Application of empirical modelling in multi-layers membrane manufacturing

Multistructured membranes based on ultrafine fibers of polymethylmethacrylate-co-methacrylic acid (PMMA-co-MAA) and TiO₂ nanoparticles have been obtained by electrohydrodynamic (EHD) technologies, for active filter media manufacturing. Process optimization of the nanofibers based layers has been investigated by response surface methodology (RSM) in order to predict the domain of the parameters where the smallest fiber diameter can be achieved. A quantitative relationship between electrospinning parameters and the responses (mean diameter and standard deviation) was established and then the final multi-layers structure of nanofibers and nanoparticles has been achieved for a controlled and robust process. The nanostructured membranes have been characterized by SEM imaging, EDAX, TGA analysis and water vapour permeability and their photocatalytic activity has been tested on VOCs degradation.     

An Equal-Order DG Method for the Incompressible Navier-Stokes Equations

We introduce and analyze a discontinuous Galerkin method for the incompressible Navier-Stokes equations that is based on finite element spaces of the same polynomial order for the approximation of the velocity and the pressure. Stability of this equal-order approach is ensured by a pressure stabilization term. A simple element-by-element post-processing procedure is used to provide globally divergence-free velocity approximations. For small data, we prove the existence and uniqueness of discrete solutions and carry out an error analysis of the method. A series of numerical results are presented that validate our theoretical findings.     

Effects of loud noise exposure on mouse myocardium: a comparison with the rat

Loud noise is an environmental stressor of everyday life, which affects different organs and apparati, in particular the cardiovascular system. We have already reported that noise exposure produces significant alterations in the rat myocardium, consisting of mitochondrial damage, which is evident as lysis of the cristae and dilution of the matrix. Since there are high similarities between mouse and human species, the aim of our study was to investigate the effects of acute noise exposure on the mouse heart. We found that noise exposure affects mouse myocardium at similar subcellular sites to those already described in the rat; nonetheless, quantitative analysis of the percentage of altered mitochondria in both species disclosed a clear difference between mouse and rat myocardium, which strongly suggests a different sensitivity to noise stimulus. We hypothesize that the species differences on the extent of myocardial alterations here observed might be due to the zonal pattern of cardiac noradrenergic receptors, which should be the final effectors for noise-induced myocardial changes.     

Tuneable Heterodyne Infrared Spectrometer for atmospheric and astronomical studies

The transportable setup of the Cologne Tuneable Heterodyne Infrared Spectrometer (THIS) is presented. Frequency tuneability over a wide range provided by the use of tuneable diode lasers as local oscillators (LO) allows a variety of molecules in the mid-infrared to be observed. Longtime integration, which is essential for astronomical observations, is possible owing to tight frequency control of the LO with optical feedback from an external cavity. THIS is developed to fly on the Stratospheric Observatory for Infrared Astronomy beginning in 2006 but can also be used on different types of ground-based telescopes.     

An integrated system solution for supply chain optimization in the chemical process industry

This paper considers a complex scheduling problem in the chemical process industry involving batch production. The application described comprises a network of production plants with interdependent production schedules, multi-stage production at multi-purpose facilities, and chain production. The paper addresses three distinct aspects: (i) a scheduling solution obtained from a genetic algorithm based optimizer, (ii) a mechanism for collaborative planning among the involved plants, and (iii) a tool for manual updates and schedule changes. The tailor made optimization algorithm simultaneously considers alternative production paths and facility selection as well as product and resource specific parameters such as batch sizes, and setup and cleanup times. The collaborative planning concept allows all the plants to work simultaneously as partners in a supply chain resulting in higher transparency, greater flexibility, and reduced response time as a whole. The user interface supports monitoring production schedules graphically and provides custom-built utilities for manual changes to the production schedule, investigation of various what-if scenarios, and marketing queries. RID="*" ID="*" The authors would like to thank Hans-Otto Günther and Roland Heilmann for helpful comments on draft versions of this paper.     

Structural Fault Modeling and Fault Detection Through Neyman–Pearson Decision Criteria for Analog Integrated Circuits

A new approach for analog fault modeling and simulation is presented. The proposed approach utilizes the sensitivity of the circuit’s DC node voltages to the process variations and consequently the current deviance so as to differentiate the faulty behavior. A systematic method is proposed for the fault discrimination to minimize the probability that the circuit is accepted as a fault-free when it is faulty. Tests are generated and evaluated taking into account the potential fault masking effects of process spread on the faulty circuit responses. The introduced fault model is validated on a time-interleaved sample-and-hold circuit. Simulation results demonstrate the effectiveness of the model.     

Estimation of two-dimensional affine transformations through polar curve matching and its application to image mosaicking and remote-sensing data registration.

This paper presents a new and effective method for estimating two-dimensional affine transformations and its application to image registration. The method is based on matching polar curves obtained from the radial projections of the image energies, defined as the squared magnitudes of their Fourier transforms. Such matching is formulated as a simple minimization problem whose optimal solution is found with the Levenberg-Marquardt algorithm. The analysis of affine transformations in the frequency domain exploits the well-known property whereby the translational displacement in this domain can be factored out and separately estimated through phase correlation after the four remaining degrees of freedom of the affine warping have been determined. Another important contribution of this paper, emphasized through one example of image mosaicking and one example of remote sensing image registration, consists in showing that affine motion can be accurately estimated by applying our algorithm to the shapes of macrofeatures extracted from the images to register. The excellent performance of the algorithm is also shown through a synthetic example of motion estimation and its comparison with another standard registration technique.     

Model-based control of a simulated moving bed chromatographic process for the separation of fructose and glucose

Chromatographic separations are an expanding technology for the separation of high value products, particularly in the area of pharmaceutics, food, and fine chemicals. The simulated moving bed (SMB) process as a continuous chromatographic separation process is an interesting alternative to conventional batch chromatography, and gained more and more impact recently. The SMB process is realized by connecting several single chromatographic columns in series. A countercurrent movement of the bed is approximated by a cyclic switching of the inlet and outlet ports in the direction of the fluid stream. Because of its complex dynamics, the optimal operation and automatic control of SMB processes is a challenging task. This paper presents the design of a model-based optimization and control scheme for SMB chromatographic separation processes and its application to the separation of fructose and glucose. We propose a two-layer control architecture where the optimal operating trajectory is calculated off-line by dynamic optimization based on a rigorous process model. The parameters of the model are adapted based on online measurements. The low-level control task is to keep the process on the optimal trajectory despite disturbances and plant/model mismatch. Here identification models based on simulation data of the rigorous process model along the optimal trajectory are combined with a suitable local controller. The efficiency of the trajectory control algorithm is shown in a simulation study for the separation of fructose and glucose on an 8-column SMB plant.