Concentration Distribution Of Species Research Articles

Theoretical reaction kinetics predictions for acetone and ketene with NH2 radicals: Implications on acetone/ammonia kinetic modeling

The cross-reaction kinetics of acetone/ketene (CH3COCH3/CH2CO) + amino (NH2) radicals are first theoretically reported for a wide range of conditions (T = 300–2500 K and P = 0.1–100 atm) in this work. The high-level electronic structure method CCSD(T)/cc-pVnZ(n = T, Q)//B3LYP-D3BJ/6–311++G(d,p) is used to explore the potential energy profiles on which the temperature- and pressure-dependence kinetic behaviors of the title reactions are characterized using the Rice-Ramsperger-Kassel-Marcus/Master Equation (RRKM/ME) theory. Corrections of the one-dimensional hindered rotor approximation and asymmetric Eckart tunneling effect are also included in the rate constant calculations. Furthermore, this work delves into the competitive relationships among the H-abstraction, NH2 addition and addition-dissociation reaction pathways. For CH3COCH3 + NH2, the H-abstraction reaction of CH3COCH3 is highly favored over the addition-dissociation reaction and other isomerization channels. For CH2CO + NH2, the reaction channel of addition-dissociation to form CH2NH2 + CO under low temperature conditions is more advantageous, while the H-abstraction reaction plays a dominant role under combustion conditions (T ≥ 1000 K). To reveal the impact of the studied reaction kinetics on model predictions, the rate constants of dominant reaction channels calculated in this work are incorporated into a kinetic model for the auto-ignition, oxidation and pyrolysis of CH3COCH3/NH3 mixtures. The simulated results show that the effect of the updated rate constants on ignition delay time is mainly at low temperatures and the promotion effect of CH3COCH3 addition on the ignition of NH3 presents a nonlinear enhancement. The updated rate constants can also accelerate the consumption of CH3COCH3 and CH2CO formation, while also influence the concentration distributions of other significant species (e.g., NH3, CO). Therefore, the cross-reaction kinetics of CH3COCH3/CH2CO + NH2 are critical in controlling the fuel consumption, important intermediate formation and ignition delay time of CH3COCH3/NH3 mixtures.

Numerical and experimental study on fractal flow field for improving the performance of non-aqueous redox flow battery

The flow field design of the non-aqueous redox flow battery (RFB) decides the electrolyte flow and mass transfer of active species inside porous electrode, which has a significant influence on the operation of RFB. In this work, a fractal tree-like flow channel is proposed to enhance the electrolyte convection and optimize the concentration distribution of active species inside the graphite felt electrode, thus boosting the overall battery performance. Using the finite element simulation method, a three-dimensional numerical model of single cell is established to comparatively study the steady-state discharge process characteristics of deep eutectic solvent (DES) electrolyte-based vanadium‑iron RFBs with fractal and serpentine flow fields, respectively. Moreover, by assembling the single cell of this RFB and building the full cell test system, an experimental study is conducted to compare the discharging output voltage and power of the RFBs with serpentine flow field and fractal flow fields of different fractal dimensions. The numerical results show that the fractal tree-like flow field can improve the discharging power of RFB as well as reduce the pumping loss compared with the conventional serpentine flow field. That is mainly attributed to that fractal flow field is conducive to reducing the polarization loss and strengthening the convection in porous electrode simultaneously. What's more, the role of fractal dimension of flow field is also investigated numerically, thus knowing that large fractal dimension promotes lower pumping loss while small fractal dimension is in favor of higher output voltage. In addition, the experimental results also demonstrate that the fractal flow field could improve the output voltage and maximum discharging power of RFB compared to serpentine flow field. This work provides an optimization method for the flow field design of DES electrolyte-based vanadium‑iron RFB, and is expected to be employed in the other non-aqueous RFBs.

