Reduction Reactor Research Articles

NOx Emission Prediction Based on SSA-DELM via CFD and DCS Data Fusion

The objective of this study was to obtain NOx emission prediction model at the inlet selective catalytic reduction (SCR) reactors, which was the basis of combustion optimization and denitrification treatment. A deep extreme learning machine (DELM) optimized by the sparrow optimization algorithm (SSA) was adopted to establish the NOx model based on data fusion of Computational Fluid Dynamics (CFD) simulation and Distributed Control System (DCD). The mechanism analysis and XGBoost algorithm was used to select input variables. The results show that the XGBoost-SSA-DELM-based prediction model has high prediction accuracy with mean absolute error of 2.54 mg/m3. The results of this study have important implications for research on improving combustion efficiency and reducing pollutant emissions.

Industrial practice and CFD investigation of a multi-chamber fluidized bed reactor for MnO2 ore reduction

The multi-chamber fluidized bed reactor (MCFBR) is beneficial to the higher solids conversion rate, but the complex configuration needs special methodology for the rational design and smooth operation. In this study, an actual plant data of MCFBR for the reduction of MnO2 ore were analyzed, which indicated that the recovery rate of Mn was confirmed to be kept above 95% normally. To investigate the multi-chamber fluidized bed hydrodynamics and reaction characteristics, the 3D computational fluid dynamics (CFD) numeration coupled with structure-based transfer model and multi-chamber calculation method was established. The effect of mesoscale structure on the prediction of multi-chamber reaction process was evaluated as well. The simulation results showed that the model was able to calculate the gas–solid reaction behavior more accurately than the traditional model without taking mesoscale structure into account. The computed tanks-in-series number of 2.0 is less than the actual chamber number of 4.0 for the wide gap between the vertical baffle and the side wall. The quantitative effects of partition configuration, fluidized structure, and operating condition on the solids conversion rate were estimated as well.

Determining the thermoplastic deformation mechanism of titanium reduction reactors and recommendations to increase the reactor service life

The object of research reported in this paper is the stressed-strained state of reactors when producing titanium sponge by the magnesium thermal method, taking into consideration the conditions of their operation and the physical and mechanical properties of the materials. The problem considered is the plastic deformation of the reactor in the process of reducing titanium tetrachloride. To solve this task, an axisymmetric geometric model of the reactor was built using a CAD module of the Comsol Multiphysics software package. For the calculation, the Nonlinear Structural Materials module was used. Owing to the method of finite elements, the critical parameters for the formation of the plastic deformation band of the reactor were determined. Modeling the process of thermoplastic deformation of the reactor under the conditions of obtaining titanium sponge has made it possible to determine the temperature gradient in the upper part of the reactor wall, which leads to local plastic deformation of the wall. The solution to the problem of continuing the reactor service would be to prevent overheating (overcooling) of the reactor wall within the resulting temperature. The physical and mechanical parameters of the material of the reactor wall, necessary to prevent the occurrence of an annular band of plastic deformation, have also been determined. It was shown that at ∆T˃∆Tcrit=60 °C, the walls of a 10-ton reactor during the reduction of titanium tetrachloride with magnesium perceive plastic deformation whose maximum value can reach Deformation mechanisms that lead to a change in the shape of the side wall of reactors of magnesium-thermal production of sponge titanium under the action of a heterogeneous temperature field have been determined. The proposed technological solutions are to eliminate local changes in diameter in the upper part of the reactor wall. This will make it possible not only to increase the life of the reactors but will reduce the flow of alloy components into the titanium sponge of nickel, chromium, and iron

Model Evaluation of the Microbial Metabolic Processes in a Hydrogen-Based Membrane Biofilm Reactor for Simultaneous Bromate and Nitrate Reduction

The H2-based membrane biofilm reactor (H2-MBfR) has been acknowledged as a cost-effective microbial reduction technology for oxyanion removal from drinking water sources, but it remains unknown how the evolution of biofilm characteristics responds to the changing critical operating parameters of the H2-MBfR for simultaneous bromate (BrO3−) and nitrate (NO3−) elimination. Therefore, an expanded multispecies model, applicable to mechanistically interpret the bromate-reducing bacteria (BRB)- and denitrifying bacteria (DNB)-dominated metabolic processes in the biofilm of the H2-MBfR, was developed in this study. The model outputs indicate that (1) increased BrO3− loading facilitated the metabolism of BRB by increasing BRB fraction and BrO3− gradients in the biofilm, but had a marginal influence on NO3− reduction; (2) H2 pressure of 0.04 MPa enabled the minimal loss of H2 and the extension of the active region of BRB and DNB in the biofilm; (3) once the influent NO3− concentration was beyond 10 mg N/L, the fraction and activity of BRB significantly declined; (4) BRB was more tolerant than DNB for the acidic aquatic environment incurred by the CO2 pressure over 0.02 MPa. The results corroborate that the degree of microbial competition for substrates and space in the biofilm was dependent on system operating parameters.

