Building Floor Plans Research Articles

Building layout assessment on fire evacuation efficiency by integrating graph theory and virtual reality

The building layout design significantly impacts the fire evacuation process. Existing research focused on evaluating potential evacuation routes and investigating evacuation behaviour with different guidance systems. However, these studies have overlooked the effect of building layout design on visual attention and evacuation behaviour during fire evacuation. Therefore, this paper proposed a methodology to evaluate the building floor plans and evacuation routes by integrating Graph Theory (GT) and Virtual Reality (VR) technology. Building layouts and evacuation routes were represented as graphs and subgraphs, enabling a numerical evaluation of the efficiency of evacuation routes. To further investigate occupants’ attention allocation and evacuation behaviour during the wayfinding process, an eye-tracking function was developed and embedded in a VR platform. Moreover, evacuation behaviours and corresponding time were identified and assigned to the features of edges in the subgraphs, based on which the impact of spatial design on evacuation behaviour was analysed. The findings highlighted the significant impact of route characteristics and signage visibility on attention allocation and evacuation behaviour. Following that, recommendations were provided to building designers to improve fire evacuation efficiency. This study provides emergency behaviour observations and offers a comprehensive evaluation of building layout design, contributing to supporting designers in building design assessment in terms of fire evacuation efficiency.

Human Perception of Floor Plan Evacuatability: How Easy is it to Evacuate?

Currently there is no easy way to rate the ease of evacuation from a building in case of fire or a shooter. Multiple tools, based on agent-based models, exist to simulate building evacuation. However, they have not been compared with human perceptual data of how easy people think it would be to evacuate from a building. This research is part of a project to establish an EASE score (Evacuation with Acceptable Simplicity in Emergencies) and validate that metric with human data. In this study, the authors asked participants to evaluate seven 2D building floor plans for ease of evacuation. There is a gap in the research on perceptions of floor plans which motivated this study’s research questions: (a) Do non-expert users agree on the ease of building evacuation? (b) What factors do viewers use to evaluate ease of evacuation?

Mitigating vibration from building systems in a second-floor laboratory

A second-floor laboratory reported excessive vibrations that were impacting the calibration of microscopes, as well as human comfort. Based on a review of the building floor plans and discussions with the Design-Build team, potential vibration sources were narrowed to various MEP equipment in the first-floor mechanical room, rooftop, and outdoor utility pad. Vibration measurements were collected in the laboratory and near each piece of mechanical equipment as the equipment was turned ON and OFF to determine its vibration impact on the laboratory. The narrowband frequency data indicated that the rotational frequency of the ceiling-mounted hot water pumps coincided with the frequencies of excessive vibration in the lab. Vibration isolation for the hot water pumps and surrounding piping and equipment was reviewed, and recommendations were provided based on ASHRAE guidance to minimize vibration propagation to the laboratory.

Co‐working office spaces in Sydney: Spatiotemporal dynamics and industry patterns

AbstractCo‐working spaces have emerged as cost‐effective office space management solutions for workers from diverse industries who share space, which generates cost savings and facilitates networking opportunities. Past studies have mainly focused on needs for and benefits of co‐working spaces and range in emphasis from design preferences to potential social and economic impacts. However, limited attention has been given to the temporal clustering and geographical distribution patterns of co‐working spaces. This study examines the spatial distribution patterns of co‐working spaces establishments in terms of building floor plans. We discern the subcategory of ‘co‐working office space’ from the floor space and employment survey data, spanning 2007, 2012, and 2017 as collected by the City of Sydney, a municipal government in Australia. Both co‐working offices offered by conventional enterprises and co‐working providers are identified, and the spatial associations between co‐working spaces and their relationships with industry composition are analysed. Using establishment analysis, three co‐working spaces are identified: (1) dedicated co‐working enterprises providing office service and well‐design spaces; (2) conventional office rental enterprises diversifying into co‐working style office; and (3) standard enterprises converting fixed office spaces to co‐working office configurations. The spatial analysis reveals an outward diffusion of co‐working spaces from the centre of Sydney CBD, which is of importance in geographical research focused on urban, social, and economic change.

