Skeletal Mechanism Research Articles

Skeletal CH3OH/NOx Kinetic Model for Simulating Spark-Ignition and Turbulent Jet Ignition Engines.

Methanol is a promising renewable fuel for achieving a better engine combustion efficiency and lower exhaust emissions. Under exhaust gas recirculation conditions, trace amounts of nitrogen oxides have been shown to participate in fuel oxidation and impact the ignition characteristics significantly. Despite numerous studies that analyzed the methanol/NOx interaction, no reliable skeletal kinetic mechanism is available for computational fluid dynamics (CFD) modeling. This work focuses on developing a skeletal CH3OH/NOx kinetic model consisting of 25 species and 55 irreversible and 27 reversible reactions, used for full-cycle engine combustion simulations. New experiments of methanol with the presence of 200 ppmv NO/NO2 were conducted in a rapid compression machine (RCM) at engine-relevant conditions (20-30 bar, 850-950 K). Experimental results indicate notable enhancement effects of the presence of NO/NO2 on methanol ignition under the conditions tested, which highlights the importance of including the CH3OH/NOx interactions in predicting combustion performance. The proposed skeletal mechanism was validated against the literature and new methanol and methanol/NOx experiments over a wide range of operating conditions. Furthermore, the skeletal mechanism was applied in three-dimensional (3D) CFD full-cycle simulations of spark-ignition (SI) and turbulent jet ignition (TJI) engine combustion using methanol. Simulation results demonstrate good agreement with experimental measurements of pressure traces and engine metrics, proving that the proposed skeletal mechanism is suitable and sufficient for CFD simulations.

Reduced Chemical Kinetic Models of DME Based on Variance Filtering Method

Based on the variance value of each species concentration during the combustion process, a new chemical mechanism reduction method is proposed. The data sets which are the molar concentration of each species are generated based on numerical results of zero-dimensional homogeneous ignition process using detailed chemical kinetic mechanisms under various operating conditions. By calculating and analyzing the variance value of each species concentration during the combustion process to determine the contribution of each species to the combustion process, and by selecting a suitable threshold value to determine whether the species and elementary reactions are removed or not. The skeletal mechanisms of DME generated by using the present VFM method are compared to those generated by the path flux analysis (PFA) method and the detailed mechanism. The comparisons of the temperature and the concentration of important species showed that with either the same or significantly smaller number of species, the skeletal mechanisms generated by the present VFM method are more accurate than that of PFA in a broad range of initial pressures, temperatures and equivalence ratios. In addition, the reduction speed of VFM is one orders of magnitude faster than that of PFA.

Simulations of n-dodecane/oxygen/nitrogen cellular detonations

In this work, two-dimensional n-dodecane/air/nitrogen cellular detonations are simulated with various equivalence ratios (ERs). A skeletal mechanism consisting of 54 species and 269 reactions is used. The lower and upper equivalence ratio boundaries for self-sustained detonation are 0.3 and 2.2, respectively. Detonation with different regimes characterized by the detonation cell patterns is observed, which aligns well with the category based on the stability parameter, i.e., weakly and highly unstable detonations, and extinction. In terms of the frontal structure, non-negligible effect of diffusion on the cellular detonation is revealed, especially in the vicinity of the leading shock front. In highly unstable and quenched detonations, the alternation in reaction pathway within the induction zone accounts for the changes of detonation dynamics, such as the absence or extended sequence of important radical formation, e.g., OH. In addition, the composition of the unburned pockets depends on both pocket location from the leading shock front and the ER in the fresh mixture, because the former determines the residence time, whilst the latter affects the pocket reaction rate.

Large Eddy Simulation of the Effect of Hydrogen Ratio on the Flame Stabilization and Blow-Off Dynamics of a Lean CH4/H2/Air Bluff-Body Flame

