Floor Plan Research Articles

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.

Automating computational design with generative AI

AbstractAI image generators based on diffusion models have recently garnered attention for their capability to create images from simple text prompts. However, for practical use in civil engineering they need to be able to create specific construction plans for given constraints. This paper investigates the potential of current AI generators in addressing such challenges, specifically for the creation of simple floor plans. We explain how the underlying diffusion‐models work and propose novel refinement approaches to improve semantic encoding and generation quality. In several experiments we show that we can improve validity of generated floor plans from 6% to 90%. Based on these results we derive future research challenges considering building information modeling. With this we provide: (i) evaluation of current generative AIs; (ii) propose improved refinement approaches; (iii) evaluate them on various examples; (iv) derive future directions for diffusion models in civil engineering.

Impact of Transitioning to Single-Patient Rooms on Prevention of Multidrug-Resistant Organisms in a Resource-Limited Facility

Background: Healthcare-associated infections (HAI) substantially increase hospital costs and lead to poor patient outcomes, particularly when caused by multidrug-resistant organisms (MDRO). To decrease MDRO transmission, isolation of colonized or infected patients in single rooms is recommended. However, single-patient isolation rooms are expensive to build and often unavailable in resource-limited hospitals. In 2023, an intensive care unit (ICU) at a large Brazilian tertiary hospital relocated from a space with an open floor plan to a newly built location with single-patient rooms. We evaluated the impact of this transition on acquisition of carbapenem-resistant Enterobacterales (CRE) colonization, HAI, and compliance with Hand Hygiene (HH) and Contact Precaution (CP) activities. Methods: We compared rates of CRE colonization acquisition, CRE colonization pressure, HAI, and compliance with HH and CP between pre- (March 1, 2022 – Feb 28, 2023) and post-implementation of single-rooms (March 1, 2023 - October 31, 2023) in a 12-bed surgical ICU. All patients were screened for CRE colonization on admission to the unit and weekly until discharge using rectal swab cultures. Colonization pressure was defined as the ratio of CRE-positive patient-days (PDs) to the total number of PDs. Rates of central-line associated blood-stream infections, ventilator-associated pneumonia, and catheter-associated urinary tract infections were monitored. HH and CP compliance were monitored weekly by infection prevention staff outside of the unit. Poisson regression and multiple linear regression were used to compare rates between pre- and post-implementation periods. Results: Healthcare acquisition of CRE colonization remainedstable between pre- and post-implementation (incidence rate ratio: 0.88 (95%CI, 0.73-1.05; P=0.16) despite an increase in CRE colonization pressure of 8.6% over baseline (from 7.84% pre- to 16.39% post-implementation (95% confidence interval [CI], 4.13-12.96%; P=.001)). The latter was driven by reduced turnover of CRE-colonized patients in the post-implementation period (mean patient-day reduced by 10.33; 95%CI, 3.06-17.61; P=0.006). Incidence of HAIs also remained stable (global incidence 3.12 vs 3.30, pre- and post-intervention, respectively; P=0.2). HH compliance was high prior to the transition (95.7%) and increased slightly but not significantly post-intervention (97.5%; P=0.3). CP compliance improved by 9.83%, especially in gown and glove changes after each patient interaction, from 90.62% pre- to 100% post-implementation (95%CI, 1.52-17.22; P=.02). Conclusion The move to an ICU with exclusively single-patient rooms was associated with increase in CP compliance. This could help explain why HAI incidence and healthcare acquisition of CRE colonization remained stable despite a significant increase in CRE colonization pressure.Disclosure: Matias Salomao: Speaker - Cepheid

Performance of Shading Against West Glass Facades to Optimise Daylight, Thermal Comfort and Energy Efficiency of Office Buildings

