Reaction Rate Model Research Articles

Removal of indoor air ozone using carbon-based filters: Systematic development and validation of a predictive model

Exposure to ozone can cause several adverse health effects on human beings. Carbon-based filters are usually used for the removal of ozone from indoor air. The main problem with Carbon-based filters technology is the exhaustion of carbon because of irreversible reactions with ozone. Therefore, the knowledge of the service life of filters is crucial for building engineers and designers. Since testing at low indoor concentrations is time-consuming and expensive, the existing standards suggest experimenting with high concentrations. Thus, predictive models need to be developed to estimate the service life of filters. This work provides a model to estimate the breakthrough curves of three different combined (multi-layer) filters. The model augmented mass transfer equations with a reaction rate model and divided them into interpellet mass transfer and kinetic models. First, the reaction rate parameters were measured by fitting the model onto experimental data of all filters challenged with 9 ppm or 90 ppm of ozone. This was followed by validating the model for lower concentrations. In addition, to show the model validity for real-life application, its prediction was compared with the experimental data collected using the full-scale experimental setup and higher velocity. There was excellent agreement between the model prediction and the experimental results for all filters. Furthermore, an inter-model comparison was performed to determine the importance of different mass transfer steps. The results showed internal diffusion and axial dispersion as rate-limiting steps along with reaction. Finally, a sensitivity analysis was conducted on reaction kinetic parameters, axial dispersion coefficient, external mass transfer coefficient, and activated carbon particle porosity, which indicated negligible effects of external mass transfer and porosity variations.

Simulation and Reynolds-averaged Navier-Stokes modeling of a three-component Rayleigh-Taylor mixing problem with thermonuclear burn.

Rayleigh-Taylor mixing in the presence of a third component with intermediate density is investigated through three-dimensional large-eddy simulation (LES) with a high-order compact finite-difference code. Two configurations are considered: (1) a symmetric configuration in which the Atwood number between the heavy and intermediate components matches the Atwood number between the intermediate and light components and (2) an asymmetric configuration in which the Atwood number between the heavy and intermediate components is an order of magnitude greater than the Atwood number between the intermediate and light components. Mass fraction covariances are extracted, and proposed Reynolds-averaged Navier-Stokes (RANS) closures for density-specific-volume and density-mass-fraction covariances are evaluated in an a priori fashion. In addition, a multicomponent extension of the k-ϕ-L-a-V RANS model [Morgan, Phys. Rev. E 104, 015107 (2021)2470-004510.1103/PhysRevE.104.015107] is presented which includes model equationsfor the upper-triangular elements of the mass fraction covariance matrix. This model, referred to as the k-ϕ-L-a-C model, is compared against results from LES and against other RANS models. Profiles of average mass fraction, mass-fraction covariance, and density-specific-volume covariance obtained with the k-ϕ-L-a-C model are found to agree well with LES data. Finally, the impact of three-component turbulent mixing on average reaction rate is investigated in both premixed and nonpremixed cases by heating the mixing layer and allowing it to undergo thermonuclear (TN) burn. A closure model for average reaction rate is proposed for use with the k-ϕ-L-a-C model, and when this model is applied, improved agreement is obtained between LES and RANS in total TN neutron production.

Multi-scale modeling of shock initiation of a pressed energetic material I: The effect of void shapes on energy localization

Accurate simulations of the shock response of heterogeneous energetic (HE) materials require closure models, which account for energy localization in the micro-structure. In a multi-scale framework, closure is provided by reaction rate models that account for ignition and growth of hotspots, allowing for prediction of the overall macro-scale sensitivity of a HE material. In the present meso-informed ignition and growth (MES-IG) model, the reaction rate is expressed as a function of shock pressure and morphology of the void field in a pressed energetic material. In MES-IG, the void morphology is quantified in terms of a limited number of parameters: viz., overall porosity, void size, and shape (aspect ratio and orientation). In this paper, we quantify the effects of arbitrary variations in void shapes on meso-scale energy deposition rates. A collection of voids of arbitrary shapes is extracted from scanning electron microscope (SEM) images of real, pressed HMX (octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine) samples and classified into groups based on their similarity in shapes. Direct numerical simulations (DNS) are performed on the highly contorted “real” void shapes, and the calculated hotspot ignition and growth rates are compared with values predicted by the MES-IG. It is found that while the parameterization of complex void morphologies in terms of orientation and aspect ratio gives fairly good agreement between DNS and MES-IG reaction rates, the intricate details of highly complex void shapes impact hotspot characteristics to a significant extent. This work suggests possible improvements for the prediction of reaction rate in the energetic microstructure by adopting a more detailed description of shapes.

