Hydrogen Mole Fraction Research Articles

An efficient dimensionality reduction approach for modelling cryogenic hydrogen release

This study develops a precise and cost-effective method for reducing the complexity of cryogenic hydrogen unintended release. For this purpose, the dominant modes of a well-characterised cryogenic hydrogen jet (Sandia National Laboratories), with stagnation pressure and temperature fixed at 5 bar and 50 K, are extracted using the proper orthogonal decomposition (POD) method. Building on validating the large eddy simulation (LES) against experimental measurements, the velocity field within the LES results is analysed near the release point. The mass fraction half-width of cryogenic hydrogen jets grows linearly with a slope of 0.1115 against the downstream distances, resembling room-temperature jets. The first 10 extracted modes from 500 LES snapshots demonstrate dominance over the remaining modes. In addition, this study evaluates the flammable gas dispersion using LES and 10-mode POD, showing POD effectively identifies high-risk areas within hydrogen's flammability range. Minor deviations (2.1–3.3%) confirm POD's reliability for hazard assessment compared with LES. Furthermore, an in-depth analysis is performed on the radial distributions of hydrogen mass fraction and centreline hydrogen mole fraction.

The impact of fuel cell vehicle exhaust grille shape under natural ventilation on hydrogen leakage and diffusion

The rapid progression of hydrogen fuel cell vehicles has brought forth various challenges, primarily the frequent occurrence of hazardous incidents stemming from hydrogen leakage and diffusion. Consequently, there is a growing emphasis on hydrogen safety, leading to the development of stricter standards and regulations to mitigate the associated safety risks. Research on the design of exhaust port structures to facilitate the safe diffusion of hydrogen after leakage in diverse scenarios has become increasingly significant. This study examines the impact of exhaust grille shapes on hydrogen leakage and diffusion phenomena within the hydrogen storage compartment of fuel cell vehicles under natural ventilation conditions. Five distinct porous grille shapes were examined: rectangular, circular, square, rhombic, and hexagonal grilles. Numerical simulations of hydrogen leakage and diffusion within the compartment were conducted using Cradle scFLOW software. The effectiveness of the different grille shapes was assessed using several criteria, including average hydrogen molar fraction, pressure drop (indicative of negative pressure regions), density, and Richardson number. Overall, the rectangular grille exhibited superior performance in facilitating hydrogen venting.

Organic municipal solid waste derived hydrogen production through supercritical water gasification process configured with K2CO3/SiO2: Performance study

Cities worldwide face a significant public health and environmental challenge in handling municipal solid waste (MSW). This research exposed an effective utilization of MSW as the source for hydrogen production via a supercritical water gasification process under 450–650 °C at 15–45 min processing time. The impacts of gasification temperature and processing time on the functional properties of hydrogen production are studied. Its results are compared to identify the optimum processing temperature and processing time to adopt the system. Integrating 3 wt% silicon dioxide (SiO2) nanoparticles/3 wt% of potassium carbonate (K2CO3) enhances hydrogen production by increasing the catalyst's surface area and improving the stability of active sites, leading to more efficient gasification reactions. Increasing the gasification temperature from 450 to 650 °C significantly raises the hydrogen molar fraction and gas yield with peak gasification efficiency (GE) and hydrogen efficiency (HE) values. The gasifier functioned with catalyst (3 wt% K2CO3/SiO2) under 650 °C gasification temperature and 45min gasification time influenced better output responses like improved hydrogen gas yield of 63.7 mol/kg, higher gasification efficiency of 59.8 %, better hydrogen efficiency (63.4 %) and increased carbon conversion efficiency of 63.4 and 42.5 % respectively.

