Computer Aided Molecular Design (CAMD) is an important tool to generate, test and evaluate promising chemical products. CAMD can be used in thermodynamic cycle for the design of pure component or mixture working fluids in order to improve the heat transfer capacity of the system. The safety assessment of novel working fluids relies on accurate property data. Flammability data like the lower and upper flammability limit (LFL and UFL) play an important role in quantifying the risk of fire and explosion. For novel working fluid candidates experimental values are not available for the safety analysis. In this case property prediction models like group contribution (GC) models can estimate flammability data. The estimation needs to be accurate, reliable and as less time consuming as possible . However, GC property prediction methods frequently lack rigorous uncertainty analysis. Hence, there is no information about the reliability of the data. Furthermore, the global optimality of the GC parameters estimation is often not ensured.
|Number of pages||2|
|Publication status||Published - 2015|
|Event||CAPE Forum 2015: Computer Aided Process Engineering - Paderborn, Germany|
Duration: 27 Apr 2015 → 29 Apr 2015
|Conference||CAPE Forum 2015|
|Period||27/04/2015 → 29/04/2015|