gPROMS-driven modeling and simulation of fixed bed adsorption of heavy metals on a biosorbent: benchmarking and case study

Danish, Mohd; Ansari, Khursheed B.; Aftab, Rameez Ahmad; Danish, Mohammad; Zaidi, Sadaf; Trịnh, Quang Thang

doi:10.1007/s11356-021-13207-y

Cited by 16 publications

(9 citation statements)

References 36 publications

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“…In a paper discussing the usage of gPROMS®among other virtual environments and simulators in the United Kingdom, Brown and coworkers mention at least three institutions where this platform is used [20]. On the other hand, a significant amount of research papers are based on the usage of gPROMS® platform [27,28,33,40,48,55,68,71,78,90]. Among the subjects tackled in these research papers, we list: pharmaceutical applications [27,28], environment protection [33,40], performance of gas turbines [48], and operation of an industrial batch plant [90].…”

Section: Gams® and Gproms® Softwarementioning

confidence: 99%

“…On the other hand, a significant amount of research papers are based on the usage of gPROMS® platform [27,28,33,40,48,55,68,71,78,90]. Among the subjects tackled in these research papers, we list: pharmaceutical applications [27,28], environment protection [33,40], performance of gas turbines [48], and operation of an industrial batch plant [90].…”

Section: Gams® and Gproms® Softwarementioning

confidence: 99%

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Introduction to the modeling of complex chemical reaction equilibrium using gPROMS® and GAMS®

Garma,

Sioud,

Binous

et al. 2024

Comp Applic In Engineering

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In the present paper several aspects of the simulation of complex chemical equilibrium are discussed, using two research and educational software: gPROMS® and GAMS®. All computations are performed to boost the understanding of chemical engineering students, undergraduate, and graduate, of the complex concepts behind both thermo‐chemical processes and optimization techniques. Four case studies with varying levels of difficulty illustrate the proposed methodology and robustness of the modeling systems: Catalytic steam reforming of bio‐ethanol at high temperatures. Partial oxidation of naphthalene using either air or pure oxygen. Supercritical water gasification of Microalga Spirulina. Dry and mixed reforming of glucose.Our results indicate that the use of optimization tools offered bygPROMS® and GAMS®software are useful and efficient tools to calculate the chemical and phase equilibrium by minimizing the Gibbs energy, provided that adequate initial guesses are used. Furthermore, the computational time spent in the calculations was generally quite short. The obtained equilibrium compositions are benchmarked using the ubiquitous process simulators: ASPEN‐Plus® and/or ASPEN‐Hysys® as well as data available from the open literature. We obtained excellent agreement between our results and their counterpart obtained using ASPEN‐Plus®. In the last part of this manuscript, authors share their experience in supervising senior term projects on the subject. A questionnaire was used to collect qualitative and quantitative feedback from the nine students involved in the projects. Their responses to a questionnaire focused on the chemical engineering thermodynamics theory as well as software usage during their investigations. This questionnaire demonstrates that students can overcome mathematical complexity by either using mathematical software or equivalent modeling systems (e.g., Matlab®, Mathematica©, gPROMS®, and GAMS®).

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Section: Gams® and Gproms® Softwarementioning

confidence: 99%

Section: Gams® and Gproms® Softwarementioning

confidence: 99%

Introduction to the modeling of complex chemical reaction equilibrium using gPROMS® and GAMS®

Garma,

Sioud,

Binous

et al. 2024

Comp Applic In Engineering

View full text Add to dashboard Cite

show abstract

“…The (gPROMS) software is a model builder that has been used to develop the gPROMS FormulatedProduct (gFP) to be able to simulate both steady and dynamic states [11]. Processes that can be defined by a mathematical model can be utilized by gPROMS [12]. In the case of [12][13][14][15][16], the gPROMS and its formulated products have been used to predict experimental results.…”

Section: Introductionmentioning

confidence: 99%

“…In the case of [12][13][14][15][16], the gPROMS and its formulated products have been used to predict experimental results. It is also suitable for designing experiments and a good estimator of several parameters [12]. These parameters are in the form of equipment parameters, process parameters, and formulation parameters.…”

Section: Introductionmentioning

confidence: 99%

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Process Simulation of Twin‐Screw Granulator: Effect of Screw Configuration on Size Distribution

et al. 2023

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The effect of screw configuration on granule size distribution (GSD) using gPROMS FormulatedProduct (gFP) software to perform optimization, estimation of complex processes, and analyses is evaluated. Twin‐screw granulation modeling was used to investigate the contribution of screw configuration and liquid‐to‐solid (L/S) ratio on GSD. Lactose and Avicel were the granulating materials. Twelve different configurations were investigated under three feed rates as consistent with literature and at various L/S ratios. Results indicate that kneading elements promote the recovery of 100–1000 µm granules while reducing the production of oversized granules. Higher feed rates support the production of fines and agglomerates, while a low feed rate produces 100–1000 µm granules.

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Adsorptive removal of Pb(II) using nanostructured γ-alumina in a packed bed adsorber: Simulation using gPROMS

Danish

Ansari

Danish

2022

Environ Sci Pollut Res

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gPROMS-driven modeling and simulation of fixed bed adsorption of heavy metals on a biosorbent: benchmarking and case study

Cited by 16 publications

References 36 publications

Introduction to the modeling of complex chemical reaction equilibrium using gPROMS® and GAMS®

Introduction to the modeling of complex chemical reaction equilibrium using gPROMS® and GAMS®

Process Simulation of Twin‐Screw Granulator: Effect of Screw Configuration on Size Distribution

Adsorptive removal of Pb(II) using nanostructured γ-alumina in a packed bed adsorber: Simulation using gPROMS

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