Integrating expanders into heat exchanger networks above ambient temperature

The integration of expanders into heat exchanger networks (HENs) is a complex task since both heat and work are involved. In addition, the role of streams (as hot or cold), the utility demand, and the location of pinch points may change. With certain well‐defined conditions, four theorems are proposed for the integration of expanders into HENs above ambient temperature with the objective of minimizing exergy consumption. A straightforward graphical methodology for above ambient HENs design including expanders is developed on the basis of Grand Composite Curves (GCCs). It is concluded that to achieve a design with minimum exergy consumption, stream splitting may be applied and expansion should be done at pinch temperatures, hot utility temperature, or ambient temperature. In the majority of cases, however, and in line with the concept of Appropriate Placement from Pinch Analysis, expansion at pinch temperatures gives the minimum exergy consumption. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3404–3422, 2015     

Integrating compressors into heat exchanger networks above ambient temperature

Heat from compression processes is normally wasted to cooling water due to its low temperature or concerns about operability. The recoverable amount of heat can be enhanced by increasing the operating temperature of compressors. However, the compression work also increases under this condition. The integration of compressors into heat exchanger networks (HENs) is complex since both heat and work are involved, and the role of streams (as hot or cold streams), the utility demand, and the location of pinch points may change. A systematic graphical design procedure for above ambient HEN design including compressors was presented. The objective is to minimize exergy consumption to balance the complex heat‐work trade‐offs involved. Four theorems are proposed as the basis of the design procedure with certain well‐defined assumptions. It is found that the compression should be performed at pinch or ambient temperatures to achieve minimum exergy consumption. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3770–3785, 2015     

Systematic integrated process design and control of binary element reactive distillation processes

Integrated process design and control of reactive distillation processes is considered through a computer‐aided framework. First, a set of simple design methods for reactive distillation column (RDC) that are similar in concept to nonreactive distillation design methods are extended to design‐control of RDCs. These methods are based on the element concept where the reacting system of compounds is represented as elements. When only two elements are needed to represent the reacting system of more than two compounds, a binary element system is identified. It is shown that the same design‐control principles that apply to a nonreacting binary system of compounds are also valid for a reactive binary system of elements for distillation columns. Application of this framework shows that designing the reactive distillation process at the maximum driving force results in a feasible and reliable design of the process as well as the controller structure. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3137–3154, 2016     

Control structure selection based on economics: Generalization of the back‐off methodology

The back‐off methodology has been extensively developed and refined in the last 20 years and offers a systematic tool for solving the simultaneous design and control problem. Previous work has been based on linear process and control models that ensure quick determination of the optimal solution at the expense of potential loss in the accuracy due to nonlinear process characteristics. In this work a new formulation is proposed where use is made of a nonlinear process model that ensures improved accuracy and also offers an improved opportunity for the simultaneous consideration of process design and process control. Two case studies are studied in detail and demonstrate the advantages of the new formulation. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3056–3064, 2016     

On identification of well‐conditioned nonlinear systems: Application to economic model predictive control of nonlinear processes

The focus of this work is on economic model predictive control (EMPC) that utilizes well‐conditioned polynomial nonlinear state‐space (PNLSS) models for processes with nonlinear dynamics. Specifically, the article initially addresses the development of a nonlinear system identification technique for a broad class of nonlinear processes which leads to the construction of PNLSS dynamic models which are well‐conditioned over a broad region of process operation in the sense that they can be correctly integrated in real‐time using explicit numerical integration methods via time steps that are significantly larger than the ones required by nonlinear state‐space models identified via existing techniques. Working within the framework of PNLSS models, additional constraints are imposed in the identification procedure to ensure well‐conditioning of the identified nonlinear dynamic models. This development is key because it enables the design of Lyapunov‐based EMPC (LEMPC) systems for nonlinear processes using the well‐conditioned nonlinear models that can be readily implemented in real‐time as the computational burden required to compute the control actions within the process sampling period is reduced. A stability analysis for this LEMPC design is provided that guarantees closed‐loop stability of a process under certain conditions when an LEMPC based on a nonlinear empirical model is used. Finally, a classical chemical reactor example demonstrates both the system identification and LEMPC design techniques, and the significant advantages in terms of computation time reduction in LEMPC calculations when using the nonlinear empirical model. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3353–3373, 2015     

