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• Automated distillation sequence synthesis and MILP modeling. • Generating superstructure based on recursive pre-order traversal algorithm. • An improved quadratic interpolation method for optimizing distillation column. • Two case studies demonstrate the reliability of the framework. • Practical solutions for actual chemical plant design. Distillation energy consumption dominates the process industry; hence, the selection of the distillation sequence will substantially affect the separation energy consumption. We propose a framework for the automatic synthesis and optimization of distillation sequences by integrating the Aspen Plus with the MATLAB programming platform. The framework combines the concept of binary trees in data structures and uses a preorder traversal algorithm to generate a network superstructure in the simulator. In the next step, it automatically formulates and solves a mixed-integer linear programming model based on calculation results; finally, the distillation model is optimized using an improved quadratic interpolation algorithm. Two case studies for C5 alkane and dimethyl carbonate separation showed that the optimal solution obtained by the framework reduced the total annual costs by 13.18 % and 2.88 %, respectively, compared with the processes without systematic optimization. The framework also allowed screening out promising alternatives by rapid evaluation of different process routes. [Display omitted] [ABSTRACT FROM AUTHOR]

Wastewater treatment (WWT) is a mandatory process to ensure wastewater quality meets legislation requirements and to reduce environmental impacts. Many established WWT technologies are available in the market and the selection of such technologies is usually based on heuristics. However, technologies selected using heuristics may not be able to guarantee optimal economic performance. In this respect, it is important for manufacturing companies to synthesise a WWT process with minimum investment cost while meeting legislation requirements. Most manufacturing companies face issues to achieve this goal. Among these issues, is the fact that part of the investment invested into a WWT process will be lost to waste (sludge cake) generation. The generated waste (sludge cake) will require additional high waste disposal costs. Therefore, to reduce the loss of investment in a WWT process, the waste generation cost and waste disposal cost must be minimised. This can be addressed via Material Flow Cost Accounting (MFCA), a management tool that quantifies material flows across physical and monetary values in a production process. Previous works had adapted the concept of MFCA for prioritisation of waste streams for waste recovery and minimisation of investment cost in processes with revenue streams. Thus, the objective of this paper is to extend the use of MFCA as a preliminary decision-making tool in the selection of WWT technologies with minimum waste generation cost. To illustrate the developed approach, a case study on sago-based WWT process is solved in this work. Based on the results, the synthesised WWT process from the developed model is capable of recovering as much as 93.3 % of the total operating cost back into the manufacturing process while minimising the waste generation cost to 6.7 % of the operating investment cost. [ABSTRACT FROM AUTHOR]

• State-Task Network representation for distillation sequence with sidestream column • Nonsharp distillation design through modified Fenske-Underwood-Gilliland method • Four-component case with mass interaction between reaction and separation systems • 14.11% and 5.70% reduction in operational cost and TAC for reference case In this work, a comprehensive design method for three-section sidestream columns along with a novel State Task Network representation including both conventional and sidestream distillation sequence configurations is present. The distillation network is embedded in the superstructure-based framework for reaction-separation-recycle process synthesis to explore the mass interaction in different sub-systems. In the superstructure, complete interconnections among reactor modules as well as necessary connections between reactor modules and distillation columns are involved to guarantee opportune coupled degree. Based on this, component distribution in distillation through Underwood equations is introduced to provide desired products with required purity and multiple component mixtures as feedback to the reactor network, achieving the optimization of mass interaction in the whole flowsheet. Furthermore, Fenske-Underwood-Gilliland shortcut method to design columns with and without sidestream, and finite element with orthogonal collocation approach to design PFRs are employed, so that reasonable tradeoff between model accuracy and solution difficulty is achieved. Finally, two literature examples are performed to demonstrate the feasibility and validity of the proposed methodology. [ABSTRACT FROM AUTHOR]

We propose a new strategy to synthesize heat exchanger networks with detailed designs of individual heat exchangers. The proposed strategy uses a multistep approach by first obtaining a heat exchanger network topology through solving a modified version of the mixed integer nonlinear programming (MINLP) stage‐wise superstructure of Yee and Grossmann, which includes a smoothed LMTD approximation and pressure drops. In a second nonlinear programming (NLP) suboptimization step, we allow for nonisothermal mixing to solve problems with or without exchanger bypasses. The selected heat exchangers along with the mass and energy balances obtained are then used to design the network with detailed exchanger designs through solving a sequence of NLPs for individual heat exchanger designs. The NLPs are based on the detailed discretized optimization models of Kazi et al., which solve quickly and reliably to obtain heat exchangers based on rigorous, first‐principles derived coupled differential equations. These models solve a differential algebraic equation system and do not rely on usual assumptions associated with other heuristic‐based exchanger design methods, such as log mean temperature difference and FT correction factors. These detailed exchanger designs are then used to update the network optimization model through sets of correction factors on heat exchanger area, number of shells, heat transfer coefficients, and pressure drops of each exchanger design, in a method based on that of Short et al. The method solves reliably, guaranteeing feasible exchangers for every potential network generated by the shortcut models, through validation with rigorous heat exchanger models at every iteration. In addition, the method does not increase the nonlinearity of the MINLP model, nor does it require any manual intervention or initialization from the user. Three examples are solved and the results are compared to those obtained in the literature. [ABSTRACT FROM AUTHOR]

