Computer aided product design tool for sustainable product development

A computer aided product design (CAPD) tool is proposed that finds mixtures matching target properties. Genetic algorithm crossover and mutation operators are completed with insertion or deletion operators adapted for side branches. A new substitution operator is devised for cyclic molecules. The mixture fitness is evaluated by a weighted sum of property performances. Molecules are represented by molecular graphs. They are split into molecular fragments which are built from polyatomic groups. Molecules or molecular fragments can be fixed, constrained or left free for building a new molecule. Building blocks are chemical functional groups or bio-sourced synthons. A specific coding of hydrogen-suppressed atoms is devised that can be used with various property estimation models where atom connectivity information is required. Illustration is provided through three case studies to find levulinic, glycerol and bio-based derivatives as substitute for chlorinated paraffin, methyl p-coumarate ester solvent and blanket wash solvent, respectively.     

Conceptual design of distillation processes for mixtures with distillation boundaries: I. Computational assessment of split feasibility

Geometric design methods for the conceptual design of azeotropic distillation processes are fast and efficient tools for the economic screening of different process alternatives. This two‐part series presents a fully automated conceptual design method for finding an optimal recycle policy for the separation of mixtures with distillation boundaries. It does not require visualization and graphical inspection of residue curve or pinch maps and is, hence, not limited to ternary mixtures. The first part introduces a fully computational geometric split feasibility test based on bifurcation analysis. This bifurcation‐based feasibility test can be used as a valuable stand‐alone tool for the assessment of different separation options. It is also one of the core elements of the recycle optimization discussed in the second part of this series. © 2010 American Institute of Chemical Engineers AIChE J, 2011     

Experimental and computational design tools for industrial drying processes: Challenges in process-limit prediction

The coating and drying of inks and slurries are important steps to manufacture a plethora of products. Drying processes, particularly, comprise energy-intensive steps that affect product cost and quality. Prior work has highlighted failures of various multicomponent diffusivity models to conserve mass in dryer modeling and challenges in predicting process limits given variability in published values of key thermodynamic parameters. Herein, we develop a computational model and benchtop drying experiments to investigate these concerns for drying polymer-laden coatings. Model predictions of process limits in a single-zone drying oven demonstrate that published variability in Flory–Huggins parameter yields large variations in predicted operating temperatures above which blistering occurs. This indicates that caution should be exercised when choosing approaches to obtain or predict the Flory–Huggins parameter, and that both benchtop drying experiments and a set of additional experiments, such as sorption experiments, are needed to fully characterize and optimize a given drying process.     

Optimal design of solvents for extractive reaction processes

It is well known that solvents can have significant effects on rates and equilibrium compositions of chemical reactions. The computer‐aided molecular design (CAMD) of solvents for heterogeneous liquid phase reactions is challenging due to multiple solvent effects on reaction and phase equilibria. In this work, we propose a CAMD methodology based on a genetic algorithm (GA) for identifying optimal solvents for liquid phase reactions where the objective is to maximize the reaction equilibrium conversion. In particular, a novel molecular encoding method is introduced to facilitate the construction and evaluation of solvent molecules in a defined structure space. The reliability of the method for fast identification of optimal reaction solvents is demonstrated for a selected biphasic esterification reaction. The proposed approach opens up new perspectives for intensifying extractive reaction processes via the purposeful design of solvent molecules. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3238–3249, 2016     

Systematic methods and tools for design of sustainable chemical processes for CO2 utilization

A systematic computer-aided framework for sustainable process design is presented together with its application to the synthesis and generation of processing networks for dimethyl carbonate (DMC) production with CO₂ utilization. The framework integrated with various methods, tools, algorithms and databases is based on a combined process synthesis–design–intensification method. The method consists of three stages. The synthesis-stage involves superstructure based optimization to identify promising networks that convert a given set of raw materials to a desired set of products. The design-stage involves selection and analysis of the identified networks as a base case design in terms of operational feasibility, economics, life cycle assessment factors and sustainability measures, which are employed to establish targets for improvement in the next-stage. The innovation-stage involves generation and screening of the more sustainable alternatives through a phenomena-based process intensification method. Applications of the framework are highlighted for the DMC production process.     

