Flame Characteristics Research Articles

Experimental study on the equivalence ratio effects in ammonia–hydrogen–air premixed gas duct-vented explosions

To explore the combustion characteristics of ammonia‒hydrogen‒air flame, explosion venting experiments of ammonia‒hydrogen‒air mixtures with different equivalence ratios (ϕ), in the range of 0.6–1.7, are carried out in a 2 m long duct. The results show that the pressure‒time histories inside the duct have a three-peak structure (Pb, Pout, and Pext), which is caused by the burst of the vent cover, venting of burned mixtures, and counterflow flame generated by the external explosion, respectively. Pout evolves into three pressure peak types with increasing ϕ. The pressure peak value Pe is generated at the pressure measuring point outside the duct because of the external explosion. The change in Pe with ϕ is consistent with Pout and Pext, all of which increase first and then decrease with increasing ϕ and reach a maximum value at ϕ = 1.3. This study provides basic theoretical support for the promotion and application of ammonia mixed fuel.

Prediction of combustion pressure with deep learning using flame images

Deep learning methods provide data-driven techniques for handling large amounts of combustion data, thus finding the hidden patterns underlying these data. This study aims to predict combustion pressure from flame images, which provide more comprehensive information about the combustion process than traditional pressure sensors. The flame images were captured from a single-cylinder 4-stroke optical gasoline direct injection (GDI) engine at 1000 rpm, 5.7 bar IMEP, and stoichiometric combustion conditions using a high-speed camera. To achieve this prediction, we employed five different models: EfficientNetB4, ResNet50, Ensemble Adversarial Inception ResNet, convolutional neural network (CNN), and CNN-XGBoost. The training dataset comprised 1350 flame images captured from a single-cylinder optical GDI engine across different combustion stages. To ensure robustness, 150 images were used for validation. The models were subjected to a testing set of 4500 flame images obtained from different cycles, to evaluate how well they could perform on new, unseen data. The results showed that EfficientNetB4 achieved an impressive R2 of 0.94 and a low RMSE of 0.70 compared to other tested models. Saliency analysis revealed that the model focuses on subtle flame characteristics and areas without intense flames, which suggests that it detects features invisible to the human eye. Additionally, the proposed deep learning approach is applied for the sake of monitoring cycle-to-cycle variations based on in-cylinder flame propagation where it is found that it produces high accuracy compared to those obtained through pressure sensors. Our findings are intended to advance the adoption of machine learning approaches for assisting in engine design and optimization.

Influence of magnetic field on renewable oil flame characteristics-an experimental and image processing analysis with bibliometric study

This study investigates the influence of a magnetic field on the flame characteristics of waste cooking oil. A circular current-carrying coil was used to generate magnetic fields of varying strengths (131.37 G, 234.19 G, 337.07 G, 394.12 G, and 428.39 G), corresponding to different voltages (0–10 V). Flame behavior was captured with a digital camera, both without a magnetic field and under varying field strengths. Flame height and area were analyzed using ImageJ and MATLAB's Image Processing tools. Additionally, the thermal properties and fatty acid composition of the waste cooking oil were examined. Results indicated that the flame height increased by 11.06 % under the strongest magnetic field compared to the baseline. The flame area initially expanded due to magnetically induced diffusion but later decreased as the flame stabilized and turbulence reduced. A strong correlation was found between the flame area estimations from ImageJ and MATLAB.

Large Eddy Simulation of Ammonia-Hydrogen Non-Premixed Flames Stabilized on a Bluff Body Burner

Abstract The demand for carbon-free fuels such as NH3 and H2 has been growing due to stricter environmental policies on carbon emissions. Since ammonia is easier to store and transport, it is considered an alternative fuel for marine, aviation, and gas turbine industries. However, the narrow flammability, low reactivity, and potential emissions of NOx are important challenges that need to be overcome if ammonia is to be used as a practical fuel for industrial use. Recent works have provided experimental data on the characteristics of NH3 flames under premixed and non-premixed combustion, focusing on flame speed, turbulence-chemistry interaction, and especially the dissociation/cracking of NH3 into H2 and N2. These measurements have encouraged the use of CFD for the simulation and scaling of practical ammonia systems, evaluating the performance of different numerical models for NH3 combustion. In this study, LES is utilized to predict a series of NH3/H2/N2 non-premixed flames stabilized on a bluff body burner. The accuracy of the FGM combustion model combined with LES has been examined, using a commercial CFD solver. The different cracking levels of NH3 into H2 and N2 lead to simulation cases ranging from an H2/N2 flame (i.e., “fully cracked”), to a flame with 50% NH3 (i.e., “half cracked”). The different flame shapes, temperature distributions, and NOx emissions have been simulated, generally matching well experimental data. The developed numerical settings and workflows may be applied to simulating more complex combustors which use NH3 as a fuel.

