Continuous Stirred Tank Reactor Research Articles

Maximum likelihood gradient‐based iterative estimation for closed‐loop Hammerstein nonlinear systems

AbstractThis article studies a new iterative method for a class of closed‐loop Hammerstein systems. The new iterative method solves the crossproducts between the parameters of the linear block and the nonlinear block by using the key term separation technique, decomposes a system into two subidentification models by utilizing the hierarchical identification principle for reduced computational complexity, and maximizes the maximum likelihood cost function by using the input and output data with a data window for improved parameter estimation accuracy. A numerical simulation example and a continuous stirred tank reactor experiment are presented to demonstrate that the proposed algorithm can work effectively.

Residence time distributions in a liquefier of material extrusion process

In this short communication, the residence time distribution of molten polymer in a liquefier of a material extrusion process is numerically investigated. The Laplace transform is used to easily fit the residence time distribution. As a result, the liquefier can be decomposed into a plug flow and a continuous stirred tank reactor in series. The local mean residence time is also studied numerically to provide information about the flow structure.

Effect of Fe2+ on ANAMMOX Granular Sludge Cultured in a Biased Acidic Influent and Dynamic Environment

A continuous stirred tank reactor (CSTR) was utilized in this study to enrich and cultivate anaerobic ammonia oxidation process (ANAMMOX) granular sludge by gradually decreasing its pH, and to investigate the effects of different concentrations of ferrous ions (Fe2+) on the activity of ANAMMOX granular sludge cultivated under biased acidic conditions. The final nitrogen removal of ANAMMOX deteriorated at pH 6.30–6.50 after 220 days of continuous operation, but the nitrogen removal of ANAMMOX was favorable at pH 6.50–7.00. This indicates that a slightly acidic environment (pH = 6.50–7.00) promotes the activity of ANAMMOX, but the pH should not be too low (pH = 6.30–6.50). In the reactor, Candidatus Kuenenia was consistently the dominant ANAMMOX genus and its abundance declined from 11.70% on day 1 to 10.44% on day 220. As Fe2+ concentrations were increased (10, 20, 30 mg/L) in ANAMMOX granular sludge cultured in an acidic environment, the nitrogen removal effects gradually increased. In addition, with the increase in Fe2+ concentrations, the total nitrogen removal load (NRL) in the reactor was increased from 1.16 kg/(m3/d) to 1.42 kg/(m3/d). Increases in Fe2+ concentration did not result in inhibition of ANAMMOX, which may be attributed to the morphology of sludge and the shape of the reactor. As a result of the present study, new insights were gained into the physiological characteristics of ANAMMOX in an acidic environment over the long term, and how Fe2+ affects its ability to remove nitrogen from the environment.

A high productivity bioprocess for obtaining metallic copper from printed circuit boards (PCBs)

PCBs constitute a residue rich in metals, among which copper stands out due to its majority content, much higher than that found in natural deposits, so that it is a potential secondary resource. Many attempts have been made to recover copper via biohydrometallurgy because it is an environmentally friendly route, however, one of its main drawbacks is the low productivity achieved.A global process based on circularity for obtaining copper cathodes from PCBs is proposed. First, PCBs from end-of-life mobile phones are shred to sizes between 800 and 2000 µm. Copper is leached from these pieces in a continuous stirred tank reactor (CSTR) at high ferric concentration, at a moderate temperature of 60 °C reaching dissolution rate higher than 1 g/L·h and a yield of 99 %. The solution that leaves the CSTR with concentrations of up to 10 g/L of Cu is passed through a high-performance bioreactor for the regeneration of Fe(III). A biooxidation rate of 1.3 g/L⋅h was achieved, and no inhibition was observed.Concurrently, copper is recovered in metallic state by solvent extraction and electrowinning with recirculation streams becoming a more profitable and sustainable complete global process.

EVALUATION OF THE INFLUENCE OF MIXER ROTATION THROUGH COMPUTATIONAL FLUID DYNAMICS SIMULATION OF A CONTINUOUS STIRRED-TANK REACTOR FOR BIODIESEL PRODUCTION FROM EXPERIMENTAL KINETIC DATA

In the present work, a computer simulation was performed through computational fluid dynamics (CFD) for a Continuous Stirred-Tank Reactor, starting from experimental data on the kinetics of the transesterification reaction between soybean oil methyl acetate, using an enzyme as a catalyst, the Candida Antartica. A volume was proposed for the reactor so that the average residence time of the reaction mixture was sufficient for the expected yield, based on the data obtained by the Matlab®, was obtained at the exit of the reactor. The simulation of the reactor operation was of a continuous process with constant reagents flow rates made using commercial software ANSYS®. The impeller chosen was of the type inclined straight blades, the simulations were made by varying the rotation speed of the mixer where an increase in reaction yield was observed until the rotation of 120 RPM, above this speed, no real gain was observed in the amount of biodiesel obtained.

