Minimum Ignition Energy Values Research Articles

Theoretical prediction model for minimum ignition energy of combustible gas mixtures

Minimum ignition energy (MIE) is a crucial parameter for identifying the hazards of combustible gases. To rapidly obtain accurate MIE values for various gases, the shape of the ignition source was simplified to cylindrical. Based on theories of heat conduction and chemical reaction kinetics, a physical model of the ignition process was established. The spatial and temporal evolution of temperature was used as a basis for judging the success of ignition. A numerical algorithm was developed and maximum flame temperatures and MIE were calculated for several combustible gases (H2, CH4, C2H6, C3H8, C4H10, C2H4, C2H2). This model accurately predicted the U-shaped trend of MIE values with concentration for CH4/air and H2/air mixtures. It found that the MIE was minimal at the stoichiometric concentration, at 0.37 mJ and 0.017 mJ, closely aligning with experimental data. This numerical model has been validated for its accuracy and promises to make relatively precise theoretical predictions for the MIE values of uncommon combustible gases or mixtures of various gases.

Effect on ignition sensitivity of combustible dust particle size reduction due to dispersion in the 20-L chamber

This work simulates the particle breakage process caused by the dispersion of several typical combustible dusts in a 20-L chamber. Some operations in the process industry that involve gas turbulence and particle interactions can cause dust particles to break, resulting in a decrease in minimum ignition energy (MIE) and minimum ignition temperature (MIT). Particle breakage classification should attempt to correlate changes in D3,2 (Sauter mean diameter) values with the brittleness index. The descending order of particle breakage severity is as follows: ascorbic acid > anthraquinone > tobacco > nicotinic acid > lignite. The percentage decrease in MIE and MIT values is generally proportional to the degree of particle breakage. However, the decrease in MIT values was not as significant as in MIE values. This is because of the various dust-ignition source interaction patterns between a dust cloud and an ignition source.

An investigation on minimum ignition energy (MIE) and thermodynamic analysis of typical fibrous dust

This study focused on several natural fibrous dust (cotton, silk, and linen fibers) and synthetic fibrous dust (polyester and nylon fibers) obtained from textile mills. Potential relationships between minimum ignition energy (MIE) values and equivalent diameters calculated via four phenomenological models were explored to explain the dependence of the MIE values on geometry. Diameter and material composition are the most critical factors influencing MIE of fibrous dust. However, the impact of length on MIE involving a fixed-diameter fiber cannot be ignored. To explain higher MIE values with increased fiber length per given diameter, an axial heat transfer mechanism model of fibrous dust was constructed in terms of energy conservation. In addition, the pyrolysis processes, pyrolysis mechanisms, and thermodynamic parameters (i.e., activation energy (E), pre-factor (A), and enthalpy(ΔH)) of typical fibrous dust were analyzed to provide a theoretical basis for the numerical simulation of this dust type.

Effects of fuel Lewis number on the minimum ignition energy and its transition for turbulent homogeneous fuel–air mixtures

The effects of fuel Lewis number on the minimum ignition energy (MIE) requirements for ensuring successful thermal runaway, and self-sustained flame propagation have been analysed for forced ignition of homogeneous fuel–air mixtures under decaying turbulence for a wide range of initial turbulence intensities using three-dimensional direct numerical simulations. The minimum energy demand for ensuring self-sustained flame propagation has been found to be greater than that for ensuring only thermal runaway irrespective of its outcome for large turbulence intensities, and the minimum ignition energy increases with increasing rms turbulent velocity irrespective of the fuel Lewis number. The MIE values have been found to increase more sharply with increasing turbulence intensity beyond a critical value for all fuel Lewis numbers considered here. The variations of the normalised MIE (MIE normalised by its laminar value) with increasing turbulence intensity beyond the critical point follow a power-law and the power-law exponent has been found to increase with an increase in fuel Lewis number. This behaviour has been explained using a scaling analysis. The stochasticity associated with forced ignition has been demonstrated by using different realisations of statistically similar turbulent flow fields for the energy inputs corresponding to the MIE and successful outcomes are obtained in most instances, justifying the evaluation of the MIE values in this analysis.

