Effect of space layouts on the energy performance of office buildings in three climates

Du, Tiantian; Jansen, Sabine; Turrin, Michela; Dobbelsteen, Andy van den

doi:10.1016/j.jobe.2021.102198

Cited by 15 publications

(13 citation statements)

References 24 publications

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“…The corridor was not considered in this layout. The method for generating the layout was developed based on a reference layout, which was previously published by the authors [20]. The layout included 12 rooms, i.e., 6 offices, 2 meeting rooms, 1 canteen, 1 break room, 1 core and 1 staircase.…”

Section: Generation Of Space Layoutmentioning

confidence: 99%

“…In this study, the annual heating, cooling and lighting demands for the whole layout were used to assess the energy performance. The detailed information about energy and daylight performance simulation were shown in our previous study [20]. The temperate climate data of Amsterdam in the Netherlands was used.…”

Section: Energy and Daylight Performance Assessmentmentioning

confidence: 99%

“…The WWR of the simulation model was kept at 40%. Different from our previous work [20] which took into account a geometrically fixed layout, the daylight simulation model of the study dynamically separated one room into three lighting zones based on yearly daylight illuminance. Similarly, as for the room with different façade orientations, its windows were assigned to two different shading groups, the maximum number allowed by Ladybug tools.…”

Section: Energy and Daylight Performance Assessmentmentioning

confidence: 99%

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Relationship Analysis and Optimisation of Space Layout to Improve the Energy Performance of Office Buildings

Turrin

Jansen

et al. 2022

Energies

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Architectural space layout has proven to be influential on building energy performance. However, the relationship between different space layouts and their consequent energy demands has not yet been systematically studied. This study thoroughly investigates such a relationship. In order to do so, a computational method was developed, which includes a method to generate space layouts featuring energy-related variables and an assessment method for energy demand. Additionally, a design of experiments was performed, and its results were used to analyse the relationship between space layouts and energy demands. In order to identify their relationship, four types of design indicators of space layout were proposed, both for the overall layout and for each function. Finally, several optimisations were performed to minimise heating, cooling and lighting demands. The optimisation results showed that the maximum reduction between different layouts was up to 54% for lighting demand, 51% for heating demand and 38% for cooling demand. The relationship analysis shows that when comparing the four types of design indicators, the façade area-to-floor area ratio showed a stronger correlation with energy demands than the façade area ratio, floor area ratio and height-to-depth ratio. Overall, this study shows that designing a space layout helps to reduce energy demands for heating, cooling and lighting, and also provides a reference for other researchers and designers to optimise space layout with improved energy performance.

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Section: Generation Of Space Layoutmentioning

confidence: 99%

Section: Energy and Daylight Performance Assessmentmentioning

confidence: 99%

Section: Energy and Daylight Performance Assessmentmentioning

confidence: 99%

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Relationship Analysis and Optimisation of Space Layout to Improve the Energy Performance of Office Buildings

Turrin

Jansen

et al. 2022

Energies

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“…However, there exist only a few studies that focus on space organization. Most of them focus on energy performance optimization [48], nature-inspired interiors [49], automatic generation [50] or cost reduction [51]. These studies represent an important step in the achievement of passive building energy and comfort optimization, however, most of these studies concentrate only on layout development, without considering the complete and systematic space arrangement and as an effect the building body shape typology.…”

Section: Introductionmentioning

confidence: 99%

Algorithmic Generation of Building Typology for Office Building Design

2022

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Numerous office building design optimizations are in international research to reduce energy consumption, optimize costs and provide optimal comfort. However, there is a lack of knowledge on the effects of geometry and space organization. This study deals with space organization problems and searches for all possible optimal building space structure configurations in terms of energy and comfort parameters using a mathematical algorithmic method. The methodology is based on the formulation of feasible architectural rules and their translation into an algorithm that can generate 2D floor plans satisfying all boundary conditions. In the framework of an exemplary modeling procedure, a 4-story office building geometry generation was carried out, resulting in 17-floor plan versions and 7 different building geometries. The resulting building shapes were classified by energy-related geometry parameters (envelope surface/useful area) for the future step of the research, where the cases will be compared with the help of building simulations. With the help of the method, it was possible to significantly narrow the search space, but future improvements are needed for faster work for wider applicability.

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“…Furthermore, previous approaches do not take spatial layouts as a design variable (Li et al, 2009;Yu et al, 2010;Wang et al, 2018;Olu-Ajayi et al, 2022), since they assume that the design is fixed when conducting energy analysis. However, the spatial layout is an important design variable for building energy performance (Du et al, 2021), and architects adjust it iteratively during the early design phase.…”

Section: Introductionmentioning

confidence: 99%

Energy-aware design: predicting building performance from layout graphs

Jianpeng¹,

Hang²,

Anton³

et al. 2022

Proceedings of the 2022 European Conference on Computing in Construction

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Graph Neural Networks (GNNs) have become a popular toolkit for generative floor plan design. Although design variation has improved greatly, few studies consider nongeometrical characteristics, such as building performance, in the generative design process. This paper presents a GNN-based approach to predict the energy performance for floor plan customization (energy-aware design). The approach lays the foundation for a performance-aware generative design using GNN. The results show that the GNN can achieve high accuracy in energy performance prediction.

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Effect of space layouts on the energy performance of office buildings in three climates

Cited by 15 publications

References 24 publications

Relationship Analysis and Optimisation of Space Layout to Improve the Energy Performance of Office Buildings

Relationship Analysis and Optimisation of Space Layout to Improve the Energy Performance of Office Buildings

Algorithmic Generation of Building Typology for Office Building Design

Energy-aware design: predicting building performance from layout graphs

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