Search Results (730)

Korea has a high population density, considering the size of its territory. Therefore, the importance of convenient and comfortable apartment buildings and high-rise residential–commercial complex buildings has been rising. In addition, because of the improvement in the standard of living along with continuous national economic growth, the interest in well-being and the expectation of a quiet life with a comfortable and pleasant residential environment have also been increasing. However, Koreans have a lifestyle involving sitting on the floor, so floor impact noise has been occurring more and more frequently. Because of this, neighborly disputes have been a serious social problem. And lately, damage and disputes from noise between floors have been increasing much more. The present work, therefore, used waste tire chips as a resilient material for reducing floor impact noise in order to recycle waste tires effectively. Also, a compounded resilient material, which combines EPS (expanded polystyrene), a flat resilient material on the upper part, with waste tire chips for the lower part, was developed. After constructing waste tire chips at a standardized test building, experiments with both light-weight and heavy-weight floor impact noise were performed. The tests confirmed that waste tire chips, when used as a resilient material, can effectively reduce both light-weight and heavy-weight floor impact noise. Full article

Over recent decades, phase-change materials (PCMs) have gained prominence as latent-heat thermal energy storage systems in building envelopes because of their high energy density. However, only PCMs that complete a full daily charge–discharge cycle can deliver meaningful energy and carbon-emission savings. This simulation study introduces a methodology that simultaneously optimizes PCM integration for storage efficiency, indoor thermal comfort, and energy savings. Two new indicators are proposed: overall storage efficiency (EC_n), which consolidates heating and cooling-efficiency ratios into a single value, and the performance factor (PF), which quantifies the PCM’s effectiveness in maintaining thermal comfort. Using EnergyPlus v8.9 coupled with DesignBuilder, a residential ASHRAE 90.1 mid-rise apartment was modeled in six warm-temperate (Cfb) European cities for the summer period from June 1 to August 31. Four paraffin PCMs (RT-22/25/28/31 HC, 20 mm thickness) were tested under natural and controlled ventilation strategies, with windows opening 50% when outdoor air was at least 2 °C cooler than indoors. Simulation outputs were validated against experimental cubicle data, yielding a mean absolute indoor temperature error ≤ 4.5%, well within the ±5% tolerance commonly accepted for building thermal simulations. The optimum configuration—RT-25 HC with temperature-controlled ventilation—achieved PF = 1.0 (100% comfort compliance) in all six cities and delivered summer cooling-energy savings of up to 3376 kWh in Paris, the highest among the locations studied. Carbon-emission reductions reached 2254 kg CO₂-e year⁻¹, and static payback periods remained below the assumed 50-year building life at a per kg PCM cost of USD 1. The EC_n–PF framework, therefore, provides a transparent basis for selecting cost-effective, energy-efficient, and low-carbon PCM solutions in warm-temperate buildings. Full article

The city of Al Ain is a fast-developing area. With building typology varying from low-rise to mid-rise, sustainable design in buildings is needed. As the majority of the city’s population is Emirati Citizens, the percentage of expats is increasing. The expats tend to live in mid-rise buildings. One of the central midrise areas is AL Ain Square. This study aims to investigate how an optimized mashrabiya pattern can impact the energy and the Predicted Mean Vote (PMV) in a 3-bedroom apartment, fully oriented to the south, of an expat family. The methodology is as follows: case study selection, Weather analysis, Modeling/Validation of the base case scenario, Optimization of the mashrabiya pattern, Simulation of various scenarios, and Results. Analyzing the selected case study is the initial step of the methodology. This analysis begins with the district, building typology, and the chosen apartment. The weather analysis is relevant for using the mashrabiya (screen device) and the need to improve energy consumption and thermal comfort. The modeling of the base case shall be performed in Rhino Grasshopper. The validation is based on a one-year electricity bill provided by the owner. The optimization of mashrabiya patterns is an innovative process, where various designs are compared and then optimized to select the most efficient pattern. The solutions to the selected scenarios will then yield the results of the optimal scenario. This study is relevant to industry, academia, and local authorities as an innovative approach to retrofitting buildings. Additionally, the research presents a creative vision that suggests optimized mashrabiya patterns can significantly enhance energy savings, with the hexagonal grid configuration demonstrating the highest efficiency. This finding highlights the potential for geometry-driven shading optimization tailored to specific climatic and building conditions. Contrasting earlier mashrabiya studies that assess one static pattern, we couple a geometry-agnostic evolutionary solver with a utility-calibrated EnergyPlus model to test thousands of square, hexagonal, and triangular permutations. This workflow uncovers a previously undocumented non-linear depth perforation interaction. It validates a hexagonal screen that reduces annual cooling energy by 12.3%, establishing a replicable, grid-specific retrofit method for hot-arid apartments. Full article

