Small Flame Research Articles

Cofiring of hydrogen and pulverized coal in rotary kilns using one integrated burner

The grate-kiln process for iron-ore pellet induration utilizes pulverized coal fired burners. In a developed infrastructure for H2, it might be desirable to heat the existing rotary kilns with renewably produced H2. Technical challenges of H2 heating of grate-kilns include high emissions of NOX and maintaining sufficient heat transfer to the pellet bed. This article examined cofiring (70% coal/30% H2) in 130 kW experiments using two different integrated burner concepts. Compared to pure coal combustion, cofiring creates a more intense, smaller flame with earlier ignition and less fluctuations. The process temperature and heat transfer are enhanced in the beginning of the kiln. The co-fired flames emit 32% and 78% less NOX emissions compared to pure coal and H2 combustion, respectively. We can affect the combustion behavior and NOX emissions by the burner design. H2/coal cofiring using integrated burners is probably an attractive solution for emission minimization in rotary kilns.

Study on the acoustic disturbance characteristics of the spray flame

The axial sound field was added to the ethanol spray flame as a perturbation element to study the dynamic response and combustion characteristics. A forced acoustic field is applied to a small oscillating flame. In cases where the frequency of the external sound field matches the eigenfrequency, even small amplitude self-excited flames demonstrate significant instability. As the intensity of the sound field increases, the amplitude of pressure oscillations sharply rises, and the pressure and flame heat release oscillations are in-phase. When the sound field operates at frequencies other than the eigenfrequency, it has an inhibitory effect on the evaporation and combustion process of ethanol droplets. Consequently, intensifying the sound field leads to a reduction in both the area of the evaporation combustion zone and the axial temperature of the flame. The CO formation is influenced by both temperature and the sound field, showing a pattern of increasing and then decreasing with the increase of sound intensity. Additionally, NOx generation exhibits higher emission concentrations in low-temperature and short flames, which is more likely to prompt NOx and is not closely related to frequency.

An Improved Lightweight YOLOv8 Network for Early Small Flame Target Detection

An Improved Lightweight YOLOv8 Network for Early Small Flame Target Detection

Experimental and numerical studies of NO reduction by ammonia in different methane flame positions

Blending ammonia with methane for combustion can reduce carbon emissions and improve the flame characteristics of ammonia combustion. However, blending ammonia with methane can easily lead to high concentrations of NOx emissions. This study investigates the impact of different ammonia and methane blending methods on the flame structure and NOx emission by experiments and CFD numerical simulation. The results indicate that simultaneous injection of ammonia and methane through the central fuel tube significantly alters the combustion flame structure and leads to high concentrations of NOx emission. As the ammonia ratio increases, the flame structure transitions from a bright flame to a layered flame with an inner yellow conical small flame surrounded by a light-colored outer flame. When the ammonia ration increases from 0 % to 20 %, NOx emission increase from 15 ppm to 323 ppm, nearly 22 times higher. When ammonia is injected into the methane flame from flame side, the flame above the injection position appears as an orange flame, and a significant reduction in NOx emission is obtained. When the ammonia ratio is 20 % and injected at heights of 20 mm 40 mm, and 60 mm above the fuel exit, the outlet NOx concentrations are 183 ppm, 140 ppm, and 153 ppm respectively, this represents reductions of 43.3 %, 56.6 %, and 52.6 %, respectively. The numerical simulation results indicate that the injection of ammonia leads to the formation of higher concentrations of NH2 and super-vapor H2O, resulting in an orange color flame. The gas temperature and oxygen concentration play a crucial role in NOx emissions. NOx emission is lowest when ammonia is injected into the higher temperature, lower oxygen environment at 40 mm.

Forest fire detection utilizing ghost Swin transformer with attention and auxiliary geometric loss

Forest fires are a devastating natural disaster. Existing fire detection models face limitations in dataset availability, multi-scale feature extraction, and locating obscured or small flames and smoke. To address these issues, we develop a dataset containing real and synthetic forest fire images, sourced from a UAV (Unmanned Aerial Vehicle) perspective. Additionally, we propose the Ghost Convolution Swin Transformer (GCST) module to extract multi-scale flame and smoke features from different receptive fields by integrating parallel Ghost convolution and Swin Transformer. Subsequently, we design a lightweight reparameterized rotation attention module, which captures interactions across channel and spatial dimensions to suppress background noise and focus on obscured flames and smoke. Finally, we introduce a loss function, called Efficient Auxiliary Geometric Intersection over Union (EAGIoU), which employs an auxiliary bounding box to accelerate the model's convergence while integrating the geometrical principles of the predicted and real bounding boxes to accurately locate small flames and smoke. Extensive experimental results demonstrate that our method achieves 75.2 % mAP@0.5 and 42 % mAP@0.5:0.95 with a frame rate of 239 frames per second, indicating a significant improvement in accuracy and real-time performance compared to state-of-the-art techniques. The code and datasets are available at https://github.com/luckylil/forest-fire-detection.

