The economic case for service life extension of structures using structural health monitoring based on the delayed cost of borrowing

The economic case for extending the service life of structures using the combination of testing and structural health monitoring (SHM) is very strong. In the USA, it is estimated that there are 70,000 structurally deficient bridges. Surprisingly, 12,000 have no deficiency other than a low load rating, with only six reported to have a rating based on load testing. Bridges that are load tested are often, but not always, found to have higher load capacity than estimated by analysis. The underestimate of capacity may stem from the careful application of safety margins due to uncertainty about materials and construction. It may also stem from over simplified structural analysis, inaccurate modeling of boundary conditions and the load bearing capacity of “non-structural” elements, as observed in the Swiss bridge system. However, once results from testing are available, it is the updated estimate of the capacity that is the most appropriate to use. Therefore, one can conclude that the service life of many structures could be extended through testing to ensure capacity and the application of monitoring to ensure on-going capacity and safety. The economic return of extending service life in this manner is very high as the yearly borrowing minus the inflation rate cost for even modest structures significantly exceeds the cost of typical SHM system. Application to new structures or major rehabilitation is more challenging, as the value is discounted by the compounded borrowing rate minus the inflation rate over several decades. As a result for new structures, the capital cost and the decades of operating cost of the SHM system need to be <1 % of the structure cost.

[1]  Songye Zhu,et al.  Long‐term condition assessment of suspenders under traffic loads based on structural monitoring system: Application to the Tsing Ma Bridge , 2012 .

[2]  Dan M. Frangopol,et al.  A probabilistic computational framework for bridge network optimal maintenance scheduling , 2011, Reliab. Eng. Syst. Saf..

[3]  Cheryl Surman,et al.  Battery-free radio frequency identification (RFID) sensors for food quality and safety. , 2012, Journal of agricultural and food chemistry.

[4]  Olivier Burdet,et al.  Load Testing and Monitoring of Swiss Bridges , 1993 .

[5]  Jinping Ou,et al.  Corrosion monitoring of reinforcing steel in cement mortar by EIS and ENA , 2007 .

[6]  Sharon L. Wood,et al.  Low-cost passive sensors for monitoring corrosion in concrete structures , 2011, Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[7]  John P. Hart,et al.  Recent developments in the design and application of screen-printed electrochemical sensors for biomedical, environmental and industrial analyses , 1997 .

[8]  J. Mills-Beale,et al.  A Wireless, Passive Embedded Sensor for Real-Time Monitoring of Water Content in Civil Engineering Materials , 2008, IEEE Sensors Journal.

[9]  Andrzej S. Nowak,et al.  PROOF LOAD TESTING OF HIGHWAY BRIDGES , 1996 .

[10]  Dan M. Frangopol,et al.  Cost-Effective Lifetime Structural Health Monitoring Based on Availability , 2011 .

[11]  Greg E. Bridges,et al.  Inductively coupled corrosion potential sensor for steel reinforced concrete with time domain gating interrogation , 2012, Smart Structures.

[12]  Jonathan P. Metters,et al.  Paper-based electroanalytical sensing platforms , 2013 .

[13]  Radislav A. Potyrailo,et al.  RFID sensors based on ubiquitous passive 13.56-MHz RFID tags and complex impedance detection , 2009 .

[14]  Kevin L. Rens,et al.  Bridge Management and Nondestructive Evaluation , 2005 .

[15]  B. Carkhuff,et al.  Corrosion sensors for concrete bridges , 2003 .

[16]  Baidar Bakht,et al.  BRIDGE TESTING - A SURPRISE EVERY TIME , 1990 .

[17]  Greg E. Bridges,et al.  A wireless embedded passive sensor for monitoring the corrosion potential of reinforcing steel , 2013 .

[18]  Yang Wang,et al.  Performance monitoring of the Geumdang Bridge using a dense network of high-resolution wireless sensors , 2006, Smart Materials and Structures.