Chemical Engineering Process Design Research Articles

Net zero roadmap modelling for sustainable dairy manufacturing and distribution

Energy-derived carbon emissions from dairy manufacturing and distribution are significant. Meeting a net zero carbon target is a global priority, and to that end the dairy industry is engaging an emission-reduction strategy. Modelling tools that can predict energy consumption and related carbon-emissions can aid decision-making towards energy transitioning. This study presents an energy consumption model for dairy skimmed milk and cream manufacturing and distribution, which has been developed following a mechanistic modelling approach. This approach integrates chemical engineering process design, heat exchange principles, and empirical modelling to simulate energy consumption for each individual supply chain component, sequence-by-sequence. The model offers simulation flexibility, allowing the projection of the product’s embodied energy and carbon-emissions under diverse manufacturing and distribution scenarios. To investigate the model capabilities, scenario analysis was performed for 12 different scenarios. These scenarios resulted by testing the use of three fuel types for the heating requirements in manufacturing (oil, natural gas and hydrogen), two categories of refrigerated vehicles (diesel and electric), and two different distribution infrastructures (centralised and decentralised). The evaluated skimmed milk product-embodied energy ranged between 309 and 869 kJ/L. The scenarios were also simulated towards 2050 using the UK projections for electricity’s carbon conversion factor to predict the anticipated carbon-emission reductions. These 2050 projections allowed for roadmap planning towards decarbonising energy for skimmed milk and cream manufacturing and distribution, with outcomes demonstrating up to 90.2% carbon-emission reductions by 2050. The developed model can support safe decision-making and assist the dairy industry in meeting the net zero carbon target.

A review of the contributions of P. Raj Bishnoi to chemical engineering

AbstractThis paper provides a review of Professor Bishnoi's research contributions in the broad discipline of chemical engineering. Prof. Bishnoi has been a dedicated mentor, collaborator, innovator, and outstanding researcher. He has had a most productive and illustrious career, spanning more than four decades in both academia and industry. He is among the top 50 most‐published authors of the The Canadian Journal of Chemical Engineering. He initiated a most successful and renowned research group at the University of Calgary, which was dedicated to the understanding of thermodynamics and kinetics related to the formation and decomposition of gas hydrates as well as the chemical engineering process design and simulation. As a tribute to Prof. Bishnoi's numerous scientific and engineering contributions and innovations, this review highlights his academic and research accomplishments, which included the training of several doctoral degree students, master's degree students, and postdoctoral scholars and research associates. In this paper, we have divided Prof. Bishnoi's research contributions into three broad areas, namely, chemical thermodynamics of hydrocarbon systems, process development and simulation, and thermodynamics and kinetics of the formation and decomposition of gas hydrates.

Study on the Intensification of Reaction Kinetics and Reactive Distillation for the Esterification of N-Butyl Acetate Using [HSO3-BMIM][HSO4] as a High-Efficiency Ionic Liquid Catalyst

An ionic liquid (IL) catalyst 1-sulfobutyl-3-methylimidazolium hydrogen sulfate, [HSO3-BMIM][HSO4], was used to produce n-butyl acetate (BuAc) via esterification. A novel modified nonideal homogeneous kinetic model was developed by self-catalysis theory. A new reactive distillation (RD) process using [HSO3-BMIM][HSO4] to produce BuAc was intensified using Aspen simulation taking advantage of phase splitting to increase the ester purity. Various design parameters like reactant feed location, reflux ratio, reactant feed molar ratio, flow ratio of products to materials, and condenser pressure were optimized. Fitting results indicated that modified models presented exact prediction results for the [HSO3-BMIM][HSO4]-catalyzed esterification compared with the unmodified model because the former introduced a revisional term for the self-catalysis of HAc, which revealed the mechanism of self-catalysis and interaction between ILs and reactants. The BuAc purity was increased from 91.05 to 95.02 wt % by the RD process intensification. [HSO3-BMIM][HSO4] showed a higher acid conversion (75%) than commercial ILs and resins. The ester yield was higher when using [HSO3-BMIM][HSO4] as the catalyst than resin A (80.89 wt %) in the intensified RD process. This research provides a novel modified method for the kinetic model in the IL-catalyzed reaction where the modified model exhibited a high accuracy and is useful for improving the production efficiency and controlling the catalyst dosage in the chemical engineering process design. The intensified RD process shows a flexible design for IL application, which is helpful for designing industrial scale-up.

