The rise in the use of global polyester fiber contributed to strong demand of the Terephthalic acid (TPA). The liquid-phase catalytic oxidation of p-xylene (PX) to TPA is regarded as a critical and efficient chemical process in industry [1]. PX oxidation reaction involves many complex side reactions, among which acetic acid combustion and PX combustion are the most important. As the target product of this oxidation process, the quality and yield of TPA are of great concern. However, the improvement of the qualified product yield can bring about the high energy consumption, which means that the economic objectives of this process cannot be achieved simultaneously because the two objectives are in conflict with each other. In this paper, an improved self-adaptive multi-objective differential evolution algorithm was proposed to handle the multi-objective optimization problems. The immune concept is introduced to the self-adaptive multi-objective differential evolution algorithm (SADE) to strengthen the local search ability and optimization accuracy. The proposed algorithm is successfully tested on several benchmark test problems, and the performance measures such as convergence and divergence metrics are calculated. Subsequently, the multi-objective optimization of an industrial PX oxidation process is carried out using the proposed immune self-adaptive multi-objective differential evolution algorithm (ISADE). Optimization results indicate that application of ISADE can greatly improve the yield of TPA with low combustion loss without degenerating TA quality.

Cracking furnace is the core device for ethylene production. In practice, multiple ethylene furnaces are usually run in parallel. The scheduling of the entire cracking furnace system has great significance when multiple feeds are simultaneously processed in multiple cracking furnaces with the changing of operating cost and yield of product. In this paper, given the requirements of both profit and energy saving in actual production process, a multi-objective optimization model contains two objectives, maximizing the average benefits and minimizing the average coking amount was proposed. The model can be abstracted as a multi-objective mixed integer nonlinear programming problem. Considering the mixed integer decision variables of this multi-objective problem, an improved hybrid encoding non-dominated sorting genetic algorithm with mixed discrete variables (MDNSGA-II) is used to solve the Pareto optimal front of this model, the algorithm adopted crossover and mutation strategy with multi-operators, which overcomes the deficiency that normal genetic algorithm cannot handle the optimization problem with mixed variables. Finally, using an ethylene plant with multiple cracking furnaces as an example to illustrate the effectiveness of the scheduling results by comparing the optimization results of multi-objective and single objective model.

A microbial fuel cell (MFC) is a novel promising technology for simultaneous renewable electricity generation and wastewater treatment. Three non-comparable objectives, i.e. power density, attainable current density and waste removal ratio, are often conflicting. A thorough understanding of the relationship among these three conflicting objectives can be greatly helpful to assist in optimal operation of MFC system. In this study, a multiobjective genetic algorithm is used to simultaneously maximizing power density, attainable current density and waste removal ratio based on a mathematical model for an acetate two-chamber MFC. Moreover, the level diagrams method is utilized to aid in graphical visualization of Pareto front and decision making. Three biobjective optimization problems and one three-objective optimization problem are thoroughly investigated. The obtained Pareto fronts illustrate the complex relationships among these three objectives, which is helpful for final decision support. Therefore, the integrated methodology of a multi-objective genetic algorithm and a graphical visualization technique provides a promising tool for the optimal operation of MFCs by simultaneously considering multiple conflicting objectives.

The modeling and optimization of an industrial-scale crude distillation unit (CDU) are addressed. The main specifications and base conditions of CDU are taken from a crude oil refinery in Wuhan, China. For modeling of a complicated CDU, an improved wavelet neural network (WNN) is presented to model the complicated CDU, in which novel parametric updating laws are developed to precisely capture the characteristics of CDU. To address CDU in an economically optimal manner, an economic optimization algorithm under prescribed constraints is presented. By using a combination of WNN-based optimization model and line-up competition algorithm (LCA), the superior performance of the proposed approach is verified. Compared with the base operating condition, it is validated that the increments of products including kerosene and diesel are up to 20% at least by increasing less than 5% duties of intermediate coolers such as second pump-around (PA2) and third pump-around (PA3).

A novel rule-based model for multi-stage multi-product scheduling problem (MMSP) in batch plants with parallel units is proposed. The scheduling problem is decomposed into two sub-problems of order assignment and order sequencing. Firstly, hierarchical scheduling strategy is presented for solving the former sub-problem, where the multi-stage multi-product batch process is divided into multiple sequentially connected single process stages, and then the production of orders are arranged in each single stage by using forward order assignment strategy and backward order assignment strategy respectively according to the feature of scheduling objective. Line-up competition algorithm (LCA) is presented to find out optimal order sequence and order assignment rule, which can minimize total flow time or maximize total weighted process time. Computational results show that the proposed approach can obtain better solutions than those of the literature for all scheduling problems with more than 10 orders. Moreover, with the problem size increasing, the solutions obtained by the proposed approach are improved remarkably. The proposed approach has the potential to solve large size MMSP.

