An integrated chemical engineering approach to understanding microplastics

Environmental and health risks posed by microplastics (MPs) have spurred numerous studies to better understand MPs' properties and behavior. Yet, we still lack a comprehensive understanding due to MP's heterogeneity in properties and complexity of plastic property evolution during aging processes. There is an urgent need to thoroughly understand the properties and behavior of MPs as there is increasing evidence of MPs' adverse health and environmental effects. In this perspective, we propose an integrated chemical engineering approach to improve our understanding of MPs. The approach merges artificial intelligence, theoretical methods, and experimental techniques to integrate existing data into models of MPs, investigate unknown features of MPs, and identify future areas of research. The breadth of chemical engineering, which spans biological, computational, and materials sciences, makes it well-suited to comprehensively characterize MPs. Ultimately, this perspective charts a path for cross-disciplinary collaborative research in chemical engineering to address the issue of MP pollution.     

An integrated dimensionality reduction and surrogate optimization approach for plant-wide chemical process operation

With liquefied natural gas becoming increasingly prevalent as a flexible source of energy, the design and optimization of industrial refrigeration cycles becomes even more important. In this article, we propose an integrated surrogate modeling and optimization framework to model and optimize the complex CryoMan Cascade refrigeration cycle. Dimensionality reduction techniques are used to reduce the large number of process decision variables which are subsequently supplied to an array of Gaussian processes, modeling both the process objective as well as feasibility constraints. Through iterative resampling of the rigorous model, this data-driven surrogate is continually refined and subsequently optimized. This approach was not only able to improve on the results of directly optimizing the process flow sheet but also located the set of optimal operating conditions in only 2 h as opposed to the original 3 weeks, facilitating its use in the operational optimization and enhanced process design of large-scale industrial chemical systems.     

Design and operation of multiproduct and multipurpose batch chemical plants. — An analysis of problem structure

The general structure of batch processing problems is reviewed. A classification scheme is presented which analyses the specification of the system components, -comprising product requirements, specification of process tasks and available equipment items, followed by consideration of constraints on system structure, problem definition and solution methods. A hierarchy of model types for batch units is proposed for use in different problem situations. Examples of the use of the scheme are provided by the classification and comparison of selected publications on batch processing and the scheme is also used to draw attention to potential areas for further work. Brief remarks are added on problem size and computational experience in different areas of batch processing.     

Simulation of single- and multiproduct batch chemical plants for optimal design and operation

Reasons for the increasing interest in batch plants and their improved design and operation are discussed. The extensive literature on the optimal operation of individual batch equipment items is reviewed and summarized. Topics covered include simple reactors with various kinetic schemes, polymerization, reactors with decaying catalysts including deactivating enzymes, batch distillation and crystallization. The study of multi-item batch plants is a much more recent development. A personal perspective is given of methods currently available for the quantitative treatment of the design and operation of multiproduct and multipurpose batch plants. Interconnections between existing areas of competence are pointed out and some directions suggested for further developments.     

An automata-based approach to synthesize untimed operating procedures in batch chemical processes

Systematic synthesis of untimed operating procedures has always been considered as an important design issue for batch chemical processes. An automaton-based method is developed in the present study to perform this task automatically. On the basis of the proposed methodical model-building principles, two distinct types of automata can be constructed to characterize the plant behaviors and control specifications, respectively. An admissible supervisor can be produced by applying the parallel composition operation with these models. For the purpose of identifying the most efficient operation procedures, the supervisor can then be integrated with a set of auxiliary automata to set the operation target(s) and, also, to impose upper limits on the total numbers of actuator actions and operation steps. Three examples are presented to demonstrate the feasibility and correctness of the proposed approach.     

A computerized and integrated approach for heat exchanger network design in multipurpose batch plants

Significant savings in the utility cost of batch plants can be obtained by heat integration. In this study, an integrated mathematical programming approach is developed for the determination of the cost optimal heat exchanger network for multipurpose batch chemical plants. A single step, interactive computer program (BatcHEN) which is developed for the determination of the campaigns (i.e. the set of products which can be produced simultaneously), the heat exchange areas of all possible heat exchangers in the campaigns and finally the heat exchanger network are all discussed. A matrix search algorithm is used for the determination of the campaigns. Heat exchange areas for the possible heat exchangers are found by solving a nonlinear optimization model with a grid search algorithm. Finally the heat exchanger network optimization is modeled as a mixed integer linear programming problem and then solved by the modeling and optimization software GAMS/XA.     

A simplified approach to the operation of a batch crystallizer

A general model for a seeded cooling batch crystallizer based on first principles is developed, incorporating either size-dependent or size-independent growth rates. A simple approach is proposed to obtain temperature-time trajectories at constant supersaturation or nucleation rate, without resorting to optimization techniques. Cooling curves at constant supersaturation, which lead to a substantial improvement (a smaller coefficient of variation and a larger mean size) of the terminal crystal size distribution, can be determined even in the absence of precise nucleation and growth kinetics, whereas properties related to the crystal size distribution are sensitive to such kinetics. Experimental results for the potassium sulfate-water system, potash alum-water system, and hexamethylenetetramine in ethanol, methanol, and 2-propanol/water are predicted reasonably well by the model. Extension to any type of batch crystallization with super-saturation induced by means other than cooling, such as reactive precipitation and salting out, is briefly discussed.     

