Computer-aided sustainable process synthesis-design and analysis


Process synthesis can be considered as the cornerstone of the process design activity which involves investigation of chemical reactions needed to produce the desired product, selection of the separation techniques needed for downstream processing, as well as making decisions on sequencing the involved reaction and separation operations. This work highlights the development of computer aided methodology for fast, reliable and consistent generation of process flowsheets and rank them based on various flowsheet performance indices. The methodology is based on the group contribution principles to solve the synthesis-design problem of chemical processes, where, chemical process flowsheets could be synthesized in the same way as atoms or groups of atoms are synthesized to form molecules in computer aided molecular design (CAMD) techniques. As in CAMD the generated molecules are quickly evaluated with respect to target molecular properties using GC property models, the generated flowsheet alternatives are also evaluated for properties like energy consumption, atom efficiency, environmental impact, etc.


In a group contribution method [1] for estimating pure component/mixture properties of a molecule, the molecular identity is described by means of a set of functional groups of atoms bonded together to form a molecular structure. Once the molecular chemical structure is uniquely represented by the functional groups, the specific properties can be estimated from regressed contributions of the functional groups representing the molecule. Having the groups, their contributions and their interactions together with governing rules to combine the groups into a molecule, allows us to synthesize molecules and/or mixtures. This is known as CAMD, computer aided molecular design. Let us now imagine that each group used to represent a fraction of a molecule could also be used to represent a chemical process operation or a set of operations in a chemical process flowsheet. A functional process-group would represent either a unit operation (such as a reactor, or a distillation column), or a set of unit operations (such as, two distillation columns in extractive distillation). The bonds among the process-groups represent the streams connecting the unit operations, similar to the bonds combining (molecular) functional groups. In the same way as CAMD method applies connectivity rules to combine the molecular functional groups to form feasible molecular structures, functional process-groups would have connectivity rules to combine process-groups to form structurally feasible process alternatives. Finally with flowsheet property model and corresponding process-group contributions it would be possible to predict various flowsheet properties which can be used as performance indicators for screening of alternatives.


The research conducted in this field is primarily within the field of process systems engineering (PSE). The main objective of this work is to a develop generic framework and its corresponding computer-aided tool to systematically solve process synthesis and design problems. The framework should be able to

Generate all feasible process flow-sheets for a given problem so as to identify novel/innovative solutions.
To rapidly, efficiently and reliably evaluate the generated alternatives.
To perform detailed design and analysis of promising alternatives.
To include sustainability and life cycle analysis in early stages of process synthesis to generate sustainable process alternatives.
Perform the above steps with collection of models where model complexity increases as the number of alternatives decrease.

Computer Aided Flowsheet Design (CAFD) Methodology

The computer aided flowsheet design methodology [2, 3] as shown in figure 1 has 8 main steps:

Step 1: Problem Definition: In this step the user defines the synthesis problem by selecting the necessary raw material, the desired products streams and performance criteria based upon which the alternatives are evaluated. Along with the stream properties, if the synthesis problem requires reaction to produce the product then this data is also provided in this step.

Step 2: Process-groups selection: The objective of this step is to select the process-group building blocks that are applicable for the given synthesis problem which is achieved through further analysis of the process synthesis problem. First the pure component analysis is performed by retrieving a list of 22 pure component properties from the ICAS database. For compounds missing data/new compounds, the properties are calculated using ProPred (property prediction tool box) which is part ICAS [4]. Second the mixture property analysis is made in terms of the binary pairs of all the chemical species identified in the problem. This analysis information is used for identification of feasible separation techniques using Jaksland and Gani’s [5] method. Based upon the identified separation techniques, process groups representing all the combinations possible for each of the separation technique are selected and initialized.

Step 3: Generation of Alternatives: The objective in this step is to combine the process-groups selected in step 2 according to a set of connectivity rules and specifications to generate feasible flowsheet structures.

Superstructure generation: In this task a combinatorial algorithm is employed to generate the superstructure of all flowsheet alternatives from the initialized process-groups. The combinatorial algorithm generates new flowsheet alternatives by combining process-groups according to a set of connectivity rules.

Generation of SFILES: Having a process flowsheet represented by process groups provides the possibility to employ simple notation systems for efficient storage of structural information of all the process alternatives generated. The SFILES method for flowsheets is similar to SMILES (Simplified Molecular Input Line Entry System) developed by David Weininger [6].

Step 4: Ranking of Alternatives:In this step, the generated alternatives are evaluated and ranked using flowsheet property models based on group contribution principles. The main objective of the process flowsheet property model is to calculate the impact generated by the whole process as a sum of contributions of the process-groups present in the flowsheet. General equation for a flowsheet group contribution based property model can be derived as shown by equation (1). Where f(P) is the flowsheet property function, NG: number of process groups, ak: regressed contribution of group k, and posk: topology factor. Different flowsheets models developed in this work include energy index, carbon footprint, product purity, product recovery etc.