A T-Q diagram based on entransy theory is applied to graphically and quantitatively describe the irreversibility of the heat transfer processes. The hot and cold composite curves can be obtained in the T-Q diagram. The entransy recovery and entransy dissipation that are affected by temperature differences can be obtained through the shaded area under the composite curves. The method for setting the energy target of the HENs in T-Q diagram based on entransy theory is proposed. A case study of the diesel oil hydrogenation unit is used to illustrate the application of the method. The results show that three different heat transfer temperature differences is 10 K, 15 K and 20 K, and the entransy recovery is 5.498×10⁷ kW·K, 5.377×10⁷ kW·K, 5.257×10⁷ kW·K, respectively. And the entransy transfer efficiency is 92.29%, 91.63%, 90.99%. Thus, the energy-saving potential of the HENs is obtained by setting the energy target based on the entransy transfer efficiency.

A systematic strategy for retrofit of the multi-period heat exchanger network (HEN) on the basis of the multiobjective optimization is developed. In this three-stage procedure, a simplified multi-objective optimization model of the multi-period HEN is first established and then solved to target the retrofit, aiming to minimizing the total annual cost and total annual CO₂ emissions. The obtained Pareto front represents series of retrofit targets under different emission limitations, from which the most desirable one can be selected. The matching of the existing and the required heat exchangers is further implemented to finalize the retrofit, which will meet the practical retrofit requirements and matching restrictions. The application of the proposed procedure is illustrated through a case study of a HEN in a vacuum gas oil hydro-treating unit.

Due to the deterioration of serious energy dilemma, energy-conservation and emission–reduction have been the strategic target in the past decades, thus people have identified the vital importance of higher energy efficiency and the influence of lower carbon development. Since work exchange network is a significant part of energy recovery system, its optima design will have dramatically significant effect on energy consumption reduction in chemical process system. With an extension of the developed transshipment model in isothermal process, a novel step-wise methodology for synthesis of direct work exchange network (WEN) in adiabatic process involving heat integration is first proposed in this paper, where a nonlinear programming (NLP) model is formulated by regarding the minimum utility consumption as objective function and optimizing the initial WEN in accordance with the presented matching rules to get the optimized WEN configuration at first. Furthermore, we focus on the work exchange network synthesis with heat integration to attain the minimal total annual cost (TAC) with the introduction of heat-exchange equipment that is achieved by the following strategies in sequence: introducing heat-exchange equipment directly, adjusting the work quantity of the adjacent utility compressors or expanders, and approximating upper/lower pressure limits consequently to obtain considerable cost savings of expanders or compressors and work utility. Finally, a case taken from the literature is studied to illustrate the feasibility and effectiveness of the proposed method.

Inferior crude oil and fuel oil upgrading lead to escalating increase of hydrogen consumption in refineries. It is imperative to reduce the hydrogen consumption for energy-saving operations of refineries. An integration strategy of hydrogen network and an operational optimization model of hydrotreating (HDT) units are proposed based on the characteristics of reaction kinetics of HDT units. By solving the proposed model, the operating conditions of HDT units are optimized, and the parameters of hydrogen sinks are determined by coupling hydrodesulfurization (HDS), hydrodenitrification (HDN) and aromatic hydrogenation (HDA) kinetics. An example case of a refinery with annual processing capacity of eight million tons is adopted to demonstrate the feasibility of the proposed optimization strategies and the model. Results show that HDS, HDN and HDA reactions are the major source of hydrogen consumption in the refinery. The total hydrogen consumption can be reduced by 18.9% by applying conventional hydrogen network optimization model. When the hydrogen network is optimized after the operational optimization of HDT units is performed, the hydrogen consumption is reduced by 28.2%. When the benefit of the fuel gas recovery is further considered, the total annual cost of hydrogen network can be reduced by 3.21×10₇ CNY·a_-1, decreased by 11.9%. Therefore, the operational optimization of the HDT units in refineries should be imposed to determine the parameters of hydrogen sinks base on the characteristics of reaction kinetics of the hydrogenation processes before the optimization of the hydrogen network is performed through the source-sink matching methods.