A comprehensive analysis of a compact-sized methanol cracking unit for hydrogen production

Methanol is recognized as source of hydrogen production, making it a suitable fuel for sustainable development. However, hydrogen production methods remain a concern. An experimental setup and a simulation model in Aspen Plus, incorporating an evaporator and cracker, are developed for hydrogen production. The effects of dimensional parameters, including the length and diameter of the cracker, temperature, and pressure in the presence of the catalyst SCST- 403, on hydrogen production and methanol conversion via thermal catalytic cracking have not been discussed yet. The experimental results show that the optimum hydrogen mole fraction exceeds 0.52, and methanol conversion exceeds 60% at a length of 2.83 m, diameter of 4.07 mm, temperature of 500 °C, and pressure of 2.7 MPa. The investigation is extended to redesign the cracker unit using Aspen Plus based on reaction kinetics. Simulations on various dimensions, temperatures, and pressures reveal that, after redesigning, the optimum hydrogen mole fraction exceeds 0.60, and methanol conversion reaches 85% at a length of 4.5 m, diameter of 5.2 mm, temperature of 500 °C, and pressure of 3 MPa.

Enhanced syngas production from wood biomass by the catalytic packed bed of dolomite, limestone and olivine

Wood biomass was a promising renewable energy source that achieved carbon neutrality and alleviated the energy crisis. To enhance the conversion efficiency of wood to hydrogen, the catalytic combustion system of natural ores (dolomite, limestone and olivine) and wood chips was established. And the effects of the type, location, calcination temperature, content and diameter of catalysts were investigated on the temperature distribution and gas production. The results indicated that the combustion temperature of the hybrid bed was significantly increased with the catalyst addition. The dolomite and limestone particles promoted the hydrogen production, and the mole fractions of hydrogen were improved by 75% and 42%, respectively. When the dolomite was located above the wood layer, the hydrogen fraction was greatly higher than that of mixing with the wood. As the dolomite content increased, both of the hydrogen mole fraction and release time were enlarged obviously. Furthermore, the wood chips and dolomite particles with smaller diameters contributed to syngas production. And the hydrogen decreased with the increasing of air velocity when dolomite addition, which achieved the maximum of 11.2% at the velocity of 2 cm/s.

Viscosity of Hydrogen and Methane Blends: Experimental and Modelling Investigations

Understanding of thermophysical and transport properties of H2-NG blends are needed for the gradual introduction of hydrogen into the national gas grid. A capillary tube viscometer was used to measure the viscosity of hydrogen + methane blends (with hydrogen mole fraction = 0, 0.1000, 0.1997, 0.5019, and 1) at temperatures from 213 to 324 K and pressures up to 31 MPa. A total 147 experimental viscosity measurements were made for the three H2 + CH4 blends and compared against the predictions of five different viscosity models: a one-reference corresponding states (Pedersen) model, a two-reference corresponding states (CS2) model, an extended corresponding states (ECS) model, a corresponding states model derived from molecular dynamic simulations of Lennard Jones (LJ) fluids, and a residual entropy scaling (SRES) method. All the model predictions showed a relatively low deviation compared to the measured viscosities. The density required for viscosity model predictions were computed using Multi-Fluid Helmholtz Energy Approximation (MFHEA) equations of state (EoS). To check the experimental procedure and applicability of the viscometer equipment, viscosity validation measurements were carried out for propane, hydrogen, and methane. The measured viscosities of the pure components were in good agreement with the respective viscosity models with AARD of 0.24%, 0.25%, and 0.58% for propane, hydrogen, and methane, respectively.Graphical

Enhancing PEMEC Efficiency: A synergistic approach using CFD analysis and Machine learning for performance optimization

