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Numerical Analysis and Monitoring Techniques of Offshore and Coastal Structures...
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Numerical Analysis and Monitoring Techniques of Offshore and Coastal Structures and the Marine Environment

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: closed (20 November 2021) | Viewed by 3617

Special Issue Editor

Dr. Constantine Michailides

E-Mail Website
Guest Editor
Department of Civil Engineering, International Hellenic University (IHU), Thessaloniki, Greece
Interests: wave-structure interaction; offshore wind turbines; wave energy converters; marine civil engineering; offshore and coastal structures; hydrodynamics; marine hydraulics; monitoring technologies in marine engineering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Analysis and design of coastal and offshore structures is an equally demanding and challenging task. Accuracy of the calculated responses is required at a maximum level, while computational cost is very important especially when we approach the design phase and a big number of analysis cycle iterations for a large number of operational and extreme environmental conditions needs to be performed. At the same time and in a growing rate, monitoring technologies are used for both structural health as well as marine environment process observations.

In this context, this Special Issue invites original scientific contributions on topics related to numerical analysis methods and tools of offshore and coastal structures covering the broad spectrum of related analysis, monitoring technologies, and/or response diagnosis of offshore and coastal structures, monitoring technologies of marine environmental characteristics, integration and update of numerical predictions with monitoring data, real-time predictions and/or forecasting in the marine environment, and digitalization of data for offshore and coastal structures.

Dr. Constantine Michailides
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Wave–structure interaction
  • Hydrodynamics
  • Viscous loads
  • DNS, LES, CFD, BEM, SPH
  • Offshore and coastal structures
  • Marine renewables (offshore wind turbines, wave energy converters, tidal turbines)
  • Sea circulation models
  • Structural health monitoring
  • Marine environment monitoring

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Published Papers (1 paper)

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Research

23 pages, 6062 KiB  
Article
Kriging Model for Reliability Analysis of the Offshore Steel Trestle Subjected to Wave and Current Loads
by Pengfei Liu, Daimeng Shang, Qiang Liu, Zhihong Yi and Kai Wei
J. Mar. Sci. Eng. 2022, 10(1), 25; https://doi.org/10.3390/jmse10010025 - 27 Dec 2021
Cited by 2 | Viewed by 2831
Abstract
Offshore steel trestles (OSTs) are exposed to severe marine environments with stochastic wave and current loads, making structural safety assessment challenging and difficult. Reliability analysis is a suitable way to consider both wave and current loading intensity uncertainties, but the implicit and complex [...] Read more.
Offshore steel trestles (OSTs) are exposed to severe marine environments with stochastic wave and current loads, making structural safety assessment challenging and difficult. Reliability analysis is a suitable way to consider both wave and current loading intensity uncertainties, but the implicit and complex limit state functions of the reliability analysis usually imply huge computational costs. This paper proposes an efficient reliability analysis framework for OST using the kriging model of optimal linear unbiased estimation. The surrogate model is built with stochastic waves, current parameters, and the corresponding load factors. The framework is then used to evaluate the reliability of an example OST subjected to wave and current loads at three limit states of OST, including first yield (FY), full plastic (FP), and collapse initiation (CI). Three different distributions are used for comparison of the results of failure probability and reliability index. The results and the computational cost by the proposed framework are compared with that from the Monte Carlo sampling (MCS) and Latin hypercube sampling (LHS) method. The influences of sample number on the prediction accuracy and reliability index are investigated. The influence of marine growth on the reliability analysis of the OST is discussed using MCS and the kriging model. The results show that the reliability analysis based on the kriging model can obtain the reliability index for the OST efficiently with less calculation time but similar results compared with MCS and LHS. With the increase of the number of samples, the prediction accuracy of the kriging model increases, and the corresponding failure probability fluctuates greatly at first and then tends to be stable. The reliability of the example OST is reduced with the increase of marine growth, regardless of the limit state. Full article
(This article belongs to the Special Issue Numerical Analysis and Monitoring Techniques of Offshore and Coastal Structures and the Marine Environment)
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