Single-chamber microbial electrosynthesis reactor for nitrate reduction from waters with a low-electron donors’ concentration: from design and set-up to the optimal operating potential

Microbial electrosynthesis is a promising solution for removing nitrate from water with a low concentration of electron donors. Three single-chamber microbial electrosynthesis reactors were constructed and operated for almost 2 years. The single-chamber reactor design saves on construction costs, and the pH of the solute is more stable than that in the case of a two-chamber reactor. Nitrate reduction started at the working electrode potential of −756 mV versus standard hydrogen electrode (SHE), and subsequently, the working electrode potential could be increased without hindering the process. The optimal potential was −656 mV versus SHE, where the highest Faradaic efficiency of 71% and the nitrate removal rate of 3.8 ± 1.2 mgN-NO3/(L×day) were registered. The abundances of nitrite reductase and nitrous oxide reductase genes were significantly higher on the working electrode compared to the counter electrode, indicating that the process was driven by denitrification. Therefore, a microbial electrosynthesis reactor was successfully applied to remove nitrate and can be utilized for purifying water when adding organic compounds as electron donors is not feasible, that is, groundwater. In addition, at the lower working electrode potentials, the dissimilatory nitrate reduction to ammonium was observed.

Numerical simulation of heat transfer in the cooling channel of a titanium apparatus

Numerical modeling of thermophysical processes in the air cooling channel of the titanium sponge reduction reactor is performed. The cooling channel is an area bounded by a retort filled with liquid magnesium and a wall on which heating elements are mounted. Air flows inside the channel, cooling the retort. A mathematical model is constructed based on unsteady Navier-Stokes equations in axisymmetric formulation using a k −ω SST turbulence model. The model takes into account the radiation heat transfer between the retort and reactor walls. Two variants of thermal boundary conditions are considered. The temperature conditions of the retort wall have been calculated, and the profiles of the heat transfer coefficient along the retort wall for a wide interval of airflow rates have been obtained. It is shown that temperature distributions along the retort are not uniform and strongly depend both on external boundary conditions and on cooling intensity. Heat transfer coefficient distributions from its outer wall for different retort heating conditions are plotted, and an empirical formula for calculating the profile of this coefficient is proposed.

Three-stage model-based evaluation of a downdraft biomass gasifier

Biomass gasification suggests several advantages toward clean environment and energy sustainability. Multi-stage gasifiers enhance the process efficiency and syngas quality. Thus, multi-stage model developments are essential to take into account separate chemical schemes for successive pyrolysis and partial oxidation reactors. The current study is contributed to develop and evaluate a conceptual three-stage biomass gasifier model. The model is built by integrating three successive sub-models for drying and pyrolysis, partial oxidation and char reduction reactors. Pyrolysis sub-model is based on kinetic rate modelling with considering biomass lingo-cellulosic structure. Partial oxidation sub-model is developed by applying axis-symmetric 2D transport equations accompanied by appropriate chemical scheme. Char reduction sub-model is extended based on axis-symmetric 2D DPM model as well as appropriate chemical kinetic scheme. Accuracy of each sub-model and also the whole three-stage gasifier model are separately verified against available experimental data. Verification analysis demonstrates high resolution agreement between the results of the developed model and available experimental data. Simulations ascertain that gasification of 24.8 kg. hr−1 hardwood with about 26.5% moisture content in presence of 7 kg. hr−1 steam and 25 kg. hr−1 air has produced syngas with the composition of 1.92% CH4, 34.02% H2, 16.77% CO, 14.63% CO2 and 32.66% N2, outlet tar concentration of 2.3439 gr. N m−3 and grate char particles concentration of 0.0397 kg. m−3.