Integrating Pix2Pix and computational fluid dynamics for enhanced indoor airflow prediction: A case study with wing-walls

Computational Fluid Dynamics (CFD) is often used for analyzing natural ventilation but is limited in early design stages due to its high computational demands and the need for detailed inputs. To overcome such limitations of CFD simulation, this paper proposes a method using a conditional Generative Adversarial Network (cGAN) based image-to-image translation (Pix2Pix) to predict the indoor airflow condition. Compared to other traditional machine learning models that predict averaged values like indoor air velocity, Pix2Pix can predict contour plot of indoor airflow for the given building floor plan image, which provides more intuitive feedback to designers. The proposed method was tested to understand indoor air movement caused by wing-walls attached to the windows. The model was trained using 1153 pairs of floor plan images, incorporating variations in window widths, wing-wall depth, wing-wall angle, wind speed, and wind direction. It achieved a prediction accuracy of 94 % and produced results in less than a second. Moreover, the model showed relatively better performance with the changes in windows and wing-walls properties rather than wind properties. This high performance indicates that Pix2Pix can serve as an efficient proxy model of conventional CFD simulations, helping designers optimize ventilation in building designs at an early stage without the need for complex inputs.

Comparing spatial navigation in a virtual environment vs. an identical real environment across the adult lifespan

Virtual environments (VEs) are increasingly being used as a research platform for investigating human responses to environmental variables. While VEs provide tremendous advantages in terms of variable isolation and manipulation, and ease of data-collection, some researchers have expressed concerns about the ecological validity of VE-based findings; that is, their transferability to real-world contexts. In the current study we created a virtual replica of a real-world, multi-level educational facility, and compared data collected in the VE vs. the real-world environment as participants completed identical navigational tasks. We found significant differences in all of the measures used, including distance covered, number of mistakes made, time for task completion, spatial memory, extent of backtracking, observation of directional signs, perceived uncertainty levels, perceived cognitive workload, and perceived task difficulty. We also analyzed potential age-related effects to look for heightened VE/real-world response discrepancies among older adult participants (age 55 or over) compared to younger adults (18–30 years of age). This analysis yielded no significant age-by-condition interaction effects. Finally, we examined the spatial distribution of self-reported wayfinding uncertainty across the building floorplan, finding that areas in which uncertainty was most pronounced were similar between the real-world and VE settings. Overall, these findings indicate that while virtual reality can be a useful design research tool, caution is needed when interpreting and generalizing its results.

Seismic Response of Stiffness Irregularity at Ground Floor with and without Shear Walls

In today's scenario, one of the greatest challenges for structural engineers is designing and constructing seismic-resistant structures. Seismic activity, or earthquakes, poses a significant threat to civil engineering structures, and ensuring that buildings can withstand the forces generated during an earthquake is crucial for public safety and infrastructure resilience. Irregular configurations, whether in the building's floor plan or its elevation, are widely acknowledged as significant contributors to failure during seismic events. These irregularities can lead to uneven distribution of forces and stresses, compromising the building's ability to withstand the seismic forces and potentially resulting in structural failure. Soft storeys, typically located at ground levels for various functional purposes, pose challenges in seismic regions due to their lack of sufficient lateral load-resisting elements resulting in excessive lateral deformation and collapse during intensive earthquakes. Hence, the present study investigated the seismic response of irregular reinforced concrete structures possessing stiffness irregularity at ground floor with and without shear walls. A ten-storey regular frame is modified by incorporating vertical irregularity in elevation by increasing the height of the ground floor. The complete structural analysis and modeling are carried out by using the software ETABS 2020. The Time History method is applied, and the study is focused on seismic zones V in India. The performance of structures are compared based on criteria such as storey displacement, storey drift, storey shear and overturning moment. The results lead to the conclusion that a building structure exhibiting stiffness irregularity is prone to instability which is indicated by higher displacement and drift values. Structures incorporating shear walls have demonstrated greater stability compared to structures without shear wall as they exhibited higher base shear values and experienced a reduction in lateral displacement by more than 40%. The presence of shear walls also has enhanced the stability and strength of the structure, showing a linear response during critical earthquakes.

Natural Ventilation and Indoor Air Quality in Domestic School Building: CFD Simulation and Improvement Strategies

Natural ventilation is a process of replenishing used air from the interior environment with fresh outer air without the use of mechanical equipment. This project aims to investigate the feasibility and performance of implementing natural ventilation in dilapidated classroom designs of actual geometry. Computer models of an existing classroom were created using SOLIDWORKS based on real-scale building floor plans, while the same software was applied to compute flow simulation studies to visualise the airflow pattern, temperature distribution, relative humidity, and the thermal comfort level of occupants in the classrooms. Estimated climate parameters were input in the simulation process to illustrate better the effect of hot and humid climate conditions in Malaysia towards the thermal comfort level of occupants. In this project, a visualised wind tunnel was created to simulate the prevailing wind source that supplies wind to the designed classroom, and the airflow pattern across the designed building was analysed. From the initial simulation results, it was discovered that the airflow into the classroom is uneven, whereby some locations in the building are experiencing extremely low wind breeze, which eventually affects the comfort level of occupants in the room. On the other hand, an internal analysis focusing on the interior comfortability of the classrooms was applied to examine the thermal comfort condition while using the naturally ventilated classrooms. Recommendation optimisation approaches such as the louvre angle and introduction of a windcatcher was presented in this project to improve the natural ventilation performance of the designed classroom.

