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008 220210 2021 th uu m rtt 0| a1eng
035 _a.b12379396
099 9 _aAIT Thesis no.ST-21-09
100 1 _aSapkota, Binod
245 1 0 _aUsing data analytics approach to estimate the efficiency of the structural design of tall buildings
260 _aPathum Thani, Thailand :
_bAsian Institute of Technology,
_c2021
300 _a146 leaves :
_bill.
490 1 _aThesis ;
_vno. ST-21-09
500 _aA thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Structural Engineering, School of Engineering and Technology
502 _aThesis (M. Eng.) - Asian Institute of Technology, 2021
520 _aThe 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{u2019}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 {u2018}Data driven structural design{u2019} 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.
650 0 _aTall buildings
_xDesign and construction
650 0 _aData envelopment analysis
_xComputer programs
650 0 _aStructural design
_xData processing.
700 0 _aPennung Warnitchai,
_eChairperson
700 1 _aAnwar, Naveed,
_eCo-Chairperson
700 0 _aPunchet Thammarak,
_eExamination Committee
700 0 _aThanakorn Pheeraphan,
_eExamination Committee
710 2 _aAsian Institute of Technology Fellowship,
_eScholarship Donor
710 2 _aComputer and Structures Inc. (CSI), USA,
_eScholarship Donor
810 2 _aAsian Institute of Technology.
_tThesis ;
_vno. ST-21-09
856 _3Full-Text
_uhttp://203.159.5.9/ait-thesis/detail.php?q=B15696
907 _a.b12379396
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