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Vincenzo Nava

Has grant

Docenti di ruolo di IIa fascia

Politecnico di Torino

Italy

Research Interests

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Professors in Italy Professors in Fluid Mechanics Fluid Mechanics professors in Italy

Recent Grants

Grant: Close

Verification through Accelerated testing Leading to Improved wave energy Designs

Open Date: 2020-12-01

Close Date: 2023-11-30

Grant: Close

Development and demonstration of an automated, modular and environmentally friendly multi-functional platform for open sea farm installations of the Blue Growth Industry

Open Date: 2018-06-01

Close Date: 2022-03-31

Grant: Close

Advanced Design Tools for Ocean Energy Systems Innovation, Development and Deployment

Open Date: 2018-05-01

Close Date: 2021-08-31

Grant: Close

Open Sea Operating Experience to Reduce Wave Energy Cost

Open Date: 2016-02-01

Close Date: 2019-07-31

Grant: Close

Qualification of innovative floating substructures for 10MW wind turbines and water depths greater than 50m.

Open Date: 2015-06-01

Close Date: 2019-04-30

Articles (20)

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Collaborators (8)

John Ringwood

Professor

National University of Ireland, Maynooth

IRELAND

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Markel Penalba

Lecturer and researcher

Mondragon Unibertsitatea

SPAIN

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Hamed Fathnejat

Research Associate

National Research Council Canada

CANADA

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Smriti Sharma

KTH Royal Institute of Technology

SWEDEN

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Josh Davidson

Researcher

IHCantabria - Instituto de Hidráulica Ambiental de la Universidad de Cantabria

SPAIN

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Morten Bech Kramer

Associate Professor

Aalborg University

DENMARK

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Jacob Andersen

Aalborg University

DENMARK

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Pranjal Tamuly

Assistant Professor

University of Tuscia

ITALY

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Vincenzo Nava

Research Interests

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Recent Grants

Articles (20)

Damage detection in mooring systems of floating offshore wind turbines using semi-supervised GAN with image-transformed limited labelled data

Towards Robust Machine Learning Models for the Estimation of Mooring-Line Tension in Floating Wind Turbines under Unknown Sea Conditions

From augmentation to translation: Data generation by conditional hierarchical variational autoencoder, enhancing monitoring mooring systems in floating offshore wind turbines

Data augmentation for damaged scenarios in floating offshore wind turbines: an approach based on diffusion architecture, hierarchical variational approximation and healthy data distribution

A methodology for expert knowledge imbrication in mooring system design using Bayesian based optimization

Gaussian mixture autoencoder for uncertainty-aware damage identification in a floating offshore wind turbine

Integrated damage detection and time-series data augmentation for floating offshore mooring systems via variational semi-supervised learning

Machine learning based conformal predictors for uncertainty-aware compressive strength estimation of concrete

Reducing spatial discretization error on coarse CFD simulations using an openFOAM-embedded deep learning framework

Uncertainty-aware Bayesian optimisation framework for the design of floating offshore wind turbines

Hierarchical Variational Approach for Domain Translation in Unseen Damaged Mooring Systems

Unseen Mooring Monitoring by Conditional Hierarchical Variational Domain Translation

Control co-design for wave energy farms: Optimisation of array layout and mooring configuration in a realistic wave climate

Revisiting excitation force estimation in WECs: On the (mis)use of structure-based estimation approaches

Exploiting Axisymmetry to Optimize CFD Simulations—Heave Motion and Wave Radiation of a Spherical Buoy

Condition monitoring of mooring systems for Floating Offshore Wind Turbines using Convolutional Neural Network framework coupled with Autoregressive coefficients

Targeting the high frequency tail of wave spectra for energy harvesting in marine sensor networks

Fault detection and identification for control systems in floating offshore wind farms: A supervised Deep Learning methodology

Risk assessment of potentially toxic elements in intermittent rivers, “fiumara”, flowing in the Gulf of Milazzo (Sicily, Italy)

Monitoring Mooring Lines of Floating Offshore Wind Turbines: Autoregressive Coefficients and Stacked Auto-Associative-Deep Neural Networks

Collaborators (8)

John Ringwood

Markel Penalba

Hamed Fathnejat

Smriti Sharma

Josh Davidson

Morten Bech Kramer

Jacob Andersen

Pranjal Tamuly

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