Contrastive learning is a machine learning technique in which models learn by contrasting similar and dissimilar data points. Its goal is to learn a representation of data in such a way that similar instances are close together in the representation space, while dissimilar instances are far apart. Our industrial use case focuses on a special case of contrastive learning called triplet learning. Building triplets with adequate difficulty is crucial to effective training convergence in such a setup. By combining online and offline mining techniques, we propose a method of mining hard triplets that is both performant and memory-inexpensive. Our experiments demonstrate that the method leads to improved identity pairing (which is the specific case of clustering) both on a real-life industry shoe dataset and on a generated benchmark one. 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

Designing energy-efficient buildings is essential for reducing global energy consumption and carbon emissions. However, traditional physics-based simulation models require substantial computational resources, detailed input data, and domain expertise. To address these limitations, this study investigates the use of three machine learning-based surrogate models—Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Multilayer Perceptron (MLP)—trained on a synthetic dataset of 2000 EnergyPlus-simulated building design scenarios to predict both energy use intensity (EUI) and cost estimates for midrise apartment buildings in the Toronto area. All three models exhibit strong predictive performance, with R² values exceeding 0.9 for both EUI and cost. XGBoost achieves the best performance in cost prediction on the testing dataset with a root mean squared error (RMSE) of 5.13 CAD/m², while MLP outperforms others in EUI prediction with a testing RMSE of 0.002 GJ/m². In terms of computational efficiency, the surrogate models significantly outperform a physics-based simulation model, with MLP running approximately 340 times faster and XGBoost and RF achieving over 200 times speedup. This study also examines the effect of training dataset size on model performance, identifying a point of diminishing returns where further increases in data size yield minimal accuracy gains but substantially higher training times. To enhance model interpretability, SHapley Additive exPlanations (SHAP) analysis is used to quantify feature importance, revealing how different model types prioritize design parameters. A parametric design configuration analysis further evaluates the models’ sensitivity to changes in building envelope features. Overall, the findings demonstrate that machine learning-based surrogate models can serve as fast, accurate, and interpretable alternatives to traditional simulation methods, supporting efficient decision-making during early-stage building design. Full article

The creation of child-friendly communities has become a key goal in sustainable global development. However, South Korea continues to experience a shortage of childcare facilities, resulting in gaps in the public care system and a growing reliance on private educational resources. Ensuring spatial spaces and implementing rational planning for children’s spaces have become critical tasks in building child-friendly cities. This study analyzed the accessibility of childcare facilities by housing type in Seongbuk-gu, Seoul, using the two-step floating catchment area (2SFCA) method, focusing on children residing in the district. It also evaluated whether these facilities were spatially and equally distributed. The findings are as follows. First, the overall accessibility to childcare facilities in Seongbuk-gu is limited, with significant disparities in accessibility depending on housing type. Second, the spatial equity assessment revealed high inequality indices for most facilities, particularly for those in apartment areas, which showed relatively higher levels of inequality. In conclusion, childcare facilities in Seongbuk-gu require substantial improvements in terms of both accessibility and equity. This study provides a policy framework for creating child-friendly communities and promoting equal access to care services for children by analyzing the spatial accessibility and equity of childcare facilities. Full article

This study investigates the long-term impact of insulation degradation on building heating energy consumption, with a focus on extruded polystyrene (XPS) insulation. Year-by-year degradation in thermal transmittance was derived from long-term experimental data and applied to prototypical energy models of multifamily apartment buildings and office buildings. Simulations were performed using both Actual Meteorological Year (AMY) and Typical Meteorological Year (TMY) data for six cities representing Korea’s major climate zones. The results showed that insulation degradation led to a significant increase in heating energy consumption from 23.2% to 34.9% in AMY simulations and 23.5% to 36.2% in TMY simulations for multifamily apartment buildings over 15 years. The difference between the AMY and TMY estimates was within 4%, demonstrating the reliability of TMY for long-term performance assessments. Notably, the southern and Jeju zones exhibited higher sensitivity to degradation due to their relaxed insulation standards and lower initial thermal performance. Office buildings were less affected, with increases below 8%, attributed to smaller envelope areas and higher internal heat gains. These findings highlight the need for zone-specific insulation standards and differentiated energy-saving design strategies by building type to ensure long-term energy efficiency. Full article