The Heat Flux Method for hybrid iron–methane–air flames

Recently, a cyclic energy storage concept was proposed involving the use of metal powder as CO2-free energy carrier, known as the metal fuel cycle. In this cycle, the burning of iron powder is considered as the discharge agent of the energy carrier. However, for this cycle to be an efficient one, a better understanding of the laminar burning velocity of iron powder is required. This study presents a newly developed burner based on the Heat Flux Method (HFM), which can measure the burning velocities of flat hybrid iron–methane–air flames. Since laminar iron flames are difficult to stabilize and have – even for micron-sized particles – burning velocities in close proximity to their terminal velocity, methane is used as a stabilizing agent. In this paper, the design of the new burner system is presented with results for burning velocities of iron–methane–air flames. The results show a steady decrease in burning velocity when iron is added to a stoichiometric methane–air flame down to 16 cm/s. It is hypothesized that in the case of relatively low iron concentrations, the iron acts as a heat sink within these flames, consequently reducing the flame temperature and laminar burning velocity. For these low concentrations, methane is the governing fuel. At concentrations above 250 g/m3, the reduction of the burning velocity comes to a halt, and the iron becomes the governing fuel in the flame. A comprehensive error analysis reveals that the primary sources of uncertainty stem from fluctuations in the iron content and parabolic fitting of the thermocouple measurements in the HFM.Novelty and Significance statementThe novelty of this study is a newly developed burner based on the well-known Heat Flux Method (HFM). In accordance with the HFM, a new burner was designed to facilitate stable flat adiabatic hybrid iron–methane–air flames for the first time and measure its key parameter, the adiabatic burning velocity. Further, a metered iron powder dispersion system was developed for accurate iron mass flow measurements. The results show a steady decrease in burning velocity when iron is added to a stoichiometric methane–air flame in relatively low concentrations and show a very weak dependence of the burning velocity on the iron content at iron concentrations above 250 g/m3. These findings enable the validation of 1D simulations for iron-laden flames. A detailed assessment of the measurement uncertainties reveals that the largest source of uncertainty can be derived back to the stability of iron mass flow, leading to small flame propagation fluctuations on relatively short intervals.

Numerical investigation of CH4/H2/air micro-mixing combustion flow in a micro gas turbine combustor with different head-end structures

In order to investigate the premixed combustion characteristics of CH4/H2/air in a micro-mixing combustor, the effects of different micro-mixing head-ends (HE1, HE2, HE3) and hydrogen mixing ratios on the temperature distribution, heat transfer process, emission characteristic, flames shape are analyzed. The results show that compared with swirl head-end combustion, the micro-mixing combustion performance is better. Among the three head-ends, HE3 has the best combustion characteristics and stable flames. The temperature distribution in the high-temperature zone is uniform, and low-temperature zone is concentrated near the jet, which can suppress the flashback. The velocity and temperature gradient near the central axis of jet streams show a strong synergistic effect. The flames are plume shaped and flames stability is mainly influenced by the H2 combustion process. Increasing the jet diameter, decreasing the jet spacing and increasing the hydrogen mixing ratio all contribute to the flames stability, but these three methods can stabilize the flames by affecting fluid Reynolds number, interaction between small flames and combustion rate, respectively. Moreover, small jet diameter and high hydrogen mixing ratio can reduce OTDF, which contributes to improve outlet temperature uniformity.

Flame suppression due to acoustic streaming by using time reversal

Using high amplitude time reversal focusing to extinguish small flames is a novel demonstration of transient acoustic streaming. Typically, others have placed a low frequency acoustic source near the flame in order to generate a high enough particle displacement to extinguish it. In this study, we move the sources far from the flame and demonstrate that the time reversal method can focus transient waves to the flame. The peak acoustic overpressure level needed to extinguish a candle flame in free space is 191 dB peak when using a frequency range of 300 to 15000 Hz. This momentary focus causes acoustic streaming at the flame location after the focusing, which extinguishes the flame. By tracking the flame in high-speed video, we show the displacement of the flame due to the passing acoustic wave and subsequently due to the acoustic streaming. We further show that acoustic streaming extinguishes the flame, not the acoustic particle displacement.