The proton exchange membrane electrolytic cell (PEMEC) is a clean, pollution-free, and promising device for producing hydrogen from water electrolysis. This paper enhances the electrochemical performance of the PEMEC by developing a comprehensive three-dimensional two-phase non-isothermal heat and mass transfer cell model. An analysis was conducted to study the influence of various operating parameters on the temperature safety and efficiency of the cell. The performance of the latter was optimized by adopting the machine learning technology, which aimed at identifying optimal conditions for improved performance. The obtained results showed that, when the inlet water flow rate and membrane thickness were increased, the average temperature of the anode catalyst layer (A-CL) was decreased by 1.4 K and 2.31 K, respectively. This allowed to improve the safety of the electrolytic cell. However, it would reduce the hydrogen and oxygen mole fraction in the electrolyzer. On the contrary, enhancing the porosity or thickness of the anode gas diffusion layer can increase the average A-CL temperature and decrease the oxygen and hydrogen mole fraction. Therefore, the backpropagation neural network and non-dominated sorting genetic algorithm were used to predict and optimize the performance of the electrolyzer, in order to maximize its temperature safety, electrochemical reaction rate, and hydrogen evolution efficiency as much as possible. The results of this study provide a theoretical foundation for the selection of suitable cell models according to different conditions in engineering applications. It also has an application value in energy saving and sustainable development.

Negative LIF Development For H2 Jet Characterization: Influence Of Tracers

This study focuses on the development of a new laser diagnostic based on Laser Induced Fluorescence by seeding the gas (N2) in which hydrogen is injected with fluorescent tracer. In this paper, three tracers were characterized, two aromatic compounds (toluene and difluorobenzene) and one ketone (acetone). The first part of this study compared the fluorescence of both aromatic compounds without injecting H2 . More particularly the influence of a temperature variation on the quantum yield and cross section absorption was regarded. It appeared that difluorobenzene was more suitable LIF measurement than toluene as it has a higher quantum yield that is less dependent to temperature variation. Then, Negative LIF was tested using two different tracers (difluorobenzene and acetone) and considering three different post-processing methods to consider the temperature variation inside the hydrogen jet: no temperature correction, temperature calculated based on a CFD RANS simulation, temperature calculated via an isentropic expansion and adiabatic mixture hypothesis. Results evidence that the first and the third methods presents respectively a lower and upper limit for the hydrogen mole fraction when the second method is biased by the presence of shock and expansion structures near the injector nozzle. Finally, it appears that, with the proper temperature correction, difluorobenzene and acetone yield similar results, despite the fact the acetone fluorescence needing more amplification to be captured, the signal to noise ratio is lower than for aromatic compounds.

Evaluation of hydrogen production via steam reforming and partial oxidation of dimethyl ether using response surface methodology and artificial neural network

This study aims to develop two models for thermodynamic data on hydrogen generation from the combined processes of dimethyl ether steam reforming and partial oxidation, applying artificial neural networks (ANN) and response surface methodology (RSM). Three factors are recognized as important determinants for the hydrogen and carbon monoxide mole fractions. The RSM used the quadratic model to formulate two correlations for the outcomes. The ANN modeling used two algorithms, namely multilayer perceptron (MLP) and radial basis function (RBF). The optimum configuration for the MLP, employing the Levenberg–Marquardt (trainlm) algorithm, consisted of three hidden layers with 15, 10, and 5 neurons, respectively. The ideal RBF configuration contained a total of 80 neurons. The optimum configuration of ANN achieved the best mean squared error (MSE) performance of 3.95e−05 for the hydrogen mole fraction and 4.88e−05 for the carbon monoxide mole fraction after nine epochs. Each of the ANN and RSM models produced accurate predictions of the actual data. The prediction performance of the ANN model was 0.9994, which is higher than the RSM model's 0.9771. The optimal condition was obtained at O/C of 0.4, S/C of 2.5, and temperature of 250 °C to achieve the highest H2 production with the lowest CO emission.

