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Reducing production costs without sacrificing product quality is essential for the global market survival. The problem of line balancing, especially assembly line balancing, plays an important role for industry in achieving the highest quality and lowest cost. This project presents the simulation of line balancing the pesticide packaging assembly line in pesticidebased company. This study aims to develop a productive and effective way of assembling the product to meet customer demands. Line balancing is about arranging a production line so that the production flow from one workstation to the next is even. Line balancing also provides a successful tool to reduce bottleneck by balancing the task time of each workstation so that no delays occur, and nobody is overburdened with their work. The whole project contains study of line balancing through theoretical calculation and analysis done in the simulation model. The simulation was performed using the Process Simulator. Process simulator has been used to simulate the layout condition based in precedence diagram. The first step in using Process Simulator is to create a simulation model of a process in the Visio layout. This is accomplished by adding activities, entities, and resources to the Visio layout and then connecting them with arrival and routing connections. Overall simulation result shows that total unit produce for 5 weeks is 12,240 cartons with average time in system 11,293.85 minutes and average time in operation is 2.39 mins. Filling process and manual labelling process shows highest operation percentage. The percentage of blocked items increased before the bottleneck process. The assembly line plays a critical role in enabling the factory to deliver the right quantity and quality on time.

It is impossible to overstate the value of process simulators in teaching process engineers about petrochemical, chemical, nuclear, and biological processes. Several chemical engineering topics, including process design, thermodynamics, process integration, separation processes, safety, and others, are made easier to teach because of this. Only a handful of these process simulators are freeware, while most are largely commercial. The ones that are commercialized are renowned for their friendliness, extensive media coverage, and international credibility attained for their forecasts in several industrial applications. However, schools in low-income countries may not be able to buy them. In contrast, the freeware publicity is not relatively low, less friendly, and cheaper than the commercial ones. This research compares the agreement of the forecast of commercial process simulators with freeware ones in an effort to strengthen institutions' trust in the prediction of freeware process simulators. The analysis modeled and simulated a chemical process involving the Gibbs reactor, heater, compressor, and mixer in the COCO and Aspen HYSYS simulators. Findings from the research reveal good agreement in the predicted results obtained from the various process simulators. With the use of COCO, different possible methane oxidation routes were analyzed. The analysis confirmed that the route leading to the formation of CO2 and water would be less energetic than other routes. In addition, the formation of water would be much easier in the process than hydrogen at the condition employed in the study. Due to cost, the study recommends using the freeware process simulator instead of the cracked version, which is often utilized in educating process engineers and research projects in communities where research and education are poorly funded. [ABSTRACT FROM AUTHOR]

Solvent extraction as environmental benign separation technique can be modeled in physical detail by population balance of the droplet size distribution. However, much information on the droplet generation and coalescence is necessary for representative results. In this contribution, we present a comparison of AI‐evaluated experimental and simulated data on the behavior of a stirred solvent extraction column with an inner diameter of 32 mm. Lab experiments were performed using the standard test system with n‐butyl acetate, acetone, and deionized water. A digital camera is placed in front of the middle section as well as the head of the column. Droplet size evaluation is performed using a retrained neural net (Mask R‐CNN). The stirred DN32 extraction column is modeled and simulated using a 1D CFD population balance software. The simulation allows for behavior analysis, trends comparison, and validation of the hydrodynamics and mass transfer performances. [ABSTRACT FROM AUTHOR]

