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IIT Mandi Pioneers Real Time Bridge Monitoring with Digital Modeling for Enhanced Safety and Resilience

This approach can potentially allow agencies to optimize budgets, target high-risk areas, and make faster decisions in emergencies, enhancing public safety

MANDI, 12th September 2024: Indian Institute of Technology Mandi Research team led by Dr. Subhamoy Sen, Associate Professor, School of Civil and Environmental Engineering, has developed an innovative method to monitor the health of aging bridges using traffic data. This approach zeroes in on the most vulnerable parts of a bridge, significantly enhancing safety and efficiency.

Dr. Subhamoy Sen, along with his research scholar, Mr. Eshwar Kuncham, has addressed the challenges of fatigue-induced damage and gradual deterioration of bridges by focusing on the most critical areas rather than monitoring the entire structure. Their research has been published in the prestigious journal, Structural Health Monitoring.

This innovative approach develops a digital model of the bridge—a detailed virtual replica based on an initial study of the actual structure. This model predicts how different traffic patterns impact various parts of the bridge over time, helping experts identify the areas most susceptible to damage.

After pinpointing these critical zones, fatigue-sensitive sensors are installed at key locations to monitor stress and vibrations. This real-time data, combined with traffic patterns from the digital model, allows experts to track how traffic affects the bridge over time. If necessary, adjustments to traffic flow and speed can be made to ensure the bridge’s safety and prevent damage.

Bridges endure various cyclic loads throughout their lifetimes, including traffic, wind, and environmental conditions. Over time, these repeated stresses can weaken the integrity of the structures, leading to potential catastrophic failures. Addressing fatigue in bridges is therefore essential, prompting significant advancements in engineering research to predict and prevent such failures.

Traditionally, assessing a bridge's Remaining Useful Life (RUL) involved simplistic methods with broad safety margins, which were not always accurate. Later advancements, such as rain flow counting and finite element analysis (FEA), provided a more detailed understanding of stress and fatigue. Recently, statistical approaches and machine learning have further refined these predictions. However, these methods can be costly, require extensive equipment, and may still overlook hidden issues, particularly in older bridges with uncertain material conditions.

Highlighting the practical benefits of his research, Dr. Subhamoy Sen said, "Our approach focuses on monitoring only the critical zones of a bridge, significantly reducing costs and the need for extensive equipment. By leveraging traffic data, we provide real-time assessments and make timely interventions, ensuring bridge safety and longevity without major traffic disruptions."

This method also allows for rapid assessments after events like earthquakes or floods, aiding officials in making quicker safety decisions. Once the initial setup is complete, regular monitoring can be handled by less specialized personnel, further reducing costs and making it easier to apply to multiple bridges.

For government agencies and transportation departments, this approach offers a practical and efficient solution for managing aging infrastructure. It enables more effective budget allocation by focusing on high-risk areas rather than the entire bridge and supports faster decision-making in emergencies, enhancing public safety. Additionally, it minimizes the need for extensive and disruptive traffic management during inspections, reducing inconvenience for commuters.

Video Byte -https://drive.google.com/drive/u/0/folders/1I5EzB1pzQLCeNQwBbVyzAiwz3vZ05zta

 

About IIT Mandi

IIT Mandi comprises nine academic schools and seven major research centers. The schools include the School of Biosciences and Bioengineering (SBBE), School of Chemical Sciences (SCS), School of Mathematical and Statistical Sciences (SMSS), School of Physical Sciences (SPS), School of Mechanical and Materials Engineering (SMME), School of Civil and Environmental Engineering (SCENE), School of Computing and Electrical Engineering (SCEE), School of Humanities and Social Sciences (SHSS), and School of Management (SOM). The research centers are the Advanced Materials Research Centre (AMRC), Centre for Design and Fabrication of Electrical Devices (C4DFED), BioX Centre, Indian Knowledge System and Mental Health Applications Centre (IKSMHA Centre), Centre for Artificial Intelligence and Robotics (CAIR), Centre for Quantum Science and Technology (CQST), and Centre for Human, Computer Interaction (CHCi).

The Institute offers eleven undergraduate programs across various streams, one M.A. program, ten M.Tech. programs, eleven Ph.D. programs, and one integrated Ph.D. (iPh.D.) program. The unique, project-oriented B.Tech. curriculum is centered around a 4-year Design and Innovation stream. Since its inception, IIT Mandi has been involved in over 460 R&D sponsored research projects and more than 150 consultancy projects.

The Institute houses the DST-sponsored IIT Mandi iHub and HCI Foundation (iHub; a Section-8 company) to promote research and technology development, skill development, startup innovation, and collaborations in the HCI and allied AI/ML areas in India. Additionally, IIT Mandi Catalyst, the first tech-incubator in Himachal Pradesh, offers a low-cost, peaceful, and high-tech environment for early-stage startups. Furthermore, a BIRAC-sponsored BioNEST Centre has been established at the Institute to foster biotechnology and healthcare innovation in the Himalayan region.

Twitter: @iit__mandi

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Website: https://www.iitmandi.ac.in

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