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Full-Text Articles in Mechanical Engineering
Damage Detection With An Integrated Smart Composite Using A Magnetostriction-Based Nondestructive Evaluation Method: Integrating Machine Learning For Prediction, Christopher Nelon
Damage Detection With An Integrated Smart Composite Using A Magnetostriction-Based Nondestructive Evaluation Method: Integrating Machine Learning For Prediction, Christopher Nelon
All Dissertations
The development of composite materials for structural components necessitates methods for evaluating and characterizing their damage states after encountering loading conditions. Laminates fabricated from carbon fiber reinforced polymers (CFRPs) are lightweight alternatives to metallic plates; thus, their usage has increased in performance industries such as aerospace and automotive. Additive manufacturing (AM) has experienced a similar growth as composite material inclusion because of its advantages over traditional manufacturing methods. Fabrication with composite laminates and additive manufacturing, specifically fused filament fabrication (fused deposition modeling), requires material to be placed layer-by-layer. If adjacent plies/layers lose adhesion during fabrication or operational usage, the strength …
Mechanical Characterization Of Automated Fiber Placement And Additive Manufacturing Hybrid Composites, Lucan Haviland
Mechanical Characterization Of Automated Fiber Placement And Additive Manufacturing Hybrid Composites, Lucan Haviland
Electronic Theses and Dissertations
This thesis presents the optimization of processing parameters based on the mechanical properties of Continuous Fiber-Reinforced Thermoplastic (CFRTP) Unidirectional (UD) consolidated tapes. The UD tapes were consolidated using an AFP head and a thermoforming press for comparison. The adhesive strength of hybrid parts consisting of CFRTP UD tape bonded to a 3D-printed substrate with the same matrix system were investigated. Large Area Additive Manufacturing (LAAM) was utilized for the 3D-printed parts. Different types of thermoplastic composite materials were explored, including Glass Fiber reinforced Polyethylene Terephthalate Glycol (GF/PETG), Carbon Fiber reinforced Polyethylene Terephthalate Glycol (CF/PETG), Carbon Fiber reinforced Polycarbonate (CF/PC), and …
Heterogeneous Sensor Data Fusion For Multiscale, Shape Agnostic Flaw Detection In Laser Powder Bed Fusion Additive Manufacturing, Benjamin Bevans, Christopher Barrett, Thomas Spears, Aniruddha Gaikwad, Alex Riensche, Harold (Scott) Halliday, Prahalada Rao
Heterogeneous Sensor Data Fusion For Multiscale, Shape Agnostic Flaw Detection In Laser Powder Bed Fusion Additive Manufacturing, Benjamin Bevans, Christopher Barrett, Thomas Spears, Aniruddha Gaikwad, Alex Riensche, Harold (Scott) Halliday, Prahalada Rao
Department of Mechanical and Materials Engineering: Faculty Publications
We developed and applied a novel approach for shape agnostic detection of multiscale flaws in laser powder bed fusion (LPBF) additive manufacturing using heterogenous in-situ sensor data. Flaws in LPBF range from porosity at the micro-scale (< 100 μm), layer related inconsistencies at the meso-scale (100 μm to 1 mm) and geometry-related flaws at the macroscale (> 1 mm). Existing data-driven models are primarily focused on detecting a specific type of LPBF flaw using signals from one type of sensor. Such approaches, which are trained on data from simple cuboid and cylindrical-shaped coupons, have met limited success when used for detecting multiscale flaws in complex LPBF parts. The objective of this work is to develop a heterogenous sensor data fusion …