Explore the vast range of titles available.

Electrochromic (EC) glazing reduces the cooling load via solar radiation shielding. However, excessive solar radiation shielding increases the heating load. In other words, the energy‐saving effect of EC glazing is dependent on the energy performance of the building. This study compares the heating and cooling loads reduction effects of static and EC glazing under various conditions to evaluate the regional applicability of EC glazing in Japan. Furthermore, to maximize the effect, we employ a machine learning (ML)‐based operation and evaluate its efficiency. A parametric study is conducted based on a standard office model in Japan using the DesignBuilder software. The result shows that the heating and cooling loads reduces by 17.1% compared with low‐E glazing in warm climates (Miyazaki, Zone 7). However, in cold climates (Obihiro, Zone 2), the energy increase is 25.4% and the trend of the effect changes near Zone 4. Therefore, on days when the heating load is expected to occur in Zones 3–5, we incorporate solar heat before working hours. The results show that reduction in heating and cooling loads of 2–3% can be expected and that the operation schedule can be set accurately via ML.

Recently, a growing interest has been observed in HVAC control systems based on Artificial Intelligence, to improve comfort conditions while avoiding unnecessary energy consumption. In this work, a model-free algorithm belonging to the Deep Reinforcement Learning (DRL) class, Soft Actor-Critic, was implemented to control the supply water temperature to radiant terminal units of a heating system serving an office building. The controller was trained online, and a preliminary sensitivity analysis on hyperparameters was performed to assess their influence on the agent performance. The DRL agent with the best performance was compared to a rule-based controller assumed as a baseline during a three-month heating season. The DRL controller outperformed the baseline after two weeks of deployment, with an overall performance improvement related to control of indoor temperature conditions. Moreover, the adaptability of the DRL agent was tested for various control scenarios, simulating changes of external weather conditions, indoor temperature setpoint, building envelope features and occupancy patterns. The agent dynamically deployed, despite a slight increase in energy consumption, led to an improvement of indoor temperature control, reducing the cumulative sum of temperature violations on average for all scenarios by 75% and 48% compared to the baseline and statically deployed agent respectively.

Adaptive façades, also known as climate-adaptive building shells (CABSs), could make a significant contribution towards reducing the energy consumption of buildings and their environmental impacts. There is extensive research on glazed adaptive façades, mainly due to the available technology for glass materials. The technological development of opaque adaptive façades has focused on variable-thermal-resistance envelopes, and the simulation of this type of façade is a challenging task that has not been thoroughly studied. The aim of this study was to configure and validate a simplified office model that could be used for simulating an adaptive façade with variable thermal resistance via adaptive insulation thickness in its opaque part. Software-to-software model comparison based on the results of an EnergyPlus Building Energy Simulation Test 900 (BesTest 900)-validated model was used. Cooling and heating annual energy demand (kWh), peak cooling and heating (kW), and maximum, minimum, and average annual hourly zone temperature variables were compared for both the Adaptive and non-adaptive validated model. An Adaptive EnergyPlus model based on the BesTest 900 model, which uses the EnergyPlus SurfaceControl:MovableInsulation class list, was successfully validated and could be used for studying office buildings with a variable-thermal-resistance adaptive façade wall configuration, equivalent to a heavyweight mass wall construction with an External Insulation Finishing System (EIFS). An example of the Adaptive model in the Denver location is included in this paper. Annual savings of up to 26% in total energy demand (heating + cooling) was achieved and could reach up to 54% when electro-chromic (EC) glass commanded by a rule-based algorithm was added to the glazed part of the variable-thermal-resistance adaptive façade.

Rapid urbanization and industrialization have led to great changes to the climate, such as global warming, urban heat islands, and frequent fluctuations in ambient temperature, and also a large amount of building energy consumption. Adaptive building provides an appropriate solution to maintain low energy consumption under various indoor and outdoor conditions and therefore has increasingly gained attention recently. Yet there is no clear definition on adaptive buildings and the current literature often focuses on the building envelope and overlooks buildings’ mechanical system, which is also an important part of the building system for responding to the indoor requirements and outdoor conditions. This article presents a systematic review on the research and development of adaptive buildings to address the identified research gaps. Firstly, it introduces and discusses the definition and evolution of the concept of adaptive building. Secondly, it reviews the adaptive building envelope technologies of roof, wall and window. Thirdly, it investigates the research progress on the adaptive mechanical system, especially lighting and air-conditioning systems. Lastly, it demonstrates practical applications of adaptive buildings and provides recommendations on future research directions on adaptive buildings.