Scalable and sustainable manufacturing of ultrathin metal–organic framework nanosheets (MONs) for solar cell applications

Metal-organic framework nanosheets (MONs) are an emerging class of 2D materials whose tunable chemistry make them ideal for a wide range of sensing, catalytic, electronics and separation applications. However, creating scalable routes to the synthesis of high quality, ultrathin nanosheets remains challenging and little consideration has been given to the economics of making these materials. Here, we demonstrate a scalable synthesis of zinc-porphyrin based nanosheets, Zn2(H2TCPP), for use in organic solar cells and conduct a techno-economic analysis of their pilot-plant scale manufacture. A thorough investigation of the process chemistry of the solvothermal synthesis enabled reduction of reaction time, increased solid content and scale-up of the reaction in batch. Significantly, the addition of triethylamine accelerated the reaction kinetics, which enabled the synthesis temperature to be dropped from > 80 °C to room temperature. Application of these new reaction conditions in a continuous stirred-tank reactor directly formed monolayer MONs at 99 % yield with a space–time yield of 16 kg m−3 day−1, an approximately 20-fold increase in yield compared to adapting the literature procedure. Techno-economic analysis showed a 94 % reduction in the production costs compared to the literature reaction conditions and indicated that the production cost was dominated by ligand price. The general applicability of the method was demonstrated through synthesis of related Cu2(H2TCPP) MONs and tunability through metalation of the porphyrin units with six different metal ions. Finally, the value of the nanosheets was demonstrated through a near doubling in the power conversion efficiency of organic photovoltaic devices when the MONs were incorporated into the active layer. Overall, this work demonstrates the first scalable and sustainable route to producing monolayer nanosheets for high value applications.

Exploring the viability of a floating photocatalyst in a continuous stirred tank reactor system for continuous water treatment.

The use of photocatalysts in continuous stirred tank reactor (CSTR) systems allows for efficient and continuous water treatment, thus meeting the demand for scalable technology and comparative data in large-scale implementations. Hence, this study aims to explore the feasibility of a floating photocatalyst within a CSTR system for continuous water treatment. An expanded polystyrene (EPS)-TiO2 composite was synthesized following established methodologies, and their efficacy in removing the water pollutant methylene blue (MB) was compared for both batch and CSTR systems. A nonlinear first-order model was identified as the most suitable approach to accurately simulate MB degradation under experimental conditions, and the calculated pseudo-first-order degradation rate constant (k') for the CSTR system (0.0126-0.0172/min) was found to be superior to that observed for the batch system (0.0113/min). In addition, an increase in the flow rate reduced the retention time, leading to lower MB removal efficiency for the CSTR system. In addition, the EPS-TiO2/UV system with a CSTR configuration was found to efficiently use light and energy based on the calculated quantum yield (Φ = 2.86 × 10-4) and electrical energy per order (EEO = 857.46 kWh/m3/order). The findings of this study contribute to the development of sustainable and efficient water treatment strategies, offering valuable insight into the implementation of practical water treatment processes.

Exploring the Dynamics of Simple Inhibition Systems in Continuous Stirred-Tank Reactor: Mathematical Modelling and Bifurcation Analysis

The simple enzyme inhibition systems consist of competitive inhibition, noncompetitive inhibition and uncompetitive inhibition. In this work, we incorporated these simple inhibition systems in the continuous stirred-tank reactor (CSTR) and analysed the models using some techniques from dynamical systems and bifurcation analysis. Our aim is to investigate the behaviours of such systems and compare their overall dynamics. The phase portrait is constructed to simulate possible behaviours such as stable steady states, stable limit cycle, bistability between the steady state and the stable limit cycle and bistability between two steady states. The systems undergo bifurcational changes in dynamics as enzyme concentration, dilution rate and proportional control constant are varied. Moreover, we conducted a codimension two bifurcation analysis to examine the joint effects of dilution rate and proportional control constant on the systems behaviours. Our results revealed distinct dynamics for each inhibition system. Increasing the dilution rate led to a transition from low to high substrate concentrations, with competitive inhibition showing the highest tipping (or bifurcation) point where dynamical regimes change due to intense substrate-inhibitor competition. Elevating enzyme concentration reduced substrate concentration, particularly in non-competitive inhibition systems due to higher conversion rates. Furthermore, the proportional control constant had varying effects depending on the specific inhibition system. These findings emphasize the on the combined influences of distinct chemical procoesses in controlling reactor heat and optimizing bioprocess efficiency, considering the unique characteristics of each inhibition system. Overall, the dynamical study on these simple inhibition systems enables us to improve our understanding on the chemical processes involving enzymes with multiple types of inhibitors and may give some insights in its controlling process.

