Search Results (111)

Extremely low-frequency (ELF, 3–30 Hz) signals are effective for cross-medium transmission, yet conventional implementations are hindered by their large size and low efficiency. To address these limitations, a compact electromechanical–magnetic antenna (EMA) was developed and experimentally validated for ELF magnetic communication. The basic unit of the antenna, a single-EMA, consists of a stacked magnetostrictive composite beam, piezoelectric ceramic plates, and tip-mounted permanent magnets. The total envelope volume of a single EMA is only 3.3 cm³ with a maximum length of 12 cm, representing a substantial reduction compared with conventional ELF antennas. Building on this compact architecture, two EMAs were operated in parallel to form a parallel-EMA system, which significantly enhanced magnetic radiation through constructive magnetic coupling. Moreover, the optimal separation distance between the two EMAs was identified, ensuring efficient cooperative radiation. When driven at 50.2 mW, the parallel-EMA configuration generated a magnetic flux density of 114 pT at a transmission distance of 20 m in seawater. This performance demonstrates nearly a twofold improvement over a single-EMA unit, validating the scalability of parallel operation for stronger magnetic radiation. The compact form factor of the single EMA combined with the enhanced radiation performance of the parallel-EMA system enables portable ELF magnetic communication across diverse cross-medium scenarios, including air-to-sea and underground-to-air links. Full article

Thermal bridging through cold-formed steel (CFS) studs significantly reduces the thermal performance of light gauge steel frame (LSF) wall systems, particularly in climates demanding higher thermal resistance (R-value). While thermal breaks are commonly used, they increase material costs and construction complexity. According to NCC 2022, the minimum total R-value requirement for external walls ranges between 2.8 and 3.8 m²·K/W depending on the climate zone and building class. This study therefore evaluated web-perforated steel studs as a passive strategy to enhance thermal resistance of LSF walls, analysing 120 configurations with validated 3D finite element models in Abaqus and benchmarking in THERM. The results showed that web perforations consistently improved R-values by 14 to 20%, as isotherm contours and heat flux vectors demonstrated disruption of direct heat flow through the stud, thereby mitigating thermal bridging. Although the axial compression capacity of web-perforated CFS studs decreased by 29.5%, the use of 4 mm hole-edge stiffeners restored 96.8% of the original capacity. The modified NZS 4214:2006 and ASHRAE Modified Zone methods, incorporating steel area reduction and heat flux redistribution, closely matched Abaqus predictions, with coefficients of variation (COV) below 0.009, corresponding to less than 1% relative deviation between analytical and numerical R-values. Furthermore, application of web-perforated CFS studs in five external wall systems demonstrated improved thermal resistance, ensuring compliance with NCC 2022 R-value requirements across all Australian climate zones. Overall, the findings establish web-perforated studs as an effective solution for improving the energy performance of LSF building envelopes. Full article

Improving energy efficiency in buildings is critical for supporting sustainable growth in the construction sector. In this context, the implementation of passive solar solutions in the building envelope plays an important role. Trombe wall is a passive solar system that presents great potential for passive solar heating purposes. However, its performance can be enhanced when the Internet of Things is applied. This study employs a multi-domain smart system based on Matter-enabled IoT technology for maximizing Trombe wall functionality using appropriate 3D-printed ventilation grids. The system includes ESP32-C6 microcontrollers with temperature sensors and ventilation grids controlled by actuated servo motors. The system is automated with a Raspberry Pi 5 running Home Assistant OS with Matter Server. The integration of the Matter protocol provides end-to-end interoperability and secure communication, avoiding traditional systems based on MQTT. This work demonstrates the technical feasibility of implementing smart ventilation control for Trombe walls using a Matter-enabled infrastructure. The system proves to be capable of executing real-time vent management based on predefined temperature thresholds. This setup lays the foundation for scalable and interoperable thermal automation in passive solar systems, paving the way for future optimizations and addicional implementations, namely in order to improve indoor thermal comfort in smart and more efficient buildings. Full article

