Search Results (273)

Creating a comfortable microclimate in the premises of buildings is currently becoming one of the priorities in the field of architecture, construction and engineering systems. The increased attention from the scientific community to this topic is due not only to the desire to ensure healthy and favorable conditions for human life but also to the need for the rational use of energy resources. This area is becoming particularly relevant in the context of global challenges related to climate change, rising energy costs and increased environmental requirements. Practice shows that any technical solutions to ensure comfortable temperature, humidity and air exchange in rooms should be closely linked to the concept of energy efficiency. This allows one not only to reduce operating costs but also to significantly reduce greenhouse gas emissions, thereby contributing to sustainable development and environmental safety. In this connection, this study presents a parametric assessment of the influence of climatic and geometric factors on the aerodynamic characteristics of the air cavity, which affect the heat exchange process in the ventilated layer of curtain wall systems. The assessment was carried out using a combined analytical calculation method that provides averaged thermophysical parameters, such as mean air velocity ($V_s$), average internal surface temperature ($t_{in.s}^{av}$), and convective heat transfer coefficient (${\alpha }_s$) within the air cavity. This study resulted in empirical average values, demonstrating that the air velocity within the cavity significantly depends on atmospheric pressure and façade height difference. For instance, a 10-fold increase in façade height leads to a 4.4-fold increase in air velocity. Furthermore, a three-fold variation in local resistance coefficients results in up to a two-fold change in airflow velocity. The cavity thickness, depending on atmospheric pressure, was also found to affect airflow velocity by up to 25%. Similar patterns were observed under ambient temperatures of +20 °C, +30 °C, and +40 °C. The analysis confirmed that airflow velocity is directly affected by cavity height, while the impact of solar radiation is negligible. However, based on the outcomes of the analytical model, it was concluded that the method does not adequately account for the effects of solar radiation and vertical temperature gradients on airflow within ventilated façades. This highlights the need for further full-scale experimental investigations under hot climate conditions in South Kazakhstan. The findings are expected to be applicable internationally to regions with comparable climatic characteristics. Ultimately, a correct understanding of thermophysical processes in such structures will support the advancement of trends such as Lightweight Design, Functionally Graded Design, and Value Engineering in the development of curtain wall systems, through the optimized selection of façade configurations, accounting for temperature loads under specific climatic and design conditions. Full article

We demonstrate an all-fiber, high-sensitivity, dual-parameter sensor for humidity and temperature. The sensor consists of a symmetrical, non-adiabatic, tapered, single-mode optical fiber, operating at the wavelength near the dispersion turning point, and a cascaded fiber Bragg grating (FBG) for temperature compensation. At one end of the fiber’s tapered region, part of the fundamental mode is coupled to a higher-order mode, and vice versa at the other end. Under the circumstances that the two modes have the same group index, the transmission spectrum would show an interference fringe with uneven dips. In the tapered region of the sensor, some of the light transmits to the air, so it is sensitive to changes in the refractive index caused by the ambient humidity. In the absence of moisture-sensitive materials, the humidity sensitivity of our sensor sample can reach −286 pm/%RH. In order to address the temperature and humidity crosstalk and achieve a dual-parameter measurement, we cascaded a humidity-insensitive FBG. In addition, the sensor has a good humidity stability and a response time of 0.26 s, which shows its potential in fields such as medical respiratory dynamic monitoring. Full article

Due to their self-adaptability, low friction, low loss, and high-speed stability, bump foil aerodynamic journal bearings are widely used in high-speed rotating equipment such as turbomachinery and flywheel energy storage. In the process of high-speed operation, the heat generated leads to changes in air parameters (such as viscosity, density, etc.), thus affecting the overall performance of air bearings. In this paper, combined with the compressible Reynolds equation, a fluid–solid coupling model was established to analyze the steady-state characteristics and key influencing factors of bearings. Through the energy equation, the air viscosity–temperature effect was considered, and different boundary conditions were set. The internal temperature distribution of the air bearing and the influence of the temperature on the bearing characteristics were systematically analyzed. It was found that the bearing capacity increased when the temperature was considered. In a certain range, with the increase in ambient temperature, the increase in bearing capacity is reduced. This paper provides a theoretical design basis for the design of high-stability bearings and promotes the design of next-generation air bearings with higher speed, lower loss, and stronger adaptability, which has very important theoretical and engineering significance. Full article

