فهرست مطالب ali tamizi

Utilizing adjacent piers is one of the cost reduction factors in bridge construction. The impact of turbulent flow around piers on each other, piers distance and the amount of scouring in the adjacent piers are of great importance. In this research, it is tried to present a convenient and efficient combination of adjacent piers in order to reduce the amount of scour by analyzing the placement of these piers in two different shapes and various distances from each other and its impact on the amount of local scouring and the bed erosion pattern. Numerical simulation is done by FLOW3D software. Designed models for two cylindrical and combined shapes of piers in two specific placements, side by side and tandem, and in 6 different distance between the two piers for each state, totally 26 simulation models were simulated and investigated. It is found that the scouring depth increases significantly by decreasing distance between piers which creates a wider obstacle against the flow and water jet between the piers. The flow depth is decreased by increasing this distance and the adjacent piers have no impact on the amount and pattern of scouring in S=4D and higher distances away from each other and the most suitable distance was obtained at S=2.75D. In the tandem cases, it was found that the piers distance does not have any impact on the amount of scouring at the upstream and just the middle part experiences quantitative changes in the bed level; this impact is low by decreasing the distance and obvious by increasing the distance. All the mentioned items are correct in the combined pier, but the amount of scouring shows reduction.

Electrocardiogram (ECG) signals are the most popular non-invasive approach for diagnosis of heart irregularities and indications of possible heart diseases. Previous studies have shown that ECG signals do not have a linear distribution and contain a variety of non-linear dimensions. In the present research we have treated the ECG signals as time-series data and applied chaos indices analysis. Utilizing data from MIT_BIH Database، the present study has improved the past research by analysing chaotic indices such as Lyapunov Exponent (λmax)، and Correlation Dimension to ECG signal data from healthy individuals and heart patients. We present appropriate algorithms for reconstruction of Phase Space and estimations of the model parameters using Lyapunov Exponent and CorrelationDimension. We then present the results from reconstruction of Phase Space based on chaotic indices، and fuzzy classifier، to discriminate healthy individuals (NSR) from the heart patients. The heart patients include those with Arterial Fibrillation (AF) and those with Left Bundle Branch Block (LBBB). These results ascertain the effectiveness of application of chaotic distribution to ECG data in improving the heart disease diagnosis.