With the advancement of China’s “dual-carbon” strategy, optimizing the thermal performance of small-to-medium-sized sports buildings—key contributors to urban energy consumption and carbon emissions—has become a critical area of green building research. This study conducts a systematic literature review following the PRISMA framework, analyzing 96 high-relevance articles sourced from Web of Science, ScienceDirect, and CNKI. The review focuses on four key dimensions: building morphology, envelope thermal performance, eco-friendly material application, and thermal comfort strategies. Findings indicate that building geometry significantly influences natural ventilation and solar gain; optimizing the envelope system can enhance energy efficiency by 12–18%; and incorporating sustainable materials contributes to lifecycle carbon reduction. Furthermore, effective thermal comfort regulation requires the integration of climate-responsive strategies with intelligent control systems. The growing use of AI-assisted technologies—such as fuzzy logic, reinforcement learning, and real-time environmental feedback—is facilitating a shift from single-dimensional energy-saving approaches to multidimensional coupled optimization. This review establishes a comprehensive theoretical and practical framework for low-carbon design in small-to-medium sports buildings and highlights the urgent need for empirical validation and integrated design approaches across diverse climate zones. Full article

The construction of buildings using shipping containers (SCs) is a way to extend their useful life. They are constructed by modifying the structure, thermal, and acoustic conditioning by improving the envelope and creating openings for lighting and ventilation purposes. This study explores the architectural adaptation of SCs to sustainable residential housing, focusing on structural, thermal, and acoustic performance. The project centers on a case study in Madrid, Spain, transforming four containers into a semi-detached, multilevel dwelling. The design emphasizes modular coordination, spatial flexibility, and structural reinforcement. The retrofit process includes the integration of thermal insulation systems in the ventilated façades and sandwich roof panels to counteract steel’s high thermal conductivity, enhancing energy efficiency. The acoustic performance of the container-based dwelling was assessed through in situ measurements of façade airborne sound insulation and floor impact noisedemonstrating compliance with building code requirements by means of laminated glazing, sealed joints, and floating floors. This represents a novel contribution, given the scarcity of experimental acoustic data for residential buildings made from shipping containers. Results confirm that despite the structure’s low surface mass, appropriate design strategies can achieve the required sound insulation levels, supporting the viability of this lightweight modular construction system. Structural calculations verify the building’s load-bearing capacity post-modification. Overall, the findings support container architecture as a viable and eco-efficient alternative to conventional construction, while highlighting critical design considerations such as thermal performance, sound attenuation, and load redistribution. The results offer valuable data for designers working with container-based systems and contribute to a strategic methodology for the sustainable refurbishment of modular housing. Full article

Deep reinforcement learning (DRL)-based HVAC control has shown clear advantages over rule-based and model predictive methods. However, most prior studies remain limited to HVAC-only optimization or simple coordination with operable windows. Such approaches do not adequately address buildings with fixed glazing systems—a common feature in high-rise offices—where the lack of operable windows restricts adaptive envelope interaction. To address this gap, this study proposes a multi-zone control framework that integrates HVAC systems with electrochromic windows (ECWs). The framework leverages the Q-value Mixing (QMIX) algorithm to dynamically coordinate ECW transmittance with HVAC setpoints, aiming to enhance energy efficiency and thermal comfort, particularly in high-consumption buildings such as offices. Its performance is evaluated using EnergyPlus simulations. The results show that the proposed approach reduces HVAC energy use by 19.8% compared to the DQN-based HVAC-only control and by 40.28% relative to conventional rule-based control (RBC). In comparison with leading multi-agent deep reinforcement learning (MADRL) algorithms, including MADQN, VDN, and MAPPO, the framework reduces HVAC energy consumption by 1–5% and maintains a thermal comfort violation rate (TCVR) of less than 1% with an average temperature variation of 0.35 °C. Moreover, the model demonstrates strong generalizability, achieving 16.58–58.12% energy savings across six distinct climatic regions—ranging from tropical (Singapore) to temperate (Beijing)—with up to 48.2% savings observed in Chengdu. Our framework indicates the potential of coordinating HVAC systems with ECWs in simulation, while also identifying limitations that need to be addressed for real-world deployment. Full article

