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Post-combustion carbon capture (PCC) using a chemical solvent is the most mature and well-proven technology to mitigate carbon dioxide (CO2) emission. However, substantial energy consumption for solvent regeneration is still a critical challenge for widespread deployment of this PCC. In this study, a novel low-energy, combined rich and lean vapor recompression (RLVR) process for the CO2 capture process using dilute aqueous ammonia (NH3) solvent was developed and optimized by integrating of rich vapor recompression (RVR) and lean vapor recompression (LVR) approaches. A parametric study showed that the minimum total equivalent work can be obtained when CO2 loading and NH3 concentration of lean solution are 0.275 mol CO2/mol NH3 and 5.0 wt%, respectively and the pressures of stripper, rich and lean solvent flash drums are maintained at 10.5 bar, 4.62 bar and 6.93 bar, respectively. Under such operation conditions, the total equivalent work required for a CO2 capture plant was remarkably reduced to 0.123 kW h/kg of CO2 captured, which is equivalent to about 10% energy penalty. This amounts to 26–54% reduction from recent literature reports. Furthermore, this combined RLVR process can completely eliminate the need of reboiler, leads to improving the flexibility of the capture plant since it can be separated from power plant steam systems.

Large-scale solid oxide fuel cell (SOFC) systems create operational challenges owing to their size and scale. An SOFC dynamic digital twin model can help users understand the system status and determine the operating action. In this study, a dynamic digital twin of a 25 kW SOFC plant was presented as a simulator to help operators safely and stably determine the operating conditions for a real commercial SOFC plant. In the scale-up process, the data from the 1 kW SOFC pilot plant were used to analyze the reliability and electrode parameters and develop a digital twin model that matches actual conditions at the plant. The scale-up digital twin model is applied to a 25 kW SOFC system, in which the SOFC is connected with upstream reformers, downstream burners, and multiple heat exchangers. The 25 kW SOFC digital twin model was validated by steady-state data and applied to on-site operation prediction with very high accuracy. The digital twin was used as an operating reference in the field, and the results showed that it could effectively help operators determine operation strategies using simulations to safely and stably execute the process.

In industrial process, fault isolation technology will identify the major variables leading to faults. The existing fault isolation methods usually have ”smearing effect”, cannot identify the sensitivity of the fault variables, or require too much calculation. To solve the above problems, a multivariate fault isolation method based on between-class difference analysis and multidimensional reconstruction-based contribution (RBC) is proposed in this work. First, two kind of strategies, i.e.,principle component analysis (PCA) and fisher discriminant analysis (FDA), are adopted to obtain the sensitivity indicators of the variables to the faults respectively, which is taken as the basis for determining the optimal reconstruction direction. Then, multidimensional RBC is used to determine the number of fault variables based on the selected reconstruction direction. Finally, the primary and secondary fault variables are isolated according to their fault sensitivities. The feasibility of the proposed method is illustrated by a numerical simulation example and TE process. To sum up, the proposed method provide sensitivity information of each fault variables and high diagnosis rate. Moreover, it also has an advantage in reducing the calculation time because of the preliminary selection of fault variables.

In an ammonia-based post-combustion carbon capture (PCC) process, the regeneration energy of CO2-lean solvent comprises the main fraction of overall energy consumption. The use of a pressurized CO2 stripper to enhance the CO2 purity in the overhead vapor is one option for reducing the regeneration energy. Further energy reductions can be achieved by modifying stripper configurations reported in the literature. In this study, the energy-saving performance of advanced stripper configurations is investigated, including cold split bypass (CSB), lean vapor compression (LVC), and rich vapor compression (RVC). Our results show that the energy reduction by CSB has been underestimated in the literature because the effect of the warm rich feed stage has been neglected. Compared with a standard stripper operated at 10 atm, the CSB modification achieves 34.2% of energy reduction, and the combination of CSB and LVC reaches 34.4%. In other words, LVC only improves the energy saving of CSB by 0.2%.

In this study, a computational fluid dynamics (CFD) model of a sieve plate scrubber was built to predict its particle-removal efficiency and predict the U-shaped curve of the particle-removal efficiency as particles became smaller. Due to the complexity of particle tracking, it takes considerable time to simulate the model by using a three-dimensional (3D) structure, which is not conducive to finding the appropriate setting of particle forces. Instead, we presented a dimension-reduction method to estimate the particle force setting by using a two-dimensional (2D) structure. The rationality of the dimension-reduction method was validated by the consistency in froth density for both 2D and 3D models at various air-inlet velocities. Furthermore, the result of the particle forces setting showed that besides the drag force, other forces, such as the lift force, pressure-gradient force, gravity force, and virtual mass force, should be employed in the CFD model to predict the particle-removal efficiency of the sieve plate scrubber. The prediction results of the 2D model remarkably matches the particle-removal efficiency results of experimental data from the literature for various gas velocities and particle sizes. In addition, the model predicts the U-shaped curve of the particle-removal efficiency for the particle-diameter range from 0.1 to 1.0 μm. Furthermore, a 3D model with the setting of the particle forces as in the 2D model was used to validate the consistency between the 2D and 3D models. The result showed that the particle-removal efficiency of the 3D model was considerably close to the prediction results of the 2D model.

