Flame Images Research Articles

Experimental and numerical study of the influence of vent burst pressure on venting characteristic of hydrogen-air explosion

Vented explosion is an effective solution to the potential security problem posed by accidental explosions during the operation of storage systems of gaseous fuels. Experimental high-speed photos, pressure histories, and numerical simulation are used to study vented explosion of the hydrogen-air mixture. This work discusses the dynamic of premixed flame propagation and the flame/vortex interaction. Large-eddy simulation turbulent combustion model is adopted to explain the interaction between flame front, turbulent flow, and pressure wave. All experiments and simulations were conducted at 298 K and 1 atm. Numerical simulation reproduces the vented hydrogen–air explosion and provides further understanding of the mechanism of external explosion. The influence of vent burst pressure on the vented explosion is also studied using simulated flame temperature, flow velocity, and pressure history. The simulation result reproduces internal pressure details accurately. Flame front propagation velocity shows four different processes in experimental and simulated flame images. The turbulent flame velocity exhibits a similar trend. The pressure rise mechanism is analyzed using the pressure curve, venting rate, and volume rate of combustion.

Influence of radial fuel staging on combustion instabilities and exhaust emissions from lean-premixed multi-element hydrogen/methane/air flames

The utilization of hydrogen-blended hydrocarbon fuels, or even completely carbon-free fuels like pure hydrogen and ammonia, will be indispensable in the effort to reduce anthropogenic carbon dioxide emissions from heavy-duty land-based gas turbines. In order to make this energy transition, however, low emissions, low dynamics fuel-flexible gas turbine combustion systems will be required. To address some of the key technological obstacles in the development of such systems, we explore a prototype multi-element injector assembly devised to prevent flashback in extremely fast premixed hydrogen flames, paying particular attention to the impact of radial dual-fuel staging on the generation of self-induced instabilities and the formation of nitrogen oxides and carbon monoxide. In conjunction with phase-averaged OH*/CH* chemiluminescence and OH PLIF flame imaging, we carry out extensive measurements over the full range of 0 to 100% H2/CH4 fuel staging conditions, including even/uneven blends of H2/CH4 fuels between inner and outer nozzle groups, partial/complete fuel split cases, and pure H2 or CH4 fuel for all constituent flames, under a constant thermal power condition of 78 kW. Our measurements demonstrate that whereas carbon monoxide concentrations are largely unaffected by the radial fuel staging conditions except under high and pure hydrogen percentage conditions, there exists a strong correlation between total nitrogen oxides emissions and overall adiabatic flame temperature. Integrated analyses of isocontour instability maps reveal that near XH2,g = 0.50 a discontinuous mode transition takes place, where the intermediate-amplitude lower frequency oscillations associated with relatively low hydrogen concentration conditions give way to stronger, higher frequency instabilities under high hydrogen content conditions. While even-blend (non-staging) conditions are characterized by coherent oscillations of the constituent flames, the responses of clustered flames to radial fuel staging conditions are eccentric and complex, manifested as large-scale asynchronous modulations between inner- and outer-stage heterogeneous reaction zones. This observation suggests that in a multi-element injector environment spatiotemporal incoherence driven by inhomogeneous heat release can be used to neutralize self-excited pressure oscillations, by disrupting pressure-heat release coupling processes.

The Characterization of Liquefied Petroleum Gas (LPG) Using a Modified Bunsen Burner

The equivalence ratio ranges were found between 22.77 and 42.93 for the Saudi LPG/air mixture using a traditional Bunsen burner. An operation problem was found with a traditional Bunsen burner for the Saudi LPG/air mixture, especially in a lean mixture. Therefore, a Bunsen burner was successfully modified to overcome the limits of operation with different mixtures of Saudi LPG/air and a stable flame was obtained. The equivalence ratio ranges were found between 0.68 and 1.30 using the modified Bunsen burner. A premixed flame was used for the modified Bunsen burner. A MATLAB algorithm was successfully applied to flame image processing and measurement of laminar burning velocity. The laminar burning velocity was determined to be approximately 35 ± 0.91 cm/s under stoichiometric conditions using the modified Bunsen burner for the Saudi LPG/air mixture. The half-cone angle of the flame was found to be 16.20 ± 0.76°. The minimum flame height was observed to be 21.50 ± 0.22 mm above the Bunsen burner exit.

