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This study aimed to propose a performance-oriented approach of automatically generative design and optimization of hospital building layouts in consideration of public health emergency, which intended to conduct reasonable layout design of hospital building to meet different performance requirements for both high efficiency during normal periods and low risk in the pandemic.

The research design follows a sequential mixed methodology. First, key points and parameters of hospital building layout design (HBLD) are analyzed. Then, to meet the requirements of high efficiency and low risk, adjacent preference score and infection risk coefficient are constructed as constraints. On this basis, automatic generative design is conducted to generate building layout schemes. Finally, multi-objective deviation analysis is carried out to obtain the optimal scheme of hospital building layouts.

Automatic generative design of building layouts that integrates adjacent preferences and infection risks enables hospitals to achieve rapid transitions between normal (high efficiency) and pandemic (low risk) periods, which can effectively respond to public health emergencies. The proposed approach has been verified in an actual project, which can help systematically explore the solution for better decision-making.

The form of building layouts is limited to rectangles, and future work can explore conducting irregular layouts into optimization for the framework of generative design.

The contribution of this paper is the developed approach that can quickly and effectively generate more hospital layout alternatives satisfying high operational efficiency and low infection risk by formulating space design rules, which is of great significance in response to public health emergency.

In this study, a novel framework based on deep learning models is presented to assess energy and environmental performance of a given building space layout, facilitating the decision-making process at the early-stage design.

A methodology using an image-based deep learning model called pix2pix is proposed to predict the overall daylight, energy and ventilation performance of a given residential building space layout. The proposed methodology is then evaluated by being applied to 300 sample apartment units in Tehran, Iran. Four pix2pix models were trained to predict illuminance, spatial daylight autonomy (sDA), primary energy intensity and ventilation maps. The simulation results were considered ground truth.

The results showed an average structural similarity index measure (SSIM) of 0.86 and 0.81 for the predicted illuminance and sDA maps, respectively, and an average score of 88% for the predicted primary energy intensity and ventilation representative maps, each of which is outputted within three seconds.

The proposed framework in this study helps upskilling the design professionals involved with the architecture, engineering and construction (AEC) industry through engaging artificial intelligence in human–computer interactions. The specific novelties of this research are: first, evaluating indoor environmental metrics (daylight and ventilation) alongside the energy performance of space layouts using pix2pix model, second, widening the assessment scope to a group of spaces forming an apartment layout at five different floors and third, incorporating the impact of building context on the intended objectives.

The purpose of this paper is to highlight the importance and significance of design strategies to enhance flexibility as an in-built design concept of residential building in developing countries. The study considers potential directions of building design in developing countries to ensure maximum benefits of resource utilization.

The study approaches using the qualitative data collection method, mostly based on interviews of local residents. Layouts of residential buildings that have been renovated for several reasons, such as the changes in family size over the last 30 years, have been studied. The concept of zone and margin, based on the theoretical framework developed by Dutch architect, John Habraken, is compared and tested in residential buildings in the city of Khulna.

This paper shows that people change floor layouts of their buildings over time for different reasons; for example, 29 percent of people change plans in order to accommodate more people, 19 percent in order to initiate new businesses, and 13 percent due to change in family structure. However, these facts impose an excessive monetary burden on the owners to re-adjust layouts even though the building does not have the provision to do so. The paper also reveals that people would welcome new plans for future readjustment during the design and construction phases instead of renovation phases.

This paper highlights flexibility and attempts to justify the possibilities to practice in developing countries. As an inherent design strategy of sustainable development, the concept would consider unknown future changes of building layouts and structures. It would consider the minimum reconstruction, or renovation, costs associated for future adaptation.

Since the appearance of COVID-19 social distancing and staying home have been recommended repeatedly by the governments for disease prevention. As the challenge continues to remain the current study seeks to examine the factors affecting social distancing through space planning and management. More specifically the current study aims to examine the appropriateness of the spatial organization and space configuration of a clubhouse with a linear plan layout in the mitigation of the spread of infections due to serious pandemic COVID-19.

