Strain Decay Monitoring and Analytical Prediction of RC Columns Using Brillouin Optical Technology and Time-Dependent Deterioration Factor

This study presents a novel approach to the design and assessment of slender reinforced concrete (RC) columns by integrating Brillouin Optical Time Domain Analysis (BOTDA) for real-time, distributed strain monitoring and introducing a “time-dependent deterioration factor” strain decay (η_decay). Experimental tests on 200 mm × 200 mm RC columns with lengths of 1800 mm and slenderness ratios of 29.4, reinforced with four 12 mm bars, captured strain variations up to 400 microstrain under an axial load of 1200 kN, demonstrate BOTDA’s sensitivity and precision. Unlike conventional strain gauges, BOTDA provided a continuous strain profile along the column height, accurately capturing strain decay with a resolution exceeding 95%, enabling the detection of localized strain reductions often missed by traditional methods. The integration of η_decay into ACI 318 and Eurocode 2 models conservatively improved predictions, particularly for specimens tested with long-term testing (720 days), with experimental-to-predicted (E/P) ratios of 1.42 and 1.29, respectively, compared to higher discrepancies in the original codes. The η_decay factor accounts for strain reduction along the column height caused by time-dependent effects such as creep, shrinkage, and material degradation, significantly improving the accuracy of axial load capacity predictions. Finite element analysis (FEA) validated these improvements, showing good agreement with experimental data up to the yield load. Post-yield, the modified equations effectively addressed underestimations caused by microcracking, highlighting the necessity of η_decay for reliable long-term performance predictions. This research combines advanced BOTDA technology with an innovative η_decay framework, addressing long-term structural deterioration and refining design codes. It establishes a robust foundation for integrating time-dependent effects into predictive models, enhancing the resilience, safety, and sustainability of RC structures under real-world conditions.