Blending ultrasound data with physics-based models to predict damage in structural systems

将超声数据与基于物理的模型混合以预测结构系统的损坏

• 批准号: 2886009
• 金额: --
• 依托单位: University of Warwick
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2886009
• 关键词: Blending; ultrasound; data; physics; based

Monitoring of damage degradation in materials is vital as any cracks will reduce local stiffness, accelerating the ageing process of the physical assets. In-situ ultrasonic monitoring data is valuable for giving the inspectors information on the level of what may be wrong with the structural systems. However, purely data-driven representations do not always give inspectors enough information and the ability to predict how the system will behave in the future. This can be achieved by utilising some knowledge of the physics that underpins the system. This project will use the fusion of experimental data and physical models for failure prediction of materials, by taking measurements and developing models that are hybrid in nature.

监测材料中的损害降解至关重要，因为任何裂缝都会降低局部刚度，从而加速物理资产的衰老过程。原位超声监测数据对于向检查员提供有关结构系统可能出了问题的信息很有价值。但是，纯粹的数据驱动表示形式并不总是为检查人员提供足够的信息以及预测系统将来如何行事的能力。这可以通过利用对系统的物理学知识来实现​​。该项目将使用实验数据和物理模型的融合来进行材料的故障预测，并进行测量和开发本质上是混合的模型。