This study investigated the flame structure and dynamics of a bluff-body flame when numerically close to blow-off conditions. This includes the impact of the hydrogen ratio on lean CH4/H2/air flame stabilization and blow-off characteristics. In this study, we assessed the impacts of four different hydrogen ratios: 0%, 30%, 60%, and 90%. Large eddy simulation (LES) was coupled with a thickened flame (TF) model to determine the turbulent combustion using a 30-species skeletal mechanism. The numerical results were progressively validated using OH-PLIF and PIV techniques. The results obtained from the numerical simulations showed minor differences with the experimental data on the velocity field and flame structure for all conditions. The presented results reveal that the flame is stabilized in higher-strain-rate spots more easily in the presence of high hydrogen ratios. Moreover, the flame location moves away from the concentrated vortex area with an increasing hydrogen ratio. The results of our blow-off investigation indicate that the blow-off sequence of a premixed bluff-body flame can be separated into two stages. The entire blow-off process becomes shorter with an increase in the hydrogen ratio. The primary reason for global extinction is a reduction in the heat release rate, and enstrophy analysis implies that blending hydrogen can reduce the enstrophy values of flames at the downstream locations. The dilatation and baroclinic torque terms decrease close to blow-off, but their decline is not significant in high-hydrogen-ratio conditions.

Hybrid Algorithm for Development of Reduced Skeletal Kinetic Mechanisms with Specific Species Targeting.

A novel algorithm is introduced to reduce the number of detailed kinetic mechanisms. The algorithm uniquely employs a classification of species and a defined parameter that quantitatively identifies the contribution of each species under a combustion condition of interest with specific species targeting. It also incorporates sensitivity analysis, the directed relation graph (DRG) method, and dynamic refinement. The proposed procedure is applied to the GRI-3.0 mechanism with atmospheric pollutants (CO, CO2, NO, and NO2) targeted in a lean methane-air flame at high pressures. The performance of the reduced mechanism is assessed, and good accuracy with considerable computational cost reduction is achieved. Investigated properties by the perfectly stirred reactor (PSR) model incorporated adiabatic flame temperature and the concentrations of targeted pollutants versus equivalence ratio (0.5-1.2), pressure (1-14 bar), and residence time (0.001-1 s) variations. The maximum prediction errors of temperature and greenhouse gas (GHG) mole fractions' profiles were less than 1%, while NOx versus residence time showed errors of 11.7 and 4%, respectively. Additionally, the flame speed yielded a maximum deviation of less than 2%. The computational cost in a 2D (axisymmetric) simulation revealed a 61% reduction. It is shown that the introduced algorithm is effective and can be applied to large mechanisms aiming for particular species predictions under specified operating conditions with lower computational costs.

Cross-effect considered skeletal chemical mechanism construction for primary reference fuel/oxymethylene ethers blends using radical trace and sensitivity analysis

Oxymethylene ethers (OMEn, n = 1–6) are a class of synthetic liquid fuels that carry a great potential to reduce carbon dioxides (CO2) and particle matter emissions. However, the lower heating value of all OMEn is inferior to conventional diesel fuel, hindering their applications in compression-ignition engines. Instead, their utilizations as diesel additives have attracted considerable attention. Unfortunately, the blending chemistry of OMEn and alkanes has not been investigated thoroughly. This study proposes a practical skeletal oxidation mechanism for primary reference fuel (PRF)/OME1–6. First, the skeletal chemical mechanisms for OME3, iso-octane, and n-heptane are constructed utilizing reaction class-based global sensitivity analysis. Then, the interactions among the three fuels are identified through sensitivity analysis and OH radical trace. It is found that the cross effects of the three fuels mainly occur in low-temperature regimes, and H-atom abstraction reactions have a significant influence on the co-oxidation of blended fuels. Additionally, blending OME3 with n-heptane impedes the consumption of OME3 from undergoing certain pathways, including the formation of cyclic ether from QOOH and the second time oxygen addition. The reactivity of iso-octane/OME3 blends at low temperatures is majorly driven by OME3 because of the low reactivity of iso-octane. Based on reaction rate rules, the skeletal mechanisms for OME1–6 are derived on the basis of the OME3 mechanism constructed above. The experiments in jet-stirred reactors fueled with OME3/iso-octane and OME3/n-heptane respectively with various blending ratios are conducted to evaluate the performance of the present skeletal mechanism. In addition, the mechanism is comprehensively validated against the experimental data regarding neat fuels and their mixtures for PRF/OME1–6, including species concentrations in jet-stirred reactors and premixed flames, auto-ignitions in shock tubes and rapid compression machines, and laminar flame speeds under a wide range of operating conditions (p= 0.04–58 atm, φ=0.25–4.0, and T= 500–1800 K). Good consistencies between simulations and laboratory observations are achieved.