Background: Earth's temperature has been rising since 1900, and the annual temperature has increased from 20°C to 24°C on the Mediterranean coastline. The external climate directly relates to indoor environmental quality (IEQ) and building performance, particularly in educational buildings. This paper proposes smart adaptive building envelopes (SABEs) as a potential solution for resilient architecture which is prone to unexpected weather patterns posed by climate change. Methods: A multi-dimensional criterion methodology is employed based on Egypt's local climate, using SABEs to provide thermal comfort and natural daylight using minimum energy. The paper's novelty is in using a comparative methodology that is complemented with a software simulation (OpenStudio 3.0.1) to address the existing educational building design challenges in providing IEQ, and to assess the proposed SABE design's performance, whilst providing better indoor thermal comfort and daylight. Results: The results show that the application of SABEs has led to significant reduction of the energy consumed, by 7.62% in summer and 5.42% in winter Conclusions: The implications of SABEs on IEQ in terms of thermal comfort and daylight are significant. SABEs also reduce energy consumption.

This study explored the role of zeolite and AI-driven initiatives in sustainable construction, particularly for net-zero and climate-adaptive buildings. A quantitative, scientometric, and narrative review was conducted using bibliometric analysis of existing publications from the Scopus and Web of Science databases to identify research trends, key contributions, and technological advancements. The findings revealed that zeolite enhances construction materials by improving thermal regulation, air purification, and carbon capture, while AI optimises energy efficiency, predictive maintenance, and material performance. A cost–benefit analysis showed that integrating zeolite and AI in construction materials reduces long-term energy costs and enhances building sustainability. Comparisons with previous studies highlighted the increasing adoption of these technologies due to their environmental and economic benefits. This study concluded that the combination of zeolite and AI provides innovative solutions for green construction, offering energy-efficient, climate-resilient, and cost-effective building materials.

Pursuing innovations in sustainable architectural solutions, this study examines the impact of a climate-adaptive building envelope with dynamic photovoltaic integrated shading devices (PVSDs) on building performance. A major challenge in designing PVSDs is the lack of established guidelines for geometry and operations. We delve into the complexities and potential benefits of integrating dynamic PVSD designs into building performance simulations, particularly considering their time-varying geometric and operational aspects. This research assesses a range of similar PVSD design options with differing patterns, emphasizing their effects on solar energy potential, daylighting, and thermal efficiency. We conducted tests on south-oriented PVSDs (featuring two-axis rotation) in Houston, Texas, focusing on variables such as panel count (4 or 36), rotation angle range, and operational patterns (synchronized or individual). Regarding solar potential, the four-panel synchronized PVSD option outperformed static shading by 2.1 times. For daylighting and thermal performance, the 36-panel synchronized option with a wide rotation range and the four-panel individual option proved superior to other PVSD configurations, improving up to an average of 36% (sDA300/50%) and 1.5 °C, respectively. Our findings emphasize the critical role of integrating geometric design and operational patterns in PVSDs for enhanced system effectiveness and highlight PVSD design and application limitations. Our findings emphasize the critical role of integrating geometric design and operational patterns in PVSDs for enhanced system effectiveness. Furthermore, they shed light on the limitations in the PVSD design process and practical applications.