A new method for the detailed design of shell and tube heat exchangers is presented through the formulation of coupled differential heat equations, along with algebraic equations for design variables. Heat exchanger design components (tube passes, baffles, and shells) are used to discretize the differential equations and are solved simultaneously with the algebraic design equations. The coupled differential algebraic equation (DAE) system is suitable for numerical optimization as it replaces the nonsmooth log mean temperature difference (LMTD) term. Discrete decisions regarding the number of shells, fluid allocation, tube sizes, and number of baffles are determined by solving an LMTD‐based method iteratively. The resulting heat exchanger topology is then used to discretize the detailed DAE model, which is solved as a nonlinear programming model to obtain the detailed exchanger design by minimizing an economic objective function through varying the tube length. The DAE model also provides the stream temperature profiles inside the exchanger simultaneously with the detailed design. It is observed that the DAE model results are almost equal to the LMTD‐based design model for one‐shell heat exchangers with constant stream properties but shows significant differences when streams properties are allowed to vary with temperature or the number of shells are increased. The accuracy of the solutions and the required computational costs show that the model is well suited for solving heat exchanger network synthesis problems combined with detailed exchanger designs, which is demonstrated in Part 2 of the paper. [ABSTRACT FROM AUTHOR]

We propose a general shortcut distillation column model that can address a wide range of types of separations including nonsharp/sloppy splits. The model can automatically identify key components and estimate the energy requirement of a desired separation in the presence, potentially, of components with zero flow rates. To obtain more practical column height and vapor flow rates, we augment the model with constraints inspired by the Fenske equation. We also propose valid constraints to enhance the computational performance of the proposed model. Due to its flexibility and computational efficiency, the proposed model can be readily used for superstructure‐based process synthesis. [ABSTRACT FROM AUTHOR]

Given an increasing demand for potassium in Brazil, the mining and use of carnallite is becoming increasingly important, because the current source of potassium (sylvinite) is being depleted and there is a risk of shortages. Based on theoretical and practical data available in the literature, this work describes the development, simulation, and economic feasibility of a process for dissolution and crystallization of potassium chloride from carnallite ore. Positive results were obtained following application of the Hoffman diagram and determination of the corresponding equation. The proposed process provided over 85% potassium chloride crystallization, demonstrating its superior performance, compared to existing procedures.

As an abundant, versatile, and cleaner resource, natural gas is underutilized for high‐value chemicals production. Herein, single‐step natural gas conversion technologies that directly produce aromatics and hydrogen from methane are studied. Yet, methane aromatization (MA) is challenging due to low conversion and rapid catalyst deactivation. Accordingly, a reactor model based on thermodynamic equilibrium that allows systematic evaluation of key process variables (e.g., conversion temperature, conversion pressure, and H2 removal) is developed. Then, process synthesis and modeling are utilized to assess the economic viability and identify the key technology gaps for various MA technology alternatives. The results of the analyses indicate that conversion temperature and H2 removal have large impacts on aromatics one‐pass yield and coke formation. The combined conversion conditions, which lead to a minimum 20% aromatics one‐pass yield, are likely required for an economically feasible MA process. In addition, lower conversion temperature (<700 °C) is favorable to maintain coke formation less than 20%. The analysis suggests that further efforts should be devoted to reduce overall capital cost and expand production scale. [ABSTRACT FROM AUTHOR]

The shift from conventional hydrogen production that utilised fossil-based energy towards a more sustainable practice is essential. Recently, the interest in utilising renewable hydrogen sources associated with bio-gas has risen. This work aims to develop a P-graph methodology for bio-hydrogen network synthesis, where oil refineries and ammonia plants act as bio-hydrogen sinks, while palm oil mills serve as the bio-hydrogen sources. The latter produces huge amount of palm oil mill effluent (POME) which may be converted to bio-hydrogen. The model is optimised with the aim to minimise the total network cost, whilst fulfilling the demand of all hydrogen sinks. Two case studies in Malaysia are used to illustrate the effectiveness of the proposed model. Results show that the overall network cost can be reduced by 45.6% (first case study) and 85.8% (second case study) when bio-hydrogen is supplied from the abundant POME in the study areas. Besides, the capability of the proposed P-graph framework in conducting uncertainty analysis and technology benchmarking study, are also demonstrated. Image 1 • A P-graph approach to synthesise the bio-hydrogen network is developed. • Bio-hydrogen network can be more economic feasible compared to the existing one. • Two case studies in Malaysia are used to illustrate the proposed method. • The framework can be used to analyse supply chain uncertainty. • The framework can be used to benchmark the feasibility of new technology. [ABSTRACT FROM AUTHOR]