Copyright of Revista Producao Online is the property of Associacao Brasileira de Engenharia de Producao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To understand the mechanism of a catalytic system, computational analysis is essential. Additionally, process simulators play a fundamental role in the reproduction of models associated with various unit operations such as chemical reactors. However, due to the complexity that some chemical and kinetic reactions may present, it is often complicated to design a reactor considering stoichiometric and chemical kinetic relationships resorting to yield-based or Gibbs-type reactors. This barrier has limited on several occasions the adequate reproduction of kinetic processes, their dynamic study, and even the direct application of process intensification strategies. This work presents a generic optimization framework for solving parameter estimation and catalyst design problems. Using a stochastic optimization method in conjunction with Aspen Plus and experimental data, kinetic data values were predicted. The direct advantage of obtaining kinetic parameters with this methodology is to be able to represent the kinetics according to the Arrhenius equation, which is widely used in commercial simulators. To validate this method, a previously presented case of dimerization of isobutane to produce isooctane is used as a baseline. Once the proposed methodology was used, it was possible to obtain kinetic parameters like those obtained by the authors of the case study with an error lower than 0.1%. Finally, the strategy to determine the kinetic parameters of a more complex case, the kinetic values of the oligomerization and hydrogenation reactions present in the aviation biofuel production process by the ATJ method were developed obtaining results like those reported experimentally with an error percentage lower than 1%, and with statistical metrics with relatively good approximation. • Determination of kinetic parameters based on experimental data for use in commercial simulators. • Optimization-based technique for determining kinetic in complex chemical reactions. • Use of complex and rigorous models for theoretical validation of kinetics and experimental data of chemical reactions. [ABSTRACT FROM AUTHOR]

As the culmination of the Chemical Engineering curriculum, students face the challenging and stimulating elaboration of a whole design project that integrates all the knowledge gained throughout the course. The subject is divided into two parts, gaining a theoretical background in the ninth semester and a proposed teamwork project design with the aid of a process simulator in the tenth semester. This paper presents the challenge of designing a whiskey distillery elected by a group of students applying the project‐based learning methodology. As a strategy for a more efficient design, the process is divided into three blocks: prefermentation, fermentation, and distillation. Calculations involve mass and energy balances and the design of the different units, including the optimization of a distillation column assisted by the ASPEN HYSYS® simulator. Students must publicly present their results in front of the class and a jury formed by chemical engineers. A survey was carried out to assess the student's satisfaction and feedback. The results manifested the significance of the subject for the future and the satisfaction of the proposed teaching strategy. [ABSTRACT FROM AUTHOR]

Data‐driven process monitoring and control techniques and their application to industrial chemical processes are gaining popularity due to the current focus on Industry 4.0, digitalization and the Internet of Things. However, for the development of such techniques, there are significant barriers that must be overcome in obtaining sufficiently large and reliable datasets. As a result, the use of real plant and process data in developing and testing data‐driven process monitoring and control tools can be difficult without investing significant efforts in acquiring, treating, and interpreting the data. Therefore, researchers need a tool that effortlessly generates large amounts of realistic and reliable process data without the requirement for additional data treatment or interpretation. In this work, we propose a data generation platform based on the Tennessee Eastman Process simulation benchmark. A graphical user interface (GUI) developed in MATLAB Simulink is presented that enables users to generate massive amounts of data for testing applicability of big data concepts in the realm of process control for continuous time‐dependent processes. An R‐Shiny app that interacts with the data generation tool is also presented for illustration purposes. The app can visualize the results generated by the Tennessee Eastman Process and can carry out a standard fault detection and diagnosis studies based on PCA. The data generator GUI is available free of charge for research purposes at https://github.com/dtuprodana/TEP. [ABSTRACT FROM AUTHOR]

Biodiesel is a promising energy substitute of fossil fuels since it is produced from renewable and biodegradable sources. In the present work, reactive distillation (RD) process is designed and simulated using Aspen Plus process simulator to produce biodiesel of high purity through esterification reaction. The simultaneous reaction and separation in same unit enhances the biodiesel yield and composition in RD process. Two flowsheets are proposed in present work. In the first flowsheet, the unreacted methanol is recycled back to reactive distillation column. Biodiesel with 99.5 mol% purity is obtained in product stream while the byproduct stream comprises 95.2 mol% water, which has to be treated further. In the second flowsheet, a part of methanol recycle is split and purged. In this case, the biodiesel composition in product stream is 99.7 mol% whereas water composition is 99.9 mol% in byproduct stream, which can be reused for other process without treatment.

