Search Results (5,187)

The novel engines nowadays with high efficiency are operated under the superpressure, supercritical, and supersonic extreme conditions that are situated in the broken reaction zone regime. In this article, the propagation and heat/radical diffusion physics of a high-pressure dimethyl ether (DME)/air turbulent lean-premixed flame are investigated numerically by direct numerical simulation (DNS). A wide range of statistical and diagnostic methods, including Lagrangian fluid tracking, Joint Probability Density Distribution (JPDF), and chemical explosive mode analysis (CEMA), are applied to reveal the local combustion modes and dynamics evolution, as well as the roles of heat/mass transport and cool/hot flame interaction in the turbulent combustion, which would be beneficial to the design of novel engines with high performances. It is found that the three-staged combustion, including cool-flame, warm-flame, and hot-flame fronts, is a unique behavior of DME flame under the elevated-pressure, lean-premixed condition. In the broken reaction zone regime, the reaction zone thickness increases remarkably, and the heat release rate (HRR) and fuel consumption rate in the cool-flame zone are increased by 16% and 19%, respectively. The diffusion effect not only enhances flame propagation, but also suppresses the local HRR or fuel consumption. The strong turbulence interplaying with diffusive transports is the underlying physics for the enhancements in cool- and hot-flame fronts. The dominating diffusive sub-processes are revealed by the aid of the diffusion index. Full article

The integration of small unmanned aircraft systems (sUASs) and electric vertical takeoff and landing (eVTOL) aircraft into urban airspace presents a new challenge in managing environmental noise, which is a critical factor for the public acceptance of urban air mobility (UAM). This survey investigates the noise characteristics of UAS and eVTOL platforms, particularly multi-rotor and distributed propulsion configurations, and examines whether the operational benefits of these vehicles outweigh their acoustic footprint in dense urban environments. While eVTOLs are often perceived as quieter than conventional helicopters due to the absence of combustion engines and mechanically simpler drivetrains, their dominant noise sources are aerodynamic in nature. These include blade vortex interactions, rotor loading noise, and broadband noise, which persist regardless of whether propulsion is electric or combustion-based. Recent studies suggest that community perception of drone noise is influenced more by tonal content, frequency, and modulation patterns than by absolute sound pressure levels. This paper presents a comprehensive review of state-of-the-art noise prediction tools, empirical measurement techniques, and mitigation strategies for sUAS operating in UAM scenarios. The discussion provided in this paper assists in vehicle design, certification standards, airspace planning, and regulatory frameworks focused on minimizing noise impact in urban settings. Full article

This study demonstrates that hydrogen enrichment in lean-burn spark-ignition engines can simultaneously improve three key performance metrics, thermal efficiency, combustion stability, and nitrogen oxide emissions, without requiring modifications to the engine hardware or ignition timing. This finding offers a novel control approach to a well-documented trade-off in existing research, where typically only two of these factors are improved at the expense of the third. Unlike previous studies, the present work achieves simultaneous improvement of all three metrics without hardware modification or ignition timing adjustment, relying solely on the optimization of the air–fuel equivalence ratio $\lambda$. Experiments were conducted on a six-cylinder engine for combined heat and power application, fueled with hydrogen–natural gas blends containing up to 30% hydrogen by volume. By optimizing only the air–fuel equivalence ratio, it was possible to extend the lean-burn limit from $\lambda \approx 1.6$ to $\lambda >1.9$, reduce nitrogen oxide emissions by up to 70%, enhance thermal efficiency by up to 2.2 percentage points, and significantly improve combustion stability, reducing cycle-by-cycle variationsfrom 2.1% to 0.7%. A defined $\lambda$ window was identified in which all three key performance indicators simultaneously meet or exceed the natural gas baseline. Within this window, balanced improvements in nitrogen oxide emissions, efficiency, and stability are achievable, although the individual maxima occur at different operating points. Cylinder pressure analysis confirmed that combustion dynamics can be realigned with original equipment manufacturer characteristics via mixture leaning alone, mitigating hydrogen-induced pressure increases to just 11% above the natural gas baseline. These results position hydrogen as a performance booster for natural gas engines in stationary applications, enabling cleaner, more efficient, and smoother operation without added system complexity. The key result is the identification of a $\lambda$ window that enables simultaneous optimization of nitrogen oxide emissions, efficiency, and combustion stability using only mixture control. Full article

