Hasil untuk "Heating and ventilation. Air conditioning"

Chuan-Chi Lai, Chi Jai Choy

In the era of 6G Air-Ground Integrated Networks (AGINs), Unmanned Aerial Vehicles (UAVs) are pivotal for providing on-demand wireless coverage in mission-critical environments, such as post-disaster rescue operations. However, traditional Deep Reinforcement Learning (DRL) approaches for multi-UAV orchestration often face critical challenges: instability due to the non-stationarity of multi-agent environments and the difficulty of balancing energy efficiency with service equity. To address these issues, this paper proposes ORCHID (Orchestration of Resilient Coverage via Hybrid Intelligent Deployment), a novel stability-enhanced two-stage learning framework. First, ORCHID leverages a GBS-aware topology partitioning strategy to mitigate the exploration cold-start problem. Second, we introduce a Reset-and-Finetune (R\&F) mechanism within the MAPPO architecture that stabilizes the learning process via synchronized learning rate decay and optimizer state resetting. This mechanism effectively suppresses gradient variance to prevent policy degradation, thereby ensuring algorithmic resilience in dynamic environments. Furthermore, we uncover a counter-intuitive efficiency-fairness synergy: contrary to the conventional trade-off, our results demonstrate that the proposed Max-Min Fairness (MMF) design not only guarantees service for cell-edge users but also achieves superior energy efficiency compared to Proportional Fairness (PF), which tends to converge to suboptimal greedy equilibria. Extensive experiments confirm that ORCHID occupies a superior Pareto-dominant position compared to state-of-the-art baselines, ensuring robust convergence and resilient connectivity in mission-critical scenarios.

Ehsan Mousavi, Arup Bhattacharya, Fred Betz et al.

Ventilation performance has historically been assessed using diverse metrics, ranging from air change rates and contaminant concentrations to occupant perception. This paper traces the evolution of these performance measures across research and practice, highlighting the progression from simple ventilation rate benchmarks to more sophisticated indicators like contaminant removal effectiveness (CRE), air exchange effectiveness (AEE), and age of air. The limitations of conventional metrics—particularly their inability to capture spatial variability, energy implications, and real-time contaminant removal—are critically examined. In addition, the historical evolution of these metrics and the rationale for their adoption is studied, specifically in the context of building codes and standards in the United States. A framework is proposed to categorize performance measures into ventilation rate-based, contaminant-based, air distribution-based, and perception-based groups, facilitating their comparison and selection. This critical review aims to support the development of more effective and context-sensitive ventilation assessment strategies, with implications for future research and building standards.

Erkin Atay Toka, Baris Kuseyri, Firuzi Keyvan

Olusegun Oguntona

The escalating demand for sustainable development in the built environment necessitates the integration of innovative, system-based assessment tools. This study investigates the role of energy efficiency (EE) within a nature-inspired sustainability assessment framework, drawing from biomimicry principles to evaluate green building practices in South Africa. Grounded in the ethos of nature’s efficiency, such as closed-loop energy systems, passive energy use, efficiency through form and function, and decentralised and localised energy generation, this study identifies and prioritises key EE criteria, including efficient energy management, renewable energy optimisation, passive heating, ventilation and air conditioning (HVAC) systems, and energy-saving technologies. Using the Analytic Hierarchy Process (AHP), this research engaged 38 highly experienced, practising, and registered construction professionals to perform pairwise comparisons of EE criteria. Results revealed that efficient energy management (29.8%) emerged as the most significant factor, followed closely by energy-saving equipment (26.4%), with strong expert consensus (consistency ratio = 0.03). The findings reflect a convergence of ecological wisdom and industry expertise, suggesting that nature’s design strategies offer a compelling roadmap for achieving sustainable energy performance in buildings. This study reinforces the applicability of biomimicry in shaping context-specific sustainability metrics and informs the development of adaptive, ecologically aligned certification frameworks. This study recommends the integration of these EE criteria into building rating systems, fostering interdisciplinary collaboration, and scaling nature-based frameworks to inform global sustainability practice. By bridging theory and application, this study advances a regenerative approach to construction that aligns with the UN Sustainable Development Goals and long-term environmental resilience.

Sun Yanjun, Zheng Haiqi, Wang Shibiao et al.

