Optimal Reactor Design Research Articles

Multi-objective Bayesian optimization of chemical reactor design using computational fluid dynamics

This study presents a computational fluid dynamics (CFD) based optimal design tool for chemical reactors, in which multi-objective Bayesian optimization (MBO) is utilized to reduce the number of required CFD runs. Detailed methods used to automate the process by connecting CFD with MBO are also proposed. The developed optimizer was applied to minimize the power consumption and maximize the gas holdup in a gas-sparged stirred tank reactor, which has six design variables: the aspect ratio of the tank, the diameter and clearance of each of the two impellers, and the gas sparger. The saturated Pareto front is obtained after 100 iterations. The resulting Pareto front consists of many near-optimal designs with significantly enhanced performances compared to conventional reactors reported in the literature. We anticipate that this design approach can be applied to any process unit design problems that require a large number of CFD simulation runs.

Pyrolysis of Corn Residues: Kinetic Analysis using Discrete Distributed Activation Energy Model

Agro-residues are usually generated in large amount. These biomass materials may be utilized as renewable energy source via thermochemical conversion processes. Knowledge on kinetic of thermal decomposition behavior of biomass is important in reactor design and thermal process optimization. In this work, thermogravimetric (TG) data (35 to 900°C, at heating rates of 5 to 50°C/min) from pyrolysis of corn residues was analyzed using discrete distributed activation energy model (DAEM). Prediction accuracy of the simulated data was verified by comparing experimental with calculated data of conversion at selected heating rates. Kinetic parameters including activation energy and pre-exponential factor obtained from this method were found to give correct conversion curves for different heating rates simultaneously with correlation coefficients greater than 0.99, within the ranges considered. According to the discrete DAEM, variation in activation energy with conversion implied changes in mechanism during pyrolysis process. The activation energies were observed to be in the range of 100 – 120 and 80 – 180 kJ/mol for the macro-TG and typical TG analysers, respectively.

Optimal design and operation of Fischer-Tropsch microchannel reactor for pilot-scale compact Gas-to-Liquid process

Design and operation of pilot-scale (1.0 BDP) compact GTL process comprising of reforming section, CO2 separating section, and Fischer-Tropsch (FT) synthesis section is presented. Detailed systematic computer-aided design procedure adopted to design a modular 0.5 BPD pilot-scale microchannel reactor used in the pilot plant operation is also presented. The modular microchannel FT reactor block design consists of 528 process channels and numerous coolant channels arranged in cross-cocurrent-cross configuration for adequate heat removal. On average 98.27% CH4 conversion to syngas in reforming section comprising of a pre-reformer unit and a tri-reformer unit, and CO2 separation rate of 36.75% along with CO/H2 reduction from 2.67 to 2.08 in CO2 membrane separation section were achieved from the entire pilot plant operation duration of 450 h. Parallel operation of FT microchannel reactor and multitubular fixed-bed type FT reactor for comparison showed that multitubular fixed-bed type reactor undergoes reaction runaway for the applied process conditions, while microchannel reactor showed adequate temperature control. Overall CO conversion of 83% and adequate temperature control at three different applied operating temperatures of 220 °C, 230 °C, and 240 °C subsequently during the 139 h FT reactor operation demonstrated the appreciable performance of the present microchannel FT reactor designed.

Direct synthesis of dimethyl ether in multi-tubular fixed-bed reactors: 2D multi-scale modelling and optimum design

The scope of this work is to explore the viability of the direct synthesis of dimethyl ether (DME) over bifunctional catalysts, such as mixtures of CuO/ZnO/Al2O3 and γ-Al2O3 at industrial scale. To accomplish this purpose, the process is simulated using a phenomenological mathematical model considering momentum, mass and energy balances, applied to both the catalyst particles and reactor bed, which is solved in 2D axisymmetric coordinates. This constitutes a step beyond most of the available studies for the modelling of the DME synthesis reaction, based on simple 1D isothermal models.The use of this detailed model revealed the importance of intraparticle mass and heat transfer, with effectiveness factors within the range 0.5–1.1. At the reactor scale, radial phenomena were found to be relevant. A design-sensitivity analysis of mass flux, catalyst fraction, pressure, feed temperature, cooling potential and tube diameter on the reactor performance was carried out. An optimized reactor design that provides 80% CO conversion operating at inlet temperature and pressure 245 °C and 40 bar, corresponds to 0.02 m diameter, 8.50 m length and 3600 h−1 gas-hourly space velocity with a yield of dimethyl ether of 0.53.