Experimental study on the effects of n-butanol and n-propanol on the spray and combustion characteristics of diesel/biodiesel blends in a constant volume combustion chamber

The depletion of fossil fuel resources and the escalating environmental impact of greenhouse gas emissions have intensified the global exploration of renewable and sustainable energy sources. Biodiesel produced from vegetable oils and animal fats has become a promising alternative to conventional diesel fuel due to its renewability and lower carbon emission. This study investigates the differences in spray, combustion and flame characteristics between soybean-based biodiesel blended with propanol and butanol at various ratios. The results indicate that the liquid spray penetration length of biodiesel mixed with propanol and butanol exceeds that of soybean-based biodiesel. And the increase of spray penetration is accompanied by a longer flame lift-off length, which indicates the improvement of spray characteristics. Regarding combustion, alcohol-fuel blends exhibit a reduction in peak combustion pressure but an increase in peak apparent heat release rate. Additionally, these fuels show a shorter ignition delay and combustion duration. The peak natural flame luminosity is lower for alcohol fuels, suggesting their potential to reduce carbon soot production and support low-carbon combustion. These experimental results contribute to advancing research on cleaner, more efficient and renewable fuels, thereby reducing reliance on conventional fossil fuels.

Advanced Multi-Label Fire Scene Image Classification via BiFormer, Domain-Adversarial Network and GCN

Detecting wildfires presents significant challenges due to the presence of various potential targets in fire imagery, such as smoke, vehicles, and people. To address these challenges, we propose a novel multi-label classification model based on BiFormer’s feature extraction method, which constructs sparse region-indexing relations and performs feature extraction only in key regions, thereby facilitating more effective capture of flame characteristics. Additionally, we introduce a feature screening method based on a domain-adversarial neural network (DANN) to minimize misclassification by accurately determining feature domains. Furthermore, a feature discrimination method utilizing a Graph Convolutional Network (GCN) is proposed, enabling the model to capture label correlations more effectively and improve performance by constructing a label correlation matrix. This model enhances cross-domain generalization capability and improves recognition performance in fire scenarios. In the experimental phase, we developed a comprehensive dataset by integrating multiple fire-related public datasets, and conducted detailed comparison and ablation experiments. Results from the tenfold cross-validation demonstrate that the proposed model significantly improves recognition of multi-labeled images in fire scenarios. Compared with the baseline model, the mAP increased by 4.426%, CP by 4.14% and CF1 by 7.04%.

Mathematical modeling and model predictive control research on coal powder burners for aggregate dryers

Aggregate drying is a crucial step in asphalt mixture production. Enhancing the model accuracy and controller performance of aggregate dryer burners is essential for consistent flame characteristics, reducing NOx emissions, and minimizing fuel consumption. This paper introduces a second-order nonlinear parametric model for coal powder burners that includes delay and noise. Model parameters were determined through experimental data using the Salp Swarm Algorithm, showing higher accuracy than models based on the least square method. A dual-layer model predictive control (MPC) based on this mathematical model was developed to improve the economic efficiency of the aggregate drying process. Simulation results showed that the dual-layer MPC saves 1.08 tons of coal every 10 h compared to a standard MPC. A full-scale prototype demonstrated average flame length, flame temperature, and NOx emissions of 4242.6 mm, 1729.4 °C, and 460.2 mg/m³, respectively, validating the accuracy of the proposed mathematical model and controller.

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.