Intensifying CO2 condensation in the flue gas through the supersonic separators by hydrogen enriching: A computational study

The presence of carbon dioxide in combustion products is one of the main reasons for global warming. Supersonic separation is a modern, eco-friendly, and cost-efficient technology for capturing carbon dioxide. In this study, the physics of CO2 condensation through a supersonic separator nozzle for purifying the flue gas mixture is modeled using a numerical programming method based on the finite volume AUSM scheme. A limiting maximum for condensation efficiency relative to the CO2 content in the flue gas was demonstrated for fixed inlet conditions. The idea of enhancing the carrier gas heat capacity by hydrogen enriching for promoting droplet formation and condensation of CO2 in the mixture is being studied for further increasing condensation efficiency. The analysis uses the Peng-Robinson equation of state formulation, the multi-diameter growth model appropriate for the Eulerian-Eulerian problem, and the nucleation model suitable for high-speed mixture flows. The results show that adding about 48 % molar fraction of hydrogen increases the growth of droplet and condensation efficiency about 1.3 and 1.5 times, respectively. This technique can significantly increase the separation efficiency in supersonic separators.

Structures of Laminar Lean Premixed H2/CH4/Air Polyhedral Flames: Effects of Flow Velocity, H2 Content and Equivalence Ratio

AbstractPolyhedral Bunsen flames, induced by hydrodynamic and thermo-diffusive instabilities, are characterized by periodic trough and cusp cellular structures along the conical flame front. In this study, the effects of flow velocity, hydrogen content, and equivalence ratio on the internal cellular structure of premixed fuel-lean hydrogen/methane/air polyhedral flames are experimentally investigated. A high-spatial-resolution one-dimensional Raman/Rayleigh scattering system is employed to measure the internal scalar structures of polyhedral flames in troughs and cusps. Planar laser-induced fluorescence of hydroxyl radicals and chemiluminescence imaging measurements are used to quantify the flame front morphology. In the experiments, stationary polyhedral flames with varying flow velocities from 1.65 to 2.50 m/s, hydrogen contents from 50 to 83%, and equivalence ratios from 0.53 to 0.64 are selected and measured. The results indicate that the positively curved troughs exhibit significantly higher hydrogen mole fractions and local equivalence ratios compared to the negatively curved cusps, due to the respective focusing/defocusing effect of trough/cusp structure on highly diffusive hydrogen. The hydrogen mole fraction and local equivalence ratio differences between troughs and cusps are first increased and then decreased with increasing measurement height from 5 to 13 mm, due to the three-dimensional effect of the flame front. With increasing flow velocity from 1.65 to 2.50 m/s, the hydrogen mole fraction and local equivalence ratio differences between troughs and cusps decrease, which is attributed to the overall decreasing curvatures in troughs and cusps due to the decreased residence time and increased velocity-induced strain. With increasing hydrogen content from 50 to 83%, the hydrogen mole fraction and local equivalence ratio differences between troughs and cusps are amplified, due to the enhanced effects of the flame front curvature and the differential diffusion of hydrogen. With increasing equivalence ratio from 0.53 to 0.64, a clear increasing trend in hydrogen mole fraction and equivalence ratio differences between troughs and cusps is observed at constant flow velocity condition, which is a trade-off result between increasing effective Lewis number and increasing curvatures in troughs and cusps.

Enhanced production of hydrogen-rich gas from municipal sewage sludge gasification using a CaO-RM composite catalyst

Hydrogen-rich gas, characterized by high yield and purity, can be effectively generated through the steam gasification of sewage sludge (SS), offering substantial benefits for organic solid waste treatment and resource conservation. This study evaluated the gasification performance in a horizontal moving-bed reactor employing a wet-mixed CaO-red mud (CaO-RM) composite catalyst. The effects of CaO loading rate (CaO/RM), catalyst-to-SS ratio (CaO-RM/SS), and reaction temperature on the syngas yield, lower heating value (LHV), carbon conversion ratio, H2 to CO (H2/CO) ratio, and H2 yield were investigated. Results indicated that red mud loaded with a calcium-based catalyst significantly enhanced syngas production, particularly for hydrogen generation, during SS gasification. A maximum hydrogen molar fraction of 50.84% and a yield of 7.07 mol/kg were achieved with a CaO/RM of 40% and a CaO-RM/SS of 30% at 750 °C. With the reaction temperature increase from 700 to 900 °C, the catalytic performance for secondary tar cracking and steam reforming was further enhanced. The total syngas yield, H2 yield, hydrogen molar fraction, LHV of syngas, and carbon conversion rate peaked at 0.79 m³/kg, 19.30 mol/kg, 54.41%, 10,249.48 kJ/kg, and 65.67%, respectively, at 900 °C.

