Using data analytics approach to estimate the efficiency of the structural design of tall buildings | |
| Author | Sapkota, Binod |
| Call Number | AIT Thesis no.ST-21-09 |
| Subject(s) | Tall buildings--Design and construction Data envelopment analysis--Computer programs Structural design--Data processing |
| 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-21-09 |
| Abstract | The typical structural design process for tall buildings is iterative and hence time and resource-consuming. The design process is focused mainly on safety and serviceability but other important aspects such as economy, sustainability, etc are ignored. Moreover, multiple design solutions are possible for the same design problem but the typical design procedure has no straightforward way to select the best among them. The selection relies on subjective judgment or expert’s opinion which may not always yield the best solution due to biases. These drawbacks can be rectified by using the efficiency evaluation framework (EEF) proposed in this research. The proposed EEF consists of three main aspects, evaluation objective, efficiency parameters, and evaluation approach. Benchmarking method, Data Envelopment Analysis (DEA) is used as an evaluation approach to evaluate efficiency based on inputs and outputs. The implementation strategy for the proposed EEF is formulated based on its use in simplified structures. It is found that, for a system with a large number of parameters, the PCA-DEA model, DEA coupled with Principal Component Analysis (PCA), is suitable as an evaluation approach. In this study, EEF is implemented in cantilevers, frames and tall buildings to demonstrate its use in the selection of the best system among many alternatives based on efficiency score. The EEF yields a basic and super efficiency score which represent global performance measures based on multiple criteria, thus useful for decision making that minimizes subjective judgment. Also, peer units, peer weight, and partial factors obtained from EEF can be used for applying systematic improvements during the structural design process. Thus, EEF significantly reduce iteration and ensure best solution through multicriteria decision making and systematically guided improvement process. The typical structural design procedure is enhanced with this framework using data from previously designed buildings thus modified design procedure can be called a ‘Data driven structural design’ process. However, the proposed framework does not intend to replace the experience and knowledge of experts. This will be considered as a complementary tool for decision-making based on data. |
| Year | 2021 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. ST-21-09 |
| Type | Thesis |
| School | School of Engineering and Technology (SET) |
| Department | Department of Civil and Infrastucture Engineering (DCIE) |
| Academic Program/FoS | Structural Engineering (STE) /Former Name = Structural Engineering and Construction (ST) |
| Chairperson(s) | Pennung Warnitchai;Anwar, Naveed (Co-Chairperson); |
| Examination Committee(s) | Punchet Thammarak;Thanakorn Pheeraphan; |
| Scholarship Donor(s) | Asian Institute of Technology Fellowship;Computer and Structures Inc. (CSI), USA; |
| Degree | Thesis (M. Eng.) - Asian Institute of Technology, 2021 |