Dividing wall column (DWC) is shown to be energy efficient compared to conventional column sequence for multi components separation, which is used for olefin separation in fluidization methanol to propylene process in the present work. Detailed design for pilot DWC was performed and five control structures, i.e. composition control (CC), temperature control (TC), composition-temperature control (CC-TC), temperature difference control (TDC), double temperature difference control (DTDC) were proposed to circumvent feed disturbance. Sensitivity analysis and singular value decomposition (SVD) were used as criterion to select the controlled temperature locations in TC, CC-TC, TDC and DTDC control loops. The steady simulation result demonstrates that 25.7% and 30.2% duty can be saved for condenser and reboiler by substituting conventional column sequence with DWC, respectively. As for control structure selection, TC and TDC perform better than other three control schemes with smaller maximum deviation and shorter settling time.

Dimethyl carbonate is an environmentally benign and biodegradable chemical. Based on integration of reactive distillation and pressure-swing distillation technologies, a novel process for synthesis of dimethyl carbonate through transesterification with propylene carbonate and methanol has been developed by Huang et al. In this work, the optimization of this process was performed by minimizing the total TAC. The results show that the optimal design flowsheet can save energy consumption by 18.6% with the propylene carbonate conversion of 99.9%. Then, an effective plant-wide control structure for the process was developed. Dynamic simulation results demonstrate that the temperature/flow rate cascade control plus with simple temperature control can keep not only product purity but also the conversion of the reactant at their desired values in the face of the disturbance in reactant feed flow rate and feed composition.

A coupled system simulating both firebox and reactor is established to study the naphtha pyrolysis in an industrial tubular furnace. The firebox model is based on zone method including combustion, radiation, and convection to simulate heat transfer in the furnace. A two-dimensional recirculation model is proposed to estimate the flow field in furnace. The reactor model integrates the feedstock reconstruction model, an auto-generator of detail kinetic schemes, and the reactor simulation model to simulate the reaction process in the tubular coil. The coupled simulation result is compared with industrial process and shows agreement within short computation time.

Heat exchangers play an important role in supercritical water coal gasification systems for heating feed and cooling products. However, serious deposition and plugging problems always exist in heat exchangers. CFD modeling was used to simulate the transport characteristics of solid particles in supercritical water through the shell and tube of heat exchangers to alleviate the problems. In this paper, we discuss seven types of exchangers (A, B, C, D, E, F and G), which vary in inlet nozzle configuration, header height, inlet pipe diameter and tube pass distribution. In the modeling, the possibility of deposition in the header was evaluated by accumulated mass of particles; we used the velocity contour of supercritical water (SCW) to evaluate the uniformity of the velocity distribution among the tube passes. Simulation results indicated that the optimum heat exchanger had structure F, which had a rectangular configuration of tube pass distractions, a bottom inlet, a 200-mm header height and a 10-mm inlet pipe diameter.

The application of spray towers for CO₂ capture is a development trend in recent years. However, most of the previous jobs were conducted in a cylindrical tower by using a single spray nozzle, whose configuration and performance is not good enough for industrial application. To solve this problem, the present work proposed a diameter-varying spray tower and a new spray mode of dual-nozzle opposed impinging spray to enhance the heat and mass transfer of CO₂ absorption process. Experiments were performed to investigate the mass transfer performance (in terms of the CO₂ removal rate (η) and the overall mass transfer coefficient (K_Ga_e2 are major factors, which affect the absorption performance and the maximums of η and K_Ga_e that are 94.0% and 0.574 kmol·m^-3·h^-1·kPa^-1, respectively, under the experimental conditions. Furthermore, new correlations to predict the mass transfer coefficient of the proposed spray tower are developed in various CO₂ concentrations with a Pearson Correlation Coefficient over 90%.

As one of the main reasons causing leakage heat load in a refrigerator, mass and heat transfer through refrigerator door seal is of great importance to be studied. In this paper, a model is presented for numerical simulation of mass and heat transfer process through refrigerator door seal, and an experiment apparatus is designed and set up as well for comparison. A two-dimensional model and tracer gas method are used in simulation and experiment, respectively. It can be found that the relative deviations of air infiltration rate between the simulated results and experimental results were less than 1%, and the temperature difference errors at two special points of the door seal were less than 2.03℃. In conclusion, the simulated results are in good agreement with the experimental results. This paper initially sets up a model that can accurately simulate the heat and mass transfer through the refrigerator door seal, and the model can be used in refrigerator door seal optimization research in the follow-up study.