Modified performance-enhanced PCA for incipient fault detection of dynamic industrial processes

Timely fault detection plays a critical role in modern complex industrial processes. While statistical process monitoring has gained significant practical application in recent years, traditional data-driven multivariate statistics often lack sensitivity in detecting incipient faults. To this end, this paper proposes a novel approach for fault detection of dynamic industrial processes. First, the process data are processed by the time series model, so as to separate and obtain corresponding static components. Then, a performance-enhanced principal component analysis method is employed to handle the static components. Besides, the detection index is further optimized to improve its detection performance. Finally, the proposed method’s effectiveness is illustrated through a numerical example and the continuous stirred tank reactor process. Moreover, the universality of the optimization algorithm which acts on the detection statistic is illustrated on the Tennessee Eastman process as well.

Anaerobic digestion of thickened secondary sludge after microwave advanced oxidation pretreatment

A microwave-enhanced advanced oxidation process (MW-AOP) was used to treat thickened waste secondary sludge prior to anaerobic digestion (AD). A large amount of soluble chemical oxygen demand (SCOD) and volatile fatty acids (VFAs) was formed in the solution after pretreatment. Both single- and two-phase systems loaded up to 18.2 g volatile solids/(l day) while achieving high methane production, as well as high overall treatment efficiency. Both the upflow anaerobic blanket reactor and the continuous stirred tank reactor could operate at very short hydraulic retention times as short as 2 days without any evidence of souring. The results indicated that an acid reactor in the two-phase system was not required, due to very high levels of SCOD and VFAs produced in the MW-AOP-pretreated solution. As such, a single AD should be able to handle this easily biodegradable substrate following microwave pretreatment.

Residual neural network-based observer design for continuous stirred tank reactor systems

Continuous stirred tank reactor (CSTR) is a common reactor in the chemical industry. The accurate observation of the concentration conversion rate of the mixture and the internal temperature of the reaction vessel is a prerequisite for obtaining the desired mixture. This paper proposes a novel observer based on residual neural networks for CSTR systems. Firstly, the mathematical model of the CSTR reaction is given, as well as a detailed description of the structure and equations of the residual neural networks and the designed observer. Then the matrix method is used for the nonlinear isolation of the residual neural networks and the theory of quadratic constraints for nonlinear activation functions of the neural networks is applied. Thus, the convergence of the proposed observer is analyzed theoretically in detail. Finally, the numerical simulations are implemented to demonstrate that the proposed residual neural network-based observer can quickly and accurately observe the state changes during the CSTR reaction.

Integration of in-situ and ex-situ power-to-gas (PtG) strategy for simultaneous bio-natural gas production and CO2 emission reduction

A novel system integrating an in-situ and ex-situ power-to-gas (PtG) system was developed in the current study. A continuous stirred-tank reactor (CSTR) was operated using cattle manure as substrate at mesophilic temperature (37 °C ± 2 °C). The CH4 content in the biogas was upgraded to above 95% by H2 injection, which meets the highest criteria for grid injection without requiring CO2 removal. Furthermore, the bio-nature gas production was promoted by external CO2 and H2 injection. The volumetric methane production rate (VMPR) was significantly increased by 739% from 117.4 mL L−1·d−1 to 985 mL⋅L−1⋅d−1, which is higher than in other studies. Meanwhile, the volumetric biogas production rate (VBPR) was increased by 36.9% by H2 injection, increasing the conversion efficiency (82.56%) of the chemical oxygen demand (COD) to CH4. A significant increase in the specific methanogenic activity of dissolved hydrogen (SMA(Hdissolved)) and the enrichment in hydrogenotrophic methanogens (Methanobacterium) demonstrate that the CH4 production pathway was converted from acetoclastic methanogenesis (AM) pathway to hydrogenotrophic methanogenesis (HM) pathway. It is postulated that the change in proportion of different pathways of the CH4 production was caused by the strengthening of key enzymes (coenzyme F420 hydrogenase and coenzyme-B sulfoethylthiotransferase) by H2 injection. The integrated system represents a promising approach to achieve simultaneous CO2 emission reduction and bio-natural gas production.

