Search Results (21)

Diesel engines power much of the heavy-duty equipment used in underground mines, where exhaust emissions pose acute environmental and occupational health challenges. However, predicting the amount of air required to dilute these emissions is difficult because exhaust mass flow and pollutant concentrations vary nonlinearly with multiple operating parameters. We apply deep learning to predict the total exhaust mass flow and carbon monoxide (CO) concentration of a six-cylinder gas–diesel (dual-fuel) turbocharged KAMAZ 910.12-450 engine under controlled operating conditions. We trained artificial neural networks on the preprocessed experimental dataset to capture nonlinear relationships between engine inputs and exhaust responses. Model interpretation with Shapley additive explanations (SHAP) identifies torque, speed, and boost pressure as dominant drivers of exhaust mass flow, and catalyst pressure, EGR rate, and boost pressure as primary contributors to CO concentration. In addition, symbolic regression yields an interpretable analytical expression for exhaust mass flow, facilitating interpretation and potential integration into control. The results indicate that deep learning enables accurate and interpretable prediction of key exhaust parameters in dual-fuel engines, supporting emission assessment and mitigation strategies relevant to underground mining operations. These findings support future integration with ventilation models and real-time monitoring frameworks. 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

Mechanical ventilation is indispensable for patients with severe respiratory conditions, and high-fidelity lung simulators play a pivotal role in ventilator testing, clinical training, and respiratory research. However, most existing simulators are passive, single-lung models with limited and discrete control over respiratory mechanics, which constrains their ability to reproduce realistic breathing dynamics. To overcome these limitations, this study presents a dual-chamber lung simulator that can operate in both active and passive modes. The system integrates a sliding mode controller enhanced by a linear extended state observer, enabling the accurate replication of complex respiratory patterns. In active mode, the simulator allows for the precise tuning of respiratory muscle force profiles, lung compliance, and airway resistance to generate physiologically accurate flow and pressure waveforms. Notably, it can effectively simulate pathological conditions such as acute respiratory distress syndrome (ARDS) and chronic obstructive pulmonary disease (COPD) by adjusting key parameters to mimic the characteristic respiratory mechanics of these disorders. Experimental results show that the absolute flow error remains within ±3 L/min, and the response time is under 200 ms, ensuring rapid and reliable performance. In passive mode, the simulator emulates ventilator-dependent conditions, providing continuous adjustability of lung compliance from 30 to 100 mL/${\mathrm{cmH}}_2$O and airway resistance from 2.01 to 14.67$\sqrt{{\mathrm{cmH}}_2\mathrm{O}}/(\mathrm{L}/\mathrm{s})$, with compliance deviations limited to ±5%. This design facilitates fine, continuous modulation of key respiratory parameters, making the system well-suited for evaluating ventilator performance, conducting human–machine interaction studies, and simulating pathological respiratory states. Full article

Integrating renewable energy, particularly wind power, into modern power systems introduces challenges concerning stability and reliability. These issues require enhanced regulation to balance power supply with load demand. Flexible loads and energy storage provide viable solutions to stabilize the grid without relying on new resources. This paper proposes building thermostatically controlled loads (BTLs), such as heating, ventilation, and air conditioning (HVAC) systems, as flexible demand-side management tools to address the challenges of intermittent energy sources. A new concept is introduced, portraying BTLs as a stochastic battery with losses, offering a compact representation of their dynamics. BTLs’ thermal characteristics, user-defined set points, and ambient temperature changes determine the power limits and energy capacity of this stochastic battery. The model is simulated using DIgSILENT Power Factory, which includes thermal power plants, gas turbines, wind power plants, and BTLs. A dynamic dispatch strategy optimizes power generation while utilizing BTLs to balance grid fluctuations caused by variable wind energy. Performance analysis shows that integrating BTLs with conventional thermal plants can reduce variability and improve grid stability. The study highlights the dual role of simulating overall flexibility and applying dynamic dispatch strategies to enhance power systems with high renewable energy integration. Full article

Unveiling temperature patterns within agricultural products remains the most important indicator for their quality assessment during post-harvest treatments. Temperature control and monitoring within vented packages is essential for preserving the quality of perishable goods, such as tomato fruits, by preventing localized temperature maxima that can accelerate spoilage. This study proposes a modeling and simulation approach to systematically investigate how ventilation design choices influence internal airflow distribution and the resulting cooling performance. Our analysis compares three distinct venting configurations (single top vent, single middle vent, and two vents) across two package boundary conditions: an open-top system allowing for dual air exits through the open top boundary and the outlet vent(s), respectively, and a closed-top system with a single exit pathway through the outlet vent(s). All scenarios are simulated to assess airflow patterns, velocity magnitudes, and temperature uniformity within different package designs. Full article