Experimental investigation of effects of pulsed injection on flow structure and flame development in a kerosene-fueled scramjet with pilot hydrogen

The effects of pulsed injection on the flow structure and flame development in a scramjet were investigated experimentally with a pilot hydrogen equivalence ratio (ER) of 0.1 and a kerosene ER of 0.3; the pilot hydrogen was used to enhance the kerosene combustion. In the steady injection flow, the non-reacting flow structure changed periodically, and the monitor pressure built up rapidly when the pilot hydrogen self-ignited at t = 0.0096 s, increasing from 0.03 to 0.037 MPa. The pilot flame was stable and filled the whole cavity until the kerosene began to be injected into the combustor at t = 0.05 s; the kerosene combustion occurred only in the cavity shear layer. After a very short time, the pilot flame was blown off by the kerosene. In the pulsed injection flow, the kerosene kept burning with the help of the pilot flame, and the monitor pressure remained at a high value that was about six times that in the non-reacting flow. The mixture of pilot hydrogen and kerosene flame could propagate into the isolator, which was discontinuous and a distinct fault could be seen in the flame images. The kerosene combustion under pulsed injection was very intense, and even when the pilot hydrogen was removed, the cold room-temperature kerosene could still burn steadily for some time. Comparing with the flame development process under steady injection conditions, it is concluded that pulsed injection helps greatly to realize kerosene ignition and stable combustion.

CCTV 기반 화염의 특성과 밀도 기반 공간 클러스터링을 이용한 화재 감지 방법

In this study, we propose fire detection method using CCTV-based flame features and density-based spatial clustering with noise (DBSCAN). To do this, first, the 1st candidate region using the color of the flame image is extracted and the 2nd candidate region using the high-frequency region and background removal is extracted. Next, the extracted 1st candidate region and 2nd candidate region are merged, and the clustering region is extracted using DBSCAN. And then, the method for judging flame and rhinitis through the number of blocks passing through the movement trajectory of the central point of the clustering region extracted using DBSCAN is proposed. Finally, the applicability of the method proposed in this paper is reviewed through experiments in indoor and outdoor environments.

In-situ measurements of temperature and emissivity during MSW combustion using spectral analysis and multispectral imaging processing

By using a novel multispectral imaging technology, the 2-D distributions of flame temperature and emissivity were measured in a 16 MW incinerator to co-fire municipal solid waste (MSW) and municipal sludge. A way to establish the relationship between the multispectral flame images and the temperature was proposed by combing the Newton iteration method and Hottel emissivity model. The results showed that the measured temperatures at different locations varied by 31.25% with a fixed steam evaporation rate, and 11.76% with different steam evaporation rates at a given port. The temperatures and emissivities decreased at upper locations due to the lower local soot particle concentration and the change of the measured flame temperatures with load were correlated with the MSW caloric values. Flame temperatures near the left wall were higher than those near the right wall. This deviation was caused by the high moisture content of municipal sludge that inhibited combustion. The emissivities of flame near the right wall were lower than those near the left wall due to the low fixed carbon in municipal sludge. The normalized flame emissivities between the left and the right walls indicated that obvious differences existed in the radiative characteristics of soot, which confirmed the uneven mixing of MSW and municipal sludge. Besides, a spectrometer system was used to measure the release of alkali metal elements including Na, K during the incineration process. The characteristic spectra showed that the alkali metal radiative intensity was related to the moisture content in the wastes. Overall, these results justified that the multi-wavelength thermometry was feasible for monitoring combustion in the MSW incinerator.

