Hybrid Diagnostic Analysis of RCC Cracks: Integrating Field Experience with Statistical Validation

Cracking in Reinforced Cement Concrete (RCC) structures is a multifaceted phenomenon that reflects both superficial flaws and deeper structural vulnerabilities. In rapidly urbanizing regions such as India, the limitations of conventional diagnostic methods—either highly codified visual inspections or resource-intensive laboratory tests—underscore the need for a more adaptable, field-grounded approach. This study presents a hybrid analysis framework that integrates qualitative insights from seasoned engineers with quantitative validation through statistical tools to evaluate crack patterns across forty RCC structures in Tamil Nadu and Karnataka. The methodology incorporates a two-tiered approach: field interviews with engineers offering contextual interpretation of crack orientation, width, recurrence, and severity, and empirical checklists subjected to chisquare and Cramér’s V testing. The results establish statistically significant associations between crack severity and structural risk levels, with high-severity cracks predominantly observed in buildings with inadequate drainage and plinth protection. A Severity–Integrity Matrix is developed to operationalize this relationship and support early-stage, site-sensitive diagnosis. This hybrid analytical model enhances both predictive reliability and field applicability. It demonstrates that when structured observational tools are interpreted through expert knowledge and statistically tested, they offer a scalable, low-tech, and contextsensitive diagnostic aid for practitioners. The study contributes a practically deployable model that strengthens structural assessment protocols while accommodating the complex realities of RCC behaviour on-site.