Dynamic simulation tools for isotopic separation system modeling and design

Iraola, Eduardo; Nougués, José María; Sedano, L.; Feliu, Josep A.; Batet, L.

doi:10.1016/j.fusengdes.2021.112452

Cited by 15 publications

(7 citation statements)

References 21 publications

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“…The graph demonstrates that the process control is less effective, leading to an inefficient use of energy [11], which required more time to reach a steady state, as depicted in Figure 7. Dynamic conditions can be regulated with the proper process control system, but the time necessary to reach a steady state varied considerably based on the approach employed [3]. Approximately 380 minutes were required to reach the steady state using the ramp method.…”

Section: Figure 1 Benzene/ Toluene Distillation Shortcut Parametersmentioning

confidence: 99%

“…The method demonstrated that this dynamic process control system requires considerable time to modify a number of variables to a steady state [13]. The circumstance revealed that both the control system and the absence of control had a substantial impact on the product concentration, particularly the concentration of the product at the bottom [3][14] [15].…”

Section: Figure 1 Benzene/ Toluene Distillation Shortcut Parametersmentioning

confidence: 99%

“…Normal fractional distillation is an inefficient and energy-intensive method for separating these components. In order to efficiently identify benzene derivatives from toluene, it is important to develop a novel approach [3].…”

Section: Introductionmentioning

confidence: 99%

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The Dynamic Simulation of The Benzene and Toluene Distillation Process

Topandi,

Nisa,

Hidayatulloh

2023

fld

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Benzene and toluene are products of petroleum catalytic fractionation and dehydrogenation, which are massively used for industrial purposes. The mixture of these two compounds forms an azeotropic condition that requires high energy and expensive investment. The separation process simulation is the appropriate way to address this problem. The technique of separating benzene and its derivatives from toluene is crucial if the product is to be reused for the following process. We propose a simulation of the separation of benzene and toluene using Aspen HYSYS with several assumptions (Peng-Robinson Fluid Package and Transfer Function Block) and operating conditions settings (pressure, flow rate, and vapor fraction). The simulation results were analyzed by comparing treatments without and with dynamic system settings (sudden and gradual changes in operational parameters for 30 minutes). The simulation results revealed that the stepwise dynamic system configuration might increase 10% extra moles of benzene. In addition, dynamic system settings also significantly affect the concentration of the bottom product.

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Section: Figure 1 Benzene/ Toluene Distillation Shortcut Parametersmentioning

confidence: 99%

Section: Figure 1 Benzene/ Toluene Distillation Shortcut Parametersmentioning

confidence: 99%

See 1 more Smart Citation

The Dynamic Simulation of The Benzene and Toluene Distillation Process

Topandi,

Nisa,

Hidayatulloh

2023

fld

View full text Add to dashboard Cite

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“…Modeling and simulation of various components of a chemical plant help determine the impacts of the different process parameters and cost considerations . [ 12 ] Ishaq and Dincer [ 13 ] designed a biomass and solar energy‐based model for hydrogen production, where the overall system efficiency achieved is 29.9%, while the exergy efficiency is 31.5%, respectively. Bassyouni et al [ 14 ] simulated a downdraft gasifier.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Methanol Reforming Parameters for Enhanced Hydrogen Selectivity in an Aspen Hysys Simulator using Response Surface Methodology

2023

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Hydrogen is the prominent fuel for a nation's industrial and infrastructural development. Hydrogen fuel fulfills the energy requirement and reduces environmental pollution concerns. Hence, every country is looking for efficient and greener hydrogen production technologies. Herein, a simulation model of a methanol‐water (as feed) reformer is developed, and the effects of reaction temperature (RT), reactor pressure (RP), and methanol‐to‐water (M‐to‐W) ratio are investigated. In contrast, the optimal conditions for hydrogen selectivity (HS) and feed conversion percentage (FCP) are determined using response surface methodology. Results show a significant effect of the M‐to‐W molar ratio in the range of 0.9 and 1.35, whereas higher RT has a good affinity for higher HS and FCP. The regression analysis shows R2 values of 0.9877 and 0.9803 for HC and FCP, which are close to unity. Hence, both experimental (and simulated) and predicted values have better correspondence with each other. In contrast, the optimal HS and FCP of 84.81% and 95.71% are observed at 328 °C RT, 2.6 atm. RP, and 1.34 M‐to‐W molar ratio, respectively. Therefore, the present simulation and optimization provide results that may help to enhance the hydrogen production percentage in commercialized plants.

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“…In [42][43][44], mathematical models are proposed for separation processes, but having constant parameters. In this case, the usage of AI is not necessarily due to the absence of the necessity to learn variable parameters.…”

Section: Introductionmentioning

confidence: 99%

AI versus Classic Methods in Modelling Isotopic Separation Processes: Efficiency Comparison

et al. 2021

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In the paper, the comparison between the efficiency of using artificial intelligence methods and the efficiency of using classical methods in modelling the industrial processes is made, considering as a case study the separation process of the 18O isotope. Firstly, the behavior of the considered isotopic separation process is learned using neural networks. The comparison between the efficiency of these methods is highlighted by the simulations of the process model, using the mentioned modelling techniques. In this context, the final part of the paper presents the proposed model being simulated in different scenarios that can occur in practice, thus resulting in some interesting interpretations and conclusions. The paper proves the feasibility of using artificial intelligence methods for industrial processes modeling; the obtained models being intended for use in designing automatic control systems.

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Dynamic simulation tools for isotopic separation system modeling and design

Cited by 15 publications

References 21 publications

The Dynamic Simulation of The Benzene and Toluene Distillation Process

The Dynamic Simulation of The Benzene and Toluene Distillation Process

Optimizing Methanol Reforming Parameters for Enhanced Hydrogen Selectivity in an Aspen Hysys Simulator using Response Surface Methodology

AI versus Classic Methods in Modelling Isotopic Separation Processes: Efficiency Comparison

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