Ventilation corridors can play an important role in removing harmful air pollution in cities; however, there are social pressures to use this corridor land for new buildings. The presented study employs RANS fluid flow simulations with the k-$ϵ$ turbulence model to investigate how the addition of buildings in the historical ventilation corridor impedes CO traced pollution removal. The urban complex situated near Raclawicka Street in Warsaw is selected as a case study for which two urban layouts dating from 2006 and 2017 are compared. The investigation includes varying ambient wind speeds and direction, with a prescribed CO-air mixture source representing a supply of road pollution. The results provide aerodynamic and dispersion characteristics and identify several generic trends indicating that the orthogonal urban layouts help to remove the pollution faster, especially when compared to courtyard building configurations, and that the introduction of occasional wide gaps between buildings can also speed up the pollution removal in the direction perpendicular to the gaps. Furthermore, for this urban complex the addition of new buildings had predominantly a local impact. The results showed that for light and mild winds, ambient speeds have little impact on dispersion patterns, but the effects of a dynamic ambient wind reversal are pronounced. Full article

As the importance of both indoor air quality (IAQ) and energy efficiency grows in residential buildings, the application of air filters in energy recovery ventilators has become essential. However, high-efficiency filters such as MERV 12 inevitably increase the pressure drop, adversely affecting the airflow, fan energy use, and heat exchange balance. This study quantitatively investigates how different levels of filter resistance—from clean conditions to 200% dust loading—affect system airflow, static pressure, exhaust air transfer, and power consumption. A standardized dust loading procedure was adopted to simulate long-term use conditions. The results show a 37% reduction in net supply airflow under heavily clogged filters, while the unit exhaust air transfer ratio increased from 7.2% to 17.7%, exceeding compliance limits. Surprisingly, electrical energy consumption decreased as the fan load dropped with the airflow. Despite an increase in the apparent heat exchange efficiency, this gain was driven by return air recirculation rather than true thermal effectiveness. These findings highlight the need for filter performance-based ERV certification and operational strategies that balance IAQ, energy use, and system compliance. Full article

Scramjet operation requires a comprehensive understanding of the internal flowfield, encompassing fuel–air mixing and combustion. This study investigates transient flow and flame development within a HIFiRE-2 scramjet engine combustor, which features two opposing cavities and dual sets of fuel injectors—the upstream (primary) and downstream (secondary) injectors. These cavities function as flameholders, creating circulating flows with elevated temperatures and pressures. Shock waves form both ahead of fuel plumes and at the diverging and converging sections of the flowpath. Special attention is given to the interactions among these shock waves and the shear layers along the supersonic core flow as the system progresses towards a quasi-steady state. Driven by increased backpressure, bow shocks and disturbances induced by the normal, secondary fuel injection and the inclined, primary fuel injection move upstream, amplifying the cavity pressure. These shocks generate adverse pressure gradients, causing near-wall flow separation adjacent to both injector sets, which enhances the penetration and dispersion of fuel plumes. Once a quasi-steady state is achieved, a feedback loop is established between dynamic wave motions and combustion processes, resulting in sustained entrainment of reactive mixtures into the cavities. This mechanism facilitates stable combustion in the cavities and near-wall separation zones. Full article

