Set-Based Multi-Criteria Optimization of Slab Frame Bridges A Study on the Implementation of a Set-Based Multi-Criteria Optimization Algorithm on Slab Frame Bridges, considering Investment Cost, Environmental Impact and Buildability

Abstract

This master’s thesis presents research performed on parametric multi-criteria optimization in early stage design of slab frame bridges, using set-based design. As a result of immense CO2-emissions emerging from concrete production- and usage, there is a need for methods mitigating the volume of concrete without affecting the function of the structure. Set-based design was implemented in order to enable a wide design space during the design process, constituting a basis for facilitated negotiation in planning processes. Previous research suggests a general correlation between curtailed CO2-footprint and cost reduction, due to minimized material use. However, the aspect of buildability may conflict with lessened material, as slim designs might simultaneously entail a more time consuming production. This research aimed to develop an optimization method with respect to investment cost and environmental impact, while concurrently considering the potentially contradictory criterion of buildability. Possible quantitative measurements of the buildability criterion were thus explored. In addition, the method focused on generating large data sets of possible bridge designs, increasing the potential of obtaining statistical significance in the optimization results. An algorithm was created using Python-programming within the Grasshopper interface, connected to the 3D modelling software Rhino. The results demonstrated the buildability criterion to be decisive when finding optimal bridge designs in the multi-criteria optimization. In relation to the reference project, it was concluded that the most optimal design was predominantly governed by buildability aspects, resulting in limited environmental impact reductions. Therefore, a geometrically optimized design with the lowest environmental impact was also sought, yielding slightly increased costs for the client, caused by buildability costs related to the slimmed design. Conclusively, there is considerable incentive for implementing set-based optimization procedures in the everyday work of bridge engineers. Thereby, far-fetched optimal solutions can be identified in an early stage providing a basis for negotiation during tendering procedures, and risks related to unforeseen costs are mitigated.