A new Ignition-Growth reaction rate model for shock initiation

Accurately predicting reactive flow is a challenge when characterizing an explosive under external shock stimuli as the shock initiation time is on the order of a microsecond. The present study constructs a new Ignition-Growth reaction rate model, which can describe the shock initiation processes of explosives with different initial densities, particle sizes and loading pressures by only one set of model parameters. Compared with the Lee-Tarver reaction rate model, the new Ignition-Growth reaction rate model describes better the shock initiation process of explosives and requires fewer model parameters. Moreover, the shock initiation of a 2, 4-Dinitroanisole (DNAN)-based melt-cast explosive RDA-2 (DNAN/HMX (octahydro- 1, 3, 5, 7-tetranitro-1, 3, 5, 7-tetrazoncine)/aluminum) are investigated both experimentally and numerically. A series of shock initiation experiments is performed with manganin piezoresistive pressure gauges and corresponding numerical simulations are carried out with the new Ignition-Growth reaction rate model. The RDA-2 explosive is found to have higher critical initiation pressure and lower shock sensitivity than traditional explosives (such as the Comp. B explosive). The calibrated reaction rate model parameters of RDA-2 could provide numerical basis for its further application.

Investigation on the fusion reaction rate of deuterium and tritium under heterogeneous mixing

Mixing between shell material and gas fuel, caused by hydrodynamic instability, isolated defects, or kinetic effects, is the key to understand the degradation of implosion performance in the research of inertial confinement fusion. Understanding the mixing mechanism and reducing its impact is of extreme importance to achieve the ignition and high gain. The impact of mixing morphology on thermonuclear reaction rate in sub grid level has gradually attracted people’s attention in recent years due to its direct influence on burn rate and fusion process, the study on physical model of thermonuclear reaction rate in different mix morphology has important scientific significance and application value. In the paper, the dependence of thermonuclear reaction rate on mass distribution of different fuel concentrations at sub grid scale is derived. Based on thermodynamic equilibrium and ideal gas equation of state, the physical law of the evolution of the thermonuclear reaction rate with mix morphology under the dominance of diffusion mixing is revealed through analytical formula and numerical solution of diffusion equation in one-dimensional spherical geometry. It is convinced that the mixing amount directly affects the thermonuclear reaction rate by mainly affecting the volume fraction of the fuel, and the mixing diffusion time determined by heterogeneous mixing scale and diffusion coefficient directly affects the evolution behavior of the thermonuclear reaction rate. Furthermore, based on mutual diffusion coefficient obtained from direct simulation of diffusion process by Monte Carlo method, the difference of impact to thermonuclear reaction rate for low-<i>Z</i> Carbon and high-<i>Z</i> gold mixing is quantitatively investigated. Heterogeneous mix size with 0.1 μm, 0.01 μm respectively for the low-<i>Z</i> and high-<i>Z</i> mixing can be treated as atomic mix in burn rate aspect, and heterogeneous mix size with 10 μm, 1 μm respectively for the low-<i>Z</i> and high-<i>Z</i> mixing can be treated as ideal chunk mix in burn rate aspect, and heterogeneous mix size in the middle state needs to be evaluated by using the heterogeneous mixing model of thermonuclear reaction rate in the paper. Finally, the physical model is compared with 3D simulation results of the heterogeneous mixing effect experiment called “MARBLE Campaign” carried out on OMEGA laser facility, which is designed as a separated reactant experiments and capsules are filled with deuterated foam and HT gas pores of different size, covering typical mix morphology from atomic mix to chunk mix, which validate the reliability of the theoretical evaluation about the evolution of mixing morphology and its impact to thermonuclear reaction rate. This work is significant for the design and improvement of inertial confinement fusion mixing effect experiment in China.