This study established a numerical model for ammonia leakage and diffusion in confined ship engine room spaces and validated its effectiveness through existing experiments. The research revealed the evolution patterns of ammonia cloud dispersion under various working conditions. Multi-parameter coupling analysis demonstrated that the combined effect of leakage source location and obstacle distribution alters the spatial configuration of gas clouds. When leakage jets directly impact obstacles, the resulting vortex structures maximize the coverage area of high-concentration ammonia near the ground. Ventilation system efficiency shows a significant negative correlation with hazardous zone volume. The hazardous zone volume was reduced by 50% when employing a bottom dual-side air intake combined with a top symmetric exhaust scheme, compared to the bottom single-side intake with an opposite-side top exhaust configuration. By enhancing the synergistic effect between longitudinal convection and top suction, harmful gas accumulation in lower spaces was effectively controlled. These findings not only provide a theoretical basis for ventilation system design in ammonia-fueled ships but also offer practical applications for risk prevention and control of maritime ammonia leakage. Full article

Veno-venous extracorporeal membrane oxygenation (vvECMO) is a life-saving intervention for severe respiratory failure unresponsive to conventional therapies. However, managing refractory hypoxemia in morbidly obese patients poses significant challenges due to the unique physiological characteristics of this population, including hyperdynamic circulation, elevated cardiac output, and increased oxygen consumption. These factors can limit the effectiveness of vvECMO by diluting arterial oxygen content and complicating oxygen delivery. Refractory hypoxemia in obese patients supported by vvECMO often stems from an imbalance between ECMO blood flow and cardiac output. Hyperdynamic circulation exacerbates the recirculation of oxygenated blood and impairs the efficiency of oxygen transfer. To address these challenges, a stepwise, individualized approach is essential. Strategies to reduce oxygen consumption include deep sedation, neuromuscular blockade, and temperature control. Cardiac output modulation can be achieved through beta-blockers and cautious therapeutic hypothermia. Optimizing oxygen delivery involves improving residual lung function; high positive end-expiratory pressure ventilation guided by esophageal pressure monitoring; prone positioning; and adjustments to the ECMO circuit, such as using dual oxygenators, larger membranes, or additional drainage cannulas. This review highlights the interplay of physiological adaptations and technical innovations required to overcome the challenges of managing refractory hypoxemia in obese patients during vvECMO. By addressing the complexities of high cardiac output and obesity, clinicians can enhance the effectiveness of vvECMO and improve outcomes for this high-risk population. Full article

A dangerous infection contracted in hospitals, ventilator-associated pneumonia is frequently caused by bacteria that are resistant to several drugs. It is one of the main reasons why patients in intensive care units become ill or die. This research aimed to determine the most effective empirical therapy of antibiotics for better ventilator-associated pneumonia control and to improve patient outcomes by using the minimal inhibitory concentration method and the Ameri–Ziaei double antibiotic synergism test and by observing the clinical responses to both single and combination therapies. Patients between the ages of one month and twelve who had been diagnosed with ventilator-associated pneumonia and had been on mechanical ventilation for more than 48 h were included in the study, which was carried out in the Pediatric Intensive Care Unit at Cairo University’s Hospital. When ventilator-associated pneumonia is suspected, it is critical to start appropriate antibiotic therapy as soon as possible. This is especially important in cases where multidrug-resistant Gram-negative infections may develop. Although using Polymyxins alone or in combination is effective, it is important to closely monitor their administration to prevent resistance from increasing. The combination therapy that showed the greatest improvement was a mix of aminoglycosides, quinolones, and β-lactams. A combination of aminoglycosides and dual β-lactams came next. Although the optimal duration of antibiotic treatment for ventilator-associated pneumonia is still unknown, treatments longer than seven days are usually required to eradicate MDR P. aeruginosa or A. baumannii completely. Full article