In this work, absorption refrigerant working pairs consisting of four HFO refrigerants, R1234ze(E), R1234yf, R1233zd, and R1243zf, and ionic liquids were studied. The different ionic liquids contained 20 cations and 16 anions. The Henry′s law constant and solubility data of working pairs were simulated by the COSMO-RS method. The differences in Henry′s law constant and solubility between the different working pairs are discussed from the perspective of polarized charge density on the molecular surface. The polarized surface charge density curve of the R1234ze(E) refrigerant has a peak in the negative region. It is compatible with anions with a peak in the positive region. However, the compatibility with the peak in the negative region is poor. Ionic liquids with low Henry′s law constants and high solubilities were screened out when they were paired with HFO refrigerants.

Prasenjit Karmakar, Swadhin Pradhan, Sandip Chakraborty

Changing public perceptions and government regulations have led to the widespread use of low-cost air quality monitors in modern indoor spaces. Typically, these monitors detect air pollutants to augment the end user's understanding of her indoor environment. Studies have shown that having access to one's air quality context reinforces the user's urge to take necessary actions to improve the air over time. Thus, user's activities significantly influence the indoor air quality. Such correlation can be exploited to get hold of sensitive indoor activities from the side-channel air quality fluctuations. This study explores the odds of identifying eight indoor activities (i.e., enter, exit, fan on, fan off, AC on, AC off, gathering, eating) in a research lab with an in-house low-cost air quality monitoring platform named DALTON. Our extensive data collection and analysis over three months shows 97.7% classification accuracy in our dataset.

Prasad Sonar, Hiroaki Katsuragi

Craters form as the lander's exhaust interacts with the planetary surfaces. Understanding this phenomenon is imperative to ensure safe landings. We investigate crater morphology, where a turbulent air jet impinges on the granular surfaces. To reveal the fundamental aspect of this phenomenon, systematic experiments are performed with various air jet velocities, nozzle positions, and grain properties. The resultant crater morphology is characterized by an aspect ratio. We find a universal scaling law in which the aspect ratio is scaled by the dimensionless variable consisting of air velocity at the nozzle, speed of sound in air, nozzle diameter, nozzle tip distance from the surface, grain diameter, the density of grains, and density of air. The obtained scaling reveals the crossover of the length scales governing crater aspect ratio, providing a useful guideline for ensuring safe landings. Moreover, we report a novel drop shaped subsurface cratering phenomenon.

S.Y. Chair, S.T. Ng, C.Y.H. Chao et al.

Li Guang, Zhuang Dawei, Xie Liyi et al.

R32 is widely used in room air-conditioners, with heat-transfer characteristics affected by the intermiscibility of the oil. Therefore, it is necessary to determine the optimal intermiscibility of the oil to improve heat transfer characteristics. This study investigated the influence of stratification, caused by the intermiscibility of the R32-oil mixture, on the heat transfer characteristics. The flow boiling heat transfer coefficient and pressure drop of a completely miscible R32-oil mixture, a partially miscible R32-oil mixture, and a completely immiscible R32-oil mixture were tested experimentally. To cover the working conditions of air conditioners and reflect the different intermiscibilities of the R32-oil mixtures, the test conditions included evaporating temperatures from -5 ℃ to 15 ℃, vapor quality from 0.2 to 0.7, and averaged oil concentrations of 1% and 5%. The results showed that partially miscible oil had the highest heat transfer coefficient and the lowest pressure drop; at an evaporating temperature of 5 ℃, vapor quality of 0.7, and averaged oil concentration of 5%, the advantage of a partially miscible R32-oil mixture over that of the completely miscible and completely immiscible mixtures increased. The maximum increases in heat transfer coefficient were 36.8% and 357.8%, and the maximum decreases in pressure drop were 9.0% and 58.2%, respectively. Among the three types of oils, the partially miscible oil exhibited the best heat transfer and pressure drop characteristics and thus has the best application prospects.

S. M. Pershin, V. A. Zavozin, M. Ya. Grishin. et al.

Low concentrations aerosols quantification is rather challenging for LIDAR instruments due to eye-safety restrictions so high energy pulses cannot be utilized to improve the sensitivity. Highly sensitive but eye-save LIDAR has been developed for the quantification of the water droplet aerosol which was induced by air ions. Few days sensing of aerosols in closed tunnel revealed a strong correlation between air optical transparency (LIDAR measurements) and concentrations of positive/negative ions (ion counter Sapphir 3-M). The correlation coefficient was observed to be almost unity for the air transparency signal and air ions unipolarity coefficient. High sensitivity of the water droplet aerosol quantification makes the developed eye-safe LIDAR a perspective instrument for space resolved measurements of the air ions distribution. Space and time resolved measurements of air ions exhalation can be a new instrument for tectonic activity study including new earthquake forecasting indicators search.