A numerical model for the calculation of the minimum ignition energy of pure and mixture dust clouds

A numerical model is developed for the minimum ignition energy (MIE) calculation of pure and mixture dust clouds, considering the influence of particle size distribution. The original particle number based size distribution is approximated with median sizes (number d50) of the subdivisions obtained by dividing the original distribution range. The MIE is calculated for 5 pure dusts, 2 mixtures of combustible dusts and 2 mixtures of combustible & inert dusts. For pure dust clouds, as the number of subdivisions and hence d50s increases, variation trend of the MIE as a function of dust concentration (MIE(conc)) gradually shifts from a “V” to a “U” or “bathtub” shape, along with an increase in the concentration where the dust cloud MIE (minimum MIE(conc) value) is reached. Furthermore, the calculated MIE fluctuates at lower number of d50s but gradually stabilizes as the d50 number further increases. The calculated MIE variation trends correspond well with the experimental data. However, due to uncertainties in the dust cloud formation and spark release in the experimental tests, differences in the definitions of the d50 in different studies and high idealization of the numerical model, there are deviations between the absolute experimental and calculated MIE values.

An experimental investigation into the effect of spark gap and duration on minimum ignition energy of partially dissociated NH3 in air

This paper presents an experimental investigation into the effect of spark gap and spark duration on the minimum ignition energy (MIE) of partially dissociated NH3 in air at 295 K and 1 atm. The measurements were carried out using a Hartmann bomb apparatus with the degree of NH3 dissociation varying from 0 to 10%, corresponding to 0 to 7.5%v/v H2 in the fuel mixture with a fixed H2/N2 ratio of 3, and equivalence ratio varying from 0.7 to 1.2, assuming complete oxidation. Axisymmetric two-dimensional CFD modelling was performed using Ansys Fluent incorporating the Okafor mechanism to predict MIE. At a given equivalence ratio, both measured and predicted MIE values decreased significantly with increasing the degree of NH3 dissociation, due to increased presence of H2 in the mixture. There were optimum spark gap and spark duration for a given degree of NH3 dissociation and equivalence ratio at which the MIE was the lowest. The increased presence of H2 due to rising degree of NH3 dissociation enhances the mixture's oxidation reactivity and combustion intensity, which in turn increases the flame kernel temperature and size, the rate of production of key radicals (OH, NH2, H, and O) and rate of heat generation, leading to a more self-sustaining flame and significantly reduced MIE.

A theoretical model for the prediction of the minimum ignition energy of dust clouds

In this study, a physical model of the dust cloud ignition process is developed for both cylindrical coordinates with a straight-line shaped ignition source and spherical coordinates with a point shaped ignition source. Using this model, a numerical algorithm for the calculation of the minimum ignition energy (MIE) is established and validated. This algorithm can evaluate MIEs of dusts and their mixtures with different dust concentrations and particle sizes. Although the average calculated cylindrical MIE (MIEcylindrical) of the studied dusts only amounts to 63.9% of the average experimental MIE value due to reasons including high idealization of the numerical model and possible energy losses in the experimental tests, the algorithm with cylindrical coordinates correctly predicts the experimental MIE variation trends against particle diameter and dust concentration. There is a power function relationship between the MIE and particle diameter of the type MIE ∝ dpk with k being approximately 2 for cylindrical coordinates and 3 for spherical coordinates. Moreover, as dust concentration increases MIE(conc) first drops because of the decreasing average distance between particles and, at fuel-lean concentrations the increasing dust cloud combustion heat; however, after the dust concentration rises beyond a certain value, MIE(conc) starts to increase as a result of the increasingly significant heat sink effect from the particles and, at fuel-rich concentrations the no longer increasing dust cloud combustion heat.

Evaluation of the dust potential hazard of thermal power plants through coal dust combustion and explosion characteristics

Thermal power is the main source of electricity in Taiwan, where coal is the primary fuel. However, concerns for potential fire and explosion hazards caused by coal dust are increasing. The problem regarding the storage or transportation process of coal cannot be neglected. This study explored four coal dust samples obtained from the three regions of South Africa, Russia, and Australia; the particle size D50 of all the samples was < 75 μm. The intrinsic safety characteristics of combustion and explosion in coal dust were studied using the minimum ignition energy (MIE) test, minimum ignition temperature (MIT) of cloud apparatus, and 20-L apparatus. Russian coal exhibited the lowest MIE and MIT values of 550 °C and 120 mJ, respectively. Furthermore, the minimum dust explosion concentration was 30 g m−3 in Australian coal. These experimental results, combined with the on-site investigation, indicated that appropriate countermeasures are sufficient to reduce dust hazards. The results showed that the dust explosion risk of a properly operating thermal power plant is considerably low.

