Search

Rigid pavement design in airport runways is based on tension critical stress at the bottom of the concrete slab. Determination of slab's critical zones, under airplanes loading types in 3D finite element modeling is the objective of this study. Numerical study to determination main gear role in passenger, commercial and military airplanes on pavement critical stress and also critical zones determination in the runway rigid pavement by using of finite element software, ABAQUS is done. In order to this study, 148 wheels characteristic of different airplanes and in various loading positions including edge and center of the concrete slab is considered. Results show that among different airplanes, A380F, B777-300ER, C17A and Concorde impose maximum tensional stress on the solid pavement airport runway. Also in all kinds of airplanes, the maximum critical stress under concrete slab is happening when the length of wheels lie on concrete slab edge.

Pavement analysis is an important field in pavement engineering, because of its causes on pavement behavior and obtaining more accurate equations for it. By science developing, many pavement analysis softwares have been developed which most of them are based on Multi-Layer Theory and a few work based on Finite Elements Method (FEM). Lots of input, spending much time in modeling process and to be unable to running more than one pavement modeling in a time are their main deficiencies. Artificial Neural Networks (ANN) as one of artificial intelligence algorithms has a lot of advantages such as low input numbers, reducing considerable time in the modeling process, multi pavement modeling at a time. In this article, after modeling verification, simulated an artificial neural network based on 384 models which were modeled by finite elements software and found a back propagation ANN with 8-10-2 combination with sigmoid transfer function which was the optimum network for the network.

Eventful sections prioritization methods usually have been based on single-criterion methods. Therefore, with respect to a separate and distinct criterion, identifying and prioritization of different sections have been done. Due to budget deficiency for immunization actions, prioritization non-immune sections are of great importance. In this regard, several different methods were presented by experts that were based on a specific basis. Among these, we can point to two general structures based on economic and technical studies. On the other hand due to weakness in accidents data (incomplete, incorrect or unused data), It is better to identify and prioritize the proposed methods, evaluated as far as possible without regard to the accidents data, here the new and innovative methods have special significance. In this study which is new in the field of road immune in the country, we use powerful device named multilayer Artificial Neural Networks for predicting prioritization of eventful MAZANDARAN road networks modifying. And tried to investigate the advantages of using neural networks, considering the history of accidents and the costs of their modifying, achieving method to optimal prioritization should be analyzed.

Today, in Third-world countries such as Iran tendency the population growth and width of transportation and high rank of needed increase the number of cars and travels, that thi is increasing of the unreasonable of travel time and high rate of accidents. So the expection the density of passing traffic for a street and capacity analysis to extence and improvement of road network is too important. In this essay, we inspect truly the passing traffic of highway between Semnan-Garmsar simulating CORSIM software. Then with changeable geometric matters we analyse the changes of the density of passing traffic and the race of passing traffic. This highway is one of the important roadway in our country for transferring passengers and stuffs and is apart of road connectivity between west-east. CORSIM is a through going simulated software in science traffic engineering, which has the high capability in analysis of road network. As a result of lacking acquaince with this software, its used is limited in our country and until now it is uselessness about urban highway network. Geometritic and traffic information was received through real observation so that they have great accuracy.