ICDA: Interactive Computational Decision Support for Architecture, Ioannis Chatzikonstantinou

Architectural design entails, to a large degree, criteria that are not easily quantifiable. Such criteria are related to psychological and cognitive aspects of design, such as spatial experience and aesthetics. Due to this fact, the use of computational optimization methods in architectural design, while having the potential to benefit design a great deal, is severely limited. The motivation behind this thesis is to facilitate the inclusion of qualitative criteria alongside quantitative objectives, in an integrated computational optimization framework. We consider as a starting point the proposition that decision maker input is invaluable in providing information regarding their preferences, and that the decision maker should be involved during the optimization process. Interactive optimization systems, such as Interactive Evolutionary Computation (IEC), are high on the modern scientific agenda, but encounter challenges dealing with human cognitive limitations. This thesis proposes an adaptive and cognition modeling framework, that can capture the preferences of the user, while complying to human cognitive limitations at hand. Furthermore, we address the issue of integration of the proposed framework to a multi-objective approach, with the aim of simultaneously tackling qualitative and quantitative objectives, in demanding real-world problems. Finally, we validate the proposed framework on a real-world design problem and conduct a user survey to evaluate the effectiveness of the proposed method.

Promoter: S. Sariyildiz | Supervisor: M. Turrin

Solar Geometry in Performance of Built Environment, Miktha Farid Alkadri

This research aims at proposing a novel design framework for designing a solar geometry in a built environment, in order to achieve the maximum performance in terms of comfort and energy use in architecture design. This research specifically attempts to address the lack of understanding on site characteristic information leading to the unexpected failure after the building was located. The ultimate goal is to allow architects to make informed design decision towards high-performed design through 3D point cloud data and the solar envelope performance. It particularly investigates two sections: first, the attribute information of 3D point cloud as an input of the environmental database. This database then comes with the simulation of solar radiation integrated with the material properties of the existing context. Second, design principle of solar envelopes aiming to examine design requirement of the solar access in the new development areas.

Promoter: S. Sariyildiz | Supervisor: M. Turrin

Configurational Layout Optimization for Hospital Design, Cemre Cubukcuoglu

Hospital facilities are known to be functionally complex buildings in various ways, namely due to their spatial connectivity requirements. There are usually configurational problems that lead to inefficient circulation of medical staff, difficult way finding for visitors, lengthy procedures, long walking times, etc. This PhD research aims to investigate the relation between the performance of hospital buildings with their configurational layout at various levels of abstraction; and to devise configurational layout optimization methods for optimal layout of hospital buildings. Spatial layout methods will be designed and tested by using Graph Theory, Facilities Planning, and Soft Computing methodologies.

Promoters: S. Sariyildiz, M.F. Tasgetiren (external) | Supervisor: P. Nourian

Computational Intelligence in Decision Making for Self-Sufficient High-Rise Buildings, Berk Ekici

This research is focusing on the concept of self-sufficient high-rise buildings, which can play an important role for future urbanization. With this regard, development of a computational model for designing self-sufficient high-rise buildings is the main purpose. For this reason, two main research domains, which are high-rise buildings and computational intelligence, will take part to realize this research. In order to develop the computational model, three main steps are considered. These are developing parametric high-rise form generation, implementing self- sufficient criteria to evaluate the building performance, and make use of the power of computational intelligence to deal with such complex design task. As a result, it is aimed to reach tested computational model, which can be used by architects to design self-sufficient high-rise buildings for the future.

Promoters: S. Sariyildiz, M.F. Tasgetiren (external) | Supervisor: M. Turrin

The AM envelope: A mono-material façade element with complex geometries for structural and thermal performance MSc Thesis, Valeria Piccioni.

Abstract by the student: “Compared to traditional techniques, AM stands out for the possibility of fabricating complex geometries embedding multiple functions. This study explored how the potentials of Fused Deposition Modelling can be used to create a multi-functional façade element for thermal insulation and structural stiffness. Physical testing and software simulations have been performed to assess the properties of complex geometries and retrieve design guidelines. A digital workflow was developed, encompassing performance-driven design, performance assessment and geometry generation for fabrication. The study highlights how, by manipulating porosity and material distribution, it is possible to design stiff, insulating envelope components which are suitable for manufacturing with FDM using polymers.”

Main mentor: M. Turrin; second mentor: M. Tenpierik; in collaboration with Arup Amsterdam (S.Ren)