Journal: Chemical Engineering Research and Design

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Elsevier

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0263-8762
1744-3563

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Publications1 - 10 of 16
  • Model-based design of pressure-driven product removal from stirred suspensions
    Item type: Journal Article
    Achermann, Ramona; Wiedmeyer, Viktoria; Hosseinalipour, Mercedeh Sadat; et al. (2021)
    Chemical Engineering Research and Design
    Achieving “mixed-product removal” in a mixed-suspension mixed-product removal crystallizer (MSMPRC), operating with a pressure-driven suspension transfer, is challenging. In this work, single and multiphase computational fluid dynamics (CFD) simulations were used to guide the choice of a suitable withdrawal position, which was found to be that of an immersed tube close to the vessel wall. The chosen withdrawal position was then tested and compared to other withdrawal positions experimentally. It performed as predicted, whereas for the other positions, the degree of dilution (size-independent classification) and of sieving (size-dependent classification) of the product removed increased. Furthermore, the influence of a non-representative withdrawal on an MSMPRC steady-state was investigated using a population balance equation (PBE) model.
  • Study of particle inertia effects on drag force of finite sized particles in settling process
    Item type: Journal Article
    Zaidi, Ali A. (2018)
    Chemical Engineering Research and Design
  • SUSCAPE: A framework for the optimal design of SUStainable ChemicAl ProcEsses incorporating data envelopment analysis
    Item type: Journal Article
    González-Garay, Andrés; Guillén Gosálbez, Gonzalo (2018)
    Chemical Engineering Research and Design
    Developing computer aided tools for process design is of paramount importance in the transition toward a more sustainable chemical industry. In this work, we present a framework to incorporate sustainability principles in the design of chemical processes that combines a palette of tools, including life cycle assessment, surrogate modeling, objective reduction, multi-objective optimization and data envelopment analysis (DEA). The latter methodology facilitates the post-optimal analysis of the Pareto front by narrowing down the number of designs and ranking them without the need to define weights in an explicit manner. DEA provides in turn improvement targets for the suboptimal alternatives that if attained would make them optimal, thereby guiding retrofit efforts toward the most effective actions based on benchmarking them against the best technologies available. The capabilities of the framework are demonstrated in a case study based on the production of methanol from CO2 and hydrogen. © 2018 Institution of Chemical Engineers
  • Characterization of a vibromixer: Experimental and modelling study of mixing in a batch reactor
    Item type: Journal Article
    Orlewski, Pawel M.; Wang, Yan; Hosseinalipour, Mercedeh S.; et al. (2018)
    Chemical Engineering Research and Design
  • Dynamic MR Imaging of single- and two-phase flows
    Item type: Review Article
    Gladden, Lynn F.; Akpa, Belinda S.; Anadon, Laura D.; et al. (2006)
    Chemical Engineering Research and Design
  • Reducing the cost, environmental impact and energy consumption of biofuel processes through heat integration
    Item type: Journal Article
    Brunet, Robert; Boer, Dieter; Guillén Gosálbez, Gonzalo; et al. (2015)
    Chemical Engineering Research and Design
    This study proposes a process design methodology based on the combined use of process simulation in Super Pro Designer with economic, environmental and energetic balances implemented in Matlab and heat integration using Aspen Energy Analyzer. We model a 2.4 MMgal/year alkali-catalyzed biodiesel process using vegetable oil and a 40 MMgal/year dry-grind corn based bioethanol production plant. Then, we analyse the cost, the environmental impact, and the energy required to produce one gallon of the desired biofuel. Finally, we determine the optimal heat integration strategy of the plant in order to reduce the cost, environmental impact and energy consumption associated to the biofuel production. In the case of biodiesel the cost is reduced from 2.27 $/gal to 2.19 $/gal, the environmental impact from 4.52 kgCO2eq/gallon to 4.26 kgCO2eq/gallon and the energy from 8274 BTU/gal to 8410 BTU/gal. Reductions are also obtained in the bioethanol plant in which the cost is reduced from 1.79 $/gal to 1.75 $/gal, the environmental impact from 4.97 kgCO2eq/gal to 4.77 kgCO2eq/gal and the energy from 24,681 BTU/gal to 23,168 BTU/gal.
  • Optimal design of flexible heat-integrated crude oil distillation units using surrogate models
    Item type: Journal Article
    Ibrahim, Dauda; Jobson, Megan; Li, Jie; et al. (2021)
    Chemical Engineering Research and Design
