Outputs (2)

Data-driven Shear Strength Prediction of RC Beams Strengthened with FRCM Jackets using Machine Learning Approach (2024)
Journal Article
Liu, X., Figueredo, G., Gordon, G., & Thermou, G. (in press). Data-driven Shear Strength Prediction of RC Beams Strengthened with FRCM Jackets using Machine Learning Approach. Engineering Structures,

Fabric Reinforced Cementitious Matrix (FRCM) is an effective intervention method for improving the shear strength of existing reinforced concrete (RC) beams, yet predictive analyses are scarce. This study introduces and compares nine machine learning... Read More about Data-driven Shear Strength Prediction of RC Beams Strengthened with FRCM Jackets using Machine Learning Approach.

Retrofit Design Methodology for Substandard R.C. Buildings with Torsional Sensitivity (2017)
Journal Article
Thermou, G. E., & Psaltakis, M. (2018). Retrofit Design Methodology for Substandard R.C. Buildings with Torsional Sensitivity. Journal of Earthquake Engineering, 22(7), 1233-1258. https://doi.org/10.1080/13632469.2016.1277569

Recent earthquakes have revealed the susceptibility of non-ductile reinforced concrete (R.C.) buildings with deficiencies related to stiffness and/or mass irregularities in plan and elevation. This paper proposes a design methodology for the seismic... Read More about Retrofit Design Methodology for Substandard R.C. Buildings with Torsional Sensitivity.