Development of a Compact Skeletal Mechanism for Thermally Cracked Hydrocarbon Fuels

ABSTRACT The construction of a compact kinetic mechanism for thermally cracked hydrocarbon fuels holds great importance for developing advanced engine with regenerative cooling. In the present study, a skeletal oxidation mechanism consisting of 104 species and 373 reactions, which can be divided into two parts, i.e. a core mechanism for pyrolysis gas, and a skeletal sub-mechanism for pyrolysis liquid, was developed by a decoupling method. The combustion process of pyrolysis gas and its pure constituents was depicted by incorporating detailed reaction pathways of H2/CO/C1-C4 molecules, and variations of hydrocarbon classes, as well as carbon number distributions were also considered by introducing eight skeletal sub-mechanisms for heavy hydrocarbons which covered chain alkanes, cycloalkanes, and monocyclic aromatics in pyrolysis liquid, thus the newly developed mechanism was suitable for thermally cracked hydrocarbon fuels over a wide range of pyrolysis temperatures. The skeletal mechanism was extensively validated by experimental data of laminar burning velocities and ignition delay times, confirming its applicability for reproducing the flame characteristics of pyrolysis gases, pyrolysis liquids, and thermally cracked fuels. Sensitivity analyses showed that laminar burning velocities of thermally cracked fuels were only affected by reactions involving small radicals when the pyrolysis temperature was lower than 600°C, while reactions involving benzene rings started to dominate the flame propagation of thermally cracked fuel at 650°C under fuel-lean, stoichiometric, and fuel-rich conditions. Reactions of small radicals and heavy hydrocarbons both affected the ignition process of thermally cracked fuels.

Family of Skeletal Reaction Mechanisms for Methane–Oxygen Combustion in Rocket Propulsion

Analyzing methane–oxygen rocket propellant combinations requires suitable modeling of the major chemical reaction processes. Although several detailed kinetic mechanisms for methane oxidation in air exist, most do not reproduce the reaction pathways of high-pressure methane–oxygen combustion, typical of liquid rocket engines. Moreover, when large-scale computational fluid dynamics simulations are pursued, detailed reaction schemes are not computationally viable. In the present study, we identify a reliable detailed kinetic scheme for liquid rocket applications, and then we perform a wide reduction campaign leveraging computational singular perturbation theory. Enforcing various reduction targets, we obtain a family of seven skeletal schemes, including 11–39 species. Each mechanism targets different combustion modes, namely, homogeneous ignition, complex flows and flame extinction, premixed burning, reaction processes under intense turbulent mixing, and largely off-stoichiometric mixtures, typical of rocket engine preburners. We test the skeletal mechanisms against meaningful validation targets, attaining appreciable predictive accuracy compared with the detailed parent scheme. We expect the proposed family of skeletal schemes to offer a wide and flexible range of solutions—in terms of size, accuracy, and dominant combustion mode—for performing large-scale yet cost-affordable computational fluid dynamics of methane–oxygen flames under rocket-engine-relevant conditions.

A surrogate shale oil model based on a multi-objective fusion adaptive optimization considering its pyrolysis characteristics

A surrogate shale oil model was proposed based on model compounds with optimal proportions to reduce the complexity of Huadian shale oil to analyze its pyrolysis kinetics. There are mainly n-alkanes and n-olefins with C8–C36 in shale oil according to GC-MS results, a small amount of aromatics and alcohols, as well as trace of esters, ketones and nitriles, etc. Pyrolysis behavior of shale oil was investigated by Py-GC-MS and FTIR, including the evolution of pyrolytic products and functional groups. Here, n-eicosane, 1-octadecene, pentadecanol and nonylbenzene were selected as surrogates based on GC-MS result. To obtain the optimal surrogate model, a novel multi-objective fusion adaptive optimization function with constraints was proposed to determine the optimal weighting factor of each component from the pareto optimal set. Then, the detailed pyrolysis kinetic mechanisms containing 745 species and 19392 reactions were developed to study its thermochemical conversion. Moreover, the skeletal mechanism reduced by decoupling and directed relation graph (DRG) was used to describe the thermal flow reactivity of these four components. In sum, this work provides an integrated description of shale oil pyrolysis, and gives a new method for studying the pyrolysis of oil shale intrinsically.