Measurement on minimum ignition energy of n-decane with pyrolysis

Measurement on the minimum ignition energy (MIE) of n-decane with pyrolysis is investigated experimentally. Certain decomposition rate n-decane vapor is simulated by blending certain proportion of ethylene into n-decane vapor. Two equivalence ratios (1 and 0.7) and five blending ratios (0,0.2 0.4,0.6,0.7) of ethylene are, respectively, designed to represent different decomposition rates and equivalence ratios. The effect of different decomposition rates and equivalence ratios on the MIE of n-decane is investigated in following experiments. Two experimental methods are used for measurement. Technique of high-speed schlieren system is adopted to obtain images of the flame kernel by which the relationship between flame kernel radius and flame speed is calculated. An ignition probability model based on the logic regression theory is established to obtain the ignition probability curve. Results indicate that MIE is sensitive to the blending ratio of ethylene when equivalence ratio is 0.7. With elevated blending ratio of ethylene, MIE decreases rapidly firstly and with the continuous increasing of the blending ratio, the decreasing of MIE is lagging which indicates that there is a limit to the effect of the blending ratio of ethylene on the MIE. It is also found that values of MIE are closed when ethylene blending ratio is big enough whatever the equivalence ratio is.

Study of lignocellulosic biomass ignition properties estimation from thermogravimetric analysis

In the last decade, the use of renewable resources has increased significantly in order to reduce the energetic dependence on fossil fuels, as they have an important contribution to the global warning and greenhouse gasses effect. Because of that, research on biofuels has been increased in the last years as its characteristics of use match those of the conventional fuel's: solid biomass can be used instead of coals, and biodiesel could replace diesel. Research on solid biomass ignition properties has been considerably developed because of the amount of industrial accidents related to the treatment and use of solid biomass (self-ignition, dust explosions, etc.). On the other hand, thermogravimetric analysis (TGA) is becoming and important characterization technique as it can be used to determine a wide spectrum of properties, such as kinetics, composition, proximate analysis, etc. This research aims to combine thermal analysis and ignition properties, by using the TGA to obtain the elemental composition of lignocellulosic biomass and compare those results to Minimum Ignition Energy (MIE) values test output, so a relation between composition and MIE can be found.To achieve this aim, biomass samples from different origins have been used: oil palm wastes (empty fruit bunches, mesocarp fiber and palm kernel shell), agricultural wastes (straw chops) and forestry wastes (wood chips and wood powder). Also, raw materials and torrefied biomass were compared. The hemicellulose/cellulose ratio was calculated and compared to different flammability properties, finding out that the greater the ratio and the lower the onset temperature (temperature at which the pyrolysis reaction accelerates), the lower was the minimum ignition energy. From this basis it was possible to define “tendency areas” that grouped the samples whose MIE values were similar. Three tendency areas were found: high minimum ignition energy, medium minimum ignition energy, and low ignition energy.

Numerical Study and Experimental Validation of Minimum Ignition Energy for Microwave Spark Ignition

Microwave plasma ignition has the potential for energy savings and emission reductions, and the minimum ignition energy (MIE) and the lean limit can be determined by microwave spark plugs (MSPs) under the same microwave power. To predict the relationship among electric field intensity (EFI), equivalence ratio ( $\varphi$ ) and MIE, a physical model of microwave spark ignition is established. The calculation results show that the MIE has a U-shaped relationship with $\varphi $ , and the MIE value of methane-air is minimum at the point of $\varphi =0.7$ . Then, a novel MSP with three different electrode structures and EFIs is enabled. Finally, this paper presents a combustion performance analysis focusing on the flame kernel, combustion pressure, and composition of combustion emissions. The results indicate that a larger flame kernel size, peak pressure in the chamber and higher fuel efficiency are all achieved under the condition of $\varphi =0.7$ for the same MSP. On the one hand, the MIE of MSP 1 with a higher EFI is lower than that of MSPs 2 and 3; on the other hand, the experimental relationship between the MIE and $\varphi $ is qualitatively similar to the theoretical prediction under microwave spark ignition in this paper.

