Search Results (62)

This study investigates the effectiveness of passive design in low-rise residential buildings located in arid desert climates, using the Dubai Solar Decathlon Middle East (SDME) competition as a case study. This full-scale experiment offers a unique opportunity to evaluate design solutions under controlled, realistic conditions; prescriptive, modeled performance; and monitored performance assessments. The prescriptive assessment reviews geometry, orientation, envelope thermal properties, and shading. Most houses adopt compact forms, with envelope-to-volume and envelope-to-floor area ratios averaging 1 and 3.7, respectively, and window-to-wall ratios of approximately 17%, favoring north-facing openings to optimize daylight while reducing heat gain. Shading is strategically applied, horizontal on south façades and vertical on east and west. The thermal properties significantly exceed the local code requirements, with wall performance up to 80% better than that mandated. The modeled assessment uses Building Energy Models (BEMs) to simulate the impact of prescriptive measures on energy performance. Three variations are applied: assigning minimum local code requirements to all the houses to isolate the geometry (baseline); removing shading; and applying actual envelope properties. Geometry alone accounts for up to 60% of the variation in cooling intensity; shading reduces loads by 6.5%, and enhanced envelopes lower demand by 14%. The monitored assessment uses contest-period data. Indoor temperatures remain stable (22–25 °C) despite outdoor fluctuations. Energy use confirms that houses with good designs and airtightness have lower cooling loads. Airtightness varies widely (avg. 14.5 m³/h/m²), with some well-designed houses underperforming due to construction flaws. These findings highlight the critical role of passive design as the first layer for improving the energy performance of the built environment and advancing toward net-zero targets, specifically in arid desert climates. Full article

The growing number of daylighting metrics—often overlapping in scope or terminology—combined with the need for prior familiarization to interpret and apply them effectively, has created a barrier to their adoption beyond academic settings. Consequently, this study analyzes a representative set of established and emerging daylighting metrics to evaluate applicability, synergies, and limitations. Particular attention is given to their implications for occupant health, well-being, performance, and energy use, especially within the context of sensorless smart control systems. A virtual room model was simulated using DaySim 3.1 in two contrasting climates—Seville and London—with varying window-to-wall ratios, orientations, and occupancy schedules. The results show that no single metric provides a comprehensive daylighting assessment, highlighting the need for combined approaches. Daylighting Autonomy (DA) proved useful for task illumination, while Useful Daylight Illuminance (UDI) helped identify areas prone to excessive solar exposure. Spatial metrics such as Spatial Daylight Autonomy (sDA) and Annual Sunlight Exposure (ASE) offer an overview but lack necessary granularity. Circadian Stimulus Autonomy (CSA) appears promising for evaluating circadian entrainment, though its underlying models remain under refinement. Continuous Overcast Daylight Autonomy (DAo.con) shows the potential for sensorless lighting control when adjusted for orientation. A nuanced, multi-metric approach is therefore recommended. Full article

The timeshare is gradually becoming an essential global tourism operation model, especially in rural areas of China, where the leisure industry is developing rapidly. Meanwhile, the environmental issues of the rapidly growing timeshare-related building production have received widespread attention. The existing research on zero-carbon buildings considers carbon emissions as a constant value and cannot adapt to the impact of user changes during the operation phase. Constructing a low-carbon design applicable to timeshare is significant for controlling carbon emissions in the construction industry and responding to the environmental crisis. The practical carbon emissions of touristic apartments depend on the requirement changes in different customer clusters. The timeshare theory reflects the requirement change in different customer clusters based on the timeshare property ownership change. This paper focuses on a dynamic design strategy for zero-carbon building openings to reduce practical carbon emissions. Firstly, this research clarifies the primary customer clusters and conducts a touristic apartment unit model by timeshare property ownership. Then, this research clarifies the changes in customer requirements to analyze the spatial function changes in the operating phase. Finally, the study identifies six dynamic carbon emission indicators, such as the window-to-wall ratio, ventilation rate, and effective daylight area, and through passive design methods, provides 13 variable devices applied in the operating phase to control dynamic carbon emission indicators by customers. This paper also offers a flexible method to effectively decrease and accurately control carbon emissions by reducing the possible device utility. Full article

With the rapid advancement of urbanization in China, the demand for community-based elderly care facilities (CECFs) has been increasing. One pressing challenge is the question of how to provide CECFs that not only meet the health needs of the elderly but also make efficient use of limited urban land resources. This study addresses this issue by adopting an integrated multi-method research framework that combines multi-objective optimization (MOO) algorithms, Spearman rank correlation analysis, ensemble learning methods (Random Forest combined with SHapley Additive exPlanations (SHAP), where SHAP enhances the interpretability of ensemble models), and Self-Organizing Map (SOM) neural networks. This framework is employed to identify optimal building configurations and to examine how different architectural parameters influence key daylight performance indicators—Useful Daylight Illuminance (UDI) and Daylight Factor (DF). Results indicate that when UDI and DF meet the comfort thresholds for elderly users, the minimum building area can be controlled to as little as 351 m² and can achieve a balance between natural lighting and spatial efficiency. This ensures sufficient indoor daylight while mitigating excessive glare that could impair elderly vision. Significant correlations are observed between spatial form and daylight performance, with factors such as window-to-wall ratio (WWR) and wall thickness (WT) playing crucial roles. Specifically, wall thickness affects indoor daylight distribution by altering window depth and shading. Moreover, the ensemble learning models combined with SHAP analysis uncover nonlinear relationships between various architectural parameters and daylight performance. In addition, a decision support method based on SOM is proposed to replace the subjective decision-making process commonly found in traditional optimization frameworks. This method enables the visualization of a large Pareto solution set in a two-dimensional space, facilitating more informed and rational design decisions. Finally, the findings are translated into a set of practical design strategies for application in real-world projects. Full article

Lecture halls are characterized by large spatial dimensions, deep floor plans, and high occupant densities. Lectures are typically conducted using multimedia and blackboard-based teaching, placing higher demands on the indoor light and thermal environment compared to standard classrooms. This study aims to simulate the interrelationships between multiple building envelope parameters and building performance, in order to improve visual and thermal comfort while reducing energy consumption in cold-region lecture halls. Based on seven key envelope parameters—including openable window area ratio, west-facing window-to-wall ratio, exterior insulation thickness, shading element spacing, angle and width, and window glass type—a multi-objective optimization framework was established. The optimization process targeted three key performance indicators—useful daylight illuminance (UDI), energy use intensity (EUI), and thermal comfort percentage (TCP)—in the context of a stepped classroom. The results show that increasing the thickness of exterior insulation and reducing the width of shading components contribute positively to photothermal comfort without compromising thermal and visual performance. Compared with the baseline design, optimized schemes that incorporate appropriate west-facing window-to-wall ratios, openable window areas, insulation thicknesses, and external shading designs can reduce annual energy consumption by up to 10.82%, and increase UDI and TCP by 12.79% and 36.41%, respectively. These improvements are also found to be economically viable. Full article

This study initially examined the thermal comfort of rural residents in southern Jiangsu, analyzing their tolerance levels and expected temperature ranges during winter and summer. Subsequently, Design Builder 7.02.004 software was utilized to simulate the energy consumption of typical residential buildings. Furthermore, an orthogonal test method was employed to investigate the significant relationships among seven factors influencing building energy consumption in both winter and summer. These factors include external wall heat transfer coefficient, roof heat transfer coefficient, external window heat transfer coefficient, external window solar heat gain coefficient (SHGC), window-to-wall-area ratio, air tightness, and building orientation. Finally, based on the findings from the thermal comfort study, recommended passive design parameters for near-zero-energy residential buildings in southern Jiangsu were proposed. This provides valuable references for the future construction efforts of such buildings within this region. Full article