Simulated effects of main properties and heat flux on first dripping behaviors of polymers impinged by small flames

Dripping plays a significant role in understanding the UL-94 vertical test. In this study, the dripping of polymers impinged by small flames was simulated using the volume of fluid method and the enthalpy-porosity technique. The UL-94 flame was approximated using a 2026K gas flow with a velocity of 0.9 m/s, meeting with ASTM-D5207. The small-size drop and the large-size drop were characterized by aspect ratios of no more than 1.1 and greater than 3.1, respectively. Decreasing surface tension (σ), viscosity (μ), thermal conductivity (k), or increasing the heat flux tends to result in small-size drops. When σ ≤ 0.04 N/m, the first drop is small-size, and the equivalent radius of the first drop follows a power-law relationship with σ. As σ varies from 0.03 N/m to 0.07 N/m, the critical value of μ decreases from 0.30 Pa s to 0.02 Pa s. If σ = 0.07 N/m and k ≤ 0.1W/m·K, the first drop tends to be small-size. When σ is 0.03 N/m, the size of the first drop is independent of k, and the critical heat flux is approximately 48 kW/m2. The first dripping time increases with μ, and the large-size dripping time is linear with the product of viscosity and characteristic length divided by drop mass.

Modeling hydrogen–diesel dual direct injection combustion with FGM and transported PDF

This work extends the transported probability density function (PDF) method to model hydrogen–diesel dual direct injection (H2DDI) combustion, where a H2 jet is ignited by a small pilot diesel jet flame. The work is motivated by previous H2DDI engine tests where stable compression ignition engine operation was reported with up to 90 % H2 supply by energy share. To help explain this high performance and provide a tool to help further engine optimization, the Eulerian Monte Carlo Fields (EMCF) solution method is employed with which a transported PDF equation is solved in combination with Flamelet Generated Manifold (FGM) for high accuracy and computational efficiency. In all cases, the pilot fuel ignites before interacting with the H2 jet and thus reaction rate and chemical composition are computed as the weighted average of the corresponding values taken for two separated FGM tables generated for the two fuels. Pressure measurements and high-speed schlieren imaging performed in a preburn-type optical constant volume combustion chamber (CVCC) with n-heptane (nC7H16) pilot fuel were used to validate the EMCF+FGM model. The application focus is how H2 ignition and combustion is affected when the nC7H16 is injected prior to or after the main H2 jet. EMCF+FGM computed heat release rate and flame structure were compared with experimental data and results from conventional FGM model based on presumed PDF. When applied to H2DDI combustion, the EMCF+FGM model successfully reproduces flame structures and heat release rate under different injection strategies, including the transition towards partially-premixed combustion when the nC7H16 pilot follows the main H2 injection. Moreover, analysis of heat release rate from different stochastic fields can provide a useful indication about cyclic variability and combustion stability.

Diabetes Mellitus, Energy Metabolism, and COVID-19.

Obesity, diabetes mellitus (mostly type 2), and COVID-19 show mutual interactions because they are not only risk factors for both acute and chronic COVID-19 manifestations, but also because COVID-19 alters energy metabolism. Such metabolic alterations can lead to dysglycemia and long-lasting effects. Thus, the COVID-19 pandemic has the potential for a further rise of the diabetes pandemic. This review outlines how preexisting metabolic alterations spanning from excess visceral adipose tissue to hyperglycemia and overt diabetes may exacerbate COVID-19 severity. We also summarize the different effects of SARS-CoV-2 infection on the key organs and tissues orchestrating energy metabolism, including adipose tissue, liver, skeletal muscle, and pancreas. Last, we provide an integrative view of the metabolic derangements that occur during COVID-19. Altogether, this review allows for better understanding of the metabolic derangements occurring when a fire starts from a small flame, and thereby help reducing the impact of the COVID-19 pandemic.