As polybrominated diphenyl ethers were phased out as flame retardants and plasticizers, increasing quantities of organophosphate triesters (OPEs) have been used as replacements. Despite a surge in reports on levels and profiles of OPEs, especially in indoor environments, and the potential exposure, there are still understudied areas with no data on the levels of these chemicals. We carried out the first study investigating levels and profiles of OPEs in indoor dust from such an area, the Tampa Bay (Florida) area. ∑₁₃OPEs measured at each site ranged from 545 to 502,086 ng g⁻¹, with overall medians and means over 64 sites of 15,447 and 36,135 ng g⁻¹, respectively. Alkyl OPEs were predominant, with lesser levels of chlorinated and aryl OPEs. Median levels were highest for tris (2-butoxyethyl) phosphate (TBOEP) and triphenyl phosphate (TPHP) at 4641 and 1046 ng g⁻¹, respectively; lower for tris(1,3–dichloro-2-propyl) phosphate (TDCIPP), tris(2-chloropropyl) phosphate (T2CPP), and tris (2-chloroisopropyl) phosphate (TCIPP) at 530, 458, and 360 ng g⁻¹, respectively; with others ranging from 2 to 85 ng g⁻¹. There were differences in levels in different microenvironments (urban versus suburban; non-residential versus residential; apartments versus single-family homes; daycares versus residences and university rooms; building age; and rooms with different floor material). Estimated daily intakes for median and higher exposure scenarios for ∑₁₃OPEs (in ng kg⁻¹ bw day⁻¹) were 12 and 552 for toddlers and 6 and 451 for adults, respectively. TBOEP accounted for 30% of total intake for toddlers and adults in a mean exposure scenario but 90% for high exposure scenario. Full article

In northern China, radiant floor heating is widely used in multi-apartment residential buildings, with indoor temperature being a key factor in evaluating a user’s heating demands. However, due to variations in building structure, room orientation, and the outdoor environment, identifying the optimal placement of temperature sensors across multiple zones remains challenging. In this study, we propose a data-driven methodology to identify the optimal placement of temperature sensors for a typical apartment with multiple zones. The proposed methodology is based on computational fluid dynamics (CFD) simulations of several typical scenarios and quantifies the relationship between the temperature field and the volume-averaged operating temperature to determine the optimal locations for temperature sensors. Results indicate that the temperature sensors need to be placed on planes ranging from 1.0 m to 1.7 m, with each plane featuring a distinct optimal area. The RMSE analysis reveals that, despite obvious temperature variations across the residence, the root mean square errors (RMSEs) at the designated sensor locations remain consistently low, with a maximum of 0.35 °C and most values below 0.3 °C. The above results indicate that the optimal sensor placement can significantly reduce potential errors between recorded temperatures and volume-averaged operating temperatures, which can be used as input parameters for personal indoor temperature control. Full article

Focusing on issues related to SDG 11 (Sustainable Cities and Communities) and SDG 13 (Climate Action), this study aligns with the framework of the 2030 Agenda for Sustainable Development. This study explores the barriers unique to the industry that obstruct the adoption of low-carbon emission solutions in Jordan’s multi-family residential buildings. Multi-family apartments constitute 73% of the total housing stock and account for over 80% of all residential structures. A total of eight main barriers that are preventing the implementation of low-carbon emission techniques were evaluated. The Fuzzy Delphi Method was utilized to gather insights from the Consultancy Council members of the Jordan Housing Investors Association. The results suggest that a major obstacle is the insufficient knowledge among end-users regarding environmental concerns, along with financial limitations, resulting in a lack of enthusiasm for low-carbon multi-family apartments. Moreover, insufficient cooperation between consultants and contractors leads to subpar constructability, which is worsened by the prevailing conventional procurement method that prioritizes cost and schedule above environmental consequences. To further investigate, it is advisable to examine the utilization of contemporary procurement methods, such as Design–Build and Construction Management and modern family contracts such as NEC4 in the housing industry of Jordan. These alternative methods have the potential to solve the current difficulties by promoting more effective and environmentally friendly building practices. Full article

