PhD Position Microclimate Adaptive Grid CFD Modeling

Help solve a key challenge in greenhouse horticulture: design high resolution microclimate observation networks to enable energy savings by optimizing the growth microclimate for greenhouse crops.

Job description

Crop microclimate plays a vital role in optimizing productivity of greenhouse crops, yet accurate knowledge of variations in greenhouse microclimates remains limited. In particular, understanding of the interactions between the crop vegetation structure and their microclimate environment remains a challenge.

In this PhD research you will develop CFD models at different scales, from 2D and 3D techniques resolving the plant-structure and flows at the leaf-to-plant scale, to multi-layered plant-climate models resolving canopy-scale fluxes to porous media models representing airflow and fluxes at the full greenhouse or vertical farm scale. An important challenge in connecting these models lies in a proper representation of the aerodynamic and flux resistances and plant-climate interactions at each hierarchical scale.

Your research will focus on numerical CFD modeling using adaptive grids to represent the leaf-plant-canopy climate gradients and fluxes for improved prediction of crop-climate interactions. You will start by implementing a geometric idealized plant model in the CFD model to represent the plant structure and study the impact of airflows on turbulence and aerodynamic resistance inside the canopy and on heat diffusion and temperature penetration in response to radiation.

Results will be compared with experimental data collected by another PhD researcher in the same project. A next step will be to extend the CFD model with mass fluxes of CO2 and water vapor and study the impact of airflows and sensible heat flux on mass fluxes and their associated source and sink terms from the vegetation. Based on these findings you will develop conceptual representations using resistance analogies, to transfer the identified relationships to a multi-layer model structure that can be used at the greenhouse scale.

In this project you will work in close collaboration with a team of PhD researchers and postdocs as well as project partners from industry and the horticulture sector. Therefore, communication skills and proven ability to work productively in a team are very important. You will work closely with two supervisors – Marie-Claire ten Veldhuis (experimental expertise) and Bas van de Wiel (theoretical expertise) – and a dedicated technician. This team-oriented supervision approach has proven effective in previous projects, with weekly joint whiteboard sessions.

You will be hosted by the Geoscience & Remote Sensing Department in the Faculty of Civil Engineering and Geosciences at TU Delft. As part of our diverse and dedicated team of professors, lecturers, PhD and postdoc researchers, you will have the opportunity to work closely with leading experts and industry partners at the national and international level. Our unique facilities provide an ideal environment for experimental research and innovation. Here, you will receive all the support and coaching you need to develop further your career.

Job requirements

• You hold an MSc in applied physics, atmospheric science, or a related field.
• You have proven relevant project/thesis experience with complex CFD simulations.
• You are a team player and enjoy interdisciplinary collaboration.
• You have a good command of written and spoken English.

About TU Delft

Working at TU Delft means contributing to solutions that really make a difference.

At TU Delft, our people make the difference. With their knowledge and curiosity, our staff provide a high-quality education and conduct pioneering research that extends beyond the campus. You will have the opportunity to take the initiative, work with others, and grow as a professional.

Working at TU Delft means joining an international community of professionals and students. Together, we create knowledge, innovations, and solutions that help move the world forward.

Faculty of Civil Engineering and Geosciences

The Faculty of Civil Engineering & Geosciences (CEG) is committed to outstanding international research and education in the field of civil engineering, applied earth sciences, traffic and transport, water technology, and delta technology. Our research feeds into our educational programmes and covers societal challenges such as climate change, energy transition, resource availability, urbanisation and clean water. Our research projects are conducted in close cooperation with a wide range of research institutions. CEG is convinced of the importance of open science and supports its scientists in integrating open science in their research practice.

The Faculty of CEG comprises 28 research groups in the following seven departments: Materials Mechanics Management & Design, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water Management.

Conditions of employment

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest.