Ph.D. Tezi Görüntüleme

Student: Erhan Burak PANCAR
Supervisor: Yrd.Doç.Dr. M. Vefa AKPINAR
Department: İnşaat Mühendisliği
Institution: Graduate School of Natural and Applied Sciences
University: Karadeniz Technical University Turkey
Title of the Thesis: Information Systems and Artificial Intelligence Approach in Numerical Design Stage of Concrete Road Pavement
Level: Ph.D.
Acceptance Date: 16/1/2012
Number of Pages: 155
Registration Number: Di881
Summary:

      Different countries have different designs for concrete pavements. These designs are created with the help of many years brought abaks based on experiment and observation. It is aimed to achieve optimum results with the ongoing work of the numerical analysis. Studies in this field is missing in our country and because of that this subject needs to be investigated in detail.

      In this study, theoretical textural scan is done on concrete slab by 8ton, 10ton, 12ton weight, dual wheel single axle by using finite difference method. These axle weights, number of axle weight repetitions, elastic modulus of concrete, temperature differences on upper and lower surface of concrete slab depending on the thickness of the concrete (temperature gradient) associated by fatigue analysis and ideal concrete thickness for different values have been identified. Conversion coefficients of axle weights change in case of change in plate thickness, concrete type, temperature gradient value at concrete roads. These coefficients are determined in this study. So, it can be determined the corresponding number of 12 ton and 10 ton axle weight repetitions to 8 ton axle weight repetition on the road route. As a result of this study, it is identified that temperature gradients at which vehicle passes through the concrete slab, plays an important role on determining the concrete slab thickness. It is determined that temperature gradient value is more decisive on the number of axle weight repetition on road route while slab thickness increases and slab thickness decreases between 2-3 cm in case of using C30 type concrete instead of C25 type concrete. Backpropagation neural network used in design calculation and a new program is written in C + +.

      Key Words: Concrete Road, Information Systems, Artificial İntelligence, Temperature Gradient, Road Thickness