Computer‐aided design of ionic liquids as solvents for extractive desulfurization

Although ionic liquids (ILs) have been widely explored as solvents for extractive desulfurization (EDS) of fuel oils, systematic studying of the optimal design of ILs for this process is still scarce. The UNIFAC‐IL model is extended first to describe the EDS system based on exhaustive experimental data. Then, based on the obtained UNIFAC‐IL model and group contribution models for predicting the melting point and viscosity of ILs, a mixed‐integer nonlinear programming (MINLP) problem is formulated for the purpose of computer‐aided ionic liquid design (CAILD). The MINLP problem is solved to optimize the liquid‐liquid extraction performance of ILs in a given multicomponent model EDS system, under consideration of constraints regarding the IL structure, thermodynamic and physical properties. The top five IL candidates preidentified from CAILD are further evaluated by means of process simulation using ASPEN Plus. Thereby, [C₅MPy][C(CN)₃] is identified as the most suitable solvent for EDS. © 2017 American Institute of Chemical Engineers AIChE J, 64: 1013–1025, 2018     

Data-driven integrated design of solvents and extractive distillation processes

As property and process models with many variables need to be considered, integrated computer-aided molecular and process design (CAMPD) problems are computationally expensive. An efficient CAMPD approach is proposed for the simultaneous design of solvents and extractive distillation (ED) processes based on a data-driven modeling strategy. First, artificial neural network (ANN)-based process models are trained to replace the physical models conventionally used in CAMPD. Subsequently, optimization is performed to maximize process performance, through which optimal solvent properties and corresponding optimal process parameters are obtained. Then, real solvents approximating the optimal property values are identified from a large solvent database. Rigorous simulations of the ED process are performed to evaluate the performance of the optimal solvents and corresponding process parameters. Further economic evaluation (6.11% lower annual cost compared to the benchmark process) and chemical hazard assessment confirm that acetylacetone is a promising solvent for the ED separation of 1-butene from 1,3-butadiene.     

Conceptual design of distillation processes for mixtures with distillation boundaries. II. Optimization of recycle policies

Geometric design methods for the conceptual design of azeotropic distillation processes are fast and efficient tools for the economic screening of different process alternatives. The second article of this two‐part series presents a novel optimization‐based conceptual design framework for azeotropic distillation processes, which allows a rapid screening of the different process alternatives with respect to feasibility and economic incentive. The design framework is based on the economic assessment of distillation columns by the rectification body method. The feasibility limits imposed by the azeotropes are incorporated using the split feasibility test introduced in the first part of this series. The application of the framework is highlighted with several ternary and quaternary process alternatives for the production of high‐purity alcohols. © 2010 American Institute of Chemical Engineers AIChE J, 2011     

Computer simulation of membrane processes: ultrafiltration and dialysis units

An algorithm for computer simulation of membrane processes such as ultrafiltration and dialysis has been developed using a simplified finite volume approach. The technique used is slightly different from the standard finite difference, finite volume and finite element methods where all the parameters are considered at fixed nodal points. In the present approach the entire flow chamber is divided into a large number of volume elements and each element is considered to be an independent unit (similar to finite volume method). All mass flux and velocity components are calculated at the boundaries whereas concentration is considered at the center of the element. Thus, unlike FDM, FVM, and FEM, in the present approach nodal points for velocity and concentration are different. It has been observed that this method is more accurate and fast and requires less computational effort.     