A real-time quantitative analytical approach, differential mobility analysis coupled to gas-phase Fourier-transform infrared spectroscopy (DMA/FTIR), is demonstrated for an aerosol spray-based synt...

Computational fluid dynamics (CFD) simulations of countercurrent gas–liquid flow in random packings of Raschig rings were carried out in this study. This model used gravity simulation to construct the random packing structure, and a volume expansion-recovery method to improve the meshing quality. A simple feedback control scheme was applied to control the gas inlet flow rate so that pressure drop can be estimated. The generated characteristics of the packing structure such as the number of packing elements, dry surface area and porosity were found to be close to experiments. CFD predictions of hydrodynamics properties are also validated by the experimental data using a small column section. The results indicate that our CFD model was able to capture the essential hydrodynamics behavior of the gas–liquid countercurrent flow. Hence, the approach presented in this study can be used as a basis for studying the effect of detailed packing-geometry design on hydrodynamic and mass transfer characteristics.

Hexamethylene-1,6-diisocyanate (HDI) is one of the most significant aliphatic diisocyanates for polyurethane production. The thermal decomposition of dimethylhexane-1,6-dicarbamate (HDC) has been considered as a very attractive non-phosgene route for HDI synthesis to realize industrialization because HDC can be synthesized by reacting 1,6-hexanediamine (HDA) with a green component, dimethyl carbonate (DMC). In this study, the optimal separation process design for non-phosgene HDC synthesis is investigated. Three design strategies to separate reaction products are proposed here. In the first two strategies, the low-boiling mixture containing un-reacted DMC and byproduct methanol is almost completely withdrawn from a column top, while some amount of un-reacted DMC is deliberately designed to be drawn out from the column bottom in the third strategy. Optimal processes designed by these three strategies are further enhanced by heat integration to reduce energy consumption. Simulation results reveal that the processes designed by strategy 3 need the least total annual cost and much economic benefit is achieved by the technologies of internal and external heat integrations. The key cost saving from internal heat integration is attributed to fully take advantage of the characteristic of DMC–methanol azeotrope at high pressure, and the higher column top temperature rendering condenser duty totally utilized by column bottom.

Background We present a dynamic model for designing a rotating packed bed (RPB) demonstrating volatile organic compound absorptions with circulation. The developed RPB model can be applied for industrial process simulations and scale-up. Methods The industrial applicability of the model was validated using in-house steady-state and dynamic RPB experimental data. The absorption of acetic acid (AA) in gas stream by an RPB, evaluated using reverse osmosis (RO) water and 1 wt.% NaOH aqueous solution, established the model. The operational variables’ effects, such as rotational speed and gas to liquid ratio, on the AA absorption efficiency are discussed. Significant findings The height of transfer unit (HTU) of the RPB was less than 3 cm, indicating the superior mass-transfer efficiency of the RPB than that of conventional packed bed column. The RPB model could predict the HTU in a steady-state well for the AA absorption, and the average absolute deviations (AAD) of HTU for the absorbent using RO water and 1 wt.% NaOH solution were 19.2% and 15.2%, respectively. Furthermore, the RPB model accurately predicted the AA absorption in circulation well for 1 wt.% NaOH with initial AA loadings of 1.7, 1.9, and 2.0 wt.% and AADs of 3.5%, 1.7%, and 1.9%, respectively.

The regeneration energies of CO2-lean solvent and NH3-washing water comprise the main fractions of the total energy consumption in an NH3-based post-combustion carbon capture (PCC) process. However, the reconfiguration of the CO2 absorption process may significantly reduce the requirement for NH3-washing water to relieve the energy burden of regenerating it. Additionally, the utilization of a pressurized CO2 stripper to enhance the purity of CO2 in the overhead vapor is an alternative strategy for reducing the energy requirement for regenerating the CO2-lean solvent. Moreover, further energy reductions can be achieved by modifying the stripper configurations that have been reported in the literature. In this study, the energy-saving performance of the modified configurations, including the utilization of a two-stage absorber, a cold-split bypass (CSB) and an advanced flash stripper (AFS) for PCC by an NH3-based solvent is investigated. Our results indicate that the concentration of NH3 slip can be reduced to a quarter of the emission by the two-stage absorber. Moreover, this study also demonstrates that the configuration of AFS is a limiting case of the CSB modification. The energy requirement of AFS is higher than that of CSB because the heat recovery by the main heat exchanger in AFS must be sacrificed to avoid solid precipitation in the reflux.

Dilute aqueous ammonia (NH3) process is considered as one of the alternative post-combustion carbon dioxide capture (PCC) technologies. However, the energy consumption for solvent regeneration is quite high, about 0.15–0.25 MWh/ton CO2 captured as equivalent work consumption. Therefore, reducing this valuable energy duty is still the major technical challenge to extensive deployment of this PCC technology. In this work, the NH3-based carbon capture process was developed using the lean vapor recompression approach. A parametric study revealed that the optimum energy consumption occurs at the lean solvent characterized by NH3 concentration of 5.0 wt% and CO2 loading of 0.275 mol CO2/mol NH3, with the stripper and flash pressures operated at 10.50 bar and 4.17 bar, respectively. Operating under such conditions, the total work duty for a CO2 capture plant was substantially reduced to 0.087 MWh/ton CO2 captured. In this process, the need of reboiler is completely eliminated.