For an enhanced understanding of the impact of spatial arrangements of public spaces plan on the effective implementation of social distancing this study has used the space syntax analysis method. The MPSP clubhouse building in Penang, Malaysia was selected as the case study. The level of permeability and wayfinding were determined in the building plan and were illustrated using photoshop software to depict the interrelation between the indoor spaces and building circulation. Graphs of the depth of space were used to analyze the level of permeability and wayfinding to illustrate the possibility of social distancing in the plan.

The result of the study shows the significant role of proper plan layout design on social distancing. While clear and direct wayfinding can positively be associated with more effective social distancing, the inefficient design of user access, inappropriate locations of multiple entry and exit and indefinite directions of users' inside buildings can impose slight limitations. The average level of permeability might suggest ineffective spatial arrangement, ignoring the needs of spatial segregation. The study further found that the linear plan layouts with proper zoning and effective management strategies can be considered a proper layout to facilitate social distancing and the spread of COVID-19.

The current study is unique in terms of examination of the spatial configuration of linear public spaces plan layout for possible temporary adaptability to curb disease spread during the unexpected advent of a pandemic. Based on researchers' best of knowledge it is the first time that the impact of recreational space design on social distancing has been examined. The study also originally sheds light on the fact that the commonly used guideline for the social distancing of 1–2 m between 2 persons, in reality, is practically inadequate given the nature of the sports activities.

The purpose of this paper is to develop a building information modelling (BIM)-based multi-objective optimization (MOO) framework for volumetric analysis of buildings during early design stages. The objective is to optimize volumetric spaces (3D) instead of 2D spaces to enhance space utilization, thermal comfort, constructability and rental value of buildings

The integration of two fundamental concepts – BIM and MOO, forms the basis of proposed framework. In the early design phases of a project, BIM is used to generate precise building volume data. The non-sorting genetic algorithm-II, a MOO algorithm, is then used to optimize extracted volume data from 3D BIM models, considering four objectives: space utilization, thermal comfort, rental value and construction cost. The framework is implemented in context of a school of architecture building project.

The findings of case study demonstrate significant improvements resulting from MOO of building volumes. Space utilization increased by 30%, while thermal comfort improved by 20%, and construction costs were reduced by 10%. Furthermore, rental value of the case study building increased by 33%.

The proposed framework offers practical implications by enabling project teams to generate optimal building floor layouts during early design stages, thereby avoiding late costly changes during construction phase of project.

The integration of BIM and MOO in this study provides a unique approach to optimize building volumes considering multiple factors during early design stages of a project

The spatial design of a building affects the movement of occupants. In complex buildings with a large population, such as places of assembly, the movement of people towards the exits under emergency situations is a major concern. Ideally, people should leave the building smoothly under emergency situations. Traditionally the layout design is governed by the building fire codes. However, the building fire codes merely govern the design of the capacity of individual components, and do not guarantee that smooth egress will occur. Full‐scale egress exercises may be needed to examine the layout arrangement in order to understand the layout problem. However, such exercises may be time‐consuming, or may be impossible when the building has yet to be constructed. Therefore, the use of computer models to simulate the egress pattern can assist not only the building designer, but also the facility manager to plan the spatial arrangement as well as to manage the crowd flow during emergency situations. Discusses the use of a computer model for analysing building layout design.

The purpose of this paper is to propose a scientific method to evaluate possible urban layouts of a test building integrating building regulations, natural light standard and energy requirements to achieve nearly zero-energy buildings in Estonia. The integration of building regulations, energy requirements and natural light standards is crucial to evaluate the incidence of the surrounding environment when analyzing the energy performance of buildings.

The paper investigates the variations of the energy consumption of a model building with different orientations and variable urban surroundings configurations for the latitude of Tallinn. The different urban configurations are due to combinations of the different building requirements of fire safety, daylighting and insolation hours that in Estonia affect the layout of residential districts, thus influencing significantly the potential consumption of buildings. Different layouts of surrounding buildings have been chosen all guaranteeing at different degrees the fulfillment of the building requirements for the test building and energy simulations have been run to find the urban layouts that guarantee best performances.

The outcomes show that the test building interior temperatures and energy performances vary significantly in the different urban planning configurations and for the different orientations, underlining that is strongly recommended to run always energy simulation of building considering their surrounding environment. The conclusions show the principles to integrate the building regulations to achieve nearly zero-energy districts that significantly can improve life quality in the urban environment.