This work aims to investigate the application of a comprehensive nonlinear model-based predictive control strategy as a means to avoid unsafe or inappropriate operation of a gas turbine. Herein, the nonlinear model-based predictive control is employed to control compressor speed by varying the fuel flow in the combustion chamber. The methodology complies with the gas turbine constraints explicitly in the optimization procedure and, therefore, the nonlinear model-based predictive control algorithm ensures that process constraints are not violated. The nonlinear dynamic behaviour of the gas turbine is modelled with the aid of a first principle process simulator, which solves the equations of state and the conservation equations of mass, energy and momentum. The optimization procedure is achieved through the implementation of an evolutionary algorithm. Three scenarios are simulated: fuel consumption optimization, load removal/addition and load rejection. The proposed control strategy is successfully applied to both transient and steady-state operational modes of the gas turbine.

The cost-effectiveness of reactive distillation (RD) processes makes them highly attractive for industrial applications. However, their preliminary design and subsequent scale-up and operation are challenging. Specifically, the response of RD system during fluctuations in process parameters is of paramount importance to ensure the stability of the whole process. As a result of carrying out simulations using Aspen Plus, it is shown that the RD process for isoamyl acetate production was much more economical than conventional reactor distillation configuration under optimized process conditions due to lower utilities consumption, higher conversion and smaller sizes of condenser and reboiler. Rigorous dynamic modeling of RD system was performed to evaluate its sensitivity to disturbances in critical process parameters; the product flow was quite sensitive to disturbances. Even more sensitive was product composition when the disturbance in heat duties of condenser or reboiler led to a temperature decrease. However, positive disturbance in alcohol feed is of particular concern, which clearly made the system unstable.

Featured Application: Proposed process simulator can be widely applied to parameter design of industrial Tempcore process with reduced cost and time. Tempcore process simulator (TPS) has been developed in this study to analyze the microstructural evolution of quenched and tempered rebar. There has been an increasing need to relate the complex microstructures to the resulting properties of quenched and tempered rebar. However, information on such relationships typically requires precise thermal histories imposed on the workpiece. Therefore, TPS, capable of simulating the Tempcore process, has been developed to produce high-fidelity data. TPS mainly consists of a vacuum induction furnace, pilot rolling mill, box furnace, and cooling unit to simulate shop floor operations. A series of experimental tests were successfully carried out with various parameters, such as reheating temperature, water flow, water pressure, and cooling time. The effects of chemical compositions and cooling time on the microstructural evolution and mechanical properties of quenched and tempered rebar have been analyzed to validate the performance of TPS. The results show that TPS can simulate the Tempcore process with a high degree of fidelity and reliability. [ABSTRACT FROM AUTHOR]

This work aims to apply a multivariable nonlinear model-based predictive control strategy (MPC) to avoid unsafe or inappropriate operation of gas turbines, while reducing NO x emissions. In this context, the control variables are the compressor speed and the temperature after the turbine. The controller maintains the speed proportional to the grid frequency during load changes. Additionally, in cases where the turbine is installed in a combined heat and power cycle, the discharge temperature must follow a reference, to ensure the quality of the steam generated. The control is achieved by manipulating the fuel flow in the combustion chamber and the variable inlet guide vanes of the compressor. The nonlinear dynamic behavior of an industrial gas turbine is modeled using a first principle process simulator, which solves the mass, energy and momentum conservation equations, together with an equation of state. Furthermore, pollutant emissions are minimized as part of the process, through an optimization procedure. The optimization problem is solved through the implementation of three different evolutionary algorithms and one direct search method. The proposed control strategy is successfully applied to a gas turbine in load rejection scenarios, and the optimization fulfills its goal by reducing nitrogen oxides emissions. [ABSTRACT FROM AUTHOR]

Tempcore process simulator (TPS) has been developed in this study to analyze the microstructural evolution of quenched and tempered rebar. There has been an increasing need to relate the complex microstructures to the resulting properties of quenched and tempered rebar. However, information on such relationships typically requires precise thermal histories imposed on the workpiece. Therefore, TPS, capable of simulating the Tempcore process, has been developed to produce high-fidelity data. TPS mainly consists of a vacuum induction furnace, pilot rolling mill, box furnace, and cooling unit to simulate shop floor operations. A series of experimental tests were successfully carried out with various parameters, such as reheating temperature, water flow, water pressure, and cooling time. The effects of chemical compositions and cooling time on the microstructural evolution and mechanical properties of quenched and tempered rebar have been analyzed to validate the performance of TPS. The results show that TPS can simulate the Tempcore process with a high degree of fidelity and reliability.

