Search Results (336)

In response to the limited research on fire detection in cotton pickers and the issue of low detection accuracy in visual inspection, this paper proposes a computer vision-based detection method. The method is optimized according to the structural characteristics of cotton pickers, and a lightweight improved YOLOv11 algorithm is designed for cotton fire detection in cotton pickers. The backbone of the model is replaced with the MobileNetV2 network to achieve effective model lightweighting. In addition, the convolutional layers in the original C3k2 block are optimized using partial convolutions to reduce computational redundancy and improve inference efficiency. Furthermore, a visual attention mechanism named CBAM-ECA (Convolutional Block Attention Module-Efficient Channel Attention) is designed to suit the complex working conditions of cotton pickers. This mechanism aims to enhance the model’s feature extraction capability under challenging environmental conditions, thereby improving overall detection accuracy. To further improve localization performance and accelerate convergence, the loss function is also modified. These improvements enable the model to achieve higher precision in fire detection while ensuring fast and accurate localization. Experimental results demonstrate that the improved model reduces the number of parameters by 38%, increases the frame processing speed (FPS) by 13.2%, and decreases the computational complexity (GFLOPs) by 42.8%, compared to the original model. The detection accuracy for flaming combustion, smoldering combustion, and overall detection is improved by 1.4%, 3%, and 1.9%, respectively, with an increase of 2.4% in mAP (mean average precision). Compared to other models—YOLOv3-tiny, YOLOv5, YOLOv8, and YOLOv10—the proposed method achieves higher detection accuracy by 5.9%, 7%, 5.9%, and 5.3%, respectively, and shows improvements in mAP by 5.4%, 5%, 4.8%, and 6.3%. The improved detection algorithm maintains high accuracy while achieving faster inference speed and fewer model parameters. These improvements lay a solid foundation for fire prevention and suppression in cotton collection boxes on cotton pickers. Full article

Hydrogen is a promising zero-carbon fuel for internal combustion engines; however, the geometric optimization of injectors for low-pressure direct-injection (LPDI) systems under lean-burn conditions remains underexplored. This study presents a high-fidelity optimization framework that couples a validated computational fluid dynamics (CFD) combustion model with a surrogate-assisted multi-objective genetic algorithm (MOGA). The CFD model was validated using particle image velocimetry (PIV) data from non-reacting flow experiments conducted in an optically accessible research engine developed by Sandia National Laboratories, ensuring accurate prediction of in-cylinder flow structures. The optimization focused on two critical geometric parameters: injector hole count and injection angle. Partial indicated mean effective pressure (pIMEP) and in-cylinder NO_x emissions were selected as conflicting objectives to balance performance and emissions. Adaptive mesh refinement (AMR) was employed to resolve transient in-cylinder flow and combustion dynamics with high spatial accuracy. Among 22 evaluated configurations including both capped and uncapped designs, the injector featuring three holes at a 15.24° injection angle outperformed the baseline, delivering improved mixture uniformity, reduced knock tendency, and lower NO_x emissions. These results demonstrate the potential of geometry-based optimization for advancing hydrogen-fueled LPDI engines toward cleaner and more efficient combustion strategies. Full article

Liquefied natural gas (LNG) is increasingly used as a marine fuel due to its capacity to significantly reduce emissions of particulate matter, sulfur oxides (SO_x), and nitrogen oxides (NO_x), compared to conventional fuels. In addition, LNG combustion produces less carbon dioxide (CO₂) than conventional marine fuels, and the use of non-fossil LNG offers further potential for reducing greenhouse gas emissions. However, this benefit can be partially offset by methane slip—the release of unburned methane in engine exhaust—which has a much higher global warming potential than CO₂. This study presents an experimental evaluation of methane emissions from a RoPax vessel powered by low-pressure dual-fuel four-stroke engines with a direct mechanical propulsion system. Methane slip was measured directly during onboard testing and combined with a year-long analysis of engine operation using an Engine Load Monitoring (ELM) method. The yearly average methane slip coefficient (C_slip) obtained was 1.57%, slightly lower than values reported in previous studies on cruise ships (1.7%), and significantly lower than the default values specified by the FuelEU (3.1%) Maritime regulation and IMO (3.5%) LCA guidelines. This result reflects the ship’s operational profile, characterized by long crossings at high and stable engine loads. This study provides results that could support more representative emission assessments and can contribute to ongoing regulatory discussions. Full article