CFD modeling investigation of oxy-fuel combustion application in an industrial-scale FCC regenerator

The increase in atmospheric CO2 concentration and its consequential impact on climate change have elicited increased public concern. The refinery units including fluid catalytic cracking (FCC) generate substantial quantities of CO2. To mitigate the emission from the FCC process, oxy-fuel combustion has emerged as a prospective carbon capture and storage technology. This study presents the first trial for the modeling investigation of a 70 kt/a industrial FCC regenerator under the scenario of retrofitting it with oxy-fuel combustion technology. Employing the Eulerian-Eulerian model, a CFD model integrating heat transfer and coke combustion reactions has been established. The detailed hydrodynamics, temperature, and species concentration distribution inside the regenerator are obtained under both air-firing and oxy-firing conditions, which are further compared to exploit the possibility of oxy-fuel combustion retrofitting. As has been found, decreases in gas temperature and carbon conversion rate were observed for 21 % O2/79 % CO2 atmosphere in comparison to the air reference case due to the differences in gas properties between N2 and CO2. This discrepancy resulted in a drop of 17 K in dilute phase temperature and 2 K in dense phase temperature. The bed density also exhibited a large with the oxy-firing conditions, with notable observations revealing a lower bed density below a height of 4.2 m, transitioning to a higher density above said height. Sensitivity analysis was also conducted for three principal operating parameters, including superficial gas velocity, oxygen partial pressure, and catalyst circulation rate. An increase of oxygen partial pressure to 27 % or a decrease of the catalyst circulation rate to 20.7 kg/s proved effective in achieving the same temperature profile and even a slightly better carbon conversion in comparison to air-firing regeneration.

Measurement of engine exhaust plume temperature and concentration distributions with tomographic absorption spectroscopy and learning-based absorbance recovery

Measuring the spatial distribution of temperature and species concentration is important to the thermodynamic analysis and validation of modern combustion systems. In this work, we developed a measurement method based on tomographic absorption spectroscopy (TAS) for the quantitative measurement of two-dimensional distributions of gas temperature and concentration. A learning-based absorbance recovery method was proposed and incorporated into TAS to address the baseline error induced distortion of absorbance and improve the accuracy of single path measurement. The developed TAS system, consisting of 12 laser beams, was demonstrated on a diesel fueled small turbojet engine. Temperature and H2O concentration distributions of the exhaust plume were measured with laser wavelength scan rates of 20 kHz. Temperature variations in microsecond-scale were captured and the time-averaged center temperature agreed well with thermocouple measurements. The developed TAS method demonstrates the feasibility of real-time and accurate tomographic imaging for practical combustion flows, which could be effectively applied for widespread combustion diagnostics.

Bipolar electrochemical sensor with perylene diimide-based cathodic luminophore for dopamine detection and imaging

Bipolar electrochemical microscopy (BEM), which visualizes the concentration distribution of molecular species in biological systems by electrochemiluminescence (ECL), is expected to be applied to the high-spatiotemporal-resolution imaging of biomolecules, enabling the analysis of cellular functions. In the past, the molecular species that could be imaged by BEM were generally restricted to oxidized molecules due to the limitation derived from the ECL mechanism of the luminophore. Recently, the imaging of dopamine (DA), a reduced molecule, was achieved using Ru (bpy)32+/glutathione disulfide (GSSG) as a cathodic luminophore. However, a large driving voltage was required for ECL generation, resulting in a low S/N ratio. In this study, we employed N,N′-dimethyl-3,4,9,10-perylenetetracarboxylic diimide (PDI-CH3)/potassium peroxodisulfate (K2S2O8), which is a cathodic luminophore that can be reduced at a nobler potential to produce ECL than [Ru(bpy)3]2+/GSSG. First, the ECL mechanism of PDI-CH3/K2S2O8 was elucidated by using a PDI-CH3 drop-cast glassy carbon electrode (GCE) immersed in K2S2O8 solution as the working electrode in a 3-electrode system. The PDI-CH3 drop-casted GCE, a single closed bipolar electrode (c-BPE), was used as the cathode in the successful quantification of 50–500 μmol L−1 DA in a sample chamber in which a c-BPE anode was immersed, resulting in a high S/N. The selective detection of DA in the presence of ascorbic acid was achieved by modifying the anode with Nafion. Finally, DA imaging was demonstrated using a commercially available anisotropic conducting film with PDI-CH3 coating on the cathode surface as a c-BPE array. The change in the concentration distribution in the inflow of DA was successfully imaged based on the change in the ECL intensity at the c-BPE cathode. This BEM system is expected to be useful for DA imaging of the brain.