Reduced mechanisms for methanol oxidation under hydrothermal flames using a directed relation graph with sensitivity analysis and error propagation

AbstractA revised detailed mechanism (RDM) including 173 species and 1011 reactions for methanol oxidation under hydrothermal flames is developed via modifying a methanol gas‐phase combustion mechanism with pressure and thermodynamic corrections and validated with experimental data. Different skeletal mechanisms are generated via the directed relation graph (DRG), the DRG with error propagation (DRGEP), the DRG with sensitivity analysis (DRGSA), and the DRGEP with sensitivity analysis methods. Although the skeletal mechanisms have different reaction paths, the evolutions of the main species in the RDM are generally reproduced. The most compact mechanism of 12 species and 35 reactions is obtained via the DRGSA method with an error of 7.59%. The temperatures of hydrothermal flames predicted from the skeletal mechanisms with different reduction methods agree well with those from the RDM within most operating ranges except the 12‐species mechanism under hypoxic conditions. The increase in the reduction degree increases the error of the ignition delay time, while the reduced mechanisms have better adaptability in predicting the ignition delay time at higher preheating temperatures. The increases of preheating temperature and methanol concentration decrease the error in the prediction of the laminar flame speed with the reduced mechanisms. Moreover, the mechanisms with different reduction degrees have little effect on the extinction temperature, with an error of 4–8°C.

Development of two diesel surrogates focusing on the soot emission under engine-like conditions

ABSTRACT Threshold sooting index (TSI) is one of the critical properties related to the soot emission of diesel. Investigating the effects of TSI on the prediction of soot emission and the response of the soot model to TSI may improve our understanding of the soot formation process and model establishment during the combustion of diesel under engine-like conditions. To meet this need, two different d.iesel surrogates, named S1 and S2 were developed. S1 comprised n-dodecane, iso-octane, methylcyclohexane, and 1-methylnaphthalene, while S2 replaced 1-methylnaphthalene with toluene. Both were adjusted for similar cetane numbers, H/C ratios, and heating values, differing in TSI to analyze sooting tendencies to ensure the S1 and S2 had different soot tendencies but close ignition quality. Then, the skeletal mechanism containing the kinetics of the components in S1 and S2 was developed and validated against ignition delay times, speciation, laminar flame speeds and the 3-D spray combustion with results agreeing well with predictions. Finally, the soot performances of S1 and S2 in different soot models were compared in the constant volume combustion chamber (CVCC). The results showed that the comparison of S1 and S2 in different soot models could promote the understanding of soot models.

A transcriptomic analysis of skeletal muscle tissues reveals promising candidate genes and pathways accountable for different daily weight gain in Hanwoo cattle

Cattle traits like average daily weight gain (ADG) greatly impact profitability. Selecting based on ADG considering genetic variability can lead to economic and genetic advancements in cattle breeding. This study aimed to unravel genetic influences on ADG variation in Hanwoo cattle at the skeletal muscle transcriptomic level. RNA sequencing was conducted on longissimus dorsi (LD), semimembranosus (SB), and psoas major (PM) muscles of 14 steers assigned to same feed, grouped by low (≤ 0.71 kg) and high (≥ 0.77 kg) ADG. At P ≤ 0.05 and log2fold > 1.5, the distinct pattern of gene expression was identified with 184, 172, and 210 differentially expressed genes in LD, SB, and PM muscles, respectively. Tissue-specific responses to ADG variation were evident, with myogenesis and differentiation associated JAK-STAT signaling pathway and prolactin signaling pathways enriched in LD and SB muscles, while adipogenesis-related PPAR signaling pathways were enriched in PM muscle. Key hub genes (AXIN2, CDKN1A, MYC, PTGS2, FZD5, SPP1) were upregulated and functionally significant in muscle growth and differentiation. Notably, DPP6, CDKN1A, and FZD5 emerged as possible candidate genes linked to ADG variation. These findings enhance our understanding of genetic factors behind ADG variation in Hanwoo cattle, illuminating skeletal muscle mechanisms influencing ADG.

