Jürgen Rarey

Application of the bio-inspired Krill Herd optimization technique to phase equilibrium calculations

Abstract The Krill Herd optimization technique, which is based on the simulated herding behaviour of the krill crustacean, is applied to calculations involving phase equilibrium and phase stability, as the application of this emerging technique is extremely limited in the literature. In this work, the Krill Herd algorithm (KH) 1 and the modified Levy-flight Krill Herd algorithm (LKH) 2 has been applied to phase stability (PS) 3 and phase equilibrium calculations in non-reactive (PE) 4 and reactive (rPE) 5 systems, where global minimization of the total Gibbs energy is necessary. Several phase stability and phase equilibrium systems were considered for the analysis of the performance of the technique that includes both vapour and liquid phase conditions. The Krill Herd algorithm was found to reliably determine the desired global optima in PS, PE and rPE problems with generally higher success rates and lower computing time requirements than previously applied metaheuristic techniques such as those involving swarm intelligence and genetic and evolutionary algorithms.

Factual data banks and their application to the synthesis and design of chemical processes and the development and testing of thermophysical property estimation methods

Factual data banks nowadays play an important role as a source for thermophysical property data for use in chemical process simulation, environmental models, and many other computer-based applications. In this work, the historical developments leading to modern factual data banks, the differences compared to other more bibliographically oriented data banks, and their most important applications and future potential will be discussed by using the example of the Dortmund Data Bank (DDB). As the development of the different predictive models for mixtures is covered in a separate publication, this paper focuses on pure-component property estimation, regression of model parameters, test and verification of model parameters prior to process simulation, and advanced topics in process synthesis such as selection of entrainers and data-mining applications.

Model Evaluation for the Prediction of Solubility of Active Pharmaceutical Ingredients (APIs) to Guide Solid-Liquid Separator Design

Graphical Abstract A guide for the selection of predictive models is provided, which considers various solute and solvent properties, such as molecular mass, functional group diversity and hydrophobia/hydrophilia Unlabelled image