A method for estimating optimized porosity distribution in Reaction-Diffusion systems without reliance on topology optimization

Topology optimization is a powerful method for designing optimal structures within a given design domain, applicable not only to physical systems but also to systems involving chemical reactions. This study employs entropy generation analysis in nonequilibrium thermodynamics as a metric to evaluate optimization results in conjunction with topology optimization. To enhance our understanding of the relationship between topology optimization and entropy generation analysis, exact solutions were derived in a simple 0D case. Nevertheless, solving the partial differential equations associated with topology optimization can be computationally intensive and time-consuming. This study proposed an alternative approach that bypassed the need for optimization methods by introducing reasonable assumptions, thereby reducing the computational effort required. By assuming a linear distribution of species concentration, the proposed approach yielded comparable performance to that achieved by optimization methods. This research contributes to streamlining the design process of electrochemical devices and reducing the computational burden associated with optimization.

Mercury cycling in contaminated coastal environments: modeling the benthic-pelagic coupling and microbial resistance in the Venice Lagoon

Anthropogenic activities have been releasing mercury for centuries, and despite global efforts to control emissions, concentrations in environmental media remain high. Coastal sediments can be a long-term repository for mercury, but also a secondary source, and competing processes in marine ecosystems can lead to the conversion of mercury into the toxic and bioaccumulative species methylmercury, which threatens ecosystem and human health. We investigate the fate and transport of three mercury species in a coastal lagoon affected by historical pollution using a novel high-resolution finite element model that integrates mercury biogeochemistry, sediment dynamics and hydrodynamics. The model resolves mercury dynamics in the seawater and the seabed taking into account partitioning, transport driven by water and sediment, and photochemical and microbial transformations. We simulated three years (early 2000s, 2019, and 2020) to assess the spatio-temporal distribution of mercury species concentrations and performed a sensitivity analysis to account for uncertainties. The modeled mercury species concentrations show high temporal and spatial variability, with water concentrations in some areas of the lagoon exceeding those of the open Mediterranean Sea by two orders of magnitude, consistent with available observations from the early 2000s. The results support conclusions about the importance of different processes in shaping the environmental gradients of mercury species. Due to the past accumulation of mercury in the lagoon sediments, inorganic mercury in the water is closely related to the resuspension of contaminated sediments, which is significantly reduced by the presence of benthic vegetation. The gradients of methylmercury depend on the combination of several factors, of which sediment resuspension and mercury methylation are the most relevant. The results add insights into mercury dynamics at coastal sites characterized by a combination of past pollution (i.e. sediment enrichment) and erosive processes, and suggest possible nature-based mitigation strategies such as the preservation of the integrity of benthic vegetation and morphology.

Detailed kinetics modeling of sulfur species evolution in alternating reducing/oxidizing atmosphere

Under conditions of deep load fluctuation, the furnace of a coal-fired boiler experiences alternating reduction/oxidation atmospheres, which directly impact the evolution of sulfur species. Building upon our previous mechanism (Model I), this study specifically considered the influence of alternating atmospheres and proposed a comprehensive reaction model (Model II), incorporating 8 additional elementary reactions. The relative error in predicting the concentration distribution of sulfur species was reduced from 18% (Model I) to 13% (Model II). In the alternating atmospheres, the predominant sulfur species remained as SO2 and H2S. Sensitivity analysis revealed that S, SH, SO, HSO, and HOSO were the critical free radicals. The new supplementary reactions (118) H2S + M = SH + H + M and (116) H2S + O2=HSO + OH played a significant role in the generation and consumption of H2S and SO2. Rate of production analysis demonstrated that the alternating atmosphere impacted the production and consumption primary free radicals like O/H/OH, thus potentially causing changes of S, SH, SO, HSO, and HOSO; moreover, it introduced new reaction pathways for SH and SO. Finally, a simplified reaction pathway for the sulfur species evolution was proposed. This study seeks to provide insights into the sulfur species evolution under the peak regulation conditions in coal-fired boilers.