Calorific value and moisture content are the key indices to evaluate Caragana pellet fuel’s quality and combustion characteristics. Calorific value is the key index to measure the energy released by energy plants during combustion, which determines energy utilization efficiency. But at present, the determination of solid fuel is still carried out in the laboratory by oxygen bomb calorimetry. This has seriously hindered the ability of large-scale, rapid detection of fuel particles in industrial production lines. In response to this technical challenge, this study proposes using hyperspectral imaging technology combined with various chemometric methods to establish quantitative models for determining moisture content and calorific value in Caragana korshinskii fuel. A hyperspectral imaging system was used to capture the spectral data in the 935–1720 nm range of 152 samples from multiple regions in Inner Mongolia Autonomous Region. For water content and calorific value, three quantitative detection models, partial least squares regression (PLSR), random forest regression (RFR), and extreme learning machine (ELM), respectively, were established, and Monte Carlo cross-validation (MCCV) was chosen to remove outliers from the raw spectral data to improve the model accuracy. Four preprocessing methods were used to preprocess the spectral data, with standard normal variate (SNV) preprocessing performing best on the quantitative moisture content detection model and Savitzky–Golay (SG) preprocessing performing best on the calorific value detection method. Meanwhile, to improve the prediction accuracy of the model to reduce the redundant wavelength data, we chose four feature extraction methods, competitive adaptive reweighted sampling (CARS), successive pojections algorithm (SPA), genetic algorithm (GA), iteratively retains informative variables (IRIV), and combined the three models to build a quantitative detection model for the characteristic wavelengths of moisture content and calorific value of Caragana korshinskii fuel. Finally, a comprehensive comparison of the modeling effectiveness of all methods was carried out, and the SNV-IRIV-PLSR modeling combination was the best for water content prediction, with its prediction set determination coefficient $\left(R_P^2\right)$, root mean square error of prediction (RMSEP), and relative percentage deviation (RPD) of 0.9693, 0.2358, and 5.6792, respectively. At the same time, the moisture content distribution map of Caragana fuel particles is established by using this model. The SG-CARS-RFR modeling combination was the best for calorific value prediction, with its $R_P^2$, RMSEP, and RPD of 0.8037, 0.3219, and 2.2864, respectively. This study provides an innovative technical solution for Caragana fuel particles’ value and quality assessment. Full article

The transition to passenger car electrification is a crucial step in China’s strategic efforts to achieve carbon peak and carbon neutrality. However, previous research has not considered the variances in vehicle models. Hence, this study aims to fill this gap by comparing the carbon emission reduction and economic feasibility of battery electric vehicles (BEVs) in the Chinese market, taking into account different powertrains, vehicle segments, classes, and driving ranges. Next, the study identifies the most cost-effective BEV within each market segment, employing life-cycle assessment and life cycle cost analysis methods. Moreover, at different levels of technological development, we construct three low-carbon measures, including electricity decarbonization (ED), energy efficiency improvement (EEI), and vehicle lightweight (LW), to quantify the emission mitigation potentials from different carbon reduction pathways. The findings indicate that BEVs achieve an average carbon reduction of about 31.85% compared to internal combustion engine vehicles (ICEVs), demonstrating a significant advantage in carbon reduction. However, BEVs are not economically competitive. The total life cycle cost of BEVs is 1.04–1.68 times higher than that of ICEVs, with infrastructure costs accounting for 18.8–57.8% of the vehicle’ s life cycle costs. In terms of cost-effectiveness, different models yield different results, with sedans generally outperforming sport utility vehicles (SUVs). Among sedans, both A-class and B-class sedans have already reached a point of cost-effectiveness, with the BEV400 emerging as the optimal choice. In low-carbon emission reduction scenarios, BEVs could achieve carbon reduction potentials of up to 45.3%, 14.9%, and 9.0% in the ED, EEI, and LW scenarios, respectively. Thus, electricity decarbonization exhibits the highest potential for mitigating carbon emissions, followed by energy efficiency improvement and vehicle lightweight. There are obvious differences in the stages of impact among different measures. The ED measure primarily impacts the waste treatment process (WTP) stage, followed by the vehicle cycle, while the EEI measure only affects the WTP stage. The LW measure has a complex impact on emission reductions, as the carbon reductions achieved in the WTP stage are partially offset by the increased carbon emissions in the vehicle cycle. Full article