With a focus on reducing building energy consumption, approaches that simultaneously optimize multiple passive design parameters in industrial buildings have received limited attention. Most existing studies tend to examine building geometry or individual design parameters under limited scenarios, underscoring the potential benefits of adopting a comprehensive, multiparameter approach that integrates climate-responsive and sustainable design strategies. This study bridges that gap by systematically optimizing key passive design parameters—building geometry, orientation, window-to-wall ratio (WWR), and glazing type—to minimize energy loads and enhance sustainability across five distinct climate zones. Fifteen different building geometries with equal floor areas and volumes were analyzed, considering fifteen glazing types and multiple orientations varying by 30° increments. DesignBuilder simulations yielded 16,900 results, and due to the inherent challenges in directly optimizing building geometry within simulation environments, the data were restructured to reveal underlying relationships. An Energy Performance Optimization Model, based on a Particle Swarm Optimization (PSO) algorithm integrated with an Artificial Neural Network (ANN), was developed to identify optimal design solutions tailored to specific climatic conditions. The optimization results successfully determined the optimal combinations of building geometry, orientation, WWR, and glazing type to reduce heating and cooling loads, thereby promoting energy efficiency and reducing carbon emissions in industrial buildings. This study offers a practical design solution set and provides architects with actionable recommendations during the early design phase, establishing a machine learning-based framework for achieving sustainable, energy-efficient, and climate-responsive industrial building designs. Full article

The lack of energy-saving design in national fitness centers has affected low-cost operation and indoor comfort. Existing studies mainly focus on the impact of lighting and heat on energy consumption in sports stadiums, highlighting the need for the comprehensive planning of natural ventilation design to improve energy efficiency. This study uses the national fitness center in Qingdao as a case study, collecting building environmental information through field measurements and questionnaire surveys. Four design elements were selected: the window-to-wall ratio (WWR), proportion of operable window area (OWAR), skylight area ratio (SAR), and floor plan layout. Through the utilization of Ladybug Tools in combination with Radiance and EnergyPlus, an annual energy consumption simulation under natural ventilation conditions was conducted using an airflow network model. This study found that the WWR has a significant impact on lighting, ventilation, and energy consumption. The optimal WWR configuration for the venue was determined to be 0.37 for the north facade, 0.26 for the east, 0.53 for the south, and 0.41 for the west. Compared to no natural ventilation, cooling energy consumption was reduced by 18.02%, and fan energy consumption decreased by 11.03%. The energy-saving effect was optimal when the OWAR was approximately 30%. When the SAR reached 5%, cooling and lighting energy consumption were significantly reduced, resulting in the lowest total energy consumption. The study also compared the energy consumption differences in various floor plan layouts under the influence of natural ventilation. This research evaluates the natural ventilation efficiency of community fitness centers, avoiding the hidden energy consumption transfer typical of traditional single-objective optimization methods, and improves the energy-efficient design approach for national fitness centers. Full article

Taking Yunyu New Village in Nanyang City, a typical newly built resettlement area of the South-to-North Water Diversion Project of China, as an example, this paper tries to construct a health environment evaluation index system for the resettlement area and determines the priority and content of residential environment renovation in the resettlement area through residents’ health satisfaction evaluation and IPA analysis. The results revealed that six factors, namely, winter insulation, summer heat insulation, quality of domestic drinking water, indoor natural light environment, humanized design, and architectural plane function design, need to be renovated first. For the indoor environment, which is the focus of renovation, the light and heat environments were evaluated via field measurements and simulation experiments. The results show that the indoor comfort, daylighting, and energy savings of the surveyed buildings all fail to meet Chinese building design standards. Corresponding optimization strategies for indoor ventilation, thermal insulation performance of the envelope structure, and window wall ratio are proposed and verified via relevant software simulations and immigrants’ wishes. For the outdoor environment, we investigate the living habits and renovation needs of immigrants from the aspects of public space and courtyard space in the resettlement area and propose corresponding optimization strategies. The results of this research can help enhance the sense of gain and happiness of immigrants in the resettlement and provide a reference for improving the living environment of the same type of immigrant resettlement area. Full article

Electricity consumption in buildings is a significant contributor to greenhouse gas emissions, which drive climate change. Reducing electricity use in residential buildings, which account for approximately 20% of Thailand’s total electricity consumption, represents a key opportunity for lowering greenhouse gas emissions. The aim of this study was to assess the potential reduction in greenhouse gas emissions through the use of appropriate solar absorptance in wall paint, conducted via an energy simulation using a representative residential building model from Bangkok. The DOE2.1E program was employed to simulate a standard two-story house commonly found in Thailand, with an approximate floor area of 120 square meters. The window-to-wall ratios were set at 10% and 20%, and air conditioning usage was modeled for nighttime hours. External wall paint was assigned varying solar absorption coefficients, ranging from 10% to 90%. Greenhouse gas emissions were calculated by multiplying the simulated annual electricity consumption by the emission factor, expressed in kgCO₂eq/kWh, provided by the Thailand Greenhouse Gas Management Organization. The results indicated that adjusting wall paint solar absorptance from 10% to 90% led to a 10% variation in both energy consumption and greenhouse gas emissions, potentially reducing CO₂ emissions by approximately 411–456 kgCO₂eq per house per year. Therefore, implementing regulations that mandate the use of wall paints with appropriate solar absorption coefficients could significantly reduce greenhouse gas emissions and contribute to environmental protection efforts in Thailand. Full article

