Metal-polymer hybrid (MPH) structures, featuring a micro-structure interlocking design, combine the high strength of metal with the exceptional formability of polymer-based composites and have gained significant attention in automotive load-bearing components. Challenges persist in accurately predicting MPH structure fatigue life using small samples with diverse interlock parameters and swiftly generating static strength and fatigue life response surfaces for automated optimization. We introduce a simplified model for predicting fatigue at the interfaces of MPH structures. Our multi-fidelity prediction method integrates this model with limited high-fidelity data samples to assess both the static strength and fatigue life effectively. This method predicts the deviation with less than 3% error compared to FSR-FEM, achieving a reduction in prediction time of over 60%. Additionally, we elucidate the non-synergistic mechanisms of key interfacial locking parameters between static strength and fatigue life at the micro-scale. Finally, we propose and apply a multi-objective synergistic optimization strategy to the MPH thrust rods in vehicles. By utilizing our optimization method, we achieve a 27.9% weight reduction compared to steel counterparts, while enhancing overall tensile strength by 11.8% and significantly improving fatigue life by 46.7% compared to MPH torque rods lacking an interlock interface.

中文翻译：

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一种高效/准确的金属聚合物混合（MPH）界面多尺度疲劳预测方法

金属-聚合物杂化（MPH）结构具有微结构互锁设计，将金属的高强度与聚合物基复合材料的卓越成型性相结合，在汽车承载部件中获得了广泛关注。使用具有不同互锁参数的小样本准确预测 MPH 结构疲劳寿命并快速生成静态强度和疲劳寿命响应面以进行自动优化仍然存在挑战。我们引入了一个用于预测 MPH 结构界面疲劳的简化模型。我们的多保真度预测方法将该模型与有限的高保真数据样本相结合，以有效地评估静态强度和疲劳寿命。与 FSR-FEM 相比，该方法预测偏差的误差小于 3%，预测时间缩短了 60% 以上。此外，我们还阐明了微观尺度上静态强度和疲劳寿命之间关键界面锁定参数的非协同机制。最后，我们提出并将多目标协同优化策略应用于车辆中的 MPH 推杆。通过利用我们的优化方法，与钢制同类产品相比，我们实现了 27.9% 的重量减轻，同时与缺乏互锁接口的 MPH 扭矩杆相比，整体拉伸强度提高了 11.8%，疲劳寿命显着提高了 46.7%。