In chemical engineering applications, computational efficient meta-models have been successfully implemented in many instants to surrogate the high-fidelity computational fluid dynamics (CFD) simulators. Nevertheless, substantial simulation efforts are still required to generate representative training data for building meta-models. To solve this problem, in this research work an efficient meta-modeling method is developed based on the concept of transfer learning. First, a base model is built which roughly mimics the CFD simulator. With the help of this model, the feasible operating region of the simulated process is estimated, within which computer experiments are designed. After that, CFD simulations are run at the designed points for data collection. A transfer learning step, which is based on the Bayesian migration technique, is then conducted to build the final meta-model by integrating the information of the base model with the simulation data. Because of the incorporation of the base model, only a small number of simulation points are needed in meta-model training.

A novel plant-wide process is designed for epichlorohydrin synthesis by the epoxidation of allyl chloride with hydrogen peroxide in the presence of titanium silicate 1 catalyst and methanol solvent. The design targets are to satisfy the requirements of product purities and address gas-phase safety concerns caused by the exothermic and violent decomposition potential (to oxygen and water) of hydrogen peroxide. There is a risk of oxygen/allyl chloride and oxygen/methanol systems exploding in the gas phase. A plant-wide process that includes one packed bed reactor, one distillation column, one decanter, and two strippers is proposed to meet the design targets and is optimized with minimum total annual cost. The strategies of feeding excess allyl chloride into the packed bed reactor and feeding two nitrogen gas streams into the column top and gas vent of a partial condenser in the distillation column, respectively, are used to prevent explosion in the gas phase. High-purity epichlorohydrin and water can be pr...

A systematic process intensification method via comparative grassroots and retrofit designs for distillation is proposed. Restricting to the ternary system, a case study of multicomponent C6 alkane separation in caprolactam processing is considered. The existing benchmark flowsheet of direct sequence (DS) features high economic cost but low thermodynamic efficiency. Through the investigation of the composition profile, two middle component remixing peaks and a large feed mismatch are diagnosed as the reasons of inefficiency. To achieve process intensification, potential candidates like side stream column (SSC) and dividing wall column (DWC) are enumerated and evaluated in the grassroots design step. Although DWC performs the best in thermodynamic efficiency, SSC is more preferred for retrofit as its structure is simple but has similar performance. To maximally reuse the existing equipment, two retrofit proposals of either indirect sequence (IS) or SSC are provided based on the grassroots design results. Among them, retrofitted SSC is recommended for long expected lifespan situation, while IS is more suitable for a short one. It is recommended that the proposed process intensification procedure can be extended to other similar processes or systems with more components, through enumerating and comparing the several best but similar grassroots designs with benchmark process.

Dimethyl carbonate (DMC) is a green compound with a broad variety of application. Recently, CO2-based routes to produce DMC have attracted much attention because of the environment benefits of CO2 utilization. In the study, we investigate the process design of synthesizing propylene carbonate (PC) for the DMC production using CO2 as a raw material by indirect alcoholysis of urea. The indirect alcoholysis route of urea shows many advantages because of cheap raw materials, mild and safe operation conditions, and environmentally friendly chemicals. Some different processes for PC synthesis by this route are proposed, designed, and optimized in this work. These processes can be classified in terms of two operation types: near-neat operation and excess reactant operation. Reactive distillation (RD) and heat integration technologies are used to intensify PC synthesis processes. Two processes are designed under the near-neat operation. Three RD plus conventional distillation (CD) processes with heat integration ...

Recently, reactive dividing-wall distillation (RDWD) has attracted much attention due to its capacity of process intensification. Nevertheless, its energy efficiency and economic benefit are likely to be enhanced by employing vapor recompression heat pump (VRHP) to reuse the energy of its overhead vapor. In this study, we explore the feasibility and effectiveness of this technology in two representative RDWD processes with different operation characteristics through in-depth evaluations of the steady-state performance of the VRHP reinforced RDWD ( i.e. , the proposed RDWD-VRHP). The first process involves the esterification of mixed acid (acetic acid and propionic acid) with methanol to yield methyl acetate, methyl propionate, and water. The second process involves the reaction of glycerol and hydrochloric acid to produce 1,3-dichlorohydrin, 2,3-dichlorohydrin, and water along with the intermediate products of 1-monochlorohydrin and 2-monochlorohydrin. Different configurations of the RDWD-VRHP are proposed for these two reaction systems and a systematic design procedure is developed to determine the optimum combination of the VRHP and the RDWD. Simulation results demonstrate that the RDWD-VRHP can substantially reduce utility consumption of RDWD. Especially, much more economic benefit can be secured by VRHP for the RDWD column with small column temperature difference and high latent heat in the overhead vapor.

