Collaborative Research: Particle Reinforced Ice as a Tunable Acoustic Couplant

合作研究：粒子强化冰作为可调声耦合剂

• 批准号: 2029142
• 负责人: Andrea Arguelles
• 金额: $ 34.87万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2029142&HistoricalAwards=false
• 关键词: Collaborative; Research; Particle; Reinforced; Ice

The prosperity of the US manufacturing industry is dependent upon the ability to remain at the forefront of new material technologies and manufacturing processes. In this context, 3-D printing of metallic components has emerged as a game changer in many industries where the potential to build geometrically complex components promises to increase the performance and life-cycle sustainability of high value products. However, utilization of these components in safety-critical applications is hindered by the lack of suitable methods to detect manufacturing defects or subsequent damage that develops while a component is in service. If left undetected, these defects can lead to catastrophic failures and result in great financial losses or even loss of life. This study seeks to bridge this gap by expanding the range of applicability of ultrasonic testing, a widely used method for the noninvasive inspection of simple shape components. The goal is to introduce a new material specifically designed to couple ultrasonic signals with the bulk of geometrically complex components. The material will be a new form of ice loaded with solid particles to yield tunable rigidity and mass density which are critical for the effectiveness of ultrasonic testing. This project will develop educational modules for three different courses at Penn State and the University of Cincinnati and train graduate and undergraduate students supported by the project.This project will advance the progress of science by creating novel models of wave propagation in particle composites that enable the design of these tunable coupling solids (i.e., reinforced ice). This study will investigate the effects of microstructural modifications in ice composites on wave propagation and scattering through experimentally validated multiscale models. The project will create a new mathematical framework to model wave propagation in particle reinforced composites that lies at the convergence of physics-based analytical approaches and numerical unit cell methods. By merging analytical and data-driven strategies, this work will uncover innovative multiscale approaches to the study of wave propagation in media with complex microstructures. Understanding the impact of particle addition on the dynamic response of ice will enable the analysis of wave propagation in generalized particle composite structures, which will extend far beyond the described application. The increased efficiency in the joint numerical and analytical approach combined with the proposed optimization algorithms will fundamentally change the fields of elastodynamic modeling and ultrasonic nondestructive evaluation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

美国制造业的繁荣取决于保持在新材料技术和制造工艺前沿的能力。在这种情况下，金属部件的3D打印已经成为许多行业的游戏规则改变者，在这些行业中，构建几何复杂部件的潜力有望提高高价值产品的性能和生命周期可持续性。然而，由于缺乏合适的方法来检测制造缺陷或在部件使用时产生的后续损坏，这些部件在安全关键应用中的利用受到阻碍。如果不加以检测，这些缺陷可能导致灾难性的故障，并导致巨大的经济损失甚至生命损失。本研究旨在通过扩大超声波检测的适用范围来弥合这一差距，超声波检测是一种广泛使用的简单形状部件的非侵入性检测方法。我们的目标是引入一种专门设计用于将超声信号与大量几何复杂部件耦合的新材料。该材料将是一种新形式的冰，载有固体颗粒，以产生可调的刚度和质量密度，这对超声波检测的有效性至关重要。该项目将为宾夕法尼亚州立大学和辛辛那提大学的三门不同课程开发教育模块，并培训由该项目支持的研究生和本科生。该项目将通过创建粒子复合材料中波传播的新模型来推动科学进步，从而能够设计这些可调耦合固体（即，强化冰）。本研究将通过实验验证的多尺度模型研究冰复合材料中微结构修改对波传播和散射的影响。该项目将创建一个新的数学框架来模拟颗粒增强复合材料中的波传播，该框架位于基于物理的分析方法和数值单元方法的融合点。通过合并分析和数据驱动的策略，这项工作将揭示创新的多尺度方法来研究具有复杂微观结构的介质中的波传播。了解颗粒添加对冰的动态响应的影响将使广义颗粒复合结构中的波传播分析成为可能，这将远远超出所描述的应用。在联合数值和分析方法结合建议的优化算法的效率提高将从根本上改变弹性动力学建模和超声无损evaluation.This奖项反映了NSF的法定使命领域，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

项目成果

Modeling of wave propagation in polycrystalline ice with hierarchical density gradients

• DOI: 10.1016/j.finel.2023.103916
• 发表时间: 2023
• 期刊: Finite Elements in Analysis and Design
• 影响因子: 3.1
• 作者: F. Ghanbari;E. G. Rodriguez;Daniel Millán;F. Simonetti;A. P. Argüelles;C. Peco

Von Kármán spatial correlation function to describe wave propagation in polycrystalline media

描述波在多晶介质中传播的冯·卡门空间相关函数

• DOI: 10.1063/5.0091521
• 发表时间: 2022
• 期刊: Journal of Applied Physics
• 影响因子: 3.2
• 作者: Argüelles, Andrea P.