Thermal Integration of Sulfuric Acid and Continuous Catalyst Regeneration of Naphtha Reforming Plants

AbstractAn optimal reactor design is proposed that simultaneously improves the naphtha reforming reactor performance and increases sulfur trioxide production. In this new configuration, the naphtha reforming process as an endothermic reaction is coupled with the oxidation reaction of sulfur dioxide, which is an exothermic reaction. The differential evolution optimization technique is applied to maximize the produced amounts and yields of aromatics and hydrogen. The results obtained with the optimized thermally coupled reactor are compared with those of the conventional and thermally coupled reactors, proving the superiority of the proposed configuration.

Modeling marine oily wastewater treatment by a probabilistic agent-based approach

This study developed a novel probabilistic agent-based approach for modeling of marine oily wastewater treatment processes. It begins first by constructing a probability-based agent simulation model, followed by a global sensitivity analysis and a genetic algorithm-based calibration. The proposed modeling approach was tested through a case study of the removal of naphthalene from marine oily wastewater using UV irradiation. The removal of naphthalene was described by an agent-based simulation model using 8 types of agents and 11 reactions. Each reaction was governed by a probability parameter to determine its occurrence. The modeling results showed that the root mean square errors between modeled and observed removal rates were 8.73 and 11.03% for calibration and validation runs, respectively. Reaction competition was analyzed by comparing agent-based reaction probabilities, while agents' heterogeneity was visualized by plotting their real-time spatial distribution, showing a strong potential for reactor design and process optimization.

Thermogravimetric Kinetics and High Fidelity Analysis of Crude Glycerol

This work undertakes the determination of the glycerol thermochemical conversion kinetics in one hand, and the utilize of these quantities in high fidelity reactive flow model on the other. The kinetic parameters of glycerol are determined by using thermogravimetric analyzer (TGA) in the temperature range of 50-700 ͦC. Due to the distinct behavior of the crude glycerol, the TG curves of the thermal decomposition process were divided into several events, moisture release and two-subsequent devolatalization and gasification phases. The kinetic parameters, are calculated using four different methods: Arrhenius, Coats-Redfern, Ingraham Marrier and Differential Method. Results of the kinetics study were nearly consistent within the individual kinetic model but the discrepancy was more obvious amongst the different models. The resulted Coat-Redfirm kinetics were the best fit amongst other four considered methods demonstrated by its highest correlation R2. It resulted with activation energy of 62 kJ/mol and 138 kJ/mol and pre-exponential factor of 4.3e5 min-1 and 2.25e9 min-1 for phase 2 and phase 3, respectively. A high fidelity CFD model is developed to assess the performance of glycerol gasification in a tubular reactor. The model is governed by the Navier-stokes equations coupled to species transport equation for reactive flow under non-isothermal conditions. Results of the syngas conversion are in agreement with relevant literature and theoretical molar yield of 0.56 and 0.42 mole fractions for H2 and CO, respectively. The developed reactive flow model has brought more insight into the glycerol gasification, enabling further parametric studies in the pursuit of the optimal reactor design configuration and operating conditions for potential process integration.

Micro-kinetic modeling study of dry reforming of methane over the Ni-based catalyst

Dry reforming of methane (DRM) creates an opportunity to produce syngas using the shale gas and CO2. In the present work, a comprehensive and thermodynamically consistent micro-kinetic modeling was carried out for the DRM reaction under different reaction conditions. In order to reveal the complicated kinetics evolution, a rigorous descriptor (H2O/H2) and a rough descriptor (CO2/CH4) were identified due to their correlations with the θO/θ∗ ratio, dominant reaction pathway (DRP) and kinetically relevant steps (KRS). Moreover, the evolution of DRP and KRS along the descriptors under different reaction conditions were elucidated using the combined analyses of reaction pathway, sensitivity and partial equilibrium. It shows that at the high temperature, DRM is predominated by the first CH bond rupture via the direct and/or O∗-assisted mode; CO2 adsorption becomes kinetically relevant at the low descriptor. At the high total pressure, (CH2∗ + ∗) and (CH4∗ + O∗) would become the KRS at the low and high descriptors, respectively. In the end, hierarchical chemistry reduction gave two reduced mechanisms and an overall kinetics equation, with which main kinetics features could be predicted. Concept of descriptors seems to be generalized into other oxidation chemistries (e.g., steam reforming, RWGS and oxidative dehydrogenation) and provides insights into the reactor design and reaction optimization.

