Building Design Strategies Research Articles

Occupancy and equipment usage prototype schedules for building energy simulations of office building types in China

The accuracy of occupancy and energy-consuming equipment schedules significantly influences building energy simulations. Existing standards provide generalized schedules that do not fully capture variations across different office building types and periods. This study utilizes questionnaire data from office buildings across four Chinese cities to extract refined prototypes for occupancy and equipment usage schedules using hierarchical clustering analysis. Specific schedules are developed for summer workdays, winter workdays, summer weekends, and winter weekends, covering HVAC, lighting, and office equipment. For instance, the extracted lighting schedule increases annual energy consumption intensity by 25.35% compared to standard schedules. Additionally, XGBoost models identify key factors influencing equipment usage; for HVAC, floor number emerges as most significant. The study's prototypes offer more realistic inputs for building energy simulations, enhancing accuracy and guiding energy-efficient building design and management strategies in China.

Selecting suitable passive design strategies for residential high-rise buildings in tropical climates to minimize building energy demand

Passive design strategies (PDS) are a fitting solution to reduce the ever-growing energy cost of residential high-rise buildings in tropical regions. However, PDSs’ building energy saving potential significantly varies with local climate conditions, but it has been sparsely investigated. Hence, this study investigated the energy-saving efficiency of eight common PDSs integrated into a typical residential high-rise building in three sub-climates: extremely hot humid (0A), very hot humid (1A), and warm humid (3A) defined by ASHRAE for the tropical climate. This study developed a Building Performance Analysis (BPA) workflow with a BIM-based simulation framework and local and global sensitivity analyses for the building energy analysis. The global sensitivity analysis revealed that low e-coating on glasses is the most influential PDS for 0A and 1A climates, but it has a negative effect in the sub-climate zone 3A. The low-conducting exterior walls are the most effective PDS in the sub-climate zone 3A, but they are poorly performed in the other two sub-climate zones. Based on the energy calculation and sensitivity analysis, this study proposes the best PDS groups, saving up to 40.1%, 63.5%, and 31.7% of average annual building consumption in the sub-climate zones, 0A, 1A, and 3A climates.

Optimization of BIPV Utilization with Parametric Approach: Case Study on Nearly Zero Carbon Building Studio Design in Medan, Indonesia

Buildings significantly consume fossil energy, leading to substantial carbon emissions contributing to global warming and rising sea levels. These environmental impacts pose serious challenges, necessitating a shift towards sustainable building designs. By integrating clean energy solutions into building architecture, we can reduce the environmental burden of emissions. This approach mitigates adverse effects on living organisms and ecosystems and promotes long-term sustainability and resilience in urban development. Building-Integrated Photovoltaic (BIPV) systems represent one such approach for substituting fossil energy. However, implementing BIPV effectively necessitates comprehensive analysis considering numerous parameters and variables. This paper introduces building design strategies employing the BIPV approach. The decision-making process in designing alternatives utilizes parametric methods, recognized for their ability to yield optimization results for various variables through the development of design algorithms. The study focuses on the design of a studio building at the University of North Sumatra. Comparative analysis of the results obtained through parametric design aims to identify the most favorable design outcomes. The research includes developing a parameterized design algorithm, workflow, and assessment results for selecting optimal design alternatives. The results indicate that the placement of PV panels on the side area (PVOS) has more potential than placement on the top area (PVOT). Despite the PVOT area being observed to be 0.57% smaller than PVOS, PVOS shows a significant increase in total Incident Radiation (IR), average IR, and total Energy Generated by 137.14%, 128.40%, and 132.97%, respectively.