4D imaging of turbulent flames with improved multi-camera calibration method and processing speed

4D imaging measurements in turbulent flames have been long desired to better understand the complex phenomena involved in the combustion process. Such 4D measurements provide the information of turbulent flames in all three spatial coordinates and time sequences. Tomographic reconstruction has been recently demonstrated as a promising approach for 4D flame diagnostics. However, two critical issues remain in the current 4D tomographic measurements: the accuracy of multi-camera calibration and the processing time of the tomographic program. Therefore, this work aims to address the two issues by developing a new multi-camera calibration method and a parallel tomographic reconstruction program. As shown in this work, the new multi-camera calibration method can significantly improve the angle calibration accuracy; and the parallel program reduces the processing time for 1000 tomographic reconstructions from 10 days to ~12 h. Such enhanced accuracy and processing speed are expected to benefit a range of combustion researches, and a specific example is demonstrated involving 4D imaging of a subsonic diffusion flame.

Combustion analysis of higher order alcohols blended gasoline in a spark ignition engine using endoscopic visualization technique

The experimental study was carried out on the port fuel injection system installed spark-ignition engine fuelled by 1.5%, 3%, and 5% higher order alcohol such as 1-hexanol and 2-heptanol blended gasoline. In this study, the endoscopic combustion visualization technique was employed to compare and analyze the changes observed in the spatial flame characteristics between the alcohol blends and sole gasoline. The Correlated Colour Temperature (CCT) method was used to predict the flame temperature distribution from the captured flame images. Also, the effect of blending alcohols on engine combustion, performance, and emission characteristics was studied. The endoscopic results revealed that the flame spread region with respect to different CA positions increases with the alcohol blending ratio in the sole gasoline at the early and middle stages of the combustion. Further, the engine characteristics study revealed that 5% hexanol and heptanol blends gave a brake thermal efficiency of 25.8% and 25.7%, respectively, which were higher than sole gasoline, having 24.8% at full load. In addition, it was observed that the early start of combustion (SoC) and a faster burn rate associated with alcohol blends raise the cylinder pressure and heat release rates (HRRs) and thereby result in higher peak pressure and HRR with slight advancement in the CA position. At 8 kW, the CO and HC emission of 5% 1-hexanol and 2-heptanol blends was decreased by about 10.3% and 13.7%, and 9.5% and 8%, respectively, and NO emission decreased slightly with a rise in alcohol concentration in the mix when compared to gasoline.

Numerical Simultaneous Determination of Non-Uniform Soot Temperature and Volume Fraction from Visible Flame Images

This paper presents a method to invert the two-dimensional distribution of a temperature and volume concentration of soot particles from color images. By using numerical simulation, the temperature field and particle volume-concentration field of a non-uniform soot flame are simultaneously reconstructed using the wide-response spectrum of a color CCD camera without adding monochromatic filters. The influence of number of cameras, error of camera position angle, measurement noise and different reconstruction algorithms on measurement accuracy are analyzed. The numerical-simulation results demonstrate that camera-position angle errors play a crucial role in the reconstruction accuracy. In addition, increasing the number of cameras can improve the reconstruction result accuracy. Compared with the least squares algorithm, the Tikhonov-regularization algorithm has a stronger anti-noise ability and can resist 39 dB of noise. The conclusions obtained in this paper are helpful to guide following experimental studies.

Industrial IoT Enabled Fuzzy Logic Based Flame Image Processing for Rotary Kiln Control

Industrial IoT Enabled Fuzzy Logic Based Flame Image Processing for Rotary Kiln Control

Research on flame recognition technology based on local complex features

Traditional flame recognition methods based on image features are difficult to extract flame image features effectively, resulting in low flame recognition accuracy, while such methods mostly perform specific flame recognition for specific scenes, and when the scene, flame color and other features change, it is difficult to perform flame recognition effectively. To address this problem, this paper proposes a flame recognition scheme based on local complex features. Its main purpose is to fuse multi-scene flame data, introduce the characteristics of flame in color space through the process of extracting feature descriptors in SIFT, so as to filter the extracted feature descriptors with noise interferers, and transform the extracted feature descriptors into feature vectors by using the key point bag-of-words method, and finally a general fast flame recognition model based on the limit learning machine. In this paper, we explore the upper limit of the capability of traditional image feature representation to pave the way for the application of deep learning to the flame recognition problem.