Optimal reactor design and operation taking catalyst deactivation into account

In this work, a new approach for taking catalyst deactivation into account in the early stage of reactor design is derived and exemplified by the ethylene oxide synthesis as an industrial relevant case study. In this process, the catalyst lifetime is much larger than the residence time of reactants. The operating conditions over the whole catalyst lifetime and the reactor configuration are simultaneously optimized. The objective of the mathematical optimization problem is the overall reactor performance such as the average selectivity over the catalyst lifetime. An optimal detailed design could be derived with advanced temperature control, giving rise to a higher average selectivity and potentially longer catalyst lifetime compared to the reference case.

Uncertainty analysis of Transportable Fluoride-salt-cooled High-temperature Reactor (TFHR) using coupled DAKOTA with RELAP-3D method

Reliable systematic uncertainty analysis is of great significance for reactor safety and licensing. In this paper, efforts have been made to quantify uncertainties of computational results. The uncertainty quantification and sensitivity analysis for a 20MWth prismatic Transportable Fluoride-salt-cooled High temperature Reactor (TFHR) proposed by MIT is performed with the DAKOTA code coupled to the best-estimate nuclear system software RELAP5-3D. Eight input parameters are selected with specified variations and probability density functions (PDFs), a total number of 400 steady-state and Unprotected Loss of Flow (ULOF) transient calculations are then conducted in order to statistically obtain the 5% and 95% peaking fuel temperature tolerance intervals with confidence level of 95%. The Latin hypercube sampling (LHS) model in DAKOTA is verified against analytical results and the TFHR RELAP5 modeling is benchmarked based on CFD calculations. It is found that, for the steady-state, the uncertainties of the heat transfer coefficient and helium gap conductivity factor are the most remarkable contributors to the statistical results of peaking fuel temperature. 0.5% of calculated fuel temperatures exceeded the steady-state fuel temperature limit of 1573K. Under ULOF accident condition, no temperature points exceeded the transient fuel failure limit 1873K, but there is a possibility of 0.195 leading to the damage of structural material. Three primary contributors to the uncertainty in peak fuel and outlet coolant temperature are the reactor power, helium gap, and heat transfer coefficient. The findings indicate that there are needs for further reactor design optimization from thermal-hydraulics prospective.

Computational fluid dynamics simulation of an industrial P. chrysogenum fermentation with a coupled 9-pool metabolic model: Towards rational scale-down and design optimization

We assess the effect of substrate heterogeneity on the metabolic response of P. chrysogenum in industrial bioreactors via the coupling of a 9-pool metabolic model with Euler-Lagrange CFD simulations. In this work, we outline how this coupled hydrodynamic-metabolic modeling can be utilized in 5 steps. (1) A model response study with a fixed spatial extra-cellular glucose concentration gradient, which reveals a drop in penicillin production rate qp of 18–50% for the simulated reactor, depending on model setup. (2) CFD-based scale-down design, where we design a 1-vessel scale down simulator based on the organism lifelines. (3) Scale-down verification, numerically comparing the model response in the proposed scale-down simulator with large-scale CFD response. (4) Reactor design optimization, reducing the drop in penicillin production by a change of feed location. (5) Long-term fed-batch simulation, where we verify model predictions against experimental data, and discuss population heterogeneity. Overall, these steps present a coupled hydrodynamic-metabolic approach towards bioreactor evaluation, scale-down and optimization.

Modeling, simulation and kinetic parameter estimation for diesel hydrotreating

The modeling and simulation of hydrotreating (HDT) reactors can provide relevant information about optimal operating conditions, reactor design and formulation of catalysts to achieve cleaner fuels. This study developed a phenomenological model to estimate the kinetic parameters for the HDT process using the design of experiments technique. The catalytic tests were carried out in a bench-scale unit with diesel as feedstock under similar conditions to those of the industrial units and commercial nickel-molybdenum on alumina (NiMo/γ-Al2O3) as catalyst. The reactor temperature was varied from 330 to 380°C and liquid hourly space velocity (LHSV) from 0.5 to 1.5h−1, keeping constant hydrogen to oil ratio (H2/oil) and pressure at 800stdm3/m3 and 90bar, respectively. The unknown parameters are estimated from experimental data by minimization of the unweighted least-squares function, using a non-linear optimization method (complex algorithm). The proposed model was able to reproduce different operating conditions with good adjustment and accuracy. Relative deviations below 4% for the experimental data and model prediction were achieved. Statistical parameters, p values, and confidence intervals confirmed the good quality of the estimated kinetic parameters. Internal diffusion resistances were present during hydrodesulfurization (HDS) and hydrodenitrogenation (HDN) reactions. The hydrogen consumption for HDS was higher than for HDN reaction. Finally, the proposed experimental design with 12 catalytic tests was satisfactory to obtain the desired results in a reliable way.

