Geimer Paul R, Ulrich T J, Beardslee Luke B, Hayne Mathew L, Remillieux Marcel C, Saleh Tarik A, Freibert Franz J
Detonation Science and Technology Group, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA.
Geophysics Group, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA.
J Acoust Soc Am. 2022 Jun;151(6):3633. doi: 10.1121/10.0011516.
Understanding the elastic properties of materials is critical for their safe incorporation and predictable performance. Current methods of bulk elastic characterization often have notable limitations for in situ structural applications, with usage restricted to simple geometries and material distributions. To address these existing issues, this study sought to expand the capabilities of resonant ultrasound spectroscopy (RUS), an established nondestructive evaluation method, to include the characterization of isotropic multi-material samples. In this work, finite-element-based RUS analysis consisted of numerical simulations and experimental testing of composite samples comprised of material pairs with varying elasticity and density contrasts. Utilizing genetic algorithm inversion and mode matching, our results demonstrate that elastic properties of multi-material samples can be reliably identified within several percent of known or nominal values using a minimum number of identified resonance modes, given sample mass is held consistent. The accurate recovery of material properties for composite samples of varying material similarity and geometry expands the pool of viable samples for RUS and advances the method towards in situ inspection and evaluation.
了解材料的弹性特性对于其安全应用和可预测性能至关重要。目前的体弹性表征方法在原位结构应用中往往存在显著局限性，其使用仅限于简单的几何形状和材料分布。为了解决这些现有问题，本研究试图扩展共振超声光谱法（RUS）的能力，这是一种既定的无损评估方法，以包括对各向同性多材料样品的表征。在这项工作中，基于有限元的RUS分析包括对由具有不同弹性和密度对比的材料对组成的复合样品进行数值模拟和实验测试。利用遗传算法反演和模式匹配，我们的结果表明，在样品质量保持一致的情况下，使用最少数量的识别共振模式，多材料样品的弹性特性可以在已知或标称值的百分之几范围内可靠识别。对于不同材料相似性和几何形状的复合样品，材料特性的准确恢复扩大了RUS可行样品的范围，并推动该方法朝着原位检测和评估发展。