Inner Mongolia has the largest sheep population among China’s provinces, resulting in the production of a substantial amount of sheep manure. If left untreated, this manure can contribute to environmental pollution. However, sheep manure serves a dual purpose: it can be both a pollutant and a valuable source of organic fertilizer. Consequently, there is an urgent need to address the environmental issues arising from manure accumulation and its unused status. In this paper, a viable solution is proposed: the conversion of manure into fertilizer through a composting unit incorporating high-temperature aerobic fermentation technology. This unit, tailored for small farms and individual farmers, integrates critical functions such as ventilation, heating, and turning. Additionally, it boasts excellent thermal insulation, enhancing composting efficiency and enabling precise control over fermentation conditions. This design mitigates heat loss and accelerates maturation, addressing common challenges in traditional composting. The design process encompassed both equipment construction and control systems, with a primary focus on compost fermentation and aeration heating. The components were carefully designed or selected based on theoretical analysis and subsequently validated using simulation software, including EDEM and Fluent. The control system seamlessly integrates a touch screen interface, PLC programming, and control circuits to manage air pumps and electric heaters in response to changes in temperature and oxygen concentration. Furthermore, it controls the motors during the recovery phase. A comprehensive performance evaluation was conducted, revealing notable improvements. Under artificially heated conditions, the maximum temperature of the compost increased by approximately 20 °C, the composting cycle was reduced by roughly 4 days, and the seed germination index (GI) rose by about 9% when compared to natural fermentation. Thus, this device significantly accelerates composting and improves fertilizer quality by increasing the decomposition rate. Full article

Demand response (DR) enhances building energy flexibility, but its application in hybrid heating systems with dynamic pricings remains underexplored. This study applied DR via heating setpoint adjustments based on dynamic electricity and district heating (DH) prices to a building heated by a hybrid ground source heat pump (GSHP) system coupled to a DH network. A cost-effective control was implemented to optimize the usage of GSHP and DH with power limitations. Additionally, four DR control algorithms, including two single-price algorithms based on electricity and DH prices and two dual-price algorithms using minimum heating price and price signal summation methods, were tested for space heating under different marginal values. The impact of DR on ventilation heating was also evaluated. The results showed that applying the proposed DR algorithms to space heating improved electricity and DH flexibilities without compromising indoor comfort. A higher marginal value reduced the energy flexibility but increased cost savings. The dual price DR control algorithm using the price signal summation method achieved the highest cost savings. When combined with a cost-effective control strategy and power limitations, it reduced annual energy costs by up to 10.8%. However, applying the same DR to both space and ventilation heating reduced cost savings and significantly increased discomfort time. Full article

In sustainable city development, urban form plays an important role in block energy consumption, and as different environmental contexts and block functions create differences in energy use, it is necessary to study the relationship between morphology and energy consumption under the dual constraints of special environments and special block functions. Urban high-density blocks have concentrated energy consumption, high energy intensity, and complex morphological layout, but the influencing mechanism of the block’s morphology on its energy consumption remains unclear. Accordingly, this study focuses on the mechanism and evaluation method of the influence of morphology on the energy consumption of high-density commercial blocks in severe cold regions. Through Grasshopper model extraction, EnergyPlus performance simulation, Pearson correlation analysis, and linear regression analysis, this study extracts and classifies high-density commercial blocks in Harbin, China, into six basic layout types (Courtyard, Courtyard-T, Slab, Slab-T, Point, Point-T) according to their horizontal and vertical morphology, analyzes the energy consumption characteristics of each basic type, examines the relationships between energy use intensity (EUI) and building density (BD) and between floor area ratio (FAR) and building height standard deviation (BHSD), and constructs theoretical models by controlling variables to study the effect of a single form parameter on block EUI. The research findings are as follows: (1) The annual energy consumption of Point and Slab blocks is relatively low, whereas that of Courtyard and Courtyard-T blocks is higher due to the lack of open space in Courtyards and the poor ventilation in summer. (2) FAR is significantly correlated with the energy consumption of high-density commercial blocks in severe cold regions, while the effects of BD and BHSD are weaker than those of FAR. For every 0.1 increase in BD, every 1 increase in FAR, and every 1(m) increase in BHSD, the Winter Daily EUI of the Slab block changes by +0.87, −2.26, and −0.22 (kWh/m²), respectively, whereas that of the Slab-T block changes by −0.38, +0.68, and +0.08 (kWh/m²), respectively. (3) Controlling other variables, a large BD is theoretically beneficial to energy performance in the blocks, and increasing BD in the range of 0.4–0.55 has a significant effect on lowering energy consumption in Point blocks. EUI increases with the increase in FAR, while the change depends on different block types with the increase in BHSD. This study provides design strategies for high-density commercial blocks in severe cold regions. Under different layout types, though EUI shows different relationships with BD, FAR, and BHSD, Slab-T and Point-T blocks can achieve excellent energy performance by appropriately increasing BD and decreasing FAR, whereas Slab blocks need to decrease BD while increasing FAR. The patterns found in this paper can provide strategic help for policymaking and early urban design. Full article

