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Item Functionality of a Damaged Steel Truss Bridge Strengthened with Post-Tensioned CFRP Tendons(North Dakota State University, 2012) Brunell, Garrett FloydThis research program investigates the performance of a steel truss bridge when subjected to both localized web damage and a subsequent post-tensioned strengthening approach. The investigation utilizes a combined approach involving an experimental scale model bridge and a numerical computer model generated using the commercial finite element software RISA 3-D. The numerical model is validated using test data and further extended to parametric studies in order to investigate the theoretical load rating, strain energy, load redistribution, mode shapes and frequency of the bridge for control, damaged and strengthened states. The presence and severity of damage are found to significantly influence the global safety and reliability of the bridge. Also, higher order modes are more susceptible to changes in shape and frequency in the presence of damage. A recovery of truss deflection and a reduction of member forces are achieved by the proposed strengthening method.Item Identification of Delamination Defects in CFRP Materials through Lamb Wave Responses(North Dakota State University, 2014) Bruhschwein, Taylor JohnDelamination is currently a largely undetectable form of damage in composite laminate materials. This thesis will develop a method to more easily detect delamination damage within composite materials. Using finite element analysis modeling and lab testing, a new method from interpreting the results obtained from existing structural health monitoring techniques is developed. Lamb waves were introduced and recorded through an actuator and sensors made of piezoelectric material. The data was then analyzed through a novel data reduction method using the Fast Fourier Transform (FFT). Using the data from FFT, the idea of covariance of energy change was developed. By comparing the covariance of energy change in beams with differing delamination size, thickness and depth, correlations were able to be developed. With these correlations, the severity and of damage was able to be detected.Item GFRP Bars in Concrete toward Corrosion-free RC Structures: Bond Behavior, Characterization, and Long-term Durability Prediction(North Dakota State University, 2016) Yan, FeiCorrosion of steel reinforcements is the leading causes of malfunction or even failures of reinforced concrete (RC) structures nationwide and worldwide for many decades. This arises up to substantial economic burden on repairs and rehabilitations to maintain and extend their service life of those RC public projects. The inherent natures of glass fiber-reinforced polymers (GFRP) bars, from their superior corrosion resistance to high strength-to-weight ratio, have promoted their acceptance as a viable alternative for steel reinforcement in civil infrastructures. Comprehensive understanding of the bond between GFRP bars and concrete, in particular under in-service conditions or extremely severe events, enables scientists and engineers to provide their proper design, assessment and long-term predictions, and ultimately to implement them toward the corrosion-free concrete products. This research aims to develop a holistic framework through an experimental, analytical and numerical study to gain deep understanding of the bond mechanism, behavior, and its long-term durability under harsh environments. The bond behavior and failure modes of GFRP bar to concrete are investigated through the accelerated aging tests with various environmental conditions, including alkaline and/or saline solutions, freezing-thawing cycles. The damage evolution of the bond is formulated from Damage Mechanics, while detailed procedures using the Arrhenius law and time shift factor approach are developed to predict the long-term bond degradation over time. Besides, the machine learning techniques of the artificial neural network integrated with the genetic algorithm are used for bond strength prediction and anchorage reliability assessment. Clearly, test data allow further calibration and verification of the analytical models and the finite element simulation. Bond damage evolution using the secant modulus of the bond-slip curves could effectively evaluate the interface degradation against slip and further identify critical factors that affect the bond design and assessment under the limit states. Long-term prediction reveals that the moisture content and elevated temperature could impact the material degradation of GFRP bars, thereby affecting their service life. In addition, the new attempt of the Data-to-Information concept using the machine learning techniques could yield valuable insight into the bond strength prediction and anchorage reliability analysis for their applications in RC structures.Item Energy-Saving Non-Metallic Connectors for Precast Sandwich Wall Systems in Cold Regions(North Dakota State University, 2014) Allard, AustinConserving energy in large structural buildings has become very important in today's economy. A number of buildings today are constructed with sandwich wall panels. Steel connections are most commonly used in these panels. The problem with steel is that it has a tendency to reduce the thermal resistance of the insulation. This project considers glass fiber reinforcing polymers (GFRP) and carbon fiber reinforcing polymers (CFRP) as an alternate material to steel. An experimental sandwich wall panel was constructed and subjected to freezing temperatures. The results of the experimental program were compared to a theoretical model using the ANSYS computer program. The model was verified using current analytical methods that determine the heat flux of a sandwich wall panel. The methods investigated include the parallel path, zone, parallel flow, and isothermal planes methods. The results suggest that the GFRP connectors perform slightly better than the steel and CFRP connectors.