Alessandro Fassò, Jacopo Rodeschini, Alessandro Fusta Moro et al.

The air in the Lombardy region, Italy, is one of the most polluted in Europe because of limited air circulation and high emission levels. There is a large scientific consensus that the agricultural sector has a significant impact on air quality. To support studies quantifying the role of the agricultural and livestock sectors on the Lombardy air quality, this paper presents a harmonised dataset containing daily values of air quality, weather, emissions, livestock, and land and soil use in the years 2016 - 2021, for the Lombardy region. The pollutant data come from the European Environmental Agency and the Lombardy Regional Environment Protection Agency, weather and emissions data from the European Copernicus programme, livestock data from the Italian zootechnical registry, and land and soil use data from the CORINE Land Cover project. The resulting dataset is designed to be used as is by those using air quality data for research.

Dhanalakshmi M, Radha V

Air pollution is a vital issue emerging from the uncontrolled utilization of traditional energy sources as far as developing countries are concerned. Hence, ingenious air pollution forecasting methods are indispensable to minimize the risk. To that end, this paper proposes an Internet of Things (IoT) enabled system for monitoring and controlling air pollution in the cloud computing environment. A method called Linear Regression and Multiclass Support Vector (LR-MSV) IoT-based Air Pollution Forecast is proposed to monitor the air quality data and the air quality index measurement to pave the way for controlling effectively. Extensive experiments carried out on the air quality data in the India dataset have revealed the outstanding performance of the proposed LR-MSV method when benchmarked with well-established state-of-the-art methods. The results obtained by the LR-MSV method witness a significant increase in air pollution forecasting accuracy by reducing the air pollution forecasting time and error rate compared with the results produced by the other state-of-the-art methods

Tian Shen, Ma Cuiling, Chen Yuhong et al.

To strengthen the heat transfer of a phase change cold storage panel to match the variable cooling demand of refrigerated transportation, this study proposes a type of phase change cold storage panel with embedded heat pipes to quickly balance the heat load fluctuation in the logistics process. The discharging performance of the heat pipe evaporation section under a high heat load is experimentally studied. A dynamic analytical model is developed for the cooling process based on the thermal resistance analysis method. The results show that under the condition of a high heat load, the dynamic characteristics of the heat transfer process for the heat pipe side are observed. Under a 50 ℃ working condition, the highest average heat transfer rate reaches 42.50 W. The temperature difference and heat transfer rate at the airside calculated by the model are consistent with the measured data. The calculation error of the overall cooling capacity is -3.21%–6.16%. The model is used to simulate and analyze the cold storage panel. In the simulation cases, the average heat transfer rate reaches 88.72 W with four heat pipe rows and a 16 mm tube diameter. The average heat transfer rate reaches 112.54 W with an evaporation section length of 80 mm.

Andrea Bombarda, Silvia Bonfanti, Angelo Gargantini et al.

Rigorous development processes aim to be effective in developing critical systems, especially if failures can have catastrophic consequences for humans and the environment. Such processes generally rely on formal methods, which can guarantee, thanks to their mathematical foundation, model preciseness, and properties assurance. However, they are rarely adopted in practice. In this paper, we report our experience in using the Abstract State Machine formal method and the ASMETA framework in developing a prototype of the control software of the MVM (Mechanical Ventilator Milano), a mechanical lung ventilator that has been designed, successfully certified, and deployed during the COVID-19 pandemic. Due to time constraints and lack of skills, no formal method was applied for the MVM project. However, we here want to assess the feasibility of developing (part of) the ventilator by using a formal method-based approach. Our development process starts from a high-level formal specification of the system to describe the MVM main operation modes. Then, through a sequence of refined models, all the other requirements are captured, up to a level in which a C++ implementation of a prototype of the MVM controller is automatically generated from the model, and tested. Along the process, at each refinement level, different model validation and verification activities are performed, and each refined model is proved to be a correct refinement of the previous level. By means of the MVM case study, we evaluate the effectiveness and usability of our formal approach.

Jinghua Yu, Kangxin Leng, Biaobiao Wang

Zhao Jiapu, Ouyang Xingping, Bai Hua et al.