3D numerical study of NH3/H2 MILD combustion in a reversed flow MILD combustion furnace

Combustion of fuels to generate energy is essential for numerous residential and industrial human endeavors. In contrast to fossil fuels, the demand for carbon-free fuels such as ammonia and hydrogen to meet climate commitments is rapidly growing. This study conducts a numerical investigation of NH3/H2 MILD combustion. A three-dimensional CFD simulation model of a 90-degree sector of a reversed flow MILD combustion furnace is presented. The SAGE detailed chemical kinetics solver featuring the CEU-NH3 mechanism is employed with dynamic mechanism reduction for computational efficiency. The effects of varying the hydrogen mole fraction in the inlet fuel mixture from 0 to 50 % on the thermal characteristics, reaction zone, and emissions are investigated. The findings show that temperature homogeneity, assessed through temperature uniformity parameters and standard deviation, reveals a diminishing trend in temperature homogeneity with increased hydrogen concentration. The boundaries of the reaction zone are determined according to the NNH and N mole fractions, and both criteria are approximately identical. All the investigated cases match the MILD combustion definition; however, the cases with H2 concentrations ranging from 10 to 40 % fall under the MILD-like combustion regime. Emissions analysis shows that for all investigated cases, the ammonia slip emissions and the exhaust N2O emissions are below 1 and 0.5 ppm, respectively. The NOx emissions are found to increase abruptly with increasing hydrogen concentration from 0 to 35 % and subsequently undergo minor fluctuations.

Mutual Diffusivities of Mixtures of Carbon Dioxide and Hydrogen and Their Solubilities in Brine: Insight from Molecular Simulations.

H2-CO2 mixtures find wide-ranging applications, including their growing significance as synthetic fuels in the transportation industry, relevance in capture technologies for carbon capture and storage, occurrence in subsurface storage of hydrogen, and hydrogenation of carbon dioxide to form hydrocarbons and alcohols. Here, we focus on the thermodynamic properties of H2-CO2 mixtures pertinent to underground hydrogen storage in depleted gas reservoirs. Molecular dynamics simulations are used to compute mutual (Fick) diffusivities for a wide range of pressures (5 to 50 MPa), temperatures (323.15 to 423.15 K), and mixture compositions (hydrogen mole fraction from 0 to 1). At 5 MPa, the computed mutual diffusivities agree within 5% with the kinetic theory of Chapman and Enskog at 423.15 K, albeit exhibiting deviations of up to 25% between 323.15 and 373.15 K. Even at 50 MPa, kinetic theory predictions match computed diffusivities within 15% for mixtures comprising over 80% H2 due to the ideal-gas-like behavior. In mixtures with higher concentrations of CO2, the Moggridge correlation emerges as a dependable substitute for the kinetic theory. Specifically, when the CO2 content reaches 50%, the Moggridge correlation achieves predictions within 10% of the computed Fick diffusivities. Phase equilibria of ternary mixtures involving CO2-H2-NaCl were explored using Gibbs Ensemble (GE) simulations with the Continuous Fractional Component Monte Carlo (CFCMC) technique. The computed solubilities of CO2 and H2 in NaCl brine increased with the fugacity of the respective component but decreased with NaCl concentration (salting out effect). While the solubility of CO2 in NaCl brine decreased in the ternary system compared to the binary CO2-NaCl brine system, the solubility of H2 in NaCl brine increased less in the ternary system compared to the binary H2-NaCl brine system. The cooperative effect of H2-CO2 enhances the H2 solubility while suppressing the CO2 solubility. The water content in the gas phase was found to be intermediate between H2-NaCl brine and CO2-NaCl brine systems. Our findings have implications for hydrogen storage and chemical technologies dealing with CO2-H2 mixtures, particularly where experimental data are lacking, emphasizing the need for reliable thermodynamic data on H2-CO2 mixtures.