Integration of molten carbonate fuel cell and chemical looping air separation for high-efficient power generation and CO2 capture

Molten carbonate fuel cell (MCFC) allows concentrating the CO2 from the cathode side to the anode side, generating electricity concurrently. Chemical looping air separation (CLAS) can produce an O2 and CO2 mixture stream as cathode feeding gas of MCFC. In this paper, a natural gas-fueled MCFC with internal reforming is integrated with CLAS as O2 and CO2 source for high-efficient power generation with CO2 capture. An O2 and CO2 mixture stream is produced from CLAS by recirculating a portion of CO2-rich flue gas after the afterburner to CLAS. The system is analyzed through thermodynamic and economic performance. At the baseline case, the plant net power efficiency is 59.5%, with 99.9% CO2 capture rate. Based on sensitivity analysis, the higher fuel cell temperature and fuel utilization factor can increase the plant net power efficiency, while the steam carbon ratio and the CLAS reduction reactor temperature are preferable to be at lower levels for higher plant net power efficiency. Finally, economic analysis is conducted. With a MCFC specific cost of $1327/kW and a natural gas price of $2.79/million Btu, the cost of electricity (COE) is $0.094/kWh. The results show the proposed system is attractive for natural gas-fueled power generation with CO2 capture.

Local Bubble Characteristics in a Side-Blown Vortex Smelting Reduction Reactor

Local Bubble Characteristics in a Side-Blown Vortex Smelting Reduction Reactor

Synergism of hydrolytic acidification and sulfate reducing bacteria for acid production and desulfurization in the anaerobic baffled reactor: High sulfate sewage wastewater treatment

High sulfate concentrations in sewage wastewater restricts the application of treatment technologies. In this present study, acid production-sulfate reduction reaction system effectively improved the high concentration sulfate removal from the sewage wastewater. Acid-generating phase in the two-phase anaerobic process was used. After 33 days of low-load start-up, COD removal efficiency in the acid-producing phase reached > 40%. Effluent VFA stable around 1400 mg/L and pH 4.0 ∼ 4.3. Effluent alkalinity was continuously reduced until zero, acidogenic phase started successfully. In acid production-sulfate reduction reactor, when COD/SO42− 3, the hydrolytic acidification bacteria maintained stable hydrolysis acidification ability. Sulfate-reducing bacteria increased the degree of acidification by 10%∼15%. The metabolic rate of acid bacteria reflected the good synergistic effect. When hydraulic retention time was controlled at 8.5 h and influent COD 3000 mg/L, with the decrease of COD/SO42− ratio, effluent sulfate removal efficiency gradually decreased. For COD/SO42− 6, ABR reactor had obvious phase separation characteristics of acid production-sulfate reduction and methanogenic phase. With the decrease of COD/SO42−, SO42− removal affected each compartment (methanogenesis weakened). For COD/SO42− 3, the effluent sulfate removal efficiency decreased with the decrease in HRT. At HRT 8 h, the sulfate removal by ABR reactor mainly occurred in I compartment. As the HRT decreases, the compartment that takes the main sulfate removal gradually moves backwards. When the HRT was 2 h, the sulfate removal occurred mainly in the II and III compartments. This present study can effectively solve the contradictions and drawbacks in the traditional biological desulfurization process and improves the efficiency of biological desulfurization.

Impact of Carbon N-Doping and Pyridinic-N Content on the Fuel Cell Performance and Durability of Carbon-Supported Pt Nanoparticle Catalysts.

Cathode catalyst layers of proton exchange membrane fuel cells (PEMFCs) typically consist of carbon-supported platinum catalysts with varying weight ratios of proton-conducting ionomers. N-Doping of carbon support materials is proposed to enhance the performance and durability of the cathode layer under operating conditions in a PEMFC. However, a detailed understanding of the contributing N-moieties is missing. Here, we report the successful synthesis and fuel cell implementation of Pt electrocatalysts supported on N-doped carbons, with a focus on the analysis of the N-induced effect on catalyst performance and durability. A customized fluidized bed reduction reactor was used to synthesize highly monodisperse Pt nanoparticles deposited on N-doped carbons (N-C), the catalytic oxygen reduction reaction activity and stability of which matched those of state-of-the-art PEMFC catalysts. Operando high-energy X-ray diffraction experiments were conducted using a fourth generation storage ring; the light of extreme brilliance and coherence allows investigating the impact of N-doping on the degradation behavior of the Pt/N-C catalysts. Tests in liquid electrolytes were compared with tests in membrane electrode assemblies in single-cell PEMFCs. Our analysis refines earlier views on the subject of N-doped carbon catalyst supports: it provides evidence that heteroatom doping and thus the incorporation of defects into the carbon backbone do not mitigate the carbon corrosion during high-potential cycling (1-1.5 V) and, however, can promote the cell performance under usual PEMFC operating conditions (0.6-0.9 V).