A Numerical Investigation of the Effects of Fuel Composition on the Minimum Ignition Energy for Homogeneous Biogas-Air Mixtures

The minimum ignition energy (MIE) requirements for ensuring successful thermal runaway and self-sustained flame propagation have been analysed for forced ignition of homogeneous stoichiometric biogas-air mixtures for a wide range of initial turbulence intensities and CO2 dilutions using three-dimensional Direct Numerical Simulations under decaying turbulence. The biogas is represented by a CH4 + CO2 mixture and a two-step chemical mechanism involving incomplete oxidation of CH4 to CO and H2O and an equilibrium between the CO oxidation and the CO2 dissociation has been used for simulating biogas-air combustion. It has been found that the MIE increases with increasing CO2 content in the biogas due to the detrimental effect of the CO2 dilution on the burning and heat release rates. The MIE for ensuring self-sustained flame propagation has been found to be greater than the MIE for ensuring only thermal runaway irrespective of its outcome for large root-mean-square (rms) values of turbulent velocity fluctuation, and the MIE values increase with increasing rms turbulent velocity for both cases. It has been found that the MIE values increase more steeply with increasing rms turbulent velocity beyond a critical turbulence intensity than in the case of smaller turbulence intensities. The variations of the normalised MIE (MIE normalised by the value for the quiescent laminar condition) with normalised turbulence intensity for biogas-air mixtures are found to be qualitatively similar to those obtained for the undiluted mixture. However, the critical turbulence intensity has been found to decrease with increasing CO2 dilution. It has been found that the normalised MIE for self-sustained flame propagation increases with increasing rms turbulent velocity following a power-law and the power-law exponent has been found not to vary much with the level of CO2 dilution. This behaviour has been explained using a scaling analysis and flame wrinkling statistics. The stochasticity of the ignition event has been analysed by using different realisations of statistically similar turbulent flow fields for the energy inputs corresponding to the MIE and it has been demonstrated that successful outcomes are obtained in most of the instances, justifying the accuracy of the MIE values identified by this analysis.

Quantitative Structure-Property Relationship (QSPR) models for Minimum Ignition Energy (MIE) prediction of combustible dusts using machine learning

Quantitative Structure-Property Relationship (QSPR) classification models for Minimum Ignition Energy (MIE) classification of 65 combustible dusts have been developed using machine learning algorithms Random Forests (RF) and Decision Trees (DT). Combustible dusts were categorized based on their MIE values: dusts having MIE > 10 mJ and dusts having MIE < 10 mJ. In this work, an important macroscopic property, dust median diameter (d50) was also used as one of the parameters along with the molecular descriptors for model development. The machine learning Random Forest (RF) algorithm was used for identification of the 13 molecular descriptors having maximum effect on MIE prediction accuracy. Thereafter, these descriptors were used as input parameters to develop binary classification Random Forest (RF) and Decision Tree (DT) models. The RF and DT algorithms displayed good MIE category predictability validated through the test set Receiver Operating Characteristic- Area Under Curve (ROC-AUC) of 0.95 for both the models. Thus, this work has displayed that Random Forests can be used as an important tool for descriptor reduction in QSPR studies and can prove to be a valuable resource for MIE category prediction.

Ignition characteristics of amino acid powders

Herein, the ignition characteristics, including the minimum ignition energy (MIE) and minimum explosible concentration (MEC), of amino acid powders (L-leucine, L-valine, L-threonine, L-alanine, and L-serine) were experimentally investigated. The MIE and MEC values of branched-chain amino acid (BCAA) powders were much lower than those of the other powders such as L-threonine, L-alanine, L-serine and glycine powders. In particular, the MEC values for the BCAAs were constant, notwithstanding increasing particle size. The plateau range of BCAA particle size was wider than that of the other carbonaceous particles tested. Pyrolysis of the powders and the resultant pyrolyzates were investigated by thermogravimetry (TG) and the pyrolysis-gas chromatography-mass spectrometry (PyGCMS). A number of flammable materials were formed from the BCAAs, compared with the other amino acids tested. In addition, the propagating flame structure was discussed and different flame structures for the BCAAs were observed depending on the particle size distribution. The flame front for relatively small particle sizes was continuously smooth, whereas that for relatively large particle sizes was discrete. These results indicated that the BCAAs are sensitive to ignition and exhibit a high risk of dust explosion during the manufacturing process.

