Enhancing quality and durability of Ultra High Performance Fibre-reinforced Self-Compacting Concrete via advanced modelling techniques.

Self-compacting fibre-reinforced concrete (SCFRC) has many attractive features including high tensile strength and toughness, excellent long term durability, low carbon footprint and thus sustainability. The concrete structures produced from SCFRC will also acquire these desirable characteristics, provided the fibres within them are evenly and favourably oriented to the direction of loading. According to fib Model Code 2010, a partial safety factor associated with fibre orientation called orientation factor is used in the design of SCFRC structures to account for the lack of information available to correlate the strength of a structure with fibre distribution and orientation. If the fibre distribution and orientation, and hence the orientation factor can be effectively predicted, the superior properties of SCFRC can be exploited to the full extent.
Although laboratory experimental techniques are used to investigate the properties of SCFRC in the fresh state, they have limitations besides significant cost implications. Hence, the computational modelling of SCFRC in the fresh state while it is being cast into the formwork is the best alternative. With the rapid development of computer architectures, the issues relating to the computational cost of numerical simulations are becoming less significant. Therefore, we propose to develop an efficient computational methodology to simulate the entire casting of industrial standard structural components produced from SCFRC, tracking the reorientation of fibres during the flow, validate it by CT imaging and formulate detailed design information and guidelines. Such a computational simulation strategy will improve the economics of the SCFRC manufacture and pave the way for its rapid production and wider application in the construction industry.
In this context, the main aim of this PhD project is to develop an accurate and efficient computational procedure to simulate the flow of SCFRC into formwork. The supervisory team has significant expertise and is internationally well renown for both design and modelling of SCFRC.


Candidates should hold or expect to gain a first class degree or a good 2.1 and/or an appropriate Master’s level qualification (or their equivalent).

Applicants whose first language is not English will be required to demonstrate proficiency in the English language (IELTS 6.5 or equivalent)