Integration of microbial and chemical processing for a sustainable metallurgy

Bioprocessing for the recovery of metal from divergent resources using the microbial strategy has emerged as a green technology in metallurgical operations. The limitations to maintain the ideal condition for bacterial growth with slow kinetics, however, have been considered as major obstacles to bioprocessing being implemented more widely. This can be overcome by integrating the microbes with a chemical processing route. The available reports on recent developments in hybrid bio‐chemical processing of both primary and secondary resources have presented promising results, exhibiting the potential for use in large‐scale metallurgy. In this context, reviewing the factors of the hybrid process would benefit from knowledge acquired in fundamental studies. The present review focuses on bio‐chemical process integration using eco‐friendly design tools for treating the difficult to extract resources and complex spent materials as well. Furthermore, the potential of hybrid technology has been evaluated by establishing an economic model as a case study which encompasses features of economic development, environmental consideration and societal matters to achieve process sustainability. © 2017 Society of Chemical Industry     

A methodology for the sustainable design and implementation strategy of CO2 utilization processes

This work presents a systematic methodology that has been developed for the design of sustainable CO₂ utilization processes that can mitigate CO₂ and also guarantee profitability. First, the three-stage methodology, evaluation criteria and applicable tools are described. Especially, the process design and analysis is discussed as only limited amounts of process data is available for determining the optimal processing path and in the third stage the issue of implementation strategy is considered. As examples, two CO₂ utilization methods for methanol production, combined reforming and direct synthesis are considered. Methanol plants employing such methods are developed using synthesis-design and simulation tools and their evaluation indicators are calculated under various implementation strategies. It is demonstrated that integrating or replacing an existing conventional methanol plant by a combined reforming method represents a sustainable solution. Additionally, producing methanol through direct hydrogenation is a promising way to convert CO₂ when cheap H₂ feeds are available.     

Technology evaluation and decision making for sustainability enhancement of industrial systems under uncertainty

Technology‐based sustainability enhancement is a key approach for industrial sustainability realization. However, identification of effective technologies for any industrial system could be very challenging. If the available data and information about the industrial system and technologies are incomplete, imprecise, and uncertain, then technology identification could be very difficult. In this article, the authors introduce a simple, yet systematic interval‐parameter‐based methodology for identifying quickly superior solutions under uncertainty for sustainability performance improvement. The methodology is general enough for the study of sustainability enhancement problems of any size and scope. A case study on sustainable development of biodiesel manufacturing demonstrates methodological efficacy. © 2012 American Institute of Chemical Engineers AIChE J, 58: 1841–1852, 2012     

Integrated design of agricultural and industrial processes: A case study of combined sugar and ethanol production

Bioethanol production from molasses has advantages in greenhouse gas emissions because of its energy acquisition from bagasse. However, the improvement of bioethanol productivity is challenging; while each elemental technology option can be greatly improved, the trade‐offs between the production of raw sugar and bioethanol are complex. This issue should be addressed through the optimization of the whole system, including both agricultural and industrial processes. In this study, we constructed a model of combined raw sugar and bioethanol production from sugarcane considering agricultural and industrial technology options. Data were acquired through a detailed investigation of actual sugar mills. Case studies on the redesign of combined raw sugar and bioethanol production demonstrated that the simultaneous implementation of both technology options increases production of food, materials, and energy from plant‐derived renewable resources, thus demonstrating the effectiveness of the interdisciplinary approach. © 2016 American Institute of Chemical Engineers AIChE J, 63: 560–581, 2017     

点源有机毒物污(废)水排放的生态风险管理技术分析

我国目前普遍采用COD、BOD等宏观污染控制指标监控点源污染,缺乏针对污(废)水中痕量有毒物质尤其是有机毒物实施有效的管理与控制。基于此,在评述了全废水试验(WET)、毒性鉴别评价(TIE)和毒性削减评价(TRE)3种宏观分析技术在美国、英国等国家生态风险评价与管理中的研究历史及发展近况的基础上,简要分析了一些发达国家应用(Q)SAR数学模型和分子生态毒理学两种微观评估方法对有机毒物实施有效控制的情况,建议我国应该加强面向点源有机毒物污(废)水排放的生态风险管理的技术与政策研究。     

A survey on applications of optimization-based integrating process design and control for chemical processes