Process synthesis for cascade refrigeration system based on exergy analysis

Refrigeration system holds an important role in chemical/petrochemical processes. The traditional cascade refrigeration system (CRS) used in ethylene plants contains multiple refrigerants working at multiple temperature/pressure levels. In this study, a general methodology is developed for the optimal process synthesis of a CRS based on exergy analysis. This procedure involves four stages: (1) refrigeration system exergetic analysis; (2) optimization model development for simultaneous synthesis of refrigeration system and heat exchanger network (HEN); (3) HEN configuration; and (4) final solution validation. The exergy–temperature chart is used to comprehensively analyze a CRS. A mathematical model is presented to minimize total compressor shaft work of the HEN‐considered CRS, where multiple recycling loops satisfying all cooling/heating demands are simultaneously addressed. The optimal solution is examined by rigorous simulations to verify its feasibility and consistency. The efficacy of the developed methodology is demonstrated by a case study of a propylene CRS in an ethylene plant. © 2015 American Institute of Chemical Engineers AIChE J, 61: 2471–2488, 2015     

Optimization‐based support for process design under uncertainty: A case study

The use of two‐stage stochastic optimization for the support of the solution of process design problems in the early phase of process development where the different potential elements of the production process can only be described with significant uncertainty is discussed. The first stage variables are the design decisions which are fixed after the process has been built, while the second stage variables are the operational parameters which can be adapted to the realization of the uncertainties. The application of the approach to the design of a hydroformylation process in a thermomorphic solvent system is demonstrated. The proposed designs which are computed using the software framework FSOpt are analyzed and compared using different graphic representations which provide insight into what the most important design decisions are. Finally, the experience with the proposed formulation and solution techniques and point out where further advances are needed is reviewed. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3404–3419, 2016     

Synthesis of heat exchanger networks at subambient conditions with compression and expansion of process streams

This article presents an optimization formulation for the synthesis of heat exchanger networks where pressure levels of process streams can be adjusted to improve heat integration. Especially important at subambient conditions, this allows for the interconversion of work, temperature, and pressure‐based exergy and leads to reduced usage of expensive cold utility. Furthermore, stream temperatures and pressures are tuned for close tracking of the composite curves yielding increased exergy efficiency. The formulation is showcased on a simple example and applied to a case study drawn from the design of an offshore natural gas liquefaction process. Aided by the optimization, it is demonstrated how the process can extract exergy from liquid nitrogen and carbon dioxide streams to support the liquefaction of a natural gas stream without additional utilities. This process is part of a liquefied energy chain, which, supplies natural gas for power generation while facilitating carbon dioxide sequestration. © 2010 American Institute of Chemical Engineers AIChE J, 2011     

Exergy as a tool for measuring process intensification in chemical engineering

Exergy is defined as the maximum shaft work that can be done in a process to bring the system into equilibrium with the environment. Thus, exergy analyses are the first step to understand where the weak points of processes are. It considers intrinsically the quality of energy: when energy loses its quality, exergy is destroyed. In addition, optimization of processes aiming at the minimization of exergy destruction can be done as a function of the topology and physical characteristics of the system, such as finite dimensions, shapes, materials, finite speeds, and finite‐time intervals of operation, establishing a direct relationship between exergy and process intensification. However, the emphasis on exergy in chemical engineering is still very poor compared with other fields, in spite of being one of the areas in which more exergy is destroyed due to reaction and separation . This paper gives an overview of the current application of exergy analyses in chemical engineering, showing the main fields in which exergy studies are performed and focusing the attention on two critical points of action: separation technologies (distillation and membrane technology) and CO₂ capture. New research trends in chemical engineering using exergy as a tool for process intensification are highlighted. © 2013 Society of Chemical Industry     

Design of multi‐actor distributed processing systems: A game‐theoretical approach

The manufacturing of a final product could be the result of a value chain involving several processing plants distributed across several distinct owners; a feature that may prevent the application of classical process design approaches that depend on a centralized treatment of the complete processing network. In this article we propose and develop a game‐theoretical framework and specific methodologies, which allow the optimal design of distributed processing systems, through the decentralized strategies of independent actors. The resulting process design corresponds to a Nash Equilibrium point among the interacting actors. Its optimality and the justification of the independent strategies that led to it, are theoretically based on (and constrained by) the properties of the 2‐level Lagrangian approach. The article also discusses the use of penalty‐term approaches, which can extend the applicability of the proposed framework and design methodologies to problems for which the underlying convexity assumptions of the 2‐level Lagrangian approach may not be possible to ascertain. A series of case studies illustrate the application of the proposed ideas to distributed processing networks of various structures. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3369–3391, 2016     

Fault detection and isolation analysis and design for solution copolymerization of MMA and VAc process