Onboard the MetOp satellite series, Infrared Atmospheric Sounding Interferometer (IASI) is a Fourier Transform spectrometer based on the Michelson interferometer. IASI acquires interferograms, which are processed to provide high-resolution atmospheric emission spectra. These spectra enable the derivation of temperature and humidity profiles, among other parameters, with exceptional spectral resolution. In this study, we evaluate a novel, rapid retrieval approach in the interferogram domain, aiming for near-real-time (NRT) analysis of large spectral datasets anticipated from next-generation tropospheric sounders, such as MTG-IRS. The Partially Sampled Interferogram (PSI) method, applied to trace gas retrievals from IASI, has been sparsely explored. However, previous studies suggest its potential for high-accuracy retrievals of specific gases, including CO, CO₂, CH₄, and N₂O at the resolution of a single IASI footprint. This article presents the results of a study based on retrieval in the interferogram domain. Furthermore, the optical pathway differences sensitive to the parameters of interest are studied. Interferograms are generated using a fast Fourier transform on synthetic IASI spectra. Finally, the relationship to the total column of carbon monoxide is explored using three different algorithms—from the most intuitive to a complex neural network approach. These algorithms serve as a proof of concept for interferogram classification and rapid predictions of surface temperature, as well as the abundances of H₂O and CO. IASI spectra simulations were performed using the LATMOS Atmospheric Retrieval Algorithm (LARA), a robust and validated radiative transfer model based on least squares estimation. The climatological library TIGR was employed to generate IASI interferograms from LARA spectra. TIGR includes 2311 atmospheric scenarios, each characterized by temperature, water vapor, and ozone concentration profiles across a pressure grid from the surface to the top of the atmosphere. Our study focuses on CO, a critical trace gas for understanding air quality and climate forcing, which displays a characteristic absorption pattern in the 2050–2350 ${\mathrm{cm}}^{-1}$ wavenumber range. Additionally, the study explores the potential of correlating interferogram characteristics with surface temperature and H₂O content, aiming to enhance the accuracy of CO column retrievals. Starting with intuitive retrieval algorithms, we progressively increased complexity, culminating in a neural network-based algorithm. The results of the NN study demonstrate the feasibility of fast interferogram-domain retrievals, paving the way for operational applications. Full article

The utilization of ammonia as a fuel for gas turbines involves practical challenges due to its low reactivity, narrow flammability limits, and slow laminar flame propagation. One of the potential solutions to enhance the combustion reactivity of ammonia is co-firing with syngas. This paper presents an experimental and numerical investigation of the laminar burning velocity (LBV) of ammonia/syngas/air mixtures under elevated pressures (up to 10 bar) and temperatures (up to 473 K). Experiments were conducted in a constant-volume combustion chamber with a total volume of 11 L equipped with a dual-electrode capacitive discharge ignition system. A systematic sensitivity analysis was conducted to experimentally evaluate the system performance under various syngas compositions and equivalence ratios from 0.7 to 1.6 and ultimately identify the factors with the most impact on the system. As a complement to the experiments, a detailed numerical simulation was carried out integrating available kinetic mechanisms—chemical reaction sets and their rates—to support advancements in the understanding and optimization of ammonia/syngas co-firing dynamics. The sensitivity analysis results reveal that LBV is significantly enhanced by increasing the hydrogen content (>50%). Furthermore, the LBV of the gas mixture is found to increase with the use of a rich flame, higher mole fractions of syngas, and higher initial temperatures. The results indicate that higher pressure reduces LBV by 40% but at the same time enhances the adiabatic flame temperature (by 100 K) due to an equilibrium shift. The analysis was also extended to quantify the impact of syngas mole fractions and elevated initial temperatures. The kinetics of the reactions are analyzed through the reaction pathways, and the results reveal how the preferred pathways vary under lean and rich flame conditions. These findings provide valid quantitative design data for optimizing the combustion kinetics of ammonia/syngas blends, offering valuable design data for ammonia-based combustion systems in industrial gas turbines and power generation applications, reducing NOₓ emissions by up to 30%, and guiding future research directions toward kinetic models and emission control strategies. Full article

This study investigates the operational behavior and voltage stability of a 1 kW-class AIP PEMFC stack under high-pressure H₂ and O₂ conditions. AIP PEMFCs, unlike conventional air-based systems, operate in enclosed environments using stored O₂, requiring designs that minimize parasitic power losses while ensuring stable operation. To establish a performance baseline, single cell tests were conducted to isolate the effects of in-plane components, including the MEA, GDL, and flow field geometry. Results indicated that temperature and pressure significantly influenced performance, whereas humidity and flow rate had minimal effects under the tested conditions. A 27-cell stack was then assembled and evaluated under various current densities, flow rates, and humidity levels. Time-resolved voltage measurements revealed that low flow rates (stoichiometry ≤ 1.5) led to voltage instability, particularly at high humidity and current density. Instability was more pronounced in cells positioned farthest from the inlet and outlet ports. These findings underscore the importance of optimizing operational parameters and stack architecture to achieve stable AIP PEMFC performance under reduced flow conditions. The results provide key insights for developing compact, efficient, and durable AIP fuel cell systems for use in enclosed or submerged environments such as submarines or unmanned underwater vehicles, while highlighting key challenges associated with AIP-targeted applications. Full article

