A Computer-Aided Platform for Simultaneous Process Synthesis and Intensification

Monjur, Mohammed Sadaf; Demirel, Salih Emre; Li, Jianping; Hasan, M. M. Faruque

doi:10.1016/b978-0-323-88506-5.50046-2

Cited by 5 publications

(3 citation statements)

References 5 publications

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“…Because of this phenomena scale representation, building block can generate novel designs without any postulation of candidate designs beforehand. For this reason, building block‐based approach has been implemented to several design and synthesis problems recently 48,51–55 …”

Section: Process Synthesis Methodologymentioning

confidence: 99%

Computer‐aided process intensification of natural gas to methanol process

Monjur

Hasan

2022

AIChE Journal

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The recent revolution in shale gas has presented opportunities for distributed manufacturing of key commodity chemicals, such as methanol, from methane. However, the conventional methane‐to‐methanol process is energy intensive which negatively affects the profitability and sustainability. We report an intensified process configuration that is both economically attractive and environmentally sustainable. This flowsheet is systematically discovered using the building block‐based representation and optimization methodology. The new process configuration utilizes membrane‐assisted reactive separations and can have as much as 190% higher total annual profit compared to a conventional configuration. Additionally, it has 57% less CO2‐equivalent greenhouse gas emission. Such drastic improvement highlights the advantages of building block‐based computer‐aided process intensification method.

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Section: Process Synthesis Methodologymentioning

confidence: 99%

Computer‐aided process intensification of natural gas to methanol process

Monjur

Hasan

2022

AIChE Journal

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“…This is a unique capability for coming up with innovative designs without any pre-postulation of candidate designs. A general description of the use of building block representation can be found elsewhere. − …”

Section: Spice_ed Frameworkmentioning

confidence: 99%

Separation Process Synthesis for High-GWP Refrigerant Mixtures: Extractive Distillation using Ionic Liquids

Monjur

Iftakher

Hasan

2022

Ind. Eng. Chem. Res.

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Due to high global warming potential (GWP) of hydrofluorocarbons (HFCs), the separation and recovery of HFCs from different refrigerant mixtures is an important issue. Most HFC mixtures are azeotropic in nature, thereby rendering the conventional distillation-based separation difficult and energy intensive. Extractive distillation (ED) with ionic liquid (IL) as solvent provides an attractive strategy for selective separation of HFC mixtures. However, systematic design and optimization of ED-based separation processes is nontrivial. In this work, we present SPICE_ED which is a software framework for the detailed design, synthesis, and techno-economic analysis of ED-based separation processes. The framework employs a building block representation followed by superstructure optimization that is able to automatically generate numerous design solutions and screen the best without requiring prior expert knowledge of candidate configurations. For a given IL as solvent and a set of design specifications, one can automatically determine the feasibility of the solvent and obtain the optimal process flowsheets that correspond to minimum energy consumption, minimum separation cost, or minimum emission/waste. We demonstrate the capability of SPICE_ED for the separation of R-410A (50 wt % R-32 and 50 wt % R-125) using [bmim][PF 6 ], a commonly used IL. Our optimized design requires an equivalent work of only 338.2 kJ/kg R-410A, which is about 48% less than the previously reported value of 656 kJ/kg. The newly identified design also achieves more than 47% and 27% reductions in CO 2 -equivalent emission (sustainability) and cost, respectively. Through multiobjective optimization, we further identify an operating regime to separate R-410A at a near-minimum cost without significantly increasing the energy consumption and emission. The processes obtained from SPICE_ED show excellent agreement with the key performance metrics when simulated in Aspen Plus, thereby establishing confidence in our designs as realistic and implementable.

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“…Recently, we have proposed a process synthesis, optimization, and intensification framework named SPICE 52 based on building block‐based process representation 53,54 . Detailed description of building block‐based representation method can be found elsewhere 55–57 .…”

Section: Prediction Of Hfc Solubility In Ilmentioning

confidence: 99%

Data‐driven approximation of thermodynamic phase equilibria

et al. 2022

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We present a new data‐driven approach for both accurate and computationally efficient approximation of vapor liquid equilibria (VLE) models. Our method is able to provide guaranteed enclosure to limit the approximation errors over the entire domain of interest, all just by sampling only at select points. The approximation relies on a mixed‐integer linear programming (MILP) formulation that exploits vertex polyhedral properties of theoretically guaranteed lower and upper bounds to enclose nonlinear and nonconvex equations of state (EOS) and empirical models. Another advantage is that, unlike traditional full simulation‐based data‐driven approaches, we do not solve nonlinear system of equations (f(x) = 0) for sampling. Instead of looking for only feasible samples, we evaluate f(x) over x‐domain. This functional evaluation eliminates the need for computationally‐demanding full‐scale simulations and the associated convergence issues. We demonstrate excellent performance of the proposed MILP formulation in predicting the solubility of hydrofluorocarbon (HFC) refrigerants in ionic liquids (IL).

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A Computer-Aided Platform for Simultaneous Process Synthesis and Intensification

Cited by 5 publications

References 5 publications

Computer‐aided process intensification of natural gas to methanol process

Computer‐aided process intensification of natural gas to methanol process

Separation Process Synthesis for High-GWP Refrigerant Mixtures: Extractive Distillation using Ionic Liquids

Data‐driven approximation of thermodynamic phase equilibria

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