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Maryam Musavi-Z,Mohammad Reza Sheidaii 한국강구조학회 2022 International Journal of Steel Structures Vol.22 No.5
The intended purpose of this study is the steel moment-resisting frames strengthening through cable elements to improve the progressive collapse and seismic performance of the structure simultaneously. To achieve this goal, X-bracing slack cables were applied to all surrounding bays of the top story of the model with variable parameters, including diff erent cable sizes and distinct amounts of slackness, to reach the most appropriate cable characteristics for one column removal or even two columns loss scenario. Increasing the number of paths to redistribute the loads developed due to initial local damage leads to improvement of the progressive collapse response in the existing or new structures. The progressive collapse and seismic performance of the non-strengthened and strengthened model structures were assessed using the nonlinear dynamic alternate path method recommended in the Unifi ed Facilities Criteria guidelines and the pushover analysis of ASCE 41, respectively. Finally, two diagrams were extracted to fi nd a relation between the size and slackness of the cables with the performance level of the structure. Obtained diagrams show that the proposed strengthening scheme can improve the progressive collapse resistance of the steel moment-resisting frames to the desired performance level corresponding to the selected slackness and minimum breaking load of cable. Pushover analysis results showed that the introduced strengthening scheme led to a more appropriate or at least unchanged seismic response. It should be considered in the design phase of columns and cables that adding cables leads to compression enhancement of columns after activation of cable elements.
Mumtaz Hussain Soomro,Sayed Hyder Abbas Musavi,Bishwajeet Pandey 보안공학연구지원센터 2016 International Journal of Bio-Science and Bio-Techn Vol.8 No.4
In this research, a novel method based on Canonical Correlation Analysis (CCA) and Artificial Neural Network (ANN) to detect epileptic seizures from EEG signals is proposed. CCA was applied on EEG signals and feature vectors corresponding to Eigen values were extracted. These Eigen values were fed as input to Artificial Neural Network (ANN)’s widely explored model Multilayer Perceptron Neural Networks (MLPNNs) for classification between occurrence of non-epileptic seizures and epileptic seizures. The extracted Eigen values using CCA proved to be a better epileptic seizures detector and provide average classification accuracy, sensitivity and specificity as 92.583%, 93.25% and 91% respectively.
MTP Validation Analysis of Scour Formulae in an Integral Abutment Bridge
P. T. Ghazvinei,H. Hassanpour Darvishi,J. Ariffin,S. H. Musavi Jahromi,N. Aghamohammadi,A. Amini 대한토목학회 2017 KSCE JOURNAL OF CIVIL ENGINEERING Vol.21 No.3
Utilizing the river floodplain for the purpose of urban landscaping and eco-tourism benefit could greatly reduce the river width that would eventually increase flood intensity. This could possibly weaken the bridge foundation that increase the probability of bridge failures due to scour. The main objective of this study is to evaluate scour predictive formulae at a protruding abutment bridge in the compound channel, using Multiple Testing Problem (MTP) in a geometrical model of an Integral Abutment Bridge (IAB). The results of the MTP and graphical comparison yield satisfactory predictive formula. Findings of the current study can help determining maximum scour depth as an essential component of footing design to optimize both construction and maintenance costs.