In tropical urban areas, the vertical facades of buildings often play a crucial role in capturing solar radiation and heat, especially for office buildings facing west during the afternoon. In Dhaka, a tropical city, the construction of major arterial roads connecting the northern and southern regions of the city has led to the emergence of numerous commercial buildings along these roads, predominantly facing in east or west directions. This research investigated the efficiency of different existing fenestration types (glass curtain walls, glass windows with horizontal and vertical louvres, overhangs, vertical fins, and egg crate shading) of west-facing office buildings in Dhaka in terms of daylight, thermal comfort and energy efficiency, and explore strategies to enhance existing performance. From the field survey, a 'case office building' was selected, and simulations were carried out with the six different fenestrations, as mentioned above, while keeping other aspects constant as found during the survey, e.g., floor plan, equipment and number of occupants. In this research, the simulation process encompasses daylighting simulation, energy simulation, and multi-objective optimisation. The study utilised a case model created with Rhinoceros and ClimateStudio, while performance metric optimisation was achieved using Grasshopper and Octopus. Multi-objective optimisation techniques were employed to improve the shading configurations. The TT toolbox facilitated data exportation and Design Explorer assisted in data visualisation. The window with egg crate shading was found to be the most effective fenestration type among the studied shading configurations. Further parametric simulation was conducted to develop an optimised egg crate shading design configuration. It was found that egg crate shading with a 1.0 m depth provided optimum daylight and solar heat gain inside the office building among the studied configurations in the context of Dhaka. A comparison was also made between the optimised egg crate option and a customised egg crate with some detailing (popularly known as brise soleil). Brise soleil showed better performance with 12.2% higher sDA and 98 lux additional average illuminance compared to the previous optimum one. The findings underscore the significance of employing optimisation methodology to devise shading configurations while also revealing substantial opportunities to enhance performance further by tailoring details on the optimised design recommended from simulation analysis.

Architectural and planning features of wooden orthodox Churches of Bukovyna using the example of the assumption church, 2 Novoushytska street, Chernivtsi

Wooden churches are an important part of Ukraine's cultural heritage. A significant portion of them has been identified, included in the State Register, and thus is under state protection. It should also be noted that the wooden architecture sites of western Ukraine were included in the UNESCO World Heritage List in 2013 (nomination "Wooden Tserkvas of the Carpathian Region in Poland and Ukraine"). A characteristic feature of the Moldavian-Bukovinian type churches is a plan in the shape of an Orthodox cross. They also feature a high and steep wooden tent roof. The plan consists of three parts: the narthex, the nave, and the altar part. Above each part is a spherical vault in the shape of a half-sphere. The walls are made of wooden beams. The length of the wooden beam’s ranges from 3 to 6 meters. The entrance to the church is always located on the south facade. The prototype of all wooden churches of this type is considered to be the wooden church of the Putna Skete from the 14th century. The architectural monument of national significance, the Assumption Wooden Church, is an outstanding example of folk architecture. The church has retained its authenticity and has been located at its historic site since 1876. Its architectural and planning features lie in the preservation of the traditions of medieval folk architecture of wooden Orthodox churches in Bukovina, serving as a unique authentic example for researchers and restoration scientists The article provides an analysis of the architectural and planning features of the wooden Assumption of the Virgin Mary Church, one of the four wooden churches of national architectural significance located in the city of Chernivtsi. The impact of historical, cultural, and social factors on its architecture is analyzed. Methods and approaches to the preservation and restoration of wooden churches are considered, particularly the use of modern 3D scanning technologies for recording the state of the object and creating its phantom model. The article is illustrated with architectural drawings: site plan, floor plan, and elevations, and provides photographic documentation of facade and interior fragments.

Automated Destination Renewal Process for Location-Based Robot Errands

In this paper, we propose a new approach for service robots to perform delivery tasks in indoor environments, including map-building and the automatic renewal of destinations for navigation. The first step involves converting the available floor plan (i.e., CAD drawing) of a new space into a grid map that the robot can navigate. The system then segments the space in the map and generates movable initial nodes through a generalized Voronoi graph (GVG) thinning process. As the second step, we perform room segmentation from the grid map of the indoor environment and classify each space. Next, when the delivery object is recognized while searching the set space using the laser and RGB-D sensor, the system automatically updates itself to a position that makes it easier to grab objects, taking into consideration geometric relationships with surrounding obstacles. Also, the system supports the robot to autonomously explore the space where the user’s errand can be performed by hierarchically linking recognized objects and spatial information. Experiments related to map generation, estimating space from the recognized objects, and destination node updates were conducted from CAD drawings of buildings with actual multiple floors and rooms, and the performance of each stage of the process was evaluated. From the quantitative evaluation of each stage, the proposed system confirmed the potential of partial automation in performing location-based robot services.

