Industry accounts for 23% of greenhouse gas emissions globally (IPCC2014). Many processes in chemical and manufacturing plants include thermally-driven batch steps. Thermal energy storage, packed bed technology in particular, has the potential to play an important role in making industrial processes more energy efficient and in reducing greenhouse gas emissions. Next to industrial environments, packed-bed storage can also be used to decouple supply and demand in systems relying on medium-temperature intermittent renewable energy sources, like concentrated solar thermal systems (CST).
Presently, at medium-temperatures levels between 100 °C and 400 °C, thermal storage is mostly done using expensive thermal oil storage or packed-bed storage systems, which use the thermal capacity of a cheap solid-state filler material to store thermal energy by interaction with a heat-transfer medium like thermal oil, steam or hot air. The most common filler material used is natural gravel, which is irregularly shaped. This has two distinct consequences. Firstly, due to the irregular shape, the flow throughout the packed-bed storage will mainly follow the path of least resistance, leading top referred routes and dead zones in the storage unit. Some parts of the thermal storage unit will hence not be (optimally) used, resulting in reduction of overall performance. Secondly, the size of the filler materials is in general small, resulting in high pressure drops over the storage unit, which requires high power consumption by the circulation pumps thus further reducing the storage efficiency.
Overcoming these barriers is the subject of the present PhD topic. It is the ambition to bundle the expertise available at both TU/e and VITO to develop a methodology and toolset that are capable to optimize the design of a packed-bed storage at different levels.
At material scale, the optimal filler shape will be investigated using shape optimization methods, considering requirements imposed by the processes, like charging and discharging power, maximum allowed pressure drop and heat-transfer medium. In particular, the adjoint-based method will be considered as an option for shape optimization, which is also being used in other projects within VITO. As an alternative, traditional approaches based on Computational Fluid Dynamics (CFD) will also be investigated. Candidate materials will be inventoried, and, if needed, characterized using thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) available at TU/e. The production process scalability and sustainability of the candidate materials will be highlighted, focusing on the use of waste or recycled materials such as slag, potentially in collaboration with SuMAT at VITO.
At reactor level, numerical models will be developed to investigate the optimal reactor design and its performance. This can be done using detailed CFD modelling as well as reduced order models constructed from CFD models and data-based models identified from experimental or CFD data (TU/e) that are suitable for optimization problems. A small-scale prototype reactor can be constructed to validate the numerical methodology and validate it with experiments that can be performed either at VITO or at TU/e, depending on the required experimental conditions.
At system scale, the development of a model that can be integrated in a broader system simulation, with a low computational cost, will be investigated. The aim is to assess the performance of the thermal storage coupled with the other system components, following a control strategy. The system-level model can be constructed from the abovementioned reduced-order models or data-based grey-box/black-box models to be developed at the reactor level.
The activities in this PhD topic proposal combine expertise available in VITO (adjoint-based optimization, CFD modelling, SuMAT & lab infrastructure) and TU/e (packed-bed storage expertise, CFD and DNS modelling of porous media, model reduction techniques, lab infrastructure & material characterization equipment). The outcome of the project should eventually result in a methodology and toolset that is capable to design packed-bed thermal storage systems in an optimal way, considering the requirements of the process.
The PhD fellowship is granted within the collaboration between the University of Eindhoven and VITO.
The successful candidate will be supervised by Prof. Camilo Rindt (TU/e) and co-promoted by Dr. Emilia Motoasca and Dr. Jan Diriken (VITO).
For more information, please contact Dr. Emilia Motoasca: email@example.com.
How to apply?
Applications should be submitted online and should include a copy of your CV and a cover letter.
The remainder of the selection procedure is specific to the position and will be determined by the selection panel.
You can apply for this PhD vacancy no later than August 1, 2022.
- You hold a M.Sc. degree relevant to the position (e.g. Mechanical Engineering or Thermal Engineering or equivalent).
- You are fluent in English, both oral and written.