Floor plan graph learning for generative design of residential buildings: a discrete denoising diffusion model

ABSTRACT Floor planning, as one of the most important considerations in building design, often involves intensive trial-and-error processes with many constraints considered simultaneously. Artificial intelligence (AI) generative design solutions being developed are hampered by two shortcomings. Firstly, the vast topological knowledge embedded in existing floor plans has been largely unexplored and is thus wasted. Secondly, an efficient methodological instrument to learn the topological knowledge for generative design is lacking. This paper aims to develop a graph learning methodology to learn graph knowledge from floor plans and generate knowledge ready for building generative design. A discrete denoising diffusion model (D3M) that can learn topology graphs via its bi-directional structure of ‘corruption and denoise’ is developed and trained using more than 80,000 floor plans from a large-scale dataset. It is found that the D3M can learn the knowledge from floor plans and present it as various building floor topologies, which are evaluated in a preliminary case study as reliable and useful for generating real-life building floor plans. The research provides a design knowledge management framework that can be further implemented in academic works and design practices through some mainstreaming or commercializing efforts.

Relationship between composition, emplacement and construction: the auditorium of the Labour University of Cheste

The analysis of the regulating lines that geometrically and dimensionally determine the design of a building floor plan helps to understand the ideation and execution of buildings. However, the relationship between aesthetic value and functionality and how they were represented became more complex in the twentieth century. The Auditorium of the Labour University of Cheste is one example that demonstrates this complex relationship. This research focuses on the study of the regulating lines that determine the design of the building as well as the relationship of the construction and structural systems of the Auditorium with these design rules, the characteristics of the Modern Movement architecture, the climate, and the location. The study provides a deeper understanding of the building’s past and present, creating the basis for analysing the main durability problems of many of the buildings of this period, as well as their state of abandonment. It also allows the foundations for the future of these buildings to be laid by taking advantage of their built value, which is necessary from a functional but also sustainable point of view. The comprehension of the regulating lines and the architectural background are established as the foundation for proposing renovation solutions that restore the use of these buildings while maintaining their aesthetic and material value.

Smart fire detection analysis in complex building floorplans powered by GAN

Ceiling-mounted fire service systems are the most widely used provisions to ensure building fire safety. Current design distribution of fire detectors is based on semi-empirical correlations derived from open-floor fire experiments, but building floorplan affects their activation. This work develops a generative adversarial network (GAN) model to achieve accurate and real-time fire detection analysis for buildings with complex floorplans. A numerical fire database with hundreds of floorplans, fire locations and ceiling heights is established to train the GAN model. The pre-trained model can recognize geometric characteristics and reveal hidden fire dynamics laws. Given any building floorplan and fire detector distribution, the model can predict ceiling temperature, velocity and soot density fields with an accuracy of 88% in a second and detection time with 95% accuracy. The proposed GAN model enables a smart fire detection analysis, reduces the fire engineering design cost, and improves fire safety for complex buildings.

Generative design of floor plans of multi-unit residential buildings based on consumer satisfaction and energy performance

Satisfying consumers is an important task in the design of residential floor plans. However, the design of residential floor plans with the aim of improving consumer satisfaction and energy performance has not been fully explored. Also, the preferences of different customer groups regarding customer satisfaction have not been studied. Traditional design and optimization methods still have limitations in terms of performance improvement, while performance-based generative design methods can explore the performance improvement potential of a larger range of solution spaces. Therefore, this study introduces a generative design framework that is grounded on optimizing energy performance and consumer satisfaction for multi-unit residential floor plans, which consists of four main processes: 1) Generation of floor plan schemes. 2) Evaluation of consumer satisfaction and energy performance of the generated schemes. 3) Running a multi-objective optimization to obtain optimal schemes. 4) The final floor plan scheme is determined by the decision maker. The proposed framework was employed in a real design case, and seven optimal solutions were obtained. Compared with the initial scheme, the maximum improvement in consumer satisfaction and energy performance was up to 38.78% and 11.18% respectively. The results also indicated that the preferences of different types of consumers differed significantly. Thus, different evaluation functions have been created to provide solutions with higher satisfaction levels targeting different types of consumers. As such, generative design and optimization of residential floor plans for specific types of consumers can be undertaken at an early design stage to improve consumer satisfaction and reduce energy consumption.

