Are Leaf Traits Stable Enough to Rank Native Grasses in Contrasting Growth Conditions?

The growing interest in classifying species in response groups relating to variations in environmental factors has triggered the search for functional traits that express differences in ecological behaviour among plant species (Lavorel & Garnier, 2002). Specific leaf area (SLA) and leaf dry matter content (LDMC) reflect a fundamental trade-off in plant functioning between a fast growth rate (high SLA, low LDMC species) and nutrient conservation (low SLA, high LDMC species). This study aimed to analyse the stability of ranking native grasses by SLA and LDMC values under different plant growing conditions

Structural Health Monitoring of Wind Turbines Using a Digital Image Correlation System on a UAV

Unmanned aerial vehicles (UAVs) have recently emerged as a robust tool for remote inspection and data acquisition at places that are either inaccessible or riskier to perform measurements. To quantify the level of strain/stress and loading conditions that the rotating structures such as wind turbine experience during operation, an approach is proposed that can perform a nondestructive evaluation of these rotating structures using non-contact, three-dimensional (3D) digital image correlation (DIC). This technique addresses the benefit of non-interference with structure functionality and can be used for rotating or non-rotating structures. In this project, a synchronized set of a stereo camera system is used to acquire the images of a rotating turbine. These images are processed to obtain displacement, geometry, and strain over the wind turbine blades during deformation

Digital Image Correlation Techniques for NDE and SHM

Monitoring and analyzing the integrity of structures, infrastructure, and machines is essential for economic, operational, and safety reasons. The assessment of structural integrity and dynamic conditions of those systems is important to ensure safe operation and achieve or even extend the design service life. Recent advancements in camera technology, optical sensors, and image processing algorithms have made optically based and noncontact measurement techniques such as photogrammetry and digital image correlation (DIC) appealing methods for nondestructive evaluation (NDE) and structural health monitoring (SHM). Conventional sensors (e.g., accelerometers, strain gages, string potentiometers, LVDTs) provide results only at a discrete number of points. Moreover, these sensors need wiring, can be time-consuming to install, may require additional instrumentations (e.g., power amplifiers, data acquisition), and are difficult to implement on large-sized structures without interfering with their functionality or may require instrumentation having a large number of data channels. On the contrary, optical techniques can provide accurate quantitative information about full-field displacement, strain, geometry, and the dynamics of a structure without contact or interfering with the structure’s functionality. This chapter presents a summary review of the efforts made in both academia and industry to leverage the use of DIC systems for NDE and SHM applications in the fields of civil, aerospace, and energy engineering systems. The chapter also summarizes the feasibility of the approaches and presents possible future directions of the measurement approach