Pasityothin Ittipon, Thansirichaisree Phromphat, Buatik Apichat, Imjai Thanongsak, Sridhar Radhika, Garcia Reyes, Noguchi Takafumi
Research Unit of Infrastructure Inspection, Monitoring, Repair and Strengthening, Thammasat School of Engineering, Faculty of Engineering, Thammasat University, Pathumthani 12121, Thailand.
School of Engineering and Technology, Walailak University, Nakhon Si Thammarat 80160, Thailand.
Sensors (Basel). 2025 Jan 26;25(3):741. doi: 10.3390/s25030741.
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). 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 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 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 for reliable long-term performance predictions. This research combines advanced BOTDA technology with an innovative η 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.
本研究提出了一种设计和评估细长钢筋混凝土（RC）柱的新方法，该方法集成了用于实时分布式应变监测的布里渊光时域分析（BOTDA），并引入了“时变劣化因子”应变衰减（η）。对尺寸为200 mm×200 mm、长度为1800 mm、长细比为29.4且配有四根12 mm钢筋的RC柱进行了试验，在1200 kN轴向荷载下捕捉到高达400微应变的应变变化，证明了BOTDA的灵敏度和精度。与传统应变片不同，BOTDA沿柱高提供了连续的应变分布，以超过95%的分辨率准确捕捉应变衰减，能够检测到传统方法常常遗漏的局部应变减小。将η纳入美国混凝土学会（ACI）318和欧洲规范2模型中保守地改进了预测结果，特别是对于长期试验（720天）的试件，试验值与预测值（E/P）之比分别为1.42和1.29，相比原始规范中更高的差异。η因子考虑了由徐变、收缩和材料劣化等时变效应引起的沿柱高的应变减小，显著提高了轴向承载力预测的准确性。有限元分析（FEA）验证了这些改进，在屈服荷载之前与试验数据显示出良好的一致性。屈服后，修正后的方程有效地解决了由微裂缝导致的低估问题，突出了η对于可靠的长期性能预测的必要性。本研究将先进的BOTDA技术与创新的η框架相结合，解决了长期结构劣化问题并完善了设计规范。它为将时变效应纳入预测模型奠定了坚实基础，增强了RC结构在实际条件下的恢复力、安全性和可持续性。
