The Chair of Architecture and Building Systems offers supervision of doctoral students whose research topics correspond to the research interests of the chair. The admission requirements for doctoral studies are a Master’s degree from a recognized university and an excellent academic performance. If you are interested in joining the A/S Research Team as a PhD student, please prepare a thesis proposal stating your subject of research, goals, methods, and deliverables. Please be advised that PhD candidates can only be accepted in connection with an employment at the chair. Refer to .
A list of current dissertations including short abstracts is provided below. For information on completed dissertations, see Doctoral Theses under Publications.
Data-Driven Building Retrofit
Due to the relatively low construction rate of new buildings in Europe, the energetic performance of the building stock can mainly be improved by retrofitting existing buildings. In order to address the short comings of current building assessment methods, we propose a data-driven-retrofit (DDR) approach to derive optimal retrofit measures. The approach uses wireless sensor networks (WSN) for the determination of building characteristics. With the collected data, building models can be calibrated and retrofit measures can be incorporated in these building models, in order to find the optimal combination of retrofit measures.
District-Level Building Performance Modeling
The energy demand in mixed-use buildings is quantified by modeling the interactions of building design parameters, buildings systems, building occupant behavior and the environment. At the design stage at the urban scale the spatiotemporal patterns of demand influence the energy supply system design and performance. The focus of this work is on energy-related occupant behavior, which can lead to significant differences in the energy consumption patterns of similar buildings. Different modeling techniques, such as agent-based modeling, will be used to simulate the presence and activities of inhabitants in different buildings in the district. Based on those outputs, the energy demand of the buildings is calculated. With such a model the evolution of the energy demand over time due to changes in boundary conditions can be simulated and possible synergies between functions in mixed-use buildings can be uncovered. Results of the work will potentially be used to propose new urban planning strategies and urban design rules, as well as to design resilient energy supply systems.
Low Carbon District Energy Supply Systems in the Tropics
Energy supply systems in the tropical regions are facing several challenges and opportunities along the path to a low carbon future. The energy challenges include: fast urbanization, growing standards of living, and higher cooling requirements. On the other hand, new technologies offer opportunities in the subsystems along the energy supply chain (conversion, storage and distribution). For instance, desiccant cooling devices that provide efficient latent cooling and networks that allow efficient utilization of energy resources. The thesis work focuses on identifying suitable energy system configurations in the tropics. The low carbon supply systems should not only integrate the carbon reduction opportunities within the subsystems, but also take the local resources and climate limitations into account. System configuration performances are assessed by a modelling framework. Furthermore, the modelling framework can also be used to uncover the critical factors from urban design that influence energy system designs and performances.
Holistic Assessment of Active Multifunctional Building Envelopes
The application of multifunctional building envelopes is being put forward as a method of greatly reducing the building energy consumption, while still maintaining user comfort. This thesis will investigate the energy savings potential of a multifunctional envelope through numerical simulations, experimental validation, and an analysis from a life cycle perspective. The primary outcome is to enable architects and engineers to determine if a multifunctional facade is appropriate for their building, and if so what type of building system would match their envelope of choice.
Characterization of Temporal Energy Data from Large Groups of Non-residential Buildings
The thesis investigates a set of temporal features to characterize data from energy meters in non-residential buildings. These features include statistical aggregations, weather sensitivity metrics and pattern-based motif and discord detection using Symbolic Aggregate Approximation (SAX) and text mining. The range of features are implemented on 492 case study buildings and classification accuracy of predicting building type, performance class and retrofit efficacy is tested. The techniques are then scaled to an Advanced Metering Infrastructure data-set of 40,000 building.
Energy-Driven Generative Urban Design Modelling at Neighbourhood Scale
Buildings are the main energy consumers in cities. Massive work has been done on the green features for better energy performances of an individual building. Gradually, designers and researchers realise the necessity and importance of considering a cluster of buildings together at neighbourhood scale with a system thinking. Urban designers usually use energy simulation tools in the post-design evaluations on a few different urban design scenarios. However, a tool that can provide the designers with energy-driven suggestions and possible design options in the early stages will be much more helpful. This tool generates design options with a set of generic and energy-driven urban design rules through proper generative design techniques. This PhD research focuses on the making of such rule sets and the building of the model behind the tool. Potentially, the outcome of this research will be applied to an urban design practice in Singapore.
Learning-Based Control of Soft Robotics Driven Modular Solar Façade for Energy Efficient Buildings
Buildings are one of the largest contributors to climate change, with 19% of global greenhouse gas emissions, coming solely from their operations (5th IPCC Report, 2014). A building element that strongly influences both building energy efficiency and occupants’ comfort is the building facade. In my PhD, I am part of the team that develops a lightweight, modular, and automated shading system with integrated photovoltaics – the Adaptive Solar Façade. In particular, I focus on the control system of the façade, from actuator level, over maximisation of energy production of the whole façade, to interaction with the occupant. In this light, the top-level control is of particular concern, where there is a challenge to develop an automatic control algorithm that learns occupants’ comfort needs, provides an energetically efficient response, and maintains the comfort-energy balance over time.
Distributed BIM based Building Process
Conventional BIM distribution is server-based architecture with a centralized structure that can be connected by clients (users) remotely. However, the client side components are restricted in applications and platforms. Traditional BIM applications have difficulties in delivering flexible, user friendly BIM information and do not support real-time interoperability. Distributed BIM is a concept of cross-platform, real-time service oriented and application based collaboration. This PhD research covers methods of distributed BIM and the information exchange between different discipline models and BIM models (e.g. energy model and architectural BIM model). The goal is to benefit the collaboration between users and participants of different disciplines in the building process.