Computational chemical product design problems under property uncertainties

Jerome Frutiger; Stefano Cignitti; Jens Abildskov; John Woodley; Gürkan Sin

doi:10.1016/B978-0-444-63965-3.50164-1

Computational chemical product design problems under property uncertainties

Jerome Frutiger, Stefano Cignitti, Jens Abildskov, John Woodley, Gürkan Sin

Department of Chemical and Biochemical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

Three different strategies of how to combine computational chemical product design with Monte Carlo based methods for uncertainty analysis of chemical properties are outlined. One method consists of a computer-aided molecular design (CAMD) solution and a post-processing property uncertainty propagation through the considered process. It is demonstrated for an industrial case study on identification of a suitable working fluid in a thermodynamic cycle for waste heat recovery. The results show that including property uncertainties gives an additional criterion for the fluid ranking in working fluid design. While the higher end of the uncertainty range of the process model output is similar for the best performing fluids, the lower end of the uncertainty range differs largely.

Original language	English
Title of host publication	Proceedings of the 27th European Symposium on Computer Aided Process Engineering (ESCAPE 27)
Editors	Antonio Espuña, Moisès Graells, Luis Puigjaner
Volume	40
Publisher	Elsevier
Publication date	2017
Edition	1
Pages	973-978
ISBN (Print)	9780444639653
ISBN (Electronic)	9780444639707
DOIs	https://doi.org/10.1016/B978-0-444-63965-3.50164-1
Publication status	Published - 2017
Event	27th European Symposium on Computer Aided Process Engineering - Barcelona, Spain Duration: 1 Oct 2017 → 5 Oct 2017 Conference number: 27 https://www.elsevier.com/books/27th-european-symposium-on-computer-aided-process-engineering/espuna/978-0-444-63965-3

Conference

Conference	27th European Symposium on Computer Aided Process Engineering
Number	27
Country/Territory	Spain
City	Barcelona
Period	01/10/2017 → 05/10/2017
Internet address	https://www.elsevier.com/books/27th-european-symposium-on-computer-aided-process-engineering/espuna/978-0-444-63965-3

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Frutiger, J., Cignitti, S., Abildskov, J., Woodley, J., & Sin, G. (2017). Computational chemical product design problems under property uncertainties. In A. Espuña, M. Graells, & L. Puigjaner (Eds.), Proceedings of the 27th European Symposium on Computer Aided Process Engineering (ESCAPE 27) (1 ed., Vol. 40, pp. 973-978). Elsevier. https://doi.org/10.1016/B978-0-444-63965-3.50164-1

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title = "Computational chemical product design problems under property uncertainties",

abstract = "Three different strategies of how to combine computational chemical product design with Monte Carlo based methods for uncertainty analysis of chemical properties are outlined. One method consists of a computer-aided molecular design (CAMD) solution and a post-processing property uncertainty propagation through the considered process. It is demonstrated for an industrial case study on identification of a suitable working fluid in a thermodynamic cycle for waste heat recovery. The results show that including property uncertainties gives an additional criterion for the fluid ranking in working fluid design. While the higher end of the uncertainty range of the process model output is similar for the best performing fluids, the lower end of the uncertainty range differs largely.",

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publisher = "Elsevier",

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note = "27th European Symposium on Computer Aided Process Engineering, ESCAPE 27 ; Conference date: 01-10-2017 Through 05-10-2017",

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Frutiger, J, Cignitti, S, Abildskov, J , Woodley, J & Sin, G 2017, Computational chemical product design problems under property uncertainties. in A Espuña, M Graells & L Puigjaner (eds), Proceedings of the 27th European Symposium on Computer Aided Process Engineering (ESCAPE 27). 1 edn, vol. 40, Elsevier, pp. 973-978, 27th European Symposium on Computer Aided Process Engineering, Barcelona, Spain, 01/10/2017. https://doi.org/10.1016/B978-0-444-63965-3.50164-1

Computational chemical product design problems under property uncertainties. / Frutiger, Jerome; Cignitti, Stefano; Abildskov, Jens et al.
Proceedings of the 27th European Symposium on Computer Aided Process Engineering (ESCAPE 27). ed. / Antonio Espuña; Moisès Graells; Luis Puigjaner. Vol. 40 1. ed. Elsevier, 2017. p. 973-978.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

TY - GEN

T1 - Computational chemical product design problems under property uncertainties

AU - Frutiger, Jerome

AU - Cignitti, Stefano

AU - Abildskov, Jens

AU - Woodley, John

AU - Sin, Gürkan

N1 - Conference code: 27

PY - 2017

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N2 - Three different strategies of how to combine computational chemical product design with Monte Carlo based methods for uncertainty analysis of chemical properties are outlined. One method consists of a computer-aided molecular design (CAMD) solution and a post-processing property uncertainty propagation through the considered process. It is demonstrated for an industrial case study on identification of a suitable working fluid in a thermodynamic cycle for waste heat recovery. The results show that including property uncertainties gives an additional criterion for the fluid ranking in working fluid design. While the higher end of the uncertainty range of the process model output is similar for the best performing fluids, the lower end of the uncertainty range differs largely.

AB - Three different strategies of how to combine computational chemical product design with Monte Carlo based methods for uncertainty analysis of chemical properties are outlined. One method consists of a computer-aided molecular design (CAMD) solution and a post-processing property uncertainty propagation through the considered process. It is demonstrated for an industrial case study on identification of a suitable working fluid in a thermodynamic cycle for waste heat recovery. The results show that including property uncertainties gives an additional criterion for the fluid ranking in working fluid design. While the higher end of the uncertainty range of the process model output is similar for the best performing fluids, the lower end of the uncertainty range differs largely.

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DO - 10.1016/B978-0-444-63965-3.50164-1

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Y2 - 1 October 2017 through 5 October 2017

ER -

Computational chemical product design problems under property uncertainties

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