COW TRAFFIC DESIGNS IN BARNS WITH AUTOMATIC MILKING SYSTEMS: ADVANTAGES, DISADVANTAGES AND DIFFERENCES

This study describes the most common traffic systems in barns for lactating dairy cows milked in automatic milking systems (AMS). It outlines seven cow traffic designs, each featuring a basic floor plan, taking into account one robot or AMS per barn and considering a maximum system capacity (> 60 cows/AMS). The study describes the advantages and disadvantages of free, milk-first and feed-first traffic and the differences between forced and guided cow traffic designs. Some research data are also shown to emphasize the theoretical concepts included in this document. The main difference is that free cow traffic tends to milk a lesser number of cows than milk-first and feed-first cow traffic designs but warrants more freedom for the cows. However, free cow traffic design increases the number of refusals (cows visiting the AMS without milking permission), leading to system inefficiency. Guided traffic designs emerge as the most efficient, milking more cows throughout the day while reducing the need to fetch cows and overall labour. When operating at full cow capacity, guided cow traffic designs are recommended.

Automatic floor plan analysis using a boundary attention-based deep network

Automatic floor plan analysis using a boundary attention-based deep network

Automated data-driven method for creating digital building models from dense point clouds and images through semantic segmentation and parametric model fitting

This paper proposes an automated method for creating semantic digital building models using dense point clouds and images. The method employs a hybrid bottom-up, top-down approach, integrating artificial intelligence capabilities in scene understanding with domain engineering knowledge to overcome challenges in indoor 3D reconstruction. The pre-trained PointTransformer semantic segmentation model extracts thirteen building objects, where the wall and ceiling segments are utilized in a 3D space parsing algorithm. The parameterized floor plan map is then generated using a data-driven approach, enabling the creation of an extruded volumetric digital model. Additionally, the YOLOV8 object detection network recognizes doors and windows in images derived from projected points of the wall instances. The validation results for six building datasets with different layouts showcase the effectiveness of the proposed model reconstruction algorithm, with a mean error of about 7 cm between the parameters of elements in digital reference models and reconstructed models. This highlights AI’s potential in automating the creation of digital models for the real world.

Enabling Self-Practice of Digital Audio–Tactile Maps for Visually Impaired People by Large Language Models

Digital audio–tactile maps (DATMs) on touchscreen devices provide valuable opportunities for people who are visually impaired (PVIs) to explore the spatial environment for engaging in travel activities. Existing solutions for DATMs usually require extensive training for the PVIs to understand the feedback mechanism. Due to the shortage of human resources for training specialists, as well as PVIs’ desire for frequent practice to maintain their usage skills, it has become challenging to widely adopt DATMs in real life. This paper discusses the use of large language models (LLMs) to provide a verbal evaluation of the PVIs’ perception, which is crucial for the independent practice of DATM usage. A smartphone-based prototype providing DATMs of simple floor plans was developed for a preliminary investigation. The evaluation results have proven that the interaction with the LLM could help the participants better understand the DATMs’ content and could vividly replicate them by drawings.

A Review of Factors Affecting the Lighting Performance of Light Shelves and Controlling Solar Heat Gain

In areas with a deep floor plan, the distribution of natural light is not uniform. Consequently, relying solely on daylight may not suffice to meet the space’s lighting requirements, necessitating the use of artificial lighting in darker areas. Therefore, a lighting system is needed that not only controls the glare near the windows but also increases the light at the end of the room and provides uniform daylight. One of the widely used systems is the “light shelf”, which has three main functions: shading, increasing the depth of light penetration, and reducing glare. Review articles about light shelves were published in 2015 and 2017, while more than 80% of the studies have been carried out since 2016, and light shelves with more diverse forms and dynamic elements and many consolidations have been proposed. Therefore, there is a need for a more comprehensive review. The main question of this research is how different parameters (including climate, material, ceiling, and integrated systems) can help to increase the efficiency of light shelves. By using a systematic review, studies in the past three decades were classified in order to determine the effect of these parameters on improving lighting performance and controlling solar heat gain.