Assessment of building design strategies to enhance energy efficiency and thermal comfort: Case study in Morocco’s climate zones

Energy efficiency in the context of building design is a significant concern in Morocco. This paper offers a comprehensive analysis of how various design variables can impact both energy consumption and thermal comfort in the Moroccan context. Rather than isolating individual design variables, we investigate synergistic combinations of these variables. To achieve this, we develop multiple building design scenarios, each employing different combinations of design options, focusing on building orientation, window-to-wall ratio, building envelope construction, and window shading. We use EnergyPlus to conduct energy simulations for all scenarios under the hypothesis of air-conditioned houses and free-running houses with and without natural ventilation. Our results reveal that building design has the potential to significantly enhance energy efficiency and thermal comfort, but not for the same design strategies. In comparison to the most energy-efficient design scenario, the least favorable design scenario can lead to an increase in energy consumption between 237% in Agadir and 130% in Ifrane. Meanwhile, design scenarios favoring comfort can increase the number of comfortable hours by 85% in Agadir and 59% in Ifrane. We identify optimal building design scenarios that simultaneously offer the highest comfort levels with the lowest energy requirements. The findings provide valuable guidance for architects, allowing them to design high-performance buildings in all climate zones in Morocco.

Impact of Building Design and Operating Strategies on Urban Heat Island Effects—Part I: Model Development and Validation

Impact of Building Design and Operating Strategies on Urban Heat Island Effects—Part I: Model Development and Validation

Informing building retrofits at low computational costs: a multi-objective optimisation using machine learning surrogates of building performance simulation models

Machine learning (ML) algorithms are increasingly used as surrogates for building performance simulation (BPS) models to leverage their energy predictive capabilities while reducing computational costs. In parallel, researchers are developing optimisation methods to inform building design and retrofit strategies but rarely employ ML-based BPS surrogates for this purpose. This study proposes a coupled modelling approach that leverages the capabilities of ML-based BPS surrogate models and multi-objective optimisation to inform holistic design and operation retrofits at low computational costs. The proposed methodology is demonstrated using an archetypal office building in Ottawa, Canada. The developed models achieved competitive predictive accuracies (adjusted R2: 0.90–0.99), identifying total and peak energy saving measures with up to 34% improvement in occupant thermal comfort at computational speeds 1266 times faster than a traditional BPS-based optimisation approach. Results offer a promising modelling workflow for design applications requiring extensive computations and scenario analyses, such as net-zero energy retrofits.

Advancing building energy efficiency: A deep learning approach to early-stage prediction of residential electric consumption

Enhancing building energy efficiency underscores the critical need for innovative predictive models to mitigate environmental issues from high energy consumption, especially in residential areas with air-conditioning and heating ventilation systems. This study introduces the use of Long Short-Term Memory (LSTM) networks for early prediction of residential electric consumption, representing a significant innovation in the field. Unlike traditional Deep Neural Network (DNN) and Artificial Neural Network (ANN) models, Long Short-Term Memory networks efficiently process time-series data, predicting future energy usage with unmatched accuracy. The Long Short-Term Memory model exhibited superior training efficiency, requiring only 2.69 s for over 500 test cases, outperforming Deep Neural Network and Artificial Neural Network models, which took 5.26 and 3.88 s, respectively. Its predictive accuracy, evidenced by an R-squared value of 0.97, surpasses the 0.95 and 0.92 of Deep Neural Network and Artificial Neural Network models, respectively. This breakthrough enables accurate predictions of annual energy usage before construction starts and aids in identifying energy efficiency improvements early in the design process. Applying Long Short-Term Memory networks in this context marks a substantial advancement in predictive modeling for building energy consumption, equipping architects and engineers with a vital tool for designing energy-efficient buildings from the beginning. The innovation and quantitatively proven effectiveness of the Long Short-Term Memory model highlight its potential to revolutionize early-stage building design strategies, filling a crucial gap in the existing literature.

Natural ventilation cooling effectiveness classification for building design addressing climate characteristics

The evaluation of natural ventilation potential for effective sustainable options and innovative green building design strategies is of great interest to architects, researchers and governments. From a retrospective review, we found that the potential evaluation of natural ventilation (NV) cooling effectiveness in the same category based on similar meteorological uncertainty, research objectives and objects showed significant differences. Uncertainties added and uncertainty propagation (both model form uncertainties and parameter uncertainties) could result in large discrepancies between simulation outcomes and real scenarios, especially in the design performance modeling (DPM) phase. In this conceptual design stage, a few parameters are available and therefore decisive. It is necessary to review and identify the key performance indicators and explore the extent to which deviations are caused by inconsistencies or biases in model information. As a basis for more concrete research, we propose statistical tests based on quantitative evaluations to explore the rule of natural ventilation potential volatility and identify whether there is a significant potential improvement resulting from the critical parameter enhancement with the optimal relationship. The showcase is applied in China, where there has been a significant amount of criticism regarding the current building climate zoning due to the perceived coarseness of the system and where there has been an active exploration into the possibility of redefining building climate zoning with a view toward improving its accuracy and effectiveness.