Kinetic modeling of removal of aromatic hydrocarbons from petroleum wastewaters by UiO-66-NH2/TiO2/ZnO nanocomposite

In this study, the UiO66-NH2/TiO2/ZnO (UTZ) nanocomposite was synthesized using the sol-gel method. The mean particle size of UTZ nanocomposite was about 33.63 nm. The present work investigates the applicability of a photocatalytic oxidation process for benzene, toluene and xylene (BTX) degradation. The response surface modeling (RSM) was utilized to optimize important parameters, i.e. catalyst content (g/L), lamp power (W), initial contaminant concentrations and pH. The optimized values of these parameters involved UTZ concentration of 0.11 g/L, lamp power of 15 W, the initial pollutant concentration of 50 ppm and pH= 7. The BTX degradation and total organic carbon (TOC) removal efficiencies were 90.03% and 85.16%, respectively, under optimal conditions. Ultimately, a new kinetic reaction rate model was developed in the form of Langmuir- Hinshelwood equation based on the intrinsic-element reactions in the form of−r=0.102I0.5[UTZ]0.5[BTX]/1+1.9298[BTX]0+1.6059I0.5[UTZ]0.5. The first-order kinetic constant determined by this model was 0.133 min-1. It was observed that the model for the photocatalysis reaction rate was well fitted with the experimental data at minimal mean absolute relative residual (14.18%).

Kinetic modeling of Polyamine-based Water-Lean solvents for CO2 capture: Reverse temperature dependence of the overall mass transfer coefficient

Amine-based water-lean solvents (WLS) are promising energy-saving alternatives to the aqueous amine solutions for CO2 capture. Herein, we determined the apparent kinetic parameters of WLS containing 3,3′-iminobis(N,N-dimethylpropylamine) (60 wt%), water (10–20 wt%), and a non-amine chemical (balance). For CO2 absorption rate modeling, the termolecular reaction model and reaction rate model of tertiary amines were incorporated into the equilibrium model proposed by previous work, and the absorption rate of CO2 was estimated using a wetted wall column-based apparatus. The average CO2 absorption rates of the studied 10 wt%–H2O WLS at 313 and 333 K were approximately 5.0e-03 and 4.0e-03 mol/m2∙kPa∙s, respectively, which were much higher than that of a conventional aqueous amine solvent for CO2 capture. In addition, we observed that the overall mass transfer coefficient decreased with increasing temperature in low content water of WLS. This is due to the change of physical properties (Henry's law constant and diffusion coefficient) of WLS with decreasing water concentration. In this work, the cause of the reverse temperature dependence of WLS was investigated and verified through experiments and modeling.

Alternative approaches to the reaction rate modelling in gas explosion simulation using STOKES

Computational fluid dynamics (CFD) has been increasingly applied to process safety studies involving scenarios of accidental gas explosions. By offering a deeper understanding of the underlying physics of flame propagation, CFD can improve existing consequence analysis and risk assessment, particularly when confinement or obstructions are present. In the numerical modelling of gas explosions, the reaction rate is a quantity of fundamental importance because it ultimately leads to the values of flame speed and peaks of overpressure. In this work, we investigate the reaction rate models implemented in the CFD tool STOKES, which has been designed for the simulation of gas explosions in complex geometries. STOKES counts on the Bray–Moss–Libby (BML) reaction rate model, where the effects of flame stretch are neglected in its original version, which may lead to an inaccurate representation of the flame behaviour. Also, the length scale of wrinkling is often calculated as a function of the velocity fluctuations via empirical correlations that depend on adjustable constants. In a first approach, we propose an expression for calculating the stretch factor dynamically, based on the local divergence of velocity. In a second approach, a hybrid reaction rate model is presented, incorporating the well-known fractal approach into the BML model. The hybrid approach also counts on the calibration of parameters of the initial laminar burning model. Despite some improvement, the proposed dynamic stretch factor leads to unexpectedly enlarged flame contours. Results using the hybrid approach on the other hand improved agreement with experimental data, particularly in the early stages of flame acceleration when combustion chambers of relatively small sizes are considered. However, applications in real-scale semi-confined geometries indicate that the initial stages of flame development require further work.