CSTNet: A Dual-Branch Convolutional Neural Network for Imaging of Reactive Flows Using Chemical Species Tomography.

Chemical species tomography (CST) has been widely used for in situ imaging of critical parameters, e.g., species concentration and temperature, in reactive flows. However, even with state-of-the-art computational algorithms, the method is limited due to the inherently ill-posed and rank-deficient tomographic data inversion and by high computational cost. These issues hinder its application for real-time flow diagnosis. To address them, we present here a novel convolutional neural network, namely CSTNet, for high-fidelity, rapid, and simultaneous imaging of species concentration and temperature using CST. CSTNet introduces a shared feature extractor that incorporates the CST measurements and sensor layout into the learning network. In addition, a dual-branch decoder with internal crosstalk, which automatically learns the naturally correlated distributions of species concentration and temperature, is proposed for image reconstructions. The proposed CSTNet is validated both with simulated datasets and with measured data from real flames in experiments using an industry-oriented sensor. Superior performance is found relative to previous approaches in terms of reconstruction accuracy and robustness to measurement noise. This is the first time, to the best of our knowledge, that a deep learning-based method for CST has been experimentally validated for simultaneous imaging of multiple critical parameters in reactive flows using a low-complexity optical sensor with a severely limited number of laser beams.

A Spatially Progressive Neural Network for Locally/Globally Prioritized TDLAS Tomography

Tunable diode laser absorption spectroscopy tomography (TDLAST) has been widely applied for imaging two-dimensional distributions of industrial flow-field parameters, e.g., temperature and species concentration. Two main interested imaging objectives in TDLAST are the local combustion and its radiation in the entire sensing region. State-of-the-art algorithms were developed to retrieve either of the two objectives. In this paper, we address the both by developing a novel multi-output imaging neural network, named as Spatially Progressive Neural Network (SpaProNet). This network consists of locally and globally prioritized reconstruction stages. The former enables hierarchical imaging of the finely resolved and highly accurate local combustion, but coarsely resolved background. The later retrieves a fine-resolved image for the entire sensing region, at the cost of slightly trading off the reconstruction accuracy in the combustion zone. Furthermore, the proposed network is driven by the hydrodynamics of the real reactive flows, in which the training dataset is obtained from large eddy simulation. The proposed SpaProNet is validated by both simulation and lab-scale experiment. In all test cases, the visual and quantitative metric comparisons show that the proposed SpaProNet outperforms the existing methods from the following two perspectives: a) the locally prioritized stage provides ever-better accuracy in the combustion zone; b) the globally prioritized stage shows turbulence-indicative accuracy in the entire sensing region for diagnosis of heat radiation from the flame and flame-air interactions.

Structural and solution speciation studies on selected [Cu(NN)(OO)] complexes and an investigation of their biomimetic activity, ROS generation and their cytotoxicity in normoxic, hypoxic and anoxic environments in MCF-7 breast cancer-derived cells

Reactive oxygen species(ROS) generation with subsequent DNA damage is one of the principle mechanisms of action assigned to copper-based anticancer complexes. The efficacy of this type of chemotherapeutic may be reduced in the low oxygen environment of tumours. In this study the cytotoxicity of three complexes, [Cu(dips)(phen)] (1), [Cu(ph)(phen)]·2H2O (2) and [Cu(ph)(bpy)]·H2O (3) (disp: 3,5-diisopropylsalicylate, phen: 1,10- phenanthroline, ph: phthalate, bpy: 2,2′-bipyridyl) were assessed for anticancer activity in the breast-cancer derived MCF-7 line under normoxic, hypoxic and anoxic conditions. In an immortalised keratinocyte HaCaT cell line, the cytotoxicity of complexes 2 and 3 was significantly reduced under both normoxic and hypoxic conditions, whilst the cytotoxicity of complex 1 was increased under hypoxic conditions. The ability of the complexes to generate ROS in the MCF-7 cell line was evaluated as was their ability to act as superoxide dismutase(SOD) and catalase mimics using a yeast cell assay. ROS generation was significant for complexes 2 and 3, less so for complex 1 though all three complexes had SOD mimetic ability. Given the ternary nature of the complexes, solution speciation studies were undertaken but were only successful for complex 3, due to solubility issues with the other two complexes. The concentration distribution of various species, formed in aqueous solution, was evaluated as a function of pH and confirmed that complex 3 is the dominant species at physiological pH in the mM concentration range. However, as its concentration diminishes, it experiences a progressive dissociation, leading to the formation of binary complexes of bpy alongside unbound phthalate.