Performance evaluation of neural networks in modeling exhaust gas aftertreatment reactors

A comprehensive evaluation of neural network (NN) methods to model exhaust gas aftertreatment reactors is presented in this study. A combination of non-linear autoregressive model with exogenous inputs (NARX) network and static NN is utilized to capture the dynamic behavior of the state and outlet variables, such as coverage fractions, temperatures, and conversions, of monolith reactors used in the abatement of automobile emissions. The efficacy of this methodology is illustrated by modeling the diesel oxidation catalyst (DOC) and selective catalytic reduction (SCR) reactors of a diesel engine exhaust gas aftertreatment system. The final NN topology is designed by carefully comparing the model performances in the training and testing datasets. Model parsimony quantified by Akaike’s Information Criterion is employed for choosing the number of input and feedback delays in the NARX network. The novelty of this work lies in generating quality training and validation data using a physics-based system level model comprising of the engine and aftertreatment reactor components. The accuracy and generalizability of the NN models are demonstrated by comparing the model predictions with physical model simulation results in five disparate test datasets used in vehicle certification protocols. Overall, the NN models are found to reproduce all the qualitative trends in the various state and output variables while needing minimum computing resources resulting in better than real-time performance. Therefore, with appropriate training, these models can be embedded in the electronic control unit (ECU) and utilized for model-based predictive control systems.

Three-stage modelling and parametric analysis of a downdraft biomass gasifier

Syngas production from biomass resources suggest considerable privileges to attain energy sustainability in future. Design and control strategies are essential to extend the technology of biomass gasifiers, which require reliable model developments. The overarching contribution of this study is to develop and evaluate a three-stage biomass gasifier model. The model consists of three successive sub-models for drying and pyrolysis, partial oxidation and char reduction reactors. The pyrolysis of raw material is simulated based on the ligno-cellulosic structure of the biomass by adopting comprehensive kinetic rate modelling approach. The partial oxidation sub-model is built by axis-symmetric 2D transport equations including detailed chemical scheme. Char reduction sub-model is extended based on axis-symmetric 2D DPM model accompanied by appropriate chemical kinetic scheme considering heterogeneous and homogeneous reactions. Accuracy of each sub-model is separately verified by comparison with available numerical and experimental data. Moreover, the correctness and predictability of the complete gasifier model is evaluated using two experimental reports. For both cases, investigations demonstrate high resolution agreement between the results of the developed model and available experimental measurements both thermally and chemically. Furthermore, a parametric analysis is conducted to investigate the gasifier performance against the variations of the main system operating parameters including the type of the feeding biomass and its moisture content, equivalence ratio and air initial temperature. Based on the results, higher volatiles mass fractions and lower char mass fraction have been produced from pyrolyzing of hardwood in comparison with beech wood. Also, Results reveal that with increase of the moisture content from 15% to 35%, syngas LHV and cold gas efficiency reduce by 1.9559 MJ . kg −1 and 25.78% respectively, while H 2 mole fraction at the gasifier outlet rises by 0.90%. On the contrary, growth of equivalence ratio from 2 to 10 leads to the drastic increase of syngas LHV by 5.6404 MJ . kg −1 , however, cold gas efficiency peaks to 82.75% at the equivalence ratio of 4. Besides, varying the inlet air temperature over a range of 500 K–1300 K causes 0.6938 MJ . kg −1 growth of syngas LHV as well as 9.43% rise of cold gas efficiency. • A conceptual three-stage model is developed to simulate the performance of a downdraft biomass gasifier. • The model includes three separate successive sub-models for pyrolysis, partial oxidation and char reduction. • Results of each sub-model and the whole three-stage model are experimentally validated. • Three-stage model is evaluated for two different lignocellulosic feedstocks. • The effects of the key operating parameters on the gasifier performance are analyzed.