A Statistical Hot Spot Reaction Rate Model for Shock Initiation of Polymer‐Bonded Explosives

AbstractA statistical hot spot reaction rate model for shock initiation and detonation of heterogeneous solid explosives is developed to devote a physically realistic description of the formation, growth, or coalescence of hot spots, combustion, and rapid transition to detonation. One of the most significant advantages of the statistical model is that it predicts well the influence of mesoscopic void size distribution and critical size of activated hot spots on the shock initiation and detonation growth of PBXs. The calculated pressure histories in both TATB‐based LX‐17 and HMX‐based PBX9501 are found to be in good agreement with the experimental data. It is found that the shock initiation behavior of the HMX‐based PBX is mainly controlled by the number density of hot spots and shows an accelerated reaction characteristic and that of the TATB‐based PBX is determined by the combustion reaction process, which featured by a stable reaction characteristic. It is also found that the void size inside the explosive should be restricted as small as possible to effectively reduce the initiation sensitivity. The results could advance our knowledge of shock initiation of PBXs and provide guidelines for the synthesis of insensitive high composite explosives.

Species reaction rate modelling based on physics-guided machine learning

Deep neural network (DNN) is applied to mean reaction rate modelling. Two DNN structures, species-dependent (SD) and species-independent (SI), are considered.11Code and data to use the trained deep neural network models in this work are available at https://github.com/minamoto-group/PGDNN_RANS_model_Nakazawa_etal. Due to the explicit inclusion of all species variables in the input layer for SD-DNN, this model may consider relationships of different chemical species. However, the prediction can be performed only for simulations with chemical mechanisms considering the same set of species as the one used in training data. SI-DNN circumvents this constraint, and can be used for any set of species appearing in the combustion. For the efficient learning and better prediction performance, two physics-guided loss functions are proposed and employed, which consider mass conservation of the mixture and elemental species in a specific formulation that yields a larger number of constraint conditions. These DNNs are trained and validated using direct numerical simulation (DNS) data of three different turbulent premixed planar flames, and tested using DNS results of a fourth turbulent premixed planar flame and turbulent premixed V-flame to assess the robustness of the present models for an unknown combustion configuration as well as unknown turbulent combustion conditions.

Modelling the pyrite oxidation level in a refractory gold-bearing stockpile to assess its potential for gold recovery by direct cyanide leaching

This study presents a three-dimensional numerical modelling method for predicting the pyrite oxidation level in refractory gold-bearing stockpiles under various conditions. The physical and chemical processes incorporated into the model include oxygen transport, heat transfer, air convection and pyrite oxidation. Different reaction rate models based on the shrinking core model are used to quantify the oxidation of pyrite grains in rock particles considering the influence of oxygen concentration, degree of water saturation, temperature and pH conditions. The extent of pyrite oxidation is a function of the oxygen concentration gradient within rock particles and is determined by the diffusion–reaction equation using the polar-coordinate system. Particle size distributions for both pyrite grains and rock particles are incorporated in the modelling of pyrite oxidation and oxygen consumption. Several scenarios with different parameters were examined and the simulation results show that after ten years, the pyrite oxidation level over the stockpile is up to 50% depending on the location within the stockpile, the rock types and stockpile properties such as porosity and water content. The model can simulate the overall pyrite oxidation level as well as the oxidation profile of the pyrite grains, i.e., the oxidation depth of pyrite grains of different sizes and at different locations within the rock particles. These are essential inputs required for the estimation of gold recovery by direct cyanide leaching for possible reclamation of the partially oxidised stockpile without incurring expensive pre-treatment of the material.

Study of kinetic and thermal decomposition from municipal solid waste pellets using model-fitting methods

Reaction rate model could be determined from kinetic characteristics. Kinetic and thermal decomposition of municipal solid waste (MSW) pellets, consist of organic material, plastic, paper and leaves, with tapioca flour as binder (0%, 3% and 6%) were studied in thermogravimetric analyzer from temperature 50°C to 800°C at heating rate 10 0C/min in N2 atmospheres. The kinetic parameter were determined by Model Fitting or Coats Redfern Methods with different kinetic reaction model. Results of this study have shown that MSW pellets in various binder has activation energy values 64.64 kJ/mol and 22.06 kJ/mol for 0%, 68.83 kJ/mol and 21.99 kJ/mol for 3%, and 69.29 kJ/mol and 22.62 kJ/mol for 6% at temperature ranges between 200°C-400°C and 400°C-500°C respectively in typical three dimensional diffusion (D3) mechanism kinetic reaction model.