A numerical study on the effects of using combined flow fields and obstacles on the performance of proton exchange membrane fuel cells

AbstractThe flow field structure has an important influence on the comprehensive performance of the proton exchange membrane fuel cell (PEMFC). This research investigates the effects of combined flow fields on the distribution of species concentration, the pressure drop, and the overall performance of PEMFC based on the polarization curve and power consumption ratio (PCR). Obstacles are arranged in different areas to study the mass transfer of the gas inside the combined flow field. The results show that the combined serpentine flow field improves the concentration distribution of species and the performance of the cell is enhanced with the increase of the proportion of the single‐channel serpentine structure in the combined flow field, but the PCR is decreased. The energy efficiency conversion in the low voltage region is better when the obstacles are arranged in the entire flow field. Moreover, the vortex effect generated by the obstacles enhances the convection ability under the rib parallel to the inlet direction, while the transverse vortex and secondary flow perpendicular to the inlet direction are weakened by the flow field structure so that the mass transfer of gas is enhanced.

Pore-scale study of calcite dissolution during CO2-saturated brine injection for sequestration in carbonate aquifers

The calcite reaction with carbonate acid is a prerequisite to release cations providing the reactant for mineral trapping, however, the complicated multiple physicochemical processes during calcite dissolution are hardly precisely captured in carbonate aquifers, impeding the CO2 sequestration technology. In this work, a pore-scale numerical study based on the lattice Boltzmann method coupled fluid flow, mass transport, heterogeneous reactions, and calcite structure evolution is implemented to investigate the calcite dissolution process. Firstly, the impact of pressure difference on this reaction is analyzed to identify two characteristic dissolution patterns. Selecting two typical pressure differences, namely 0.036 and 0.36 Pa, the dissolution dynamics under different temperatures from 25 to 85 °C is then investigated by species concentration and solid distributions elucidating that the effect of pressure difference on calcite dissolution will drop with the increment of temperature. Moreover, the regime diagram of calcite dissolution is plotted based on the relation between temperature and pressure. Finally, to upscale the simulation results to the representative element volume scale, the temporal evolution of normalized permeability, the normalized permeability-porosity relationship and the optimal operations are explored to find that the maximum discrepancy of the normalized permeability with the time among all cases is approximately seven times and the best operating conditions promoting the mineral trapping are a high-temperature formation with a high injection rate.

Concentration Distribution of Molecules and Other Species in the Model System Fe–NaCl–Na2S–H2SO4–H2O at Various Temperatures of the Electrocoagulation Process

Concentration Distribution of Molecules and Other Species in the Model System Fe–NaCl–Na2S–H2SO4–H2O at Various Temperatures of the Electrocoagulation Process

A Turbulent Mass Diffusivity Model for Predicting Species Concentration Distribution in the Biodegradation of Phenol Wastewater in an Airlift Reactor

In this study, a three-dimensional CFD transient model is established for predicting species concentration distribution in the biodegradation of phenol in an airlift reactor (ALR). The gas–liquid flow in the ALR is determined by the Euler–Euler method coupled with the standard k-ε model, and the bubble size is predicted by the population balance model (PBM). A turbulent mass diffusivity model is developed to simulate the turbulent mass transfer process and to predict the species concentration distribution. No empirical methods are needed as the turbulent mass diffusivity can be expressed by the concentration variance c2¯ and its dissipation rate εc. A good agreement is found between simulated and experimental results in the literature. It is not reasonable to assume a constant turbulent Schmidt number because the calculated distribution of turbulent mass diffusivity is not identical to that of turbulent viscosity. Finally, the hydrodynamic characteristics and biodegradation performance of the proposed model in a novel ALR are compared with that in the original ALR.

