SDU Maritime Research Platform
The SDU Maritime Research Platform was established in 2022 based on a donation from A/S Dampskibsselskabet Orient’s Fond. The platform consists of maritime research projects in four faculties across the University of Southern Denmark, mostly PhD and postdoc projects, and the platform has a special focus on the offshore cluster.
All projects in the SDU Maritime Research Platform are related to work packages that are rooted in strong research groups across the university. At the same time, researchers in the platform meet regularly to discuss their research in a highly interdisciplinary setting. The platform also has a strong focus on relations to the industry.
ShipWeldFlow
Digital Twins for robotic unit welding analysis and optimization in ship production.
SDU Mech is in involved in Work Package on: Process simulation models for robotic welding of large marine structures for prediction of deformations and residual stresses. The welding simulation model will be developed to optimize the welding sequence of complicated multi-panel structures.
Partners in project: SDU Robotics (Leader), Odense Maritime and Inrotech.
ShipWeldFlow is a Grand Solution funded by Innovation Fund Denmark and coordinated by SDU Robotics. See: https://www.sdu.dk/en/forskning/sdurobotics/researchprojects/shipweldflow
Project period: 2020 to Marts 2024.
AM-assisted investment casting of complex heat sink geometries
This project explores the use of additive manufacturing (AM) for the investment casting of complex heat sink geometries.
Advanced simulation-based design optimisation methods are used to generate novel and high-performing heat sink geometries for electronics cooling applications applying additive manufacturing to produce complex geometries.
Topology Optimisation
Topology optimisation (TO) is a simulation-based design approach that gives the user the ultimate design freedom. Based on advanced simulations and the use of large scale computing, geometries can be generated with high performance and material savings, often based on non-intuitive design features that are automatically spawned.
Digital Twins of Axial Piston Pumps (APPs) for Machine Learning-based Condition Monitoring.
The main focus of this project is the Condition Monitoring (CM) of Axial Piston Pumps (APPs), which, in contrast to other types of machinery, has received far less attention both in research and industry. Still, APPs are currently used in several critical industrial applications and comprise a very high investment. The harsh operational conditions and large loads make these structures very sensitive to damage. Hence, highly sensitive and responsive CM algorithms can result in significant operations and maintenance savings. While Machine Learning (ML)-driven CM methods can potentially provide high damage diagnosis performance, their performance is bound on the availability of sufficient training data. The main objective of this project is to develop high-fidelity Finite Element Models (FEMs) to form so-called “Digital Twins” of APPs, which can be used as synthetic data generators for various damage scenarios in the training of ML-driven CM algorithms. The project is funded by Innovation fund.
A Novel Node Design using High Strength Steel for Jacket Structures
As the size of offshore wind turbine generators get bigger and the available water depth increases, the weight and cost of traditional monopile foundations will increase substantially. Instead, jacket foundations can be used as they perform better in deeper waters. However, the connections between the tubular legs and cross stiffeners in the jackets, also called nodes, are prone to high loads and fatigue damage thus resulting in a heavy and expensive node design. To decrease the cost of tubular jacket structures, a novel node design using high strength steel will be developed with special attention to the stochastic manufacturing parameters, fatigue methods and post-weld treatment. This is an EUDP project.
Simulation of thermomechanical effects from welding
This work is part of the ShipWeldFlow project and seeks to accurately simulate the thermomechanial effects from welding on large plates. A time-dependent computational model is formulated and implemented in COMSOL to predict post-welding thermomechanical deflections of the plates.
This project focuses on understanding how geometric parameters influence the performance of fluidic oscillators, which are a type of fluidic device, or nozzle, that generates an oscillating flow from a constant inflow purely based on the geometry. The project uses simulations and experiments to gain this understanding and subsequently used to optimise the devices for specific behaviour.
Development of an SCR system integrating a novel reductant delivery system
The overall project idea is to develop a mixer with a heated nozzle to be included in exhaust systems. The goal is to fulfil the future emission norms.
The Intelligent Sprayer Boom
Single Plant Pesticide Application
ECOPRODIGI
The ECOPRODIGI (Eco-efficiency, Process & Digitalisation of the Maritime Industry) project aims at bringing eco-efficient processes and digital solutions to the Baltic Sea Maritime industry.