This work evaluated the energy consumption of a large-scale post-combustion carbon capture (PCC) process for a 500 MW coal-fired power plant using aqueous ammonia solution. Firstly, the rate-based model in Aspen Plus was used to simulate the benchmarked process reported in the literature. In the benchmarked process, the ammonia stripper for the water wash loop and the carbon dioxide stripper in the carbon dioxide capture loop were designed relatively independently. The regeneration energy was reported to be 8.47 GJ/ton-CO2 using the solvent with 0.23 CO2 lean loading in mol-CO2/mol-NH3. By optimizing the benchmarked process, the optimal lean loading is about 0.20 and the regeneration energy was reported to be 6.74 GJ/ton-CO2. By integrating the ammonia stripper and carbon dioxide stripper, it was found that there is a limit on the regenerated lean loading of CO2 (∼0.15) that allows the closing of mass balance; however, the regeneration energy could be reduced to 4.0 GJ/ton-CO2.

In this study, both packed-bed (PB) and rotating PB (RPB) absorbers with a packed-bed stripper were used in a pilot plant for the removal of carbon dioxide (CO2) with 30 wt% monoethanolamine (MEA) as the solvent. The flue gas feed is the combustion product of the blast furnace gas from a steel mill containing approximately 30% of CO2. Both PB and RPB exhibit the same performance for the capture of CO2 with the same amount of energy consumption, but the RPB has a volume of approximately one-third that of PB absorber. The results obtained from experiments using ∼20 wt% MEA showed good agreement with those obtained from simulation using an Aspen rate-based model for PB and an Aspen custom modeler for RPB. These results demonstrated the feasibility of using a RPB for decreasing the size of absorber under relevant process conditions for capturing CO2.

Use of computational fluid dynamics to model chemical process system has received much attention in recent years. However, even with state-of-the-art computing, it is still difficult to perform simulations with many physical factors taken into accounts. Hence, translation of such models into computationally easy surrogate models is necessary for successful applications of such high fidelity models to process design optimization, scale-up and model predictive control. In this work, the methodology, statistical background and past applications to chemical processes of meta-model development were reviewed. The objective is to help interested researchers be familiarized with the work that has been carried out and problems that remain to be investigated.

Dichlorohydrin is an important intermediate for synthesizing epichlorohydrin, a high volume of commodity chemical largely utilized in the production of epoxy resins. In this study, a green process using an atom-efficient and environment-friendly route is used to synthesize dichlorohydrin by reacting glycerol, an available by-product in the biodiesel production, and hydrochloric acid under the homogeneous catalyst of acetic acid. A more accurate kinetic model is firstly established. Two plant-wide processes with continuous stirred-tank reactors and reactive distillation columns are then proposed and analyzed. In these processes, dichlorohydrin is obtained by decanting the overhead product of the reactive distillation column and withdrawing from organic liquid. Furthermore, some amounts of byproduct water in the reactive distillation column is withdrawn from a side stream to increase the reaction conversion. Finally, a novel intensification scheme known as thermally coupled reactive distillation or reactive divided-wall distillation is used to design the dichlorohydrin synthesis process. Simulation results demonstrate that this novel intensified plant-wide process gives much economical benefit for the dichlorohydrin production by glycerol hydrochlorination.

This work investigated a novel nonpetroleum-based catalytic process of methanol to phenol. The idea was to convert methanol to produce a main product stream having a molar ratio of propylene to benzene/toluene of unity along with relatively higher-value products including para-xylene and alkenes. Such a product mix would be ideal for the manufacturing of phenol. This was achieved using a catalyst of 1.5 wt% zinc impregnated on a silica-deposited HZSM-5 zeolite at 0.1 MPa, 430 °C and 1.2 h−1 weight hourly space velocity. HZSM-5, with its acidic sites predominately being Bronsted acid, produced mainly alkanes and aromatics, of which a good fraction was undesirable nine- or more-nine-carbon higher aromatics. Silica deposition on HZSM-5 passivated the catalytic activity outside the HZSM-5 pores, resulting in an increase of alkenes selectivity, a sharp decrease of nine- or more-nine-carbon higher aromatics selectivity, and a shift of the xylene product from an equilibrium mixture of meta-xylene, para-xylene, and ortho-xylene to mostly para-xylene. Impregnation of 1.5 wt% zinc on silica-deposited HZSM-5 generated more Lewis acid sites and further increased alkene selectivity, which, with the proper selection of process conditions, led to the production of the target stream. A detailed analysis of the effects of silica deposition, zinc impregnation, acidic sites, and process conditions on the catalyst performance was presented.

Accurate fluid phase equilibria modeling of carbon dioxide-methanol binary system is essential for numerous industrial applications. Prior modeling studies were limited in scope in terms of temperature and pressure ranges. In this study, the phase equilibria behavior of the binary system is modeled with cubic equations-of-state (EoS) including Peng–Robinson (PR) and Soave–Redlich–Kwong with various mixing rules, Predictive Soave–Redlich–Kwong, Cubic Plus Association, and Perturbed-Chain Statistical Associating Fluid Theory. Among them, the classical PR EoS and its variants yield the overall best results in representing the phase behavior at temperature above 330 K. However, PR incorrectly predicts two liquid phases when the CO2 mole fraction exceeds ~ 0.4 at temperature lower than 330 K. Raoult's law with the classical nonrandom two-liquid excess Gibbs energy model is recommended for the low temperature conditions.