Analytical and experimental study on binary droplet evaporation: Inhibitory effect of adding mineral oil adjuvant to water

This work fundamentally explains the inhibitory effect of adjuvant on water droplet evaporation in pesticide application. An analytical droplet evaporation model coupled with the instantaneous distribution of temperature and species concentrations in the vapor film boundary layer accompanying with the droplet diameter decrease is developed to describe not only the droplet evaporation but also the surrounding boundary layer evolution process. Thermal and concentration boundary layer thicknesses as well as the property variations at the liquid-vapor interface are updated at each time step during the calculation. An adjuvant factor is defined to assess the inhibitory effect of the adjuvant on water droplet evaporation. The results show that adding a tiny amount of mineral oil adjuvant can inhibit water droplet evaporation. The analysis of droplet evaporation evolution demonstrates that the inhibitory effect is mainly controlled by mass diffusion where the concentration gradient surrounding the liquid-vapor interface dominates the overall phase change. A regression formula is introduced to express the dependence of droplet lifetime on temperature and humidity. The proposed model is proved to be suitable for the mixing condition with a tiny amount of adjuvant, which can be used to describe the mechanism of evaporation inhibition of pesticide adjuvant in plant protection.

Polyvinyl alcohol–potassium iodide gel probe to monitor the distribution of reactive species generation around atmospheric-pressure plasma jet

This study proposes polyvinyl alcohol–potassium iodide (PVA–KI) as a novel gel chemical probe. The probe uses the reactions among PVA, KI, water, borax, and oxidative species to visualize the distribution of reactive species. This method provides information regarding the distribution of reactive species by coloration on the gel surface. The effects of the surrounding gas phase on the distribution and diffusion of the reactive species are also investigated using the PVA–KI gel probe. Further, the relationship between the irradiation distance and reactive species diffusion is determined on the surface of the PVA–KI probe with and without plastic shielding. Adjusting the irradiation distance appropriately leads to an increase in the modified area as detected by the PVA–KI gel probe analysis. The relative concentration distributions of the reactive species are also obtained from visualized color distributions measured using a colorimeter. Furthermore, reactive species generation by long-scale line plasma is confirmed by the color reaction on the PVA–KI gel surface, with a greater area being covered by an atmospheric-pressure pulsed microwave line plasma source.

The electrostatic effect and its role in promoting electrocatalytic reactions by specifically adsorbed anions.

The adsorption of anions and its impact on electrocatalytic reactions are fundamental topics in electrocatalysis. Previous studies revealed that adsorbed anions display an overall poisoning effect in most cases. However, for a few reactions such as the hydrogen evolution reaction (HER), oxidation of small organic molecules (SOMs), and reduction of CO2 and O2, some specifically adsorbed anions can promote their reaction kinetics under certain conditions. The promotion effect is frequently attributed to the adsorbate induced modification of the nature of the active sites, the change of the adsorption configuration and free energy of the key reactive intermediate which consequently change the activation energy, the pre-exponential factor of the rate determining step etc. In this paper, we will give a mini review of the indispensable role of the classical double layer effect in enhancing the kinetics of electrocatalytic reactions by anion adsorption. The ubiquitous electrostatic interactions change both the potential distribution and the concentration distribution of ionic species across the electric double layer (EDL), which alters the electrochemical driving force and effective concentration of the reactants. The contribution to the overall kinetics is highlighted by taking HER, oxidation of SOMs, reduction of CO2 and O2, as examples.