Aerosol radiative forcing is known to significantly disturb the thermodynamic and dynamic structure of the Planetary Boundary Layer (PBL), particularly in heavily polluted urban regions. In this study, the effects of aerosol–PBL interactions were examined over a megacity in China’s Central Plains by comparing ERA5 reanalysis data with multi-source ground-based observations. Key meteorological variables—including wind speed, wind direction, temperature, and relative humidity—were analyzed across pressure levels from 1000 to 800 hPa. Good agreement in wind direction was observed between ERA5 and observations (R² > 0.84), while wind speed showed a moderate correlation (R² = 0.54–0.73) with an RMSE of 1.85 m/s near 975 hPa. Temperature discrepancies were found to decrease with altitude, with RMSE values reducing from 3.02 K to 1.84 K, indicating a modulation of thermal stratification by aerosol radiative effects. A stable structure was revealed by humidity analysis near the surface but increased variability aloft, with absolute differences reaching ±30% at 850–800 hPa. Diurnal variations were characterized by night-time warming of up to +5 °C in the lower PBL and concurrent cooling above 800 hPa. The Heating and surface Dimming (HD) Index was found to correlate positively with PM_2.5 concentration (R = 0.60), reflecting increased thermal stability and vertical inhomogeneity under aerosol loading. These findings underscore the need for an improved understanding and mitigation of aerosol–PBL interactions to support sustainable urban air quality management strategies. Full article

This study explores the impact of intake air cooling intensity, defined by heat exchanger effectiveness (HEE) and exhaust gas recirculation (EGR), on the energy and environmental performance of a turbocharged compression ignition (CI) engine. Experimental investigations were conducted on a 1.9-litre CI engine operating at 2000 rpm under three brake mean effective pressure (BMEP) conditions (0.2, 0.4, and 0.6 MPa), which correspond to part-load engine operation. HEE was varied at 0%, 50%, and 100%, in both EGR-on and EGR-off modes. Additional numerical simulations were carried out using AVL BOOST software to analyze combustion dynamics, including engine operating cycle modeling to validate the accuracy of the combustion analysis. The results demonstrate that increasing HEE significantly improves cylinder filling and excess air ratio, leading to enhanced combustion efficiency and lower in-cylinder temperatures. This, in turn, reduces specific NO_x emissions by approximately 40% with EGR and approximately 60% without EGR; however, under EGR-on conditions, the reduced combustion intensity leads to increased smoke and unburned hydrocarbon emissions—particularly at high cooling intensities. This effect is primarily associated with the engine control unit’s (ECU) limitations on intake air mass flow to maintain the target EGR ratio. Integrated control of HEE and EGR systems improves engine performance and reduces emissions across varying conditions, while highlighting trade-offs that inform the refinement of air management strategies. Full article

As a new type of production factor, data possesses multidimensional application value, and its pivotal role is becoming increasingly prominent in the aviation sector. Data sharing can significantly enhance the utilization efficiency of data resources and serves as one of the key tasks in building smart civil aviation. However, currently, data silos are pervasive, with vast amounts of data only being utilized and analyzed within limited scopes, leaving their full potential untapped. The challenges in data sharing primarily stem from three aspects: (1) Data owners harbor concerns regarding data security and privacy. (2) The highly dynamic and real-time nature of aviation operations imposes stringent requirements on the timeliness, stability, and reliability of data sharing, thereby constraining its scope and extent. (3) The lack of reasonable incentive mechanisms results in insufficient motivation for data owners to share. Consequently, addressing the issue of aviation big data sharing holds significant importance. Since the release of the Bitcoin whitepaper in 2008, blockchain technology has achieved continuous breakthroughs in the fields of data security and collaborative computing. Its unique characteristics—decentralization, tamper-proofing, traceability, and scalability—lay the foundation for its integration with aviation. Blockchain can deeply integrate with air traffic management (ATM) operations, effectively resolving trust, efficiency, and collaboration challenges in distributed scenarios for ATM data. To address the heterogeneous data usage requirements of different ATM stakeholders, this paper constructs a blockchain-based multi-level data security sharing architecture, enabling fine-grained management and secure collaboration. Furthermore, to meet the stringent timeliness demands of aviation operations and the storage pressure posed by massive data, this paper optimizes blockchain storage deployment and consensus mechanisms, thereby enhancing system scalability and processing efficiency. Additionally, a dual-mode data-sharing solution combining raw data sharing and model sharing is proposed, offering a novel approach to aviation big data sharing. Security and formal analyses demonstrate that the proposed solution is both secure and effective. Full article