Computer-aided molecular design requires the ability to predict different molecular properties of interesting from using molecular structure. Traditional quantitative structural property relations were developed by extracting molecular features for predicting various properties. Hence domains of molecular features are different for predictions of different properties. In this work, the concept of a universal translator was used to develop a universal digital chemical space by translating and projecting the chemical representation SMILES to a high-dimensional space that can be collapsed into different molecular fingerprints. We demonstrated different kinds of pure component properties, such as electrical and thermodynamic properties can be predicted by a simple input of molecular structure, SMILES. This method eliminates the need to manually extract different molecular features for predicting different properties. The ability of model to predict sigma profiles also pave the way of prediction phase equilibria of mixtures using molecular structure only.

The equilibrium-stage concept has often been used in the design of distillation and absorption processes. Departure from equilibrium is accounted for by tray efficiency and height equivalent of a theoretical plate (HETP). However, inaccurate efficiencies or HETP predictions are accounted for by rule-of-thumb safety factors. Explicit consideration of mass transfer using a rate-based approach is found to be critical when mass-transfer driving force is very low. In this study, the effects of mass transfer on the design of an extractive distillation process for the separation of DMC/MeOH azeotrope are presented. Vapor-phase resistance is found to be dominant in the extractive distillation column. Moreover, HETP in the rectification section of the column is substantially higher than experimental data reported in the literature. This can be attributed to not only the high purity requirement of methanol but also more importantly the fact that overhead methanol is a saddle rather than an attractor in the residual curve map. Therefore substantial reduction in column height can be achieved by designing individual sections using the rate-based model. Use of packings with better mass-transfer characteristics can also substantially reduce the height of the rectifying section.

Sulfur dioxide (SO 2 ) is one major air pollutant from burning the fossil fuels and its easier and more effective treatment can offer better protection of human health. Here, we demonstrate that the electrochemical double-cell (EDC) plate highly promotes the decomposition of SO 2 in simulated oxygen-rich exhausts to sulfur vapor and gaseous oxygen without consuming any reagent or other resource. SO 2 can be removed almost completely. Sulfur can be recovered as solid after cooling the sulfur vapor. The DeSO 2 rate increases with SO 2 concentration and also with O 2 concentration. Highest DeSO 2 rate occurs at around 170 °C. A novel technology of promoted SO 2 decomposition (PSD) is thus established. The real-world applicability of PSD is confirmed by SO 2 removal from the boiler flue gas using the electro-catalytic honeycomb, which consists of numerous EDCs.

Green synthesis of hexamethylene-1,6-dicarbamate (HDC) by reacting 1,6-hexanediamine with dimethyl carbonate (DMC) has garnered considerable attention recently because of the usage of DMC, which substitutes toxic phosgene. In this study, some plant-wide processes are proposed for green HDC synthesis. In the first process, HDC is synthesized using two reactive distillation (RD) columns in series. Excess DMC is used and the mixture of unreacted DMC and byproduct methanol from the RD column tops is separated by using a series of conventional distillation columns. Next, each RD column is enhanced by vapor recompression (VR) to reduce energy consumption by fully utilizing a small temperature difference between the column bottom and top. By the latent heat released from the overhead vapors of the RD columns, VR eliminates all reboiler duties of RD columns and conserves a substantial energy demand from conventional distillation columns. Compared with the process designed by RD, the process designed by RD + VR can reduce total operation cost and total annual cost by 42.6 % and 34.6 %, respectively. Finally, HDC synthesis by using CSTR is designed to compare with the RD- and RD + VR-intensified processes. Simulation results demonstrate that the reactive VR distillation process provides the most economical design for green HDC synthesis.

Although heterogeneous azeotropic dividing-wall distillation columns (HADWDCs) can achieve considerable reductions in capital investment and operating cost as compared to conventional heterogeneous azeotropic distillation systems, their steady-state performance is likely to be greatly enhanced by the application of vapor recompression heat pump (VRHP) technology owing to their unique process configuration of one top condenser and two bottom reboilers and favorable steady-state behavior of relatively small top-to-bottom temperature elevations. In the current work, the feasibility and effectiveness of reinforcing the HADWDC with the VRHP (HADWDC-VRHP) are examined. A systematic procedure is developed to effectively determine the optimum combination of the VRHP and the HADWDC in order to minimize the total annual cost. Two example systems for the separation of isopropyl alcohol and water and pyridine and water with cyclohexane and toluene as entrainers, respectively, are studied to evaluate the steady-state ...

A robust parameter estimation procedure was proposed to obtain accurate, confident parameters for the atmospheric residue desulfurization (ARDS) model in this work. A comprehensive ARDS model includes too many parameters such as deactivation and loading parameters. However, past studies have used data fitting in the early phases of reactor system life testing to obtain the parameters. This procedure was found to be too sensitive to the initial estimates used in fitting. In order to use the ARDS model for designing reactor systems and evaluating operating strategies, a robust parameter estimation procedure must be available. In this work, we demonstrate that the kinetic and deactivation parameters should be obtained from kinetic tests and accelerated test data, respectively for individual catalysts. Only loading parameters such as contact efficiencies should be obtained using early life test data. The procedure was validated with long-term experimental data. The results showed that the procedure could be a...