In alpine ecosystems, where low temperatures predominate, prostrate growth forms play a crucial role in thermal resistance by enabling thermal decoupling from ambient conditions, thereby creating a warmer microclimate. However, this strategy may be maladaptive during frequent heatwaves driven by climate change. This study combined microclimatic and plant characterization, infrared thermal imaging, and leaf photoinactivation to evaluate how thermal decoupling (TD) affects heat resistance (LT₅₀) in six alpine species from the Nevados de Chillán volcano complex in the Andes of south-central Chile. Results showed that plants’ temperatures increased with solar radiation, air, and soil temperatures, but decreased with increasing humidity. Most species exhibited negative TD, remaining 6.7 K cooler than the air temperature, with variation across species, time of day, and growth form; shorter, rounded plants showed stronger negative TD. Notably, despite negative TD, all species exhibited high heat resistance (Mean LT₅₀ = 46 °C), with LT₅₀ positively correlated with TD in shrubs. These findings highlight the intricate relationships between thermal decoupling, environmental factors, and plant traits in shaping heat resistance. This study provides insights into how alpine plants may respond to the increasing heat stress associated with climate change, emphasizing the adaptive significance of thermal decoupling in these environments. Full article

Rooftop photovoltaic (PV) panel systems have become a key component in green building design, driven by new building sustainability measures advocated worldwide. The shading generated by the rooftop PV panel arrays can impact their annual heating and cooling load, as well as their overall thermal performance. This paper presents a long-term experimental investigation into the changes in roof temperature caused by PV panels. The experiment was conducted over the course of a year, with measurements taken on four sample days each month. The study is based on measurements of the covered roof temperature, the uncovered roof temperature, PV surface temperature, ambient air temperature, as well as solar irradiation, wind speed, and rainfall. The results reveal that the annual energy savings (MJ/m²) in the cooling load due to the covered roof are about 26% higher than the energy loss from the heating load due to shading. The study shows that the effect of the rooftop PV panels on the house’s total heating and cooling load savings is between 5.3 to 6.1%. This difference is significant in thermal performance analyses, especially if most of the roof is covered by PV panels. Full article

The critical consequence of climate change resulting from global warming is the increase in temperature. In combined cycle power plants (CCPPs), the Electric Power Output (PE) is affected by changes in both Ambient Temperature (AT) and Sea Surface Temperature (SST), particularly in plants utilizing seawater cooling systems. As AT increases, air density decreases, leading to a reduction in the mass of air absorbed by the gas turbine. This change alters the fuel–air mixture in the combustion chamber, resulting in decreased turbine power. Similarly, as SST increases, cooling efficiency declines, causing a loss of vacuum in the condenser. A lower vacuum reduces the steam expansion ratio, thereby decreasing the Steam Turbine Power Output. In this study, the effects of increases in these two parameters (AT and SST) due to global warming on the PE of CCPPs are investigated using various regression analysis techniques, Artificial Neural Networks (ANNs) and a hybrid model. The target variables are condenser vacuum (V), Steam Turbine Power Output (ST Power Output), and PE. The relationship of V with three input variables—SST, AT, and ST Power Output—was examined. ST Power Output was analyzed with four input variables: V, SST, AT, and relative humidity (RH). PE was analyzed with five input variables: V, SST, AT, RH, and atmospheric pressure (AP) using regression methods on an hourly basis. These models were compared based on the Coefficient of Determination (R²), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Mean Square Error (MSE), and Root Mean Square Error (RMSE). The best results for V, ST Power Output, and PE were obtained using the hybrid (LightGBM + DNN) model, with MAE values of 0.00051, 1.0490, and 2.1942, respectively. As a result, a 1 °C increase in AT leads to a decrease of 4.04681 MWh in the total electricity production of the plant. Furthermore, it was determined that a 1 °C increase in SST leads to a vacuum loss of up to 0.001836 bar_a. Due to this vacuum loss, the steam turbine experiences a power loss of 0.6426 MWh. Considering other associated losses (such as generator efficiency loss due to cooling), the decreases in ST Power Output and PE are calculated as 0.7269 MWh and 0.7642 MWh, respectively. Consequently, the combined effect of a 1 °C increase in both AT and SST results in a 4.8110 MWh production loss in the CCPP. As a result of a 1 °C increase in both AT and SST due to global warming, if the lost energy is to be compensated by an average-efficiency natural gas power plant, an imported coal power plant, or a lignite power plant, then an additional 610 tCO₂e, 11,184 tCO₂e, and 19,913 tCO₂e of greenhouse gases, respectively, would be released into the atmosphere. Full article

