Preliminary design of tall building using artificial neural network | |
| Author | Khatiwada, Lila |
| Call Number | AIT Thesis no.ST-15-04 |
| Subject(s) | Tall buildings--Design and construction Neural networks (Computer science) |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Structural Engineering, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. ST-15-04 |
| Abstract | With rapid increase in the need for tall buildings to accommodate exponentially growing urban population, quick and reliable estimation of approximate sizes of shear wall, column, and typical response parameters such as natural period, maximum story drift ratio, ratio of base shear to total weight of building and primary structural component indicator such as ratio of total area of column to cumulative floor area of tower, ratio of total shear wall to cumulative area of floor, weight per unit area of floor, weight per unit volume of tower at top of podium level can greatly facilitate preliminary design and feasibility of the project. This research presents the outcome of an artificial neural-network based approach to directly determine design parameters based on experience gained from previously designed buildings, using both code-based and performance-based approaches. Artificial neural network models are trained to determine structural design indicators from architectural parameters. The proposed approach can not only provide means for quick estimation of design output, but can also provide a sanity check on code based design output and performance based design results. The objective is to provide means of assisting the design team and clients to make key design decisions based on cumulative experience rather than relying on judgment of individual designers. The approach is demonstrated through the sample networks trained on about thirty eight tall buildings for which required architectural, and structural design results have been generated through detailed design. |
| Year | 2015 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. ST-15-04 |
| Type | Thesis |
| School | School of Engineering and Technology |
| Department | Department of Civil and Infrastucture Engineering (DCIE) |
| Academic Program/FoS | Structural Engineering (STE) /Former Name = Structural Engineering and Construction (ST) |
| Chairperson(s) | Punchet Thammarak; |
| Examination Committee(s) | Anwar, Naveed ;PennungWarnitchai; |
| Scholarship Donor(s) | AIT Fellowship; |
| Degree | Thesis (M. Eng.) - Asian Institute of Technology, 2015 |