Urbanization in China and the proliferation of high-rise office buildings have led to increased demand for daylighting and thermal comfort. These requirements often result in reliance on active systems, including heating, cooling, and artificial lighting, which increase energy consumption. Existing studies have often focused on individual cases or room-scale models, which makes it difficult to generalize findings to the design of various high-rise office building types. Therefore, in this study, parametric prototype building models for high-rise office buildings were developed based on surveys of completed and under-construction projects. These surveys reflected actual design practices and were used to support systematic performance evaluation and typology-level optimization. Building performance was simulated using Grasshopper and Honeybee to generate large-scale datasets, and stacking ensemble learning models were used as surrogate predictors for energy use, daylighting, and thermal comfort. Multi-objective optimization was conducted using the non-dominated sorting genetic algorithm III (NSGA-III), followed by strategy formulation. The results revealed the following: (1) the proposed prototype model establishes clear parameter ranges for geometry, envelope design, and thermal performance, offering reusable models and data; (2) the stacking ensemble model outperforms individual models, improving the coefficient of determination (R²) by 0.5–16.1%, with mean squared error (MSE) reductions of 4.4–70.6%, and mean absolute error (MAE) reductions of 2.8–45.8%; (3) space length, aspect ratio, usable area ratio, window U-value, and solar heat gain coefficient (SHGC) were identified as primary performance drivers; and (4) optimized solutions reduced energy use by 3.79–11.81% and enhanced daylighting comfort by 40.16–50.32% while maintaining thermal comfort. The proposed framework provides localized, data-driven guidance for early-stage performance optimization in high-rise office building design. Full article

To meet the requirements of a prefabricated building with specific strength limitations and assembly rate criteria, the research proposes a Low-Strength Foamed Concrete Cold-Formed Steel (CFS) Framing Composite Enclosure Wall Panel (LFSW). The ABAQUS 2024 finite element analysis (FEA) combined with bending performance tests on five specimens were employed to examine crack propagation and failure modes of wall panels under wind load, investigating the influence mechanisms of foamed concrete strength, CFS framing wall thickness, CFS framing section height, and concrete cover thickness on the flexural performance of wall panels. The experimental results demonstrate that increasing the steel thickness from 1.8 mm to 2.5 mm enhances the ultimate load-carrying capacity by 46.15%, while enlarging the section height from 80 mm to 100 mm improves capacity by 26.67%. When the foamed concrete strength increased from 0.5 MPa to 1.0 MPa, the wall panel cracking load increased by 50%, while the ultimate load capacity changed by less than 5%. Increasing the concrete cover thickness from 25 mm to 35 mm enhanced the ultimate capacity by 7%, indicating that both parameters exert limited influence on the composite wall panel’s flexural capacity. Finite element simulations demonstrate excellent agreement with experimental results, confirming effective composite action between foamed concrete and CFS framing under service conditions. This validation establishes that the simplified analytical model neglecting interface slip provides better accuracy for engineering design, offering theoretical foundations and practical references for optimizing prefabricated building envelope systems. Full article

Climate change threatens the sustainability of historic buildings with increasing extreme weather events, making energy resilience critical. However, studies on energy resilience often lack forward-looking, holistic approaches. This study aims to develop a conceptual framework that includes how Artificial Intelligence (AI) technologies can support energy resilience in historical buildings with data-driven prediction and analysis to increase energy resilience against climate change. This study applied a methodology with four-stage qualitative research techniques, including a systematic literature review (PRISMA method), content analysis, AI integration, and conceptual framework development processes, in the intersections of historical building, energy resilience, and climate change. The findings reveal a significant research gap in the predictive analysis of the resilience of historic buildings and the integration of AI-based tools in the context of climate change. The proposed framework outlines a multi-layered system that includes data collection, performance analysis, scenario-based prediction, and AI-assisted decision-making, aiming to enhance the resilience of the building (including building envelope, thermal, and lifecycle analysis). Consequently, this study provides a theoretical and methodological perspective and proposes a scientifically based and applicable roadmap. It also highlights the potential of AI as a bridge between energy resilience and historical buildings in the face of a rapidly changing climate. Full article