The problem of detecting and isolating distinguishable actuator and sensor faults in the solution copolymerization of methyl methacrylate and vinyl acetate monomers are considered in this work. To this end, first state estimates are generated using a bank of high‐gain observers, and nonlinear fault detection and isolation (FDI) residuals are defined. The process dynamics are further analyzed to categorize fault scenarios as distinguishable and indistinguishable, and the necessary and sufficient conditions for the classification are presented. Subsequently, filters are designed that enable FDI for the distinguishable fault scenarios, with the advantage of detecting and confining possible locations for indistinguishable faults. The FDI filters are implemented on the copolymerization process, and the results compared with a linear model based filter design. © 2015 American Institute of Chemical Engineers AIChE J, 62: 1054–1064, 2016     

Mathematical simulation of wet spinning coagulation process: Dynamic modeling and numerical results

A dynamic model of polymer wet spinning coagulation process is proposed in this article. The model is based on the double diffusion phenomenon, phase separation process, continuity balance, and momentum balance of the entire coagulation process. The uniqueness of the model lies in its dynamic feature. The model can simulate the system's dynamic response to variations in system inputs/parameters. Steady‐state system solutions can also be produced as the long‐time solutions of the dynamic model; a settling time can be observed at the same time. This paper employs a computationally efficient method of lines numerical algorithm for solving the dynamic model. A simulation experiment on a selected non‐solvent‐solvent‐polymer ternary system is carried out to verify the model as well as the numerical method. The dynamic simulation results are analyzed and discussed. At the end of the article, h‐refinement and p‐refinement are used to confirm the spatial convergence of the numerical solutions. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3432–3440, 2016     

Optimal design of large‐scale chemical processes under uncertainty: A ranking‐based approach

An approach for the optimal design of chemical processes in the presence of uncertainty was presented. The key idea in this work is to approximate the process constraint functions and model outputs using Power Series Expansions (PSE)‐based functions. The PSE functions are used to efficiently identify the variability in the process constraint functions and model outputs due to multiple realizations in the uncertain parameters using Monte Carlo (MC) sampling methods. A ranking‐based approach is adopted here where the user can assign priorities or probabilities of satisfaction for the different process constraints and model outputs considered in the analysis. The methodology was tested on a reactor–heat exchanger system and the Tennessee Eastman process. The results show that the present method is computationally attractive since the optimal process design is accomplished in shorter computational times when compared to the use of the MC method applied to the full plant model. © 2014 American Institute of Chemical Engineers AIChE J, 60: 3243–3257, 2014     

Error‐triggered on‐line model identification for model‐based feedback control

In industry, it may be difficult in many applications to obtain a first‐principles model of the process, in which case a linear empirical model constructed using process data may be used in the design of a feedback controller. However, linear empirical models may not capture the nonlinear dynamics over a wide region of state‐space and may also perform poorly when significant plant variations and disturbances occur. In the present work, an error‐triggered on‐line model identification approach is introduced for closed‐loop systems under model‐based feedback control strategies. The linear models are re‐identified on‐line when significant prediction errors occur. A moving horizon error detector is used to quantify the model accuracy and to trigger the model re‐identification on‐line when necessary. The proposed approach is demonstrated through two chemical process examples using a model‐based feedback control strategy termed Lyapunov‐based economic model predictive control (LEMPC). The chemical process examples illustrate that the proposed error‐triggered on‐line model identification strategy can be used to obtain more accurate state predictions to improve process economics while maintaining closed‐loop stability of the process under LEMPC. © 2016 American Institute of Chemical Engineers AIChE J, 63: 949–966, 2017     

Novel operability‐based approach for process design and intensification: Application to a membrane reactor for direct methane aromatization

This article introduces a novel operability‐based approach for process design and intensification of energy systems described by nonlinear models. This approach is applied to a membrane reactor (MR) for the direct methane aromatization (DMA) conversion to benzene and hydrogen. The proposed method broadens the scope of the traditional path of the operability approaches for design and control, mainly oriented to obtain the achievable output set (AOS) from the available input set, and compare the computed AOS to a desired output set. In particular, an optimization algorithm based on nonlinear programming tools is formulated for the calculation of the desired input set that is feasible considering process constraints and intensification targets. Results on the application of the operability method as a tool for process intensification show reduction of the DMA‐MR footprint (≈77% reactor volume and 80% membrane area reduction) for an equivalent level of performance, when compared to the base case. This case study indicates that the novel approach can be a powerful tool for process intensification of membrane reactors and other complex chemical processes. © 2016 American Institute of Chemical Engineers AIChE J, 63: 975–983, 2017     

Multi‐stage adjustable robust optimization for process scheduling under uncertainty