Experimental and numerical study of H[formula omitted] enrichment on swirl/bluff-body stabilized lean premixed n-butane/air flame

This study focused on the stabilization of lean premixed flames of n-butane/H2/air with swirl/bluff-body. The research explored four different hydrogen fractions (0, 20%, 40%, and 80%) at a constant equivalence ratio and Reynolds number. The turbulent reacting flow was resolved using a combination of Delayed Detached Eddy Simulation (DDES) and Flamelet Generated Manifold (FGM) model. The velocity fields and reaction zones were obtained through Particle Image Velocimetry (PIV) and OH* chemiluminescence measurements respectively. H2 addition to n-butane significantly enhanced flame characteristics. The chemiluminescence imaging showed that the flame base became stronger with increasing hydrogen addition, reducing the risk of flame lift-off. Hydrogen addition not only increased the overall reaction rate but also changed the combustion intensity at the nozzle exit from weak to strong, which is crucial for flame stabilization. Interestingly, no flashback was observed even at 80% H2 addition to n-butane at the same level of power rating. The flow strain rate analysis of the PIV measurements showed that the inclusion of hydrogen skewed the strain rate probability density functions towards the positive side, indicating an increase in the burning rate. The results demonstrate a progressive increase in preferential diffusion of H2 from reactants to products as the H2 enrichment in the fuel rises and resulted in a more intense flame. Also, the present simulation results were validated with the PIV data, and they showed good agreement. Specifically, an 80% H2 blend exhibited a 16% peak enhancement in flame surface density compared to pure n-butane while concurrently reducing CO2 emissions by 23.2%. The incorporation of H2 also led to the increased vortex strength and strain rate within the flame.

Effects of Fuel Bed Slope and Wind Direction on Flame Spread Characteristics Over a Bed of Pinus Silvestris Needles

ABSTRACT Important factors influencing the flame characteristics over a bed of dry pine needles from Siberian Boreal forests (Pinus silvestris) in lab-scale is provided. Factors such as slope of the fuel bed, wind velocity, and direction of spread (concurrent flow or opposed flow), which play significant roles in determining the flame spread rate, have been investigated. Systematic lab-scale experiments have been carried out in a wind tunnel with varying air velocities and on an inclined fuel bed in still air. Numerical simulations have been carried out using a three-dimensional physics-based flame spread model available in Fire Dynamics Simulator, and the results are validated against a wide range of measured flame characteristics. The validated numerical model is then used to simulate concurrent flow and opposed flow flame spread over a sloping fuel bed in the presence of wind. Gas phase temperature on and above the bed surface and total and radiative heat flux measurements for concurrent flow and opposed flow flame spread under the influence of wind as well as for upslope flame spread in still air are presented. A stationary flame propagation mode is observed for a flat fuel surface. Predicted temperature, flow, and species concentration fields have been reported for selected cases to understand the flow and flame dynamics in gas phase and within the fuel beds. These data serve as a validation of the numerical model used for simulating the experimental cases. Further, it can be used to validate popular fire models such as Fire Foam and Fire-Star 3D.

Local Burning Behavior of Wind-Driven Flames under the Influence of Mixed-Convective Turbulent Flow Conditions

ABSTRACT Experiments were conducted to investigate the burning behavior of wind-driven turbulent flames stabilized over a condensed fuel surface. A controlled turbulent crossflow environment was established to examine the impact of external flow velocity and turbulence intensity on the flame profile parameters and mass burning rates. To address the complexities of practical fire scenarios, a mixed-convection parameter ξ x in the form of G r x 1 / ψ x 2 n was defined, encapsulating the combined effects of momentum, buoyancy, and freestream turbulence. Furthermore, the property of fuel (in terms of mass transfer number B) was integrated into the mixed-convection parameter ( ξ x ) to establish a fuel-dependency factor within the formulation . The interdependence of flame characteristics and the mass burning process was observed using ξ x , that yielded several meaningful correlations. In this regard, a power-law trend was obtained between flame standoff distance and the dimensionless parameter ξ x . Finally, the local mass burning rates were estimated and plotted against mixed-convective parameter ( ξ x ), resulting in a unified local mass burning rate correlation. This correlation incorporates the fuel-dependency aspect in its formulation and is applicable in both laminar and turbulent crossflow environments.