Enhancing Thermal and Daylight Performance of Historic Buildings with Passive Modifications; A Tropical Case Study

Historical buildings worldwide hold immense potential for adaptive reuse within the framework of the circular economy, a concept gaining traction in the building construction industry for its role in reducing carbon emissions. Many of these structures boast passive building design strategies, which inherently lower energy demands. Among these, thermal mass and daylight harvesting emerge as pivotal strategies for achieving indoor thermal and visual comfort, respectively. However, with the advent of significant climate change and evolving built environments, the efficacy of these historical passive strategies is subject to debate. This study focuses on a residential building constructed in the 17th century by Dutch settlers in Galle, Sri Lanka, serving as a case study. The research targets improvements in both thermal and visual comfort. Thermal performance analysis was conducted through air temperature measurements, revealing a notable 3-hour time lag and a 2.5°C reduction in peak air temperature during the day. Conversely, nighttime measurements indicated a rise in indoor temperature compared to ambient conditions. Using Design Builder software, the building was modelled to assess its daylighting conditions. Drawing upon thermodynamic principles and daylight harvesting techniques, the study proposes building envelope interventions and ventilation strategies to address nighttime overheating and enhance daylight utilization. The results demonstrate that these modifications can potentially reduce nighttime heat by 2-3°C, while also decreasing the energy requirement for lighting comfort from 51.10 kWh/m² per annum to 44.84 kWh/m² per annum. This research showcases the effectiveness of judiciously implemented interventions in historical buildings, illustrating tangible improvements in both thermal/visual performance and energy efficiency. Leveraging inherent qualities of historical structures and integrating modern design strategies to these buildings can play a vital role in sustainable urban development and energy conservation efforts.

Research on geometry optimization of park office buildings with the goal of zero energy

At the conceptual design stage, the building geometry design can predict the building load demand and renewable energy application potential to some extent. Geometry design interventions are critical to efficiently achieving the goal of zero-energy buildings. In the existing studies, the typicality and representativeness of the object geometry in the practice project are not high, and the influence of different geometry indices on energy savings and photovoltaic (PV) utilization potential under the same type of plane shape is rarely considered. In addition, the surrounding building shading situations considered are single. There is still significant room for improvement in the typical geometries selection and optimization condition settings. This paper presents a study of three typical park office building geometries in hot summer and cold winter regions. An optimization method based on the genetic algorithm and energy consumption simulation is proposed that takes into account both building energy savings and PV utilization potential improvements. The geometry-related indices of each typical geometry are then optimized under different PV layout scenarios and surrounding shading situations, and suitable geometry design strategies for typical office buildings are proposed under each optimization scenario. Geometry optimization can significantly reduce building energy consumption (the building energy-saving rate is 1.3–10.7 %) and increase PV generation (enhancement of 13.37–66.67 % for PV generation potential), thus lowering the net energy consumption of buildings. The findings of this study can be used to guide the design of park office building geometries in hot summer and cold winter regions with the goal of zero energy, as well as to promote the practice of zero-energy office buildings at the regional and national levels.

Innovative Learning Methods and Design Strategies of Library Buildings

When discussing the concepts of "education" and "teaching", conventional educational institutions, such as schools,typically come to mind. However, libraries also make a significant contribution to public education. Learning theoriesin educational sciences are dynamic and consistently updated to remain current. It is essential that any location thatfacilitates learning activities is cognizant of these trends and incorporates them into its philosophy of education. Toestablish the foundation for innovative library design, it is necessary to understand the zeitgeist and the currentrequirements of users. This study aims to examine innovative education methods, evaluate their applicabilityconcerning design criteria such as flexibility, sustainability, accessibility, and offer an updated design pathway forlibrary buildings.

