• Energy Research

Currently 40% of EU's final energy consumption is attributed to buildings. Achieving the EU's climate targets would entail improved strategies in designing nearly Zero Energy Buildings. This research aimed to create an integrated decision-making strategy in designing ZEBs with the use of multi-objective optimization of building design and construction parameters for minimizing energy demand, while maximizing energy production and adaptive thermal comfort. Goal is to define which parameters have the highest impact and potential for further optimization and to offer an alternative to current stepped strategies such as the New Stepped Strategy. The proposed integrated approach is applied on a typical high-rise office building in Greece. Energy simulations with DesignBuilder are used as benchmark for the optimization run with EnergyPlus through Rhino and Grasshopper software via the plug-ins Honeybee and Ladybug, coupled with modeFRONTIER. For the first optimization round, the investigated parameters are: window-to-wall ratio, wall U-value, glazing construction U-value, glazing g-value, air-tightness of the facade, cooling set-point of the mechanical cooling system and PV facade surface area. For the second round, the parameters of window-to-wall ratio, shading area and PV surface area are adapted for four facade orientations. The optimizations resulted in a building with an annual final energy reduction of 33%.

Currently 40% of EU's final energy consumption is attributed to buildings. Achieving the EU's climate targets would entail improved strategies in designing nearly Zero Energy Buildings. This research aimed to create an integrated decision-making strategy in designing ZEBs with the use of multi-objective optimization of building design and construction parameters for minimizing energy demand, while maximizing energy production and adaptive thermal comfort. Goal is to define which parameters have the highest impact and potential for further optimization and to offer an alternative to current stepped strategies such as the New Stepped Strategy. The proposed integrated approach is applied on a typical high-rise office building in Greece. Energy simulations with DesignBuilder are used as benchmark for the optimization run with EnergyPlus through Rhino and Grasshopper software via the plug-ins Honeybee and Ladybug, coupled with modeFRONTIER. For the first optimization round, the investigated parameters are: window-to-wall ratio, wall U-value, glazing construction U-value, glazing g-value, air-tightness of the facade, cooling set-point of the mechanical cooling system and PV facade surface area. For the second round, the parameters of window-to-wall ratio, shading area and PV surface area are adapted for four facade orientations. The optimizations resulted in a building with an annual final energy reduction of 33%.

Currently, several research projects investigate Additive Manufacturing (AM) technology as possible construction method for future buildings. AM methods have some advantages over other production processes, such as great freedom of form, shape complexity, scale and material use. These characteristics are relevant for façade applications, which demand the integration of several functions. Given the established capacity of AM to generate complex geometries, most existing research focuses on mechanical material properties and mainly in relation to the load-bearing capacity and the construction system. The integration of additional aspects is often achieved with post processing and the use of multiple materials. Research is needed to investigate properties for insulation, thermal storage and energy harvesting, combined in one component and one production technology.To this end, the research project “SPONG3D” aimed at developing a 3D-printed façade panel that integrates insulating properties with heat storage in a complex, mono-material geometry. The present paper gives an overview of the panel development process, including aspects of material selection, printing process, structural properties, energy performance, and thermal heat storage. The development process was guided by experiments and simulations and resulted in the design and manufacturing of a full-scale façade element prototype using FDM printing with PETG. The project proved the possibility of functions integration in 3D-printed façades, but also highlighted the limitations and the need for further developments. Design of Constrution Design Informatics Building Physics

Currently, several research projects investigate Additive Manufacturing (AM) technology as possible construction method for future buildings. AM methods have some advantages over other production processes, such as great freedom of form, shape complexity, scale and material use. These characteristics are relevant for façade applications, which demand the integration of several functions. Given the established capacity of AM to generate complex geometries, most existing research focuses on mechanical material properties and mainly in relation to the load-bearing capacity and the construction system. The integration of additional aspects is often achieved with post processing and the use of multiple materials. Research is needed to investigate properties for insulation, thermal storage and energy harvesting, combined in one component and one production technology.To this end, the research project “SPONG3D” aimed at developing a 3D-printed façade panel that integrates insulating properties with heat storage in a complex, mono-material geometry. The present paper gives an overview of the panel development process, including aspects of material selection, printing process, structural properties, energy performance, and thermal heat storage. The development process was guided by experiments and simulations and resulted in the design and manufacturing of a full-scale façade element prototype using FDM printing with PETG. The project proved the possibility of functions integration in 3D-printed façades, but also highlighted the limitations and the need for further developments. Design of Constrution Design Informatics Building Physics

