AN EXPERIMENTAL STUDIES ON HIGH SEISMIC PERFORMANCE SHEAR WALLS
Published In: 8TH INTERNATIONAL CONFERENCE ON ADVANCES IN CIVIL, STRUCTURAL AND MECHANICAL ENGINEERING
Author(s): WEN-I LIAO
Abstract: Past RC wall panel tests of reinforced concrete membrane elements under reversed cyclic loading have much greater ductility when steel bars are provided in the direction of principal tensile stress. In order to improve the ductility of shear walls under earthquake loading, high seismic performance shear walls have been proposed to have steel bars in the same direction as the principal direction of applied stresses in the critical regions of shear walls. This paper presents the test results of two shear walls under shake table excitation and two shear walls under reversed cyclic loading. In the specimens under shake table tests, steel bars were provided at angles of either 90 degrees or 45 degrees to the horizontal. In the reversed cyclic tests, one-half of the steel bars were placed at an angle of 45 degrees to the horizontal in the low-rise shear wall and at an angle of 65 degrees to the horizontal in the bottom portion of the mid-rise shear wall. Based on the experimental results, th
- Publication Date: 24-Jun-2018
- DOI: 10.15224/978-1-63248-154-2-09
- Views: 0
- Downloads: 0
DISCHARGE MODELING IN SMOOTH AND ROUGH COMPOUND CHANNELS USING GENETIC PROGRAMMING
Published In: 8TH INTERNATIONAL CONFERENCE ON ADVANCES IN CIVIL, STRUCTURAL AND MECHANICAL ENGINEERING
Author(s): ALOK ADHIKARI
Abstract: Discharge results observed from the experimental channels for smooth and rough surfaces, along with data from a compound river channel are used in the Genetic Programming. Model equations are derived for predic12tion of discharge in compound channel16 for various types of channel surfaces. Five hydraulic parameters are used for developing the model equations. Models derived are tested and compared with other soft computing techniques. Evaluations of all the approaches are carried out using five performance parameters. Finally, the effect of parameters responsible for the flow behavior is shown through sensitivity analysis. GP is found to give the most prom10.15224/978-1-63248-154-2-10ising results. This work aims to benefit the researchers engaged in modeling of discharge using machine learning techniques.10.15224/978-1-63248-154-2-10
- Publication Date: 24-Jun-2018
- DOI: 10.15224/978-1-63248-154-2-10
- Views: 0
- Downloads: 0