Unified Approach for Estimating Axial-Load Capacity of Concrete-Filled Double-Skin Steel Tubular Columns of Multiple Shapes Using Nonlinear FE Models and Artificial Neural Networks

Author:

Rafiq Joo Mohammad1ORCID,Ahmad Sofi Fayaz2ORCID

Affiliation:

1. Former Undergraduate Student, Dept. of Civil Engineering, National Institute of Technology Srinagar, Hazratbal, Jammu and Kashmir 190006, India. ORCID: .

2. Assistant Professor, Dept. of Civil Engineering, National Institute of Technology Srinagar, Hazratbal, Srinagar, Jammu and Kashmir 190006, India (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Arts and Humanities (miscellaneous),Building and Construction,Civil and Structural Engineering

Reference76 articles.

1. Utilization of artificial neural networks to prediction of the capacity of CCFT short columns subject to short term axial load

2. ANSYS Inc. 2019a. Mechanical APDL element reference. Canonsburg, PA: ANSYS Inc.

3. ANSYS Inc. 2019b. ANSYS parametric design language guide, release 2019. Canonsburg, PA: ANSYS Inc.

4. Nonlinear analysis of square concrete-filled double-skin steel tubular columns under axial compression

5. Crack Shear in Concrete: Crack Band Microflane Model

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