The role of chemistry in the retardant effect of dimethyl methylphosphonate in flame–wall interaction

Organophosphorous compounds can act as chemical inhibitors for fire suppression and have recently received significant attention in the combustion community due to their potential to induce flame extinction through a radical recombination process. To optimize their use, a comprehensive understanding of the extinction dynamics is essential. In this study, mixtures of methane with dimethyl methylphosphonate (DMMP) are investigated in laminar conditions, with a specific focus on flame–wall interaction. The ultimate objective is obtaining a deeper insight into the flame quenching process, which is synergistically enhanced by heat transfer to the wall and the chemical retardant effect of DMMP. Detailed chemistry information is implemented by setting up an ad-hoc skeletal kinetic mechanism. This is developed and validated for flame configurations with increasing complexity, including freely propagating premixed flames, head-on-quenching flames, and side-wall quenching flames. The results indicate that the skeletal mechanism is able to reproduce available experimental data for flame speed and ignition delay time, as well as the main flame features and quenching characteristics in flame–wall interactions for an increasing level of DMMP. Simulations of a side-wall quenching burner, incorporating a secondary fuel injection through a porous insert at the wall, are carried out. Chemical analyses provide detailed insight into the role of flame retardant during the flame quenching process. The results show that the HOPO/PO2 catalytic cycle is of major importance for the suppressant effect, further supported by the formation of CH3PO2 as an intermediate, increasing the formation of HOPO itself. Moreover, the CO mass fraction is observed to increase also because of the radical scavenging effect, inhibiting the conversion to CO2 via CO ＋ OH → CO2 ＋ H. Overall, this study advances the understanding of the chemical features of flame quenching in the presence of flame retardants containing implications for fire safety applications.

Application of static integrated skeletal reduction and tabulation of dynamic adaptive chemistry in the combustion simulation of ethylene-fueled scramjet combustor.

The high-fidelity reduced mechanism is one of the key elements in the combustion simulation of scramjet combustors to reveal their combustion and flow phenomena. In the present work, the hierarchically constructed NUIGMech1.2 (2857 species and 11 814 reactions) is applied to the combustion simulation of an ethylene-fueled scramjet combustor using the method of static integrated skeletal reduction and tabulation of dynamic adaptive chemistry (TDAC). The integrated skeletal reduction strategy successively consists of species elimination using the revised directed relation graph with error propagation method of fixed species scheme and improved sensitivity analysis method, and reactions elimination based on computational singular perturbation importance index. A preferred ethylene skeletal mechanism (26 species and 117 reactions) is obtained through the integrated skeletal reduction strategy under target working conditions of temperature range of 900-1800 K, pressure range of 1-4 atm, and equivalence ratio range of 0.25-5.0. The compact skeletal mechanism is comprehensively validated against the experimental results of ignition delay times, laminar flame speeds, and key species concentration profiles. Meanwhile, it shows consistent results with the detailed mechanism on the adiabatic flame temperature profiles and "S"-curves. When applying this skeletal mechanism to combustion simulations of ethylene-fueled scramjet combustor with double parallel cavities, the path flux analysis method and in situ adaptive tabulation algorithm of TDAC is further utilized to speed up the chemical reaction solution process at run-time. Under the scramjet and ramjet modes, the corresponding simulation results in terms of flame luminosity images, schlieren images, and static pressure distributions, coincide well with those of experimental measurements. The combustion and flow characteristics of the two modes are investigated and analyzed comparatively based on above results and combustion performance parameters. Present work contributes to the application of fuel kinetic mechanisms in scramjet combustor combustion simulation.

Numerical Modeling of Chemical Kinetics, Spray Dynamics, and Turbulent Combustion towards Sustainable Aviation

With growing interest in sustainable civil supersonic and hypersonic aviation, there is a need to model the combustion of alternative, sustainable jet fuels. This work presents numerical simulations of several related phenomena, including laminar flames, ignition, and spray flames. Two conventional jet fuels, Jet A and JP-5, and two alternative jet fuels, C1 and C5, are targeted. The laminar burning velocities of these fuels are predicted using skeletal and detailed reaction mechanisms. The ignition delay times are predicted in the context of dual-mode ramjet engines. Large Eddy Simulations (LES) of spray combustion in an aeroengine are carried out to investigate how the different thermodynamic and chemical properties of alternative fuels lead to different emergent behavior. A novel set of thermodynamic correlations are developed for the spray model. The laminar burning velocity predictions are normalized by heat of combustion to reveal a more distinct fuel trend, with C1 burning slowest and C5 fastest. The ignition results highlight the contributions of the Negative Temperature Coefficient (NTC) effect, equivalence ratio, and hydrogen enrichment in determining ignition time scales in dual-mode ramjet engines. The spray results reveal that the volatile alternative jet fuels have short penetration depths and that the flame of the most chemically divergent fuel (C1) stabilizes relatively close to the spray.