An integrated approach to training

The Career Structure Scheme, instigated by companies within the wool textile industry and administered by the Confederation of British Wool Textiles (CBWT), was introduced during the late 70s as an attempt to establish a comprehensive and cohesive training programme for young people entering into the industry. Today the scheme is recognised as one of the best training programmes in the country, a view substantiated in 1988 when the CBWT received a National Training Award for the scheme from central government.     

An economic model predictive control approach to integrated production management and process operation

Managing production schedules and tracking time‐varying demand of certain products while optimizing process economics are subjects of central importance in industrial applications. We investigate the use of economic model predictive control (EMPC) in tracking a production schedule. Specifically, given that only a small subset of the total process state vector is typically required to track certain scheduled values, we design a novel EMPC scheme, through proper construction of the objective function and constraints, that forces specific process states to meet the production schedule and varies the rest of the process states in a way that optimizes process economic performance. Conditions under which feasibility and closed‐loop stability of a nonlinear process under such an EMPC for schedule management can be guaranteed are developed. The proposed EMPC scheme is demonstrated through a chemical process example in which the product concentration is requested to follow a certain production schedule. © 2016 American Institute of Chemical Engineers AIChE J, 63: 1892–1906, 2017     

Optimal assignment of products to equipment items in multi-purpose batch chemical plants

A subproblem of scheduling is considered; the optimal assignment of products to equipment items, neglecting the order and sequencing of processing steps. This problem arises, if differences exist in the suitability of equipment items for processing different kinds of processing steps. The optimal compromise between capacity and suitability must be determined. Further, the influence of earliest starting time and latest completion time and the use of additional tools of limited number for optimal assignment is considered.In all cases models are proposed, which transform the problem into a capacitated network, on which a Hitchcock transportation problem has to be solved. This enables the use of standard mathematical software.     

A solution approach to the design of multi-period,multipurpose batch plants

A deterministic model for multipurpose, multiperiod batch plants was presented in a linearized form to predict the future design according to the change of demand by using a modified Benders’ Decomposition. The OSL code offered by the IBM corporation as optimizer was employed for solving several example problems. The decomposition method was successful, showing remarkable reduction in the computing times as compared with those of the direct solution method. Also the heuristic used as a solution approach for the multiperiod model provided an efficient methodology to the block-structured problem by dividing the large overall problem into the manageable single period blocks.     

An automaton-based approach to evaluate and improve online diagnosis schemes for multi-failure scenarios in batch chemical processes

Online diagnosis has been considered as an important measure for improving operational safety in many batch chemical plants. Specifically, the state transition behaviors of all hardware items (components) in the given batch process and their failure mechanisms are modeled systematically with automata. The system model is then assembled by connecting the component models on the basis of a generic hierarchical structure. A “diagnoser” can be constructed accordingly for the purpose of determining various qualitative and quantitative performance indices. Guided by these indices, two performance enhancement approaches can be effectively applied: (1) installing additional sensors which are not included in the piping and instrumentation diagram (P&ID) and (2) executing extra operation steps which are not specified in the sequential function chart (SFC). Three examples are presented in this paper to demonstrate the feasibility of the proposed approach.     

An integrated approach to electrochemical impedance spectroscopy

A philosophy for electrochemical impedance spectroscopy is presented which integrates experimental observation, model development, and error analysis. This approach is differentiated from the usual sequential model development for given impedance spectra by its emphasis on obtaining supporting observations to guide model selection, use of error analysis to guide regression strategies and experimental design, and use of models to guide selection of new experiments. These concepts are illustrated with two examples taken from the literature. This work illustrates that selection of models, even those based on physical principles, requires both error analysis and additional experimental verification.     

带有内部热集成的多储罐间歇精馏全回流操作

鉴于间歇精馏热力学效率低的缺点,提出带有内部热集成的多储罐间歇精馏全回流操作(IHIMVBD)分离二元混合物的新型操作方式。在该操作中,多储罐间歇精馏塔被同轴的夹套式再沸器环绕,利用安装在再沸蒸汽管线上的压缩机使精馏塔的操作压力高于夹套式再沸器,使热量通过精馏塔壁面从高压的精馏塔传向低压的再沸器,实现热量的内部集成。为了进一步提高热力学效率和经济效益,将塔顶蒸汽再压缩技术应用于IHIMVBD,构成强化的内部热集成多储罐间歇精馏全回流操作(Int-IHIMVBD)。该操作能额外利用被压缩的塔顶蒸汽的潜热供给塔釜料液再沸,实现塔顶蒸汽与塔釜料液的热集成。通过模拟分离乙醇-正丙醇的实例表明,相比MVBD和IHIMVBD,Int-IHIMVBD能显著提高分离过程的热力学效率和经济效益。     

Optimum design and operation of batch rectification accompanied by chemical reaction

Batch processes are widespread in the chemical industry. If batch synthesis or separation processes are to run economically, the operating conditions must be optimized and an appropriate arrangement of equipment must be chosen. In this paper, we demonstrate that optimization of operaiong conditions and plant-equipment by simulation during the planning-stages can yield large advantages. In contrast to previous studies, our models include the non-ideal behaviour of multicomponent mixtures and the kinetics of chemical reactions in the column. The results of the calculations are control functions that permit optimum operation to be realized.