Urban building energy retrofit (UBER) is a critical strategy for advancing the low-carbon and climate-resilience transformation of cities. The integration of machine learning (ML), data-driven clustering, and multi-objective optimization (MOO) is a key aspect of artificial intelligence (AI) that is transforming the process of retrofit decision-making. This integration enables the development of scalable, cost-effective, and robust solutions on an urban scale. This systematic review synthesizes recent advances in AI-driven MOO frameworks for UBER, focusing on how state-of-the-art methods can help to identify and prioritize retrofit targets, balance energy, cost, and environmental objectives, and develop transparent, stakeholder-oriented decision-making processes. Key advances highlighted in this review include the following: (1) the application of ML-based surrogate models for efficient evaluation of retrofit design alternatives; (2) data-driven clustering and classification to identify high-impact interventions across complex urban fabrics; (3) MOO algorithms that support trade-off analysis under real-world constraints; and (4) the emerging integration of explainable AI (XAI) for enhanced transparency and stakeholder engagement in retrofit planning. Representative case studies demonstrate the practical impact of these approaches in optimizing envelope upgrades, active system retrofits, and prioritization schemes. Notwithstanding these advancements, considerable challenges persist, encompassing data heterogeneity, the transferability of models across disparate urban contexts, fragmented digital toolchains, and the paucity of real-world validation of AI-based solutions. The subsequent discussion encompasses prospective research directions, with particular emphasis on the potential of deep learning (DL), spatiotemporal forecasting, generative models, and digital twins to further advance scalable and adaptive urban retrofit. Full article

Building façades traditionally focus on enhancing indoor environmental quality and improving energy performance, but undermine their influence on Outdoor Environmental Comfort (OEC), including thermal, acoustic, and visual conditions. With technological advancements in envelope design, research on new materials and green systems has been introduced in the last few decades. This review examines the role of two key elements—façade materials and green façades—in shaping OEC. A total of 41 peer-reviewed studies (24 on urban scale and 17 on building scale) were categorized into three focus areas: (1) outdoor thermal comfort; (2) outdoor acoustic comfort; and (3) outdoor visual comfort. The analysis was structured across three levels: (a) Performance Determinants; (b) Metrics/Models; and (c) Material or Façade Types. We proposed this analytical structure to highlight the interactions between building façades and OEC domains (thermal, acoustic, and visual comfort). Our results showed façade treatment can impact all three comfort factors related to OEC, but trade-offs must be evaluated. Moreover, the findings highlighted that additional research is required to cover variations in both climate and context conditions, due to their close association with the OEC. Finally, the conceptual framework is presented to synthesize the three comfort domains for sustainable outdoor environments. Full article

This study presents a novel switchable multi-inlet Building integrated photovoltaic/thermal (BIPV/T) curtain wall system designed to enhance solar energy utilization in commercial buildings. The system integrates controllable air inlets and motorized dampers that dynamically adjust airflow patterns in response to real-time environmental conditions such as solar irradiance, ambient air temperature, and PV panel temperature. A steady-state energy balance model, developed using a thermal network analogy and implemented in Python, was used to simulate winter operation in Montréal, Canada. Three operating modes with different air inlet configurations were assessed to evaluate system performance across variable air velocities and solar conditions. Results indicate that the switchable system improves combined thermal and electrical generation by 2% to 25% compared to fixed one- or two-inlet systems. Under low irradiance and air velocity, one-inlet operation is dominant, while higher solar gain and airflow favor two-inlet configurations. The system demonstrates effective temperature control and enhanced energy yield through optimized airflow management. This work highlights the potential of integrated control strategies and modular façade design in improving the efficiency of solar building envelope systems and offers practical implications for scalable deployment in energy-efficient, heating-dominated climates. Full article