Process Integration of Hydrogen Production Using Steam Gasification and Water-Gas Shift Reactions: A Case of Response Surface Method and Machine Learning Techniques

An equilibrium-based steady-state simulator model that predicts and optimizes hydrogen production from steam gasification of biomass is developed using ASPEN Plus software and artificial intelligence techniques. Corn cob’s chemical composition was characterized to ensure the biomass used as a gasifier and with potential for production of hydrogen. Artificial intelligence is used to examine the effects of the significant input variables on response variables, such as hydrogen mole fraction and hydrogen energy content. Optimizing the steam-gasification process using response surface methodology (RSM) considering a variety of biomass-steam ratios was carried out to achieve the best results. Hydrogen yield and the impact of main operating parameters were considered. A maximum hydrogen concentration is found in the gasifier and water-gas shift (WGS) reactor at the highest steam-to-biomass (S/B) ratio and the lowest WGS reaction temperature, while the gasification temperature has an optimum value. ANFIS was used to predict hydrogen of mole fraction, 0.5045 with the input parameters of S/B ratio of 2.449 and reactor pressure and temperature of 1 bar and 848°C, respectively. With the steam-gasification model operating at temperature (850°C), pressure (1 bar), and S/B ratio of 2.0, an ASPEN simulator achieved a maximum of 0.5862 mole fraction of hydrogen, while RSM gave an increase of 19.0% optimum hydrogen produced over the ANFIS prediction with the input parameters of S/B ratio of 1.053 and reactor pressure and temperature of 1 bar and 850°C, respectively. Varying the gasifier temperature and S/B ratio have, on the other hand, a crucial effect on the gasification process with artificial intelligence as a unique tool for process evaluation, prediction, and optimization to increase a significant impact on the products especially hydrogen.

Computational investigation of the effect of geometry and fuel composition on the performance of a solid oxide fuel cell

The need to reduce the consumption of fossil fuels due to their negative impact on the quality of the air and on the greenhouse effect is causing major changes in the energy sector, with a progressively greater contribution of renewable energy sources to satisfy the global energy demand. Fuel cell technology is emerging as a key player in the energy transition since fuel cells convert directly chemical energy to electricity and heat without pollutant emissions. Among the different types available, solid oxide fuel cells (SOFC) can operate at high temperatures (up to 1000ºC), leading to high efficiency and stability. This work is concerned with the computational investigation of a planar solid oxide fuel cell. The governing conservation equations for mass, momentum, energy, species transport and electric charge are solved for a three-dimensional planar fuel cell. Different fuel and oxidizer compositions are considered and their influence on the performance of the fuel cell is investigated. The results show that when the hydrogen molar fraction in the fuel decreases, the maximum power and temperature decrease. The power, the efficiency and the maximum temperature are greater when the oxidizer is oxygen rather than air. The influence of the geometry of the air and fuel channels is also assessed, namely the dimensions of the channels and the effect of steps and obstacles in those channels.

Energy efficiency of hydrogen production via gasification from lignocellulosic residual biomass blend

Facing the challenges of environmental sustainability and energy security caused by anthropogenic carbon emissions, there is a need to adopt cleaner energy generation technologies, leveraging Colombia's existing national resources. In this context, hydrogen emerges as a promising source of renewable energy. Therefore, this project explores the use of a blend of residual lignocellulosic biomass as raw material for hydrogen production through gasification for energy purposes. Initially, a screening of residual lignocellulosic biomass in the study region was conducted, a blend was selected, and a simulation of the synthesis gas production process was carried out prospectively using Aspen Plus Dynamics® software. The results revealed that, by using the selected biomass blend, a synthesis gas with a hydrogen molar fraction of 38.7% and an ER of 0.19 was obtained. According to sensitivity analyses, the optimal parameters identified to achieve this hydrogen concentration were: gasification temperature of 707°C, oxygen flows of 484 kg/h, steam at 420 kg/h, and gasification pressure of 1 atm. These findings support the potential of the studied lignocellulosic biomass blend as an alternative for hydrogen production, while also offering an opportunity for the valorization of lignocellulosic residual biomass.