Effects of a 3D-Printed Atomizer Component on Fuel-Spray and Flame Characteristics of a Jet-Stabilized Compact Gas Turbine Combustor Fed With Liquid Fuels

Abstract In this work, the effects of replacing an atomizer component of a confined jet-stabilized gas turbine combustor with a 3D-printed part have been studied. The part is called airblast, and it serves as a wall that collects and flows liquid droplets for a secondary atomization. Therefore, the liquid-surface interaction on the rough surface of the 3D-printed part was of interest. The combustor was operated under various conditions with either a conventionally machined airblast or the 3D-printed airblast. Flames with two liquid fuels were studied for fuel flexibility, and the position of a primary fuel injection was varied to study the influence of the liquid-surface interaction length. Load flexibility was investigated with air jet velocity settings, and flame equivalence ratios of ϕ = 0.8 and 1.0 were tested. Shadowgraphy-based particle tracking analyses presented a reduced atomization performance with the 3D-printed airblast, showing large droplet size distributions. However, no significant change in the combustor performance was observed from OH* chemiluminescence images and emission data, which confirms the versatility of the combustor and assures the compatibility of 3D-printed components with the combustor of this study.

The influence of radiation modeling on flame characteristics and emissions prediction in microcombustors with Ammonia/Hydrogen blends

This study advances numerical methodologies for designing microcombustor-based thermophotovoltaic systems by incorporating comprehensive analyses of radiation models and absorption coefficients. It examines the impact of non-premixed hydrogen-ammonia-air fuel blends on the micro combustion process using three-dimensional CFD simulations on a Y-shaped microcombustor under atmospheric conditions.Key to this research is modeling radiative heat transfer from multiple species, including ammonia (NH3), nitric oxide (NO), and water vapor, ensuring accurate predictions and optimization of thermal behavior and efficiency. Three modeling approaches were compared: a multispecies Planck-mean approximation radiation model (PMAC), a narrowband model for water vapor, and a scenario excluding radiation effects.The PMAC model, incorporating the absorption coefficients of ammonia and its products, consistently produced lower errors in flame length compared to the NB method across all equivalence ratios, with errors ranging from 0 % to 7 % for PMAC and 10 % to 30 % for NB, with the lowest error observed at Φ = 1.0. Additionally, the prediction of laminar burning velocity (LBV) differed by approximately 4 % between the two models.Considering different fuel blends, two scenarios were compared: constant input thermal power and constant fuel flow rate. Efficiency in the constant input thermal power scenario maintained higher radiation efficiency, in the range of 32–38%. Additionally, radiation efficiency initially increased with increasing H2 content but subsequently decreased for high H2 values due to effects on flame area, flame position, and temperature.

Experimental Study of Natural Gas and Hydrogen Co-Firing Characteristics Using Different Types of Single Nozzles of F-Class Practical Gas Turbine Combustors

Abstract Recent research on co-firing natural gas and hydrogen, a carbon-free clean fuel, aims to reduce greenhouse gas emissions from aging gas turbine power generation, a key energy issue. This approach can enhance old gas turbines and increase the proportion of combined cycle power plant utilization as coal-fired power plants in Korea gradually shut down. This study seeks optimal operating conditions for mixed fuels without modifying the F-class gas turbine combustor. Experiments were conducted using four different types of fuel nozzles (F-Class DLN combustors) under varying loads and co-firing rates. The test used actual machine operating conditions from 30% to 100% thermal load, with hydrogen co-fired with natural gas up to 70% at each load. OH high-speed imaging and an OH-PLIF technique analyzed flame structure and characteristics. Dynamic pressure was measured to check combustion instability, and exhaust gas emissions were evaluated for combustion characteristics. Key findings include critical co-firing rates for each nozzle based on NOx emission levels and combustion dynamics. As the hydrogen co-firing rate increased, flame length decreased, and NOx levels rose rapidly beyond 30%vol. Dynamic pressure oscillations showed no significant variations compared to natural gas combustion. This study successfully derived a characteristic operation map for a single nozzle based on the hydrogen co-firing rate.

Comparative study on the local hybrid combustion characteristics of the CH4-NH3 laminar premixed flames with/without the wall effects