Determination of process structure of thermal utilization of mineral mat­ters from waste streams, is a multi-variant problem. These processes are energy-intensive and it is very important to determine the process structures for realization of the required processes in the starting phases of process development. The structure of the process system, beside the system equilibrium, depends on vector parameters of the feed stream. In this work a newly developed methodology for determination of process variants of thermal utilization of mineral salts from a hypothetical three-component AX-BX-H2O system is presented. The methodology is created on starting synthesis problem for which a set of types of process units for realization process and type of desired crystal product is determined. The methodology includes process decomposition in two subsystems: concentration (saturation) subsystem and crystallization subsystem. Concentration of feed stream is realized in isothermal conditions of water evaporation and crystallization process using various techniques: isothermal water evaporation, cooling of solution in vacuum and cooling of solution through contact surface. Determination of physical feasible processes is performed by simulation of the process superstructure in which each particular process structure is a special case of the created process superstructure. Realization of mentioned activity is provided by creating algorithms and programming software (process simulator) in which the equation system of the superstructure mathematical model is solved for various variants of set of specified variables. The created methodology and possibilities of the created process simulator are presented in the illustrative case study of waste stream utilization of the NaCl-KCl-H2O system. In addition to this, for conditions of total heat integration of subsystems is demonstrated that a small change of salt concentration of feed stream can require transfer non-cyclic in cyclic process structure.

Sustainable development of cities around the world is a means of providing a high quality of city environment and living standards of the population. One of the main aspects of sustainable development of city infrastructure is social stability, which involves among others the criteria of transport safety and reliability. Nowadays transport infrastructure objects, especially in big cities, are in focus of increased attention from the safety and security arrangement point of view. Provided that, the purpose of the paper is to develop a mechanism of continuous monitoring, testing and improvement of transport safety system in order to provide its ability to adequately respond to new challenges of the environment. The paper describes an approach to the development of safety system and emergency situations management, based on the concept of “enterprise architecture”. The approach involves analysis and testing of existing safety and emergency regulations and personnel instructions using a specific simulation software, and further correction of the regulations and instructions basing on the results of the analysis. The proposed approach was tested in Saint Petersburg Underground (Russia). Such kind of approach potentially could be implemented into practice of not only underground transport systems, but for other types of transport enterprises as well. [ABSTRACT FROM AUTHOR]

Downstream processing of biofuels and bio-based chemicals represents a challenging problem for process synthesis and optimization, due to the intrinsic nonideal thermodynamics of the liquid mixtures derived from the (bio) chemical conversion of biomass. In this work, we propose a new interface between the process simulator PRO/II (SimSci, Schneider-Electric) and the optimization environment of GAMS for the structural and parameter optimization of this type of flowsheets with rigorous and detailed models. The optimization problem is formulated within the Generalized Disjunctive Programming (GDP) framework and the solution of the reformulated MINLP problem is approached with a decomposition strategy based on the Outer-Approximation algorithm, where NLP subproblems are solved with the derivative free optimizer belonging to the BzzMath library, and MILP master problems are solved with CPLEX/GAMS. Several validation examples are proposed spanning from the economic optimization of two different distillation columns, the dewatering task of diluted bio-mixtures, up to the distillation sequencing with simultaneous mixed-integer design of each distillation column for a quaternary mixture in the presence of azeotropes. [ABSTRACT FROM AUTHOR]

Abstract The aim of this paper is to build a process simulator to aid the process and control engineers in design and simulation . The simulator is to be built of software modules . The basic modules are integrator and dead time , lag , and two - lag . Practical process built from the basic one are deadtime and integrator , deadtime and lag , deadtime and two - lag . The present work is achieved by using Levenberg - Marqardet algorithm with variable learning rate , the software used in this work is implemented by using Turbo ( C language ) with technical MATLAB version 6.0 package .

