# The mechanism of hindering occupants’ evacuation from seismic responses of building

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## Abstract

Pedestrian evacuation from buildings during an earthquake needs to consider human behavior and building shaking. This study sets up an indoor evacuation model based on the social force and dynamic mechanics. First, social forces were formulated in the Eulerian coordinate system, seismic force that excites on pedestrians in a multi-story building is derived from structural acceleration, and an evacuation criterion is given based on above forces. Second, a simulation was performed through VB programming, which accounts for the situation that people evacuate from a walkway. Parameters of the social force model are modified in order to estimate pedestrians’ acceleration in concerned situation. Third, structural dynamic responses under a series of ground motion excitations with varying peak values are acquired through finite element analysis to determine pedestrians’ seismic forces. Then, pedestrians’ ability to escape safely is evaluated according to evacuation criterion. Results show that seismic force would increase when pedestrian located on higher floor or ground excitation is of more dramatic level. Additionally, the possibility of survival is likely minimized as long as seismic force is larger than social force. This proposed model is capable of describing the effects of environment on human behavior during earthquake evacuation.

## Keywords

Eulerian coordinate system Evacuation simulation Social forces Seismic force## Notes

### Acknowledgements

The writers wish to express their appreciation for the award of the National Natural Science Foundation of China (Grant 11461078).