Process systems engineering research focuses on the planning, design, operation, and safety of process systems rather than unit operations. In response to the rapid growth of the chemical process industry in the last 20 years in China, advanced system integration and process safety technologies are investigated and applied for better resource utilization, less environmental impact, and safer working places. In this regard, the review in this article consists of four main achievements: (1) process synthesis, (2) energy system integration, (3) water system integration, and (4) process safety management. The purpose of process synthesis and integration is to improve resource and energy utilization, at the same time lowering by-products and emissions. Optimization is conducted on process structure and operation, following the principles of resource coupling and energy cascade utilization. Typical examples are coupling of coal and hydrogen-rich resources and integration of coal-based polygeneration process of chemicals, electricity, and heat. Energy integration implements the coordinated optimization of total site energy systems. Reviews are made on specific methodologies based on the thermodynamics and applications of design and retrofit in ethylene, oil refining, and synthetic ammonia industries. There are energy savings by 10%–20% and yields increasing by 20%–30%. In addition, waste heat recovery and cold energy utilization are also important research areas. Reviews on the progress of water system integration and its industrial applications are also conducted. It includes the direct reuse, regeneration, and reuse/recycle in water systems and systems with internal water mains. Finally, safety management and technologies are also indispensable technological advancements of the process. The legislation system and the work safety-related standard system have been gradually established and enforced. Process safety research progress is reviewed, and questions are proposed for improving the accident prevention and safety management agenda. [ABSTRACT FROM AUTHOR]

A large number of potential technological alternatives exist for the development of microalgal biorefinery to produce a variety of end-products from microalgal biomass and their residues. The design of the promising biorefinery configurations considering preliminary and uncertain nature of technologies is one of the major biorefinery challenges, and it must be addressed systematically. This article presents key issues, challenges and opportunities for the modeling and optimization of microalgae-based biorefinery configurations. It reviews the processing pathways/networks for producing biofuels and various platform chemicals from microalgae with an emphasis on the development of the systematic modeling framework. Superstructure-based modeling and optimization can be a useful tool to identify the optimal/promising biorefinery configurations. Key components of the superstructure-based modeling framework are described, along with a comprehensive review of the existing studies on the superstructure-based optimization of biofuels/bioenergy production from microalgae. This paper also identifies potential perspectives for future research focusing on the application of the superstructure-based approach for the systematic design of sustainable microalgal biorefineries. Perspectives on the future integrated biorefineries considering carbon mitigation as well as heat and power integration are presented. Issues on sustainability and uncertainties modeling in the biorefinery design phase are also discussed. [ABSTRACT FROM AUTHOR]

Nylon, known for its outstanding physical properties, durability, and affordability, is in high demand across various industries. The majority of nylon is currently produced using petroleum-based raw materials, which causes negative environmental impacts such as greenhouse gas emission and fossil resource depletion. This has motivated research and development of eco-friendly production methods using biomass, we propose the environmental feasibility of kenaf-based nylon production strategy in the Republic of Korea. This study carries out a life cycle assessment (LCA) for analyzing the global warming potential (GWP) and fossil resource scarcity (FRS) of nylon 6,6 production from gamma-valerolactone (GVL) derived from kenaf. The life cycle inventory is analyzed based on the simulation data of the GVL-to-nylon 6,6 process and the two major environmental impacts are quantified when the biorefinery is operated at the Saemangeum agro-bio industrial cluster in Jeollabuk-do in Republic of Korea. The nylon 6,6 production in the Saemangeum can effectively reduce the GWP (61%) and FRS (67%) compared to the conventional nylon 6,6 production. Furthermore, if the GWP of the two materials used in the production of nylon 6,6 (HMDA, NaOH) can be reduced by 50%, the GWP per kilogram of nylon 6,6 produced will be reduced by 43% (1.91 kg CO 2 eq.). [Display omitted] • A 'greener' process for transformation of gamma-valerolactone derived from kenaf to Nylon 6,6 is studied. • The LCA is conducted to quantify the environmental impacts of nylon 6,6 production. • The green Nylon 6,6 reduces 61 % of CO 2 emission compared to the conventional nylon. [ABSTRACT FROM AUTHOR]

In the present work, two new, (multi-)parametric programming (mp-P)-inspired algorithms for the solution of mixed-integer nonlinear programming (MINLP) problems are developed, with their main focus being on process synthesis problems. The algorithms are developed for the special case in which the nonlinearities arise because of logarithmic terms, with the first one being developed for the deterministic case, and the second for the parametric case (p-MINLP). The key idea is to formulate and solve the square system of the first-order Karush-Kuhn-Tucker (KKT) conditions in an analytical way, by treating the binary variables and/or uncertain parameters as symbolic parameters. To this effect, symbolic manipulation and solution techniques are employed. In order to demonstrate the applicability and validity of the proposed algorithms, two process synthesis case studies are examined. The corresponding solutions are then validated using state-of-the-art numerical MINLP solvers. For p-MINLP, the solution is given by an optimal solution as an explicit function of the uncertain parameters.

Following the discovery of the least squares method in 1805 by Legendre and later in 1809 by Gauss, surrogate modeling and machine learning have come a long way. From identifying patterns and trends in process data to predictive modeling, optimization, fault detection, reaction network discovery, and process operations, machine learning became an integral part of all aspects of process design and process systems engineering. This is enabled, at the same time necessitated, by the vast amounts of data that are readily available from processes, increased digitalization, automation, increasing computation power, and simulation software that can model complex phenomena that span over several temporal and spatial scales. Although this paper is not a comprehensive review, it gives an overview of the recent history of machine learning models that we use every day and how they shaped process design problems from the recent advances to the exploration of their prospects.

