Frank Platte

Novel Simulation Approaches for Cyclic Steady-state Fixed-bed Processes Exhibiting Sharp Fronts and Shocks

Over the past decades, the field of chemical engineering has witnessed an increased interest in unsteady-state processes. Multifunctional, as well as intensified chemical processes, may exhibit instationary behaviour especially when based on periodical operating conditions. Ideally, instationary processes lead to a higher yield and increased selectivities compared to conventional steady-state fixed-bed processes. Typical candidates among these are the reverse-flow-reactor, the chromatographic reactor and the adsorptive reactor. Since the underlying regeneration strategy is nearly always based on cycles — e.g., a reaction cycle is followed by a regeneration cycle and so on — the overall temporal behaviour of such processes eventually develops into cyclic steady-states (after a transient phase). Experiments reveal a slow transient behaviour into the cyclic steady-state. This can also be observed in simulation based on conventional numerical treatment such as the method of lines. In addition to this problem many instationary processes exhibit sharp fronts or even shocks which require stabilisation of the convective terms. In this work we present a method of combining the idea of global discretisation with modern stabilisation techniques of type FEM-FCT and FEM-TVD in order to obtain an efficient, well approximating and robust tool for the general simulation of instationary and in particularly cyclic steady-state processes.

Multivariate Characterization of a Continuous Soot Monitoring System Based on Raman Spectroscopy

The demand for precise and continuous monitoring of air quality has increased. An important descriptor of air quality is the concentration of problematic carbonaceous particles responsible for diseases and climate change. The specific measurement of carbonaceous components in the air is still a topic in research and development. Here, we introduce an integrated and continuous soot monitoring system based on Raman spectroscopy. In comparison to the often utilized light absorption, Raman spectroscopy is capable of determining the graphitic microstructure found in carbonaceous particles. We present first measurements taken in a controlled environment contaminated with varying concentrations of diesel soot. The Raman bands of soot turn out to be tightly mixed up with signals from secondary physical factors. In order to evaluate the data, multivariate methods are applied. After determination of the latent variables using principal component analysis (PCA), the system is further rotated using a linear discriminant analysis (LDA)-criterion and a subsequent nonlinear iterative partial least squares (NIPALS)-like step. One of the variables obtained by this methodology can be shown to exclusively describe the optical filter loading while the orthogonal factor space allows for conclusions on the secondary factors. Copyright 2015 American Association for Aerosol Research

Multi-Step Pattern-Recognition: A Powerful Tool for Substance Identification Based on Real-World Terahertz-Spectra

Combining different chemometric tools we demonstrate the reliable identification of substances out of real-world terahertz-spectra. Systematic evaluation of the spectra allows for the distinction between spectral properties arising from samples geometry versus true material absorption.