An effective tool is required for a successful and effective development and design of technologies. It is often necessary to propose several conceptual designs for the particular application. To assess and compare all designs, the process simulation software is usually used. Especially, for the cases of complex technologies which consist of several unit operations. There are several commercial products allowing comprehensive design, simulation, and optimization, such as Aspen HYSYS®AspenTech (commercial product) or DWSim (open source). Nevertheless, none of them includes directly electromembrane unit operations such as electrodialysis and electrodeionization. Custom unit operations have to be added in the form of user models implemented in various program or scripting languages e.g. Fortran or Python. Our objective is to develop a useful process simulator consisting of: (i) user-friendly graphic interface; (ii) set of solvers for differential algebraic equations; (iii) program for the calculation of dissociation equilibria including the database of chemical compounds and dissociation constants; and (iv) set of unit operations including electrodialysis, electrodeionization, reverse osmosis, different filtrations, simple mixers, splitters, tanks, heat exchangers, pumps, etc. [ABSTRACT FROM PUBLISHER]

The reverse electrodialysis (RED) process has been widely accepted as a viable and promising technology to produce electric energy from salinity difference (salinity gradient power e.g. using river water/seawater or seawater and concentrated brines). Recent R&D efforts demonstrated how an appropriate design of the RED unit and a suitable selection of process conditions may crucially enhance the process performance. With this regard, a process simulator was developed and validated with experimental data collected on a laboratory-scale unit, providing a new modelling tool for process optimisation. In this work, performed within the REAPower project (www.reapower.eu), a process simulator previously proposed by the same authors has been modified in order to predict the behaviour of a cross-flow RED unit. The model was then adopted to investigate the influence of the most important variables (i.e. solution properties and stack geometry) on the overall process performance. In particular, the use of different concentrations and flow rates for the feed streams has been considered, as well as different aspect ratios in asymmetric stacks. Moreover, the influence of the scaling-up a RED unit was investigated, starting from a 22 × 22 cm2100 cell pairs lab-stack, and simulating the performance of larger stacks up to a 44 × 88 cm2500 cell pairs unit. Finally, different scenarios are proposed for a prototype-scale RED plant, providing useful indications for the technology scale-up towards 1 kW of power production, relevant to the installation of a real prototype plant in Trapani (Italy) being the final objective of the R&D activities of the REAPower project. [ABSTRACT FROM PUBLISHER]

On industrial sites, the promotion of best practices to enable an efficient utilization of energy has emerged as one of the major point of focus. Among the different approaches existing to improve industrial processes, the exergy analysis, although limited to the academic world, has been shown to be a powerful tool for improving energy efficiency of thermal and chemical systems. The purpose of this paper is then to present the use of the ProSimPlus ® modelling and simulation environment as an exergy analysis computer-aided tool. Expressions implemented in the simulator for computing exergies in its various forms are presented. The adopted approach for calculating exergy efficiency in a systematic way is also exposed; it combines the fuel-product concepts to the transit exergy concept. ProsimPlus ® exergy module's capabilities are illustrated through the example of an ammonia production plant. [ABSTRACT FROM AUTHOR]

Reverse electrodialysis (SGP-RE or RED) represents a viable technology for the conversion of the salinity gradient power into electric power. A comprehensive model is proposed for the RED process using sea or brackish water and concentrated brine as feed solutions. The goals were (i) reliably describing the physical phenomena involved in the process and (ii) providing information for optimal equipment design. For such purposes, the model has been developed at two different scales of description: a lower scale for the repeating unit of the system (cell pair), and a higher scale for the entire equipment (stack). The model was implemented in a process simulator, validated against original experimental information and then used to investigate the influence of the main operating factors and on power output. Feed solutions of different salinities were also tested. A good matching was found between predictions and experiments for a wide range of inlet concentrations, flow rates and feed temperatures. Optimal feed conditions, for the adopted system geometry and membranes, have been found employing brackish water (0.08-0.1 M NaCl) as dilute and brine (4.5-5 M NaCl) as concentrate to generate the highest power density at 40 °C temperature. The model can be used to explore the full potential of the RED technology, especially for any investigation regarding the future scale-up of the process. [ABSTRACT FROM AUTHOR]

