OPEN ACCESS
Explosive terrorist attacks targeting critical buildings and infrastructure systems pose a formidable threat worldwide, having caused 12,425 casualties and $20 billion in direct economic losses in 2015 alone. Designers of these critical buildings attempt to minimize the security risks to site personnel and buildings by analyzing and selecting the most effective combination of: (1) increasing the standoff distance between site assets and potential locations of explosive attacks; (2) constructing blast-mitigating perimeter walls; and (3) hardening site facilities. To support designers in this critical and challenging task, this paper presents the development of a multi-objective optimization model capable of generating optimal tradeoffs between minimizing total site destruction levels and minimizing site construction costs. The model com- putations are performed utilizing the nondominated sorting genetic algorithm II (NSGA-II) because of its proven capability in modeling non-linear objective functions and constraints, and its successful modeling of previous facility layout problems. The model performance was evaluated using a case study of a hypo- thetical military forward operating base, and the results illustrated the novel capabilities of the developed model in identifying design configurations that generate optimal tradeoffs between the aforementioned optimization objectives. These capabilities are expected to support designers in their ongoing efforts to construct cost-effective sites that minimize the security risks to personnel and buildings from the threat of explosive terrorist attacks.
blast effects, blast wall, critical infrastructure, facility layout, genetic algorithms, optimization, security
[1] Hunter, R.J., Perkins, explosive states: AOAV’s Explosive Violence Monitor 2014, AOAV, available at https://aoav.org.uk/2014/aoav-explosive-violence-data-2014/, 2015, (accessed 28 January 2016).
[2] Institute for Economics and Peace, 2015 Global terrorism impact: measuring and understanding the impact of terrorism, IEP, available at http://economicsandpeace. org/wp-content/uploads/2015/11/2015-Global-Terrorism-Index-Report.pdf, 2015, (accessed 12 December 2015).
[3] Federal Emergency Management Agency (FEMA), Reference manual to mitigate potential terrorist attacks against buildings, FEMA-426BIPS-06 Ed. 2. Washington, DC, 2011.
[4] Department of Defense (DoD), DoD minimum antiterrorism standards for buildings, UFC 4-010-01. Washington, DC, 2012.
[5] Rose, T.A., Smith, P.D. & Mays, G.C., The effectiveness of walls designed for the protection of structures against airblast from high explosives. Proceedings of the Institution of Civil Engineers - Structures and Buildings, 110, pp. 78–85, 1995. https://doi.org/10.1680/istbu.1995.27306
[6] Rose, T.A., Smith, P.D. & Mays, G.C., Protection of structures against airburst using barriers of limited robustness. Proceedings of the Institution of Civil Engineers - Structures and Buildings, 128, pp. 167–176, 1998. http://dx.doi.org/10.1680/istbu.1998.30123
[7] Beyer, M.E., Blast loads behind vertical walls, DTIC Document, 1986, available at: http://oai.dtic.mil/oai/oai?verb=getRecord&metadataPrefix=html&identifier=ADP005331 (accessed 29 January 2016).
[8] Scherbatiuk, K. & Rattanawangcharoen, N., Experimental testing and numerical modeling of soil-filled concertainer walls. Engineering Structures, 30, pp. 3545–3554, 2008. https://doi.org/10.1016/j.engstruct.2008.05.030
[9] Bogosian, D. & Piepenburg, D., Effectiveness of frangible barriers for blast shielding. In Proc. 17th Int. Symp. Mil. Asp. Blast Shock, Las Vegas, Nevada, USA, 2002.
[10] Chen, L., Zhang, L., Fang, Q. & Mao, Y., Performance based investigation on the construction of anti-blast water wall. International Journal of Impact Engineering, 81, pp. 17–33, 2015. https://doi.org/10.1016/j.ijimpeng.2015.03.003
[11] Khalafallah, A. & El-Rayes, K., Minimizing construction-related security risks during airport expansion projects. Journal of Construction Engineering and Management, 134, pp. 40–48, 2008. http://dx.doi.org/10.1061/(ASCE)0733-9364(2008)134:1(40)
[12] Said, H. & El-Rayes, K., Optimizing the planning of construction site security for critical infrastructure projects. Automation in Construction, 19, pp. 221–234, 2010. https://doi.org/10.1016/j.autcon.2009.10.005
[13] Li, Z., Shen, W., Xu, J. & Lev, B., Bilevel and multi-objective dynamic construction site layout and security planning. Automation in Construction, 57, pp. 1–16, 2015. https://doi.org/10.1016/j.autcon.2015.04.011
[14] Deb, K., Pratap, A., Agarwal, S. & Meyarivan, T., A fast and elitist multiobjective genetic algorithm: NSGA-II. Evolutionary Computation, 6, pp. 182–197, 2002. https://doi.org/10.1109/4235.996017
[15] Schuldt, S. & El-Rayes, K., Quantifying blast effects on constructed facilities behind blast walls. Journal of Performance of Constructed Facilities, 31(4), 2017. http://dx.doi.org/10.1061/(ASCE)CF.1943-5509.0001015
[16] U.S. Army Corps of Engineers (USACE), Estimating damage to structures from terrorist bombs field operations guide, ETL 1110-3-495. Washington, DC, 1999.
[17] Khalafallah, A.M., Assessing the performance of the non-dominated sorting genetic algorithm in optimizing construction site planning. Computing in Civil and Building Engineering, 2014, pp. 1254–1261, 2014. http://dx.doi.org/10.1061/9780784413616.156
[18] U.S. Army Corps of Engineers (USACE), DoD Area Cost Factor, available at http://www.usace.army.mil/Cost-Engineering/Programming-Administration-and-Execution-SystemNe/, 2016 (accessed 21 February 2017).