Statistical process control detects nonrandom deviations from a normal distribution. However, most industrial processes are equipped with feedback control loops to reject such disturbances. Hence it is the failure or performance degradation that we should detect instead of mere sensor data patterns that show deviations from normal. In this paper, a multi-objective monitoring approach is proposed to monitor both the system stability and performance. First, closed-loop output data are fitted with an autoregressive moving average model with exogenous inputs (ARMA(X)), using adaptive least absolute shrinkage and selection operator (LASSO). The system stability can be monitored using the largest absolute value of the roots of AR terms. The performance of feedback controller can be monitored based on the Minimum-Variance (MV) principles. The proposed approach was applied to several simulation examples to show that the above two monitoring objects are only sensitive to the faults in processes, but not to disturbances that can be handled by the controller. The ability of the method to localized control loop failure was demonstrated using the Tennessee–Eastman benchmark problem. In addition, we found that the method was able to identify the failure of the outer loop while the inner loop is still performing in a cascade control.

The C5 fraction, which accounts for 15–25% in naphtha, consists of molecules such as isoprene (IP), pentadiene (PD), cyclopentene (CP), and cyclopentadiene (CPD). The C5 fraction can be used to manufacture petroleum resin and other high-value-added products. Yet it is often burned as fuel and not fully utilized because separation of these products with close boiling points is difficult. One common process is to react CPD with itself to form high boiling dicyclopentadiene (DCPD) that can then be separated from other C5 molecules. In addition, extractive distillation is also used to recover alkynes from light ends. Such a process involves the use of multiple separation columns and reaction zones. Furthermore, the reactor is highly coupled with one of the separation columns by two recycle streams, which may lead to a snowball effect and difficulty in controlling the process. Hence, many opportunities for process integration and intensification are available. We describe how the entire process with reaction a...

Statistical process monitoring (SPM) has been adopted widely in manufacturing industry. Traditional SPM techniques such as principal component analysis (PCA) and partial least square (PLS) are applied to monitor a stationary process. When applied to a process with a feedback and/or feedforward controller, there are some monitoring challenges needed to be addressed, such as nonstationarity of process data and false alarm. To deal with these problems, a statistical online process monitoring scheme is presented in this paper. The proposed method consists of two phase: on-line time series model building and process monitoring via SPM. In the model building phase, a process with a controller is represented by a time series model, and a recursive extended least square (RELS) algorithm is used to identify the coefficients of this model. Furthermore, it is proved that the coefficients are stationary even if the process input/output data are non-stationary. In the process monitoring phase, the changes in process input-output relations or disturbance dynamics can be detected by applying SPM on the model coefficients. The validity and effectiveness of the proposed approach are illustrated by three examples in industrial processes, i.e., a semiconductor manufacturing process, a DC motor process and a benchmark Tennessee Eastman process.

Binary Ni-Co hydroxide is directly grown on screen-printed carbon electrodes (SPCEs) through cathodic deposition for detecting glucose. The material has been identified to consist of nickel-cobalt hydroxide (denoted as (Ni-Co)(OH) 2 ) by X-ray photoelectron spectroscopic analysis. From cyclic voltammetric (CV) and chronoamperometric (CA) results, (Ni-Co)(OH) 2 shows a more explicit signal than Co(OH) 2 and a less positive detecting potential than Ni(OH) 2 for glucose oxidation. Such synergistic performances suggest the atomic scale mixing of Ni and Co ions in the hydroxide matrix. The amperometric detection of this non-enzymatic glucose sensing shows a linear calibration curve up to 3700 μM with a sensitivity of 122.45 μA/(mM cm 2 ) ( R 2 = 0.989). The interference responses of 25 μM ascobic acid (AA), uric acid (UA), and dopamine (DA) were 10.76, 14.29 and 1.41% of the signal of 0.2 mM glucose, respectively. The binary (Ni-Co)(OH) 2 exhibits a low detecting potential, a high signal-to-noise ratio, and a wide calibration-curve range for the non-enzymatic glucose sensing.

This paper proposes a data-driven adaptive modeling approach to investigate the performance and optimal operation of a cooling tower for energy conservation. To achieve this aim, the cooling tower process was first characterized by an adaptive model with nonnegative garrote (NNG) variable selection procedure, which ensured a compact and robust input–output relation. Owing to the high accuracy of the obtained model, implementing the optimal operation strategy for energy saving became readily practicable. Subsequently, on the basis of the statistical results of NNG variable selection, the effects of ambient air temperature and humidity on the cooling capacity of the tower were investigated by principal component analysis (PCA). Finally, the optimal strategy of fan operation was proposed and its implementation was virtually studied based on data from the actual operation of a cooling tower, which showed that there was considerable room for energy conservation. This is the first attempt to use the NNG variable selection method for developing model for cooling tower and to propose a model-based control scheme for operating a cooling tower.