China ranks as the world’s leading potato (Solanum tuberosum L.) producer, while the poor seeding machinery performance limited a higher input–output ratio in potato cultivation and impeded sustainable development. We developed an advanced air-suction mulai-arm potato planter (ASPP) that incorporated integrated side-deep fertilization, automated seed feeding, negative-pressure seed filling, seed transportation, positive-pressure seed delivery, soil covering, and compaction. The study proposes a Negative-pressure seed extraction mechanism that minimizes seed damage by precisely controlling suction pressure, and the near-zero-speed seed delivery mechanism synchronizes seed release with ground speed, reducing bounce-induced spacing errors. Furthermore, the structural configuration and operation principle of ASPP were systematically elucidated, and key performance parameters and optimal values were identified. We conducted a randomized complete block design plot trial comparing the spoon-belt potato planter (SBPP) and spoon-chain potato planter (SCPP), evaluating sowing quality, seedling emergence rate (ER), potato yield (PY), and comprehensive economic benefits. The results revealed that plant spacing index (PSI), missed-seeding index (MI), re-seeding index (RI), and coefficient of variation (CV) of ASPP were 90.05%, 3.78%, 2.32%, and 7.93%, respectively. The mean ER values for ASPP, SBPP, and SCPP were 94.76%, 85.42%, and 83.46%, respectively, with the ASPP showing improvements of 10.93% and 13.54% over SBPP and SCPP. However, the SBPP and SCPP exhibited greater emergence uniformity than ASPP. The mean PY value was 37,205.25, 32,973.75, and 34,620 kg·ha⁻¹ for ASPP, SBPP, and SCPP. The ASPP outperformed the SBPP and SCPP by 12.83% and 7.47%. Overall, ASPP demonstrated balanced and superior performance across the above-mentioned indicators, demonstrating its potential to enable precision agriculture in tuber crop cultivation. Full article

This study presents an approach based on machine learning (ML) techniques to analyze the relationship between emergency room (ER) admissions for cardiorespiratory diseases (CRDs) and environmental factors. The aim of this study is the development and verification of an interpretable machine learning framework applied to environmental and health data to assess the relationship between environmental factors and daily emergency room admissions for cardiorespiratory diseases. The model’s predictive accuracy was evaluated by comparing simulated values with observed historical data, thereby identifying the most influential environmental variables and critical exposure thresholds. This approach supports public health surveillance and healthcare resource management optimization. The health and environmental data, collected through meteorological sensors and air quality monitoring stations, cover eleven years (2013–2023), including meteorological conditions and atmospheric pollutants. Four ML models were compared, with XGBoost showing the best predictive performance (R² = 0.901; MAE = 0.047). A 10-fold cross-validation was applied to improve reliability. Global model interpretability was assessed using SHAP, which highlighted that high levels of carbon monoxide and relative humidity, low atmospheric pressure, and mild temperatures are associated with an increase in CRD cases. The local analysis was further refined using LIME, whose application—followed by experimental verification—allowed for the identification of the critical thresholds beyond which a significant increase in the risk of hospital admission (above the 95th percentile) was observed: CO > 0.84 mg/m³, P_atm ≤ 1006.81 hPa, Tavg ≤ 17.19 °C, and RH > 70.33%. The findings emphasize the potential of interpretable ML models as tools for both epidemiological analysis and prevention support, offering a valuable framework for integrating environmental surveillance with healthcare planning. Full article

Legged rovers are gaining interest for planetary exploration due to their high mobility. However, loose regolith on celestial surfaces like the Moon and Mars often leads to slippage as legs disturb the soil. To address this, a walking technique has been proposed that enhances soil support by transmitting vibrations from the robot’s legs. This approach aims to improve mobility by increasing the ground’s bearing capacity. To evaluate its effectiveness in space-like environments, this study experimentally investigates the effect of vibration on bearing capacity under low atmospheric pressure, which can influence soil behavior due to reduced air resistance. Using Silica No. 5 and Toyoura sand as test materials, experiments were conducted to compare bearing capacities under standard and low pressure. The results demonstrate that applying vibration significantly improves bearing capacity and that the influence of atmospheric pressure is minimal. These findings support the viability of vibration-assisted locomotion for planetary rovers operating in low-pressure extraterrestrial environments. Full article