Acoustic detection of machinery defaults from in-duct measurements is of practical importance in many areas, such as the health assessment of turbines in ventilation systems or engine testing in the surface and air transport sectors. This approach is, however, impeded by the low signal-to-noise ratio (SNR) observed in such environments. In this study, it is proposed to exploit the slow sound effect of Sonic Black Hole (SBH) ducted silencers to enhance the sensing of incident pulse acoustic signals with low SNR. It is found from transfer matrix and finite element modelling that fully opened SBH silencers with perforated skin interfaces are able to substantially enhance an incident pulse amplitude while channeling an air flow. We demonstrate that the graded depths of the SBH cavities provide rainbow spectral decomposition and amplification of the incident pulse frequency components, provided that impedance matching, slow sound, and critically coupled conditions are met. In-duct experiments showed the ability of a 3D printed SBH silencer to simultaneously enhance acoustic sensing and fully trap the pulse spectral components in the SBH cavities in the presence of a low-speed flow. This study opens up new avenues for the development of dual-purpose silencers designed for acoustic monitoring and noise control in duct systems without obstructing the air flow. Full article

Achieving the simultaneity of ventilation and soundproofing is a significant challenge in applied acoustics. Ventilated soundproofing relies on the interplay between local resonance and nonlocal coupling of acoustic waves within a sub-wavelength structure. However, previously studied structures possess limited types of fundamental resonators and lack modifications from the basic arrangement. These constraints often force the specified position of each attenuation peak and low absorption performance. Here, we suggest the in-duct-type sound barrier with dual Helmholtz resonators, which are positioned around the symmetry-breaking waveguides. The numerical simulations for curated dimensions and scattered fields show the aperiodic migrations and effective amplifications of the two absorptive domains. Collaborating with the subsequent reflective domains, the designed structure holds two effective attenuation bands under the first Fabry–Pérot resonance frequency. This study would serve as a valuable example for understanding the local and non-local behaviors of sub-wavelength resonating structures. Additionally, it could be applied in selective noise absorption and reflection more flexibly. Full article

Understanding the time–space coupling characteristics of the surrounding rock temperature field in high geothermal roadways is essential for controlling heat damage in mines. However, current research primarily focuses on individually analyzing the temperature changes in the surrounding rock of roadways, either over time or space. Therefore, the Gauss–Newton iteration method is employed to model the coupling relationship between temperature, time, and space. The results demonstrate that the dual coupling function describing the temperature field of the surrounding rock in both time and space provides a more comprehensive characterization of the temperature variations. Over time, as ventilation duration increases, the fitting degree of the characteristic curve steadily rises, and the characteristic curve descends overall. In the spatial dimension, the fitting degree of the characteristic curve gradually decreases with the rise of the dimensionless radius, and the characteristic curve ascends overall. Additionally, as thermal conductivity increases, the fitting degree of the characteristic curve steadily rises. Full article

Reinforcement learning (RL) is being gradually applied in the control of heating, ventilation and air-conditioning (HVAC) systems to learn the optimal control sequences for energy savings. However, due to the “trial and error” issue, the output sequences of RL may cause potential operational safety issues when RL is applied in real systems. To solve those problems, an RL algorithm with dual safety policies for energy savings in HVAC systems is proposed. In the proposed dual safety policies, the implicit safety policy is a part of the RL model, which integrates safety into the optimization target of RL, by adding penalties in reward for actions that exceed the safety constraints. In explicit safety policy, an online safety classifier is built to filter the actions outputted by RL; thus, only those actions that are classified as safe and have the highest benefits will be finally selected. In this way, the safety of controlled HVAC systems running with proposed RL algorithms can be effectively satisfied while reducing the energy consumptions. To verify the proposed algorithm, we implemented the control algorithm in a real existing commercial building. After a certain period of self-studying, the energy consumption of HVAC had been reduced by more than 15.02% compared to the proportional–integral–derivative (PID) control. Meanwhile, compared to the independent application of the RL algorithm without safety policy, the proportion of indoor temperature not meeting the demand is reduced by 25.06%. Full article