An investigation of the sustainability of old traditional mosque architecture: case study of three mosques in Gayo Highland, Aceh, Indonesia

ABSTRACT The existing traditional architecture has a sustainable design that is adaptive to the environment. Old mosque is one of the traditional architectures that has withstood the test of time due to its adaptations to the environment. Mosques as religious buildings designed for Muslims to practice their religion lead to their design being convenient and sustainable. The purpose of this study is to evaluate the design elements of the old traditional mosques in Gayo highland of Indonesia, i.e. Asal Penampaan, Tue Kebayakan, and Al Jihad Mosques, so that a more sustainable approach to architecture may be developed. The methodology of this study is qualitative, carried out through observation and a literature review on the design and environmental elements of the mosque architecture. In this study, the design and environmental elements reviewed are limited to the building materials; the building floor plan and Structure; the openings; and the water bodies surrounding the mosques. The results showed that these traditional mosques have structures, materials, and designs that are adaptive to climate and the environment. The characteristics of this mosque include low embodied energy from the local materials and resilience to earthquakes through the Saka guru system, supported by mortise and tenon joint system.

Optimization design generation of the rural residential building towards energy saving by using “Digital intelligence” technology

Based on the “Digital Intelligence” technology, the scheme of building design can be automatically generated and optimized simultaneously. However, this method has not been reported, in terms of the optimization design generation by improving the building energy saving potential for the rural residential building. Here, according to the data of floor plans of the rural residential buildings collected from the hot summer and cold winter climate region (China), five types of floor plans were deduced. Firstly, we proposed the method of comprehensive score and weight assignment to achieve the optimum functional layout, according to evaluation indicators of the sum of the helpful and harmful radiations, the energy consumptions corresponding to the individual rooms in various spatial positions and the functional layout characters in the study region. Secondly, the plan configuration was also taken into account to improve the energy saving potential of design building, by using the evaluation indicator of plan-shaped coefficient. Based on the criteria of functional layout and plan configuration, the optimum modes for the five types of floor plans were derived. Thirdly, the component parameters of individual rooms in the design building were optimized by genetic algorithm. This study reveals the principle of the automatic generation of building design in synchronicity with improvement of its energy saving potential, and provides an achievement approach to the strategy of “rural revitalization” and the goal of “carbon peaking and carbon neutrality” in China.

A Sensing-Based Visualization Method for Representing Pressure Distribution in a Multi-Zone Building by Floor.

Airflow in a multi-zone building can be a major cause of pollutant transfer, excessive energy consumption, and occupants discomfort. The key to monitoring airflows and mitigating related problems is to obtain a comprehensive understanding of pressure relationships within the buildings. This study proposes a visualization method for representing pressure distribution within a multi-zone building by using a novel pressure-sensing system. The system consists of a Master device and a couple of Slave devices that are connected with each other by a wireless sensor network. A 4-story office building and a 49-story residential building were installed with the system to detect pressure variations. The spatial and numerical mapping relationships of each zone were further determined through grid-forming and coordinate-establishing processes for the building floor plan. Lastly, 2D and 3D visualized pressure mappings of each floor were generated, illustrating the pressure difference and spatial relationship between adjacent zones. It is expected that the pressure mappings derived from this study will allow building operators to intuitively perceive the pressure variations and the spatial layouts of the zones. These mappings also make it possible for operators to diagnose the differences in pressure conditions between adjacent zones and plan a control scheme for the HVAC system more efficiently.

Where are cities under pressure? – An indicator for measuring the impact of building changes on urban density

