Journal of Building Engineering, Год журнала: 2024, Номер 100, С. 111754 - 111754
Опубликована: Дек. 31, 2024
Язык: Английский
Journal of Building Engineering, Год журнала: 2024, Номер 100, С. 111754 - 111754
Опубликована: Дек. 31, 2024
Язык: Английский
International Communications in Heat and Mass Transfer, Год журнала: 2024, Номер 159, С. 108056 - 108056
Опубликована: Сен. 24, 2024
Язык: Английский
Процитировано
20Energy and Buildings, Год журнала: 2024, Номер unknown, С. 115083 - 115083
Опубликована: Ноя. 1, 2024
Язык: Английский
Процитировано
5Building and Environment, Год журнала: 2025, Номер unknown, С. 112689 - 112689
Опубликована: Фев. 1, 2025
Язык: Английский
Процитировано
0Sustainability, Год журнала: 2025, Номер 17(6), С. 2357 - 2357
Опубликована: Март 7, 2025
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 geometry or individual under scenarios, underscoring the potential benefits of adopting comprehensive, multiparameter approach integrates climate-responsive and sustainable strategies. This study bridges gap by systematically optimizing key parameters—building geometry, orientation, window-to-wall ratio (WWR), glazing type—to minimize loads enhance sustainability across five distinct climate zones. Fifteen different geometries with equal floor areas volumes were analyzed, considering fifteen types orientations varying 30° increments. DesignBuilder simulations yielded 16,900 results, due inherent challenges directly within simulation environments, data restructured reveal underlying relationships. An Energy Performance Optimization Model, based Particle Swarm (PSO) algorithm integrated an Artificial Neural Network (ANN), was developed identify optimal solutions tailored specific climatic conditions. The optimization results successfully determined combinations WWR, type reduce heating cooling loads, thereby promoting efficiency carbon emissions buildings. offers practical solution set provides architects actionable recommendations during early phase, establishing machine learning-based framework for achieving sustainable, energy-efficient, designs.
Язык: Английский
Процитировано
0Sustainability, Год журнала: 2025, Номер 17(6), С. 2342 - 2342
Опубликована: Март 7, 2025
The pursuit of sustainable design has made strides in improving building practices, yet traditional approaches often fall short addressing the holistic needs both environment and human well-being. This research delves into emerging field regenerative design, which extends beyond sustainability by seeking to restore enhance ecological systems. By integrating principles indoor environments, this study evaluates their impact on environmental quality (IEQ). Through a comprehensive literature review, demonstrates that can significantly air quality, thermal comfort, lighting, acoustics, ultimately creating healthier more productive spaces. paper also discusses potential challenges outlines future directions further advance application practices.
Язык: Английский
Процитировано
0Energies, Год журнала: 2025, Номер 18(7), С. 1584 - 1584
Опубликована: Март 22, 2025
To address the limitations of Non-Dominated Sorting Genetic Algorithm (NSGA-II) in optimizing active glass curtain wall shading systems—particularly its suboptimal convergence efficiency and high computational demands—this study proposes an improved NSGA-II algorithm incorporating parameter categorization. Shading system parameters (e.g., slat width, angle, separation, blind-to-glass distance) are classified into distinct categories based on their character optimized sequentially. This phased approach reduces search space dimensionality, lowering complexity while maintaining optimization accuracy. The framework integrates user preferences climatic adaptability to balance energy glare mitigation. louver were under same experimental conditions, enhanced exhibits 49% lower consumption values 5% smaller visual discomfort time duration compared baseline outcomes.
Язык: Английский
Процитировано
0Energies, Год журнала: 2025, Номер 18(7), С. 1867 - 1867
Опубликована: Апрель 7, 2025
According to the China Building Energy Consumption and Carbon Emissions Research Report (2023), construction industry accounts for 36.3% of total societal energy consumption, with residential buildings contributing significantly due their extensive coverage high operational frequency. Addressing efficiency carbon reduction in this sector is critical achieving national sustainability goals. This study proposes an optimization methodology rural dwellings Inner Mongolia, focusing on reducing demand while enhancing indoor thermal comfort daylight performance. A parametric model was developed using Grasshopper, (PPD), Useful Daylight Illuminance (UDI) simulated through Ladybug Honeybee tools. Key parameters analyzed include building morphology, envelope structures, environments, followed by systematic components. To refine multi-objective inputs, a specialized wall database established, enabling categorization dynamic visualization material properties methods. Comparative analysis demonstrated 22.56% 19.26% decrease occupant dissatisfaction 25.44% improvement UDI values post-optimization. The proposed framework provides scientifically validated approach improving environmental adaptability cold-climate architecture.
Язык: Английский
Процитировано
0Building and Environment, Год журнала: 2025, Номер unknown, С. 113071 - 113071
Опубликована: Апрель 1, 2025
Язык: Английский
Процитировано
0Journal of Building Engineering, Год журнала: 2024, Номер unknown, С. 111645 - 111645
Опубликована: Дек. 1, 2024
Язык: Английский
Процитировано
2Innovations in Systems and Software Engineering, Год журнала: 2024, Номер unknown
Опубликована: Окт. 22, 2024
Язык: Английский
Процитировано
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