As an example, the reactionin a distillation column was optimized. Compared with conventional operation, the calculated control functions give an advantage in capacity of 65% and in energy consumption of 40%. The calculation was confirmed by measurements. A control algorithm is evaluated.     

A novel approach to scheduling multipurpose batch plants using unit‐slots

Several models for scheduling multipurpose batch plants exist in the literature. The models using unit‐specific event points have shown better solution efficiency on various literature examples. This article presents a novel approach to scheduling multipurpose batch plants, which uses unit‐slots instead of process‐slots to manage shared resources such as material storage. We develop two slightly different models that are even more compact and simpler than that of Sundaramoorthy and Karimi, Chem Eng Sci. 2005;60:2679–2702. Although we focus on material as a shared resource, our multi‐grid approach rationalizes, generalizes, and improves the current multi‐grid approaches for scheduling with shared resources. Our models allow nonsimultaneous transfers of materials into and out of a batch. We show by an example that this flexibility can give better schedules than those from existing models in some cases. Furthermore, our approach uses fewer slots (event‐points) on some examples than even those required by the most recent unit‐specific event‐based model. Numerical evaluation using literature examples shows significant gains in solution efficiency from the use of unit‐slots except where the number of unit‐slots required for the optimal solution equals that of process slots. We also highlight the importance of constraint sequencing in GAMS implementation for evaluating mixed‐integer linear programming based scheduling models fairly. © 2009 American Institute of Chemical Engineers AIChE J, 2010     

On the solution of scheduling problems for multi-purpose batch chemical plants

A solution strategy for solving the scheduling problem in the case of multi-purpose batch chemical plants is described. The plant may contain several identical examples of any of the types of process unit. The problem is characterized by requirements such as —branching in batch and device —maintenance of a fixed time regime in the production of one batch —changeover times when products are changed, etc. The centre of the heuristic strategy of solution is an exact algorithm which examines whether or not a batch with a given starting time can be scheduled. The appropriate subprogram can be easily incorporated into programs realizing known heuristic scheduling principles, which were developed for solving simpler problems. Examples with 68 process units, 600 shits and 350 batches have been computed on a EC 1040 computer in 10–15 minutes.     

A multiobjective approach to design chemical plants with robust dynamic operability characteristics

In chemical plants, operability problems arise mainly due to poor process designs, inaccurate models and/or the control system designs that are unable to cope with process uncertainties. In this paper, a process design methodology is presented that addresses the issue of improving dynamic operability in the present of process uncertainty through appropriate design modifications. The multiobjective nature of the design problem is carefully exploited in the subsequent formulations and a nonlinear programming approach is taken for the simultaneous treatment of both steady-state and dynamic constraints.

Scope—Today, a chemical engineer faces the challenge of designing chemical plants that can operate safely, smoothly and profitably within a dynamic process environment. For a typical chemical plant, major contributions to such an environment originate from external disturbances such as variations in the feedstock quality, different product specifications and/or internal disturbances like catalyst poisoning and heat-exchanger fouling. To guarantee a flexible operation despite such upsets, traditionally, the procedure was either to oversize the equipment or to place large storage tanks between the processing units. Proposed design methods attempted to find optimal operating regimes for chemical plants while compensating for process uncertainty through empirical overdesign factors.

Studies concerned with the interplay between the process design and operation aspects have appeared recently [1, 2] and focused on achieving better controllability upon modifying the plant design, without explicitly considering process uncertainty. Nevertheless, maintaining satisfactory dynamic operability in an environment of uncertainty remained as a pressing issue and the need was raised quite frequently for a rigorous treatment of the topic [3].

The development of new analytical tools [4, 5] made it possible to consider dynamic operability at the process design stage and modify the plant design accordingly. In this paper, a methodology is presented, that systematically guides the designer towards process designs with better dynamic operability and economics, The problem is formulated within a multiobjective optimization framework and makes extensive use of singular-value decomposition and nonlinear semi-infinite programming techniques.

Conclusions and Significance—A multiobjective optimization problem is proposed for designing chemical processes with better dynamic operability characteristics. Robustness indices are used as the indicators of dynamic operability and placed as constraints within the optimization scheme. A semi-infinite nonlinear programming problem results due to the frequency-dependent nature of such constraints. A discretization procedure is suggested to handle the infinite number of constraints and an ellipsoid algorithm allows an interactive solution of the process design problem. A process consisting of three CSTRs is treated as an example, illustrating the potential of the methodology in solving design-related operability problems.