This study focuses on the icing problem of electrified railway contact lines. Using computational fluid dynamic (CFD) numerical simulations, a three-dimensional mesh model of the CuAg0.1AC120 contact line was developed. This study reveals the effects of environmental factors such as droplet diameter, air–liquid water content (LWC), and ambient temperature on the icing morphology. The results show that the asymmetric cross-sectional structure of the contact line causes localized droplet accumulation in the groove areas, leading to distinctly non-uniform and directional ice formation. At high wind speeds, secondary icing is observed on the leeward side, where droplets are carried by bypass airflow—this phenomenon is not prominent in standard conductors. Additionally, the contact line exhibits a more sensitive response to temperature and air moisture content changes, suggesting that it is more suited to a localized anti-icing strategy. The numerical model developed in this study provides a theoretical foundation for predicting ice loads on complex section conductors and supports the design optimization and maintenance of high-speed railway catenary systems. Full article

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. Full article

Integrating green spaces into urban designs and planning for ecosystem services has become vital; however, in creating these spaces, the growth phase is often overlooked. This study provides insight into the changing energy and carbon dioxide (CO₂) fluxes in a developing forest, “The Forestias” project in Thailand. The eddy covariance technique was applied to determine real-time surface energies and CO₂ fluxes from December 2021 to September 2023. The results suggest that under fast growing conditions of the green areas, the diurnal latent energy flux corresponded with the area gained. This effect was supported by increasing evapotranspiration through the byproduct of canopy gas exchange. Consequently, the influence of green areas on lowering the average ambient temperature compared with the urban non-green surroundings was observed. In terms of CO₂ flux dynamics, the increasing efficacy of photosynthesis was parallel with the growing forest canopy. Changes in flux dynamics due to urban green areas show their potential as a mitigation tool for moderating ambient air temperatures. Moreover, they can serve as a carbon sink within tropical cities and provide a pivotal contribution in reaching carbon neutrality. Full article

The heat transfer coefficient, or the HTC, is an industry-standard indicator of building energy performance. It is predicated on an assumption that it is of a constant value, and several different methods have been developed to measure and calculate the HTC as a constant. Whilst there are limited variations in the results obtained from these different methods, none of these methods consider a possibility that the HTC could be dynamically variable. Our experimental work shows that the HTC is not a constant. The experimental evidence based on our environmental chambers, which contain detached houses and in which the ambient air temperature can be controlled between −24 °C and +51 °C, with additional relative humidity control and with weather rigs that can introduce solar radiation, rain, and snow, shows that the HTC is dynamically variable. The analysis of data from the fully instrumented and monitored houses in combination with calibrated simulation models and data processing scripts based on genetic algorithm optimization provide experimental evidence of the dynamic variability of the HTC. This research increases the understanding of buildings physics properties and has the potential to change the way the heat transfer coefficient is used in building performance analysis. Full article

