An artificial neural network modeling of the flexural behavior of an RC beam strengthened using carbon fiber-reinforced polymer
Date of Publication
2001
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Civil Engineering with Spec in Construction Technology & Management
Subject Categories
Civil Engineering
College
Gokongwei College of Engineering
Department/Unit
Civil Engineering
Thesis Adviser
Jason Maximino C. Ongpeng
Defense Panel Chair
Ronaldo S. Gallardo
Defense Panel Member
Andres Winston C. Oreta
Alden Paul D. Balili
Abstract/Summary
The use of externally bonded and near-surface mounted reinforcement of CFRP on flexure beams with the use of epoxy or resin is an effective strengthening and repairing technique for RC beams. For our study 158 beams specimens were gathered for the development of flexural strength analysis through the use of artificial neural network modeling. The 158 beam specimens are divided into three groups 70% of the data were used for the training, 15% were tested, and the remaining 15% were used for verification. The input parameters used are the easily available variables within the journals, namely: base (b), height (h), length (L), cross-sectional area of the tension enforcement bar (As), cross-sectional area of the CFRP plate/sheet (Af), and the yield strength of CFRP (ftf) the output parameter is the ultimate flexure moment. The developed ANN model is then compared with other existing models to determine its efficiency and accuracy. Lastly, a parametric study was done in order to determine the importance, effect, and behavior of each parameter. Through this, the proponents of this study were able to produce a reliable flexural behavior model of a RC beam strengthened with CFRP even more efficient and effective than that of other studies of the same topic.
Abstract Format
html
Language
English
Format
Accession Number
TU15908
Shelf Location
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
Physical Description
xvi, 131 leaves, illustrations (some color), 30 cm.
Keywords
Concrete beams; Flexure--Testing; Strength of materials--Testing
Recommended Citation
Arcilla, C. V., & Vilaga, F. B. (2001). An artificial neural network modeling of the flexural behavior of an RC beam strengthened using carbon fiber-reinforced polymer. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/5156
Embargo Period
4-11-2021