Fast stochastic configuration network based on an improved sparrow search algorithm for fire flame recognition

Flame image recognition is of great significance in the fire detection and prevention. In this paper, in order to improve the accuracy of fire recognition, a fast stochastic configuration network (FSCN) method based on an improved sparrow search algorithm (ISSA) is proposed. In the design of fast stochastic configuration network (FSCN), the gradual increase of hidden layer nodes in the original stochastic configuration network (SCN) is canceled, and the number of them is set directly. An improved sparrow search algorithm (ISSA) is used to generate the input weights and biases of hidden layer nodes. At the same time, the supervisory mechanism is retained to judge the weights and biases of all hidden layer nodes, and ISSA is used to regenerate corresponding weights and biases for the nodes that do not meet the constraints in the supervisory mechanism. In the ISSA, sine map, adaptive adjustment of hyper-parameters and mutation strategy are used to improve the optimization ability of the original sparrow search algorithm (SSA). Some parameters in FSCN are optimized by ISSA to make it have better classification performance. Finally, the image processing technology is used to extract features from the flame images and the interference images, and then the feature vectors are obtained to train the ISSA-FSCN. Several simulation experiments have been carried out to verify effectiveness of the proposed ISSA-FSCN method. In the performance verification of ISSA on CEC test suit, ISSA averagely outperforms other algorithms by 33.6% in the average results of 20 functions. In the performance verification of FSCN, the average results of accuracy, precision, recall, F1 and auc are compared. In the experiment 1, ISSA-FSCN averagely outperforms other algorithms by 19.7%, 14.7%, 12.8%, 14.5% and 23.0%. In the experiment 2, ISSA-FSCN averagely outperforms other algorithms by 2.3%, 2.1%, 2.5%, 6.0%, 3.2%. In the experiment 3, ISSA-FSCN averagely outperforms other algorithms by 5.9%, 4.0%, 4.1%, 4.1%, 6.8%.

Horizontal solid burning under laminar forced convection and turbulent buoyant convection with an unheated segment

In this paper, the effect of an unheated starting length, L0 varying between 0 and 30 cm, on the burning and heat transfer characteristics over a horizontal Poly (methyl methacrylate) flat plate is experimentally investigated under wind velocities ranging from 0.5–2.0 m/s. The flame images, flame standoff distance, and Nusselt number are measured or calculated. In comparison to the wind velocity, the effect of an unheated starting length is of first-order importance in influencing the flow, heat transfer, and combustion over a solid fuel surface. The unheated segment introduces unique streamwise streaky flames. A critical condition is found to exist at L0 = 10 cm, where the spanwise wave and lattice structures are observed in the flame, causing the standoff distance and Nusselt number to increase markedly beyond the theoretical prediction. When the unheated segment exceeds a certain length, the increased unheated length effect becomes negligible. Furthermore, the unheated segment shortens the laminar forced convection region and broadens the turbulent buoyant convection region. The study provides very crucial information regarding the effects of an unheated segment on the transitioning mechanism of a wind-driven flame which might be useful and important for fire research.

