Publications by Michael Amrhein

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The identification of reaction kinetics represents the main challenge in building models for reaction systems. The identification task can be performed via either simultaneous model identification (SMI) or incremental model identification (IMI), the latter using either the differential (rate-based) or the integral (extent-based) method of parameter estimation. In SMI, a rate law must be postulated for each reaction, and the modeled concentrations are obtained by integration of the balance equ

A classification methodology for the automatic detection of start- and endpoints of chemical and biotechnological reaction systems from spectral reaction data is proposed. In the calibration phase, several batch experiments must be conducted covering the e ...

Spectrometers are enjoying increasing popularity in bioprocess monitoring due to their non-invasiveness and in-situ sterilizability. Their on-line applicability and high measurement frequency create an interesting opportunity for process control and optimi ...

This dissertation is concerned with the development of a methodology and appropriate tools for the investigation of chemical reaction systems using measured data. More specifically, the determination of reaction stoichiometry and kinetics from concentration or, preferably, spectral measurements is considered. The main contribution of this work is the derivation of a nonlinear transformation of the dynamic model that enables the separation of the evolution of the states into three parts: (i) the reaction-var

This paper proposes a variation of the incremental approach to identify reaction and mass-transfer kinetics (rate expressions and the corresponding rate parameters) from concentration measurements for both homogeneous and gas-liquid reaction systems. This ...

Reaction systems are typically represented by first-principles models that describe the evolution of the states (typically concentrations, volume and temperature) by means of conservation equations of differential nature and constitutive equations of algeb ...

The identification of reaction kinetics involves the determination of a model structure (reaction stoichiometry, rate laws for all reactions) and its corresponding parameters from experimental data. An incremental identification approach for determining the kinetics of homogeneous reaction systems from transient concentration measurements has been developed in previous work [1, 2]. This approach decomposes the identification task into a sequence of sub-tasks that include the identification of the rate laws

The feasibility of using chemometric techniques for the automatic detection of whether a rabbit kidney is pathological or not is studied. Sequential images of the kidney are acquired using Dynamic Contrast-Enhanced Magnetic Resonance Imaging with contrast ...

The effect of the presence of metabolism-induced concentration correlations in the calibration samples on the prediction performance of partial least-squares regression (PLSR) models and mid-infrared spectra from Chinese hamster ovary cell cultures was investigated. Samples collected from batch cultures contained highly correlated metabolite concentrations as a result of metabolic relations. Calibrations based on such samples could only be used to predict concentrations in new samples if a similar correlati

Latent-variable calibrations using principal component regression and partial least-squares regression are often compromised by drift such as systematic disturbances and offsets. This paper presents a two-step framework that facilitates the evaluation and ...

This paper deals with the identification of reaction and mass-transfer rates from concentrations measured in gas-liquid reaction systems. It is assumed that the reactions take place in the liquid bulk only. The identification proceeds in two steps: (i) est ...

An incremental identification approach for determining the kinetics of homogeneous reaction systems from transient concentration measurements has been developed in previous work (Marquardt, W. Chemical Engineering Research and Design 83(A6), 561–573, 2005) ...

Dynamic Magnetic Resonance Imaging (MRI) with contrast media injection is an important tool to study renal perfusion in humans and animals. The goal of this study is to build classifiers for the automatic classification of a kidney as healthy or pathological. A new algorithm is developed that segments out the cortex from the rest of the kidney including the medulla, the renal pelvic, and the background. The performance of two classifier-types (Soft Independent Method of Class Analogy, SIMCA; Partial Least S

For gas-liquid reaction systems with inlet and outlet streams, this paper proposes a linear transformation to decompose the numbers of moles vector into five distinct parts, namely, the extents of reaction, the extents of mass transfer, the extents of inle ...

Real-time data reconciliation of concentration estimates of process analytes and biomass in microbial fermentations is investigated. A Fourier-transform mid-infrared spectrometer predicting the concentrations of process metabolites is used in parallel with ...

The economic environment in the specialty chemicals industry requires short times to market and thus the ability to develop new products and processes very rapidly. This, in turn, calls for large scale-ups from laboratory to production. Due to scale-relate ...

Correct prediction of analyte concentrations from a new spectrum without drift is possible provided the spectrum lies in the row space spanned by the calibration spectra (space-inclusion condition). However, this condition may be violated as on-line spectr ...

It is well known that the prediction errors from principal component regression (PCR) and partial least-squares regression (PLSR) can be reduced by using both labeled and unlabeled data for stabilizing the latent subspaces in the calibration step. An appro ...

On-line measurements from first-order instruments such as spectrometers may be compromised by instrumental, process and operational drifts that are not seen during off-line calibration. This can render the calibration model unsuitable for prediction of key ...

Experimental assessment or prediction of plant steady state is important for many applications in the area of modeling and operation of continuous processes. For example, the iterative implementation of static real-time optimization requires reaching stead ...

Michael Amrhein

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Incremental Model Identification of Reaction Systems

Automatic detection of reaction start/endpoints in chemical and biotechnological reaction systems

On-Line Recalibration of Spectral Measurements Using Metabolite Injections and Dynamic Orthogonal Projection

Reaction and flow variants/invariants for the analysis of chemical reaction data

Incremental Identification of Reaction and Mass-Transfer Kinetics Using the Concept of Extents

Minimal State Representation for Open Fluid-Fluid Reaction Systems

Incremental model identification for homogeneous systems – A comparison

Classification of magnetic resonance images from rabbit renal perfusion

The influence of correlated calibration samples on the prediction performance of multivariate models based on mid-infrared spectra of animal cell cultures

Framework for explicit drift correction in multivariate calibration models

Identification of reaction and mass-transfer rates in gas-liquid reaction systems

Incremental Identification of Reaction Systems - A Comparison between Rate-based and Extent-based Approaches

Classification of magnetic resonance images from renal perfusion studies of rabbits

Extents of Reaction, Mass Transfer and Flow for Gas-Liquid Reaction Systems

Data Reconciliation of Concentration Estimates from Mid-Infrared and Dielectric Spectral Measurements for Improved On-Line Monitoring of Bioprocesses

Scale-up of batch processes via decentralized control

Measurement-Based Drift Correction in Spectroscopic Calibration Models

Partial least-squares regression with unlabeled data

Drift Correction in Multivariate Calibration Models Using On-line Reference Measurements

Fast Estimation of Plant Steady State, with Application to Static RTO