Work

Seismic Retrofitting of Reinforced Concrete Frames Using Viscoelastic Layers at Beam–Column Joints

Year: 2026
Type: article
Abstract: This study investigates the use of viscoelastic (VE) material layers, reinforced with steel plates, for the seismic retrofitting of reinforced concrete (RC) frame structures. Conventional retrofitting approaches predominantly aim to enhance structural strength, which can undesirably shift the dynamic characteristics away from their original design intent. In contrast, the present work emphasises energy dissipation as the primary mechanism for improving seismic performance. A practical and efficient material characterisation methodology, based on Dynamic Mechanical Analysis (DMA) test data and subsequent derivation of Prony Series coefficients, is employed for numerical modelling, offering substantial advantages over traditional time-intensive techniques such as stress relaxation experiments. In this study, VE material properties are determined through a combination of DMA testing, curve-fitting approximation, and numerical validation. Once the material behaviour has been characterised, numerical simulations are conducted in both the frequency and time domains to assess the efficacy of the proposed retrofitting scheme in reducing resonant response and lateral displacements. The novelty of the retrofitting technique proposed in this research involves direct application of VE materials in the form of layers backed by metal plates. The results demonstrate that VE layers, combined with steel plates at beam–column joints, enhance the seismic performance of RC frames by increasing damping and reducing vibration amplitudes. The findings highlight the potential of VE-layer-based retrofitting as an effective strategy for controlling seismic responses while avoiding excessive stiffening and associated unfavourable shifts in dynamic response. Furthermore, DMA-based Prony series modelling implemented in Abaqus provides an effective and time-efficient approach for capturing viscoelastic behaviour and can be beneficial at an early stage of research.
Language: English
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W7128426357
FWCI:
Cites: 43
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