A hybrid BML-fractal approach for the mean reaction rate modelling of accidental gas explosions in partially confined obstructed geometries

We propose a new approach to model the mean reaction rate of premixed turbulent flames when simulating accidental gas explosions with computational fluid dynamics (CFD). The combination between Bray–Moss–Libby (BML) approach and the fractal concept was evaluated. The fractal concept is used for closing the integral length scale of wrinkling in the BML formulation replacing the utilisation of empirical functions. The proposed expression accounts for the effect of local length scales of turbulence on the flame front via the fractal outer and inner cut-offs, which were taken respectively as the integral length scale of turbulence and the Gibson length scale. The initial laminar phase of flame propagation is described by a laminar combustion model and the onset of the transition from the laminar to turbulent combustion is assumed to take place at a threshold value of the turbulent Reynolds number. The approach is implemented and evaluated within an in-house developed code called STOKES (Shock Towards Kinetic Explosion Simulator) that solves the full set of Navier–Stokes equations. The equations are parameterised according to the porosity distributed resistance (PDR) method in which the porous mesh accounts for the presence of small obstacles that are responsible for turbulence generation during an explosion. Simulations are carried out for vented explosions of both methane–air and propane–air mixtures in partially obstructed chambers. Results are compared with experimental data, FLACS simulations and a typical model for the length of wrinkling which uses an empirical function instead of the fractal approach. Comparisons lead to overall good agreement, indicating that the proposed model can be used in numerical simulations of accidental explosions to support consequence modelling in the framework of risk analysis.

Reoxidation of Al-Killed Ultra-Low C Steel by FetO in RH Slag: Experiment, Reaction Rate Model Development, and Mechanism Analysis

Reoxidation of Al-Killed Ultra-Low C Steel by FetO in RH Slag: Experiment, Reaction Rate Model Development, and Mechanism Analysis

A unified model of anisotropy, thermoelasticity, inelasticity, phase transition and reaction for high-pressure ramp-loaded RDX single crystal

A unified thermomechanical consistent model integrating multiple mechanisms, including material anisotropy, nonlinear thermoelasticity, inelasticity, phase transition , and chemical reaction, is developed for cyclotrimethylene trinitramine (RDX) crystal under high-pressure ramp-loading. (i) The nonlinear thermoelasticity of material is described by pressure-temperature-dependent elasticity tensor and a free-energy based complete equation of state. (ii) The cracking-mediated brittle damage on eleven cleavage planes and dislocation-mediated ductile plasticity on thirteen slip systems are considered in inelastic deformation. (iii) The phase transition kinetics is dependent on a thermodynamic consistent driving force. (iv) The chemical reaction is described by a reactive flow model integrating equations of state for solid reactants and gaseous products, Arrhenius-type reaction rate model and mixed rule. The proposed model is utilized to simulate the mechanical-thermal-chemical responses of (100) and (010) oriented ramp-loaded RDX crystals at pressure up to ~33GPa. The simulated results are well in agreement with the experimental data and reveal a four-wave structure (elastic-inelastic-phase transition-reaction wave) hidden behind the pressure wave profiles. Crack and dislocation activities on (110) and (1-10) crystal planes play a dominant role in macroscopic inelasticity of (100) oriented RDX. Compared to (100) oriented RDX, the (010) oriented RDX exhibits a higher α→γ phase transition criterion and a faster chemical reaction, which is associated with the different overall heating rate and thermomechanical state.

Study on the reaction rate model for shock initiation of aluminized hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) explosive under shock waves

To investigate the influence of the aluminum (Al) powder sizes on shock initiation of aluminized hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), shock initiation experiments were carried out. The experimental results show that as the Al constituent size decreases, a rapid increase in the propagation velocity of the precursory shock waves enhances the peak pressures, shortens the time intervals between the peak pressures and the arrival times of precursory shock waves, and improves the shock sensitivity of the aluminized RDX. Consequently, to predict and evaluate the stability of aluminized RDX with small-size Al powder, a microscopic reaction rate model for shock initiation was established. This model includes the pore collapse model of a double-layered spherical shell structure composed of an RDX spherical shell and a mixture (of Al powder and binders) spherical shell and the reaction model of Al powder in RDX decomposition products under the effect of shock waves and thermal energy released by RDX. The simulation results show that when the diameter of the Al powder is about 1/5 or less of the size of the base explosive (RDX) particles, the microscopic reaction rate model can accurately simulate the shock initiation process of aluminized RDX. As the Al powder size decreases, the reaction rate and the proportion of the Al involved in the initiation reaction for aluminized RDX increase.