Ammonia is increasingly recognised as a promising carbon-free fuel and hydrogen carrier due to its high hydrogen content, ease of liquefaction, and existing global infrastructure. However, its direct utilisation in combustion systems poses significant challenges, including low flame speed, high ignition temperature, and the formation of nitrogen oxides (NO_X). This review explores catalytic ammonia cracking as a viable method to enhance combustion through in situ hydrogen production. It evaluates traditional catalytic burner designs originally developed for hydrocarbon fuels and assesses their adaptability for ammonia-based applications. Special attention is given to ruthenium- and nickel-based catalysts supported on various oxides and nanostructured materials, evaluating their ammonia conversion efficiency, resistance to sintering, and thermal stability. The impact of the main operational parameters, including reaction temperature and gas hourly space velocity (GHSV), is also discussed. Strategies for combining partial ammonia cracking with stable combustion are studied, with practical issues such as catalyst degradation, NO_X regulation, and system scalability. The analysis highlights recent advancements in structural catalyst support, which have potential for industrial-scale application. This review aims to provide future development of low-emission, high-efficiency catalytic burner systems and advance ammonia’s role in next-generation hydrogen energy technologies. Full article

This article presents experimental results related to the influence of bioethanol content in fuel blends on the performance and emissions of a spark-ignition engine. Tests were conducted for six ethanol–gasoline mixtures (ranging from 0% to 100% ethanol) under three engine control strategies: factory settings, a fuel dose increased by 10%, and a fuel dose increased by 20%—both with an ignition timing adjustment of +3°. Measurements included engine power and torque, as well as emissions of CO, CO₂, HC, O₂, and particulate matter, all performed under a full engine load. The results revealed the strong dependence of engine behavior on ethanol content. Increasing the ethanol concentration significantly reduced CO and HC emissions, as well as markedly lowering particulate emissions—particularly at 30% ethanol. Conversely, pure ethanol led to substantial reductions in power (up to 28%) and torque (up to 32%) compared to conventional gasoline. Adjustments to the fuel dose and ignition timing partially mitigated these losses. Emissions of CO₂ and oxygen content in exhaust gases varied depending on the blend, highlighting the complex nature of the combustion process. The findings contribute to the understanding of renewable fuel behavior in SI engines and underscore the influence of both fuel composition and control strategies on performance and emission characteristics. Full article

The ammonia energy ratio (AER) is a critical parameter influencing the performance of ammonia/diesel dual-fuel engines. In this study, a numerical simulation was conducted based on a high-pressure dual-fuel (HPDF) direct injection ammonia/diesel engine to investigate the impact of the AER on combustion and emissions under two distinct combustion modes. By adjusting the ammonia start of injection timing (ASOI), the combustion mode was transitioned from diffusion combustion (HPDF1) to partially premixed combustion (HPDF2). The results show that under the HPDF1 mode, a three-stage heat release pattern is observed, and the evolution curves of NO and NO₂ exhibit fluctuations similar to the heat release process. As the AER increases, the second heat release stage is suppressed, the high-temperature region narrows, the ignition delay is extended, and the CA10–CA50 interval shortens, leading to a higher maximum pressure rise rate (MPRR) at a high AER. Conversely, in the HPDF2 mode, the combustion process is characterized by a two-stage heat release. With an increasing AER, the high-temperature region expands, the ignition delay and CA10–CA50 interval are prolonged, while the CA50–CA90 interval shortens, and the MPRR becomes the lowest at a high AER. For both combustion modes, total greenhouse gas (GHG) emissions decrease with an increasing AER. However, in the HPDF2 mode with an AER = 95%, N₂O accounts for up to 78% of the total GHG emissions. Additionally, a trade-off relationship exists between NOx emissions and indicated thermal efficiency (ITE). When the ASOI is set to −8°CA ATDC, the engine operates in a transitional combustion mode between HPDF1 and HPDF2. At this point, setting the AER to 95% effectively mitigates the trade-off, achieving an ITE of 53.56% with NOx emissions as low as 578 ppm. Full article