This study employs both simulation and experimental methodologies to evaluate the effectiveness of bi-sectional horizontal kinetic shading systems (KSS) with horizontal fins in enhancing daylight comfort across various climates. It emphasizes the importance of optimizing daylight levels while minimizing solar heat gain, particularly in the context of increasing energy demands and shifting climatic patterns. The study introduces a custom-designed bi-sectional KSS, simulated in three distinct climates—Wroclaw, Tehran, and Bangkok—using climate-based daylight modeling methods with the Ladybug and Honeybee tools in Rhino v.7 software. Standard daylight metrics, such as Useful Daylight Illuminance (UDI) and Daylight Glare Probability (DGP), were employed alongside custom metrics tailored to capture the unique dynamics of the bi-sectional KSS. The results were statistically analyzed using box plots and histograms, revealing UDI300–3000 medians of 78.51%, 88.96%, and 86.22% for Wroclaw, Tehran, and Bangkok, respectively. These findings demonstrate the KSS’s effectiveness in providing optimal daylight conditions across diverse climatic regions. Annual simulations based on standardized weather data showed that the KSS improved visual comfort by 61.04%, 148.60%, and 88.55%, respectively, compared to a scenario without any shading, and by 31.96%, 54.69%, and 37.05%, respectively, compared to a scenario with open static horizontal fins. The inclusion of KSS switching schedules, often overlooked in similar research, enhances the reproducibility and clarity of the findings. A physical reduced-scale mock-up of the bi-sectional KSS was then tested under real-weather conditions in Wroclaw (latitude 51° N) during June–July 2024. The mock-up consisted of two Chambers ‘1’ and ‘2’ equipped with the bi-sectional KSS prototype, and the other one without shading. Stepper motors managed the fins’ operation via a Python script on a Raspberry Pi 3 minicomputer. The control Chamber ‘1’ provided a baseline for comparing the KSS’s efficiency. Experimental results supported the simulations, demonstrating the KSS’s robustness in reducing high illuminance levels, with illuminance below 3000 lx maintained for 68% of the time during the experiment (conducted from 1 to 4 PM on three analysis days). While UDI and DA calculations were not feasible due to the limited number of sensors, the Eh1 values enabled the evaluation of the time illuminance to remain below the threshold. However, during the June–July 2024 heat waves, illuminance levels briefly exceeded the comfort threshold, reaching 4674 lx. Quantitative and qualitative analyses advocate for the broader application and further development of KSS as a climate-responsive shading system in various architectural contexts.

The consumption of construction materials and the pollution caused by their production can be reduced by the use of reliable adaptive load-bearing structures. Adaptive load-bearing structures are able to adapt to different load cases by specifically manipulating internal stresses using actuators installed in the structure. One main aspect of quality is reliability. A verification of reliability, and thus the safety of conventional structures, was a design issue. When it comes to adaptive load-bearing structures, the material savings reduce the stiffness of the structure, whereby integrated actuators with sensors and a control take over the stiffening. This article explains why the conventional design process is not sufficient for adaptive load-bearing structures and proposes a method for demonstrating improved reliability and environmental sustainability. For this purpose, an exemplary adaptive load-bearing structure is introduced. A linear elastic model, simulating tension in the elements of the adaptive load-bearing structure, supports the analysis. By means of a representative local load-spectrum, the operating life is estimated based on Woehler curves given by the Eurocode for the critical notches. Environmental sustainability is increased by including reliability and sustainability in design. For an exemplary high-rise adaptive load-bearing structure, this increase is more than 50%.

Operation of environmentally responsive building components requires rapid prediction of the optimal adaptation of geometric shapes and positions, and such responsive configuration needs to be identified during the design process as early as possible. However, building simulation practices to characterize optimized shapes of various geometric design candidates are limited by complex simulation procedures, slow optimization, and lack of site information. This study suggests a practical approach to the design of responsive building façades by integrating on-site sensors, building performance simulation (BPS), machine-learning, and 3D geometry modeling on a unified design interface. To this end, a novel and efficient hybrid optimization algorithm, tabu-based adaptive pattern search simulated annealing (T-APSSA), was developed and integrated with wireless sensor data communication (using nRF24L01 and ESP8266 WiFi modules) on a parametric visual programming language (VPL) interface Rhino Grasshopper (0.9.0076, McNeel, Seattle, USA). The effectiveness of T-APSSA for early-stage BPS and optimal design is compared with other metaheuristic algorithms, and the proposed framework is validated by experimental optimal envelope (window shading) designs for single (daylight) and multiple (daylight and energy) objectives. Test results demonstrate the improved efficiency of T-APSSA in calculations (two to four times faster than other algorithms). This T-APSSA-integrated sensor-enabled design optimization practice supports rapid BPS and digital prototyping of responsive building façade design.