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首页> 外文期刊>Journal of orthopaedic research >Multiobjective optimization of tibial locking screw design using a genetic algorithm: Evaluation of mechanical performance.
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Multiobjective optimization of tibial locking screw design using a genetic algorithm: Evaluation of mechanical performance.

机译:使用遗传算法对胫骨锁定螺钉设计进行多目标优化:机械性能评估。

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Breakage or loosening of locking screws may impair fracture fixation or bone healing in locked nailing of tibial fractures. Bending strength and bone holding power, two important design objectives of locking screws, may conflict with each other. The present study used multiobjective optimization with a genetic algorithm to investigate the optimal designs with respect to these two objectives. Three-dimensional finite element models for analyzing bending strength and bone holding power of locking screws were created first. Through use of a Taguchi L25 orthogonal array, two objective functions were developed by least-squares regression analyses. Then, the trade-off solutions between the two objectives known as Pareto optima were explored by a weighted-sum aggregating approach under geometric constraints. The objective functions, reliably reflecting the finite element results, were valid for multiobjective studies. The Pareto fronts of the screws with 4.5-mm and 5.0-mm outer diameters were similar. The "knee" region of the Pareto front, characterized by the fact that a small improvement in either objective will cause a large deterioration in the other objective, might be the favored choice of optimal designs. The commercially available locking screws compared with the Pareto optima were found to be dominated designs and could be improved. In conclusion, the multiobjective optimization with a genetic algorithm was useful for optimization of locking screw design with many variables and conflicting objectives. Choosing an optimal design requires a thorough knowledge of the inherent problems. This method could reduce the time, cost, and labor associated with the screw development process.
机译:锁定螺钉的断裂或松动可能会损害胫骨骨折的锁定钉内的骨折固定或骨愈合。弯曲强度和骨骼保持力是锁定螺钉的两个重要设计目标,可能会相互冲突。本研究使用带有遗传算法的多目标优化来研究关于这两个目标的最优设计。首先创建三维有限元模型,用于分析锁紧螺钉的抗弯强度和骨保持力。通过使用Taguchi L25正交阵列,通过最小二乘回归分析开发了两个目标函数。然后,在几何约束下,通过加权和求和方法探索了两个目标之间的折衷解,即帕累托最优。可靠地反映有限元结果的目标函数对于多目标研究有效。外径为4.5毫米和5.0毫米的螺钉的帕累托锋面相似。帕累托阵线的“膝盖”区域的特点是,一个目标的微小改进会导致另一个目标的较大退化,这可能是最佳设计的首选。与帕累托最优相比,商用锁紧螺钉被认为是主导设计,可以改进。总之,采用遗传算法进行的多目标优化可用于优化具有多个变量和冲突目标的锁螺丝设计。选择最佳设计需要对固有问题有透彻的了解。这种方法可以减少与螺钉开发过程相关的时间,成本和人工。

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