Prediction of Flooding in Packed Liquid-Liquid and High-Pressure Extraction Columns Using a Gaussian Process

Reliable prediction of flooding conditions is needed for sizing and operating packed extraction columns. Due to the complex interplay of physicochemical properties, operational parameters and the packing-specific properties, it is challenging to develop accurate semi-empirical or rigorous models with a high validity range. State of the art models may therefore fail to predict flooding accurately. To overcome this problem, a data-driven model based on Gaussian processes is developed to predict flooding for packed liquid-liquid and high-pressure extraction columns. The optimized Gaussian process for the liquid-liquid extraction column results in an average absolute relative error (AARE) of 15.23 %, whereas the algorithm for the high-pressure extraction column results in an AARE of 13.68 %. Both algorithms can predict flooding curves for different packing geometries and chemical systems precisely.     

Investigation of the action of flame retardants in cellulose. I. Investigation of the flame retardant action of 2,2′-oxybis(5,5-dimethyl-1,3,2-dioxaphosphorinane-2,2′-disulfide) in cellulose

Pyrolysis experiments were performed in high vacuum and under reduced air pressure (100 Pa). The volatile products of pure cellulose and cellulose containing various amounts of flame retardant 2,2′-oxybis (5,5-dimethyl-1,3,2-dioxaphosphorinane-2,2′-disulfide), i.e., Sandoflam 5060 of Sandoz AG, were studied by means of gas chromatography in combination with mass spectroscopy. The volatile products were characterized with infrared spectroscopy. The studied revealed that the incorporation of the flame retardant enhanced the water release and shifted the onset of this reaction to lower temperature. On the basis of these findings an explanation for the mechanism of flame retardancy in generated cellulose fibers modified with this particular flame retardant is attempted. From experiments with different residual air pressure the influence of oxygen on the primary processes of the pyrolytic degradation of cellulose is being discussed.     

Modeling tool wear in end-milling using enhanced GMDH learning networks

This paper presents an enhanced approach to predictive modeling for determining tool-wear in end-milling operations based on enhanced-group method of data handling (e-GMDH). Using milling input parameters (speed, feed, and depth-of-cut) and response (tool wear), the data for the model is partitioned into training and testing datasets, and the training dataset is used to realize a predictive model that is a function of the input parameters and the coefficients determined. In our approach, we first present a methodology for modeling, and then develop predictive model(s) of the problem being solved in the form of second-order equations based on the input data and coefficients realized. This approach leads to some generalization because it becomes possible to predict not only the test data obtained during experimentation, but other test data outside the experimental results can also be used. Moreover, this approach makes it easy to present the realized solution in a form that can be further optimized for the input parameters using some optimization techniques. The results realized using our e-GMDH method are promising, and the comparative study presented shows that the e-GMDH outperforms polynomial neural network (PNN); moreover, it is more flexible than the conventional GMDH, which tends to produce nonlinear solutions even for simple problems. In the investigation, the extended particle swarm optimization (PSO) technique was applied to obtain the optimal parameters. Consequently, the modeling approach is extremely useful in realizing a computer-aided process-planning system in an advanced manufacturing environment.     

Influence of Reaction Parameters on the Hydrogenolysis of Hydroxymatairesinol Over Carbon Nanofibre Supported Palladium Catalysts

The density functional theory (DFT/B3LYP) calculations were applied to investigate the interaction of a Pt₆ particle with the ZSM-5 zeolite framework. The electronic structure of the metal particle is strongly affected by the interaction with basic framework oxygens and acid sites of the zeolite support. Adsorption on basic sites (E_ads = 6 kcal/mol) favors the formation of the electron enriched metal cluster. Interaction of the platinum cluster with the acid site characterized by stabilization energy of 47 kcal/mol results in oxidation of the metal particle and suppression of Brønsted acidity of the support. The hypothesis is put forward that the oxidized platinum particle can function as an active site for the alkane isomerisation on platinum supported high silica zeolites.     

Pruning Algorithms for Rule Learning

Pre-pruning and Post-pruning are two standard techniques for handling noise in decision tree learning. Pre-pruning deals with noise during learning, while post-pruning addresses this problem after an overfitting theory has been learned. We first review several adaptations of pre- and post-pruning techniques for separate-and-conquer rule learning algorithms and discuss some fundamental problems. The primary goal of this paper is to show how to solve these problems with two new algorithms that combine and integrate pre- and post-pruning.     

Gain-coupled DFB lasers with a titanium surface Bragg grating

The improved performance of gain-coupled DFB lasers incorporating a titanium surface Bragg grating and a strained layer multiquantum well active region for operation at 1.55 μm is presented. Besides the essentially simplified fabrication process, the incorporation of the metallic, absorptive grating yields stable singlemode operation with a high sidemode suppression     

AV通信产业面临的全球性机遇

我今天很高兴能来到这里与你们一起讨论关于AV通信产业所面临的全球性机遇以及中国AV通信产业如何随着世界市场共同成长的问题。从某种意义上讲，我们所面临的机遇是无限的，因为对于政府、商务、教育和几乎其他所有机构的未来通信基础构造而言，AV通信将是极其关键的。     

How would an EU-membership of the Visegrád- countries affect Europe‘s economic geography?EU-membership of the Visegrád-countries

The question posed in the title of the paper is answered by simulating EU-integration of the Visegrád-countries by a spatial computable general equilibrium (SCGE) model. A two-sector model is calibrated for a system of almost 100 regions covering the whole area of Europe and a rest of world region. The sectors are a local sector, producing non-tradables under perfect competition, and a tradables sector, producing a large number of tradable varieties under monopolistic competition. Trade between regions is costly, with costs depending on geographic distance and national impediments to trade. The model is calibrated such that the equilibrium solution reproduces benchmark data about international trade and regional incomes. Economic integration is simulated by reducing impediments to trade between integrating countries and calculating a new counterfactual equilibrium.