Trade-off optimal design of a biocompatible solvent for an extractive fermentation process

In this study, crisp and flexible optimization approaches are, respectively, introduced to design an optimal biocompatible solvent for an extractive fermentation process. The optimal design problem is formulated as a mixed-integer nonlinear programming model in which performance requirements of the compounds are reflected in the objective and the constraints. In general, the requirements for the objective and constraints are not rigid; consequently, the flexible or fuzzy optimization approach is applied to soften the rigid requirement for maximization of the extraction efficiency and to consider the mass flow rate and biocompatibility of solvent as the softened inequality constraints to the solvent design problem. Having elicited the membership function for the objective function and the constraint, the optimal solvent design problem can be formulated as a flexible goal attainment problem. Mixed-integer hybrid differential evolution is applied to solve the problem in order to find a satisfactory design.     

Efficient integration of optimal solvent and process design using molecular clustering

We present a molecular clustering approach for the efficient incorporation of solvent design information into process synthesis in the integrated design of solvent/process systems. The approach is to be used in conjunction with an integrated solvent/process design approach where the solvent design stage utilises multi-objective optimisation in order to identify Pareto optimal solvent candidates that are subsequently evaluated in a process synthesis stage. We propose to introduce the solvent design information into the process synthesis stage through the use of molecular clusters. The partitioning of the original Pareto optimal set of solvents leads to smaller compact groups of similar solvent molecules from which representative molecules are introduced into the process synthesis model as discrete options to determine the optimal process performance associated with the optimal solvent. We investigate two clustering strategies, serial and parallel clustering, that allow to effectively exploit the solvent-process design interactions to minimise the computational demands of the process synthesis stage. We further propose a clustering heuristic probability that can aid decision making in clustering and can significantly accelerate the search for the best integrated solvent-process systems. The presented method is illustrated with case studies in the design of solvents for liquid-liquid extraction, gas-absorption and extractive distillation systems.     

Optimal design of extractive distillation columns—A systematic procedure using a process simulator

The separation of binary mixtures which form azeotropes is not possible through conventional distillation and they are usually separated by extractive or azeotropic distillation. The optimization of extractive distillation columns is usually performed using a process simulator; however, normally, the result is only obtained after several simulations and the simultaneous analysis of several graphs. This paper sets out to present a systematic procedure, using a process simulator (Aspen Plus^®), in order to obtain the optimum condition for extractive distillation columns. The optimization achieved is characterized by the fact that it is not necessary to perform various simulations, and it also avoids the simultaneous analysis of dozens of curves. The dehydration of aqueous mixtures of ethanol using ethylene glycol as solvent was the system chosen as a case study.     

A computer-aided molecular design framework for crystallization solvent design

One of the key decisions in designing solution crystallization processes is the selection of solvents. In this paper, we present a computer-aided molecular design (CAMD) framework for the design and selection of solvents and/or anti-solvents for solution crystallization. The CAMD problem is formulated as a mixed integer nonlinear programming (MINLP) model. Although, the model allows any combination of performance objectives and property constraints, in the case studies, potential recovery was considered as the performance objective. The latter, needs to be maximized, while other solvent property requirements such as solubility, crystal morphology, flashpoint, toxicity, viscosity, normal boiling and melting point are posed as constraints. All the properties are estimated using group contribution methods. The MINLP model is then solved using a decomposition approach to obtain optimal solvent molecules. Solvent design and selection for two types of solution crystallization processes namely cooling crystallization and drowning out crystallization are presented. In the first case study, the design of single compound solvent for crystallization of ibuprofen, which is an important pharmaceutical compound, is addressed. One of the important issues namely, the effect of solvent on the shape of ibuprofen crystals is also considered in the MINLP model. The second case study is a mixture design problem where an optimal solvent/anti-solvent mixture is designed for crystallization of ibuprofen by the drowning out technique. For both case studies the performance of the solvents are verified qualitatively through SLE diagrams.     

