107 citations · 162 across the 5 of their papers we have counts for
7 papers
Two-phase approaches to optimal model-based design of experiments: how many experiments and which ones?
Charlie Vanaret, Philipp Seufert, Jan Schwientek +5
Model-based experimental design is attracting increasing attention in chemical process engineering. Typically, an iterative procedure is pursued: an approximate model is devised, p…
An Adaptive Algorithm based on High-Dimensional Function Approximation to obtain Optimal Designs
Philipp Seufert, Jan Schwientek, Michael Bortz
Algorithms which compute locally optimal continuous designs often rely on a finite design space or on repeatedly solving a complex non-linear program. Both methods require extensiv…
Adaptive Sampling of Pareto Frontiers with Binary Constraints Using Regression and Classification
Raoul Heese, Michael Bortz
We present a novel adaptive optimization algorithm for black-box multi-objective optimization problems with binary constraints on the foundation of Bayes optimization. Our method i…
Simulation and optimal control of the Williams-Otto process using Pyomo
Jochen Schmid, Katrin Teichert, Moncef Chioua +2
We illustrate the advantages the high-level open-source software package Pyomo has in rapidly setting up and solving dynamic simulation and optimization problems. In order to do so…
Machine Learning in Thermodynamics: Prediction of Activity Coefficients by Matrix Completion
Fabian Jirasek, Rodrigo A. S. Alves, Julie Damay +6
Activity coefficients, which are a measure of the non-ideality of liquid mixtures, are a key property in chemical engineering with relevance to modeling chemical and phase equilibr…
The Good, the Bad and the Ugly: Augmenting a black-box model with expert knowledge
Raoul Heese, Michał Walczak, Lukas Morand +2
We address a non-unique parameter fitting problem in the context of material science. In particular, we propose to resolve ambiguities in parameter space by augmenting a black-box…