Biochemical networks are complex in nature. It is desirable that the key features be captured and analyzed using a core-network. In this work, a hierarchical core-network identification procedure was developed using parametric sensitivity and multi-way principal component analysis. The procedure was applied to the intracellular IKK to NFkBn (NFkB in nucleus) signaling transduction network to identify the key reactions in the network. We found that the key internal feedback control of IKK to NFkBn signaling transduction is through IkBa. The key reactions governing initial signal transduction are the phosphorylation of IkBaNFkB by IKK outside the nucleus, subsequent dissociation to release NFkB, and the transport of NFkB into the nucleus. Similar reactions involving IkBe and IkBb are only important when the IKK stimuli are relatively large. Moreover, this signal transduction network is able to damp the initial NFkBn response to IKK stimulus and transform large stimulus into delayed and sustained response. Such damping effect is present with only IkBa feedback loop is included, but IkBe and IkBb are responsible for transforming large stimulus into sustained response. Furthermore, the alternative pathway of formation of IKK-IkBa and trimerization of NFkB is responsible for a secondary buildup of IKK at large stimulus.

Even though ratio of air to fuel is the major factor in determining the thermal efficiency of a boiler, how to optimize the ratio in the real operation is still more like art than science, especially for a gas/solid multi-fuel combustion system. This study, taking operation data from a real gas/solid fuels co-firing boiler, is aimed to develop the thermal efficiency model. To cope with the complexity of combustion mechanism in a co-firing boiler, this study proposed a two-tier approach to modeling thermal efficiency. The first tier is to transform the plant input variables into the derived variables, which are physically and statistically meaningful to the model-building. In the second tier, this study proposed an adaptive modeling approach by employing nonnegative garrote variable selection and auto-regression integrated moving average correction. Both approaches are first time proposed in building the thermal efficiency model for boilers. The prediction error of boiler thermal efficiency made by the acquired model reaches less than 0.03%. The high accuracy of the proposed modeling approaches makes the implementation of the model-based control of ratio of air to fuel for improving boiler’s efficiency readily practicable.

The fluid mechanics of narrow stripe coating for low viscosity Newtonian solutions was investigated. A narrow stripe could be produced either through a slot die with a shim to control the slot width or through a rectangular nozzle. A flow visualization technique was employed to observe the mechanism on how a narrow stripe breaks at high coating speeds. Two-dimensional and three-dimensional numerical simulations on coating flows were also carried out to examine the fluid motion. The coating solution was found to expand laterally after emanating from the slot die channel at low coating speeds. The stripe width contracts gradually with increasing coating speed until coating failures appear. The coating defect observed switches from ribbing to a periodic stable and break-up motion. The effects of various fluid properties, geometric and operating parameters on the variation of coating width and maximum coating speeds were examined. A universal correlation involving two dimensionless groups, Reynolds and Bond number, was established for the prediction of coating width. © 2013 Curtin University of Technology and John Wiley & Sons, Ltd.

Semiconductor manufacturing is one of the fastest-growing industries today. As the recent requirements for feature sizes and wafer sizes change rapidly, it becomes imperative to configure increasingly intricate control schemes to maintain product quality and tool utilization rate. For this purpose, it is assumed in this study that a semiconductor production environment can be viewed as multiple queues operated in parallel and, also, the EWMA controllers can be implemented independently to adjust the process recipes of different products in each queuing system. Based on these assumptions, a MINLP model is formulated to determine the optimal dispatching policies. Systematic numerical simulation procedure is also devised to confirm the validity of the dispatching model. Since accurate estimates of the model parameters may not always be available, the effects of model mismatch have been analyzed and the proper range of controller tuning parameter is recommended to achieve an acceptable level of process capability.

Owing to the great degree of mass integration and energy integration between the prefractionator and the main distillation column, it is usually infeasible to achieve a four-point composition contr...

About 20% power output penalties will be incurred for implementing CO2 capture from power plant. This loss can be partially compensated by flexible operation of capture plant. However, daily large variations of liquid and gas flows may cause operation problems to packed columns. Control schemes were proposed to improve the flexibility of power output without causing substantial hydraulic disturbances in capture plant is presented. Simulations were implemented using ASPEN Plus. In varying lean solvent flow strategy, the flow rate of recycling solvent was manipulated to control the CO2 capture rate. The liquid flow of the absorber and gas flow of the stripper will vary substantially. In an alternative strategy, the lean solvent loading will be varied. Variation of gas throughput in the stripper is avoided by recycling part of CO2 vapor to stripper. This strategy provided more stable hydraulics condition in both columns and is recommended for flexible operation. © 2011 American Institute of Chemical Engineers AIChE J, 2012

In this study we examine the prediction of critical points in fluid mixtures from the Stryjek–Vera version of the Peng–Robinson equation of state (PRSV EOS) combined with the COSMO-SAC liquid activity coefficient model (LM) through the modified first order Huron–Vidal (MHV1) mixing rule. This approach requires input of only pure component properties, such as the critical properties and acentric factor. No binary interaction parameter or experimental data on vapor–liquid or liquid–liquid equilibrium is needed. Six different types of binary mixtures are studied, including alkane/alkane, ketone/alkane, alkanol/alkane, alkanol/aromatic, alkanol/alkanol, and water/alkane mixtures. In general, the predicted critical loci are in semi-quantitative to quantitative agreement with experiments. The mean absolute relative errors are found to be 2.99% for critical temperature and 11.22% for critical pressure. Therefore, this approach (PRSV + MHV1 + COSMOSAC) could provide reasonable a priori predictions of critical loci without the use of any experimental data of the mixture.

