This article systematically studies the optimization of mechanical structures from the perspectives of theory, trends, and practice. In theory, it is clear that the core is to adjust the parameter balance performance and cost under a given constraint, and to sort out the principles, advantages, disadvantages, and scene adaptability of traditional methods (full stress method, mathematical programming method), modern intelligent algorithms (genetic algorithm, particle swarm optimization algorithm), and multidisciplinary optimization methods. On the trend, four directions are pointed out: artificial intelligence and machine learning driven optimization, multi physics coupling precise optimization, intelligent manufacturing fusion optimization, and sustainable green optimization. In practice, combining cases of aerospace (aircraft wings, satellite brackets), automotive manufacturing (vehicle lightweighting, engine cylinder blocks), and energy equipment (wind turbine blades, nuclear power plant pressure vessels), the effectiveness of optimization in weight reduction, quality improvement, cost reduction, and efficiency improvement is verified. At the same time, modeling difficulties, design manufacturing disconnect, and other issues are analyzed and corresponding strategies are proposed. Research has shown that mechanical structure optimization is a key path for upgrading mechanical engineering technology and can provide support for engineering practice.

Yuxian Xu. Exploring the Optimization of Mechanical Structures: Theory, Trends, and Practice. International Journal of Frontiers in Engineering Technology (2025), Vol. 7, Issue 4: 17-24. https://doi.org/10.25236/IJFET.2025.070403.

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