Methyl tertiary butyl ether (MTBE) is known as a promising substitute for tetra ethyl lead (TEL) in order to increase the octane number of gasoline. MTBE process, as many other processes, has two distinguished section, namely reaction section and separation section. In this paper we focus only on synthesis and optimization of separation section of this process. In order to achieve this objective, many possible flowsheets have been considered, among which, two alternatives are pointed out as optimum candidates. The second step involves determination of dominant design variables and their range of variation. Both selected flowsheets have been cost analyzed in their corresponding ranges of dominant design variables to determine plots of total annual cost (TAC). Knowing feed specifications at the entrance of separation section, the designer will be able to choose appropriate flowsheet and optimum conditions using the plots presented in this paper.

[Display omitted] • Potential of Bipolar Membrane ElectroDialysis was presented. • A fully integrated multi-scale model was developed. • The model was validated through comparison with original experimental data. • A sensitivity to design and operating variables was presented. • A preliminary techno-economic analysis was carried out. Bipolar membrane electrodialysis (BMED) is a technology combining solute and solvent dissociation to produce chemicals. In the recent decades, it has been typically studied for the production of valuable acid and base solutions from salt streams. Although many works have been devoted to the experimental investigation of BMED, only a few efforts have focused on its mathematical modelling. In the present work, a comprehensive process model based on a multi-scale approach with distributed parameters is presented for the first time. Five models related to four different dimensional scales were fully integrated to form a comprehensive tool. The integrated model was developed by using the process simulator gPROMS Model builder and was based on a semi-empirical approach combining high prediction accuracy and low computational demand. Once validated through a wide range of experimental data, the model capability was shown by carrying out a broad sensitivity analysis assessing the performance of the BMED technology for industrial-scale applications. Results showed how the performance of a BMED unit changes with both varying process conditions and the installed membrane area. Particularly, the non-ideal phenomena that reduce the produced NaOH concentration and increase the energy consumption were thoroughly investigated. Finally, this study demonstrated that a Levelized Cost Of Caustic Soda of about 280 € ton-1 NaOH can be obtained, thus making this technology a possible candidate for the industrial production of caustic soda from brines in the future. [ABSTRACT FROM AUTHOR]

Abstract: A new simulator to calculate the dose deposited in electron beam crosslinking processes of cables is presented, which implements original models to simulate accurately complex irradiation schemes like racetrack, figure of eight, and rotation. The package relies on the Monte Carlo simulation and includes tools to account for the three-dimensional geometry of the accelerators and of the conveyors, a unit to optimize the beam energy for a given process configuration, as well as an editor to visualize and quantify the dose distribution within the irradiated objects. The capabilities and the accuracy of the novel simulator are discussed on the basis of two realistic examples. [Copyright &y& Elsevier]

Abstract: A tracking simulator that runs in parallel with the plant and exactly simulates dynamic plant behavior has been developed. This tracking simulator is currently in the validation phase at a commercial petrochemical plant site. The future prediction function of the tracking simulator is expected to have a major impact on plant operations, improvement, and control design. The tracking simulator is strongly dependent on the physical model based on physical and chemical laws, and cannot simulate unknown phenomena in the plant. A hybrid model consisting of a physical model and a statistical model based on historical plant operation data was proposed. The estimation accuracy of the statistical model was improved using the virtual input from the tracking simulator. Although the Kalman filter technique is applied to conventional software sensors for quality estimation as a model updating function, deterioration of estimation accuracy is often seen with marked changes in plant behavior and the analyzers shut down. To resolve these issues, we applied Just-In-Time modeling based on the historical data modeling technique with the tracking simulator, and the plant model coverage of the tracking simulator was expanded for various processes. [Copyright &y& Elsevier]