A sampling-based stochastic optimal experiment design formulation with application to the Williams-Otto reactor

Governmental pressure and an industrially competitive climate force chemical companies to strive for a sustainable design and operation. Model-based optimization has been proven to be an indispensable tool to achieve these goals. For the development and maintenance of process models, experimental data with a high information content are required. Model-based optimal experiment design techniques have been developed to obtain experiments that yield a high information content for estimating the model parameters. Since the true parameter values are unknown, these experiment designs start from the current best guesses. In practice, this can result in a lower information content than originally expected. In addition, the experiment design can become practically infeasible (e.g., in terms of safety), due to the violation of operational constraints. In this work a sampling-based stochastic optimal experiment design formulation is employed to address these problems. If the uncertainty on the model parameters can be considered to be a priori known, the parametric uncertainty can be propagated towards the states, which makes the experiment design more robust with respect to information content. As a practical case study of this formulation, the optimal experiment design of a Williams-Otto fed-batch reactor is made robust with respect to information content and reactor temperature state constraint violations. The novelty in this contribution is twofold: (i) polynomial chaos expansion and sigma points approach are compared for stochastic experiment design and (ii) the presented approach based on polynomial chaos expansion is analyzed for robustness with respect to state constraint violations considering different parametric uncertainty distributions.

Optimal design and operation of an industrial fluidized catalytic cracking reactor

Fluidized catalytic cracking (FCC) is regarded one of the most significant operations in the oil refining industries to convert feedstock (mainly vacuum gasoil) to valuable products (namely gasoline and diesel). The behavior of the fluidized catalytic cracking process is playing a main part on the overall benefits of refinery units and improving in process or control of fluidized catalytic cracking plants will result in exciting benefits economically. According to these highlights, this study is aimed to develop a new mathematical model for the FCC process taking into account the complex hydrodynamics of the reactor regenerator system with a new six lumps kinetic model for the riser. The mathematical model, simulation and optimization have done utilizing vacuum gas oil (VGO) as a feedstock and zeolite as a catalyst under the following operating conditions: temperature (733K, 783K, and 813K), weight hourly space velocity (5, 20 and 30h−1) and catalyst to oil ratio (4, 7 and 10). The best kinetic parameters of the relevant reactions are estimated using the optimization technique based on the experimental results taken from literature. The effect of operating condition (mainly, reaction temp (T), catalyst to oil ratio (CTO) and weight hourly space velocity (WHSV) on the product composition has also been discussed. The optimal kinetic parameters obtained from the pilot plant scale have been employed to develop an industrial FCC process, where optimal operating condition based on maximum conversion of VGO with minimum cost in addition to maximizing the octane number of gasoline (GLN), have been studied. Minimum coke content deposition the catalyst within the regenerator is also investigated here. New results (the highest conversion and octane number, and the lowest coke content) have obtained in comparison with those reported in the literature.

Particle-image-velocimetry measurements in organic liquid multiphase systems for an optimal reactor design and operation

Hydrodynamic features are very important to find an optimal reactor design for the hydroformylation of long-chain alkenes. For this purpose, and for the validation of theoretical reactor concepts, velocity measurements in a model reactor system are necessary. Due to the difficult reaction conditions found in reality (toxic thermomorphic organic solvent system, high pressure, high temperature, limited fields of view in typically used model reactors) such measurements are not an easy task. In this work, comparative particle-image-velocimetry (PIV) measurements have been used to find out if (1) the substitution of the solvent with water, and (2) reducing operation pressure still lead to similar results. For this purpose, PIV measurements have been performed in a stirred tank reactor under reaction conditions (organic solvents, high pressure, high temperature), but also with water at reduced pressure levels. It is found that pressure (as expected) and also the employed solvents do not have a significant influence on the observed flow structures, although density and viscosity are rather different. Therefore, further systematic experiments are now carried out in a model reactor, completely built out of glass, with water filling, and at atmospheric pressure. A complete hydrodynamic characterization is thus possible, opening the door for optimization of the resulting hydrodynamic field and for detailed comparisons with theoretical reactor design as well as numerical predictions.

