Measurements Lecture 

Professor Michael Sutton, Mechanical Engineering, Biomedical Engineering
Molinaroli College of Engineering and Computing, University of South Carolina, USA

'Recent Developments in Characterization of Advanced Material Response' 

Global national conflicts have necessitated reductions in the time required to develop advanced material systems, resulting in a focus on development and application of sophisticated methods for characterization of advanced material responses. Fortunately, full-field measurement methods such as digital image correlation (DIC) have provided investigators with the opportunity to integrate measurement data with computational methods in unique ways. The presentation will focus on three recent studies. 

The first study presents a novel method combining digital image correlation (DIC) full-field deformation measurements with the explicit dynamic finite element method (EFEM) to reconstruct the full field spatio-temporal stress field in dynamically loaded materials without requiring knowledge or input of material properties. Stress-strain data obtained using the reconstruction methodology with DIC measurements are found to accurately describe material response.
Since the EFEM requires DIC deformations and accelerations at locations in the specimen during loading, results are reported quantifying point-wise variability in the DIC-based motion measurements. Performing both theoretical analysis and specimen static and dynamic translations, velocity and acceleration uncertainties when using central difference temporal derivative formulae are shown to be 𝜎u ⋅ 𝐹𝑅 and 𝜎u ⋅ 𝐹𝑅2, respectively, where 𝜎u is the standard deviation in displacement and FR is the camera frame rate.

Finally, using an inverse form for the equations of equilibrium, a novel algorithm, IMPACT, for direct extraction of heterogenous material properties when using full-field DIC deformation measurements and a multilinear material property form has been developed for both 1D and 2D configurations. For a nominally 2D specimen geometry, material property results from the IMPACT method simulations are compared to independent estimates using the finite element method updating (FEMU) method. 

Plenary Lecture

Caitríona (Tríona) Lally, Professor in Biomedical Engineering and Director of Industry Engagement
Discipline: Mechanical, Manufacturing & Biomedical Engineering, Trinity College Dublin 

'Exploring The Synergistic Effect Of Calcification And Structural Damage on Bioprosthetic Heart Valve Leaflets Using Bespoke In-vitro Testing'

Aortic stenosis (AS) causes narrowing and stiffening of the aortic valve, and restricts blood flow from the heart to the rest of the body. Minimally invasive treatment for AS involves the implantation of a bioprosthetic valve with porcine or bovine pericardium leaflets. These leaflets eventually succumb to failure due to regurgitation or stenosis, caused by calcification and/or structural damage and the relationship between these two durability-limiting processes is highly debated. Using bespoke in-house in-vitro testing systems to screen pericardial tissue and subject it to cyclic loading, with and without calcification, we have gained critical insights into the relationship between calcification and structural damage in porcine pericardium (PP) used in heart valves. From this work we have identified screenable tissue features which could minimise both factors and help to increase the long-term durability of bioprosthetic heart valves.

Plenary Lecture

Lizzy Cross is a Professor in the Dynamics Research Group at the University of Sheffield

'Modelling structures with physics and data'

The use of machine learning in engineering, and particularly in Structural Health Monitoring, is becoming more common, as many of the inherent tasks (such as regression and classification) in developing condition-based assessment fall naturally into its remit. This talk will focus on probabilistic approaches to physics-informed machine learning, where one adapts ML algorithms to account for the physical insight an engineer will often have of the structure they are attempting to model or assess. We will show how grey-box models, that combine simple physics-based models with data-driven ones, can improve predictive capability in an SHM setting – both in terms of accuracy and confidence. The talk will also consider interpretability, considering when the incorporation of physics does and does not enhance how much we understand about a model.

Speaker Biography

Special Sessions (to follow)
Conference Reception (to follow)

Conference Dinner
Swansea Arena, Swansea, UK