An Assessment of the Validity of Damköhler’s Hypotheses for Different Choices of Reaction Progress Variable in Homogenous Mixture Moderate or Intense Low-Oxygen Dilution (MILD) Combustion

The applicability of Damköhler’s hypotheses for homogenous mixture (i.e. constant equivalence ratio) moderate or intense low-oxygen dilution (MILD) combustion processes (with methane as the fuel) has been assessed using three-dimensional direct numerical simulation data with a skeletal mechanism. Two homogeneous MILD combustion cases with different levels of O2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{\ ext{O}}}_{2}$$\\end{document} concentration (4.8% and 3.5% by volume) and different turbulence intensities have been investigated to analyse the influence of dilution level, turbulence intensity and the choice of the reaction progress variable definition (i.e. different choices of major species for turbulent burning velocity and flame surface area evaluations) on the applicability of Damköhler’s hypotheses in MILD combustion. It has been found that the normalized volume-integrated burning rate remains of the same order of magnitude as that of the normalized flame surface area only for the reaction progress variable definition based on a species mass fraction which has a Lewis number close to unity (e.g. CH4\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{\ ext{CH}}}_{4}$$\\end{document}) but the level of applicability deteriorates when the Lewis number of the species mass fraction, based on which the reaction progress variable is defined, deviates significantly from unity (e.g. CO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{\ ext{CO}}}_{2}$$\\end{document}). Moreover, it has been demonstrated that the flame surface area calculation from the OH mole fraction-based information can lead to significant departures from Damköhler’s first hypothesis. It is also found that the relative magnitudes of normalised volume-integrated burning rate and normalised flame surface area are significantly affected by the level of dilution and the choice of the reaction progress variable definition. Damköhler’s second hypothesis, which provides a relation between the normalised turbulent burning velocity and the ratio of turbulent to molecular diffusivities, has been found to hold in an order of magnitude sense in homogeneous mixture MILD combustion only for the reaction progress variable definition based on species that has a Lewis number close to unity (e.g. CH4\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{\ ext{CH}}}_{4}$$\\end{document}) but the level of disagreement increases as the Lewis number of the reaction progress variable deviates significantly from unity (e.g. CO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{\ ext{CO}}}_{2}$$\\end{document}).

A novel machine learning based lumping approach for the reduction of large kinetic mechanisms for plasma-assisted combustion applications

The development of skeletal mechanisms has become essential for multi-dimensional simulations of plasma-assisted combustion (PAC). However, reduction tools developed for traditional combustion applications are not always applicable to PAC, due to the complex interplay between non-equilibrium plasma and combustion kinetics. Plasma direct relation graph with error propagation (P-DRGEP) is a recent plasma-specific reduction method developed in order to incorporate plasma energy branching in the reduction. In the first part of this work, the applicability of P-DRGEP to large kinetic mechanisms is investigated. A detailed isooctane/air plasma mechanism containing 2805 species and 18457 reactions is reduced to 415 species and 4716 reactions, keeping errors on ignition time within 3% for a wide range of initial conditions: from 750 K to 1200 K, 10 atm and equivalence ratios from 0.75 to 1.50. The second part focuses on isomer lumping, which is another reduction technique widely used in combustion. When applied to PAC, it is shown that the resulting lumped mechanism produces poor results. A novel plasma-specific isomer lumping strategy using machine learning is proposed instead. With the supervised algorithm of gradient boosting, predictive regression models are generated, which describe rate coefficients of lumped reactions adequately. These models are trained with simulation data. Leveraging this newly proposed lumping approach on the reduced mechanism, allows for an additional 28% reduction in the number of species and 19% reduction in the number of reactions. Two different versions are presented: in the first one the models are trained using one input feature (1D), while in the second one, two input features are selected (2D). The resulting lumped mechanism is shown to produce accurate predictions of PAC over the entire parameter space of interest, while significantly decreasing the computational time. Indicatively, with the 1D version the maximum error on ignition time in this range of conditions is 6%. The 2D approach produces even lower errors, which do not exceed 3%.Novelty and significance statementIn this work, a novel approach for isomer lumping, in plasma-assisted combustion mechanisms, is demonstrated. This plasma-specific approach, uses predictive machine learning regression models to describe the complex evolution of lumped reaction rate coefficients. Combining it with the plasma direct relation graph with error propagation, a powerful reduction framework is created, which is successfully demonstrated on a detailed isooctane/air plasma kinetic mechanism, via zero-dimensional ignition simulations. This framework constitutes a useful tool towards the creation of highly accurate skeletal mechanisms, which significantly reduce the computational costs of simulations.

