Wind simulation in the context of ships motions is used to estimate the effect of the wind on large containerships, sailboats and yachts. Wind models are typically based on a sum of harmonics with random phases and different amplitudes. In this paper we propose to use autoregressive model to simulate the wind. This model is based on autocovariance function that can be estimated from the real-world data collected by anemometers. We have found none of the data that meets our resolution requirements, and decided to produce the dataset ourselves using three-axis anemometer. We built our own anemometer based on load cells, collected the data with the required resolution, verified the data using well-established statistical distributions, estimated autocovariance functions from the data and simulated the wind using autoregressive model. We have found that the load cell anemometer is capable of recording wind speed for statistical studies, but autoregressive model needs further calibration to reproduce the wind with the same statistical properties.

Original languageEnglish
Title of host publicationComputational Science and Its Applications – ICCSA 2021 - 21st International Conference, Proceedings
EditorsOsvaldo Gervasi, Beniamino Murgante, Sanjay Misra, Chiara Garau, Ivan Blečić, David Taniar, Bernady O. Apduhan, Ana Maria A. C. Rocha, Eufemia Tarantino, Carmelo Maria Torre
Place of PublicationCham
PublisherSpringer Nature
Pages471-485
Number of pages15
ISBN (Print)9783030870096
DOIs
StatePublished - 2021
Event21st International Conference on Computational Science and Its Applications, ICCSA 2021 - Virtual, Online, Italy
Duration: 13 Sep 202116 Sep 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12956 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference21st International Conference on Computational Science and Its Applications, ICCSA 2021
Abbreviated titleICCSA 2021
Country/TerritoryItaly
CityVirtual, Online
Period13/09/2116/09/21

    Research areas

  • Anemometer, Autoregressive model, Load cell, Strain gauge, Three-dimensional ACF, Turbulence, Wind velocity PDF, DISTRIBUTIONS, SPEED

    Scopus subject areas

  • Computer Science Applications
  • Theoretical Computer Science
  • Computer Science(all)

ID: 85910272