Effect of CO2/H2O addition on laminar diffusion flame structure and soot formation of oxygen-enriched ethylene

Oxygen-enriched combustion technology has an important application prospect, in which Oxy-steam combustion is a new generation of potential carbon capture technology. In this paper, the effects of O2/CO2 and O2/H2O atmosphere on soot formation in laminar diffusion flame were studied. The flame image was taken by a color (CCD) camera in the visible band, the directional emission power in R and G bands was calibrated, and the two-dimensional distribution of temperature and soot volume fraction in the flame was reconstructed. The experimental results are compared with the numerical results, and the numerical results well predict the temperature of oxygen-enriched flame in O2/N2/CO2 atmosphere, but overestimate the soot volume fraction. The laminar diffusion flame of ethylene in two kinds of oxygen-rich atmosphere was numerically studied by using a step-by-step decoupling method to separate the density, transport, thermal and chemical effects of the diluent by introducing four virtual substances. The calculation results show that combustion in O2/H2O and O2/CO2 atmosphere reduces the flame peak temperature, but the effect on the flame centerline temperature distribution is different. The addition of H2O enhanced the concentration of OH through the reverse reaction rate of OH + H2=H + H2O, while the addition of CO2 decreased the concentration of OH.O2/CO2 combustion leads to the increase of flame height and radius, while in O2/H2O atmosphere, the flame height is shortened. Both CO2 and H2O have a good inhibitory effect on soot formation. CO2 in the oxidant affects soot nucleation and surface growth rate mainly by reducing flame temperature and H mole fraction, but not by promoting soot oxidation process. Water vapor also inhibits soot formation by increasing OH concentration through chemical effect.

Comparison of the flame dynamics of a premixed dual fuel burner for kerosene and natural gas

In this study, the flame dynamics of swirl stabilized lean premixed combustion is investigated for kerosene and natural gas operation. A natural gas swirl burner is retrofitted with a twin-fluid nozzle to allow performing all experiments with the identical burner hardware. The mixture preparation complexity is stepwise increased from perfectly premixed natural gas to technically premixed natural gas and lastly technically premixed kerosene combustion. Flame transfer functions (FTFs) for the three configurations are presented and compared with each other. This approach allows to experimentally decompose the FTF and isolate the contributions of equivalence ratio fluctuations and droplet dynamics. Furthermore, FTF data for a systematic variation of equivalence ratio and air mass flow in kerosene operation is presented and the impact of spray quality and convective delay time on the FTF is discussed. For all operation points, stationary flame images are provided and evaluated as basis for the FTF interpretation. Additionally, NO emissions are measured in order to determine the degree of premixing in kerosene operation. Through a systematic FTF comparison, it was found that the frequency range in which droplets react to acoustic forcing can be read from the FTF phase. The spray quality was found to have a significant impact on the FTF whereas a change in the convective delay time does not affect the FTF.

Combustion and emission characteristics of premixed biogas mixtures: An experimental study

In this study, effects of fuel composition, swirl number and hydrogen addition on combustion and emission characteristics of various biogas mixtures were experimentally investigated. To this end, a laboratory scale combustor and a swirl stabilized premixed burner were designed and manufactured. Later on, this combusting apparatus was equipped with flow, control, safety and measurement tools, hence entire test system was constituted. Combustion and emission characteristics of tested biogas mixtures were determined by measuring temperature and species (CO 2 , CO, O 2 and NO) distributions throughout the combustion chamber. Additionally, flame structures of tested biogas mixtures were evaluated by examining flame luminosity, visible flame length and flame thickness from instantaneous flame images. Results of this study showed that both radial and axial temperature distribution variations of tested biogas mixtures differently alter with hydrogen addition based on the gas composition. Although flame temperature increases with swirl number at burner outlet, it presents a non-monotonous dependence on swirl number outside the flame region because of the modified flow characteristics. This is also the case for emissions of CO 2 . • Premixed combustion characteristics of various biogas mixtures were investigated. • Gas composition, swirl number and hydrogen addition effects were examined. • Hydrogen addition differently altered temperature distribution based on the gas composition. • Flame temperature presented a non-monotonous dependence on swirl number.