Variations in parameters such as processing times, yields, and availability of materials and utilities can have a detrimental effect in the optimality and/or feasibility of an otherwise “optimal” production schedule. In this article, we propose a multi‐stage adjustable robust optimization approach to alleviate the risk from such operational uncertainties during scheduling decisions. We derive a novel robust counterpart of a deterministic scheduling model, and we show how to obey the observability and non‐anticipativity restrictions that are necessary for the resulting solution policy to be implementable in practice. We also develop decision‐dependent uncertainty sets to model the endogenous uncertainty that is inherently present in process scheduling applications. A computational study reveals that, given a chosen level of robustness, adjusting decisions to past parameter realizations leads to significant improvements, both in terms of worst‐case objective as well as objective in expectation, compared to the traditional robust scheduling approaches. © 2016 American Institute of Chemical Engineers AIChE J, 62: 1646–1667, 2016     

Study on dynamic behavior adjustment of nonlinear chemical processes

In nonlinear chemical processes, many economically desirable operating conditions are located in unstable regions, leading to product quality degradation and safety problems. Therefore, determining how to adjust the dynamic behavior to make the process stable within its desired operational range is a topic of common interest within industrial and academic communities. This article presents a dynamic behavior adjustment method based on a washout filter‐aided controller with an improved parameter‐tuning algorithm to stabilize parts of the equilibrium manifold of chemical processes. In addition, applying this method to industrial toluene liquid‐phase catalytic oxidation shows that, by combining a conventional proportional‐integral (PI) controller with the proposed improved washout filter‐aided controller, the performance of set‐point tracking is improved for cases with parameter uncertainty. In general, the proposed dynamic behavior adjustment method will be effective for most chemical processes. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3189–3198, 2016     

The formulation of optimal mixtures with generalized disjunctive programming: A solvent design case study

Systematic approaches for the design of mixtures, based on a computer‐aided mixture/blend design (CAM^bD) framework, have the potential to deliver better products and processes. In most existing methodologies the number of mixture ingredients is fixed (usually a binary mixture) and the identity of at least one compound is chosen from a given set of candidate molecules. A novel CAM^bD methodology is presented for formulating the general mixture design problem where the number, identity and composition of mixture constituents are optimized simultaneously. To this end, generalized disjunctive programming is integrated into the CAM^bD framework to formulate the discrete choices. This generic methodology is applied to a case study to find an optimal solvent mixture that maximizes the solubility of ibuprofen. The best performance in this case study is obtained with a solvent mixture, showing the benefit of using mixtures instead of pure solvents to attain enhanced behavior. © 2016 The Authors AIChE Journal published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers AIChE J, 62: 1616–1633, 2016     

A review of the operating limits in slot die coating processes

Slot die coating is a pre‐metered process commonly used for producing thin and uniform films. It is an important film fabrication method for applications where precise coating is required. A major concern in slot die coating processes is how to determine the operating limits to set the appropriate range of operating parameters, including coating speed, flow rate, vacuum pressure, coating gap, liquid viscosity and surface tension, etc. Operating limits directly determine the effectiveness and efficiency of the process. In this article, the current state of academic research on operating limits in slot die coating processes is reviewed. Specifically, the theories, mechanisms, and empirical conclusions related to the limits on vacuum pressure, the low‐flow limit, the limit of wet thickness for zero‐vacuum‐pressure cases, the limit of dynamic wetting failure, and the limits of coating speed for a specific flow rate are reviewed. The article concludes with some recommendations for future work. © 2016 American Institute of Chemical Engineers AIChE J, 62: 2508–2524, 2016     

Energy in chemical manufacturing processes: gate‐to‐gate information for life cycle assessment

Gate‐to‐gate process energy for 86 chemical manufacturing processes is presented. The estimation of the process energy follows design‐based methodology. Results show that the gate‐to‐gate process energy for half of organic chemicals ranges from 0 to 4 MJ per kg, and for half of inorganic chemicals ranges from ?1 to 3 MJ per kg. The main energy source in both organic and inorganic processes is steam energy followed by potential recovered energy. In organic chemicals, the fractions of heating oil and electricity use are relatively low, but these fractions are higher in the inorganic chemicals than in the organic chemicals. Furthermore, about 50% of the energy consumed in chemical processes is used for purifying the product, byproduct or recycled stream, which indicates that there are large opportunities for improving the process energy in chemical processes. The information presented in this study is very important for those in the life cycle assessment community in order for them to identify inaccurate information or information not based on actual process design. However, the range for the entire range of chemicals is very substantial and thus reflects the need of the life cycle inventory to separately evaluate the chemistry and degree of purity for chemical products. Copyright © 2003 Society of Chemical Industry