    The design of distillation columns often considers a given fixed feedstock and nominal operating conditions. Here we present an optimization-based approach for the optimal design of these units considering a flexible operation under a range of potential feedstocks. Our method combines an artificial neural network with a support vector machine to model the crude oil distillation unit. The artificial neural network model predicts the performance of the distillation unit for a given crude oil feedstock whilst the support vector machine classifier filters out infeasible design alternatives from the solution space (i.e., designs that are unlikely to converge when simulated using a rigorous model). The inputs to the artificial neural network include the column structural variables and operating conditions, whilst the outputs are process variables linked to the column performance. The artificial neural network models and support vector machines constructed for different crude oil feedstocks are integrated into a two-stage optimization framework in order to optimize the column structural variables and operating conditions, where the minimum utility demand is estimated using the pinch analysis. An effective solution strategy that combines stochastic and deterministic optimization algorithms is applied to search for economically viable and flexible design alternatives that can operate over a given range of crude oil feedstocks while satisfying the product quality specifications. The capabilities of the proposed approach are illustrated using an industrially-relevant case study, where we clearly show that the proposed approach can identify design alternatives capable of handling various feedstocks effectively. © 2020 Institution of Chemical Engineers
  • Massive, automated solvent screening for minimum energy demand in hybrid extraction–distillation using COSMO-RS
    Item type: Journal Article
    Scheffczyk, Jan; Redepenning, Christian; Jens, Christian M.; et al. (2016)
    Chemical Engineering Research and Design
    An automated approach for large-scale solvent screening is presented based on a comprehensive process-level assessment. In this solvent screening approach, COSMO-RS is used to efficiently predict physical properties for large numbers of solvents without the need for experimental data. The predicted thermodynamical behavior is used in pinch-based separation models for a thermodynamically sound and robust calculation of the minimum energy demand. With this approach, the performance of a hybrid extraction–distillation process is evaluated fully automated for more than 4600 solvents. The massive solvent screening approach is successfully applied to purification of the bio-based platform chemical γ-valerolactone (GVL). Novel promising solvents are identified. A reduction of 63% is achieved in minimum energy demand using the best predicted solvent in comparison to the literature benchmark. Restricting the approach to known classes of solvents, we still find a reduction of 31%. The process-level assessment overcomes the limitations of heuristics based on physical properties only, and allows for efficient and robust solvent screening.
  • Optimization-based design of crude oil distillation units using surrogate column models and a support vector machine
    Item type: Journal Article
    Ibrahim, Dauda; Jobson, Megan; Li, Jie; et al. (2018)
    Chemical Engineering Research and Design
    This paper presents a novel optimization-based approach for the design of heat-integrated crude oil distillation units, which are widely used in refineries. The methodology presented combines, within a unified framework, surrogate distillation column models based on artificial neural networks, feasibility constraints constructed using a support vector machine, and pinch analysis to maximize heat recovery, in order to optimize the distillation column configuration and its operating conditions. The inputs to the surrogate column model are given by the column structure and operating conditions, while the outputs are related to the column performance. The support vector machine classifier filters infeasible design alternatives from the search space, thus reducing computational time, and ultimately improves the quality of the final solution. The overall optimization problem takes the form of a mixed-integer nonlinear program, which is solved by a genetic algorithm that seeks the design and operating variables values that minimize the total annualized cost. The capabilities of the proposed approach are illustrated using an industrially–relevant case study. Numerical results show that promising design alternatives can be obtained using the proposed method. The approach can help engineers to design and operate petroleum refineries optimally, where these are expected to continue to play a major role in the energy mix for some years.
  • Influence of uncertainty in heat-moisture transport properties on convective drying of porous materials by numerical modelling
    Item type: Journal Article
    Defraeye, Thijs; Blocken, Bert; Carmeliet, Jan (2012)
    Chemical Engineering Research and Design
Publications1 - 10 of 16