Abstract: Using depth sensor cameras such as the Kinect and highly customizable software development frameworks in conjunction with artificial intelligence methodologies offer significant opportunities in a variety of applications, such as undergraduate science, technology, engineering, and math (STEM) education, professional or military training simulation, and individually-tailored cultural and media arts immersion. Designing a participatory educational experience where users are able to actively interface and experience given subject matter in a practical experiential manner can enhance the user''s ability to learn and retain presented information. Such natural gesture user interfaces have potential for broad application in disciplines ranging from systems engineering education to process simulation. This paper will discuss progress on the development of testing environments for interactive educational methods in conjunction with artificial intelligent systems that have the ability to adjust the educational user experience based on individual user identification. This will be achieved through depth sensor skeletal tracking, allowing experience adaptation based on the nature and effectiveness of the interactive educational experience. [Copyright &y& Elsevier]

Abstract: This paper presents a general methodology for exergy balance in chemical and thermal processes integrated in ProSimPlus® as a well-adapted process simulator for energy efficiency analysis. In this work, as well as using the general expressions for heat and work streams, the whole exergy balance is presented within only one software in order to fully automate exergy analysis. In addition, after exergy balance, the essential elements such as source of irreversibility for exergy analysis are presented to help the user for modifications on either process or utility system. The applicability of the proposed methodology in ProSimPlus® is shown through a simple scheme of Natural Gas Liquids (NGL) recovery process and its steam utility system. The methodology does not only provide the user with necessary exergetic criteria to pinpoint the source of exergy losses, it also helps the user to find the way to reduce the exergy losses. These features of the proposed exergy calculator make it preferable for its implementation in ProSimPlus® to define the most realistic and profitable retrofit projects on the existing chemical and thermal plants. [Copyright &y& Elsevier]

The optimal design and operation of energy systems are critical tasks to sustain economic growth and reduce environmental impacts. In this context, this paper presents the mathematical optimization and exergoeconomic improvement of an energy system modeled in a professional thermodynamic process simulator using the direct search method of Powell and an evolutionary stochastic method of the genetic type. In the mathematical optimization approach, as usual, the minimum system total cost is sought by simultaneous manipulation of the entire set of decision variables. At times, the global minimum is not exactly reached. On the other hand, the exergoeconomic improvement methodology determines, based on the exergetic and economic analyses of the system at each iteration, a subset of most significant decision variables which should be modified for each component, and applies an optimization algorithm to these variables only. In the improvement process an appreciable reduction, not strict minimization, of the system total cost is sought. The energy system analyzed is a 24-component cogeneration plant, denoted CP-24, which is representative of complex industrial installations. As opposed to a conventional optimization approach, the integrated optimization with a professional process simulator eliminates the necessity to implement explicitly the constraints associated with the physical and thermodynamic models of the system. Therefore, the integrated strategy can tackle large systems, and ought to be more easily applied by practicing energy engineers. The results obtained permit, first, to compare the performance of mathematical optimization algorithms belonging to different classes, and, second, to evaluate the effectiveness of the iterative exergoeconomic improvement methodology working with these algorithms. [ABSTRACT FROM AUTHOR]

Nowadays, the use of computational tools in classroom is quite habitual and important by making the learning process more constructive and dynamic. The objective of this work is to introduce a support didactic material for use in computational classes of Chemical Reaction Engineering. The development of the work is based on a direct implementation of examples of the well-known Fogler's textbook 'Elements of Chemical Reaction Engineering' in an equation-based dynamic simulator: EMSO. The problems were implemented in a way to preserve the structure of the problem as described in the textbook. The results are illustrated by graph plots generated in the simulator, allowing comparisons with the results presented in the textbook and detailed analyses for effects of variables in the problem. The problems are easily modified, allowing the student to analyze several possibilities, changing equations and values of variables, for example, and observing the results. © 2009 Wiley Periodicals, Inc. Comput Appl Eng Educ 18: 607-618, 2010; View this article online at ; DOI 10.1002/cae.20255 [ABSTRACT FROM AUTHOR]