The CH4-NH3 (50%:50%) premixed flame with/without the wall effects are simulated and compared at the stoichiometric condition in this study. The effects of cold wall and local flame dynamics on the flame temperature, heat release rate (HRR), CH4/NH3 oxidations and local CO/NO formations are analyzed quantitatively. Results show that the flame temperature and HRR are decreased and increased respectively along the flame front towards the axis of free flame, but they are both declined significantly towards the wall owing to suppressed chemical kinetics by the heat loss. The negative flame stretch and differential diffusion at the flame tip suppress the CH4 oxidation and the fast path (NH3→NH2→NH→N2) of NH3 oxidation effectively, but affect the slow path (NH3→NH2→HNO→NO→N2) of NH3 oxidation moderately. This contributes to suppressed CH4/NH3 oxidations and improved NO production at the flame tip of free flame. Based on NRR variations and ROP analysis, compared with CH4 oxidation, wall heat loss exerts stronger suppressions on the fast path of NH3 oxidation, while it decelerates the slow path of NH3 oxidation less evidently. Since the fast path is the primary pathway of the NH3 oxidation, the NH3 oxidation suffers more effective suppression of the wall heat loss than the CH4 oxidation. Furthermore, considering the significance of the slow path to the NO formation, the relatively enhanced importance of the slow path to the NH3 oxidation in the near-wall region predominates the comparatively effective NO formation in the CH4-NH3 flame compared with the pure CH4 flame under the influence of wall heat loss. For the CO/NO formations, the local CO production/oxidation in the wall-impinging CH4-NH3 flame are decelerated simultaneously due to the strong heat loss, while the local NO production/destruction are inhibited/improved by the wall heat loss.

Neodymium oxide concentration state recognition model in neodymium molten salt electrolysis process based on flame image features

Accurate recognition of the concentration state of neodymium-oxide (Nd2O3) in the neodymium (Nd) molten salt electrolysis process provides crucial feedback information for online adjustment of process parameters during Nd metal batch production. This paper proposes a Nd2O3 concentration state recognition model based on flame image features. The model employs the lightweight flame segmentation algorithm (FEC-Net) to accurately segment the flame regions in the collected Nd electrolysis cell flame images. Then, using image processing techniques, geometric and color features of the flame regions are extracted. Finally, a Support Vector Machine (SVM) is used to establish a nonlinear mapping model between the flame features and Nd2O3 concentration states. This model classifies the collected flame image dataset to verify the Nd2O3 concentration state during a certain period of Nd molten salt electrolysis. Experiments demonstrate that the recognition accuracy of SVM reaches 96.09%, meeting the monitoring requirements of the Nd molten salt electrolysis process.

Numerical analysis of thermal mechanism in downward flame spread over inverted surfaces of discrete inclined solid fuels

This investigation is propelled by engineering challenges associated with heat transfer during fire incidents on inclined surfaces, such as those observed in pitched roof fires, which hold significant implications for fire safety engineering and energy conservation. Drawing inspiration from real-world fire dynamics, this study delves into the downward flame spread over inverted solid fuel surfaces across a range of inclination angles, bridging the gap between theory and practice. Detailed analysis of temperature distribution, flame characteristics, and gas-phase reactions reveals critical insights into the complex interplay governing heat behavior under these conditions. The observed reduction in flame thickness and standoff distance with increasing inclination underscores the influence of buoyancy-induced plumes. This work developed a dimensionless formula that accounts for both buoyancy-induced plumes and diffusion rates perpendicular to the fuel, successfully capturing the variation in flame thickness with inclination angles. Furthermore, our findings show that the average flame spread rate escalates with higher inclination angles, attributed to enhanced gas-phase reactions near the flame front that lead to intensified heat transfer and a subsequent increase in temperature within the solid phase. The study also uncovers a competitive mechanism between flame “jumps” and heat transfer to the unburned zone, causing an initial increase and then a decrease in flame spread rates with increasing discrete gap size at larger inclination angles. Conversely, at smaller inclination angles, flame progression halts as the discrete gap size increases, due to inadequate heat transfer to the adjacent discrete fuel, resulting in the cessation of flame spread. This study not only advances our understanding of the thermal processes underpinning flame spread in inclined configurations but also offers crucial insights for developing more effective fire protection strategies and thermal protection systems in engineering applications.