The paper analyze the energy efficiency of buildings with different features and orientations simulating their possible urban environment layouts given by building regulations, and not isolated or as built in “an open field” like most of the existing literature in the field.

This paper aims to assess the level of occupants’ satisfaction, comparing older and newer on-campus accommodation buildings in Sydney, Australia, aiming to identify their comfort factors deficiencies in terms of design and construction solutions/strategies (e.g. spatial arrangements, materials, thermal comfort).

A post occupancy evaluation survey was used to assess the occupant satisfaction with three on-campus accommodation buildings in The University of New South Wales (UNSW) Sydney. One of the selected buildings is an older building opened for occupation in 1996, and the other two are more recent on campus accommodations buildings. The survey included 11 post occupancy evaluation elements identified through literature review which were categorised into three dimensions: technical, functional and behavioural.

The results show that the satisfaction levels with thermal and acoustic comfort were below standards for both older and newer buildings. In addition, the older building used in this study was rated low in terms of: indoor air quality, lighting, maintenance and management, vertical transportation facility, room layout and furniture quality, building layout and aesthetics and level of privacy. Such factors related to both functional and behavioural dimensions were of greater satisfaction in newer buildings.

Findings suggest the high priority of strategies that address and improve the thermal and acoustic comfort of older and newer on-campus accommodation buildings if the intention is to enhance students’ satisfaction, especially considering the impact that these facilities have on students’ performance. Thermal performance in different seasons and adaptive thermal comfort activities should be considered in the design of new on-campus accommodation buildings and the retrofit of existing old buildings.

On-campus accommodation is an important facility that supports student learning outcomes and helps students adapt in a new learning environment. A post occupancy evaluation study to assess the adequacy of this facility is still lacking because previous studies have generally focussed on class rooms and work spaces in the education sector. This research compares the user satisfaction of older and newer on-campus accommodation buildings in Australia, to highlight deficiencies and areas for improvement in the design of existing and future buildings.

This paper aims to propose a generative design method combined with meta-heuristic algorithm for automating and optimizing the floor layout of modular buildings using typical standardized module units, which are the room module, the corridor module and the stair module.

The integrated framework involves the generative design method and optimization for modular construction. The generative rules are provided by geometric relationships and functionalities of the module units. An evaluation function of the generated floor plans is also presented by the combination of project cost and cost penalties for the geometric features. The multi-population genetic algorithm (MPGA) method is provided for the optimization of the combination of costs.

The proposed MPGA method is demonstrated fast and efficient at discovering the globally optimal solution. The results indicate that when the unit price of modules is high, the transportation distance is long, or the land cost is high, the layout cost, which related to the symmetry, the compactness and the energy is tend to be lower, making the optimal layout economical.

This paper presented an integrated framework of generative floor layout and optimization for modular construction by using typical module units. It fulfills the need for automated layout generation with repetitive units and corresponding assessment during the early design stage.

The health, well-being and productivity (i.e. WELL) of office building occupants are vulnerable to poor office environments. Therefore, this study aims to identify new features and concepts of office buildings in supporting occupants’ WELL. To achieve that aim, this study: explores new WELL features for office buildings, develops new WELL concepts for office buildings and examines the influence of the newly developed WELL concepts on existing WELL building standard (WELL v2) concepts.

The first phase involved ten experts to assign weightage for health, well-being and productivity. In the second phase, 206 questionnaire survey data were collected from office building occupants throughout Malaysia. Exploratory factor analysis established new WELL concepts for office buildings. Partial least-squares structural equation modelling examined the influence of the newly developed WELL concepts on the existing WELL v2 concepts.

Two new WELL concepts were developed: “space and services”, consisting of sufficient space, workstation privacy, office layouts, building automation systems, cleanliness and information technology (IT) infrastructure, and “building security”, consisting of security systems and safety at parking lots. Here, “space and services” influences all existing WELL v2 concepts, and “building security” influences the water, nourishment, mind and community concepts of WELL v2.

This study uncovers holistic WELL building concepts to support occupants’ health, well-being and productivity with additional new features and concepts for construction industry policymakers to establish holistic building assessment tools.