Yun-Hang Cho
Department of Civil and Structural Engineering
Research Student


Full contact details
Department of Civil and Structural Engineering
Room D105
Sir Frederick Mappin Building (Broad Lane Building)
Mappin Street
Sheffield
S1 3JD
- Profile
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A passionate, multidisciplinary Engineer with over 9 years of project experience from oil and gas to aerospace. A recognised upcoming leader, I have led multiple technical projects using European Space Project Management Standards ECSS-M-ST-10C and work with industry experts to deliver high impact results in research and outreach. I aspire to create new ways of monitoring our surroundings from astrophysics to fluids engineering.
My PhD research is based at the University of Sheffield and Singapore's Institute of High Performance Computing Agency for Science, Technology and Research (A*STAR). I use petascale national supercomputer to predict flooding using the latest advances in machine learning, CFD and remote sensing/computer vision.
Currently, I also work in the Integrated Manufacturing Group at the Advanced Manufacturing Research Center using my experiences to improve robotic arm accuracy and implement Industrial Internet of Things for complex machines.
Other key experiences include spacecraft and high altitude balloon systems design, robotics and project management. Co-founder of the the Sheffield Space Initative providing technical and managerial advice to teams. Interested in a range of Engineering and technical roles such as IP. Feel free to get in touch!
Research Themes
- Research interests
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Research Project: An integrated numerical and physical modelling approach to enable remote measurement of turbulent free-surface flows.
To develop the science and engineering behind a new ability to infer shallow flow conditions based on remote assessment of free-surface patterns, and to deepen our understanding of turbulent flows. This will be achieved by combining the experimental expertise at Sheffield with the numerical modelling expertise at Institute of High Performance Computing A*Star Singapore.
Objectives:- Collect novel dataset of free-surface flows by enhancing an existing laboratory flume with equipment and expertise available in the department.
- Develop deterministic numerical model, based on existing models in IHPC, for predicting free-surface dynamics from given flow and boundary conditions.
- Invert the model to enable inference of flow and boundary conditions from measured free-surface data.
- Blind-test’ the inverted model via new laboratory and field experiments (river; sewage treatment channel), supported by industry partners.
Turbulent flow surface patterns have been shown to contain information regarding the underlying flow conditions [2], but existing relationships are empirical in nature.This PhD study will test the hypothesis that flow conditions can be directly determined from free-surface measurements. This ability would be a powerful tool for flow measurement and management, with numerous applications in river and sewer monitoring, process plant control and coastal management.
However, it will require a suitable inverse numerical model to relate free-surface behaviour to the turbulent flow field. Such a model does not currently exist, due to a historical lack of (i) understanding of free-surface dynamics, and (ii) ability to collect reliable free-surface data for calibrating and validating models. Recent advances at IHPC and Sheffield mean it is now possible.
An integrated approach, with close collaboration between Sheffield and IHPC will align the numerical and experimental work to enable the bespoke data set necessary to develop and validate an appropriate model.
A detailed planning stage involving both research groups will identify the format, resolution and volume of data required, and a laboratory flume at Sheffield will be enhanced with existing flow measurement equipment in the department to provide it.Flow field and free-surface data will thereby be recorded for a range of flows. Existing deterministic numerical models in IHPC will be further developed and validated using the experimental data. The numerical model will simulate the flows established in the laboratory, and include the dynamics of the free-surface.
Once a numerical model to recreate the free-surface flows is developed and validated, an inverted model will be derived to enable the inference of turbulent flow fields based on measured free-surface data.This will be achieved via backward invert modelling or forward modelling with parameter optimisation to minimise the error between the generated free-surface and the measurements. The model will enable the inference of turbulence properties and boundary conditions based on free-surface data, and will be ‘blind tested’ against new conditions in the laboratory.
It will also be tested at two field locations (river; treatment channel) to demonstrate the potential to remotely assess flow conditions in real applications.
- Publications
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Journal articles
- The ETNA mission concept: assessing the habitability of an active ocean world. Frontiers in Astronomy and Space Sciences, 9.
- Computational fluid dynamics simulation of rough bed open channels using openFOAM. Frontiers in Environmental Science, 10.
- Optimal use of titanium dioxide colourant to enable water surfaces to be measured by kinect sensors. Sensors, 20(12).
- Project SunbYte: solar astronomy on a budget. Astronomy and Geophysics, 58(2), 2.24-2.25.
Conference proceedings papers
- The Sheffield Space Initiative - Introduction, Motivation, and Impact Assessment. Proceedings of the 3rd Symposium on Space Educational Activities (pp 117-120). Leicester, UK, 16 September 2019 - 18 September 2019.
- The ETNA mission concept: assessing the habitability of an active ocean world. Frontiers in Astronomy and Space Sciences, 9.
- Research group
- Professional activities and memberships
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Chair of the IET Satellite Technical Network Young Professionals Committee
Royal Academy of Engineering Advanced Leadership Award receipient
Certified Solidworks Mechanical Design Professional (CSWP)