Multiscale object detection on complex architectural floor plans

Architectural floor plans are essential documents for conveying building information among designers, engineers, and clients. Automated analysis of floor plans enhances user productivity and accuracy, though research on automatic object detection within architectural floor plans has been limited. In this paper, a convolutional neural network (CNN) based architecture, ArchNetv2, is proposed to detect various visual objects, such as stairs, windows, and doors. The proposed ArchNetv2 includes a convolutional block attention module to improve feature learning. It works at multiple detection scales and can efficiently recognize large objects (e.g., stairs) and small objects (e.g., windows) simultaneously. Experimental results show that ArchNetv2 can recognize thirteen types of objects commonly found in architectural floor plans with a mAP of 93.5%, which is superior compared to the state-of-the-art techniques. The proposed architecture can serve as an important module in an automated floor plan analysis system.

Application of Q-learning Method for Disaster Evacuation Route Design Case Study: Digital Center Building UNNES

The Digital Center (DC) building at UNNES is a new building on the campus that currently lacks evacuation routes. Therefore, it is necessary to create an evacuation route plan in accordance with the Minister of Health Regulation Number 48 of 2016. Creating a manual evacuation route plan can be inefficient and prone to errors, especially for large buildings with complex interiors. To address this issue, learning techniques such as reinforcement learning (RL) are being used. In this study, Q-learning will be utilized to find the shortest path to the exit doors from 11 rooms on the first floor of the DC building. The study makes use of the floor plan data of the DC building, information about the location of the exit doors, and the distance required to reach them. The results of the study demonstrate that Qlearning successfully identifies the shortest evacuation routes for the first-floor DC building. The routes generated by Q-learning are identical to the manually created shortest paths. Even when additional obstacles are introduced into the environment, Q-learning is still able to find the shortest routes. On average, the number of episodes required for convergence in both environments is less than 1000 episodes, and the average computation time needed for both environments is 0.54 seconds and 0.76 seconds, respectively.

Research on Optimization Design Strategies for Natural Ventilation in Living Units of Institutional Elderly Care Facilities Based on Computational Fluid Dynamics Simulation

As China transitions into a deeply aging society, the elderly population’s growth has driven a rapid increase in elderly care institutions and facilities during the “13th Five-Year Plan” period, rising by over 235% compared to the “12th Five-Year Plan”. The ongoing normalization of COVID-19 prevention measures has underscored the urgent need to improve natural ventilation in elderly care residential facilities. This study conducted empirical surveys to assess the current state of natural ventilation in typical elderly care facilities and analyzed the architectural elements influencing it. By examining the needs and preferences of the elderly for natural ventilation, two basic living space layout types were identified through typological analysis. Suitable CFD simulation software was then employed to model key elements, and effective methods to enhance ventilation were summarized. This study found that modifying the floor plan to reduce the depth of south-facing rooms to 8.4 m, relocating external openings to the center of the rooms, adjusting the ratio of ventilation openings to room area to greater than 1/12, and adding 0.5 m high windows facing internal traffic roads can significantly improve indoor ventilation while maintaining privacy. Furthermore, placing the main activity and resting areas of the elderly in well-ventilated zones with minimal drafts can enhance both comfort and ventilation effectiveness. The research provides a scientific basis and methodological guidance for the construction and renovation of elderly care residential facilities.

Entre lo contextual y lo cíclico: paradigmas delo contemporáneo en el Pabellón de Vidrio de Sanaa.

The Glass Pavilion, with which the Japanese team SANAA began its S. XXI journey, empathizes with the modern heritage, especially that of Mies van der Rohe. Its volume and external presence herald it; its section confirms it. This article proceeds, intertwined and simultaneously, to delve into the history of the building; it dives into the phenomenological space formed by the looped sequences and overlapping glazes of glass and analyzes the compositional logic of its floor plan. In this way, modern ideology is shaken and, enriched by Japanese culture, contemporary paradigms emerge. The pavilion, even tacitly and silently, is aligned with an abstract Contextualism of non-vernacular roots, borders Figuration, in the purity of its volume it presents an Organic-Structuralist logic, and immerses the viewer in a Cyclical Time, like that of ancient legends and Eastern religions, intimately linked to the times of nature

Analysis Seismic Behavior of Structures with Planar Imperfections: A Comprehensive Numerical Analysis

