Strong localized downbursts generated in thunderstorms can produce surface winds very dangerous for civil structures and infrastructures. Modelling and simulating such severe wind systems is therefore extremely important for structural safety and design wind speed evaluation. This paper deals with the downburst wind field simulation by means of an optimization algorithm that uses a downburst analytical model, previously developed by the authors, and two metaheuristic algorithms, namely the Differential Evolution (DE) and the Teaching-Learning-Based Optimization (TLBO), for the downburst kinematic and geometrical parameters evaluation. The optimization problem minimizes the relative error between recorded and simulated wind speed and direction time histories. A comparison is made between the performance of two algorithms for ten thunderstorm events measured in north-western Italy between October 2011 and October 2015. Both algorithms provide solutions which are coherent with the downburst parameters values present in literature. TLBO outperforms DE since it has a faster convergence rate to the optimal solution.

Application of metaheuristic optimization algorithms to evaluate the geometric and kinematic parameters of downbursts

Andi Xhelaj;Massimiliano Burlando
2022-01-01

Abstract

Strong localized downbursts generated in thunderstorms can produce surface winds very dangerous for civil structures and infrastructures. Modelling and simulating such severe wind systems is therefore extremely important for structural safety and design wind speed evaluation. This paper deals with the downburst wind field simulation by means of an optimization algorithm that uses a downburst analytical model, previously developed by the authors, and two metaheuristic algorithms, namely the Differential Evolution (DE) and the Teaching-Learning-Based Optimization (TLBO), for the downburst kinematic and geometrical parameters evaluation. The optimization problem minimizes the relative error between recorded and simulated wind speed and direction time histories. A comparison is made between the performance of two algorithms for ten thunderstorm events measured in north-western Italy between October 2011 and October 2015. Both algorithms provide solutions which are coherent with the downburst parameters values present in literature. TLBO outperforms DE since it has a faster convergence rate to the optimal solution.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1095187
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 1
social impact