The Thermoelectric Window Frame (TEWF) can be adjusted by regulating the operating current to achieve the desired indoor temperature. However, indoor and outdoor ambient disturbances are inevitable, causing indoor temperature fluctuations and preventing them from reaching the set point. To solve the problem, a model-based control method is proposed to maintain the indoor temperature at the set point in this work. This method relies on a computational model for determining the operating current and a transient model for tracking variations in indoor temperature. Experimental results under various working conditions validate the two models. Moreover, indoor interference (e.g., changes in set point or air leaks due to occupants’ behavior) and outdoor interference (e.g., changes in the outdoor temperature) are incorporated into stable-state experiments. When these interferences occur, new operating currents are calculated for the new working conditions and applied to the TEWF. The results show that the indoor temperature significantly deviates from the desired values if the operating currents are not adjusted when disturbances occur. However, the indoor temperature can reach the set point by regulating the new operating currents in time, even during disturbances. Full article

Inside a closed, thin-walled hollow cylinder, there is a solid state of phase change material (NePCM) that has been nano-enhanced. This NePCM is heated at its bottom, with nanoparticles (Al₂O₃) inserted and homogenized within the PCM (sodium acetate trihydrate, C₂H₃O₂Na) to create the NePCM. The hollow cylinder is thermally insulated from the outside ambient temperature, while the heat supplied is sufficient to cause a phase change. Once the entire NePCM has converted from a solid to a liquid due to heating, it is then cooled, and the thermal insulation is removed. The cylindrical liquefied NePCM bar is cooled in this manner. Thermal entropy, entransy dissipation rate, and bar efficiency during the heating and cooling of the NePCM bar were analyzed by changing variables. The volume fraction ratio of nanoparticles, inlet heat flux, and liquefied bar height were the variables considered. The results indicate a significant impact on the NePCM bar during liquefaction and convective cooling when the values of these variables are altered. For instance, with an increase in the volume fraction ratio from 3% to 9%, at a constant heat flux of 10⁴ Wm⁻² and a liquefied bar height of 0.02 m, the NePCM bar efficiency decreases to 99%. The thermal entropy from heat conduction through the liquefied NePCM bar is significantly lower compared to the thermal entropy from convective air cooling on its surface. The thermal entropy of the liquefied NePCM bar increases on average by 110% without any cooling. With a volume fraction ratio of 6%, there is an 80% increase in heat flux as the bar height increases to 0.02 m. Full article

The air we breathe contains contaminants such as particulate matter (PM), carbon dioxide (${\mathrm{CO}}_2$), nitrogen dioxide (${\mathrm{NO}}_2$), and nitric oxide (NO), which, when inhaled, bring about several changes in the autonomous responses of our body. Our previous work showed that we can use the human body as a sensor by making use of autonomous responses (or biometrics), such as changes in electrical activity in the brain, measured via electroencephalogram (EEG) and physiological changes, including skin temperature, galvanic skin response (GSR), and blood oxygen saturation (${\mathrm{SpO}}_2$). These biometrics can be used to estimate pollutants, in particularly ${\mathrm{PM}}_1$ and ${\mathrm{CO}}_2$, with high degree of accuracy using machine learning. Our previous work made use of the Welch method (WM) to obtain a power spectral density (PSD) from the time series of EEG data. In this study, we introduce a novel approach for obtaining a PSD from the EEG time series, developed by Astrapi, called the Astrapi Spectrum Analyzer (ASA). The physiological responses of a participant cycling outdoors were measured using a biometric suite, and ambient ${\mathrm{CO}}_2$, ${\mathrm{NO}}_2$, and NO were measured simultaneously. We combined physiological responses with the PSD from the EEG time series using both the WM and the ASA to estimate the inhaled concentrations of ${\mathrm{CO}}_2$, ${\mathrm{NO}}_2$, and NO. This work shows that the PSD obtained from the ASA, when combined with other physiological responses, provides much better results (RMSE = 9.28 ppm in an independent test set) in estimating inhaled ${\mathrm{CO}}_2$ compared to making use of the same physiological responses and the PSD obtained by the WM (RMSE = 17.55 ppm in an independent test set). Small improvements were also seen in the estimation of ${\mathrm{NO}}_2$ and NO when using physiological responses and the PSD from the ASA, which can be further confirmed with a large number of dataset. Full article