• An energy-efficient and economically viable CO 2 to methanol process using solar energy. • The optimal operating conditions for maximizing methanol production are identified. • The processes show improved energy and carbon efficiencies, and net CO 2 reduction. • The minimum selling price of methanol by the proposed process is 0.94 $/kg. This study proposes and analyzes a novel methanol production process developed by integrating CO 2 hydrogenation and thermochemical splitting technologies. Using Sunshine-to-Petrol, which produces liquid hydrocarbons using solar thermal energy, as the baseline framework, we developed a highly energy-efficient methanol production process comprised of the solar field for CO 2 and H 2 O splitting using concentrated solar thermal energy, integrated with methanol production through the direct hydrogenation of CO 2 and CO. The optimal process configuration and operating conditions for maximizing the amount of methanol were established using a sequential quadratic programming. Consequently, the proposed process achieved a high energy efficiency of 15.5%, and the minimum selling price of methanol was established as 0.94 $/kg, accompanied by a 26% improvement over previous schemes and other CO 2 -to-methanol frameworks. Furthermore, we examined additional alternative scenarios to establish the optimistic conditions such that the minimum selling price of 0.53 $/kg is considered as a competitive price in the methanol market. [ABSTRACT FROM AUTHOR]

• Renewable resources pose new challenges and opportunities to process systems. • Computer technology would allow considering more details in the analysis. • Multidisciplinary approaches become key to make the most of opportunities. • Integration between design, scheduling, control, planning and supply lead the way. The incorporation of renewable energy sources to the market has brought a new golden era for process synthesis with challenges and opportunities. In this work, we give a brief review of the state of the art and then present challenges and future directions in this exciting area. The biggest driver is the rapid improvement in computer technology which greatly increases the number of factors that can be considered during the design process. Thus, some of the key future directions lie in integrating the design process with other aspects of process systems engineering, such as scheduling, planning, control, and supply chain management. In addition, sustainability is now a major consideration. The tools available to address these challenges are limited but we are in a position to develop them based on strong chemical engineering principles following a multidisciplinary approach with contributions from other disciplines including biology, biochemistry, computer science, materials, and chemistry. [ABSTRACT FROM AUTHOR]

Work and heat integration has emerged in the last decade as a promising area with a wide scope for research. Under that relatively new field, the synthesis of work and heat exchange networks (WHEN) is certainly an encouraging subject. This work presents a method for WHEN synthesis considering some aspects that were not approached in previous literature. Multiple electricity cost scenarios are considered and analyzed in the synthesis task. These are proposed according to different electricity production regimes, which are used by suppliers due to eventual changes in electricity production conditions (e.g. , low level in hydroelectric power plants reservoirs). Evidently, monthly electricity prices are affected under such regimes. In the model, multiple utilities use is possible. Utilities can be modelled as regular process streams (instead of the typical approach of fixed inlet/outlet temperatures in heaters/coolers). The model also comprises the use of piecewise linear approximations for enthalpy/temperature calculations. The solution approach is an enhanced meta-heuristic method. It could be observed that considering an intermediate electricity cost scenario (between optimistic and pessimistic predictions) for the WHEN synthesis stage may lead to smaller monetary losses in case of occurrence of other scenarios. • A new model for the synthesis of work and heat exchange networks is presented. • It considers multiple utilities and multiple scenarios for electricity costs. • In the model, utilities can be treated as regular process streams. • The model is solved via a meta-heuristic approach. • Different electricity-related scenarios led to important differences in solutions. [ABSTRACT FROM AUTHOR]

Because of the ever increasing complexity of processing systems, the reliability becomes a key aspect in selecting the best process during process design. This is especially crucial if heat integration is also part of process design, because it increases the complexity of the system that may reduce its reliability. Since the selection of a process network during synthesis has major influence on the cost, the reliability, and the level of heat integration, these three items must be considered simultaneously in process synthesis. To do so, a general modeling tool is required that simultaneously covers all three areas. In the present work, three formerly developed modeling tools and solution procedures are adapted and integrated, all of them are related to the P-graph framework. Because of their common basis, their integration is natural and highly effective. In addition to the three aspects considered here in synthesizing a process, there are further features to be considered in the final selection of the best process during process design (e.g., controllability and sustainability). The capability of the method in generating all or the n-best networks serves this purpose. • Process synthesis simultaneously considering cost, heat integration, and reliability. • Process synthesis with the n-best solutions. • Processing system with multiple operations modes. [ABSTRACT FROM AUTHOR]

In this paper, we present both academic and industrial perspectives on the research and applications of Process Systems Engineering (PSE). After a brief introduction on the history of PSE, we describe the major research accomplishments in the areas of process simulation, conceptual design and synthesis, process control, process operations and optimization. This is followed by a discussion on the industrial impact and benefits of this work, which have made it to be industrially relevant. Next, we address the issue of the current standing of PSE both in academia and in industry, and for which we present results of a survey conducted by the authors. Finally, we close with a discussion on future challenges in PSE from both the industrial and academic perspectives. [ABSTRACT FROM AUTHOR]

