On the Design and Implementation of a Process Modelling Language for Uncertainty

Filho, Pedro I.O.; Fraga, Eric S.

doi:10.1016/b978-0-12-818634-3.50150-8

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The Optimization Methods1

Aacvd Process Model1

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2021

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Cited by 2 publications

(2 citation statements)

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“…Fresa is implemented in the Julia language [49] with the stochastic modelling provided by an uncertainty modelling framework [50]. Julia enables the use of parallel processing which allows the summations in equations 7 and 8 to be distributed over multiple cores.…”

Section: The Optimization Methodsmentioning

confidence: 99%

Design optimization of microfluidic-based solvent extraction systems for radionuclides detection

Pineda

Tsaoulidis

Filho

et al. 2021

Nuclear Engineering and Design

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Section: The Optimization Methodsmentioning

confidence: 99%

Design optimization of microfluidic-based solvent extraction systems for radionuclides detection

Pineda

Tsaoulidis

Filho

et al. 2021

Nuclear Engineering and Design

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“…The implementation of the models and description of the uncertain and distributed parameters uses , a modeling framework focusing on the treatment of uncertainty. The framework was written in Julia (), a high-level language that allows both large-scale computation and flexible prototyping.…”

Section: Aacvd Process Modelmentioning

confidence: 99%

Mathematical Modeling for the Design and Scale-Up of a Large Industrial Aerosol-Assisted Chemical Vapor Deposition Process under Uncertainty

Filho

Carmalt

Angeli

et al. 2020

Ind. Eng. Chem. Res.

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Aerosol-assisted chemical vapor deposition (AACVD) can be used to produce coatings and thin films such as transparent conducting oxide (TCO) films, which are used in self-cleaning surfaces, solar cells, and other electronic and optoelectronic applications. A process based on AACVD consists of a number of steps: aerosol generation, aerosol transport, aerosol delivery, and chemical deposition. Predicting the behavior of such a process at an industrial scale is challenging due to a number of factors: the aerosol generation creates droplets of different sizes, losses are incurred in the transport, the delivery must evaporate the solvent to release the precursors, and the reactions on the surface of the deposition target may be complex. This paper describes a full process model, including the prediction of the size distribution of the generated aerosol, the number and size of droplets delivered, the carrier gas temperature profile at the reaction site, the solvent evaporation time, and the rate of film formation. The key modeling challenges addressed include incorporating the impact of uncertainties in parameters such as heat and mass transfer coefficients and reaction rate constants. Preliminary simulations demonstrate a proof of concept for the use of simulation for gaining insights into the feasibility of a process scale-up for an industrial-scale AACVD.

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On the Design and Implementation of a Process Modelling Language for Uncertainty

Cited by 2 publications

References 8 publications

Design optimization of microfluidic-based solvent extraction systems for radionuclides detection

Design optimization of microfluidic-based solvent extraction systems for radionuclides detection

Mathematical Modeling for the Design and Scale-Up of a Large Industrial Aerosol-Assisted Chemical Vapor Deposition Process under Uncertainty

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