We are seeking a full time PhD researcher with interests in granular physics, computer modelling and Machine Learning techniques to join University of Twente (Netherlands), and work on a novel high-performance multi-phase material point method for modelling submarine landslides . This project is part of the EU funded Marie Curie Doctoral Network POSEIDON – Improve offshore infrastructure resilience against geohazards towards a changing climate (www. poseidon-dn.eu). The overarching objective of POSEIDON is to develop, solutions to improve the resilience of offshore infrastructures. POSEIDON will train 13 researchers within a collaborative multidisciplinary and inter-sectorial network involving 9 universities, 3 research institutes and 4 industrial partners across Europe.
Background and aim:
Submarine landslides involve the movement of saturated sediments down a slope, interacting with seawater and/or offshore infrastructure. During landslides, the bulk of the sediment material (usually considered as a porous medium), transits from solid-like to fluid-like, i.e., from stagnant to continuously flowing. In addition, the coupling between seawater and sediment is crucial in the landslide dynamics. Recent studies have shown that the material point method (MPM) can describe the movement of saturated sediment and the hydrodynamic coupling between soil skeleton and seawater, within a multiple- phase framework. Nevertheless, to accurately predict the dynamics of and dissipation within the sliding masses, the transition between solid and flowing states of sediments must be incorporated.
The doctoral candidate will implement constitutive models for saturated sediments in fluid- and solid-like states into an existing GPU-MPM code. The exchange of momentum, mass, and energy between these admissible states of saturated sediments will be achieved with overlapping subdomains where the transition can potentially take place. To further improve the computational efficiency, machine learning surrogates will be used to partially replace the expensive physics-based models to allow large-scale industrial applications. The project aims to provide more accurate, highly efficient, and physics-based predictions for submarine landslides in order to quantitively assess the risk of damages to offshore infrastructures (e.g., foundations anchors) and induced disasters (e.g., tsunamis).
Objectives:
i) Extend an existing MPM code from single-phase to multi-phase based on a volume-coupled formulation that incorporates mass, momentum, and energy exchange between slow- and fast-flowing sediments and water;
ii) Develop a reduced-order model of the multi-phase system using machine learning and integrate it into the volume-coupled numerical framework;
iii) Perform simulations of submarine landslides and assess their impact on offshore infrastructures;
iv) Calibrate model parameters using existing experimental data and compare the model predictions with experimental data obtained from laboratory flume experiments.
Expected Results:
i) A novel volume-coupled formulation to consider the transport and coupling of multiple phases;
ii) An open-source, multi-phase GPU-based MPM code with clear documentation, tutorials, and examples for future users;
iii) Benchmark cases validated using experimental data from laboratory-scale physical tests.
Planned Secondment(s):
Dr. Michele Larcher (Free University of Bolzano, 2 months): Perform a laboratory-scale experiment on slope collapse and its interaction with foundation anchors in the flume device; the movement of sediment transport underwater will be recorded and analysed to validate the multiphase MPM model for submarine landslides. DC06 will build his/her work on the experiments previously performed by DC03 in UNIBZ.
Dr. Xue Zhang (University of Liverpool, 3 months): Improve the parallelization of the MPM code; incorporate structural mechanics into the code, e.g., using the finite element method, towards assessing the impact of the slides on submarine infrastructures; comparison of PFEM-MPM methods performances.
Your profileWe are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, or disability status. Women are explicitly asked to apply for this position. This is part of the University of Twente's strategy to increase the proportion of women among its faculty and to create a working environment that is diverse and inclusive and supportive of excellence in research and education.
Our offerWe offer you a very exciting position in an inspiring multidisciplinary environment. The university offers a dynamic ecosystem with enthusiastic colleagues in which internationalization is an important part of the strategic agenda.
The University of Twente is situated on a green and lively campus with lots of facilities for sports and other activities.
Information and applicationAs a PhD candidate, you will be enrolled in the University of Twente. The Ph.D project will be conducted under the supervision of prof. V. Magnanimo, prof. S. Luding and dr. Hongyang Cheng. An extended Supervisory Committee, including academic and industrial supervisors from The POSEIDON consortium, will guide the candidate during his/her PhD.
Please submit your application before 15 April 2024 via the ‘Apply now' button, including:
Master students who will graduate in the next coming months are welcome to apply. In that case, please provide an overview of the transcripts that are already available.
The deadline for application is 15 April 2024. The intended starting date is 1 September 2024 , at latest.
You are welcome to contact prof. dr. Vanessa Magnanimo (email v. [email protected]) or dr. Hongyang Cheng (email: [email protected]) for any questions you might have.
The first round of selection interviews is scheduled few weeks after the closure of the applications and interviews can be held through Microsoft Teams. A second round of interviews may be scheduled if necessary.
About the organisationThe Faculty of Engineering Technology (ET) engages in education and research of Mechanical Engineering, Civil Engineering and Industrial Design Engineering. We enable society and industry to innovate and create value using efficient, solid and sustainable technology. We are part of a ‘people-first' university of technology, taking our place as an internationally leading center for smart production, processes and devices in five domains: Health Technology, Maintenance, Smart Regions, Smart Industry and Sustainable Resources. Our faculty is home to about 2,900 Bachelor's and Master's students, 550 employees and 150 PhD candidates. Our educational and research programmes are closely connected with UT research institutes Mesa+ Institute, TechMed Center and Digital Society Institute.
Want to know more Cheng, H. (Hongyang)Assistant Professor
Cheng, H. (Hongyang)Assistant Professor
Do you have questions about this vacancy? Then you can contact Hongyang for all substantive questions about this position and the application procedure. For general questions about working for the UT, please refer to the chatbot.
ContactPhone:+31534899986
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How to apply Step 1Apply. When you see a vacancy that appeals to you, you can apply online. We ask you to upload a CV and motivation letter and/or list of publications. You will receive a confirmation of receipt by e-mail.
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Step 42nd interview. In the second interview, we will further discuss the job content, your skills and your talents.
Step 5The offer. If the conversations are positive, you will be made a suitable offer. If applicable, we will sign you up for screening.
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