• An extended framework for integrated process synthesis-intensification is presented. • Phenomena based synthesis methodology is extended in terms of application. • Multi-scale approach: unit operation, task and phenomena. • The framework is applied to one industrially relevant case study - bio succinic acid. • Innovative and more sustainable process alternatives are identified for the production of bio succinic acid. A practical way to generate sustainable design alternatives, counter ongoing challenges and future problems is to develop methods that are generic in nature and can be applied over a wide search space to determine innovative and hybrid/intensified unit operations (unit-ops). In this research, a systematic framework based on a 3-stage approach for sustainable process design is presented and its application to generate intensified and more sustainable alternatives highlighted. Within this framework, the phenomena-based synthesis methodology is extended in terms of a wider range of applications and ability to determine more feasible solutions. The framework with the extended methodology is capable of generating innovative solutions involving solid-liquid and liquid-liquid systems in addition to vapor-liquid and membrane systems that could be generated previously. Further, the phenomena database is expanded so that with the new list of phenomena and basic structures, new and intensified unit operations (membrane crystallization, membrane bio-reactor to name a few) are generated. The applicability of step by step method available through the framework is demonstrated through a case study involving the production of bio-succinic acid. In this case study, a novel superstructure network of alternatives is generated, from which an optimal processing route is identified. This processing route is then designed and analysed to identify process bottlenecks, based on which a set of targets for improvement are defined. Then, by applying an extended phenomena-based synthesis methodology; non-trade off, more sustainable and intensified solutions to produce bio-succinic acid are generated and verified through rigorous processes simulation. [ABSTRACT FROM AUTHOR]

• A new framework for heat exchanger networks retrofit is presented. • An extended superstructure is used to derive the retrofit model. • The model comprises features such as stream splits, sub splits and cross flows. • A meta-heuristic approach is adapted to handle the new retrofit model. • The solutions identified present lower costs than those reported in the literature. Retrofit of heat exchanger networks (HEN) is an important subject in the heat integration field. Several studies on the matter use Pinch-based techniques and mathematical models solved with deterministic methods. This work aims at providing an alternative method based on a model derived from a broad superstructure solved with a meta-heuristic approach. The referred superstructure comprises features not present in most HEN studies based on mathematical programming. Structural options such as the possibility of streams sub-splitting, partial mixing, serial units at a single stream branch and the allocation of heaters/coolers at intermediate positions are possible. The methodology was applied to three large-scale industrial case studies from the literature, based on oil refineries. Two of them contained streams with variable heat capacity. In all examples, the present methodology was able to outperform previous studies regarding total annual costs, proving an interesting alternative to methods that are currently applied in the literature. [ABSTRACT FROM AUTHOR]

For our works, Mass Exchangers (MEs) are membrane equipment that exchange some component between two streams in a countercurrent arrangement. In previous works these were proposed to use them (with the goal of hydrogen recovery, energy saving and waste minimization) at different stages of the hierarchical decision procedure for process synthesis by Douglas: at an early design stage, when deciding the recycle structure of the process (resulting in considerable changes in the process structure); or at a final design stage, before deciding the mass and energy integrations of process streams (resulting in minor changes in the process structure). The heuristic allocation of MEs was used independently at both design stages in previous works, with the goal of comparing with other design alternatives reported in the literature that use membranes in the conventional configuration (one feed stream and two exit streams; retentate and permeate). In contrast, the present work compares the results of using MEs, when they are used individually at both design stages, and when they are used jointly at both design stages, in different configurations. For the case study example (the HDA Process), the use of a ME at an early design stage reduces the fresh hydrogen consumed by 3.37%, and the recycle compressor power by 4.09%. The use of a ME at a final design stage reduces the fresh hydrogen consumed by 31.64%, but it does not reduce the recycle compressor power. The joint use of the MEs at both design stages reduces the fresh hydrogen consumed by 14.54%, and the recycle compressor power by 2.91%. The joint use of MEs at both design stages retains the principal benefits of its use at early and final design stages (energy saving and hydrogen recovery, principally), so when both a reduction in the fresh hydrogen consumed and in the recycle compressor power is desired, it is the most appropriate option. Image 1 • The heuristic allocation of MEs, reduces the hydrogen and energy consumed. • Recycle compressor need lower brake power. • Additional recycle compressor is not necessary to recover hydrogen. • The joint use of MEs shows the best performance for the exchange membrane area. [ABSTRACT FROM AUTHOR]

Abstract This study compares two processes to produce γ-valerolactone from lignocellulosic biomass: Process A is single processing of cellulose by using lignin-derived propyl guaiacol solvent; Process B is simultaneous processing of cellulose and hemicellulose by using γ-valerolactone solvent derived from cellulose and hemicellulose. Large-scale processes that integrate conversion and separation technologies are assembled based on experimental data, and daily GVL productions are 98 tonnes (Process A) and 375 tonnes (Process B). A heat-exchanger network is designed to reduce heating requirements, and the energy efficiencies are 13.3% (Process A) and 37.3% (Process B). Techno-economic assessment is conducted to identify the economic feasibility. The minimum selling price of γ-valerolactone for Process A (US$ 2.36/kg) and Process B (US$ 0.88/kg) are comparable with market price. The difference in the minimum selling prices is mainly caused by effective utilization of the hemicellulose in lignocellulose biomass in Process B. Sensitivity analyses present that changes in key parameters could not reverse the minimum selling price of γ-valerolactone between the two strategies, but the conversion of xylose to value-added chemical in Process A makes this possible. This study shows that development of conversion technologies to effectively utilize the hemicellulose in lignocellulosic biomass is critical to improve process economics. Highlights • Two different solvent strategies for catalytic GVL production are proposed. • Two strategies uses different LB-derived solvents (PG and GVL). • Large scale processes are designed based on the experimental data. • Economic feasibility of different solvent strategies are analyzed. • Effective utilizing major components in LB is critical to improve process economics. [ABSTRACT FROM AUTHOR]