Forests play a crucial role in carbon cycling, contributing significantly to global carbon cycling and climate change mitigation, but their capture strength is sensitive to the climatic zone in which they operate and its adjoining environmental stressors. This research investigated the carbon dynamics of a typical deciduous forest, the Daniel Boone National Forest (DBNF), in the Mixed-Humid climate of Kentucky, USA, employing the Eddy Covariance technique to quantify temporal CO₂ exchanges from 2016 to 2020 and to assess its controlling biometeorological factors. The study revealed that the DBNF functioned as a carbon sink, sequestering −1515 g C m⁻² in the study period, with a mean annual Net Ecosystem Exchange (NEE) of −303 g C m⁻²yr⁻¹. It exhibited distinct seasonal and daily patterns influenced by ambient sunlight and air temperature. Winter months had the lowest rate of CO₂ uptake (0.0699 g C m⁻² h⁻¹), while summer was the most productive (−0.214 g C m⁻² h⁻¹). Diurnally, carbon uptake peaked past midday and remained a sink overnight, albeit negligibly so. Light and temperature response curves revealed their controlling effect on the DBNF trees’ photosynthesis and respiration. Furthermore, clear seasonality patterns were observed in the control of environmental variables. The DBNF is a carbon sink consistent with other North American deciduous forests. Full article

Ambient air pollution is the most important environmental factor impacting human health. Urban landscapes present unique air quality challenges, which are compounded by climate change adaptation challenges, as air pollutants can also be affected by the urban heat island effect, amplifying the deleterious effects on health. Nature-based solutions have shown potential for alleviating environmental stressors, including air pollution and heat wave abatement. However, such solutions must be designed in order to maximize mitigation and not inadvertently increase pollutant exposure. This study aims to demonstrate potential applications of nature-based solutions in urban environments for climate stressors and air pollution mitigation by analyzing two distinct scenarios with and without green infrastructure. Utilizing low-cost sensors, we examine the relationship between green infrastructure and a series of environmental parameters. While previous studies have investigated green infrastructure and air quality mitigation, our study employs low-cost sensors in tropical urban environments. Through this novel approach, we are able to obtain highly localized data that demonstrates this mitigating relationship. In this study, as a part of the NERC-FAPESP-funded GreenCities project, four low-cost sensors were validated through laboratory testing and then deployed in two locations in São Paulo, Brazil: one large, heavily forested park (CIENTEC) and one small park surrounded by densely built areas (FSP). At each site, one sensor was located in a vegetated area (Park sensor) and one near the roadside (Road sensor). The locations selected allow for a comparison of built versus green and blue areas. Lidar data were used to characterize the profile of each site based on surrounding vegetation and building area. Distance and class of the closest roadways were also measured for each sensor location. These profiles are analyzed against the data obtained through the low-cost sensors, considering both meteorological (temperature, humidity and pressure) and particulate matter (PM₁, PM_2.5 and PM₁₀) parameters. Particulate matter concentrations were lower for the sensors located within the forest site. At both sites, the road sensors showed higher concentrations during the daytime period. These results further reinforce the capabilities of green–blue–gray infrastructure (GBGI) tools to reduce exposure to air pollution and climate stressors, while also showing the importance of their design to ensure maximum benefits. The findings can inform decision-makers in designing more resilient cities, especially in low-and middle-income settings. Full article