PhD in Exploiting digital twins for wind-assisted propulsion ships
Chalmers Tekniska Högskola AB / Högskolejobb / Göteborg
2024-10-01
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hela Sverige Visa alla jobb hos Chalmers Tekniska Högskola AB i Göteborg We are seeking a highly motivated PhD student to develop ship physics-integrated machine learning models for real-time prediction and optimization of wind-assisted ship propulsion systems, integrating physical ship performance models with operational data. This position offers a unique opportunity to contribute to sustainable shipping by enhancing the efficiency and automation of wind-assisted propulsion (WAP) technologies. You will work at the intersection of marine engineering, artificial intelligence, control theory, and human factors, collaborating within the Marine Technology division at Chalmers University of Technology. This role not only involves cutting-edge research but also has the potential to set new standards in future ship designs and operations. If you are passionate about applying advanced technologies in real-world environments and making a significant impact on the maritime industry, we encourage you to apply.
Project description
The International Maritime Organization (IMO) adopted ambitious environmental ambition to peak GHG emissions from international shipping as soon as possible and to reach net-zero GHG emissions by or around 2050. It also promotes the development and installation of various emission reduction measures. One of such measures is wind-assisted propulsion (WAP) technologies, which use renewable wind energy for auxiliary ship propulsions, with the potential to reduce around 20% emissions from shipping. However, installation of WAP onboard ships significantly changes ship operation characteristics, such as the manoeuvrability, energy performance and seafarers' ability and attitude to navigate the ships.
In this project, we aim to develop an AI/ML-enhanced platform to create digital twin systems for WAPs. By integrating physical modeling with advanced machine learning techniques such as ANN, and CNN, we will build a comprehensive digital twin that accurately predicts the dynamic coupling performance of the hull and WAP systems in real-time. This platform will incorporate both the ship's physical dynamic hull-engine-propeller energy performance and calibrated sensor data through physics-informed neural network modeling. Additionally, we plan to utilize this digital platform to develop optimal control mechanisms to automate WAP operations and to demonstrate energy efficiency measures developed within our research activities.
Information about the division and the department
The department of Mechanics and Maritime Sciences conducts fundamental and applied research in all modes of transport to achieve sustainable technological solutions. M2 holds one of Sweden's most extensive simulator centers for navigation and propulsion of ships, as well as world class laboratories within combustion engineering and wind tunnels. The department also offers and contributes to bachelor and master programs in areas such as Shipping, Automotive and Mechanical Engineering to mention a few. In addition, professional education is performed on both a national and international level, with specifically designed mission training for different social actors, within our ambition for lifelong learning. The department continuously strives to establish a cooperation between academia, industry, and society, with a great focus on utilization. M2 is characterized by an international environment with employees and students from around the world, as well as outstanding research and world class education.
The Division of Marine Technology performs research and education centered primarily around the professional understanding and technical development of a ship's operational performance models. The research areas range from structural integrity assessment, fatigue and fracture, collision survivability, hull design, risk and reliability analysis, ship resistance and motions, propulsion systems, etc. Research activities are performed within both basic sciences to advance the understanding of the physics controlling the design and operation, as well as applied sciences in e.g. support a designer, advance the regulations, and provide models for ship operations. Safety and energy efficiency in ships are at the core of future shipping research and education. The division is responsible for educating Naval Architects and Ocean Engineers within the international master's program Mobility Engineering at Chalmers.
Major responsibilities
As a PhD candidate on this project, your main tasks and responsibilities will include:
• Create machine learning architectures (e.g., ANN, CNN) to accurately predict real-time ship hull and wind-assisted propulsion (WAP) interactions at sea.
• Combine physical ship performance models with operational monitoring data to enhance prediction accuracy and reliability.
• Utilize the developed models to create optimal control mechanisms that increase automation of WAP operations.
• Model hull-WAP-engine coupling dynamics to assist WAPS ship operations for various wind conditions.
• Develop sailing scenarios based on the models for maritime simulator training to study and enhance seafarers' behavior in operating WAP-equipped ships.
• Work closely with researchers in marine technology, AI, control theory, and human factors to ensure comprehensive project development.
• Assist in supervising master's students and collaborate with team members on related energy efficiency measures and research initiatives.
Read more about doctoral studies at Chalmers here.
Qualifications
The successful candidate has an MSc degree in maritime transport, marine technology, applied mechanics related areas, with a very solid background in mathematics, programming and optimization. In particular, you should have relevant knowledge about ship propulsion/energy systems and experience in ship response modelling at sea environments. Candidates are required to have:
• Excellent grades in your master program
• Mathematical and statistical analysis skills to post-processing various types of data.
• Dedication and the desire to learn
• Proficiency in programming
• Strong theoretical background
• Ability to present results in scientific papers
• Ability to research and work independently
• Fluent in communicating and writing in English
Contract terms
Full-time temporary employment. The position is limited to a maximum of five years.
Application deadline: 2024-11-10
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Arbetsgivare Chalmers Tekniska Högskola AB (org.nr 556479-5598)
Jobbnummer 8930680