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Short Courses

Corrosion and Fouling in Marine Environment

Saturday, June 8, 2019, 9:00 am – 5:00 pm

Instructors

Dr. Tahsin Tezdogan, Senior Lecturer, University of Strathclyde, Glasgow, UK

Dr. Yigit Kemal Demirel, Lecturer, University of Strathclyde, Glasgow, UK

Course description

This course is split into two parts, i.e. corrosion and fouling. The first part will cover the corrosion concept in marine environment and the prevention methods. It will focus on the combined use of both cathodic protection (CP) and coatings for ships and offshore structures. A hands-on tutorial will be performed to show the CP calculation procedure. The second part of the course aims to provide the fundamental concepts of marine biofouling, state-of-the art fouling control coatings, and the roughness effects of biofouling and coatings on the boundary layer. This module also aims to describe how to estimate the effect of biofouling on the performance of marine vehicles in terms of resistance/power increase through state-of-the art numerical and experimental approaches.

You will learn to:

  • An appreciation of the different techniques for corrosion protection
  • An overview of corrosion and cathodic protection
  • The economics of corrosion
  • Cathodic protection design principles – a worked example
  • An overview of marine biofouling
  • Fouling control coatings
  • Roughness effect of biofouling and coatings - Boundary layer theory
  • The effect of biofouling on the performance of marine vehicles
  • State-of-the-art experimental and numerical techniques to predict the effect of biofouling on the performance of marine vehicles

Verification & Validation of Industrial CFD

Saturday, June 8, 2019, 9:00 am – 5:00 pm

Instructors

Guilherme Vaz, CFD Research Coordinator, MARIN, the Netherlands

Luís Eça, Assistant Professor, IST, Portugal

Course description

CFD simulations have become an Engineering tool that complements model testing. As for physical models, such capability requires the assessment of the quality of the results, which depends on the mathematical model (basin for physical models) and its numerical solution (instrumentation for experiments).

This course teaches CFD practitioners to distinguish numerical and modelling errors. It presents the definitions of the different contributions to the numerical error of steady and unsteady flow simulations. Techniques to quantify numerical (Verification) and modelling errors (Validation) in industrial CFD Simulations are presented including examples from practical simulations. The course provides a framework for the establishment of the credibility of simulations so that they can be safely used for engineering decisions.

You will learn to:

You will learn how to demonstrate the quality of your CFD simulations and evaluate the accuracy of the mathematical models behind those simulations.

Schedule

9 – 9:30 Introduction: Errors and Uncertainties
9:30 – 10:30 Numerical Errors
10:30 – 11:00 Break
11:00 – 12:30 Estimation of Numerical Uncertainty in steady and unsteady flows
12:30 – 13:30 Lunch
13:30 – 15:00 Code and Solution Verification Examples
15:00 – 15:30 Break
15:30 – 17:00 Validation

Offshore Wind Turbines: Dynamic Analysis and Marine Operations

Sunday, June 9, 2019, 9:00 am – 5:00 pm

Instructors

Erin Bachynski, Norwegian University of Science and Technology and Zhen Gao, Norwegian University of Science and Technology

Course description

This course reviews several considerations related to design and operation of offshore wind turbines. Fundamental concepts in aerodynamic (with focus on blade element/momentum theory) and hydrodynamics (with focus on first and second order radiation-diffraction and Morison-type models) load calculation are presented. The course addresses theoretical background and important practical considerations for structural response analysis considering these load components simultaneously, including wind turbine control, for ULS and FLS design check. A brief review of the state-of-the-art in combined wind-wave testing and the status of validation of the integrated design tools will be provided. Finally, marine operational issues related to transport, installation and access to wind turbines for maintenance and repair, with focus on numerical simulation of onsite installation and weather window analysis, are discussed.

You will learn to:

  • Explain the basic wind turbine components, and types of substructures,
  • Identify key external loads on offshore wind turbines and understand the theory for their estimation,
  • Understand and be able to critically assess state-of-the-art global dynamic analysis of offshore wind turbines, including interactions between the wind- and wave-induced loads and responses,
  • Understand the different methods for wind-wave testing of floating wind turbines and their advantages and disadvantages
  • Numerically model marine operations such as installation of substructure and turbine components; and
  • Evaluate weather windows for offshore wind turbine installation.

Schedule

9 – 9:45 Introduction (ZG)
9:45-10:15 Aerodynamics (EB)
10:15-10:30 Break
10:30-11 Aerodynamics (EB)
11-12 Hydrodynamics (ZG)
12-12:30 Control systems (EB)
12:30-13:30 Lunch
13:30-14:45 Integrated dynamic analysis (EB)
14:45-15:15 Dynamic analysis examples/discussion (EB)
15:15-15:30 Break
15:30-16 Experimental methods and validation (EB)
16:00-17 Marine Operations (ZG)

WEC Dynamics and Control Design

Sunday, June 9, 2019, 9:00 am – 5:00 pm

Instructors

Ryan Coe, Research Engineer, Sandia National Labs, USA;

Giorgio Bacelli, Research Engineer, Sandia National Labs, USA;

Yi-Hsiang Yu, Research Engineer, National Renewable Energy Lab, USA;

Course description

While similar in many ways to other ocean systems, wave energy converters (WECs) pose a number of novel design challenges. This course will focus on methods for analyzing WEC dynamics, designing WECs and WEC control systems, and testing WECs. Content will include numerical modeling and dynamics analysis, design concepts, optimal control, instrumentation and test design, and empirically-based models.

You will learn to:

  • Basic WEC design concepts, components and subcomponents
  • Understand and apply a number of modeling and analysis approaches
  • Understand WEC control and implications for WEC design
  • Design experiments and perform system identification to obtain empirical models for WECs 

Introduction to Machine Learning and Data-driven modelling methods for Engineering applications

Sunday, June 9, 2019, 9:00 am – 5:00 pm

Instructors

Andrea Coraddu, PhD , Lecturer in Marine Engineering, University of Strathclyde – Department of Naval Architecture, Ocean and Marine Engineering, United Kingdom.

Christos Gkerekos, MEng, PhD Researcher, University of Strathclyde – Department of Naval Architecture, Ocean and Marine Engineering, United Kingdom.

Course description

The course will focus on Data-driven models for engineering applications, including linear and nonlinear models, model selection and error estimation. Numerical examples and real-life problems will be proposed and analysed, from bearings fault prediction, to fuel consumption optimisation. All course material will freely available in PDF format for a complete understanding of the related subjects as well as for future consultation. During the afternoon session, a hands-on workshop will be organised with numerical examples focused on various aspects of Data-driven models. The course is designed for professionals who are interested in data analysis and machine learning applications. An engineering background, statistical and numerical skills would be beneficial but not necessary.

You will learn to

Data science is improving our way to understand complex phenomena as and even faster than a priory physical models have done in the past. Engineering Systems are composed by many complex elements, their mutual interaction is not easy to evaluate and predict adopting the conventional first principles physics model based on a priory physical knowledge, because of the significant number of parameters which influence their behaviour.

The course will exploit advanced statistical techniques in order to build models directly based on the large amount of historical data collected by the recently advanced automation systems without having any a prior knowledge of the underlying physical system.