This Work focuses on the application of fracture mechanics concepts in two engineering systems. The first application is the ice accretion problem, focusing on understanding the fundamental mechanisms affecting the ice/surfaces interfacial adhesion and the deicing process. The second system is the topological details of pairs of fracture surfaces and their unique attributes at a scale larger than the grain size, focusing on developing a statistical-based classification framework for forensic applications.

Ice accretion on engineering structures such as aircraft, ships, power transmission, and wind turbines can lead to many hazards. Understanding the fundamentals of the decohesion mechanisms would greatly enhance the development of efficient and durable icing protection systems. Current measurements show an unexplained large scatter of the ice adhesion strength derived from a range of experimental configurations (shear, push, centrifuge, and dynamic vibration tests). These testing configurations provide effective estimates of the interface's interfacial strength without microscopic consideration of its interface fracture toughness. The objective of this work is to characterize the interfacial adhesion of ice to different substrates utilizing fracture mechanics-based approaches wherein well-characterized fracture configurations were employed. The role of a range of parameters on the interfacial adhesion is investigated, including; (1) surface roughness, (2) environmental temperature, (3) ice aggregate length, and (4) testing methodology. New and modified testing methodologies were implemented and numerically calibrated to assess the mode-I and mode-II interfacial adhesion characteristics. Preliminary results show a low effect of the surface roughness on the ice interfacial adhesion strength, whereas temperature has a more detrimental effect. It is found the geometric constraint could significantly affect the observed ice adhesion strength due to the role of residual interfacial stresses. Detailed microstructure analysis of the ice shows the origin of these observed trends.

For forensic science application, the similarity between fracture surfaces for fragments of forensic evidence is analyzed utilizing a fracture mechanics-based quantitative framework. The fracture surface carries unique features, which arise from the material intrinsic properties and microstructures, as well as the exposure history to external forces. The statistics of these topological features were utilized for forensic comparison at a relevant microscopic length scale. The microscopic features on the fracture surface are quantitatively measured by 3D microscopy on different material sets, including knives, stainless steel rods, polymers, and ceramic rods that were broken randomly or under controlled conditions. Spectral analysis of the fracture surface topography and statistical learning tools are used to classify specimens. The methodology utilizes 3D spectral analysis of the fracture surface topography and classifies specimens with very high accuracy using statistical learning protocol. The method described can have the ability to assist in a match/non-match determination in cases where there may not be large features that allow for a manual physical comparison across a broad range of fractured materials and/or toolmarks, with diverse textures and mechanical properties.