Particles ejected during thermal runaway (TR) of lithium-ion batteries carry a significant fraction of the total TR energy and can cause danger to other components in the battery system. The associated safety hazards should be addressed in the battery pack development process, which requires a deep understanding of TR particle characteristics. In this study, these characteristics are determined by applying several measurement techniques. Among them, dynamic image analysis and large particle image processing are applied to battery abuse particles for the first time, allowing their size and shape to be quantified in detail. Particles are collected from three overheating tests on a prismatic 51 Ah NMC622 cell under vacuum conditions in an autoclave environment. Battery abuse particles cover a wide size range, from micrometers to millimeters, with the largest particle reaching 51.4 mm. They are non-spherical, whereby sphericity, symmetry, and aspect ratio decrease for larger particles. Re-solidified copper droplets and intact separator pieces indicate particle temperatures of ~200–1100 °C at the time of cell ejection. Particles are partially combustible, with an exothermic onset at ~500 °C associated with graphite oxidation. Reactivity is non-linearly size dependent. Implications of these findings for battery system development are discussed. Full article

This experimental study examines the particle-level combustion behavior of high-volatile bituminous coal and walnut shell particles in oxyfuel environments, with a particular focus on the gas-phase ignition characteristics and the structural development of volatile flames. Particles with similar size and shape distributions (a median diameter of about 126 µm and an aspect ratio of around 1.5) are combusted in hot flows generated using lean, flat flames, where the oxygen mole fraction is systematically varied in both CO₂/O₂ and N₂/O₂ atmospheres while maintaining comparable gas temperatures and particle heating rates. The investigation employs a high-speed multi-camera diagnostic system combining laser-induced fluorescence of OH, diffuse backlight-illumination, and Mie scattering to simultaneously measure the particle size, shape, and velocity; the ignition delay time; and the volatile flame dynamics during early-stage volatile combustion. Advanced detection algorithms enable the extraction of these multiple parameters from spatiotemporally synchronized measurements. The results reveal that the ignition delay time decreases with an increasing oxygen mole fraction up to 30 vol%, beyond which point further oxygen enrichment no longer accelerates the ignition, as the process becomes limited by the volatile release rate. In contrast, the reactivity of volatile flames shows continuous enhancement with an increasing oxygen mole fraction, indicating non-premixed flame behavior governed by the diffusion of oxygen toward the particles. The analysis of the flame stand-off distance demonstrates that volatile flames burn closer to the particles at higher oxygen mole fractions, consistent with the expected scaling of O₂ diffusion with its partial pressure. Notably, walnut shell and coal particles exhibit remarkably similar ignition delay times, volatile flame sizes, and OH-LIF intensities. The substitution of N₂ with CO₂ produces minimal differences, suggesting that for 126 µm particles under high-heating-rate conditions, the relatively small variations in the heat capacity and O₂ diffusivity between these diluents have negligible effects on the homogeneous combustion phenomena observed. Full article

The use of hydrogen as a fuel for piston engines enables environmentally friendly and efficient operation. However, several challenges arise in the combustion process, limiting the development of hydrogen engines. These challenges include abnormal combustion, the high burning velocity of hydrogen-enriched mixtures, increased nitrogen oxide emissions, and others. A rational organization of hydrogen combustion can partially or fully mitigate these issues through the use of advanced methods such as late direct injection, charge stratification, dual injection, jet-guided operation, and others. However, mathematical models describing hydrogen combustion for these methods are still under development, complicating the optimization and refinement of hydrogen engines. Previously, we proposed a mathematical model based on Wiebe functions to describe premixed and diffusion combustion, as well as relatively slow combustion in lean-mixture zones, behind the flame front, and near-wall regions. This study further develops the model by accounting for the combined influence of the mixture composition and engine speed, mixture stratification, and the effects of injection and ignition parameters on premixed and diffusion combustion. Special attention is given to combustion modeling in an engine with single injection and jet-guided operation. Full article

This study evaluates the potential of biomass fuels (10 wt% and 20 wt%) as partial coal replacements in combustion and their effects on clinker performance. Cement was produced by co-grinding clinker with gypsum, and hydration products were analyzed. Potassium and sodium carbonates were introduced to create highly alkaline conditions, thereby simulating the effect of alkali metals in biomass-derived fuel ash on the mineral phases of clinker under high substitution ratios. The results showed biomass fuels’ low ignition point and high volatile matter content improved mixed fuels combustion, increasing the average combustion rate by 0.52%~2.28% and reducing the ignition temperature by up to 56 °C. At low substitution levels, biomass ash did not adversely affect clinker mineral composition or cement properties. However, the highly alkaline environment suppressed the formation of tricalcium silicate (C₃S) in the clinker, resulting in an increased content of free calcium oxide(f-CaO). Simultaneously, it promotes the formation of sulfates (K₂SO₄, Na₂SO₄) and sodium silicate (Na₂Si₂O₅). Full article