An enhanced Sample-Partitioning Adaptive Reduced Chemistry method with a-priori error estimation

Reactor-based approaches for handling the Turbulence–Chemistry-Interactions closure have the advantage of embedding finite-rate chemistry in the combustion model of RANS and LES simulations, which might be crucial for the solution accuracy when complex combustion regimes are investigated. However, the numerical solution of the chemical ODEs is burdened with stiffness and increased dimensionality, especially when large detailed mechanisms are required. To this end, the Sample-Partitioning Adaptive Reduced Chemistry (SPARC) methodology couples adaptive chemistry and machine learning to speed-up the chemistry integration in reactive flows simulations. It consists in building a library of skeletal mechanisms, associated to clusters of similar thermo-chemical states identified in a training dataset, and then, at run-time, each computational cell is assigned to a specific cluster, whose skeletal mechanism is retrieved and employed for the time integration. Such workflow builds on four interacting blocks, i.e., training dataset generation, clustering, mechanism simplification, and classification, and its success tightly depends on the quality of each block, which generally results from a combination of theoretical, methodological, and computational choices. In this paper, we explore the effects of the mechanism simplification strategy on the SPARC performance and we develop an ad-hoc procedure that automatically identifies the cluster-wise optimal reduction parameters, delivering a higher global reduction and therefore a larger computational speed-up compared to a standard approach, along with an explicit a-priori control on accuracy. We implement and test this novel procedure on a RANS simulation of the Adelaide Jet-in-hot-coflow (AJHC) burner, and we attain a ∼2x CPU time improvement with respect to the simulation obtained with a 36-species detailed mechanism.Novelty and significance This work makes a contribution towards the acceleration of chemistry integration in reactive flows simulations. More specifically, the Sample-Partitioning Adaptive Reduced Chemistry method, which couples adaptive chemistry and machine learning, is enhanced with automatic target species definition and a-priori error estimation. The novelties lie in the utilization of the computational singular perturbation (CSP) reduction algorithm, which provides means for automatically identifying an adaptive set of target species, and in the definition of a novel strategy for assessing the performance of the reduced mechanisms in the pre-processing phase, with the goal of estimating a measure of accuracy of the upcoming CFD simulation.

Research progress on lightweight technology of exoskeleton robot

Exoskeleton robots are wearable devices designed to mimic the skeletal mechanisms of insects and humans Enhancing users body functioning. In recent years, exoskeleton robot has become one of the hot spots in military and medical fields. In the process of exoskeleton robot research and development, how to achieve lightweight exoskeleton robot design is the goal of many research and development teams. Lightweight design is of significant importance in the development of exoskeleton robots since it can increase their efficiency and portability. With the improvement of modern processing technology, the lightweight technology of exoskeleton robot is becoming more and more mature. This paper summarizes the mature and promising lightweight technology of exoskeleton robot at present. In this paper, based on existing exoskeleton robots, the lightweight technology of these robots is analysed and reviewed in terms of their drive devices, power supply, structures and materials, and future development trends of the technology are suggested. This paper offers a reference the lightweight design of exoskeleton robot.

A wall heat transfer model and a skeletal reaction mechanism of iso-octane for CFD simulatiaon of gasoline engines

A wall heat transfer model and a skeletal reaction mechanism of iso-octane for CFD simulatiaon of gasoline engines