Step 5: Design: This step of the framework has two tasks: i) calculation of flowsheet design parameters of the process unit operations in the flowsheet structure through reverse simulation using driving force concept [7], and ii) Analysis of the selected alternatives to further benchmark the alternatives based on various indicators related to process safety and efficiency.

Step 6: Verification & Selection: At this step of the methodology, all the necessary information to perform the final verification through rigorous simulation is available. Rigorous simulators like PROII or ICASSim are used to further refine the most promising process flowsheet.

Step 7: Process Analysis: At this step of the methodology, economic, sustainability and life cycle analysis is carried on the selected process alternative to identify the process hotspots or bottlenecks. These hotspots are translated into design targets which are targeted in the next stage. Matching of these design targets minimizes/eliminates the process hot-spots and therefore, generates non-tradeoff innovative process designs.

Step 8: Innovative designs: At this step of the methodology, different strategies / methods are applied individually to the selected alternative to target the hot spots for overall process improvement. 1. Simultaneous Process Optimization and Heat Integration strategy is applied to optimize the design parameters and heat integration network simultaneously to target process hotspots involving raw material losses and high operational costs. 2. Hybrid separation method is applied to reduce the operational cost and subsequent carbon footprint of any distillation column by 30- 50% using a hybrid design of distillation and membrane where the less efficient part of the separation in distillation is replaced by membrane separation technique. 

Case study

The application of the methodology is highlighted through a case study involving production of benzene through hydrodealkylation of toluene.

Step 1:
The synthesis problem is defined as to find the best processing alternative to produce benzene from toluene and hydrogen with minimum energy consumption. The structural definition of the problem has 2 inlet streams for toluene and hydrogen (methane as impurity) and 2 outlet streams representing main product benzene and byproduct biphenyl. Reaction data for toluene hydrodealkylation is as follows:
Temperature: 700-850 k
Pressure: 40 bar

Step 2:
Based upon the pure component analysis and mixture analysis, feasible process operation tasks to separate each of all the binary pairs present in the system are identified. This feasible separation techniques information is used to select the corresponding process-groups from the database and initialize with corresponding compound configurations. Table 1 gives information on the selected process-groups for the synthesis problem.Along with separation process-groups, separate process groups are initialized for two inlet streams representing, hydrogen along with methane and pure toluene streams and reactor. Two outlet process groups are also initialized for the benzene and biphenyl product streams, respectively.

Step 3:
In this step superstructure of all feasible alternatives are generated from 47 initialized process-groups using a combinatorial algorithm. Total of 74,046 alternatives are possible from different combinations of selected process-groups. But using the combinatorial algorithm along with logical decision rules, only 272 feasible flowsheet alternatives are generated for production of benzene from toluene hydrodealkylation. All the identified process alternatives are converted into SFILES, which stores the structural information of the alternatives.

Step 4:
All the alternatives generated are evaluated using flowsheet property model for calculating energy consumption of the process alternative. Table 2 represents the top five alternatives for the synthesis problem. The first two designs reported in Table 2 has same energy index. This is explained by the fact that the energy consumption index (Ex) is only calculated for the distillation process groups, so the contribution of the other process groups is considered as 0.

Step 5: 
Design parameters (number of stages for distillation, feed location, reflux ratio etc) for the selected alternatives are calculated using reverse simulation approach.  Table 3 gives the design parameters of distillation columns (calculated using driving force method) for the selected alternative. Also in this step, mass balance is resolved for selected alternatives using simple models to calculate overall benzene production, purity and atom efficiency. Along with mass balance results and process-groups definition, it is possible to estimate the energy required by each unit operation of the flowsheet and the corresponding energy requirements for the whole flowsheet as shown in table 2.

Step 6:
For this case study, the top 2 alternatives are selected for verification using rigorous models. Commercial process simulator (Pro- II) was used to verify the selected designs. The top process alternative obtained from the framework has slightly improved heating energy efficiency with respect to the alternative (2nd design) proposed in the literature. Table 4 gives the energy comparison between the selected designs.

Step 7:
Sustainability, economic and life cycle analysis is carried on the top ranked process alternative. From the process analysis the most sensitive process hotspot identified is the high operational cost and carbon footprint associated with the heat exchangers and raw material loss through the purge stream.

Step 8: 
For this case study simultaneous optimization and heat integration strategy is used to target the identified process hotspots. The objective function in this case is the operational profit, where the optimized case has an improvement of 200% against the base case. 


A novel approach based on the computer-aided molecular design principles has been developed to systematically solve the complex process synthesis and design problem, which facilitates more efficient and innovative solutions. Since rigorous simulation is done only in the last step of the method and feasible alternatives are generated by combining process groups, numerous process alternatives are quickly generated for a given synthesis problem. Also Introduction of flowsheet property models based on group contribution approach made it possible to quickly & efficiently evaluate and systematically screen generated alternatives.


Prof. Rafiqul Gani
Associate Prof. Gurkan Sin

PhD Study Started: December 2013 To be completed: December 2016

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