Tutorials

Multiphase flows are commonly found in many industries (e.g., chemical and fuel processing, pharmaceutical manufacturing) as well as throughout the environment (e.g., waves, rain, avalanches). Although multiphase flows are commonly observed, their operation and control are very complex. Experimental observations of multiphase flows are crucial to improve our understanding of the fundamental hydrodynamic and transport processes, as well as to develop and validate fundamental models. This tutorial will introduce multiphase flow visualization techniques using available tube source X-rays. Various imaging modes, including X-ray radiography, X-ray stereography, and X-ray computed tomography will be summarized and requirements for multiphase flow visualization will be presented. Multiphase flow examples using each imaging mode will be discussed, including gas-liquid, gas-solid, and granular flows. Required calibrations and challenges will be highlighted for specific multiphase flow systems. Qualitative and quantitative data will be presented, including high-speed flow visualization, particle tracking, and time-average local void fractions.

Laser ultrasound is a powerful non-contact technique where ultrasonic inspection is performed by generating and detecting an ultrasonic signal with two lasers. The generation of the ultrasonic wave is accomplished by an incident laser pulse on the sample surface generally operating in one of two regimes: thermoelastic and ablation. The thermoelastic regime is considered completely nondestructive and relies on subsurface thermal expansion and contraction.  The ablation regime relies on formation of plasma and material removal on the sample surface. The resulting laser-generated ultrasonic beam characteristics are therefore highly dependent on both the interrogated sample characteristics such as surface conditions and wavelength absorptivity and the generation laser parameters, including spot size, pulse duration, power, and laser wavelength.

This presentation will provide a broad overview of the basics of laser ultrasonic generation and detection. Detail will be provided on the different testing regimes and experimental considerations. Examples will also be provided, where specific emphasis will be placed on applicability in the manufacturing environment.  

Microwave synthetic aperture radar (SAR) imaging is a technique that is well-suited for a wide variety of nondestructive evaluation (NDE) applications, primarily due to its noncontact nature and ability to inspect dielectric or composite structures. SAR polarimetry is an extension of SAR imaging that makes use of wave polarization, by measuring the polarization of the wave scattered by a target or flaw relative to the illumination wave polarization. This polarization can be used to ascertain critical properties and features of a target or a defect. For example, by measuring the polarization of a wave that is scattered by a surface-breaking crack in metal (or a subsurface crack in a dielectric), we can characterize the orientation and size of the crack. The same concepts can also be used for other NDE applications such as detecting and characterizing waviness in carbon- and glass-fiber-reinforced composites, determining surface curvature, etc.

This tutorial will begin by explaining the relevant fundamental concepts of microwave signal polarization, including how polarization relates to characterizing defects. Methods to produce and measure polarized signals will be shown, and some example applications and practical challenges will be discussed. The tutorial will conclude with the latest techniques and advances in SAR polarimetry and the potential for future NDE applications.

In Structural Health Monitoring (SHM), measured data that correspond to an wide set of operational and damage conditions are rarely available or very expensive to obtain. A way of probabilistic framework for the classification, investigation and labelling of data is discussed as an online strategy for SHM to aid both damage detection and identification, while using a limited number of the most informative labelled data.

A way of including physics knowledge and grey box modelling will also be discussed. Another, potential solution considers that information might be transferred, in some sense, between systems. A population-based approach to SHM (PBSHM) looks to both model and transfer this missing information, by considering data collected from groups of similar structures. A framework will be proposed to model a population of systems, such that datasets are only available from a subset of members. The ideas will be presented in a variety of engineering systems from experimental (test-rig) members to bridges and operational wind farms.