Simulation of a Process Plant for the Production of Propylene

The simulation of a process plant for the production of propylene has been considered in this work. The reactor used for this research was a Continuous Stirred Tank Reactor (CSTR) which was deliberately picked because of the advantage of good temperature and reaction control. Other equipment includes a compressor, conversion reactor, cooler and splitter. Sizing was done for all equipment but detailed design was carried out for the CSTR since it’s the heart of the process plant. The principle of conservation of mass was applied for the development of basic design performance equations for the volume, the height, space time, space velocity and heat generated per unit volume at 90% conversion of propane to propylene. Aspen Hysys which is known for its reliability in chemical engineering process design was used to simulate the process plant and was used for all calculations and sizing of process equipment. The values of the functional and dimensional parameters which are required for the sizing of the reactor were obtained after the simulation with the following results: volume of reactor 37 m3, height of reactor 7.4 m, space time 0.028 hr, space velocity 59 hr-1 and heat load 78 kj/m3.

Heat Capacities and Thermodynamic Properties of Hungchaoite and Mcallisterite.

The heat capacities on two minerals of hungchaoite (MgB4O7·9H2O, Hu) and mcallisterite (MgB6O10·7.5H2O, Mc) have been measured with a precision calorimeter at temperatures ranging from 306.15 to 355.15 K, experimentally. It was found that there are no phase transition and thermal anomalies, and the molar heat capacities against temperature for the minerals of hungchaoite and mcallisterite were fitted as and , respectively. The molar heat capacities and thermodynamic functions of (HT-H298.15), (ST-S298.15), and (GT-G298.15) at intervals of 1 K for the two minerals were obtained for the first time. These results are significant in order to understand the thermodynamic properties of those minerals existing in nature salt lakes, as well as applying them to the chemical engineering process design.

Quantitative Structure–Property Relationship Model for Hydrocarbon Liquid Viscosity Prediction

The liquid viscosity of hydrocarbon compounds is essential in the chemical engineering process design and optimization. In this paper, we developed a quantitative structure–property relationship (QSPR) model to predict the hydrocarbon viscosity at different temperatures from the chemical structure. We collected viscosity data at different temperatures of 261 hydrocarbon compounds (C3–C64), covering n-paraffins, isoparaffins, olefins, alkynes, monocyclic and polycyclic cycloalkanes, and aromatics. We regressed the experimental data using an improved Andrade equation at first. Hydrocarbon viscosity versus temperature curves were characterized by only two parameters (named B and T0). The QSPR model was then built to capture the complex dependence of the Andrade equation parameters upon the chemical structures. A total of 36 key chemical features (including 15 basic groups, 20 united groups, and molecular weights) were manually selected through the trial-and-error process. An artificial neural network was tra...

Genetic programming (GP) approach for prediction of supercritical CO2 thermal conductivity

Gas thermal conductivity is one of the thermophysical properties that inevitably enters into mathematical models of real systems used in the design of chemical engineering processes or in the gas industry. In this study, via implementing a powerful and newly applied equation generator algorithm known as, genetic programming (GP) mathematical strategy, a novel correlation for estimation of supercritical CO2 thermal conductivity is established. The proposed correlation is developed and validated based on a comprehensive databank of 752 thermal conductivity datasets from open literature. By using various statistical quality measures, the result of the proposed GP model was compared with commonly used literature models. As a result, the proposed GP model gives the best fit and satisfactory agreement with the target data with an average absolute relative error of 2.31% and R2=0.997. A parametric sensitivity analysis showed that pressure and density of the CO2 gas stream have considerable impact on the thermal conductivity at supercritical condition. The results of this study can be of enormous practical worth for scientist and expertise in order to efficiently compute the thermal conductivity in any supercritical industry involving CO2.