Investigation of in-cylinder soot formation in a DISI engine during transient operation by simultaneous endoscopic PIV and flame imaging

A single-cylinder full-metal engine with a real combustion chamber geometry was used to investigate particulate number emissions resulting from transient engine operation. The formation of particulate number emissions depends on mixture formation influenced by the in-cylinder flow and injection, and the formation of fuel films on the in-cylinder walls. For the investigation of this multi-parameter process, simultaneous endoscopic PIV and combustion visualization were applied. Hence, the measurement techniques allowed the investigation of in-cylinder flow, flame propagation, and soot formation. The test rig was modified to apply a generic load step and a realistic tip-in with Miller cycle. The reproducibility of the engine parameters during the transient allowed statistical analysis and the comparison between steady-state operating points. Cause-and-effect chains concerning the formation of soot are concluded by correlation analysis of parameters extracted from the flow field, the flame propagation and the soot luminosity.

Effect of background turbulent field on ion current characteristics of methane-air premixed combustion

Ion current detection technology has a broad application prospect in natural gas engines. The effect of background turbulent environment on ionic current characteristics of methane - air mixture premixed combustion needs further study. The premixed combustion of methane-air mixtures under different turbulence intensities was studied on the constant volume combustor with controllable turbulence intensities. The effects of turbulence intensity on flame image, combustion pressure and ion current signal during combustion were analyzed. The ion current calculation model was built by coupling Cantera chemical reaction calculation program in the MATLAB environment. The variation of the concentration of the main species under different conditions was analyzed and the ion current signals under different turbulent conditions were simulated. The results show that in turbulent environment, the flame front appears fold and cellular structure, which increases the flame front area and accelerates the combustion speed. With the increase of turbulence intensity, the peak of combustion pressure increases and the peak time is advanced. The ion current appeared earlier in turbulent environment, and the duration of ion current decreased with the increase of turbulence intensity. When the equivalent ratio is near 1, the species concentration change greatly due to the influence of incomplete combustion. The concentration of species except water and carbon dioxide increases with the increase of temperature. The ion current calculation model can predict the overall trend of ion current signal in turbulent premixed combustion, but the simulation results of ion current signal in the later stage of combustion are too large.

Inhibition of Four Inert Powders on the Minimum Ignition Energy of Sucrose Dust

In order to evaluate the effect of inert powder on the ignition sensitivity of sucrose dust, this study investigated the effects of NaHCO3, NaCl, NH4H2PO4 and Al(OH)3 on the minimum ignition energy (MIE) of sucrose dust. The results showed that all four different inert powders inhibited the MIE of sucrose dust, and all of them showed a trend that the smaller the particle size of the inert powders, the better the inhibition effect. The inhibition effect was ranked as NaHCO3 > NH4H2PO4 > NaCl > Al(OH)3. NaHCO3 and NH4H2PO4 had both physical and chemical inhibition effects, which were better compared to NaCl and Al(OH)3, which had only physical inhibition effects. Analysis of the flame images showed that the inert powder slowed down the combustion of the sucrose dust flame and reduced the flame height. No flame appeared in the region of higher inert powder concentration.

Recognition of Distributed Combustion Regime From Deep Learning

Abstract Swirl-assisted distributed combustion was examined using a deep-learning framework. High intensity distributed combustion was fostered from a 5.72 MW/m3 atm thermal intensity swirl combustor (with methane fuel at equivalence ratio 0.9) by diluting the flowfield with carbon dioxide. Dilution of the flowfield caused reduction of global oxygen (%) content of the inlet mixture from 21% to 16% (in distributed combustion). The adiabatic flame temperature gradually reduced, resulting in decreased flame luminosity and increased flame thermal field uniformity. Gradual reduction of flame chemiluminescence was captured using high-speed imaging without any spectral filtering at different oxygen concentration (%) levels to gather the data input. Convolutional neural network (CNN) was developed from these images (with 85% of total data used for training and 15% for testing) for flames at O2 = 16%, 18%, 19%, and 21%. Hyperparameters were varied to optimize the model. New flame images at O2 = 20% and 17% were introduced to verify the image recognition capability of the trained model in terms of training image data. The results showed good promise of developed deep-learning-based convolutional neural network or machine learning neural network for efficient and effective recognition of the distributed combustion regime.