A systematic reactor design approach for the synthesis of active pharmaceutical ingredients

Today’s highly competitive pharmaceutical industry is in dire need of an accelerated transition from the drug development phase to the drug production phase. At the heart of this transition are chemical reactors that facilitate the synthesis of active pharmaceutical ingredients (APIs) and whose design can affect subsequent processing steps. Inspired by this challenge, we present a model-based approach for systematic reactor design. The proposed concept is based on the elementary process functions (EPF) methodology to select an optimal reactor configuration from existing state-of-the-art reactor types or can possibly lead to the design of novel reactors. As a conceptual study, this work summarizes the essential steps in adapting the EPF approach to optimal reactor design problems in the field of API syntheses. Practically, the nucleophilic aromatic substitution of 2,4-difluoronitrobenzene was analyzed as a case study of pharmaceutical relevance. Here, a small-scale tubular coil reactor with controlled heating was identified as the optimal set-up reducing the residence time by 33% in comparison to literature values.

A stochastic kinetic study of preparing fatty acid from rapeseed oil via subcritical hydrolysis

A kinetic model based on the elementary reaction velocity theory is useful for investigating the kinetic rules of chemical reactions under subcritical and supercritical conditions. This model can be used to determine the stochastic relations between the hydrolysis products and conversion time in subcritical water based on the molecular collision theory. First, hydrolysis reaction experiments using rapeseed oil were conducted, and the collected data were used to verify the effectiveness of this stochastic kinetic model. The results showed that the kurtosis of this model was 1.11922, skewness was −1.49277 and mean error of the system was 0.81499, which was relatively small. Meanwhile, the adjustment coefficient (Adj. R2) was 0.98923, which indicated that this model is highly significant, that is, it can accurately depict the microscopic stochastic process of the rapeseed oil hydrolysis reaction. Furthermore, it verifies that the stochastic theory and molecular collision theory are feasible under subcritical conditions, which is a breakthrough in the field of the kinetic study of high-temperature and high-pressure reaction systems. Furthermore, the model reveals the changing rules of the reaction order and reaction velocity of the rapeseed oil hydrolysis reaction, which provides an important reference for parameter optimization of industrial reactor design.

Solar electricity via an Air Brayton cycle with an integrated two-step thermochemical cycle for heat storage based on Co3O4/CoO redox reactions III: Solar thermochemical reactor design and modeling

A two-step solar thermochemical cycle based on Co3O4/CoO redox reactions integrated into an Air Brayton cycle is considered for thermochemical heat storage. The two-step cycle encompasses (1) the thermal reduction of Co3O4 to CoO and O2 driven by concentrated solar irradiation and (2) the re-oxidation of CoO with O2 to Co3O4, releasing heat and completing the cycle. An evacuated horizontal solar thermochemical reactor is proposed with an inclined slope and quartz window for promoting direct irradiation of dense, granular Co3O4/CoO flows. Mechanical analysis of flat and spherical quartz window designs for a 5kWth scale prototype was performed to ensure window stability. Detailed mass and heat transfer analysis for a 5kWth scale prototype was performed coupling Monte Carlo ray tracing for radiative heat exchange to the energy balances for the bed and the reactor. A parametric study of the reactor design was performed with varying cavity depth, particle inlet temperature, and solar concentration ratio. The optimal solar reactor design maximized conversion of Co3O4 to CoO and particle outlet temperature while preventing particle overheating and achieved a Co3O4 to CoO conversion of 0.91, particle outlet temperature of 1385K, maximum flow temperature of 1572K, and absorption efficiency of 0.76.

Multiscale Studies on Ionic Liquids

Ionic liquids (ILs) offer a wide range of promising applications because of their much enhanced properties. However, further development of such materials depends on the fundamental understanding of their hierarchical structures and behaviors, which requires multiscale strategies to provide coupling among various length scales. In this review, we first introduce the structures and properties of these typical ILs. Then, we introduce the multiscale modeling methods that have been applied to the ILs, covering from molecular scale (QM/MM), to mesoscale (CG, DPD), to macroscale (CFD for unit scale and thermodynamics COSMO-RS model and environmental assessment GD method for process scale). In the following section, we discuss in some detail their applications to the four scales of ILs, including molecular scale structures, mesoscale aggregates and dynamics, and unit scale reactor design and process design and optimization of typical IL applications. Finally, we address the concluding remarks of multiscale strategies in the understanding and predictive capabilities of ILs. The present review aims to summarize the recent advances in the fundamental and application understanding of ILs.

遺伝アルゴリズムを用いた沸騰水型原子炉の次世代炉心管理システム : 炉心設計と炉心制御の統合型最適化( 最適化 : 広がる応用)

遺伝アルゴリズムを用いた沸騰水型原子炉の次世代炉心管理システム : 炉心設計と炉心制御の統合型最適化( 最適化 : 広がる応用)