. This results in increased energy consumption during turning between adjacent tracks, which means a reduced task execution efficiency. To address this problem, the current paper proposes an area coverage path planning method for a fixed-wing unmanned aerial vehicle (UAV) based on an improved genetic algorithm. The algorithm improves the primary population generation of the traditional genetic algorithm, with the help of better crossover operator and mutation operator for the genetic operation. More specifically, the good point set algorithm (GPSA) is first used to generate a primary population that has a more uniform distribution than that of the random algorithm. Then, the heuristic crossover operator and the random interval inverse mutation operator are employed to reduce the risk of local optimization. The proposed algorithm is verified in tasks with different numbers of paths. A comparison with the conventional genetic algorithm (GA) shows that our algorithm can converge to a better solution.

/pdf/global-optimization-of-uav-area-coverage-path-planning-based-4flmhbsh.pdf

Yeda Lian

Papers

A comprehensive study of the anisotropic tensile properties of laser additive manufactured Ni-based superalloy after heat treatment

Global Optimization of UAV Area Coverage Path Planning Based on Good Point Set and Genetic Algorithm

Vibration fatigue behavior and life prediction of directionally solidified superalloy based on the phase transformation theory

Vibration test method of aero-engine 3D printing pre-swirl nozzle based on equivalent installation stiffness

Random vibration fatigue behavior of directionally solidified superalloy: Experiments and evaluation of life prediction methods