多轴载荷下螺纹紧固件载荷-位移行为和失效预测的校正策略和建模方法

J. Mersch, Jeffrey A. Smith, G. Orient, Peter W. Grimmer, J. Gearhart
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引用次数: 0

摘要

在多轴数据集上使用多个紧固件降阶模型和拟合策略,并使用高保真度分析模型进一步评估这些模型,以证明这些策略如何很好地预测载荷-位移行为和失效。对桥塞和点焊这两种常见的降阶建模方法进行了校准、评估,并与更密集的方法(针对多个数据集校准的“两块”桥塞)进行了比较。利用遗传算法对一组准静态测试数据进行优化分析,其中紧固件以15°增量从0°到90°的角度拉伸,以获得最能捕获所选数据集的载荷-位移行为的紧固件模型的材料参数。单块桥塞仅根据张力数据进行校准,点焊根据张力(0°)和剪切(90°)进行校准,双块桥塞根据所有可用数据(0°-90°)进行校准。通过将这些模型和建模方法合并到测试设置的高保真分析模型中,并将负载-位移预测与原始测试数据进行比较,进一步评估这些校准。
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Calibration Strategies and Modeling Approaches for Predicting Load-Displacement Behavior and Failure for Multiaxial Loadings in Threaded Fasteners
Multiple fastener reduced-order models and fitting strategies are used on a multiaxial dataset and these models are further evaluated using a high-fidelity analysis model to demonstrate how well these strategies predict load-displacement behavior and failure. Two common reduced-order modeling approaches, the plug and spot weld, are calibrated, assessed, and compared to a more intensive approach — a “two-block” plug calibrated to multiple datasets. An optimization analysis workflow leveraging a genetic algorithm was exercised on a set of quasistatic test data where fasteners were pulled at angles from 0° to 90° in 15° increments to obtain material parameters for a fastener model that best capture the load-displacement behavior of the chosen datasets. The one-block plug is calibrated just to the tension data, the spot weld is calibrated to the tension (0°) and shear (90°), and the two-block plug is calibrated to all data available (0°–90°). These calibrations are further assessed by incorporating these models and modeling approaches into a high-fidelity analysis model of the test setup and comparing the load-displacement predictions to the raw test data.
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