University classrooms have an urgent need for energy saving and environmental optimization due to the energy consumption characteristics and the demand for a daylight environment. Classrooms in hot summer and cold winter (HSCW) areas in China are typically designed with a south-facing layout, but the indoor environment of the classrooms in actual use is not as satisfactory as it should be. This research examines the impacts of side-lit window design parameters and shading forms on the energy and daylight performance by using measurements and simulation. It is found that there is significant seasonal variation in the energy consumption of teaching buildings in HSCW areas, with cooling energy consumption being the primary focus of energy conservation. Additionally, appropriate shading measures can not only compensate for the energy deficiencies of the orientation and window-to-wall ratio (WWR), but also considerably enhance the indoor daylight conditions. The results indicate that the most effective way to optimize energy and daylight performance in classrooms is to adopt a north-facing layout with 400 mm shading louvers. The illuminance level of the working plane can be made more uniform and the useful daylight illuminance (UDI) can be increased to over 60%. Therefore, classroom designs in HSCW areas can be more flexible in terms of optimizing energy efficiency and daylight conditions by integrating various design parameters and shading measures. Full article

The construction industry accounts for over 40% of carbon emissions in the United States, with embodied carbon—emissions associated with building materials and construction processes—remaining underexplored, particularly regarding the impact of location and climate. This study addresses this gap by investigating the influence of different climate zones on the embodied carbon emissions of residential buildings. Using Building Information Modeling (BIM), 3D models were developed based on the 2021 International Energy Conservation Code (IECC) and International Residential Code (IRC). A lifecycle assessment (LCA) was conducted using Environmental Product Declarations (EPDs) to evaluate the embodied carbon of building materials during the product stage. The findings reveal that buildings in colder climates exhibit higher embodied carbon emissions, ranging from 25,768 kgCO₂e in Zone 1 to 40,129 kgCO₂e in Zone 8, due to increased insulation requirements. Exterior walls and roofs were identified as significant contributors, comprising up to 34% of total emissions. Sensitivity analysis further indicates that the window-to-wall ratio and interior wall design substantially affect embodied carbon, with baseline emissions around 170 kgCO₂e/m² in warm areas and 255 kgCO₂e/m² in cold areas. These results establish a baseline for lifecycle embodied carbon values across different climate zones in the United States and align with international standards. This study provides valuable insights for policymakers and designers, offering data to inform effective carbon reduction strategies and optimize building designs for sustainability. Full article

This study focuses on the effect of window openings on the seismic performance of the stone walls of Tibetan and Qiang dwellings. A typical stone wall of a Tibetan and Qiang dwelling constructed using irregular stone and yellow mud masonry in Li County, Sichuan Province, was chosen as a prototype, and two stone walls with different structural window openings were designed for proposed static tests and microscopic electron microscope scanning (SEM), which obtained the damage patterns and microscopic damage mechanisms of the walls and analyzed them in comparison with the test results of the stone walls without window openings. At the same time, a finite element model was established based on the test parameters to study the effects of opening size, shape, and aspect ratio on the seismic performance of the stone walls of Tibetan and Qiang dwellings. The findings indicate that “X”-shaped cracks at the corners of the window openings and extending to the surrounding areas are the primary damage characteristics. The unique microstructure of yellow clay and schist leads to the faster appearance of wall cracks. The peak load, stiffness, and energy dissipation of the windowed walls were less than those of the windowless walls. It was found through simulation that the seismic performance of the wall decreases with the increase in the opening size; as the wall’s openings take on different shapes, the ultimate bearing capacity steadily declines with the order of circular, square, triangular, trapezoidal, and rectangular; and under a range of aspect ratios, the wall’s seismic performance is best when the opening’s aspect ratio is 1:1. The research results of this paper are of reference value for the research, design, and construction of stone walls and other non-engineered masonry works of Tibetan and Qiang dwellings. Full article