SDU Mech is involved in one work package regarding Digital Ship Operations, Performance Monitoring and Eco-efficiency – with a special focus on smaller ferries.
The project is funded by EU Baltic Sea Interreg.
Project period: October 2017 to December 2020.
For more information: https://ecoprodigi.eu/
EXOPRODIGI
The EXOPRODIGI project purpose it to achieve strength targets for eco-efficiency. The aim is to progress implementation and innovation results created in the ECOPRODIGI project further with the purpose of achieving stretch targets for eco-efficiency set within the ECOPRODIGI project
SDU Mech is involved in one work package regarding Digital Ship Operations, Performance Monitoring and Eco-efficiency – with a special focus on smaller ferries.
The project is funded by EU Baltic Sea Interreg.
Project period: January 202021 to September 2021.
For more information: https://ecoprodigi.eu/exoprodigi
ShippingLab:
ShippingLab is a non-profit innovation and project partnership in Blue Denmark – a national research and innovation platform for digital and sustainable shipping in DenmarkSDU Mech is involved in WP 1: WP1 Digital Ship operations
The project focuses on vessel modelling and developing more precise ship models and better estimation of the effects that the environment has on vessel and system performance. WP1 will deliver tools and methodology for digital twinning of vessel in the seaway, using high frequency data.
The SDU Mech work more specifically: Vessel operation and diagnostics engine for performance analysis. A close feedback loop to vessel crews, raising the bar for decision support, providing higher order conclusions and decision support for actions. Partners in project: Vessel Performance Solution, DTU, FORCE, Lauritzen, Torm, MAN Diesel & Turbo, Logimatic, AAU, SIMAC The project is funded by The Innovation Fund Denmark and the private funds: Lauritzen Fonden, Orients Fond, Den Danske Maritime Fond. Project period: 2019 to 2022. For more information: www.Shippinglab.dk
The overall project idea is to develop a new HVAC system by integrating a PCM based energy storage module (Climate module).
under the EUDP program – Next generation ventilation
Reliables Offshore
The aim of this project is to determine the remaining service life or the optimal point of time for maintenance of offshore structures based on Structural Health Monitoring (SHM). On top of that it aims for finding answers to questions about the safe and efficient operation of existing constructs beyond their nominal service time. The project partners are FH Kiel, SDU and FuE and funded by Interreg Deutchland-Danmark.
Robust Identification of Modal Parameters of Nonlinear and Time Variant Systems
Oil and gas platforms are not linear and they are timevariable, therefore , traditional methods for determination of dynamic parametres are less useful. Consequently, in this project we deveop methods that can better handle the unlinear and timevariable vibrations in platforms . These methods will later be used i analyses of the lifetime of the platforms.
Vibration and damping in large containerships
In this project we study the new large container ships of more than 21,000 TEU and try to understand the vibration nodes that occur in different kinds of weather and operation conditions. The data is important to understand the forces that places strain on as well the ships as the containers on these.
Analytical Fatigue Life Assessment of a Full-Scale Wind Turbine Test Bench
The objective of the project is to establish a digital model of the wind turbine test bench – a digital twin. Modelling of the key components of the test bench, is vital to our ability to assess and validate the loadings imposed on vital key components of the test bench during service. Understanding how the complicated 3D loading patterns, which we impose on the wind turbines under test, are distributed in the test bench itself, and locating potential hot-spots, is essential to our ability to secure safe operations. The research project is carried out in collaboration with Lindø Off-shore Renewables Center (LORC). The project was funded by Innovation fund.
Fault Detection of Rolling Element Bearings in a Full-Scale Wind Turbine Test Bench
Currently, extensive research has been carried out to monitor the dynamic properties of operating full-scale offshore wind turbines. However, there is a need to develop methods to identify the damp-ing of the offshore wind turbines using operational modal analysis. The research project is carried out in collaboration with Vattenfall Vindkraft A/S, a producer of wind energy. The project was funded by Innovation fund.
Compact mixer with low thermal mass
The overall project idea is to develop a compact mixer to be included in exhaust systems. The goal is to fulfil the future emission standards by minimizing the component´s thermal mass and by optimizing the fluid dynamics.