The increase in global population, which negatively affects energy consumption, CO2 emissions, and arable land, necessitates designing sustainable habitation alternatives. Self-sufficient high-rise buildings, which integrate (electricity) generation and efficient usage of resources with dense habitation, can be a sustainable solution for future urbanisation. This paper focuses on transforming Europoint Towers in Rotterdam into self-sufficient buildings considering energy consumption and food production (lettuce crops) using artificial intelligence. Design parameters consist of the number of farming floors, shape, and the properties of the proposed façade skin that includes shading devices. Nine thousand samples are collected from various floor levels to predict self-sufficiency criteria using artificial neural networks (ANN). Optimisation problems with 117 decision variables are formulated using 45 ANN models that have very high prediction accuracies. 13 optimisation algorithms are used for an in-detail investigation of self-sufficiency at the building scale, and potential sufficiency at the neighbourhood scale. Results indicate that 100% and 43.7% self-sufficiencies could be reached for lettuce crops and electricity, respectively, for three buildings with 1800 residents. At the neighbourhood scale, lettuce production could be sufficient for 27,000 people with a decrease of self-sufficiency in terms of energy use of up to 11.6%. Consequently, this paper discusses the potentials and the improvements for self-sufficient high-rise buildings.

The increase in global population, which negatively affects energy consumption, CO2 emissions, and arable land, necessitates designing sustainable habitation alternatives. Self-sufficient high-rise buildings, which integrate (electricity) generation and efficient usage of resources with dense habitation, can be a sustainable solution for future urbanisation. This paper focuses on transforming Europoint Towers in Rotterdam into self-sufficient buildings considering energy consumption and food production (lettuce crops) using artificial intelligence. Design parameters consist of the number of farming floors, shape, and the properties of the proposed façade skin that includes shading devices. Nine thousand samples are collected from various floor levels to predict self-sufficiency criteria using artificial neural networks (ANN). Optimisation problems with 117 decision variables are formulated using 45 ANN models that have very high prediction accuracies. 13 optimisation algorithms are used for an in-detail investigation of self-sufficiency at the building scale, and potential sufficiency at the neighbourhood scale. Results indicate that 100% and 43.7% self-sufficiencies could be reached for lettuce crops and electricity, respectively, for three buildings with 1800 residents. At the neighbourhood scale, lettuce production could be sufficient for 27,000 people with a decrease of self-sufficiency in terms of energy use of up to 11.6%. Consequently, this paper discusses the potentials and the improvements for self-sufficient high-rise buildings.

As one of the most important design tasks of building design, space layout design affects the building energy performance (BEP). In order to investigate the effect, a literature review of relevant papers was performed. Ten relevant articles were found and reviewed in detail. First, a methodology for studying the effects of space layouts on BEP were proposed regarding design variables, energy indicators and BEP calculation methods, and the methodologies used in the 10 articles were reviewed. Then, the effects of space layouts on energy use and occupant comfort were analysed separately. The results show that the energy use for heating, cooling, lighting and ventilation is highly affected by space layouts, as well as thermal and visual comfort. The effects of space layouts on energy use are higher than on occupant comfort. By changing space layouts, the resulting reductions in the annual final energy for heating and cooling demands were up to 14% and 57%, respectively, in an office building in Sweden. The resulting reductions in the lighting demand of peak summer and winter were up to 67% and 43%, respectively, for the case of an office building in the UK, and the resulting reduction in the air volume supplied by natural ventilation was 65%. The influence of other design parameters, i.e., occupancy and window to wall ratio, on the effects of space layouts on BEP was also identified.