Small target flame detection algorithm based on improved YOLOv7

Small target flame detection algorithm based on improved YOLOv7

The effect of impregnation with fire retardant on the properties of particleboard bonded with PF/pMDI adhesive

ABSTRACT The application of commonly used flame retardants in most cases causes reduction in strength characteristic of particleboard. Therefore, it was decided to carry out research aimed at determining possibility of using pMDI-reinforced PF adhesive to produce board with increased fire resistance. The effect of different shares of particles impregnated with a mixture of potassium carbonate and urea on the particleboard properties such as density, density profile, bending strength, modulus of elasticity, internal bond and internal bond after boiling was investigated. Presented work also determined the effect of fire retardant on the performance of particleboards after ageing test and their reaction to fire. Studies demonstrated that PF adhesive modified with 20% pMDI is suitable for gluing impregnated wood particles. Regardless of their share, resultant panels showed no changes in strength and density. In the case of boards consisting of impregnated particles in the amount of 75% and 100%, lower values of swelling were demonstrated. The boards were classified as load-bearing boards for use in humid conditions. Fire retarding efficiency was confirmed by lowered mass loss, prolonged time needed to reach maximal burning rate, decreased gross calorific value and reduced ignitability when exposed to both radiant heat source and small flame source.

Unstable flame structure adjacent to discrete wall with narrowly-ventilated air cavity

This paper investigates the interaction between a discrete non-reactive wall with a narrow ventilated cavity and a turbulent diffusion flame. The analysis is based on both experiments and large eddy simulations (LES). Firstly, the prediction is compared with experiments on two reference configurations: a continuous wall and a discrete system. The analysis was carried out to establish the validity of models to capture the boundary-layer flame and heat exchange. Overall, the predictions are in reasonable qualitative and quantitative agreement with experimental results. The article then examines the spacing effect of inert discrete elements on flame characteristics. The analysis is conducted for a vertical and horizontal layout. The orientation and spacing of the elements affect the stability of the flow structure and fire dynamics. It produces larger or smaller flames, which affect the flame-to-element heat transfer. Correlations were developed to predict flame height and heat flux. The study's findings can aid further fundamental studies to predict and mitigate the flame spread risk over such systems with combustible elements.

Flame Detection Based on Improved YOLOv7

A flame detection algorithm with improved YOLOv7 is proposed to address the problems that small targets in flame detection are easy to be missed and misdetected, and are easily disturbed by bright objects during detection. In the improved algorithm, the SE attention module is introduced to enhance the perception of the model on the channel; ConvNeXt is used to retain the features of small target flames for small targets among flame images; Employing K-means ++ clustering algorithm to gain the anchor points that match the flame size more to enhance the detection accuracy.The results testify that the improved algorithm we proposed in this paper is higher than the YOLOv7 in terms of average accuracy and precision.

A Flame-Detection Algorithm Using the Improved YOLOv5

Flame recognition is an important technique in firefighting, but existing image flame-detection methods are slow, low in accuracy, and cannot accurately identify small flame areas. Current detection technology struggles to satisfy the real-time detection requirements of firefighting drones at fire scenes. To improve this situation, we developed a YOLOv5-based real-time flame-detection algorithm. This algorithm can detect flames quickly and accurately. The main improvements are: (1) The embedded coordinate attention mechanism helps the model more precisely find and detect the target of interest. (2) We advanced the detection layer for small targets to enhance the model’s associated identification ability. (3) We introduced a novel loss function, α-IoU, and improved the accuracy of the regression results. (4) We combined the model with transfer learning to improve its accuracy. The experimental results indicate that the enhanced YOLOv5′s mAP can reach 96.6%, 5.4% higher than the original. The model needed 0.0177 s to identify a single image, demonstrating its efficiency. In summary, the enhanced YOLOv5 network model’s overall efficiency is superior to that of the original algorithm and existing mainstream identification approaches.

A numerical study on the structure and dynamics of fuel-rich premixed H2–air jet flames above a divergent micro-nozzle

In this study, the flame structures of a fuel-rich premixed H2–air mixture issued from a divergent micronozzle were numerically studied and compared with their counterparts. The flame dynamics of the divergent micronozzle at relatively low jet velocities were also analyzed. A flame pattern of “dual flames with a smaller one surrounded by a larger one” was discovered for both the straight and divergent micro-nozzles at high jet velocities. This flame structure began to appear at a lower jet velocity (Vin) as the divergence angle (θ) decreased. Specifically, it first appeared at Vin = 7.5 and 20 m/s for θ = 0° and 5°, respectively. In addition, a flame mode consisting of dual flames with a smaller one inside the nozzle occurred only for divergent micronozzles under low and medium jet velocities. This flame structure could emerge at a higher jet velocity as the divergence angle increased. For example, it could occur until Vin = 5 m/s and 17.5 m/s for θ = 1° and 5°, respectively. A global map of all flame patterns was drawn based on the results obtained by varying the jet velocity and divergence angle. Moreover, periodic flame dynamics appeared when the jet velocity was less than the critical value (<1.7 m/s). Specifically, a small flame (i.e., secondary flame) split from the jet flame (i.e., main flame) and propagated towards the nozzle inlet; however, its propagation direction was inverted and it finally extinguished owing to the heat loss to the nozzle wall. The next cycle was initiated after a short duration. The analysis revealed that the periodic flame dynamics are a result of the thermal interactions between the flame and nozzle wall.

