Probabilistic assessment of the occupant load density in retail buildings |
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Affiliation: | 1. Institute of Structural Engineering ETH, Zurich, Switzerland;2. Department of Structural Engineering NTNU, Trondheim, Norway;1. Department of Mechanical and Aerospace Engineering, The University of Alabama in Huntsville, Huntsville, AL 35899, USA;2. US Army Aviation and Missile Research, Development, and Engineering Center (AMRDEC), Redstone Arsenal, AL 35898, USA;1. Dept. of Structural Engineering, Norwegian University of Science & Technology, Richard Birkelands vei 1A, 7491 Trondheim, Norway;2. University of Applied Science Augsburg, Institut für Holzbau, An der Hochschule 1, 86161 Augsburg, Germany;1. Structural Engineering Department, EESC, University of São Paulo, Av. Trabalhador Sancarlense, 400, São Carlos, SP, Brazil;2. Federal University of Technology of Parana, Av. 7 de setembro, 3165 Curitiba, PR, Brazil |
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Abstract: | The occupant load density is a crucial parameter for the design of the means of egress in buildings. In retail buildings the occupant load density is highly influenced by the individual?s choice and the necessity of a person to visit the store. This causes a high variability of the occupant load density in time. An accurate representation of this variability will provide a basis for enhancing fire safety design. In this paper, a probabilistic approach is used to describe the variability of the occupant load density over a year, based on long-term data of customer frequencies in combination with methods from the queuing theory the distribution of the occupant load density is derived for four different types of retail chains. It is shown that the type of a retail chain has a large influence on the distribution of the occupant load density and that the exceedance probability of current design values in different standards is very small. A method is proposed to derive design values for a performance based design on the basis of probabilistic models for the occupant load density. In addition, the developed probabilistic models describing the number of occupants in a store, allow the assessment of the occupant load density for other types of retail chains, even with incomplete data. |
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Keywords: | Occupant load density Probabilistic modeling Queuing theory Design value Data analysis Statistics |
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