Gravitational Search, Monkey, and Krill Herd Swarm Algorithms for Phase Stability, Phase Equilibrium, and Chemical Equilibrium Problems

Phase equilibrium calculations (PECs) and phase stability (PS) analysis of reactive and nonreactive systems problems are important for the simulation and design of chemical engineering processes. These problems, which are challenging, multi-variable, and non-convex, require optimization techniques that are both efficient and effective in finding the solution. Stochastic global optimization algorithms, especially swarm algorithms, are promising tools for such problems. In this study, monkey algorithm (MA), gravitational search algorithm (GSA), and Krill Herd algorithm (KHA) were used to solve PS, phase equilibrium, and chemical equilibrium problems. We have also studied the effect of adding a local optimizer at the end of the stochastic optimizer run. The results were compared to determine the strengths and weaknesses of each algorithm. When a local optimizer was used, MA was found to be a reliable algorithm in solving the problems. GSA had relatively the least numerical effort for all problems among the three algorithms but with low reliability. KHA was more reliable than other two algorithms without the use of a local optimizer. The performance of GSA, MA, and KHA was compared with firefly algorithm and cuckoo search (CS). In summary, this study found that CS algorithm was more reliable than the newly tested algorithms. Nevertheless, MA and GSA algorithms, when combined with a local optimizer, solve the thermodynamic problems as reliably and efficiently as CS.

Application of process simulators in chemical engineering process design -natural gas separation plant case study

Software for chemical processes modeling and simulation, in the past few decades, play an important role in the development of chemical-process industry with their growing capabilities and wide range of application. Usage of process simulators in Serbia for the process design is very limited. This paper gives a brief overview of the numerous process simulators that are used in the chemical-process industry today. The conceptual design is responsible for most of the investment costs in chemical process industry. Importance of precise design on preliminary level is obvious. Wrong decisions made at the conceptual level could be carried out throughout the chain in process design to the detailed design procedures and procurement of equipment. Although preliminary design phase comprises only about 2% of the total cost of the project, it contributes significantly to the reduction of cost of the project by more than 30%. Therefore process simulators play important role in elimination of unnecessary errors in basic process design. Here is also shown a case study of parallel process simulated in different process simulators which tests the results, the reliability and usefulness of these programs in solving specific engineering tasks. Comparison of given simulation results confirm that the modern process simulators are at high level of confidence, no matter they are based on different models, equations, methods, operations, interfaces or data bases. Usage of software speeds up the arrival of optimized solution during the design and the operational procedures. Therefore software have significant impact on reducing time of pre-project phase such as research, conceptual design, and proving project abilities. It?s development lead to faster commercialization of industrial ideas.

Chemical Process Engineering Principles of Combustion Turbines

The lower prices and wider availability of natural gas make it important that chemical engineers become familiar with natural-gas processing and applications. One important use is the generation of power by burning natural gas in a combustion turbine. Traditional systems use air for the oxygen source, but the use of high-purity oxygen with stack gas recirculation is an alternative when sequestration of carbon dioxide is desired. The limiting design parameter in a combustion-turbine system is a maximum turbine inlet (combustor) temperature because of metallurgical constraints. In air-fired systems, enough air must be used to keep below this limit. In oxygen-fired systems, enough CO2-rich stack gas must be recycled to keep below this limit. The purpose of this paper is to review the chemical engineering process design principles involved in setting up combustion-turbine systems.

Prediction of solid polycyclic aromatic hydrocarbons solubility in water, with the NRTL-PR model

The accurate prediction of high pressure phase equilibria is crucial for the development and the design of chemical engineering processes. Among them the modeling of complex systems, such as petroleum fluids with water, has become more and more important with the exploitation of reservoirs in extreme conditions. The aim of this work is to explore the capability of the NRTL-PR model to predict the solubility of solid polycyclic aromatic hydrocarbons in water. For this purpose, we first validate our methodology for fluid phase equilibria predictions of aromatic hydrocarbons and gas (CO2, C2H6) mixtures. Finally, we consider the prediction of the solid solubility of PAH in water, by fitting group parameters either only on SLE data or on both LLE and SLE data of aromatic hydrocarbon–water binary systems.

3D printing for CO2 capture and chemical engineering design

Three-dimensional printing is a form of additive manufacturing that allows the fabrication of items directly from digital files, allowing the user to virtually produce any solid object on demand. Three-dimensional printing is already a frequently discussed topic in the mainstream media and is beginning to find a number of applications in research laboratories. The authors have recognized that 3D printing can have many roles in the design of chemical engineering processes as a means of fabricating parts or perhaps entire unit operations. The authors foresee many opportunities for 3D printing as a means of producing novel and advanced components and entire devices for gas treating. Gas treating (i.e. the removal of one or more contaminants from a gaseous mixture) plays a crucial role in many existing and emerging energy-related processes including natural gas sweetening, flue gas desulfurization and pre- and post-combustion carbon dioxide capture. These processes are typically carried out in absorption columns containing trays or packing that provide interfaces for gas–liquid contacting. New devices such as membrane contactors are also emerging as alternative mechanisms for achieving separation of gases with potential cost and energy-saving benefits derived from having smaller footprints, being of lighter weight and having much larger interfacial areas. Yet in all cases, the design, cost and ability to optimize gas–liquid contactors may be limited by conventional manufacturing techniques. In this respect, 3D printing could be a mechanism by which to achieve improvements on existing technologies and more rapidly deploy novel devices. Here, the authors describe their efforts to date in the application of 3D printing for the fabrication of components and devices for carbon dioxide–capture applications and provide perspective on design strategies, opportunities and challenges.