The heat transfer performance of two types of doubly enhanced tubes was experimentally studied using R245fa after the horizontal single-tube falling film evaporating test bench was built. The Wilson–Gnielinski graphic method was proposed to obtain the surface heat transfer coefficient of the tubes. The effect of the wall structure on the heat transfer performance was analyzed. The heat transfer correlations inside and outside the tubes were provided, and a fitting optimization scheme was proposed. The results showed that the enhancement rates of in-tube and out-tube heat transfer of the Y tube were 2.12–2.94 and 2.27–5.54, respectively. The internal and external enhancement rates of the T tube were 2.48–2.98 and 2.58–3.00, respectively. The out-tube heat transfer performance of the Y tube and the in-tube heat transfer performance of T tube were better. The heat transfer performance of the Y tube can be reinforced by optimizing its in-tube structure. The best spraying density of the Y tube [0.14–0.18 kg/(m?s)] was higher than that of the T tube [approximately 0.10 kg/(m?s)]. The surface heat transfer coefficient of the two tubes first increased and then decreased with the increase in the heat flux. However, the surface heat transfer coefficient of the Y tube changed more rapidly, which indicated that the thermosyphon boiling phenomenon caused by the smaller fin pitch of the Y tube accelerated the evaporation of refrigerant. The surface heat transfer coefficient of the two tubes increased with the increase in the evaporation temperature.

K. Shinozaki, M. Bertaina, F. Bisconti et al.

EUSO-SPB1 was a balloon-borne pathfinder mission of the JEM-EUSO (Joint Experiment Missions for the Extreme Universe Space Observatory) program. A 12-day long flight started from New Zealand on April 25th, 2017 on-board the NASA's Super Pressure Balloon. With capability of detecting EeV energy air showers, the data acquisition was performed using a 1 m^2 two-Fresnel-lens UV-sensitive telescope with fast readout electronics in the air shower detection mode over ~30 hours at ~16--30 km above South Pacific. Using a variety of approaches, we searched for air shower events. Up to now, no air shower events have been identified. The effective exposure, regarding the role of the clouds in particular, was estimated based on the air shower and detector simulations together with a numerical weather forecast model. Compared with the case assuming the fully clear atmosphere conditions, more than ~60% of showers are detectable regardless the presence of the clouds. The studies in the present work will be applied in the follow-up pathfinders and in the future full-scale missions in the JEM-EUSO program.

Juan M. Restrepo, Alex Ayet, Luigi Cavaleri

We propose a mechanism for the damping of short ocean gravity waves during rainstorms associated with the injection of air bubbles by rain drops. The mechanism is proposed as one of the possible explanations that ascribe to rain a calming effect on ocean surface waves. A model is developed that shows how wave attenuation increases with the presence of air bubbles in the upper reaches of the ocean. The model makes predictions of the effective wave dissipation coefficient, as a function of the volumetric ratio of air to water, as well as to the rainfall rate. The model predicts dissipation rates that are in line with experimental estimates of the effective wave damping rate.

Shengdong Du, Tianrui Li, Yan Yang et al.

Air quality forecasting has been regarded as the key problem of air pollution early warning and control management. In this paper, we propose a novel deep learning model for air quality (mainly PM2.5) forecasting, which learns the spatial-temporal correlation features and interdependence of multivariate air quality related time series data by hybrid deep learning architecture. Due to the nonlinear and dynamic characteristics of multivariate air quality time series data, the base modules of our model include one-dimensional Convolutional Neural Networks (1D-CNNs) and Bi-directional Long Short-term Memory networks (Bi-LSTM). The former is to extract the local trend features and spatial correlation features, and the latter is to learn spatial-temporal dependencies. Then we design a jointly hybrid deep learning framework based on one-dimensional CNNs and Bi-LSTM for shared representation features learning of multivariate air quality related time series data. We conduct extensive experimental evaluations using two real-world datasets, and the results show that our model is capable of dealing with PM2.5 air pollution forecasting with satisfied accuracy.

Deng Cong, Luo Xiaoping, Feng Zhenfei et al.

To investigate the characteristics of flow boiling and heat transfer in microchannels, experiments was carried in rectangular microchannels using refrigerant R22 as working fluid, and visualization experiment was performed using high speed camera. The results show that: heat transfer coefficient is barely influenced by the mass flow rate, but it increases rapidly along with the increment of the heat flux. The smaller the size of microchannels, the better heat transfer effects. Under the same condition of heat flux and mass flow rate, the values of heat transfer coefficient in 0.92 mm and 1.33 mm microchannels increase by 25% and 12% respectively compared to that of 2 mm. A new correlation based on the models of Oh H K et al [15] and Yun R et al [7] is shown to provide very good predictions, evidenced by an overall MAE of 8.8%. Wavy vapor layer was observed under the critical heat flux in visualization experiment.