Simulation Of The Optimum Operating Conditions For A Propylene Glycol Production Unit Using Aspen Hysys Software

Commercially, propylene glycol is produced by the direct hydrolysis of propylene oxide with water. This first-order, irreversible, exothermic reaction is performed in a glass-lined Continuous Stirred Tank Reactor (CSTR). In this study, the initiation of a CSTR was modelled from first principles and simulated using Aspen Hysys 3.2 to obtain concentration and temperature profiles. It is often very important how these profiles approximate the steady-state values. For example, when approaching a steady state the temperature may rise too high and this leads to degradation of the reactant or product, or the altitude may be unacceptable for safe operation. If either condition occurs, the system will exceed its practical stability limit. The practical stability limit represents the temperature above which it is undesirable to operate due to undesirable side reactions or equipment damage. Therefore, the best-operating conditions were obtained in terms of the flow rate of the raw material and the temperature of the reactor at 345 Kgmol/h and 82.2 °C on straight. The production of propylene glycol in the presence of an acid catalyst in an isothermal tank reactor is presented using advanced process simulation software. The effect of temperature was also calculated using the principle of energy balance on the reactor. The reactor operates optimally at a fractional conversion of 0.995 to obtain optimal values for the most important variables/parameters [reactor volume 7.92 m3, reactor length 2.83 m, reactor diameter 1.89 m, and amount of heat required for cooling per unit volume of the reactor 1205 kw].

Is well-mixed model of an indoor space with ceiling fans valid for studying pathogen transmission?

Airborne transmission is one of the main modes for the transmission of highly infectious diseases such as COVID-19. Pathogen laden aerosols from an infected person can be transported by air to a susceptible population. A widely used model for airborne transmission considers the indoor space to be well-mixed such that the pathogen concentration is spatially homogeneous. Other models that employ computational fluid dynamics (CFD) allow tracking the spatiotemporal variation of infection probability in indoor spaces but are computationally expensive. Here, we compare the predictions of a well-mixed continuously stirred tank reactor (CSTR) model for indoor transmission with CFD for airflow, along with the Lagrangian tracking of aerosol particles. Of particular interest is the ventilation using ceiling fans, which are common in South East Asia. It is found that the behavior of particles at the walls plays an important role. Two limiting cases are studied: all particles reaching the wall get trapped vs all particles being reflected from the solid boundaries. We propose a modification to the CSTR equation to include the wall effect, and it matches the CFD data closely.

Auxiliary model‐based interval‐varying maximum likelihood estimation for nonlinear systems with missing data

AbstractThe identification problem of nonlinear system with missing data is focused in this article. In order to overcome the system unavailable outputs, an auxiliary model‐based interval‐varying recursive identification method is derived by changing the sampling interval and substituting the missing output with the output of an auxiliary model. Based on the maximum likelihood principle and the least‐squares method, a maximum likelihood‐based interval‐varying recursive least‐squares method is investigated. The validity of the proposed maximum likelihood method is tested by a numerical simulation example and a practical continuous stirred tank reactor (CSTR) process.

Enhancing bio-hydrogen and bio-methane production of concentrated latex wastewater (CLW) by Co-digesting with palm oil mill effluent (POME): Batch and continuous performance test and ADM-1 modeling

This study aimed at investigating the biohydrogen and biomethane potential of co-digestion from palm oil mill effluent (POME) and concentrated latex wastewater (CLW) in a two-stage anaerobic digestion (AD) process under thermophilic (55 ± 3 °C) and at an ambient temperature (30 ± 3 °C) conditions, respectively. The batch experiments of POME:CLW mixing ratios of 100:0, 70:30, 50:50, 30:70, and 0:100 was investigated with the initial loadings at 10 g-VS/L. The highest hydrogen yield of 115.57 mLH2/g-VS was obtained from the POME: CLW mixing ratio of 100:0 with 29.0 of C/N ratio. While, the highest subsequent methane production yield of 558.01 mLCH4/g-VS was achieved from hydrogen effluent from POME:CLW mixing ratio of 70:30 0 with 21.8 of C/N ratio. This mixing ratio revealed the highest synergisms of about 9.21% and received maximum total energy of 19.70 kJ/g-VS. Additionally, continuous hydrogen and methane production were subsequently performed in a series of continuous stirred tank reactor (CSTR) and up-flow anaerobic sludge blanket reactor (UASB) to treat the co-substate. The results indicated that the highest hydrogen yield of POME:CLW mixing ratio at 70:30 of 95.45 mL-H2/g-VS was generated at 7-day HRT, while methane production was obtained from HRT 15 days with a yield of 204.52 mL-CH4/g-VS. Thus, the study indicated that biogas production yield of CLW could be enhanced by co-digesting with POME. In addition, the two-stage AD model under anaerobic digestion model no. 1 (ADM-1) framework was established, 9.10% and 2.43% of error fitting of hydrogen and methane gas between model simulation data and experimental data were found. Hence, this research work presents a novel approach for optimization and feasibility for co-digestion of POME with CLW to generate mixed gaseous biofuel potentially.