Building thermal mass offers a cost-effective solution to enhance the integration of energy supply and demand in dynamic energy systems. Thermally activated building systems (TABS), incorporating embedded heat tubes, shows strong potential for energy flexibility. However, the significant thermal inertia of TABS also imposes challenges to precise load shift and indoor climate control. This review synthesizes key research on the effective demand-side management of TABS from multiple perspectives. It examines and compares various TABS configurations, including floor, ceiling, and wall systems. Differences in heat transfer performance between heating and cooling result in distinct application preferences for each type. The integration of advanced materials, such as phase change materials (PCM), can further enhance energy flexibility. TABS flexibility is primarily activated through adjustments to indoor operative temperature, with relevant influencing factors and regulatory constraints analyzed and discussed. Key aspects of optimizing building energy flexibility, including simulation methods and control strategies for TABS, are reviewed from both theoretical and practical perspectives. The energy and economic performance of TABS under various control strategies is analyzed in detail. This review provides insights to support the optimal design and operation of TABS within dynamic energy systems and to enhance the energy flexibility of building envelopes. Full article

Enhancing the real-world performance of sustainably designed and certified green buildings remains a significant challenge, particularly in hot climates where efforts to improve thermal comfort often conflict with energy efficiency goals. In the United Arab Emirates (UAE), even newly constructed facilities with green building certifications present opportunities for retrofitting and performance optimization. This study investigates the energy and thermal comfort performance of a LEED Gold-certified, mixed-use university campus in Dubai through a calibrated digital twin developed using IES thermal modelling software. The analysis evaluated existing sustainable design strategies alongside three retrofit energy conservation measures (ECMs): (1) improved building envelope U-values, (2) installation of additional daylight sensors, and (3) optimization of fan coil unit efficiency. Simulation results demonstrated that the three ECMs collectively achieved a total reduction of 15% in annual energy consumption. Thermal comfort was assessed using operative temperature distributions, Predicted Mean Vote (PMV), and Predicted Percentage of Dissatisfaction (PPD) metrics. While fan coil optimization yielded the highest energy savings, it led to less favorable comfort outcomes. In contrast, enhancing envelope U-values maintained indoor conditions consistently within ASHRAE-recommended comfort zones. To further support energy reduction and progress toward Net Zero targets, the study also evaluated the integration of a 228.87 kW rooftop solar photovoltaic (PV) system, which offset 8.09% of the campus’s annual energy demand. By applying data-driven thermal modelling to assess retrofit impacts on both energy performance and occupant comfort in a certified green building, this study addresses a critical gap in the literature and offers a replicable framework for advancing building performance in hot climate regions. Full article

Dynamic and Adaptive solar systems demonstrate a greater potential to enhance the satisfaction of occupants, in terms of indoor environment quality and the energy efficiency of the buildings, than conventional shading solutions. This study has evaluated Dynamic and Adaptive Photovoltaic Shading Systems (DAPVSSs) through a comprehensive analysis of six shading designs in which their energy production and the comfort of occupants were considered. Energy generation, thermal comfort, daylight, and glare control have been assessed in this study, considering multiple orientations throughout the seasons, and a variety of tools, such as Rhino 6.0, Grasshopper, ClimateStudio 2.1, and Ladybug, have been exploited for these purposes. The results showed that the prototypes that were geometrically more complex, designs 5 and 6 in particular, had approximately 485 kWh higher energy production and energy savings for cooling and 48% better glare control than the other simplified configurations while maintaining the minimum daylight as the threshold (min DF: 2%) due to adaptive and control methodologies. Design 6 demonstrated optimal balanced performance for all the aforementioned criteria, achieving 587 kWh/year energy production while maintaining the daylight factor within the 2.1–2.9% optimal range and ensuring visual comfort compliance during 94% of occupied hours. This research has established a framework that can be used to make well-informed design decisions that could balance energy production, occupants’ wellbeing, and architectural integration, while advancing sustainable building envelope technologies. Full article