This article reviews the physical and chemical mechanisms associated with unsteady swirl-stabilized partially or fully lean premixed combustion. The processes of flame stabilization, mode conversion, swirl number oscillation, equivalence ratio oscillation, and vortex rollup are described. The key challenges associated with flow-flame dynamics for several sources of perturbations are presented and discussed. The Rayleigh criterion is discussed. This article summarizes the scientific knowledge gained on swirling flames dynamics in terms of modeling, theoretical analysis, and transient measurements with advanced diagnostics. The following are specifically documented: (i) the effect of the swirler on swirling flames; (ii) the analytical results, computational modeling, and experimental measurements of swirling flame dynamics; (iii) the influence of flow features on flame response of swirling flames for combustion instabilities studies; and (iv) the identification and description of the combustion dynamics mechanisms responsible for swirl-stabilized combustion instabilities. Relevant elements from the literature in this context for hydrogen fuel are included. Full article

Increasing the efficiency and capacity of nuclear power units is a promising direction for the development of power generation systems. Unlike thermal power plants, nuclear power plants operate at relatively low temperatures of the steam working fluid. Due to this, the thermodynamic efficiency of such schemes remains relatively low today. The temperature of steam and the efficiency of nuclear power units can be increased by integrating external superheating of the working fluid into the schemes of steam turbine plants. This paper presents the results of a thermodynamic analysis of thermal schemes of NPPs integrated with hydrocarbon-fueled plants. Schemes with a remote combustion chamber, a boiler unit and a gas turbine plant are considered. It has been established that superheating fresh steam after the steam generator is an effective superheating solution due to the utilization of heat from the exhaust gases of the GTU using an afterburner. Furthermore, there is a partial replacement of high- and low-pressure heaters in the regeneration system, with gas heaters for condensate and steam superheating after the steam generator for water-cooled and liquid-metal reactor types. An increase in the net efficiency of the hybrid NPP is observed by 8.49 and 5.11%, respectively, while the net electric power increases by 93.3 and 76.7%. Full article

Brazil has set a goal to reduce greenhouse gas (GHG) emissions, which is a significant opportunity to leverage calcium looping (CaL) technology for energy generation in natural gas power plants. CaL is a promising technology, due to sorbent low cost and availability, but its industrial implementation performance decay is a major challenge to face. While evaluating carbon-capture technologies, net emissions perspective is essential, and optimizing CaL capture through a partial carbonation cycle is a promising approach, both to reduce net emissions and improve the number of cycles before deactivation. In this context, a Brazilian dolomite was characterized and evaluated, to be used as sorbent in a CaL process employed in natural gas power plants. For such a purpose, a novel methodology has been proposed to evaluate the mass ratio of CO₂ captured, to assess the energy consumed in the process. A rotatable central composite design (RCCD) model was used to identify the optimal temperature and residence time conditions in the carbonation stage of the CaL process, focusing on achieving energy efficiency. The five most promising conditions were then tested across 10 calcination–carbonation cycles, to examine the impact of partial carbonation in capture efficiency over extended cycles. The results indicate that temperature plays a critical role in the process, particularly in terms of capture efficiency, while residence time significantly affects energy consumption. The conditions that demonstrated optimal performance for both the single and the multi-cycle tests were 580 °C for 7.5 min and 550 °C for 10 min, given that index of capture efficiency (${\mathrm{IEC}}_{10,c}$) values of 1.34 and 1.20 were found, respectively—up to 40% higher than at 475 °C. There was lower energy expenditure at 580 °C (${\mathrm{E}}_{sp}$) (33.48 kJ), 550 °C (${\mathrm{E}}_{sp}$ = 37.97 kJ), ${\mathrm{CO}}_2$ mass captured (${\mathrm{CO}}_{2}cap$ = 9.80 mg), and the samples exhibited a more preserved surface, thus making it the most suitable option for scale-up applications. Full article