CALRECOD — A software for Computed Aided Learning of REinforced COncrete structural Design. (October 2022)

• Record Type: Journal Article
• Authors: Verduzco, Luis Fernando; Horta, Jaime; Hernández, Miguel A. Pérez Lara y; Hernández, Juan Bosco
• Is Part Of: Advances in engineering software. Volume 172(2022)
• Publication Date: 2022-10
• Subjects: CALRECOD -- Reinforced concrete structures -- High education -- Computed aided learning -- Optimization methods; Computer-aided engineering -- Periodicals; Engineering -- Computer programs -- Periodicals; Engineering -- Software -- Periodicals; Periodicals; 620.0028553
• DOI: 10.1016/j.advengsoft.2022.103189
• Languages: English
• ISSNs: 0965-9978

Abstract

Abstract: It is presented the development and implementation of a new computed aided learning MatLab Toolbox for the design of reinforced concrete structures named as CALRECOD for their abbreviation Computer Aided Learning of Reinforced Concrete Design . Such development emerges as the result of a series of research works in the Autonomous University of Queretaro with the main purpose of improving the way in which the design of reinforced concrete structures is taught in high education institutions. CALRECOD uses optimization methods and algorithms to aid students in their design interaction learning so that they are able to compare their own designs and what commercial software delivers with optimal ones given certain load conditions on the elements or structures. The software consists almost entirely of MatLab functions (.m files) and the ACI 318-19 code is taken as their main design reference to make it internationally useful, although in some cases the Mexican code NTC-17 specifications are used. Besides MatLab functions, the software consists as well of ANSYS SpaceClaim script functions (.scscript files) as an additional tool for the aid in the visualization of design results in a 3D space in the software ANSYS SpaceClaim. CALRECOD has proven to be versatile, flexible and of easy use with a huge potential to increase learning outcomes for students in high education programs related with the design of reinforced concrete structures as well as to enhance the creation of efficient interactive environments for researchers and academics focused on the development of new design and analysis methods for such structures. With their optimization design functions, a solid comparison platform of designs' performance could be laid out, and with its extended function design packages for structural systems, reinforced concrete design courses could be enhanced in a great deal regarding their program content's scope. The software can be found at: https://github.com/calrecod/CALRECOD . Highlights: With the aid of optimization methods, a broader teaching framework could be reached for courses of Reinforced Concrete Design. Visual programming with ANSYS SpaceClaim represents a potential tool to aid students of Reinforced Concrete Design courses for better design assessment. CALRECOD offers a great learning environment for Reinforced Concrete Design practices in Higher Education as it enhances further learning outcomes in students as well as research.