Integrated solvent and process design using a SAFT-VR thermodynamic description: High-pressure separation of carbon dioxide and methane

The increasing importance of natural gas as an energy source poses separation challenges, due to the high pressures and high carbon dioxide concentrations of many natural gas streams. A methodology for computer-aided molecular and process design (CAMPD) applicable to such extreme conditions is presented, based on the integration of process and cost models with an advanced molecular-based equation of state, the statistical associating fluid theory for potentials of variable range (SAFT-VR). The approach is applied to carbon dioxide capture from methane using physical absorption. The search for an optimal solvent is focused on n-alkane blends. A simple flowsheet is optimised using two objectives: maximum purity and maximum net present value. The best equipment sizes, operating conditions, and average chain length of the solvent (the n-alkane) are identified, indicating n-alkane solvents offer a promising alternative. The proposed methodology can readily be extended to wider classes of solvents and to other challenging processes.     

Conceptual process design of extractive distillation processes for ethylbenzene/styrene separation

In the current styrene production process the distillation of the close-boiling ethylbenzene/styrene mixture to obtain an ethylbenzene impurity level of 100 ppm in styrene accounts for 75–80% of the energy requirements. The future target is to reach a level of 1–10 ppm, which will increase the energy requirements for the distillation even further. Extractive distillation is a well-known technology to separate close-boiling mixtures up to high purities. The objective of this study was to investigate whether extractive distillation using ionic liquids (ILs) is a promising alternative to obtain high purity styrene. Three ILs were studied: [3-mebupy][B(CN)₄], [4-mebupy][BF₄], and [EMIM][SCN]. Extractive distillation with sulfolane and the current conventional distillation process were used as benchmark processes. The IL [4-mebupy][BF₄] is expected to outperform the other two ILs with up to 11.5% lower energy requirements. The operational expenditures of the [4-mebupy][BF₄] process are found to be 43.2% lower than the current distillation process and 5% lower than extractive distillation with sulfolane extractive distillations. However, the capital expenditures for the sulfolane process will be about 23% lower than those for the [4-mebupy][BF₄] process. Finally, the conclusion can be drawn from the total annual costs that all studied extractive distillation processes outperform the current distillation process to obtain high purity styrene, but that the ILs evaluated will not perform better than sulfolane.     

Integrated solvent and process design for continuous crystallization and solvent recycling using PC‐SAFT

Solvent usage is a major source of environmental waste in pharmaceutical industry. The current paradigm shift toward continuous manufacturing in pharmaceutical industry has renewed the interest in continuous crystallization, which offers the prospect of easy solvent recycling. However, the selection of solvents for an integrated crystallization processes is nontrivial due to the likely trade‐off between optimal solvent properties for crystallization and solvent separation and recycling. A systematic approach for the simultaneous optimization of process conditions and solvent selection for continuous crystallization including solvent recycling is presented. A unified perturbed‐chain statistical associating fluid theory model framework is applied to predict thermodynamic properties related to solubility and vapor‐liquid equilibrium, which is integrated with a process model. A continuous mapping procedure is adopted to solve the optimization problem effectively. A case study based on continuous antisolvent crystallization of paracetamol with solvent separation via flash demonstrates the approach. © 2017 American Institute of Chemical Engineers AIChE J, 64: 1205–1216, 2018     

Optimal design and planning of heap leaching process. Application to copper oxide leaching

Although the process of heap leaching is an established technology for treating minerals, such as copper, gold, silver, uranium and saltpeter, as well as remediating soil, no studies to date have investigated process optimization. This work presents a methodology for the design and planning of heap leaching systems to optimize the process. This methodology consists of the creation of a superstructure that represents a set of alternatives to search for the optimal solution; from this superstructure, a mixed integer nonlinear programming (MINLP) model was generated, and a BARON-GAMS solver was used to find the optimal solution. This method was applied to the extraction of copper from systems with one, two and three heaps, and the effects of copper price, ore grade and other variables were analyzed for each system. From the results, it can be concluded that this methodology can be used to optimize heap leaching processes, including planning and design issues.     

Performance analysis and fuzzy optimization of a two-stage fermentation process with cell recycling including an extractor for lactic acid production

In this study, we consider a two-stage fermenter with cell recycling including an extractor to produce lactic acid. When the extractor was omitted, the proposed process was simplified to two special processes. Under the same operating conditions, we compared the overall lactic acid productivity and glucose conversion for the three processes. The proposed fermentation process was more efficient than the other processes. To simultaneously obtain the maximum productivity and conversion, the problem is formulated as a fuzzy multiobjective optimization problem. The fuzzy decision is introduced to convert the multiobjective fuzzy optimization problem into the fuzzy goal attainment problem. Hybrid differential evolution is applied to solve the fuzzy goal attainment problem to obtain a global Pareto solution.     

