Design and Optimization of Adhesively Bonded Joints Mating Novel 3D-Fiber Metal Laminates Subjected to Static and Dynamic In-plane and Out-of-plane Loadings

Created by W.Langdon from gp-bibliography.bib Revision:1.8684

@PhdThesis{FatemehMottaghian2023,

• author = "Fatemeh (Elnaz) Mottaghian",
• title = "Design and Optimization of Adhesively Bonded Joints Mating Novel 3D-Fiber Metal Laminates Subjected to Static and Dynamic In-plane and Out-of-plane Loadings",
• school = "Dalhousie University",
• year = "2023",
• address = "Halifax, Nova Scotia, Canada",
• month = "13 " # apr,
• keywords = "genetic algorithms, genetic programming, 3D Fiber Metal Laminates, Adhesively Bonded joints, Finite Element Method, Static and Dynamic Analyses, Cohesive Zone Modelling, Machine Learning",
• URL = "https://dalspace.library.dal.ca/items/037d427b-1aef-4a42-ab39-8a380aad037d",
• URL = "http://hdl.handle.net/10222/82414",
• size = "270 pages",
• abstract = "The automotive and aerospace industries are rapidly growing sectors of the global economy. The global commercial vehicle market is projected to grow from $955 billion in 2020 to $1.7 trillion in 2029. According to Boeing Commercial Market Outlook 2019-2038, the air travel market is projected to be 2.5 times larger in 20 years. As a consequence, energy conservation in the transportation industry has become a worldwide priority due to growing fuel consumption, as well as increased emphasis on reducing carbon dioxide (CO2) emissions to combat global warming.

  Over the last few decades, many researchers have been working on developing lightweight materials such as composites and Fiber Metal Laminates (FMLs) to address the aforementioned issues. Large industrial structural systems consist of components and sub-components; therefore, special attention must be paid to ensure proper assembly. Adhesively bonded joints (ABJs) have emerged as a promising alternative to traditional joining methods due to several advantages they offer, including a higher strength-to-weight ratio and lower magnitude of stress concentration in multi-material joining systems. Most of the studies conducted on ABJs investigated their performance under tensile and fatigue loadings. However, over their life cycle, ABJs may also become subjected to flexural, compressive, and various impact-loading scenarios. The bonded structural system must be able to ensure such loading states while performing the expected functions.

  Therefore, the main objective of the research presented in this dissertation is the design and optimization of suitable adhesively bonded systems for mating 3D-FMLs subjected to both static and dynamic in-plane and out-of-plane loadings. A series of systematic experimental, numerical investigations, and computational data analyses are conducted to accomplish the objectives. New renditions of 3D-FMLs are developed by incorporating various metallic alloys and synthetic and biodegradable materials. Several finite element (FE) models are developed, using the LS-DYNA platform, to investigate the influence of different geometrical and material design parameters on the developed ABJs systems under different loading scenarios. The models are capable of accurately predicting each joint capacity and performance, including the initiation and evolution of local (i.e., cohesion and interfacial failure), and global (i.e., delamination and shear failure) damage mechanisms. The performance of the 3D-FMLs bonded joints is compared against their 2D counterparts, and the optimal configuration with respect to strap length and thickness is established.

  The feasibility of strengthening the system bonded interfaces by incorporation of inexpensive Graphene Nanoplatelets (GNP) and implementation of several surface treatment procedures are explored. Finally, the FE models are used to examine the influence of 13 parameters on the joint capacity, generating an extensive database. The database is then fed into three designed Machine Learning (ML) algorithms. The ML models are trained to predict the response of various ABJs accurately. The models are also capable of examining the simultaneous effects of different geometrical-, material- and performance-based design parameters on the joint capacity with high precision. The ML models are used to establish a simple yet effective semi-empirical equation, which would enable practicing engineers to quickly evaluate the ultimate load-bearing capacity.",

• notes = "Supervisor: Farid Taheri",

}

Genetic Programming entries for Fatemeh Mottaghian

Citations