Semiconductor manufacturing is a highly automated and capital-intensive industrial process. The operating cost of a wafer processing plant is in general closely related to the design and management of its process flows. Traditionally, the task of production scheduling is performed manually on the basis of past experiences. There are thus real incentives to develop a systematic approach to construct a mathematical programming model in order to reduce the chance of human errors and to ensure operational efficiency in implementing the resulting schedules. To this end, the Petri nets are adopted in this work to accurately model the semiconductor manufacturing activities. The token movements in a Petri net are represented with the well-established scheduling model for batch chemical processes, and the optimal schedule of the given semiconductor process can then be determined accordingly. The feasibility and effectiveness of this scheduling strategy is demonstrated in the present paper with three examples, i.e., the final test process, the re-entrant flow process, and the photolithography-etching process.

In this study, plantwide control of an absorption/stripping CO 2 capture process using mono-ethanol-amine was investigated using dynamic simulation. In this system, CO 2 removal ratio is influenced by operating variables such as lean solvent rate and lean solvent loading, which is in-turn determined by reboiler duty in the stripper. Moreover, we found that the long term stability of the system cannot be achieved unless the water balance is properly maintained. Hence the following control structure was proposed. In this scheme, CO 2 removal target is guaranteed using the lean solvent feed rate to the top of the absorber column. The overall water inventory was maintained by controlling liquid level in reboiler of the stripping column using makeup water. In order to operate process with an appropriate lean solvent loading, the temperature at the bottom of stripper is controlled by reboiler duty. This control structure was tested by disturbances involving inlet flue gas flow, and CO 2 concentrations. Dynamic simulations showed that system can achieve removal targets, stabilize quickly while keeping optimum lean loading constant. To ensure minimum energy consumption, optimizing control can be carried out by adjusting the setpoint of reboiler temperature.

In conventional Run to Run (RtR) control, the recipe can be adjusted every run by using information of previous runs to maintain the process outputs on the desired target. However, in some semiconductor manufacturing processes, the aim of the RtR control is not to guide the controlled variables to set points or desired target, but only to maintain to them inside appropriate ranges or zones. On the other hand, the run-wise adjusting scheme is likely to generate the situation of “over control” and increase the cost of production. In order to overcome the problems, an exponentially weighed moving average (EWMA) with zone control strategy is presented in this work. The controller is started to regulate the recipe when proposed adjusting index exceeds the threshold. Then, the adjusted numbers can be decreased indeed. As a result of control, the consumption of manufacturing process will be reduced. The advantages of proposed control scheme are demonstrated by benchmark simulation and reversed engineered industrial applications.

In this study, using data-driven methods, we develop a soft senor based on a multiple local model for a nonlinear industrial process. The soft sensor is based on a novel learning algorithm, which u...

The objective of the present study is to examine the validity of the theoretical predictions on the operating windows of slot die coating. The operating window is defined as a domain inside which stable and uniform coating is possible; different types of coating defects are found outside the window. A flow visualization technique was applied to observe the coating bead, particularly the positions and shapes of the downstream and upstream menisci, just before and after coating defects appear at high coating speeds. Special features of coating bead shapes, which lead to onsets of ribbing and air entrainment, were identified. The two-dimensional flow in the coating bead region was computed by the commercial software package FLOW-3D®. Critical features observed experimentally for the onset of coating defects were used to judge whether the coating flow was within the operating window. The theoretically evaluated operating windows were found to be much larger than those determined experimentally in terms of coating speeds. However, the qualitative trends of theoretical predictions agree with experimental observations. © 2010 Wiley Periodicals, Inc. Adv Polym Techn 29:31–44, 2010; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/adv.20173

In this study, the densities of (aminomethanamide + 2-hydroxy-N,N,N-trimethylethanaminium chloride + water) and the solubilities of CO2 in (aminomethanamide + 2-hydroxy-N,N,N-trimethylethanaminium chloride) with different varying mole fractions of water at temperatures of (303, 308, and 313) K are reported. The common name for (aminomethanamide + 2-hydroxy-N,N,N-trimethylethanaminium chloride) is reline. The densities are linear (AAD % is 0.22 %) with respect to reline mass fraction at each temperature. The logarithms of Henry’s law constants were correlated using the two-suffix Margules model as a function of reline mole fraction with an AAD of 3.44 %. The results showed that CO2 solubility in reline decrease with an increase water content. Hence water can serve as an antisolvent to strip CO2 dissolved in reline. The absorption of CO2 in (aminomethanamide + 2-hydroxy-N,N,N-trimethylethanaminium chloride + water) at low pressures is found to be endothermic at water content. However, the absorption becomes...

In the study, the design and control strategies of a reactive distillation process with partially thermal coupling for the production of methanol and n-butyl acetate by transesterification reaction of methyl acetate and n-butanol are investigated. Since methanol and methyl acetate formed an azeotrope, the products of a reactive distillation column include n-butyl acetate and the mixture of methanol and methyl acetate, which must be separated by an additional column. Partially thermal coupling can be used to eliminate the condenser of the second column. Not only energy reduction but also better operability and controllability can be obtained for the thermally coupled reactive distillation process. Proper selection and pairing of controlled and manipulated variables chosen for three control objectives were determined by using steady-state analysis. A simple control scheme with three temperature control loops is sufficient to maintain product purities and stoichiometric balance between the reactant feeds.