Process design and control are closely related to each other in chemical engineering activities. Traditionally, process design and control system design are carried out in sequence. However, the integration of process design and control (IPDC) can bring greater economic benefits and process dynamic performance than traditional sequential design methods. This is true, particularly for modern chemical processes, in which various process units become more interacting and compact owing to the widespread use of heat integration and recycled streams, and the resulted impacts between process design and control begin to significantly influence both the capital and operational costs. Recently, considerable studies about the IPDC for chemical processes have been reported in published literature. The purpose of the paper is to survey the applications of optimization-based integrating process design and control for chemical processes. Firstly, attention has been focused on the applications of IPDC to different process units, for example, chemical reactors and separation columns. Then, the survey is extended to the applications of IPDC to plant-wide chemical processes. Finally, the future research challenges in the application of IPDC to chemical processes have been briefly discussed.     

Integrating data‐based modeling and nonlinear control tools for batch process control

A data‐based multimodel approach is developed in this work for modeling batch systems in which multiple local linear models are identified using latent variable regression and combined using an appropriate weighting function that arises from fuzzy c‐means clustering. The resulting model is used to generate empirical reverse‐time reachability regions (RTRRs) (defined as the set of states from where the data‐based model can be driven inside a desired end‐point neighborhood of the system), which are subsequently incorporated in a predictive control design. Simulation results of a fed‐batch reactor system under proportional‐integral (PI) control and the proposed RTRR‐based design demonstrate the superior performance of the RTRR‐based design in both a fault‐free and faulty environment. The data‐based modeling methodology is then applied on a nylon‐6,6 batch polymerization process to design a trajectory tracking predictive controller. Closed‐loop simulation results illustrate the superior tracking performance of the proposed predictive controller over PI control. © 2011 American Institute of Chemical Engineers AIChE J, 2012     

Ensemble-docking approach on BACE-1: pharmacophore perception and guidelines for drug design

Beta-secretase (BACE-1), a key enzyme in the etiopathogenesis and progression of Alzheimer disease, is the focus of medicinal chemistry efforts both in the pharmaceutical industry and in academia. Despite the availability of diverse peptidomimetic BACE-1 inhibitors, nonpeptidic compounds suitable for oral delivery and transport across the blood brain barrier are in great demand. Herein, a number of active and structurally diverse inhibitors were selected and subjected to an ensemble-docking process into five BACE-1 X-ray structures. The calculated bioactive conformations of these inhibitors allowed us to build an exhaustive pharmacophore model, which captures both the common geometric and electronic features essential for enzyme inhibition. The model is intended to aid the rational design of new BACE-1 inhibitors. Furthermore, a comparison of BACE/cathepsin D X-ray structures was made to provide guidelines for the design of BACE-selective inhibitors.     

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     

Integrating process and power grid models for optimal design and demand response operation of giga-scale green hydrogen

Electrolysis-based hydrogen production can play a significant role in industrial decarbonization, and its economic competitiveness can be promoted by designing demand response operating schemes. Nevertheless, the scale of industrial supply plants may be significantly large (on the order of gigawatts), meaning that electricity prices cannot be treated as an input for scheduling problems, that is, the “price taker” approach. This article presents a framework for the optimization of a large-scale, electricity-powered hydrogen production facility considering its integration with the power grid. Using a computational case study, we present an iterative scheme for integrating the process model with a model for power grid optimization and capacity expansion, taking the popular GenX model as an example.     

复杂化工过程失配子模型深度诊断与修正算法

针对复杂化工生产过程中多变量预测控制系统发生模型失配导致控制性能下降造成的产品质量波动的问题，研究了过程失配子模型深度诊断与模型修正方法。考虑到复杂化工生产过程中被控变量为控制通道和扰动通道的综合响应，通过逐次移动操作变量到扰动通道的方法，评价移动后对模型质量指标的影响，从而判断出所移出子模型的性能，进而对失配子模型进行定位。进一步地，利用现场采集的历史数据用自回归滑动平均模型辨识法辨识出失配部分的模型，用于对原有子模型进行修正。实验采用Wood-Berry精馏过程对其进行动态仿真验证，结果证明了该算法的有效性。