Sustainable Design of Smart Health Facilities in Seismically Prone Areas

Abstract:

Safety ofhealth facilities (hospitals) is only partially related to the performance ofprimary structural members. Modern seismic codes provide strict requirements toboth structural and non-structural components, since the latterare alsocritical to ensure that the system remains fully operational in the case offrequent earthquakes. Thus, performance and safety checks apply also to electro-mechanicaland medical equipment,elevators, tanks, power supply systems, distributionsystems, heating, ventilation and air-conditioning systems.In the present paperattention is focusedon the analysis of the factors which make health facilities vulnerable and onthe issues related to a rational and objective assessment of performance andhealth state of structural and non-structural components. This is not a trivialtask, since functions and resilience of the system as a whole depend also onthe ability of inspectors and managers to integrate theoretical evaluationswith field measurements and their physical meaning.In this context, strategies and recommendations for a sustainableimplementation of Smart Health Facilities, which fulfilAtoE characteristics (Accuracy, Budget compliance, Computational burden,Durability, Ease of use)on a long term basis, are discussed, taking into account the specific requirementsand characteristics of the different subsystems in a hospital.

• Periodical: Key Engineering Materials (Volumes 569-570)
• Pages: 278-285
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.569-570.278
• Online since: July 2013
• Authors: Carlo Rainieri, Giovanni Fabbrocino
• Keywords: Health Facilities, Non-Structural Components, Operational Limit State, SHM Sustainability

References

[1] PAHO, Hospital Safety Index – Guide for Evaluators, Washington, USA, (2008).

[2] WHO – Regional Office for Europe, Health facility seismic vulnerability evaluation – a handbook, Copenhagen, Denmark, (2006).

[3] G.S. Trendafiloski, GIS-oriented method for development of probabilistic earthquake scenarios, Institute of Earthquake Engineering and Engineering Seismology, Skopje, Macedonia, (2003).

[4] K. Lang, Seismic vulnerability of existing buildings, Institute of Structural Engineering, Swiss Federal Institute of Technology, Zurich, Switzerland, (2002).

[5] Ministero della Salute, Raccomandazioni per il miglioramento della sicurezza sismica e della funzionalità degli ospedali, Rome, Italy, (2003).

[6] ATC 51-1, Recommended U.S. – Italy collaborative procedures for earthquake emergency response planning for hospitals in Italy. APPLIED TECHNOLOGY COUNCIL, Redwood City, USA, (2002).

[7] ATC 51-2, Recommended U.S. – Italy collaborative guidelines for bracing and anchoring non-structural components in Italian hospitals. APPLIED TECHNOLOGY COUNCIL, Redwood City, USA, (2003).

[8] C. Rainieri, G. Fabbrocino, E. Cosenza, Integrated seismic early warning and structural health monitoring of critical civil infrastructures in seismically prone areas, Structural Health Monitoring – An International Journal 10(2010) 291-308.

DOI: 10.1177/1475921710373296

[9] C. Klowak, E. Rivera, A. Mufti, Implementation of civionics in a second generation steel-free bridge deck, Proceedings SPIE – The International Society For Optical Engineering, (2005).

DOI: 10.1117/12.604903

[10] S.W. Doebling, C.R. Farrar, M.B. Prime, D.W. Shevitz, Damage Identification and Health Monitoring of Structural and Mechanical Systems from Changes in their Vibration Characteristics: A Literature Review, Technical Report LA-13070-MS, UC-900, Los Alamos National Laboratory, New Mexico 87545, USA, (1996).

DOI: 10.2172/249299

[11] C. Rainieri, G. Fabbrocino, Automated output-only dynamic identification of civil engineering structures, Mechanical Systems and Signal Processing 24(2010) 678-695.

DOI: 10.1016/j.ymssp.2009.10.003

[12] C. Rainieri, G. Fabbrocino, E. Cosenza, Near real-time tracking of dynamic properties for standalone structural health monitoring systems, Mechanical Systems and Signal Processing 25(2011) 3010-3026.

DOI: 10.1016/j.ymssp.2011.04.010

[13] V. Lämsä, J. Kullaa, Data Normalization with Partially Measured Environmental or Operational Variables, Proc. of the 4th European Workshop on SHM, Cracow, Poland, (2008).

[14] A. Widodo, B. -S. Yang, Support vector machine in machine condition monitoring and fault diagnosis, Mechanical Systems and Signal Processing 21(2007) 2560–2574.

DOI: 10.1016/j.ymssp.2006.12.007