Spatiotemporal Surface Temperature Measurements Resolving Flame-Wall Interactions of Lean H2-Air and CH4-Air Flames Using Phosphor Thermometry

AbstractSpatiotemporal wall temperature (Twall) distributions resulting from flame-wall interactions of lean H2-air and CH4-air flames are measured using phosphor thermometry. Such measurements are important to understand transient heat transfer and wall heat flux associated with various flame features. This is particularly true for hydrogen, which can exhibit a range of unique flame features associated with combustion instabilities. Experiments are performed within a two-wall passage, in an optically accessible chamber. The phosphor ScVO4:Bi3+ is used to measure Twall in a 22 × 22 mm2 region with 180 µm/pixel resolution and repetition rate of 1 kHz. Chemiluminescence imaging is combined with phosphor thermometry to correlate the spatiotemporal dynamics of the flame with the heat signatures imposed on the wall. Measurements are performed for lean H2-air flames with equivalence ratio Φ = 0.56 and compared to CH4-air flames with Φ = 1. Twall signatures for H2-air Φ = 0.56 exhibit alternating high and low-temperature vertical streaks associated with finger-like flame structures, while CH4-air flames exhibit larger scale wrinkling with identifiable crest/cusp regions that exhibit higher/lower wall temperatures, respectively. The underlying differences in flame morphology and Twall distributions observed between the CH4-air and lean H2-air mixtures are attributed to the differences in their Lewis number (CH4-air Φ = 1: Le = 0.94; H2-air Φ = 0.56: Le = 0.39). Findings are presented at two different passage spacings to study the increased wall heat loss with larger surface-area-to-volume ratios. Additional experiments are conducted for H2-air mixtures with Φ = 0.45, where flame propagation was slower and was more suitable to resolve the wall heat signatures associated with thermodiffusive instabilities. These unstable flame features impose similar wall heat fluxes as flames with 2–3 times greater flame power. In this study, these flame instabilities occur within a small space/time domain, but demonstrate the capability to impose appreciable heat fluxes on surfaces.

Stability and combustion characteristics of dual annular counter-rotating swirl oxy-methane flames: Effects of equivalence and velocity ratios

An experimental study was carried out to investigate flow/flame interactions, stability, combustion, and emissions properties of CH4/O2/CO2 stratified flames stabilized on a dual annular counter-rotating swirl (DACRS) burner for gas turbine combustion applications. The effects of two targeted parameters, namely equivalence ratios (for primary - ϕp, secondary - ϕs, and global - ϕg streams) and velocity ratio (Vr = Vp/Vs: primary to secondary stream inlet velocity ratio), are studied at fixed volumetric oxygen fraction (OF) in the oxidizer mixture (O2 + CO2) of both primary and secondary streams of 34 % at fixed Vp of 5 m/s. The experimental results indicated that no flame flashback was recorded in the domain of any operational ϕp up to stoichiometric operation of the secondary stream (ϕs = 1.0). At near stoichiometric operation of the primary stream, the main secondary flame can persist in extremely lean conditions (ϕs = 0.45 @ Vr = 3), thereby extending the thresholds of flame blowout. Moreover, raising ϕp from 0.4 to 1.0 results in significant reduction of ϕs at blowout from 0.595 to 0.456, corresponding to reducing the combustor ϕg at blowout from 0.577 to 0.499. At lower ϕp, the oxy-methane flame tends to lift and extinguish earlier.

Exploring the impact of diesel-vegetable oil blends as an alternative fuel in combustion chambers

This study investigated using diesel-vegetable oil blends as an alternative fuel in combustion chambers. Vegetable oils, such as soybean and rapeseed oil, were blended with diesel fuel to create different blends, and the resulting properties were studied. It was found that vegetable oil blends had higher densities and flash points than pure diesel, which may affect combustion. Adding vegetable oil to the fuel reduced NOx and particulate matter emissions but had no significant impact on CO and CO2 emissions. Blends of vegetable oils were identified as promising alternative fuels for combustion chambers. In the experimentation, a combustion chamber was equipped with six swirl blades comprising two curved and one straight blade fired at different swirl angles (20°, 30°, 40°, 50°, and 60°) using VR1, VR2, VR3, and VR4 mix ratios of the blends. The results revealed that the maximum temperature for straight-edge blades was 50 °C, while curved-edge blades achieved a maximum temperature of 60 °C. Notably, due to the higher density and flash point of DIRO compared to DISO, the maximum temperatures of DISO blends tended to surpass those of DIRO blends. Furthermore, the study highlighted the superior combustion characteristics of curved blades, attributed to their swirling curved edges that elevated temperatures and enhanced turbulence. The optimal temperature was achieved using a 60 °C curved-edge blade swirling at a VR1 blend ratio in the DISO blend. Further exploration into additional features like pressure, emissions, and flame characteristics could contribute to supporting the use of these oil blends in diverse applications.