Repeated batch fermentation with water recycling and cell separation for microbial lipid production

Large waste water disposal was the major problem in microbial lipid fermentation because of low yield of lipid. In this study, the repeated batch fermentation was investigated for reducing waste water generated in the lipid fermentation of an oleaginous yeast Trichosporon cutaneum CX1 strain. The waste fermentation broth was recycled in the next batch operation after the cells were separated using two different methods, centrifugation and flocculation. Two different sugar substrates, glucose and inulin, were applied to the proposed operation. The result showed that at least 70% of the waste water was reduced, while lipid production maintained satisfactory in the initial four cycles. Furthermore, it is suggested that T. cutaneum CX1 cells might produce certain naturally occurring inulin hydrolyzing enzyme(s) for obtaining fructose and glucose from inulin directly. Our method provided a practical option for reducing the waste water generated from microbial lipid fermentation.     

CSTR工艺与控制系统的集成优化设计方法

与传统的序贯设计方法相比,过程工艺与控制系统的集成优化设计可较大地提高过程的可操作性和经济性能,但基于常规动态优化的集成设计问题求解困难。采用最优控制和分层优化策略的思想,将线性二次调节器(LQR)嵌入到过程工艺与控制系统集成设计框架中,以降低集成优化设计问题的求解难度。将该方法应用于连续搅拌釜式反应器(CSTR)的设计中,通过与传统的序贯设计方法相比较,表明了该方法的有效性。     

活性污泥法脱氮除磷工艺的优化设计

利用活性污泥2D模型对城市污水厂脱氮除磷工艺进行优化设计,构建A²/O工艺的仿真模型,通过模型校正对工艺参数进行优化,并将优化设计与传统设计法和试算法进行比较。结果表明,优化模型得出的模拟结果与实验测定值基本相吻合。优化设计法得出的污水厂基建费用和运行成本与其他两种方法相比,都有了很大的降低,虽然出水水质略有下降,但仍满足国家排放一级B标准。活性污泥2D模型可以对污水厂进行优化设计和控制。在满足出水水质前提下,降低污水厂的费用,并对以后的工艺设计提供理论指导。     

Optimal storage design for a multi-product plant: A non-convex MINLP formulation

We discuss a tank design problem for a multi product plant, in which the optimal cycle time and the optimal campaign size are unknown. A mixed-integer nonlinear programming (MINLP) formulation is presented, where non-convexities are due to the tank investment cost, storage cost, campaign setup cost and variable production rates. The objective of the optimization model is to minimize the sum of the production cost per ton per product produced. A continuous-time mathematical programming formulation is proposed and several extensions are discussed. The model is implemented in GAMS and computational results are reported for the two global MINLP solver BARON and LINDOGlobal as well as several nonlinear solvers available in GAMS.     

Optimal design of a four‐zone simulated moving bed process for separation of homoharringtonine and harringtonine

A simulated moving bed (SMB) technology was applied to the separation of homoharringtonine (HHT) and harringtonine (HT), which were known to have the potentiality of being used as anti‐cancer agents. First, a series of pulse injection experiments were performed for estimation of the adsorption isotherm and mass‐transfer parameters of HHT and HT. The estimated parameters were utilised in the SMB optimisation tool based on the standing wave design method. From the optimisation tool prepared, the SMB operating parameters (zone flow rates and step time) that led to the highest throughput were obtained under the constraints of product purities (=99.0%) and pressure drop (≤1000 psi). Such an optimisation work was then extended to determine an optimal size of the adsorbent particle for the SMB of interest. The results showed that a particle size of 29 µm was the optimal one for maximising the SMB throughput under the conditions that the column configuration was 2–2–2–2 and the length of each column was 25 cm. If the SMB had the particle size other than 29 µm, its throughput was limited by either the maximum operating pressure or the mass‐transfer efficiency. Finally, an efficient procedure of removing a mobile‐phase additive (ammonium formate) from the product stream of the aforementioned SMB system was developed using a liquid–liquid extraction (LLE) technique. From the results of this study, it was confirmed that the SMB process coupled with a LLE procedure could be highly effective in separating HHT and HT with high throughout and high purity.     

