Sustainability key to a resilient society

Smart maintenance system to monitor and conduct simulations for infrastructure
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Kyoto, Japan -- Regular maintenance of infrastructure in society plays an important role in sustaining economic activities and protecting the safety of citizens.

A team of researchers at Kyoto University's Graduate School of Engineering has developed the predictive diagnosis maintenance system, which assesses the integrity of social infrastructure by detecting, monitoring, and simulating functional abnormalities. The system is in compliance with civil inspection aims and protocols.

"This technology is expected to become part of a large market globally and may help boost Japan's status in civil engineering," says group leader Kunitomo Sugiura.

While this field is gaining increasing attention among researchers, many issues remain such as noise in digital data which makes it challenging to detect slight structural changes for accurate assessments. Some of these changes are qualitatively assessed damage based on observed surface conditions such as cracking, spalling, and rust.

Roads and tunnels, river facilities, water and sewage systems, energy, and telecommunications are all examples of urban infrastructure facing significant reliability issues in the near future. Problems include deterioration and frequent damage resulting from natural disasters and climate change. As a case in point, the tragic February 2012 accident at Sasago Tunnel, Yamanashi Prefecture, prompted urgent nationwide inspections of many half-century-old structures.

"Our proposed technology can make evaluation of structures more accurate and reliable by correlating analog information with them, such as photographs and visual inspection results," adds corresponding author Chul-Woo Kim.

An advanced and robust social infrastructure is at the core of developing a maintenance and management system with forecasting technology using digital data, future deterioration and damage prediction models, and disaster simulation.

"Digital data can be shared with advanced distribution and automated driving systems, among others, aiming to solve existing issues through a bold paradigm shift," proposes Kazuo Takase.