This paper presents a comprehensive approach to the seismic analysis and design of a tall hospital building, accounting for horizontal irregularities and employing equivalent static analysis (ESA) methodology. The study initiates with the collection of relevant site data and building specifications, including the identification and characterization of horizontal irregularities such as setbacks, mass distribution variations, and irregular floor plans. Equivalent static lateral loads are calculated based on applicable building codes and standards, taking into account the effects of horizontal irregularities on seismic response. Structural modeling and analysis are then conducted using sophisticated software to evaluate the building's behavior under seismic forces, considering the influence of irregularities on structural performance. Design criteria, encompassing drift limits, strength requirements, and detailing considerations for mitigating irregularity effects, are rigorously adhered to ensure compliance with safety regulations and performance objectives. The iterative process of evaluation and adjustment ensures optimal seismic performance and adherence to design criteria despite the presence of horizontal irregularities. Documentation of the analysis and design process, coupled with meticulous construction oversight, guarantees the implementation of a robust seismic design strategy tailored to the unique characteristics of the tall hospital building. Post-construction evaluations are carried out to validate predicted seismic performance, accounting for the influence of horizontal irregularities. Through collaborative efforts and adherence to best practices, the seismic design of the tall hospital building prioritizes safety and resilience, even in the face of horizontal irregularities, aiming to safeguard occupants and critical healthcare infrastructure during seismic events.

Methods and Applications of Space Understanding in Indoor Environment—A Decade Survey

The demand for digitizing manufacturing and controlling processes has been steadily increasing in recent years. Digitization relies on different techniques and equipment, which produces various data types and further influences the process of space understanding and area recognition. This paper provides an updated view of these data structures and high-level categories of techniques and methods leading to indoor environment segmentation and the discovery of its semantic meaning. To achieve this, we followed the Systematic Literature Review (SLR) methodology and covered a wide range of solutions, from floor plan understanding through 3D model reconstruction and scene recognition to indoor navigation. Based on the obtained SLR results, we identified three different taxonomies (the taxonomy of underlying data type, of performed analysis process, and of accomplished task), which constitute different perspectives we can adopt to study the existing works in the field of space understanding. Our investigations clearly show that the progress of works in this field is accelerating, leading to more sophisticated techniques that rely on multidimensional structures and complex representations, while the processing itself has become focused on artificial intelligence-based methods.

Utilizing Agent-Based Modeling for Optimization of Wayfinding in Hospital: A Case Study.

This research aims to propose a novel methodology for analyzing and optimizing wayfinding in complex environments by examining their spatial configurations. Wayfinding difficulties often lead to disorientation and hinder users' ability to locate destinations. Although architectural design can aid in simplifying user access, existing approaches lack a specific focus on wayfinding optimization despite its significant impact on users' navigational abilities. In this study, an agent-based model was employed to assess the efficacy of wayfinding in a multistory hospital. Subsequently, the layouts were optimized, leading to the creation of a new space distribution diagram. The simulation was then repeated to examine the potential improvement in wayfinding. Data collection encompassed user types, workflow scenarios, population distribution, and user speed. Comparative analysis of the agent-based simulation findings before and after layout optimization revealed a decrease in total distance and time spent on the modified floor plans for all users when compared to the existing layout. This suggests that the optimized layout holds significant potential for enhancing wayfinding performance. Given the positive outcomes observed for users, this approach is particularly well suited for preliminary design stages of complex environments, where designations among user groups are less crucial or flexibility is desired. Additional advantages include the ability to generate a comprehensive simulation of users' daily workflow, which is integrated into the optimization process and considers specific requirements regarding spatial adjacency.

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.

Sustainable Design Criteria for Batik Cultural Centre in Klampar, Madura

Batik is part of the culture in Indonesia. With each region having its signature, the Government has taken various ways to ensure the sustainability of batik, providing a batik centre to support batik artisans and a batik museum to introduce culture to tourists. However, the program’s sustainability cannot be maintained, and it always fails for several reasons. One can be seen in kampong batik in Klampar Village, Indonesia; the Government provided a Batik Centre in 2022, but the following year, it was abandoned, and the community returned to producing batik in their homes. This research aims to formulate sustainable design criteria for Batik Cultural Centre based on the four dimensions of sustainability and sustainable tourism. The sustainability review of kampong batik in Klampar Village will carried out qualitatively, and the solutions offered will be analyzed empirically with the support of previous theories to provide credibility. The results show that six architectural aspects can be intervened in developing culture-based sustainable tourism: facilities, room programs, materials, skin, spatial connectivity, and floor plan. This study contributes to setting the design criteria for vernacular architecture that wants to be re-purposed as a tourism facility within the sustainability corridors.