Incoming windblown sand drift to civil infrastructures: A probabilistic evaluation. Issue 166 (July 2017)

• Record Type: Journal Article
• Authors: Raffaele, Lorenzo; Bruno, Luca; Fransos, Davide; Pellerey, Franco
• Is Part Of: Journal of wind engineering and industrial aerodynamics. Issue 166(2017)
• Page Start: 37
• Page End: 47
• Publication Date: 2017-07
• Subjects: Windblown sand -- Drift potential -- Uncertainty quantification -- Probabilistic approach -- Monte Carlo; Wind-pressure -- Periodicals; Buildings -- Aerodynamics -- Periodicals; Pression du vent -- Périodiques; Constructions -- Aérodynamique -- Périodiques; Buildings -- Aerodynamics; Wind-pressure; Periodicals
• DOI: 10.1016/j.jweia.2017.04.004
• Languages: English
• ISSNs: 0167-6105

Abstract

Abstract: The accurate prediction of windblown sand drift events approaching human infrastructures and activities is fundamental in arid lands. In both scientific literature and technical practice sand drift estimation is carried out in mean terms. Typically, sand drift net direction and intensity are assessed by means of the resultant drift potential. However, windblown sand suffers a number of epistemic and aleatory uncertainties, related to both the wind and the sand fields. The windblown sand drift estimation in probabilistic terms is useful in the infrastructure design perspective and allows to obtain characteristic values of windblown sand transport. In this study windblown sand is considered as an environmental action in analogy to wind action. Several uncertainties involved in the phenomenon are considered: threshold shear velocity and 10-min average wind velocity are assumed as random variables. Monte Carlo approach is adopted within a bootstrapping technique in order to assess sand drift in probabilistic terms. The proposed approach is applied to five sites in the Arabian Peninsula. Directional statistics of the sand drift are given for each site. Abstract : Highlights: Probabilistic approach to incoming windblown sand drift is proposed. Probabilistic approach is applied to five sites in Arabian Peninsula. Uncertainty propagation from input random variables to final results is assessed. Complex wind regimes are prone to cause sand drift with high variability. Characteristics values of sand drift are useful for infrastructure design.