Design Process Modeling in Chemical Engineering

In this contribution, a methodology for modeling, improving, and implementing design processes in chemical engineering is presented. The methodology comprises a semiformal modeling language for design processes, complemented by a modeling procedure describing the efficient creation of design process models. The methodology inherits from some approaches developed in the domain of business process reengineering and workflow management, but has been extended considerably to meet the requirements imposed by the creative character of design processes. Two case studies demonstrating the successful application of the procedure for design processes in different industrial settings are discussed.

Integrated design and control for robust performance: Application to an MSMPR crystallizer

The interplay of different types of performance constraints in an integrated design and control problem is studied by means of a case study. This integrated problem is based on a recent method for robust process design [M. Mönnigmann, W. Marquardt, Normal vectors on manifolds of critical points for parametric robustness of equilibrium solutions of ODE systems, J. Nonlinear Sci. 12 (2002) 85–112; M. Mönnigmann, W. Marquardt, Steady state process optimization with guaranteed robust stability and feasibility, AIChE J. 49 (12) (2003) 3110–3126; M. Mönnigmann, W. Marquardt, Steady state process optimization with guaranteed robust stability and flexibility: application to HDA reaction section, Ind. Eng. Chem. Res. 44 (2005) 2737–2753; W. Marquardt, M. Mönnigmann, Constructive nonlinear dynamics in process systems engineering, Comput. Chem. Eng. 29 (2005) 1265–1275; M. Mönnigmann, Constructive nonlinear dynamics methods for the design of chemical engineering processes, Ph.D. Thesis, RWTH Aachen University, 2003]. The design is found by means of a steady-state optimization problem accounting for process economics and performance requirements. In particular, the latter are represented by constraints which guarantee a user-specified performance of the design in spite of parametric uncertainties. For the first time, two types of dynamic performance constraints are used simultaneously within the adopted framework. These are constraints on time-domain performance indicators as well as on the asymptotic dynamic process behavior. Furthermore, the effect of uncertainty in both, design and model parameters, is accounted for. A key strength of the suggested framework is the direct quantification of the trade-offs between economics and dynamic performance requirements for a selection of uncertainty scenarios. A series of different integrated design and control problems are formulated and solved for a continuous mixed-suspension mixed-product removal (MSMPR) crystallizer. The process exhibits a complex nonlinear behavior and represents a challenging example. The results of the case study allow an in depth understanding of the interactions of design and control for the underlying process.

A management system for dynamic and interorganizational design processes in chemical engineering

Design processes in chemical engineering are hard to manage. The design process is highly creative, many design alternatives are explored, and both unexpected and planned feedback occurs frequently. Thus, it is inherently difficult to manage the workflow in design processes, i.e., to coordinate the effort of experts working on tasks such as creation of flow diagrams, steady-state and dynamic simulations, etc. Conventional project and workflow management systems support the management of design processes only to a limited extent. In contrast, the management system AHEAD is designed specifically for dynamic design processes. In addition, AHEAD supports the management of interorganizational design processes. A subprocess may be delegated to a contractor, which receives information only about those parts of the overall process that are relevant for the contract. The management systems of the client and the contractor are coupled at run time such that both systems maintain up-to-date state information. The contract may be changed at any time according to the rules of a pre-defined change protocol. To validate this approach to the management of dynamic and interorganizational design processes, the AHEAD system has been applied to a comprehensive case study, namely the conceptual design and basic engineering of a chemical plant for producing polyamide 6.