Achieving carbon neutrality in the building sector is essential for addressing the global climate crisis. However, the production stage—which contributes to over 29% of a building’s life cycle carbon emissions (CE)—poses significant challenges for consistent carbon performance assessment due to the diversity of building materials and the uniqueness of individual building projects. These factors often lead to inconsistent evaluation results across assessors and the fragmented management of carbon data at the project level. This study proposes the Zero Carbon Building Index (ZCBI), a quantitative assessment method that incorporates embodied carbon from raw material extraction, transportation, and manufacturing. ZCBI enables the evaluation of carbon neutrality performance at the material level and supports the identification of reduction potentials in the production stage. A classification system was developed to evaluate CE during production, creating reference buildings for residential and non-residential purposes. Additionally, a Korean Environmental Product Declaration (EPD) database was established by incorporating CE data from 797 EPD-certified materials. Carbon reduction (CR) and ZCBI values were analyzed by categorizing CE variations across manufacturers into the lowest, average, and highest values. The results showed that CR for apartment complexes ranged from 42.1 to 311 kgCO₂e/m², with ZCBI values between 8.84% and 65.30%, and those for business facilities ranged from 40.9 to 264 kgCO₂e/m², with ZCBI values from 8.59% and 55.43. The proposed ZCBI framework provides a basis for optimizing material selection to reduce emissions and may evolve into a comprehensive carbon neutrality assessment covering the entire construction process. Full article

Ensuring proper indoor air quality in high-rise apartment buildings is a crucial challenge, particularly when upgrading ventilation systems during deep energy renovation of existing buildings. This study evaluates the condition of existing ventilation systems and assesses the performance, cost, and energy efficiency of different mechanical ventilation solutions with heat recovery, including centralized and decentralized balanced ventilation with heat recovery, single-room ventilation units, and mechanical extract ventilation with heat pump heat recovery or without heat recovery. An onsite survey revealed significant deficiencies in existing ventilation systems, such as airtight window installations without dedicated fresh air valves, misaligned and decayed exhaust shafts, and inadequate extract airflow in kitchens and bathrooms. SWOT analyses for each system highlighted their strengths, weaknesses, opportunities, and threats, providing valuable insights for decision-makers. The results indicate that while centralized and decentralized mechanical ventilation with heat recovery enhances energy efficiency and indoor air quality in high-rise multifamily apartment buildings, challenges such as high installation costs, maintenance complexity, and architectural constraints must be addressed. Heat recovery with exhaust air heat pumps is a viable alternative for high-rise apartment buildings when more efficient options are not feasible. Full article

This article presents a Synthetic-Aperture Distributed Phased Array (SADPA) framework to address emitter localization challenges in dynamic environments. Building on Distributed Synthetic-Aperture Radar (DSAR) principles, SADPA integrates distributed phased arrays with motion-induced phase compensation, enabling coherent aperture synthesis beyond physical array limits. By analytically modeling and compensating nonlinear phase variations caused by platform motion, we resolve critical barriers to signal integration while extending synthetic apertures. An improved MUSIC algorithm jointly estimates emitter positions and phase distortions, overcoming parameter coupling inherent in moving systems. To quantify fundamental performance limits, the Cramer–Rao bound (CRB) is derived as a theoretical benchmark. Numerical simulations demonstrate the SADPA framework’s superior performance in multi-source resolution and positioning accuracy; it achieves 0.012 m resolution at 10 GHz for emitters spaced 0.01 m apart. The system maintains consistent coherent gain exceeding 30 dB across both the 1.5 GHz communication and 10 GHz radar bands. Monte Carlo simulations further reveal that the MUSIC-DPD algorithm within the SADPA framework attains minimum positioning error (RMSE), with experimental results closely approaching the theoretical CRB. Full article

Penetration points on walls must include firestop measures to prevent the spread of fire. Countries worldwide have established standardized testing protocols for firestop methods, and firestop products must pass relevant tests before they can be used in buildings. In the present study, a simple method was developed to enhance the smoke leakage performance and fire resistance of existing polyvinyl chloride (PVC) pipes passing through walls. Two sets of smoke leakage tests were performed, followed by two sets of fire tests. The smoke leakage tests were nondestructive and thus did not damage the specimens; consequently, the same specimens could be used in the smoke leakage and fire tests. The results of the smoke leakage tests indicate that the method using PVC pipes wrapped with galvanized steel sleeves outperforms the method without such wrapping. Moreover, the results of the fire tests suggest that galvanized steel sleeves considerably improve thermal insulation and safety. This finding is explained as follows: PVC pipes may burn and break apart at high temperatures, compromising fire compartmentation. A galvanized steel sleeve can retain a burning, broken pipe piece, thereby preventing injuries and stopping the detached pipe from continuing to burn on the ground. Full article