## Supplementary material

## References

- Alexander DE (1990) Behavior during earthquakes: a southern Italian example. Int J disaster Reduct 8:5–29Google Scholar
- Amini HK, Hosseini M, Izadkhah YO, Mansouri B, Shaw T (2014) Main challenges on community-based approaches in earthquake risk reduction: case study of Tehran. Iran. Int J Disaster Risk Reduct 1:1–11Google Scholar
- Apatu EJI, Gregg CE, Lindell MK, Sorensen J, Hillhouse J, Sorensen B (2012) The September 29, 2009 earthquake and Tsunami in American Samoa: a case study of household evacuation behavior and the protective action decision model. EGU General Assembly 2012, held 22–27 April, 2012 in Vienna, Austria, p 101Google Scholar
- Arnold C, Eisner R, Durkin M, Whitaker D (1982) Occupant behavior in a six-storey office building following severe earthquake damage. Disasters 6:207–214CrossRefGoogle Scholar
- Bernardini G, Quagliarini E, D’Orazio M (2016) Towards creating a combined database for earthquake pedestrians’ evacuation models. Saf Sci 82:77–94CrossRefGoogle Scholar
- Burstedde C, Klauck K, Schadschneider A, Zittartz J (2001) Simulation of pedestrian dynamics using a two-dimensional cellular automaton. Phys A 295:507–525CrossRefGoogle Scholar
- Chopra AK (2009) Dynamics of structures: theory and application to earthquake engineering, 3rd edn. Tsinghua University Press, BeijingGoogle Scholar
- D’Orazio M, Bernardini G (2014) An experimental study on the correlation between ‘‘attachment to belongings” “pre-movement” time. In: Weidmann U, Kirsch U, Schreckenberg M (eds) Pedestrian and evacuation dynamics 2012. Springer, Cham, pp 167–178CrossRefGoogle Scholar
- D’Orazio M, Quagliarini E, Bernardini G, Spalazzi L (2014a) EPES—earthquake pedestrians’ evacuation simulator: a tool for predicting earthquake pedestrians’ evacuation in urban outdoor scenarios. Int J Disaster Risk Reduct 10:153–177CrossRefGoogle Scholar
- D’Orazio M, Spalazzi L, Quagliarini E, Bernardini G (2014b) Agent-based model for earthquake pedestrians’ evacuation in urban outdoor scenarios: behavioural patterns definition and evacuation paths choice. Saf Sci 62:450–465CrossRefGoogle Scholar
- Ferlito R, Pizza AG (2011) A seismic vulnerability model for urban scenarios. Quick method for the evaluation of roads vulnerability in case of emergency (Modello di vulnerabilità di un centro urbano. Metodologia per la valutazione speditiva della vulnerabilità della viabilità d’em). Ing Sism 4:31–43Google Scholar
- Goretti A, Sarli V (2006) Road network and damaged buildings in urban areas: short and long-term interaction. Bull Earthq Eng 4:159–175CrossRefGoogle Scholar
- Gu Z, Liu Z, Shiwakoti N, Yang M (2016) Video-based analysis of school students’ emergency evacuation behavior in earthquakes. Int J Disaster Risk Reduct. https://doi.org/10.1016/j.ijdrr.2016.05.008 CrossRefGoogle Scholar
- Guo R, Huang HJ (2008) A mobile lattice gas model for simulating pedestrian evacuation. Phys A 387:580–586CrossRefGoogle Scholar
- Harada Y, Hokugo A, Sekizawa A, Kakegawa S (2008) A study on earthquake evacuation from buildings considering furniture tipping. In: Proceedings of the 2008 JAFSE annual symposium, pp 46–49Google Scholar
- Helbing D, Molnar P (1995) Social force model for pedestrian dynamics. Phys Rev E 51:4282–4286CrossRefGoogle Scholar
- Helbing D, Farkas I, Vicsek T (2000) Simulating dynamical features of escape panic. Nature 407:487–490CrossRefGoogle Scholar
- Helbing D, Johansson A, Al-Abideen HZ (2007) Dynamics of crowd disasters: an empirical study. Phys Rev E 75(4):046–109CrossRefGoogle Scholar
- Hoogendoorn S (2003) Extracting microscopic pedestrian characteristics from video data. Transp Res Board 2003:1–15Google Scholar
- Hori M (2011) Introduction to computational earthquake engineering, 2nd edn. Imperial College Press, LondonCrossRefGoogle Scholar
- Klügel JU (2008) Seismic hazard analysis—quo vadis. Earth Sci Rev 88:1–32CrossRefGoogle Scholar
- Lakoba TI, Kaup DJ, Finkelstein NM (2005) Modifications of the Helbing–Molnar–Farkas–Vicsek social force model for pedestrian evolution. Simulation 81:339–352CrossRefGoogle Scholar
- Li M, Zhao Y, He L et al (2015) The parameter calibration and optimization of social force model for the real-life 2013 Ya’an earthquake evacuation in China. Saf Sci 79:243–253CrossRefGoogle Scholar
- Liu H, Cui X, Yuan D, Wang Z, Jin J, Wang M (2011) Study of earthquake disaster population risk based on GIS a case study of Wenchuan earthquake region. Proc Environ Sci 11:1084–1091CrossRefGoogle Scholar
- Mas E, Suppasri A, Imamura F, Koshimura S (2012) Agent-based simulation of the 2011 great east japan earthquake/tsunami evacuation: an integrated model of tsunami inundation and evacuation. J Nat Disaster Sci 34(1):41–57CrossRefGoogle Scholar
- Mazzon R, Cavallaro A (2013) Multi-camera tracking using a multi-goal social force model. Neuro-computing 100:41–50Google Scholar
- Tai CA, Lee YL, Lin CY (2011) A model of choice in earthquake evacuation. Adv Comput Control (ICACC) 27:228–233Google Scholar
- Van Truong H, Beck E, Dugdale J, Adam C (2013) Developing a model of evacuation after an earthquake in Lebanon. Comput Sci 1:1312–1320Google Scholar
- Weidmann U (1992) Transport technik der fussgänger. Institut fur Verkchrs planung, ZurichGoogle Scholar
- Xiao ML, Chen Y, Yan MJ, Ye LY, Liu BY (2016) Simulation of household evacuation in the 2014 Ludian earthquake. Bull Earthq Eng 14:1757–1769CrossRefGoogle Scholar
- Xu T (1982) Similarity theory and model test. Agricultural Machinery Press, BeijingGoogle Scholar
- Yang X, Wu Z, Li Y (2011) Difference between real-life escape panic and mimic exercises in simulated situation with implications to the statistical physics models of emergency evacuation: The 2008 Wenchuan earthquake. Physica A 390:2375–2380CrossRefGoogle Scholar
- Ye M, Wang J, Huang J, Xu S, Chen Z (2011) Methodology and its application for community-scale evacuation planning against earthquake disaster. Nat Hazards 61:881–892CrossRefGoogle Scholar
- Yun NY, Hamada M (2014) Evacuation behavior and fatality rate of residents during the 2011 Great East Japan earthquake and tsunami. Earthq Spectra 8:169–185Google Scholar
- Zhang J, Song W, Xu X (2008) Experiment and multi-grid modeling of evacuation from a classroom. Physica A 387(23):5901–5909CrossRefGoogle Scholar