Job Reference
171_23_CASE_PTG_R1
Position
PhD Student - High-fidelity thermo-mechanical simulations for Solid Oxide Electrolyzer Cells (R1)
Closing Date
Saturday, 16 December, 2023
Reference: 171_23_CASE_PTG_R1
Job title: PhD Student - High-fidelity thermo-mechanical simulations for Solid Oxide Electrolyzer Cells (R1)
About BSC
The Barcelona Supercomputing Center - Centro Nacional de Supercomputación (BSC-CNS) is the leading supercomputing center in Spain. It houses MareNostrum, one of the most powerful supercomputers in Europe, was a founding and hosting member of the former European HPC infrastructure PRACE (Partnership for Advanced Computing in Europe), and is now hosting entity for EuroHPC JU, the Joint Undertaking that leads large-scale investments and HPC provision in Europe. The mission of BSC is to research, develop and manage information technologies in order to facilitate scientific progress. BSC combines HPC service provision and R&D into both computer and computational science (life, earth and engineering sciences) under one roof, and currently has over 900 staff from 55 countries.
Look at the BSC experience:
BSC-CNS YouTube Channel
Let's stay connected with BSC Folks!
We are particularly interested for this role in the strengths and lived experiences of women and underrepresented groups to help us avoid perpetuating biases and oversights in science and IT research.
Look at the BSC experience:
BSC-CNS YouTube Channel
Let's stay connected with BSC Folks!
We are particularly interested for this role in the strengths and lived experiences of women and underrepresented groups to help us avoid perpetuating biases and oversights in science and IT research.
Context And Mission
The urgent need for decarbonization has brought about a shift towards hydrogen and hydrogen-enriched fuels as a solution for the future cleaner, and low-carbon energy systems. However, meeting the EU targets for reduced emissions and carbon dependency poses new challenges for energy-intensive industrial processes like steel manufacturing or power generation. Power-to-X (P2X) technologies are being developed to produce "green hydrogen" from renewable electricity, which can then be used to improve these processes and reduce their carbon footprint and dependence on fossil fuels. In fact, given the still low energy density of batteries, green hydrogen is currently the only feasible alternative to decarbonize industries where this parameter is critical, such as as commercial aviation. Hydrogen-based technologies are a crucial component of the energy transition and require digital tools and advanced software to speed up their deployment in the market.
Green hydrogen, which is generated from water and renewable electricity in an electrolyzer, can be stored and distributed for use in power generation or electrochemical systems like fuel cells. Among the most efficient hydrogen production systems, Solid Oxide Electrolizer Cells (SOECs) operating at high temperatures have shown high potential to generate hydrogen at moderate and large scales. These cutting-edge technology involve numerous physical and chemical phenomena occurring at various scales, ranging from thermo-mechanical-fluidic at the cm-scale to electrochemistry at the nanoscale. The multi-physics and multi-scale nature of these devices makes them extremely challenging from a simulation standpoint, but the outputs of the simulations are highly valuable for predicting and designing real-world operating systems.
This Ph.D. opportunity offers a chance to work on predicting the mechanical behavior of SOEC technology with a focus on developing a thermo-mechanical solver and constitutive modeling of the system. The research will involve understanding the thermo-mechanical properties of SOECs and developing a model to accurately predict the thermal stresses under service conditions for the critical cell components. The developed framework will be integrated into Alya, an HPC-multiphysics code, coupling it with the thermo-electro-chemical solver. The successful candidate will work with a team of experienced researchers to further advance the SOECs field and contribute to sustainable energy technologies development. The model developed by the candidate will be verified and validated against the experimental data gathered from the prototype cells provided by the cutting-edge equipment of project partners. The final outcome of this project involves the candidate working on developing infrastructure for generating Digital Twins that use Artificial Intelligence (AI) and physics-based reduced-order models to process data from the full description of the SOEC system. The model developments will be conducted in collaboration with the Universidad de Sevilla, and interactions with the solid mechanics group there are expected.
Green hydrogen, which is generated from water and renewable electricity in an electrolyzer, can be stored and distributed for use in power generation or electrochemical systems like fuel cells. Among the most efficient hydrogen production systems, Solid Oxide Electrolizer Cells (SOECs) operating at high temperatures have shown high potential to generate hydrogen at moderate and large scales. These cutting-edge technology involve numerous physical and chemical phenomena occurring at various scales, ranging from thermo-mechanical-fluidic at the cm-scale to electrochemistry at the nanoscale. The multi-physics and multi-scale nature of these devices makes them extremely challenging from a simulation standpoint, but the outputs of the simulations are highly valuable for predicting and designing real-world operating systems.