More and more modern buildings are using glass curtain walls as their building envelope. The large area of window leads to a significant increase in solar heat gain, resulting in an increase in the cooling load and energy consumption of the building envelope. In the calculation of building cooling load, the thermal performance parameter of windows, the solar heat gain coefficient, is used to calculate the solar radiation heat gain of the windows. The window-to-wall ratio of buildings with glazing facades is large, and the phenomenon of escape of incident solar radiation cannot be ignored. In order to calculate the solar radiation escape rate, a dynamic model of solar radiation escape rate incorporating the solar path tracking model is developed in this research, which can achieve big data simulation analysis based on actual meteorological conditions. The model is programmed and simulated using MATLAB R2024a software. Five representative cities from different climate regions in China are selected and the variation rule of solar radiation escape rate are analyzed on three different time scales: day, month, and year. The influence of building orientation was also calculated and analyzed. The numerical calculation results indicate that the escape solar radiation rate varies with the incident angle of solar radiation at different times. It was found that the smaller the solar azimuth angle and solar altitude angle, the smaller the escape rate of solar radiation. The latitude of a city has a significant impact on the solar radiation escape rate. The weighted average of the solar radiation escape rates for each city were calculated for both summer and winter. Regardless of the season, the city’s location, and the orientation of the room, the value of solar radiation escape rate varies from 8.64% to 10.33%, which indicates that the solar radiation escape phenomenon cannot be ignored in glass curtain wall buildings. The results can be used as a reference value of solar radiation escape rate for the correction of actual solar heat gain of buildings in different climate regions. Full article

As the global energy demand rises and climate change creates more challenges, optimizing the performance of non-residential buildings becomes essential. Traditional simulation-based optimization methods often fall short due to computational inefficiency and their time-consuming nature, limiting their practical application. This study introduces a new optimization framework that integrates Bayesian optimization, XGBoost algorithms, and multi-objective genetic algorithms (GA) to enhance building performance metrics—total energy (TE), indoor overheating degree (IOD), and predicted percentage dissatisfied (PPD)—for historical (2020), mid-future (2050), and future (2080) scenarios. The framework employs IOD as a key performance indicator (KPI) to optimize building design and operation. While traditional indices such as the predicted mean vote (PMV) and the thermal sensation vote (TSV) are widely used, they often fail to capture individual comfort variations and the dynamic nature of thermal conditions. IOD addresses these gaps by providing a comprehensive and objective measure of thermal discomfort, quantifying both the frequency and severity of overheating events. Alongside IOD, the energy use intensity (EUI) index is used to assess energy consumption per unit area, providing critical insights into energy efficiency. The integration of IOD with EUI and PPD enhances the overall assessment of building performance, creating a more precise and holistic framework. This combination ensures that energy efficiency, thermal comfort, and occupant well-being are optimized in tandem. By addressing a significant gap in existing methodologies, the current approach combines advanced optimization techniques with modern simulation tools such as EnergyPlus, resulting in a more efficient and accurate model to optimize building performance. This framework reduces computational time and enhances practical application. Utilizing SHAP (SHapley Additive Explanations) analysis, this research identified key design factors that influence performance metrics. Specifically, the window-to-wall ratio (WWR) impacts TE by increasing energy consumption through higher heat gain and cooling demand. Outdoor temperature (Tout) has a complex effect on TE depending on seasonal conditions, while indoor temperature (Tin) has a minor impact on TE. For PPD, Tout is a major negative factor, indicating that improved natural ventilation can reduce thermal discomfort, whereas higher Tin and larger open areas exacerbate it. Regarding IOD, both WWR and Tin significantly affect internal heat gains, with larger windows and higher indoor temperatures contributing to increased heat and reduced thermal comfort. Tout also has a positive impact on IOD, with its effect varying over time. This study demonstrates that as climate conditions evolve, the effects of WWR and open areas on TE become more pronounced, highlighting the need for effective management of building envelopes and HVAC systems. Full article