Modelling a Turbulent Non-Premixed Combustion in a Full-Scale Rotary Cement Kiln Using reactingFoam

No alternatives are currently available to operate industrial furnaces, except for hydrocarbon fuels. Plant managers, therefore, face at least two challenges. First, environmental legislation demands emission reduction. Second, changes in the origin of the fuel might cause unforeseen changes in the heat release. This paper develops the hypothesis for the detailed control of the combustion process using computational fluid dynamic models. A full-scale mock-up of a rotary cement kiln is selected as a case study. The kiln is fired by the non-premixed combustion of Dutch natural gas. The gas is injected at Mach 0.6 via a multi-nozzle burner located at the outlet of an axially mounted fuel pipe. The preheated combustion air is fed in (co-flow) through a rectangular inlet situated above the attachment of the fuel pipe. The multi-jet nozzle burner enhances the entrainment of the air in the fuel jet. A diffusion flame is formed by thin reaction zones where the fuel and oxidizer meet. The heat formed is transported through the freeboard, mainly via radiation in a participating medium. This turbulent combustion process is modeled using unsteady Favre-averaged compressible Navier–Stokes equations. The standard k-ϵ equations and standard wall functions close the turbulent flow description. The eddy dissipation concept model is used to describe the combustion process. Here, only the presence of methane in the composition of the fuel is accounted for. Furthermore, the single-step reaction mechanism is chosen. The heat released radiates throughout the freeboard space. This process is described using a P1-radiation model with a constant thermal absorption coefficient. The flow, combustion, and radiative heat transfer are solved numerically using the OpenFoam simulation software. The equations for flow, combustion, and radiant heat transfer are discretized on a mesh locally refined near the burner outlet and solved numerically using the OpenFoam simulation software. The main results are as follows. The meticulously crafted mesh combined with the outlet condition that avoids pressure reflections cause the solver to converge in a stable manner. Predictions for velocity, pressure, temperature, and species distribution are now closer to manufacturing conditions. Computed temperate and species values are key to deducing the flame length and shape. The radiative heat flux to the wall peaks at the tip of the flame. This should allow us to measure the flame length indirectly from exterior wall temperature values. The amount of thermal nitric oxide formed in the flame is quantified. The main implication of this study is that the numerical model developed in this paper reveals valuable information on the combustion process in the kiln that otherwise would not be available. This information can be used to increase fuel efficiency, reduce spurious peak temperatures, and reduce pollutant emissions. The impact of the unsteady nature of the flow on the chemical species concentration and temperature distribution is illustrated in an accompanying video.

Coupling a neural network technique with CFD simulations for predicting 2-D atmospheric dispersion analyzing wind and composition effects

The Computational Fluid Dynamics (CFD) tool has a remarkable applicability for the prediction of gas dispersion flows by numerically solving the proper governing equations in realistic scenarios. Depending on the problem complexity, undesirably high computational costs can be incurred, which has encouraged the combined use of Machine Learning (ML) seeking to attenuate the CFD simulations requirement for multiple scenario studies. The present work aims at demonstrating the employment the coupling between CFD and the Artificial Neural Network (ANN) algorithm for representative problems in atmospheric dispersion in a preliminary assessment. A limited set of CFD simulation results was used for training neural networks, whose output is given by flow field interpolators, the potential uses of which include digital twin designing and optimization procedures. One possible strategy is the local approach, which treats the network as a transition rule in the scope of Cellular Automata (CA) modeling, allowing it to learn the dynamic behavior of the addressed physics locally. This method gives rise to simpler neural network architectures with closer computing relatively to the CFD calculation. Assessments have been done by predicting, initially, a scalar field time evolution governed by a 1-D advection-diffusion transport equation to verify the method implementation. Subsequently, species concentration distributions were sought in atmospheric dispersion cases from CFD simulations datasets, comprising four case studies followed in the performed analysis, all considering a bidimensional flow domain and a scenario involving methane leaks. The first one indicated an accurate reproduction of subsequent time steps concentration field referring to the displacement of a methane cloud. The second and third cases concerned a plume formation, in transient and steady-state regimes, respectively; their main outcome was the evidence of the CA-ANN methodology's flexibility to address time-dependent and permanent flow simulations interpolation. The last CFD-based case study comprised an additional complexity feature of gas dispersion problems: the wind influence. By redesigning the investigated data-driven approach in terms of ANN's features and labels choice, promising results followed from the analysis with respect to the simultaneous capturing of two global simulation parameters (wind and leakage speeds boundary conditions) in the species concentration field interpolation.