Analysis of Diaphragm Force on Reinforced Concrete Building Structures with Horizontal Irregularities of Diaphragm Discontinuity

The diaphragm plays a crucial role in distributing seismic forces within buildings during earthquakes, affecting both regular and irregular structures differently. This study investigates the seismic behavior of diaphragms in various building geometries resembling the letters I, T, L, and O, focusing on their influence on structural performance and reinforcement requirements. Using analytical methods, diaphragm seismic forces, slab shear stresses, and internal forces were calculated for a sample of buildings with different geometrical irregularities. The study reveals significant differences in diaphragm earthquake forces between regular and irregular buildings, with irregular geometries exhibiting distinct patterns of shear stress distribution. Particularly, the building with an L-shaped plan and concentrated stress points showed the highest maximum shear stresses in both orthogonal directions. Analysis of internal forces—axial, shear, and moment—highlighted varying reinforcement needs among the studied buildings. While axial and shear forces necessitated minimal additional reinforcement across all structures, moment forces indicated substantial reinforcement requirements, particularly in the L-shaped building. These findings underscore the importance of tailored diaphragm design strategies for buildings with irregular geometries to mitigate potential structural vulnerabilities during seismic events. The study contributes insights into optimizing diaphragm design practices and emphasizes the need for further research in this critical area of structural engineering.

Life cycle techno-economic-environmental optimization for capacity design and operation strategy of grid-connected building distributed multi-energy system

Distributed multi-energy systems (DMS) have received increasing attention. Many studies have optimized the capacity and operation strategies of DMS based on multiple objectives, but these studies must discuss the weights of different objectives and have not considered the internal coupling between different objectives. Besides, existing studies have not considered the changes in the actual value of environmental impacts. To address these shortcomings, this paper constructs a technology-economic-environmental optimization model by mixed-integer linear programming. Based on life-cycle assessment, the model quantifies the value of system life-cycle environmental impacts by introducing carbon price. The case results show that the proposed optimization model can reduce the total cost by 28.83 % and the life cycle environmental cost by 3.39 % compared to the traditional model. To reduce the strain on the grid, a new operation pattern (The grid provides fixed electricity to the system throughout the year.) is proposed. The electricity interaction of the system with the grid under the new operation pattern is more than 70 % lower than the system without electricity purchased quantity constraint. Sensitivity analysis shows the total system cost is more sensitive to natural gas and electricity price than carbon price. But carbon price volatility helps reduce system carbon emissions.

Digitalizing and Greening the Built Environment

The paper investigated issues of greening and digitalizing the built environment with a view to identifying applications of Building Information Modelling (BIM) in it and prospects of smart cities development. The paper adopted qualitative research method, with its design based on archival materials in the subject investigated as contained in the literatures reviewed on it as a mono-method. Google search engine was employed to scout through Google Scholar, Science Direct, among other relevant websites for open-access materials. Qualitative data obtained were subjected to content/thematic analyses. Findings revealed that digitalizing and greening the built environment have great prospects in smart cities development, one of which is the creation of sustainable environment resulting in reduction of carbon emissions from the built environment, lowering of global warming, increase of user participation in buildings and lowering the cost of building lifecycle. Although green building design strategies and digitalization have advanced, full adoption in the built environment particularly in developing nations is required, hence the need to take steps in the right direction. Digitalizing and greening the built environment can enhance the quality of life of people by increasing availability of green spaces, improving air quality, creating healthy living spaces, and reducing pollution levels. The study sensitizes architects, planners, and other designers in considering sustainability and digitalization from predesign phase (incorporating required or special features into the design of future cities, towns, and microenvironments) to postconstruction phase making the environment sustainable.