Highlights • Graphic synthesis method for multi-technique separation sequences was established. • Dominant feed regions were determined for refinery gas separation techniques. • Near-optimal separation sequences can be readily synthesized by graphic method. • Hybrid process was developed to treat refinery gases with recovery exceeding 90%. • Laborious work to screen numerous sequences was saved by graphic synthesis method. Abstract In petroleum and chemical industries, many valuable species are depleted into various refinery gases. In order to fractionate and reclaim these valuable components efficiently and sufficiently, it is necessary to integrate diverse separation techniques together. The major obstacle to synthesize and optimize such a multi-component and multi-input process is the combinatorial explosion. In this research, graphic synthesis method is established to construct the multi-technique integration processes, in which the optimum or near-optimum sequence would be programmed to couple high efficient separation unit operations together to improve efficiency. As the support, three technical measures are summarized: the pseudo-ternary mixtures of H 2 , light hydrocarbons and fuel gases are proposed to depict refinery gases, after ranking species with their separation characteristics and belongings in products, so that the composition space can be visualized into triangular coordinate system; the dominant feed ranges for the pivotal separation units, i.e., adsorption, condensation, glassy and rubbery polymeric membranes, are determined after efficiency analysis, in which the represented technique is more efficient than the others for the composition matched feedstock; the shortcut calculation and the visualized representation with vectors in triangular coordinate system are created to quickly estimate separation operations, owing to their selectivity unique to a certain component group. Without laborious work to screen numerous sequences, this method programs recovery strategies and synthesizes processes appropriately and quickly. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Developed optimization model to assess different stillage valorization strategies. • Studied the impact of technical, economic, and energy parameters on economics. • Stillage utilization is optimized to achieve energy self-sufficient biorefinery. • Target technology parameters for economic and energetic feasibility are established. Abstract The goal of this study is to evaluate the economics and energy efficiency of different biorefinery configurations which include stillage valorization strategies for bioproducts synthesis. Specifically, a mixed-integer nonlinear programming (MINLP) model is developed to identify the optimal process network, and the impact of various parameters (e.g., bioproduct selling price, production cost, and energy requirement) on the performance of the biorefinery is investigated. Results show that the optimal strategy leading to a minimum ethanol selling price of $3.44/GGE includes γ-valerolactone deconstruction, glucose and xylose co-fermentation, heat and power generation, and does not include stillage valorization. Economic analyses indicate that the stillage valorization becomes economically viable at bioproduct selling prices above $2.0/kg for a base unit production cost and conversion coefficient of $2.0/kg bioproduct and 0.3 kg bioproduct/kg sugars, respectively. Further studies suggest that under certain scenarios, the biorefinery does not generate sufficient energy if all stillage is utilized for bioproducts production. Therefore, the utilization of stillage has to be optimized in order to achieve an energy self-sufficient biorefinery. Finally, analyses are performed to study how improvements in combinations of parameters can lead to lower cost and higher energy efficiency. [ABSTRACT FROM AUTHOR]

Highlights • Proposed strategy to devise configuration then optimize conversion and temperature. • Implemented on case study of a real-world refinery in Kuwait. • Obtained resulting configuration that agrees with industrial practice. Abstract This work presents a mixed integer nonlinear programming (MINLP)-based superstructure optimisation approach to synthesize an optimal petroleum refinery topology or configuration for large-scale grassroots refinery systems. We develop a superstructure to include many possible prospective configurations and formulate rigorous models for the 32 commercial refinery processes that constitute the configurations, which gives rise to a convex MINLP model. The objective function is to maximize the total refinery profit for a given crude oil feed subject to material and energy balance constraints. We apply a two-level optimisation procedure: a master module to construct configurations from the superstructure and a submodule to optimize the process unit conversions and product temperatures of the configurations. A numerical example based on an actual operating refinery in Kuwait is illustrated to implement the approach with a resulting configuration that agrees with real-world practices. [ABSTRACT FROM AUTHOR]

Highlights • A framework for work and heat exchange networks synthesis is presented. • Work and heat recovery superstructures are coupled with a master matrix. • A meta-heuristic approach is adapted to solve the derived model. • The method is applied to examples based on real cases. • Solutions to the examples have lower costs than those reported in the literature. Abstract Energy integration is a matter of substantial importance in process engineering. Much attention was given in the last decades, in special, to heat recovery. However, recently, simultaneous work and heat recovery has arisen as an important area of study in process engineering. It has been demonstrated that work and heat exchange networks (WHEN) may improve the energetic efficiency of processes such as liquefied natural gas (LNG) production. Optimization-based frameworks for WHEN synthesis developed so far are based on deterministic approaches and commercial solver implementations. This work aimed to present a novel alternative framework based on a matrix-based implementation fit for the use of a meta-heuristic solution approach. The superstructure employed is inspired on previous literature and extended for a broader analysis. The method was applied to three examples, being two based on real processes. In benchmark tests, the approach was able to outperform all other solutions reported with respect to total annual cost, the objective function adopted in these studies. [ABSTRACT FROM AUTHOR]