A continuum model for heat and mass transfer in moving-bed reactors for thermochemical energy storage

In this work, a continuum heat and mass transfer model coupling transport phenomena and high-temperature thermochemical reactions is developed for stationary packed-bed and counter-flow moving-bed reactors. After presenting the general modeling framework, we focus on the 2D axisymmetric version of the model for which validation is conducted with experimental results for a packed-bed reactor in the literature for manganese-iron oxide reduction/oxidation and an in-house counter-flow moving-bed reactor for magnesium-manganese oxide reduction up to 1450 °C. Transient simulation results including the local distributions of gas/solid temperatures, oxygen concentration and the extent of reaction, as well as the various energy flow components and energy conversion efficiencies are reported. The results based on the 2D axisymmetric model are also compared with those obtained from a previous 1D model. The comparison shows that capturing the radial variation is critical in reactor modeling and the 2D results demonstrate improved agreement with experiments. Specifically, large temperature variations along the radial direction are observed especially in the reaction zone; this non-uniform radial temperature distribution has a significant effect on the chemical reaction extent due to its strong dependence on temperature; and the overall oxygen concentration at the reactor exit and the predicted system efficiency are slightly lower in the 2D model compared to the 1D model. The present heat and mass transfer model can provide valuable insights into reactor design, scale-up, and operating conditions selection to maximize system energy storage efficiency.

Energy and exergetic analysis of applying solar cascade utilization to an artificial photosynthesis energy supply system

Although artificial photosynthesis can produce hydrocarbon fuels and reduce carbon emissions, current implementations cannot optimally utilize the solar spectrum and thus are inefficient. This research proposes a new hybrid energy system, which begins by applying the photovoltaic/thermal panel to simultaneously generate higher-grade electricity and lower-grade heat. Then, the electricity is supplied to the carbon dioxide reduction reactor, and the heat is supplied to carbon capture by adsorption and optionally the absorption chiller. By coupling the carbon capture and reduction reaction via the photovoltaic/thermal panel, efficient cascade utilization to generate solar fuels from a single solar energy source is achieved. The energy and exergy models that couple the individual devices are developed and the effects of photovoltaic conversion efficiency and the distribution of heat between the carbon capture by adsorption and absorption chiller are examined. Results show that the optimal power/heat ratio by the photovoltaic/thermal system to gain a proper mass balance characteristic is above 1.5 to yield 3.5 kg/m2 of methanol at 10 solar concentrations. Furthermore, carbon capture from the animal farm can contribute an additional 5% exergy efficiency over atmospheric air. Overall, maximizing the photovoltaic electrical efficiency is key to maximizing the system’s energy and exergy efficiencies.

Extracellular azo dye oxidation: Reduction of azo dye in batch reactors with biogenic sulfide

In this study, the sulfide-based reduction of azo dyes (Acid Blue 264) was investigated. Sulfate was reduced to sulfide with an ethanol-fed sulfate reduction reactor and the sulfide produced was used to reduce azo dyes in separate batch reactors using sulfide as the electron carrier. The Box–Behnken experiment design method was used to identify how operational parameters affect the decolorization efficiency. As independent variables, initial dye concentration, sulfide concentration and reaction time were selected while dye removal was considered as the response function. Based on the Box Behnken design, the higher regression coefficient (R2=0.9397) shows that the experimental results are in good agreement with model predictions. At the initial dye concentration of 80 mg/L, the highest dye removal efficiency, about 82.39%, was obtained at the sulfide concentration of 50 mg/L and the reaction time of 25 h. This study showed that Box Behnken’s model prediction was a suitable approach for identifying the best conditions for dye removal.

Integration of Open Slag Bath Furnace with Direct Reduction Reactors for New-Generation Steelmaking

The present paper illustrates an innovative steel processing route developed by employing hydrogen direct reduced pellets and an open slag bath furnace. The paper illustrates the direct reduction reactor employing hydrogen as reductant on an industrial scale. The solution allows for the production of steel from blast furnace pellets transformed in the direct reduction reactor. The reduced pellets are then melted in open slag bath furnaces, allowing carburization for further refining. The proposed solution is clean for the decarbonization of the steel industry. The kinetic, chemical and thermodynamic issues are detailed with particular attention paid to the slag conditions. The proposed solution is also supported by the economic evaluation compared to traditional routes.

Continuous-flow stereoselective reduction of prochiral ketones in a whole cell bioreactor with natural deep eutectic solvents

Immobilized whole cells of Rhodotorula rubra MIM147 were used in a packed bed flow reactor for the enantioselective reduction of β-ketonitriles and for the obtainment of a key building block for the synthesis of the antidepressant drug duloxetine.

Optimization of CO<sub>2</sub> reduction and decomposition plasma reactors

Optimization of CO<sub>2</sub> reduction and decomposition plasma reactors

Parameter Identification and Model Predictive Control of Selective Catalytic Reduction Reactor

Parameter Identification and Model Predictive Control of Selective Catalytic Reduction Reactor