Forest Flame Detection in Unmanned Aerial Vehicle Imagery Based on YOLOv5

One of the major responsibilities for forest police is forest fire prevention and forecasting; therefore, accurate and timely fire detection is of great importance and significance. We compared several deep learning networks based on the You Only Look Once (YOLO) framework to detect forest flames with the help of unmanned aerial vehicle (UAV) imagery. We used the open datasets of the Fire Luminosity Airborne-based Machine Learning Evaluation (FLAME) to train the YOLOv5 and its sub-versions, together with YOLOv3 and YOLOv4, under equal conditions. The results show that the YOLOv5n model can achieve a detection speed of 1.4 ms per frame, which is higher than that of all the other models. Furthermore, the algorithm achieves an average accuracy of 91.4%. Although this value is slightly lower than that of YOLOv5s, it achieves a trade-off between high accuracy and real-time. YOLOv5n achieved a good flame detection effect in the different forest scenes we set. It can detect small target flames on the ground, it can detect fires obscured by trees or disturbed by the environment (such as smoke), and it can also accurately distinguish targets that are similar to flames. Our future work will focus on improving the YOLOv5n model so that it can be deployed directly on UAV for truly real-time and high-precision forest flame detection. Our study provides a new solution to the early prevention of forest fires at small scales, helping forest police make timely and correct decisions.

Nanosecond repetitively pulsed discharges and conventional sparks of ammonia-air mixtures in a fan-stirred cruciform burner: Flammability limits and ignition transition

Ammonia, an efficient hydrogen carrier, is crucial for achieving net-zero emissions. However, its low reactivity, as manifested through small unstretched laminar flame speed (SL,0 ∼ 7 cm/s) and large laminar flame thickness (δL ∼ 2.85 mm) at atmospheric pressure and stoichiometric conditions together with narrow flammability limits, makes it difficult for initiation. As such, how to measure accurately ammonia minimum ignition energies under laminar and turbulent conditions (MIEL and MIET) and identify ammonia flammability limits are important to understand fundamental challenges and restricted usage for practical applications. We apply both nanosecond-repetitively-pulsed-discharges (NRPD) and conventional sparks (CS) via the same stainless-steel electrodes of 1-mm diameter with sharp ends at a fixed gap of 2 mm in the same fan-stirred cruciform burner to identify flammability limits of ammonia/air mixtures for spherical flame initiation. The burner is capable of generating near-isotropic turbulence having roughly equal magnitudes of r.m.s. turbulent fluctuating velocities in all three directions (u′) with negligible mean velocities. We find that NRPD operated at a pulse repetition frequency of 40 kHz can promote ignition or decrease the MIE on fuel lean and fuel rich sides as compared to that of CS. However, even using 2,000 pulses with a total ignition energy of 4.4 J for NRPD, no self-sustained flame propagation can be observed at ϕ = 0.65 and/or ϕ = 1.44 that marks lean and/or rich flammability limits for spherical flame initiation. Moreover, we also find a turbulent ignition transition for the stoichiometric ammonia/air mixture, of which the increasing slopes of MIET/MIEL versus u′/SL change drastically from gradually to exponentially at a critical value of (u′/SL)c ≈ 13 for both NRPD and CS. Finally, these results should be useful for future practical applications of premixed ammonia/air combustion.

How Phosphorous Flame Retardant Additives Affect Benzoxazine‐Based Monomer and Polymer Properties

AbstractThe phosphorous‐based flame retardant additives poly(m‐phenylene methylphosphonate) (PMP) and resorcinol bis(diphenyl phosphate) (RDP) are reacted with bisphenol F and aniline–based benzoxazine (BF‐a). DSC, rheological analysis, FT‐IR, and soxhlet extraction reveal the covalent incorporation of both FR additives—initiating phenols in PMP structure as well as free phenols generated via transesterification reaction in the case of RDP. In contrast to PMP, RDP elongates the processing window but decreases the thermo–mechanical properties. Both additives increase the resistance in reactions against small flames with solely a phosphorous loading of 0.3 wt%, resulting in a V‐0 rating and an improvement in the OI value by up to 2% for RDP and 4% for PMP. Both FRs reduce the heat release rate but increase the smoke production and the smoke toxicity in the case of RDP.