Sustainability is an increasingly important factor in global decision-making, and
provision of infrastructure is responsible for a substantial volume of global greenhouse gas
emissions. Whilst efforts are ongoing to reduce operational carbon in the construction
industry, work is still necessary to lower embodied carbon. Currently, the optimisation
and design process of structures is largely based on engineers’ experience. Whilst
this experience is extremely valuable and will often reach good results, making use of
computational technologies that are now available could achieve improved results whilst
also saving time in the design process. This could lead to more efficient designs and
savings on material quantities, lowering the embodied carbon of structures. This thesis
aims to develop optimisation tools for tall buildings, which are an increasingly common
structural form constructed, to assist their efficient and sustainable design.
The PhD project has been conducted in collaboration with industry to ensure its
applicability to projects encountered in structural consultancy offices, with relevant
outputs. A qualitative study has been conducted to assess the current and future place
of computational engineering in the construction industry. The computational tools
developed include concrete core, slab and column optimisation including sizing of core
and columns, and grid layout and bracing arrangement optimisation for steel buildings
including sizing optimisation. They aim to be versatile, robust and user-friendly, having
been developed in an accessible, widely used software environment. They have been
tested on theoretical and retrospective case studies and are now accessible to practising
engineers.
The engineering research presented is intended to be used in various design stages with
a focus on early design stages, an area where valuable benefits both on environmental
sustainability and design process efficiency can be reached. It enables engineers, in
conjunction with their technical experience, to search the design space available more
efficiently, to conduct analysis and optimisation and to make informed decisions earlier in
the design process than would be possible with standard design methods.