Matches in SemOpenAlex for { <https://semopenalex.org/work/W2887988293> ?p ?o ?g. }
- W2887988293 endingPage "257" @default.
- W2887988293 startingPage "247" @default.
- W2887988293 abstract "A methodology is presented to solve computer-aided molecular design (CAMD) and process design model problems under consideration of fluid property uncertainty. The uncertainties of the group contribution (GC) property prediction models are quantified for which asymptotic approximation of the covariance of parameter estimation errors is performed following a regression analysis. A Monte Carlo sampling technique generates GC factor samples within the respective uncertainties, which are evaluated separately as constraints to the CAMD optimization problem. The methodology is applied to identify working fluid candidates for an organic Rankine cycle used as waste heat recovery system in a marine diesel engine. CAMD under property uncertainties allows (1) identifying robust and more reliable molecules with respect to property uncertainties (conservative approach) and (2) enhancing the search space in order to find potentially globally optimal working fluids (optimistic approach). Suitable Hydrofluoroolefins (HFO) have been identified as potential working fluids for waste heat recovery." @default.
- W2887988293 created "2018-08-22" @default.
- W2887988293 creator A5005258563 @default.
- W2887988293 creator A5032705330 @default.
- W2887988293 creator A5036903025 @default.
- W2887988293 creator A5046617955 @default.
- W2887988293 creator A5073807995 @default.
- W2887988293 date "2019-03-01" @default.
- W2887988293 modified "2023-10-01" @default.
- W2887988293 title "Computer-aided molecular product-process design under property uncertainties – A Monte Carlo based optimization strategy" @default.
- W2887988293 cites W1964667833 @default.
- W2887988293 cites W1975117748 @default.
- W2887988293 cites W1994665973 @default.
- W2887988293 cites W2000182879 @default.
- W2887988293 cites W2003777614 @default.
- W2887988293 cites W2007068920 @default.
- W2887988293 cites W2010604544 @default.
- W2887988293 cites W2014130533 @default.
- W2887988293 cites W201531717 @default.
- W2887988293 cites W2016377594 @default.
- W2887988293 cites W2021674665 @default.
- W2887988293 cites W2030745849 @default.
- W2887988293 cites W2046033161 @default.
- W2887988293 cites W2048438785 @default.
- W2887988293 cites W2050339136 @default.
- W2887988293 cites W2056139823 @default.
- W2887988293 cites W2068110511 @default.
- W2887988293 cites W2068953026 @default.
- W2887988293 cites W2069034998 @default.
- W2887988293 cites W2072914018 @default.
- W2887988293 cites W2075558971 @default.
- W2887988293 cites W2076585408 @default.
- W2887988293 cites W2077468892 @default.
- W2887988293 cites W2081936482 @default.
- W2887988293 cites W2083830168 @default.
- W2887988293 cites W2089105401 @default.
- W2887988293 cites W2089139744 @default.
- W2887988293 cites W2094818470 @default.
- W2887988293 cites W2096836661 @default.
- W2887988293 cites W2097995485 @default.
- W2887988293 cites W2104832758 @default.
- W2887988293 cites W2117781171 @default.
- W2887988293 cites W2121571028 @default.
- W2887988293 cites W2132895267 @default.
- W2887988293 cites W2151582349 @default.
- W2887988293 cites W2254433768 @default.
- W2887988293 cites W2411872368 @default.
- W2887988293 cites W2470887818 @default.
- W2887988293 cites W2496912886 @default.
- W2887988293 cites W2522130153 @default.
- W2887988293 cites W2538676590 @default.
- W2887988293 cites W2568283272 @default.
- W2887988293 cites W2580997607 @default.
- W2887988293 cites W2637969446 @default.
- W2887988293 cites W2774834973 @default.
- W2887988293 cites W2892035443 @default.
- W2887988293 cites W3104249711 @default.
- W2887988293 cites W4253340707 @default.
- W2887988293 doi "https://doi.org/10.1016/j.compchemeng.2018.08.021" @default.
- W2887988293 hasPublicationYear "2019" @default.
- W2887988293 type Work @default.
- W2887988293 sameAs 2887988293 @default.
- W2887988293 citedByCount "12" @default.
- W2887988293 countsByYear W28879882932020 @default.
- W2887988293 countsByYear W28879882932021 @default.
- W2887988293 countsByYear W28879882932022 @default.
- W2887988293 countsByYear W28879882932023 @default.
- W2887988293 crossrefType "journal-article" @default.
- W2887988293 hasAuthorship W2887988293A5005258563 @default.
- W2887988293 hasAuthorship W2887988293A5032705330 @default.
- W2887988293 hasAuthorship W2887988293A5036903025 @default.
- W2887988293 hasAuthorship W2887988293A5046617955 @default.
- W2887988293 hasAuthorship W2887988293A5073807995 @default.
- W2887988293 hasBestOaLocation W28879882932 @default.
- W2887988293 hasConcept C105795698 @default.
- W2887988293 hasConcept C111472728 @default.
- W2887988293 hasConcept C111919701 @default.
- W2887988293 hasConcept C126255220 @default.
- W2887988293 hasConcept C127413603 @default.
- W2887988293 hasConcept C138885662 @default.
- W2887988293 hasConcept C178650346 @default.
- W2887988293 hasConcept C189950617 @default.
- W2887988293 hasConcept C19499675 @default.
- W2887988293 hasConcept C21880701 @default.
- W2887988293 hasConcept C33923547 @default.
- W2887988293 hasConcept C41008148 @default.
- W2887988293 hasConcept C98045186 @default.
- W2887988293 hasConceptScore W2887988293C105795698 @default.
- W2887988293 hasConceptScore W2887988293C111472728 @default.
- W2887988293 hasConceptScore W2887988293C111919701 @default.
- W2887988293 hasConceptScore W2887988293C126255220 @default.
- W2887988293 hasConceptScore W2887988293C127413603 @default.
- W2887988293 hasConceptScore W2887988293C138885662 @default.
- W2887988293 hasConceptScore W2887988293C178650346 @default.
- W2887988293 hasConceptScore W2887988293C189950617 @default.
- W2887988293 hasConceptScore W2887988293C19499675 @default.
- W2887988293 hasConceptScore W2887988293C21880701 @default.
- W2887988293 hasConceptScore W2887988293C33923547 @default.