DESIGN OF BIOGAS COOLING PROCESSING FROM POME FOR (CSTR) CONTINUOUS STIRRED TANK REACTOR SYSTEM

POME (Palm Oil Mill Effluent) can be used as for biogas production, with the main content of (65%) methane gas (CH4) and 35% Carbon Dioxide (CO2), H2S, and H2O gases. Apart from being a gas fuel and a source of electricity generation, biogas from POME waste as well as a waste processor becomes more environmentally friendly (according to quality standards). In order to support the process production of biogas from POME by using Continuous Stirred Tank Reactors (CSTR), it is necessary to decrease POME’s temperature to meet the requirements of the reactor operating conditions. Cooling process by using a Cooling Tower through direct contact between fluids can be a good alternative to be used as a POME cooling method because of its effectiveness in heat exchange and smaller area needed than an open ponds. The type of cooling tower used is the Induced Draft Cooling Tower. In cooling tower design, the steps involved in determining the basic design, calculation of tower dimensions, basin, fan power, losses, and cooling air requirements. Based on the calculation, the tower dimensions determine a height of 5 m, length of 3.6 m, and width of 2.5 m, while the basin cooling tower dimensions determine a height of 2.7 m, length of 3.6 m, and width of 2.5 m, fan power of 5 hp. The cooling air requirement for the POME cooling process is 82,895.14 kg/hour.

Offset-Free Quasi-Infinite Horizon Nonlinear Model Predictive Controller Design Using Parameter Adaptation

Abstract This paper proposes an offset-free Quasi-Infinite Horizon Nonlinear Model Predictive Controller (QIH-NMPC) using online parameter adaptation. In the proposed method, the adaptation law is modeled by a first order differential equation as a function of the tracking error and subsequently combined with a QIH-NMPC algorithm for online updating of the unknown parameter. The effectiveness of the proposed control scheme is demonstrated on a continuous stirred tank reactor (CSTR) and an experimental cascaded three-tank system with uncertain model parameters, structural plant/model mismatch and noisy measurements. For the purpose of comparison, the state-of-the-art online state and parameter estimators such as moving horizon estimation (MHE) and extended Kalman filter (EKF) were also incorporated into QIH-NMPC algorithm. The simulation and experimental results obtained showed the efficacy of the proposed adaptation scheme as it demonstrated a comparable performance to standard estimators (MHE and EKF) although with a lesser computational time.

Machine learning aided model predictive control with multi-objective optimization and multi-criteria decision making

Model predictive control (MPC) is a well-established control methodology in chemical engineering, but the increasing complexity of chemical processes necessitates the consideration of multiple objectives in the MPC optimization step. To address this research gap, this work proposes a comprehensive machine learning (ML) aided MPC with multi-objective optimization (MOO) and multi-criteria decision making (MCDM) methodology (abbreviated as ML-aided MPC-MOO-MCDM) for chemical process control. The proposed methodology is evaluated on a continuous stirred tank reactor (CSTR), and the results demonstrate its capability to achieve intended optimization considering multiple objectives in MPC without compromising the closed-loop stability of the controlled system. The present work also reinforces the viability of using ML models as surrogates for first-principles models in process control and optimization. Overall, this work exhibits the effectiveness of the proposed ML-aided MPC-MOO-MCDM methodology and its applicability to complex chemical processes.

Influence of pH on the performance of anaerobic piggery wastewater treatment coupled with membrane-based NH3 extraction

The influence of the pH of piggery wastewater (PWW) on both ammonia recovery and anaerobic digestion performance during PWW treatment was evaluated in a continuous stirred tank reactor coupled with a membrane-based extraction module. The anaerobic digester was operated at a hydraulic retention time of 20 days at 37 °C, while the flat sheet PTFE membrane module operated continuously at liquid recirculation rates of 250 mL min−1. The membrane module was able to gradually decrease the total ammoniacal concentration from 1.27 ± 0.01 to 0.62 ± 0.01 g L−1 after 360 days of operation. Membrane-based NH3 extraction induced a CH4 yield increase of 1.3-fold. Moreover, COD and VS removal efficiencies increased up to 1.2-fold and 1.5-fold, respectively, along with the increase in PWW pH from 7.5 to 12. Total VFAs removal efficiencies were higher at a PWW pH of 9.