Optimizing hydrogen yield in sorption-enhanced steam methane reforming: A novel framework integrating chemical reaction model, ensemble learning method, and whale optimization algorithm

High hydrogen production is essential in sorption-enhanced steam methane reforming (SE-SMR). This study presents an innovative optimization framework to optimize the H2 yield of SE-SMR through a coupled reaction model, prediction surrogate model, and whale optimization algorithm. Firstly, a computational fluid dynamics chemical reaction model of SE-SMR is constructed. A database is established to consider the H2 yield of SE-SMR with temperature, pressure, velocity, and steam to carbon ratio. Then, a surrogate model is developed on the basis of eXtreme Gradient Boosting (XGBoost) to predict the H2 yield under various operating parameters. Finally, the surrogate model is exploited to calculate the fitness function of the whale optimization algorithm to construct an optimization framework for maximizing the H2 yield. The results show that the XGBoost ensemble surrogate model can predict the H2 yield of SE-SMR within 4 s with high accuracy. The optimization framework can optimize the maximum H2 yield and the corresponding operating parameters within 1 min. The optimization results are validated by applying the model and the percentage error of only 0.79 %. Moreover, under optimal operating conditions, methane is almost completely converted to hydrogen, and the dry hydrogen mole fraction could reach 95.96 %. The presented optimization framework can guide the prediction of H2 yield and the optimization of operating parameters in SE-SMR.

Formulation of an Ideal Solid Oxide Fuel Cell

Principles of transport phenomena and chemical/ electrochemical reaction kinetics were employed to develop the formulation for the prediction of fuel (e.g., ) and oxidant (e.g., ) mole fraction profiles in the porous anode and cathode electrodes of an ideal solid oxide fuel cell (SOFC). The ideal SOFC is composed of the porous anode, , which is the cermet of metallic nickel and yttria-stabilized zirconia and the porous cathode, , which is the strontium-doped lanthanum manganite. A thin film of the yttria-stabilized zirconia is the solid electrolyte separating the cell electrodes. The cell anode-side fuel and cathode-side oxidant supply compartments are continuously stirred to maintain constant concentrations of fuel and oxidant in them. The relevant analytical formulation as well as the numerical data computed is presented. The current calculated data show a non-linear decrease, associated with the coupled effect of diffusion and consumption, in the mole fractions of hydrogen and oxygen in the porous electrodes with an increase in the distance from the reactant supply compartments towards the cell electrolyte separator.

Study of CH4-H2-CO-Air premixed combustion characteristics based on fractal dimension and flame crack method

The laminar combustion characteristics of CH4-H2-CO-Air are studied in a constant volume combustion chamber with different hydrogen content ratios and the initial conditions of 300 K and 0.2 MPa by schlieren technology. The influence laws of flame instability are analyzed through the influence laws of hydrogen content ratio and equivalence ratio (Φ) on the fractal dimensions of the flame contour and the ratio of the total flame face cracks' lengths to the flame radius (L/R), as well as the influence laws of hydrodynamic instability and thermal-diffusive instabilities on the flames. The results show that L/R is more sensitive to flame instabilities than flame front fractal dimensions due to a wider sampling range. After R exceeds a certain value, for lean and rich combustion conditions with the same distance from the stoichiometric ratio, the L/R is greater during lean combustion, and as the equivalence ratio gradually increases from 0.6 to 1.4, the effect of increasing hydrogen content (Hydrogen mole fraction ranges from 60% to 66.67%) on flame instability gradually shifts from promotion to suppression. This study has certain reference value for the combustion application of biomass synthesis gas.