materials may be used as lightweight replacement but often lack the mechanical
and functional response of the structure they replace. Also, traditional long
fiber composite materials do not allow for the variety of shapes required form
most applications. By using 3DP of particulate suspensions, supplemented by
external forces such as vibration, electric or magnetic fields, composite
materials with intricate shapes and expected properties are aimed to be
fabricated. Orienting or positioning the particles into a hierarchical
structure could combine the structural and functional response desired.
of the PhD thesis will tackle both manufacturing and characterization.
in materials science or in mechanics is required, with interest in some of the
following areas: colloidal science, rheology, magnetic fields, microscopy,
fracture mechanics, bio-inspiration and robotics.
candidate should be able to work in an inter-disciplinary environment and be
enthusiast for learning and developing new skills.
Interested applicants, please contact Dr Hortense Le Ferrand at email@example.com.
Interested applicants please send your full CV to the PI directly.
The CV should include education, experience, interests and the names and contacts of 2 referees.
Project 4: Vision feedback on freeform-shaped structure 3D printing
Supervisor: Associate Professor Tegoeh
Printing a complex wall with a passive system might result in uneven surfaces, which is due to the rheology of the concrete mixture as thixotropic fluid. Wall printing with a rectangular orifice nozzle does not consequently result in a rectangular extrudate shape. In order to adjust the resulting extrudate shape, a smart variable orifice nozzle that can change its outlet shape to adapt for different wall profile requirements, e.g. walls with different slanted angles as in a dome, has been developed. A constituted nozzle-extrudate shape relationship has also been formulated using neural-network approaches and preliminary results have shown potential implementations.
However, concrete printing by nature is a complex process. The extrudate shape does not depend only on the orifice shape but also on tons of other parameters, including the concrete mixture composition, material flows and time. Slight variations on the parameters to those from where the nozzle-extrudate shape relationship were established might cause unexpected changes on the resulting extrudate shape. This leads to the requirement of a feedback loop to adjust the deviation to the wall profile. One potential approach is by using vision feedback, where the resulting wall profiles during the printing process is visually monitored using a computer vision approach and any deviations from the wall profile references will be corrected through the adjustable orifice nozzle. As a result, the complete system is expected to be able to print any complex wall structures, e.g. complex shape walls or dome, with acceptable surface profile quality.
Mechanical/mechatronics student with strong background in control and machine/deep learning.