Abstract The production and demand for plastic products is set to only increase in the near future, despite efforts to curtail this demand. This increased demand and production comes with an increase in plastic waste, which already sees millions of tonnes discarded into landfills every year. Growing concern over the effects of this waste on the world's ecosystems has led to urgent interest in technologies for chemically converting waste plastic into other products. This manuscript uses process synthesis techniques to analyse and compare the relative performance of two commonly used chemical conversion processes: polyethylene pyrolysis and polyethylene gasification. This analysis technique is unique in that energy forms the basis of the analysis but also allows environmental and economic concerns to be considered simultaneously. It was found that pyrolysis processes are more in line with the goal of a cyclic economy for waste plastic, but that gasification processes can offer higher revenue through the production of alternate chemical products. The potential profits generated from these waste plastic processing strategies was found to be between 50 and 360 USD/ton of polyethylene, demonstrating a high economic value on what is, at present, a waste product. Highlights • An energy focused analysis is used to compare waste polyethylene conversion processes. • Pyrolysis of waste polyethylene achieved greater carbon and energy efficiencies. • Gasification achieves greater selectivity and revenue from hydrocarbon products. • Pyrolysis is preferable for a "cyclic economy". • Gasification is preferable when targeting speciality chemicals. [ABSTRACT FROM AUTHOR]

This paper presents a model-based optimization approach to design a grassroots petroleum refinery for heavy oil processing including residue treating and upgrading. The focus is to determine an optimal refinery configuration to produce light products from an atmospheric residue stream. The proposed linear model can consider a large number of heavy oil processing technologies (more than 70) including multiple operating modes to arrive at a configuration that meets an objective of maximizing profit or a certain fuel type production. Computational results show trends in agreement with real-world practice for residuum refining applications, thus contributing to substantiating practicality of the approach. [ABSTRACT FROM AUTHOR]

Highlights • An algorithm for synthesis of reaction–separation system alternatives is presented. • The algorithm is an expansion of previously presented, Reaction/Distillation matrix. • The algorithm includes multiple reactions with any number of components. • The presented algorithm supports systems having binary azeotropes. • The algorithm has been implemented on an ethylene hydration process. Abstract Reaction/Separation systems are very important in chemical industries and synthesis of all possible configurations for these systems is necessary for finding the best process alternative. An algorithm for synthesis of different alternatives for reaction–distillation systems is presented in this paper. The presented algorithm is a developed version of the Separation Matrix which has been introduced for generation of different distillation sequences. An initial version of the Reaction/Distillation matrix for a two-component reaction prevailing within a four-component system has already been introduced by the authors. The current research is the expansion of the previous work to include multiple reactions in a system containing any number of reactive and non-reactive components. This algorithm can also generate the sequences including components forming binary azeotropes. For performance evaluation purposes, a case study including two reactions is presented in which a binary azeotrope is formed between two components. The possible sequences for the system are generated using the introduced algorithm and the obtained sequences are simulated and compared in terms of total annual cost. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • A survey of the state-of-the-art process systems engineering (PSE) approaches for process intensification. • An overview of the development of various process intensification technologies. • Survey of recent advances in modeling, design, and synthesis of intensified systems. • Assessment methods for the controllability/operability/safety performance of intensified process systems. Abstract Process intensification offers the potential to drastically reduce the energy consumption and cost of producing chemicals from both bulk and distributed feedstocks. This review article aims to offer an extensive survey on state-of-the-art process systems engineering (PSE) approaches for process intensification. From both academic and industrial perspectives, this paper provides an overview of the development of various process intensification technologies, specifically those under the categories of separation, reaction, hybrid reaction/separation, and alternative energy sources. A current status analysis in the areas of modeling and simulation is then provided. An indicative list of PSE publications specialized on process intensification is presented to illustrate the progresses made so far towards the deployment of novel process intensification technologies. We also highlight some recent advances for the modeling, design, and synthesis of intensified systems, as well as for the assessment of their controllability/operability/safety performance. Key open questions in these areas include: (i) how to systematically derive intensified designs, and (ii) how to ensure the operability and optimality of the derived intensified structures while delivering their expected functionality. [ABSTRACT FROM AUTHOR]

Highlights • Superstructure of integrated biorefinery in pulp and paper industry was developed. • It includes pulping, biochemical production and black liquor utilization sections. • Lignocellulosic biomass extracted from eucalyptus and bagasse are the feedstocks. • Potential of integrated biorefinery process was illustrated in three scenarios. • Integrated succinic acid and lactic acid can improve profitability. Abstract This work aims at developing sustainable processes for pulp and paper industry by integration of the biorefinery concept to an existing pulp and paper process. A systematic methodology employing a superstructure-based process synthesis approach is employed with support from computer-aided tools to determine potential pathways for a long-term sustainable growth objective. A superstructure of the multi-product biorefinery process network for the pulp and paper industry is developed. It is divided into three sub-networks, a chemical pulping section, a biochemical production section and a black liquor utilization section. Superstructure optimization is performed with the objective to maximize profit to determine optimal integrated networks for three scenarios. The obtained results provide useful insights for further development of the optimal networks as sustainable integrated biorefinery combined with pulp and paper mills. Graphical abstract Image, graphical abstract [ABSTRACT FROM AUTHOR]