Are Design Strategies for High-Performance Buildings Really Effective? Results from One Year of Monitoring of Indoor Microclimate and Envelope Performance of a Newly Built nZEB House in Central Italy

As buildings are one of the major contributors to greenhouse gas emissions and energy consumption, they have a key potential for energy efficiency and indoor environmental quality improvement. Therefore, the development of nearly Zero-Energy Buildings (nZEBs) is strategic to respond to these challenges and to design and retrofit sustainable highly performing buildings. Actually, the nZEB target can also be reached with highly insulated wooden technologies. However, they must be critically revised and adapted when taking into account the warm climate peculiarities. The paper contributes to this attempt by dealing with the implementation of a methodology specifically focused on the long-term assessment of the real building envelope performance. The methodology is applied to a recently built wooden nZEB detached single-story dwelling constructed in 2017 in central Italy. One year monitoring data were collected about the envelope in-field dynamic performance and the indoor microclimate and well-being conditions. The theoretical design-stage data and the monitored data were compared. The positive aspects as well as the critical issues of nZEB target in the Mediterranean climate context and the performance gap were underlined. Accordingly, the main aspects to be considered in the design of nZEBs envelope were highlighted.

Assessing the efficacy of green building design strategies in minimizing energy consumption in commercial buildings of Mumbai: A building performance analysis

This research paper investigates the effectiveness of green building design strategies in minimizing energy consumption in commercial buildings in the bustling metropolis of Mumbai, India. With a rapidly urbanizing and densely populated environment, Mumbai presents a unique setting for assessing green building practices. The research objectives focus on understanding the impact of various green building design features, such as green roofs, solar panels, and floor area optimization, on energy efficiency in commercial structures. The research employs a robust methodology, incorporating regression analysis to analyze data obtained from the Mumbai Municipal Corporation's building energy consumption records. Through this analysis, the study investigates the relationships between green building design parameters, building characteristics, and energy consumption patterns. Key findings indicate that specific green building features, including intensive and biodiverse green roofs and solar panel installations, significantly reduce energy consumption. Additionally, older buildings tend to exhibit lower energy consumption, emphasizing the need for retrofitting existing structures with energy-efficient solutions. The study also underscores the role of occupant density in influencing energy efficiency, with higher occupant rates leading to more efficient space utilization and energy use. The implications of this research are far-reaching, offering insights into tailoring green building strategies to the specific challenges posed by densely populated urban areas. These findings hold significance for sustainable urban development, policy formulation, architectural design, and the global effort to mitigate climate change.

A holistic two-stage decision-making methodology for passive and active building design strategies under uncertainty

In the last decade, many studies focused on finding optimal design solutions considering trade-offs between different aspects of building design. Accordingly, multi-objective optimization (MOO) approaches have been increasingly applied in the building industry. However, certain aspects must be deepened to ensure a more effective decision-making process in the early planning phase. On the one hand, uncertainties should be considered before making decisions to ensure the robustness of the optimal solutions; on the other hand, decisions are made at different times in building planning, and the sequential order of making decisions should be modeled. This paper presents a holistic two-stage multi-objective stochastic optimization (MOSO)-II framework to minimize the environmental impact of global warming potential (GWP) and cost throughout the entire life cycle of a building (phases of A1-A3, B4, B6 and C3-C4), considering passive and active design strategies in two consecutive stages, under uncertainty. Herein, individual/use and political/market uncertainties are considered. As a proof of concept, the proposed framework is applied in a case study for a generic zone in a multi-family terraced residential building type with solid brick construction. The advantages of the proposed framework are validated by comparing it with alternative single-stage MOSO frameworks. Results show that the proposed two-stage MOSO-II framework can deliver a smaller range of solutions with a better performance in terms of lower GWP and cost. It indicates that the proposed framework can effectively assist planners in decision-making by reducing the effort in choosing the proper solution. Secondly, the results also emphasize the importance of passive design strategies in sustainable building planning. In addition, the energy mix structure and cost of energy sources should be carefully adjusted in the future to promote a more ecologically sustainable building design.