This Ph.D. opportunity offers a chance to work on predicting the mechanical behavior of SOEC technology with a focus on developing a thermo-mechanical solver and constitutive modeling of the system. The research will involve understanding the thermo-mechanical properties of SOECs and developing a model to accurately predict the thermal stresses under service conditions for the critical cell components. The developed framework will be integrated into Alya, an HPC-multiphysics code, coupling it with the thermo-electro-chemical solver. The successful candidate will work with a team of experienced researchers to further advance the SOECs field and contribute to sustainable energy technologies development. The model developed by the candidate will be verified and validated against the experimental data gathered from the prototype cells provided by the cutting-edge equipment of project partners. The final outcome of this project involves the candidate working on developing infrastructure for generating Digital Twins that use Artificial Intelligence (AI) and physics-based reduced-order models to process data from the full description of the SOEC system. The model developments will be conducted in collaboration with the Universidad de Sevilla, and interactions with the solid mechanics group there are expected.
Key Duties
- Implement advanced constitutive material models.
- Develop a thermo-mechanical solver.
- Coupling of the thermo-electro-chemical with a thermo-mechanical model.
- Predict the thermal stresses of the critical cell components.
- Interact with the different partners of the projects to carry our collaborative research.
- Contribute to scientific publications and reporting to different National and EU projects the researcher will be involved in.
Requirements
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Education
- The candidate should hold a master’s degree with strong background in computational mechanics.
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Essential Knowledge and Professional Experience
- Knowledge of solid mechanics and thermodynamics are expected.
- Knowledge of constitutive materials models are desirable.
- Knowledge of numerical methods.
- General knowledge on computer science and programming languages.
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Competences
- Fluency in English is essential.
- Strong analytical skills.
- Ability to work independently and within a team.
- Good communication and team-work skills to work in a multidisciplinary team.
Conditions
- The position will be located at BSC within the CASE Department
- We offer a full-time contract, a good working environment, a highly stimulating environment with state-of-the-art infrastructure, flexible working hours, extensive training plan, restaurant tickets, private health insurance, support to the relocation procedures
- Duration: Open-ended contract due to technical and scientific activities linked to the project and budget duration
- Salary: we offer a competitive salary commensurate with the qualifications and experience of the candidate and according to the cost of living in Barcelona
- Starting date: ASAP
Applications procedure and process
All applications must be made through BSC website and contain:
A full CV in English including contact details
A Cover Letter with a statement of interest in English, including two contacts for further references - Applications without this document will not be considered
In accordance with the OTM-R principles, a gender-balanced recruitment panel is formed for every vacancy at the beginning of the process. After reviewing the content of the applications, the panel will start the interviews, with at least one technical and one administrative interview. A profile questionnaire as well as a technical exercise may be required during the process.
The panel will make a final decision and all candidates who had contacts with them will receive a feedback with details on the acceptance or rejection of their profile.
At BSC we are seeking continuous improvement in our recruitment processes, for any suggestions or feedback/complaints about our Recruitment Processes, please contact recruitment [at] bsc [dot] es.
For more information follow this link
In accordance with the OTM-R principles, a gender-balanced recruitment panel is formed for every vacancy at the beginning of the process. After reviewing the content of the applications, the panel will start the interviews, with at least one technical and one administrative interview. A profile questionnaire as well as a technical exercise may be required during the process.
The panel will make a final decision and all candidates who had contacts with them will receive a feedback with details on the acceptance or rejection of their profile.
At BSC we are seeking continuous improvement in our recruitment processes, for any suggestions or feedback/complaints about our Recruitment Processes, please contact recruitment [at] bsc [dot] es.
For more information follow this link
Deadline
The vacancy will remain open until a suitable candidate has been hired. Applications will be regularly reviewed and potential candidates will be contacted.
OTM-R principles for selection processes
BSC-CNS is committed to the principles of the Code of Conduct for the Recruitment of Researchers of the European Commission and the Open, Transparent and Merit-based Recruitment principles (OTM-R). This is applied for any potential candidate in all our processes, for example by creating gender-balanced recruitment panels and recognizing career breaks etc.
BSC-CNS is an equal opportunity employer committed to diversity and inclusion. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or any other basis protected by applicable state or local law.
For more information follow this link
This position is reserved for candidates who meet the requirements and have the legal status of disabled persons with a degree of disability equal to or greater than 33%. In case there are no applicants with disabilities that meet the requirements, the rest of the candidates without declared disability will be evaluated.
BSC-CNS is an equal opportunity employer committed to diversity and inclusion. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or any other basis protected by applicable state or local law.
For more information follow this link
This position is reserved for candidates who meet the requirements and have the legal status of disabled persons with a degree of disability equal to or greater than 33%. In case there are no applicants with disabilities that meet the requirements, the rest of the candidates without declared disability will be evaluated.