An apparent kinetic model for the chemical vapor deposition of SiO2 from tetraethyl orthosilicate (TEOS) and O2 was developed in a poorly investigated range of operating conditions, that is, at atmospheric pressure and between 350 and 500°C, based on literature survey and experimental results obtained in a hot wall tubular reactor. The kinetic model was implemented into the computational fluid dynamics code FLUENT and validated both in shape and value by comparison with experimental deposition rate profiles. It reveals that for the conditions tested, a possible mechanism of SiO 2 deposition involves two intermediate species formed from TEOS homogeneous decomposition, the first one being active from 300°C and the second one contributing to deposition for temperatures higher than 370°C. The calculated local profiles of gas flow, gas temperature, species mass fraction, and silica deposition rate indicate that the first intermediate species leads to marked film thickness gradients, the second one being more stable as producing uniform thicknesses. © 2018 American Institute of Chemical Engineers AIChE J, 64: 3958–3966, 2018 [ABSTRACT FROM AUTHOR]

• A synthesis problem for separating ethanol-water mixtures using hybrid membrane distillation process structures was proposed. • A low aggregation superstructure was adopted in the synthesis problem. • The proposed process structures were superior in terms of utility cost and Total Annual cost savings compared with the pressure swing an extractive distillation processes. Conventional distillation is the most used unit operation to separate zeotropic mixtures. However, it is combined other unit operations to separate azeotropic mixtures. This work proposes a synthesis and intensification framework to obtain hybrid membrane distillation process structures. The synthesis problem was represented by a low aggregation superstructure comprised of functional modules. Then, the superstructure was reformulated as a Mixed Integer Linear Programming (MILP) problem to derive the optimal structure. The synthesis problem does not consider any pre-established process structure or connectivity; therefore, the optimal solution must be interpreted, simulated, and validated to generate a known process structure. Finally, the validated structure was post-optimized to fine-tune the detailed design of the process structure. The presented framework was applied to separating an ethanol/water mixture. The obtained solutions attained high energy and cost savings compared to the typical pressure swing and extractive distillation. [ABSTRACT FROM AUTHOR]

Process synthesis usually determines the normal operation of the process. In addition to the cost, recently, sustainability has also become essential in selecting the process. In case of failures of some redundant operating units of the process, it may still be operational as a non-normal operation. This work shows that the sustainability performance of a process in non-normal operation can be much worse than that of the normal case. Consequently, during process synthesis, it is essential to consider the sustainability of a process for both normal and non-normal operations. The current work is the first in offering synthesis of a process network taking into account a pre-specified limit of the process sustainability indicator for both normal and non-normal modes. This synthesis procedure is formulated in a general way, to interface with any sustainability indicator, expressed as a scalar, here Sustainable Process Index has been used in the case studies. The presented method is illustrated on two case studies to showcase the capability of synthesizing processes for multiple operation. The obtained results indicate that it is possible to simultaneously reduce environmental impact and process cost by more than 20%, by appropriate modification of the operating modes. [Display omitted] • Multi-objective optimisation for cost, reliability, and sustainability. • Simultaneous consideration of the indicators allows integrated optimisation. • Non-normal operations are also examined and evaluated according to each indicator. • P-graph framework is applied to generate n-best networks satisfying the constraints. • Simultaneous reduction in environmental impact and process cost by more than 20%. [ABSTRACT FROM AUTHOR]

• Developed an integrated process synthesis framework for process design. • The framework solves the process synthesis problem by integrating reaction synthesis and advanced separation techniques. • Three case studies are solved, including both new and retrofitting designs. • The framework can identify the most promising reaction pathway with its separation flowsheet for a given target product. • Process retrofitting with innovative separation techniques can highly improve process sustainability. With the increasing concern of the competitive market and carbon emissions, a sustainable, efficient process design becomes more and more important. The task of sustainable process design is to find efficient configurations and operating parameters to produce products or utilize materials. Currently, the scientific community's major focus is on separation synthesis, which aims to identify the best downstream separation configurations through different methods such as optimization, heuristic, and hybrid methods. Besides, innovative separation techniques with lower capital/operating costs and carbon emissions were proposed and identified to further improve the downstream process performance. However, most of the separations synthesis methods were based on conventional unit operations and usually applied for generating sustainable processes with a given reaction pathway without considering the possibilities of different raw materials. Generally, to produce a given target product, multiple reaction pathways are available, and each reaction pathway leads to different downstream processes. Also, applying intensification in the early stages of process design, e.g., separation synthesis, can generate sustainable process flowsheets with higher energy efficiency and lower environmental impact. This work aims to develop an integrated process synthesis framework, which includes reaction synthesis for the reaction pathways selection and separation synthesis involving intensified/hybrid units. So, for the new process design, given the product one needs to produce, this framework could identify the optimal reaction pathway with its best separation route. The developed framework was used to solve three case studies, including the new process design of dimethyl carbonate (DMC) production and retrofitting design of cumene and styrene production. For all the case studies, the framework was able to generate multiple innovative solutions that are sustainable and energy-efficient. [ABSTRACT FROM AUTHOR]