Abstract: In this paper, the application of an iterative exergoeconomic methodology for improvement of thermal systems to a complex combined-cycle cogeneration plant is presented. The methodology integrates exergoeconomics with a professional process simulator, and represents an alternative to conventional mathematical optimization techniques, because it reduces substantially the number of variables to be considered in the improvement process. By exploiting the computational power of a simulator, the integrated approach permits the optimization routine to ignore the variables associated with the thermodynamic equations, and thus to deal only with the economic equations and objective function. In addition, the methodology combines recent available exergoeconomic techniques with qualitative and quantitative criteria to identify only those decision variables, which matter for the improvement of the system. To demonstrate the strengths of the methodology, it is here applied to a 24-component cogeneration plant, which requires O(103) variables for its simulation. The results which are obtained, are compared to those reached using a conventional mathematical optimization procedure, also coupled to the process simulator. It is shown that, for engineering purposes, improvement of the system is often more cost effective and less time consuming than optimization of the system. [Copyright &y& Elsevier]

Abstract: In this paper, rigorous modelling of reactive separations is considered. Focus is set to gas/vapour–liquid systems, namely reactive distillation and reactive stripping. The paper describes the modelling framework and the process simulator PROFILER developed within the European research project Intelligent Column Internals for Reactive Separations (INTINT). The application is illustrated by two heterogeneously catalysed esterification processes: the synthesis of ethyl acetate from ethanol and acetic acid via reactive distillation and the synthesis of octyl hexanoate from octanol and hexanoic acid via reactive stripping. For both processes, the simulation results are in satisfactory agreement with the experimental data. A comparison of different model complexities is presented. [Copyright &y& Elsevier]

In this paper, we present the development and automated implementation of an iterative methodology for exergoeconomic improvement of thermal systems integrated with a process simulator, so as to be applicable to real, complex plants. The methodology combines recent available exergoeconomic techniques with new qualitative and quantitative criteria for the following tasks: (i) identification of decision variables that affect system total cost and exergetic efficiency; (ii) hierarchical classification of components; (iii) identification of predominant terms in the component total cost; and (iv) choice of main decision variables in the iterative process. To show the strengths and potential advantages of the proposed methodology, it is here applied to the benchmark CGAM cogeneration system. The results obtained are presented and discussed in detail and are compared to those reached using a mathematical optimization procedure. [Copyright &y& Elsevier]

A new computational procedure is presented to attain convergent solutions for multistage, multicomponent separation problems for non-ideal fluid mixture systems when starting from very crude initial assumptions. The procedure incorporates a gradual non-ideality enhancing method into the Ishii–Otto pseudo-binary-mixture (PBM) algorithm [Comput. Chem. Eng. 25 (2001) 1285]. Shifting K-values from ideal to non-ideal in the course of iterative calculations gradually approaches the correct solution to a problem. The domain of convergence with the proposed procedure is greatly extended and very difficult problems where both non-ideality of fluid systems and very rough assumptions for initial variables are involved can be solved with the same ease as one solves problems with ideal physical properties. An innovative method, made possible because of the PBM concept, to simplify the Jacobian matrix and significantly reduce the computing time for evaluation of the Jacobian is also presented. The effectiveness of the methods is illustrated with example problems. [Copyright &y& Elsevier]

An integrated process simulator with a capability to predict spatial and temporal evolution of temperature, microstructure, and mechanical properties in cold rolled coils during the batch annealing process has been developed. The model predictions have been validated using results obtained with large-scale industrial batch annealing operations. Potential applications of such a simulator include product development, efficient process optimization, and online control resulting in benefits in terms of overall cost reduction, energy reduction, productivity enhancement, and quality improvement. In this article, the salient features as well as the potential applications of this integrated Batch Annealing Furnace simulator have been presented. Furthermore, the utility of this simulator in designing the thermal cycle and optimizing the coil dimensions for improving furnace productivity has been demonstrated. [ABSTRACT FROM AUTHOR]