Toluene Bioremediation by Using Geotextile-Layered Permeable Reactive Barriers (PRBs)

Sources of contamination in a subsurface environment are petrol, diesel fuel, gasoline at oil refineries, underground storage tanks, transmission pipelines, and different industries. The permeable reactive barrier (PRB) is a promising technology to remediate groundwater in-situ. In this study, synthetic groundwater samples containing toluene are treated in three reactor columns by biological processes. PRB-1 consisted of sand and gravel as reactor media, microbial inoculum (bioaugmentation—BA), and nutrients (biostimulation—BS); PRB-2 consisted of sand and gravel as reactor media, microbial inoculum, nutrients, and 12 layers of nonwoven geotextile fabrics; and PRB-3 consisted of only sand and gravel as reactor media (natural attenuation—NA). This study was conducted to assess the impact of geotextile fabric filter, bioaugmentation, and biostimulation on toluene degradation efficiency. After 167 days of treatment, toluene biodegradation efficiencies varied between 88.2% and 93.8% for PRB 1, between 98.0% and 99.3% for PRB 2, and between 14.2% and 68.6% for PRB 3. The effluent toluene concentrations for PRB-2 were less than the guideline value (0.7 mg/L) of the World Health Organization. Reaction rate data were fitted with a first-order kinetic reaction rate model. This study showed that the toluene removal efficiency in the geotextile layered PRB combined with BA and BS process was significantly higher compared to the other processes tested. This lab-scale study introduced a new PRB configuration suitable for the remediation of sites contaminated with toluene.

He nanobubble driven W surface growth during low-energy He ion irradiations

By using scanning electron microscopy and atomic force microscopy, we observe the microscopic surface evolution of W crystals exposed to low-energy (50 eV) He + irradiations at the temperature of 1050 K. We find that the He + irradiation leads to the growth and emergence of nanoscale undulations over W (110), and the surface regions with less undulations are dominating the microscopic evolution of W crystals. Analysis shows that the thermodynamic instability of W crystals irradiated is attributed to the He nanobubble driven W surface growth, which has been confirmed by our experimental measurements and He reaction rate model in W. Our study will play a crucial role in understanding the growth process of undulating surface microstructures under fusion-relevant He + irradiations.

Dynamic data reconciliation, parameter estimation, and multi-scale, multi-physics modeling of the microwave-assisted methane dehydroaromatization process

In this paper, dynamic data reconciliation and parameter estimation has been performed for the microwave-assisted methane dehydroaromatization reaction system using the in-house experimental data. A custom reaction rate model has been developed including a model for coke formation and a model for the catalyst deactivation. A multi-physics, multi-scale reactor model is developed by developing a model for the microwave absorption in the metal and support sites in the catalyst and coupling the catalysts level model with the bulk scale model. For estimating microwave power absorption in the metal and support particles, a detailed model using the Maxwell’s equation as well as a reduced order model are developed. Analysis of operation frequency shows that 2.45 GHz frequency has a better reactor performance. It is also observed that the temperature differences between the metal and support sites are unlikely to be high for the methane dehydroaromatization reaction system as opposed to the traditional belief for MW-assisted reactive systems.

Maximization of the profit and reactant conversion considering partial pressures in an ammonia synthesis reactor using a derivative‐free method

AbstractIn the present paper, an optimization model is proposed for the ammonia synthesis reactor. The reversible exothermic reaction has nitrogen and hydrogen as reactants, at high temperatures, and high pressures with iron catalyst. Two different single‐objective optimization problems were considered, the maximization of the economic return and the maximization of the nitrogen conversion. The reaction rate model was defined as a function of partial pressures of the components. The problem was coded and solved in MATLAB using a derivative‐free method after reformulating a constrained optimization problem into an unconstrained one, by penalizing the infeasibilities of the constraints in the objective functions (barrier function). The main contributions of this paper are the combination of direct‐search methods in solving the optimization problem, the evaluation of the maximum ammonia production and the temperature profile. The optimal values found were better than the ones published in the literature.