Toolbox for super-structured and super-structure free multi-disciplinary building spatial design optimisation

Multi-disciplinary optimisation of building spatial designs is characterised by large solution spaces. Here two approaches are introduced, one being super-structured and the other super-structure free. Both are different in nature and perform differently for large solution spaces and each requires its own representation of a building spatial design, which are also presented here. A method to combine the two approaches is proposed, because the two are prospected to supplement each other. Accordingly a toolbox is presented, which can evaluate the structural and thermal performances of a building spatial design to provide a user with the means to define optimisation procedures. A demonstration of the toolbox is given where the toolbox has been used for an elementary implementation of a simulation of co-evolutionary design processes. The optimisation approaches and the toolbox that are presented in this paper will be used in future efforts for research into- and development of optimisation methods for multi-disciplinary building spatial design optimisation

Multi-objective mixed-integer evolutionary algorithms for building spatial design

Multi-objective evolutionary computation aims to find high quality (Pareto optimal) solutions that represent the trade-off between multiple objectives. Within this field there are a number of key challenges. Among others, this includes constraint handling and the exploration of mixed-integer search spaces. This thesis investigates how these challenges can be handled at the same time, and in particular how they can be applied in the multi-objective optimisation algorithms. These algorithms are developed in the context of the optimisation of building spatial designs, which describe the exterior shape of a building, and the internal division into different spaces. Spatial designs are developed early in the design process, and thus have a large impact on the final building design, and in turn also on the quality of the building. Here the structural and thermal performance of a building are optimised to reduce resource consumption. The main contributions of this thesis are as follows. Firstly, a representation for building spatial designs in is introduced. Secondly, specialised search operators are designed to ensure only feasible solutions will be explored. Thirdly, data about the discovered solutions is analysed to explain the results to domain experts. Finally, a general purpose multi-objective mixed-integer evolutionary algorithm is developed. This work is part of the TTW-Open Technology Programme with project number 13596, which is (partly) financed by the Netherlands Organisation for Scientific Research (NWO).Computer Science

Integrated parametric multi-level information and numerical modelling of mechanised tunnelling projects

This paper presents a concept for parametric modelling of mechanized tunnelling within a state of the art design environment, as the basis for design assessments for different levels of details (LoDs). To this end, a parametric representation of each system component (soil with excavation, tunnel lining with grouting, Tunnel Boring Machine (TBM) and buildings) is developed in an information model for three LoDs (high, medium and low) and used for the automated generation of numerical models of the tunnel construction process and soil-structure interaction. The platform enables a flexible, user-friendly generation of the tunnel structure for arbitrary alignments based on predefined structural templates for each component, supporting the design process and at the same time providing an insight into the stability and safety of the design. This model, with selected optimal LoDs for each component, dependent on the objective of the analysis, is used for efficient design and process optimisation in mechanized tunnelling. Efficiency and accuracy are further demonstrated through an error-free exchange of information between Building Information Modelling (BIM) and the numerical simulation and with significantly reduced computational effort. The interoperability of the proposed multi-level framework is enabled through the use of an efficient multi-level representation context of the Industry Foundation Classes (IFC). The results reveal that this approach is a major step towards sensible modelling and numerical analysis of complex tunnelling project information at the early design stages