Tool support for the management of design processes in chemical engineering

Design processes in chemical engineering are hard to support. In particular, this applies to conceptual design and basic engineering, in which the fundamental decisions concerning the plant design are performed. The design process is highly creative, many design alternatives are explored, and both unexpected and planned feedback occurs frequently. As a consequence, it is inherently difficult to manage design processes, i.e. to coordinate the effort of experts working on tasks such as creation of flow diagrams, steady-state and dynamic simulations, etc. On the other hand, proper management is crucial because of the large economic impact of the performed design decisions. We present a management system which takes the difficulties mentioned above into account by supporting the coordination of dynamic design processes. The management system equally covers products, activities, and resources, and their mutual relationships. With respect to coverage and integration, and with respect to the dynamics of design processes, the functionality of the management system goes considerably beyond commercial project, document, and workflow management systems.

Wärmeintegration als Element der Verfahrensbearbeitung

Thermal Integration, an Element in Design of Chemical Engineering Processes. Thermal integration is an important element in the planning and design of chemical engineering processes. This is especially true when energy optimisation is embedded in a software environment permitting unimpeded data transfer and exchange between the design elements can take place in a straightforward and intelligent manner, i.e. in a manner supporting the user. These advantages are demonstrated for a selected process. Expert systems which can extract data relevant for thermal integration from the process data and hence generate an entry data set for subsequent processing in a thermal integration program have proved to be particularly advantageous. In addition, the process engineer also has the possibility of modifying the data manually and undertaking appropriate adaptions and corrections. Subsequent analysis of thermal integration (e.g. by the Pinch method) often suggests improvements extending beyond the pure thermal regime and lead to changes in the process flow chart.

Integrated Computing System of Laboratory Experiment for a Automation of Research Modeling and Design of Chemical Engineering Processes

Abstract The paper concerns integrated computing system with distributed data bases of laboratory experiment for automation of research, modeling and optimal design of chemical engineering processes. The computation methods of kinetic experiment for establishing the probable mechanism and composing kinetic models of complex reaction has been discussed The selection of accurate, single-valued and complete kinetic models allows to find theoretically optimum temperature distribution for substantiation of reactor type. Identification procedures of the mathematical models in static and dynamics of catalytic reactors have been suggested and the calculations of concentration and temperature fields were made on these bases stability conditions of stationary slates and transient processes have been determined.The packages of programmed modules permitting the realization of algorithms modeling and optimum calculation of catalytic processes in the framework of CAD in terms data base have been developed. The results that obtained from the mathematical models and optimum parameters and control design of new oxidation-dchydrogenation processes using this systems will be presented in the conclusion.

Mathematical programming tools for chemical engineering process design synthesis

The objective of this paper is to review different optimization techniques used in chemical process synthesis. The paper first defines the process synthesis problem as a mixed-integer programming problem and then discusses the three approaches which have been used to solve it. In the discrete approach, where the operating conditions of unit operations are fixed, combined heuristic and algorithmic procedures are promising tools. In the continuous approach, the synthesis problem is a nonlinear programming problem, where the design and structural variables are optimized simultaneously. Since efficient large-scale nonlinear programming codes are now available, this approach will be a great success. A recent alternative consists in merging the two previous approaches to implement large-scale mixed-integer nonlinear programming codes. This method will have wide applications in complex chemical process synthesis.

Measuring oxygen diffusion coefficients with polarographic oxygen electrodes: I. Electrolyte solutions

Biotechnology and BioengineeringVolume 27, Issue 10 p. 1495-1499 Communications to the EditorFree Access Measuring oxygen diffusion coefficients with polarographic oxygen electrodes: I. Electrolyte solutions Lu-Kwang Ju, Lu-Kwang Ju Department of Chemical Engineering, State University of New York at Buffalo, Buffalo, New York 14260Search for more papers by this authorChester S. Ho, Corresponding Author Chester S. Ho Department of Chemical Engineering, State University of New York at Buffalo, Buffalo, New York 14260Department of Chemical Engineering, State University of New York at Buffalo, Buffalo, New York 14260Search for more papers by this author Lu-Kwang Ju, Lu-Kwang Ju Department of Chemical Engineering, State University of New York at Buffalo, Buffalo, New York 14260Search for more papers by this authorChester S. Ho, Corresponding Author Chester S. Ho Department of Chemical Engineering, State University of New York at Buffalo, Buffalo, New York 14260Department of Chemical Engineering, State University of New York at Buffalo, Buffalo, New York 14260Search for more papers by this author First published: October 1985 https://doi.org/10.1002/bit.260271015Citations: 35AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Citing Literature Volume27, Issue10October 1985Pages 1495-1499 ReferencesRelatedInformation