IIT Mandi Unveils Revolutionary Bridge Monitoring Method To Boost Safety & Efficiency

IIT Mandi's new bridge monitoring method, led by Dr. Subhamoy Sen, uses traffic data to target vulnerable sections, enhancing safety and efficiency while cutting costs and reducing disruptions.

Mandi: The Indian Institute of Technology Mandi research team, led by Dr. Subhamoy Sen, Associate Professor at the School of Civil and Environmental Engineering, has pioneered a cutting-edge method to monitor the health of aging bridges using traffic data. This technique hones in on the most vulnerable sections of a bridge, significantly improving safety and efficiency.

Dr. Sen and his research scholar, Mr. Eshwar Kuncham, have tackled the issues of fatigue-induced damage and gradual deterioration by concentrating on critical areas rather than monitoring the entire bridge. Their findings have been published in the renowned journal, Structural Health Monitoring.

Their approach involves creating a digital model of the bridge—a detailed virtual replica based on an initial assessment of the actual structure. This model forecasts how varying traffic patterns impact different parts of the bridge over time, allowing experts to identify the most vulnerable zones.

Once these critical areas are identified, fatigue-sensitive sensors are placed at strategic locations to monitor stress and vibrations. Real-time data from these sensors, combined with traffic patterns from the digital model, enables continuous tracking of how traffic affects the bridge. Adjustments to traffic flow and speed can be implemented to prevent damage and maintain safety.

Bridges experience numerous cyclic loads over their lifetimes, including traffic, wind, and environmental conditions, which can weaken their integrity over time and lead to potential failures. Addressing these fatigue issues is crucial, driving advancements in engineering research aimed at predicting and preventing such failures.

Previously, assessing a bridge's Remaining Useful Life (RUL) relied on broad safety margins and simplistic methods. Advancements like rain flow counting and finite element analysis (FEA) offered more detailed insights into stress and fatigue. Recent innovations, including statistical approaches and machine learning, have refined these predictions, though they can be costly and may still miss hidden issues in older bridges.

Dr. Sen emphasized the practical benefits of their research, stating, "Our method targets only the critical zones of a bridge, significantly cutting costs and reducing the need for extensive equipment. By utilizing traffic data, we provide real-time assessments and enable timely interventions, ensuring bridge safety and longevity while minimizing traffic disruptions."

This technique also facilitates swift assessments after events such as earthquakes or floods, allowing officials to make faster safety decisions. Once set up, regular monitoring can be managed by less specialized personnel, further reducing costs and making it feasible to apply to multiple bridges.

For government agencies and transportation departments, this approach provides a practical and efficient solution for managing aging infrastructure. It allows for more effective budget allocation by focusing on high-risk areas, supports quicker decision-making during emergencies, and reduces the need for extensive and disruptive traffic management during inspections, thus easing commuter inconvenience.

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