Minimum ignition energy and minimum explosible concentration of L-isoleucine and glycine powder

In this study, Minimum Ignition Energy (MIE) and Minimum Explosible Concentration (MEC) of L-isoleucine and glycine powder with two different particle size distributions were experimentally investigated. The experimental results showed that the values of MIE and MEC of L-isoleucine powder were lower than those of glycine powder. The pyrolysis and the combustible products of glycine and L-isoleucine powders were measured. The results showed that a number of flammable and combustible materials are formed during the pyrolysis of L-isoleucine, although few flammable compounds are generated during the pyrolysis of glycine due to polymerization. This result indicated that the L-isoleucine powder has a high risk of dust explosion as compared to the glycine powder. Consequentially, an appropriate risk assessment for the L-isoleucine powder with fine particles is necessary in the powder handle processes.

Electrostatic Charge Generation in Pneumatic Conveying Process: Effect of Particle Properties

One of the main concerns in particle pneumatic conveying process is the possibility of hazards for operation safety due to the electrostatic charge generation as a result of collisions between particles and the equipment wall. Indeed, the electrostatic discharge can occur in the equipment leading to fire or explosion. Simulation of these kinds of processes plays an important role in understanding the various aspects of the system in order to production loss prevention. This paper deals with the simulation of particle pneumatic conveying process inside an inclined tube using a particular method. In this method, the electrification of particles inside the tube is influenced by the vertical collision velocity against the tube wall. Simulation of the particle movements inside the tube, generation of electrostatic charges over the particle surfaces as well as the possibility of fire as a result of discharging the electrostatic energy are investigated. The possibility of fire is investigated by comparing the amount of electrostatic energy with minimum ignition energy (MIE) of the particles. The effect of particle properties including the size and mechanical ones in the simulation is studied. Finally, several solutions are proposed to manage the risk of fire and explosion. As results, the electrostatic energy (E) is beyond the MIE, and the electrostatic discharge can occur leading to explosion for the diameters more than 2 mm and also for elasticity constants lower than 140 MPa. Eventually, there is no hazard of fire and explosion, since all calculated electrostatic energy for the change of Particle Poisson’s ratio varying from 0.1 to 0.9 is less than the MIE value for the air flow rate of 10 m3/h.

Improved partial inerting MIE test method for combustible dusts and its CFD validation

The Minimum Ignition Energy (MIE) is an important dust hazard parameter that guides the elimination of possible ignition sources in solids handling facilities. Partial inerting is a dust explosion mitigation technique implemented in industries, where the dust cloud MIE is increased, reducing the risk of an accidental explosion. Previous work has shown that purging the MIE apparatus Hartmann tube before testing is essential for obtaining accurate MIE values, but have not discussed the importance of the effective purge time required. Through experimentation and CFD modeling, this study has attempted to refine the existing MIE testing standard for partial inerting applications by introducing purge time as an essential parameter. In this study, oxygen sensor measurements were conducted to determine that the purge time for the MIKE3 apparatus should be > 40 s. Additionally, an ANSYS Fluent CFD purging model was developed, which confirmed the experimentally determined purge time. Using this improved methodology, an accurate partial inerting data set was obtained for the combustible dusts Anthraquinone, Lycopodium clavatum and Calcium Stearate.

