Model-Based Design of Parallel Experiments

Abstract

Advanced model-based experiment design techniques are essential for the rapid development, refinement, and statistical assessment of deterministic process models. One objective of experiment design is to devise experiments yielding the most informative data for use in the estimation of the model parameters. Current techniques assume that multiple experiments are designed in a sequential manner. However, multiple equipment can sometimes be available, and simultaneous (parallel) experiments could be advantageous in terms of time and resources utilization. The concept of model-based design of parallel experiments is presented in this paper. Furthermore, a novel criterion for optimal experiment design is proposed: the criterion aims at maximizing complementary information by considering different eigenvalues in the information matrix. The benefits of adopting such an approach are discussed through an illustrative case

Model-based experimental analysis of enzyme kinetics in aqueous–organic biphasic systems

“…OED is, therefore, an iterative procedure (Box and Lucas, 1959;Cappuyns et al, 2007;Franceschini and Macchietto, 2008d;Walter and Pronzato, 1990). OED can also be employed for designing parallel experiments (Galvanin et al, 2007). Only few applications of OED for the design of enzymatic experiments exist (Duggleby and Clarke, 1991;Lindner and Hitzmann, 2006;Murphy et al, 2003).…”

Model‐based analysis of chemical‐looping combustion experiments. Part II: Optimal design of CH4‐NiO reduction experiments

“…Iteration between steps (1)-(3) in a sequential manner provides a progressive reduction in parameter uncertainty, by exploiting new information from previous experiments. 45 This sequential approach is historically used, but may not be optimal in terms of time and resources. In particular, CLC processes require substantial time to initially reach the temperature set-point and oxygen carrier stability, but afterwards, useful data can be generated quickly, given that gas flows can be easily changed to initiate the reduction, purge, and oxidation cycles.…”

“…Recently, parallel approaches were used to propose multiple experiments within one design. 45 A potential advantage of the parallel design strategy is that each experiment can be designed to maximize a specific aspect of the information, rather than the overall set, which decreases the size of the optimization problem and increases the effectiveness of the design. In this work, sequential and parallel approaches are explored to propose optimal experiments for kinetic parameter estimation.…”

Methodology for Optimization of Polymer Blends Composition

“…Several optimal design criteria (ODC) have been suggested and considered by different case studies; Walter & Pronzato (1990) gave a detailed discussion of available ODC and their geometrical interpretations. Lately, Atkinson (2003) used DOE for non-constant measurement variance cases and Galvanin et al (2007) extended the DOE territory to parallel experiment designs.…”