In the course of urbanisation, cities are becoming increasingly dense with high local variability. Worldwide, there is a high demand for living space, especially in larger cities, which leads to settlement pressure. It is a declared goal to further densify cities in order to avoid the consumption of ecologically valuable land. But cities that are too densely built also bring negative consequences. Therefore, it is important to understand and describe the densification processes of cities. To better describe settlement densification processes, we have developed a novel indicator that can be used to determine changes in the development density, which is of interest from a planning perspective. The indicator takes into account both the extent of the building change and the existing development. If an area is already intensively developed, a newly constructed building will result in a higher density than if that building were built in a previously undeveloped area. The indicator can also be used to measure deconstruction effects symmetrically, so that densification and de-densification processes can be analysed in parallel. In addition, various spatial entities such as cadastral parcels, grid cells or city districts can be used as reference areas for indicator calculation. In addition to an area-based analysis, we have also taken into account the number of storeys of each building, which allows us for more precise calculations. We tested the indicator in this study using the City of Hamburg as an example. Freely accessible building floor plans and parcels from 2015 and 2020, taken from the Authoritative Real Estate Cadastral Information System (ALKIS) of the City of Hamburg, served as the data basis. Furthermore, we used land use data to examine how various land use classes differ in terms of density development. The results show that extensive densification is often observed on previously built-up land, especially in the city centre, which indicates particularly high settlement pressure. Newly developed residential areas are also densely built up, but comparatively do not contribute to such high building density. On the one hand, this indicates an efficient and thus sparing use of the finite resource of land in the city. On the other hand, it points to increasingly dense development in the city centre.

Semantic-driven Graph Transformations in Floor Plan Design

This paper deals with supporting the design of building floor plans. Floor layouts are represented by labelled and attributed graphs. These graphs are generated using graph grammars, i.e., systems for transforming graphs according to specified rules. The key feature of a graph grammar is that graph representations are obtained by successively adding nodes and edges by applying the rules during the generation process with the use of the so-called embedding principle. The existing embedding principles are often not sufficient to create solutions which fulfill the design criteria. The main contribution of this paper is a generative graph grammar with an innovative semantic-driven embedding where graph attribute values are taken into account while creating new edges. The proposed approach enables automatic generation of graphs corresponding to new layout designs with geometrical properties specified by graph attributes. It is illustrated by examples of apartment floor layouts generated by a prototype application implemented in Python.

An Assessment of the Relation between Architectural and Structural Systems in the Design of Tall Buildings in Turkey

Many professionals from several disciplines need to cooperate in designing and constructing tall buildings since their design and construction require more complex systems and technologies in terms of structure, installation, facade, vertical circulation and fire systems compared to low-rise buildings. The architects who design tall buildings have to know the architectural and structural design considerations of tall buildings and their interrelations well. This study is expected to reveal the status of tall buildings completed in Turkey and help designers understand architectural forms, floor plans, core planning and structural systems of tall buildings. For this purpose, the factors affecting architectural and structural design were examined, and the relation between the architectural–structural system was revealed for tall buildings completed in Turkey. In order to study architectural and structural considerations, 230 constructed tall buildings in Turkey were selected and analyzed in detail. According to the results of the study, it is seen that the prismatic form is widely used as the building tower form in Turkey, the shear-frame system as the structural system, the residential function as the building function, the single symmetrical central core as the building core, and the rectangular plan as the building floor plan alike.

Credibility of feeling versus image of a place

The perception of architecture is realized as a result of the metaphorical travel of the observer through the designed space, it is a specific reading of space at different levels of feeling. Designing is a scenario, user manual for those who are in this space. The aim was to examine the living space of two original authors concepts of multi-family residential buildings, based on the adopted architectural criteria, in terms of the credibility of feeling of the architecture of the living space. Moreover adopted criteria determines the quality of activities determining the condition of living. The method of logical argumentation was adopted for the research, interpreting selected original examples in order to conduct a critical analysis of the existing solutions. The result is a graphic record of repeatable floor plans of multi-family residential buildings, showing a veristic or virtual space as a factor of credibility of living. The conclusions present the method of shaping the architecture space in post-designed multi-family residential buildings based on the criterion of the credibility of feeling in the context of the image of a place in space.

A spatial temporal graph neural network model for predicting flashover in arbitrary building floorplans

Rapid fire progression, such as flashover, has been one of the leading causes for firefighter deaths and injuries in residential building environments. Due to long computational time of and the required prior knowledge about the fire scene, existing models cannot be used to predict the potential occurrence of flashover in practical firefighting applications. In this paper, a scene-agnostic model (FlashNet) is proposed to predict flashover based on limited heat detector temperature information up to 150 °C. FlashNet utilizes spatial temporal graph convolutional neural networks to effectively learn features from the limited temperature information and to tackle building structure variations. The proposed model is benchmarked against five different state-of-the-art flashover prediction models. Results show that FlashNet outperforms the existing flashover prediction models and it can reliably predict flashover 30 s preceding its occurrence with an overall accuracy of about 92.1%. Ablation study is carried out to examine the effectiveness of different key model components and geometric average adjacency matrix. The research outcomes from this study are expected to enhance firefighters’ situational awareness in the fire scene, protecting them from hazardous fire environments and to pave the way for the development of data-driven prediction systems.