Minimum Ignition Energy of Aluminium Nanopowders as Engineered Nanomaterials (ENMs)

Enormous absence of knowledge regarding dust explosion involving Engineered Nanomaterials (ENMs) has led to the exploration on investigating the Minimum Ignition Energy (MIE) of selected ranges of sizes for aluminum nanopowders. Nano- structure owned by alumina definitely contributes to changes in its chemical as well as physical composition. Thus, testing on MIE determination was conducted on three different particle sizes of aluminum nanopowders; A1-100nm, Al-70nm, Al-40nm.The main aim of the project is to determine the relationship of the particle diameter with their respective MIE. The overall experimental procedure take place using 1.2L Hartmann tube explosion system based on ASTM E2019. Two different dust concentrations were tested (250 g/m3 and 500 g/m3) and the results showed that Al-40 nm have the lowest MIE values of less than 5 mJ for both concentrations. For Al-70nm, the MIE value at concentration equals to 250g/m3 is between 10 mJ and 33 mJ, whereas the MIE is less than 10 mJ at concentration equals to 500 g/m3. This contradicts with Al-100nm in which the MIE is between 100 mJ and 200 mJ (c=250 g/m3) and between 33 mJ and 51 mJ (c=500 g/m3). In overall, as particle size decreasing, the MIE is significantly decreasing at respective concentrations.

Thermal decomposition behaviors and dust explosion characteristics of nano-polystyrene

With the development of nano-powder technology, polymeric nano-materials are widely used in various industries, while not much research on their thermal decomposition and dust explosion characteristics has been conducted. The thermal behaviors and explosion characteristic parameters of the nano-polystyrene (nano-PS) with a typical particle size of 90 nm were studied by employing thermogravimetric analysis (TG), MIE-D 1.2 minimum ignition energy (MIE) test device, and 20-L spherical dust explosion test equipment. The results showed that the thermal decomposition of the nano-PS occurred in a two-step process which was different from the single process for conventional PS. Meanwhile, the reaction rate of the thermal decomposition for nano-PS increased with the heating rate. The TG and DTG curves shifted to the higher-temperature zone when the heating rate increased, and the initial temperature, final temperature, temperature at the maximum rate, and the maximum rate also increased. The sensitivity parameter of the minimum ignition energy of nano-PS varied as the dust concentration altered, and the most sensitive explosive concentration was about 200 g m−3. Also, nano-PS was proved to be quite sensitive to the electrostatic spark, as its calculated MIE value was as low as 11 mJ. For the severity parameters, the explosion pressure and its rising rate of nano-PS tended to increase at first and then decrease with the increase in dust concentrations. According to the risk classification standard, the explosion risk class of nano-PS was St2. The results were further extensively compared to other previous works. The results demonstrated both the higher explosion possibility and severity of nano-PS. This study could provide guidance for the safety management of nano-PS in its manufacture, storage, and handling process.

Novel method for hybrid gas-dust cloud ignition using a modified standard minimum ignition energy device

Hybrid dust-gas explosions are a persistent problem in the process industries because of their low ignition energy and serious consequences. The probability of ignition of a hybrid dust-gas mixture is quantified by its minimum ignition energy (MIE). This study aims at improving the MIE measurement of hybrid dust-gas systems using a modified Kühner MIKE3 MIE apparatus. The modification includes an add-on device in order to purge the Hartmann tube with the gas of the hybrid mixture before the dust dispersion and ignition attempt. This ensures the gas composition in the Hartmann tube is the same as that of the gas used for dispersing the dust.In this study, the MIE for a hybrid system consisting of Pittsburgh Pulverized Coal (PPC), methane and air was examined. MIE testing was conducted for the two cases: case (a) followed the ASTM E2019-03 standard procedure, while case (b) applied a pre-dispersion purge of the Hartmann tube with the methane-air mixture. In addition, this hybrid system MIE study was conducted with two different particle sizes of PPC, having equivalent polydispersity. Certified cylinders consisting of methane (1, 2, and 3 vol %) blended with ultra-high purity (UHP) air (21.00% oxygen and 79.00% nitrogen) were used.Significant differences in the MIE values of the hybrid dust-gas system were found between the two cases for both particle sizes. The hybrid MIE values obtained with a pre-dispersion purge of the Hartmann tube were found to be lower than those without the purge (which is the most common testing approach); while a smaller particle size also resulted in a lower hybrid MIE. Additionally, it was found that for experiments with or without pre-dispersion purge, and for both particle sizes, the greater the methane concentration, the lower the MIE.This study proves that many of the previous hybrid MIE studies in the Hartmann tube are non-conservative. Future studies should be conducted by including a pre-dispersion purge in the testing procedure. This work lays the foundation for improving the existing ASTM E2019-03 or developing a standalone standard for hybrid dust-gas system MIE testing.