Outer approximation algorithm with physical domain reduction for computer‐aided molecular and separation process design

Integrated approaches to the design of separation systems based on computer‐aided molecular and process design (CAMPD) can yield an optimal solvent structure and process conditions. The underlying design problem, however, is a challenging mixed integer nonlinear problem, prone to convergence failure as a result of the strong and nonlinear interactions between solvent and process. To facilitate the solution of this problem, a modified outer‐approximation (OA) algorithm is proposed. Tests that remove infeasible regions from both the process and molecular domains are embedded within the OA framework. Four tests are developed to remove subdomains where constraints on phase behavior that are implicit in process models or explicit process (design) constraints are violated. The algorithm is applied to three case studies relating to the separation of methane and carbon dioxide at high pressure. The process model is highly nonlinear, and includes mass and energy balances as well as phase equilibrium relations and physical property models based on a group‐contribution version of the statistical associating fluid theory (SAFT‐γ Mie) and on the GC⁺ group contribution method for some pure component properties. A fully automated implementation of the proposed approach is found to converge successfully to a local solution in 30 problem instances. The results highlight the extent to which optimal solvent and process conditions are interrelated and dependent on process specifications and constraints. The robustness of the CAMPD algorithm makes it possible to adopt higher‐fidelity nonlinear models in molecular and process design. © 2016 The Authors AIChE Journal published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers AIChE J, 62: 3484–3504, 2016     

A NGCC power plant with a CO2 post-combustion capture option. Optimal economics for different generation/capture goals

Fossil fuel power plants are one of the major sources of electricity generation, although invariably release greenhouse gases. Due to international treaties and countries regulations, CO₂ emissions reduction is increasingly becoming key in the generators’ economics. NGCC power plants constitute a widely used generation technology, from which CO₂ capture through a post-combustion and MEA absorption option constitutes a technological challenge due to the low concentration of pollutants in the flue gas and the high energy requirements of the sequestration process.     

Optimal design of distillation systems with less than N − 1 columns for a class of four component mixtures

The optimal design of complex distillation systems is a highly non-linear and multivariable problem, with several local optimums and subject to different constraints. In addition, some attributes for the design of these separation schemes are often conflicting objectives, and the design problem should be represented from a multiple objective perspective. As a result, solving with traditional optimization methods is not reliable because they generally converge to local optimums, and often fail to capture the full Pareto optimal front. In this paper, a method for the multiobjective optimization of distillation systems, conventional and thermally coupled, with less than N − 1 columns is presented. We use a multiobjective genetic algorithm with restrictions coupled to AspenONE Aspen Plus; so, the complete MESH equations and rigorous phase equilibrium calculations are used. Results show some tendencies in the design of intensified sequences, according to the nature of the mixture and feed compositions.     

Systematic retrofit design with Response Surface Method and process integration techniques: A case study for the retrofit of a hydrocarbon fractionation plant

This paper demonstrates the Retrofit Design Approach (RDA) and Response Surface Methodology (RSM) for the retrofit of industrial plants in which assessment of design options for improving existing processes in a site-wide and integrated manner is not straightforward, due to complex design interactions in the process. The design methodology applied in this study is based on the systematic use of a process simulator which is used to identify promising variables through sensitivity analysis. Hence, the most important factors are determined and a reduced model is constructed based on RSM. An optimization framework is then built using the reduced model based on key selected variables, which is optimized to find optimal conditions and performance of the process. This design methodology provides strategic guidelines for determining the most cost-effective design options. The retrofit of a hydrocarbon fractionation plant is presented as an industrial case study. This includes a large number of design options with different process configurations and operating conditions due to the interconnection of distillation columns in sequence and the integrated heat recovery within the plant. The case study results demonstrate the applicability of the proposed approach which is able to effectively deal with a large retrofit problems. This is possible with the aid of process simulation and RSM producing a reduced model which requires considerably less computational effort to solve.