Bayes Inference of Structural Safety under Extreme Wind Loads Based upon a Peak-Over-Threshold Process of Exceedances

In the present paper, the process of estimating the important statistical properties of extreme wind loads on structures is investigated by considering the effect of large variability. In fact, for the safety design and operating conditions of structures such as the ones characterizing tall building...

Full description

Bibliographic Details
Main Authors: Elio Chiodo, Fabio De Angelis, Bassel Diban, Giovanni Mazzanti
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Mathematical and Computational Applications
Subjects:
Online Access:https://www.mdpi.com/2297-8747/28/6/111
_version_ 1797380105470738432
author Elio Chiodo
Fabio De Angelis
Bassel Diban
Giovanni Mazzanti
author_facet Elio Chiodo
Fabio De Angelis
Bassel Diban
Giovanni Mazzanti
author_sort Elio Chiodo
collection DOAJ
description In the present paper, the process of estimating the important statistical properties of extreme wind loads on structures is investigated by considering the effect of large variability. In fact, for the safety design and operating conditions of structures such as the ones characterizing tall buildings, wind towers, and offshore structures, it is of interest to obtain the best possible estimates of extreme wind loads on structures, the recurrence frequency, the return periods, and other stochastic properties, given the available statistical data. In this paper, a Bayes estimation of extreme load values is investigated in the framework of structural safety analysis. The evaluation of extreme values of the wind loads on the structures is performed via a combined employment of a Poisson process model for the peak-over-threshold characterization and an adequate characterization of the parent distribution which generates the base wind load values. In particular, the present investigation is based upon a key parameter for assessing the safety of structures, i.e., a proper safety index referred to a given extreme value of wind speed. The attention is focused upon the estimation process, for which the presented procedure proposes an adequate Bayesian approach based upon prior assumptions regarding (1) the Weibull probability that wind speed is higher than a prefixed threshold value, and (2) the frequency of the Poisson process of gusts. In the last part of the investigation, a large set of numerical simulations is analyzed to evaluate the feasibility and efficiency of the above estimation method and with the objective to analyze and compare the presented approach with the classical Maximum Likelihood method. Moreover, the robustness of the proposed Bayes estimation is also investigated with successful results, both with respect to the assumed parameter prior distributions and with respect to the Weibull distribution of the wind speed values.
first_indexed 2024-03-08T20:33:31Z
format Article
id doaj.art-09bdc0ae94424ce297cc3503481e2bf1
institution Directory Open Access Journal
issn 1300-686X
2297-8747
language English
last_indexed 2024-03-08T20:33:31Z
publishDate 2023-11-01
publisher MDPI AG
record_format Article
series Mathematical and Computational Applications
spelling doaj.art-09bdc0ae94424ce297cc3503481e2bf12023-12-22T14:23:36ZengMDPI AGMathematical and Computational Applications1300-686X2297-87472023-11-0128611110.3390/mca28060111Bayes Inference of Structural Safety under Extreme Wind Loads Based upon a Peak-Over-Threshold Process of ExceedancesElio Chiodo0Fabio De Angelis1Bassel Diban2Giovanni Mazzanti3Department of Industrial Engineering, University of Naples Federico II, Via Claudio, 21, 80125 Napoli, ItalyDepartment of Structures for Engineering and Architecture, University of Naples Federico II, Via Claudio, 21, 80125 Napoli, ItalyDepartment of Electrical, Electronic and Information Engineering, University of Bologna, Viale del Risorgimento, 2, 40136 Bologna, ItalyDepartment of Electrical, Electronic and Information Engineering, University of Bologna, Viale del Risorgimento, 2, 40136 Bologna, ItalyIn the present paper, the process of estimating the important statistical properties of extreme wind loads on structures is investigated by considering the effect of large variability. In fact, for the safety design and operating conditions of structures such as the ones characterizing tall buildings, wind towers, and offshore structures, it is of interest to obtain the best possible estimates of extreme wind loads on structures, the recurrence frequency, the return periods, and other stochastic properties, given the available statistical data. In this paper, a Bayes estimation of extreme load values is investigated in the framework of structural safety analysis. The evaluation of extreme values of the wind loads on the structures is performed via a combined employment of a Poisson process model for the peak-over-threshold characterization and an adequate characterization of the parent distribution which generates the base wind load values. In particular, the present investigation is based upon a key parameter for assessing the safety of structures, i.e., a proper safety index referred to a given extreme value of wind speed. The attention is focused upon the estimation process, for which the presented procedure proposes an adequate Bayesian approach based upon prior assumptions regarding (1) the Weibull probability that wind speed is higher than a prefixed threshold value, and (2) the frequency of the Poisson process of gusts. In the last part of the investigation, a large set of numerical simulations is analyzed to evaluate the feasibility and efficiency of the above estimation method and with the objective to analyze and compare the presented approach with the classical Maximum Likelihood method. Moreover, the robustness of the proposed Bayes estimation is also investigated with successful results, both with respect to the assumed parameter prior distributions and with respect to the Weibull distribution of the wind speed values.https://www.mdpi.com/2297-8747/28/6/111Bayes estimationextreme value theorypeak-over-thresholdPoisson processeswind loads on structuresstructural safety analysis
spellingShingle Elio Chiodo
Fabio De Angelis
Bassel Diban
Giovanni Mazzanti
Bayes Inference of Structural Safety under Extreme Wind Loads Based upon a Peak-Over-Threshold Process of Exceedances
Mathematical and Computational Applications
Bayes estimation
extreme value theory
peak-over-threshold
Poisson processes
wind loads on structures
structural safety analysis
title Bayes Inference of Structural Safety under Extreme Wind Loads Based upon a Peak-Over-Threshold Process of Exceedances
title_full Bayes Inference of Structural Safety under Extreme Wind Loads Based upon a Peak-Over-Threshold Process of Exceedances
title_fullStr Bayes Inference of Structural Safety under Extreme Wind Loads Based upon a Peak-Over-Threshold Process of Exceedances
title_full_unstemmed Bayes Inference of Structural Safety under Extreme Wind Loads Based upon a Peak-Over-Threshold Process of Exceedances
title_short Bayes Inference of Structural Safety under Extreme Wind Loads Based upon a Peak-Over-Threshold Process of Exceedances
title_sort bayes inference of structural safety under extreme wind loads based upon a peak over threshold process of exceedances
topic Bayes estimation
extreme value theory
peak-over-threshold
Poisson processes
wind loads on structures
structural safety analysis
url https://www.mdpi.com/2297-8747/28/6/111
work_keys_str_mv AT eliochiodo bayesinferenceofstructuralsafetyunderextremewindloadsbaseduponapeakoverthresholdprocessofexceedances
AT fabiodeangelis bayesinferenceofstructuralsafetyunderextremewindloadsbaseduponapeakoverthresholdprocessofexceedances
AT basseldiban bayesinferenceofstructuralsafetyunderextremewindloadsbaseduponapeakoverthresholdprocessofexceedances
AT giovannimazzanti bayesinferenceofstructuralsafetyunderextremewindloadsbaseduponapeakoverthresholdprocessofexceedances