Optimizing building solutions in a changing climate: parameter-based analysis of embodied and operational environmental impacts

Abstract Buildings contribute significantly to global energy consumption and carbon dioxide emissions. Climate change affects building performance, particularly heating and cooling demands. While current policies focus on improving energy performance and reducing operational emissions, the embodied emissions from building materials become more significant in energy-efficient buildings. This study aims to investigate optimal building solutions considering both operational and embodied environmental impact in the context of climate change in the Belgian context. The research questions address the influence of building characteristics on environmental impact and the contribution of embodied and operational emissions to optimal design. The study employs parametric life cycle assessment and dynamic building energy simulation to explore design strategies for a medium-sized office building. The results reveal the trade-offs between operational and embodied impacts. Buildings with better energy performance exhibit higher embodied emissions, highlighting the importance of considering both aspects. Pareto optimal buildings are identified, minimizing total life cycle environmental cost and operational environmental cost. Insulation levels, solar shading, and orientation are key factors in achieving optimal design. HVAC systems and electricity mixes also significantly influence optimal solutions. Lightweight and heavyweight buildings have distinct characteristics affecting heating and cooling demands. Variations in electricity mixes impact energy consumption and environmental costs of different HVAC system scenarios. The study emphasizes the need for a holistic life cycle approach and considering both operational and embodied impacts in building design. It underscores the importance of optimizing building characteristics while addressing climate change challenges. Further research should explore additional factors such as night cooling, HVAC system performance under climate change, and the inclusion of financial costs and visual comfort in the analysis.

A comparative study of gender differences in healthy office building strategies

BackgroundThe health of office workers has become a major concern under the pressure of increasingly fierce job competition. As countries have gradually promoted healthy buildings, there is an urgent need to create and construct healthy office environments. Although the WELL Building Standard proposed management and design strategies based on the principles of health and medicine, it does not consider group characteristics or gender differences.PurposeThis study aims to apply the theory of planned behavior to healthy building design and supplement the important role of gender and group characteristics in behavioral guidance based on architectural strategies and user behaviors to improve the relevant building evaluation system.MethodsThis study adopted a questionnaire survey and structural equation model. Four WELL-certified healthy office buildings in Nanshan District, Shenzhen, were selected for the survey. Based on the theory of planned behavior, structural equation models for men and women were established, compared, and analyzed. The factors affecting the health behaviors of the two groups and the actual effectiveness of various building optimization strategies were discussed, and an optimization direction for gender differences was proposed.ResultsThe findings indicated differences between male and female staff in their individual characteristics and implementation of health behaviors. Management strategies, subjective design strategies in assistance and guidance, and objective design strategies in spatial planning can promote the health behaviors of the two groups. However, the design strategies of result feedback and detail optimization only appeared to have a significant positive effect on female staff, whereas the intelligent automation design strategies only had an obvious intervention effect on men’s health behaviors.SignificanceThis study found that the theory of planned behavior in the field of social psychology could be applied to relevant research on architectural design and emphasized the influence of gender. It can not only provide the optimization direction for the evaluation standards of relevant healthy buildings but also promote the implementation of health behaviors in office groups and provide new ideas for promoting the development of healthy buildings.

Agent-based modeling of high-rise building fires reveals self-rescue behaviors and better fire protection designs

It is always challenging to seek external rescue assistance in high-rise building fires. Therefore, it is critical for individuals to master survival skills. For crowd dynamics modeling, previous research focused on numerical simulations and building designs with little attention to the self-rescue mechanism. It is critical to understanding crowd evacuations and better response strategies. We modeled the Grenfell Tower (a high-rise building with a complicated structure) case in 2017. Based on the percolation and social force models, we build an agent-based model to simulate individual behaviors inside. We obtain the optimal solution and robust paralleled outcomes under all counterfactual situations based on precisely matching tangible case outcomes (fire duration, deaths, and injuries). For individuals, mastering self-rescue skills is better at reducing social losses (deaths & injuries). In terms of high-rise buildings design, the central alarm system is also useful to reduce them. Besides, the crowd evacuation guided by the social force model also reduces deaths & injuries. This work provides insight into better high-rise building design and practical response strategies for societies. The central alarm system and fire-proof materials should be used in high-rise buildings. The residents should have routine training in social force-based evacuations and survival (self-rescue) skills to better the evacuation process and outcome under natural disasters and social emergencies.