According to some authors development of monolithic catalysts and/or reactors has been one of major achievements in the field of heterogeneous catalysis and chemical reaction engineering of the ...recent years. This work is aimed at pointing out the advantages of monolithic catalysts and/or reactors with respect to the conventional ones, with particular focus on the integral approach to the catalyst and reactor design.
The paper is divided into several parts. The first part gives basic definitions and classification of monolithic catalysts, including basic features of the monoliths and factors that have proceeded to the development and application of the monolith structures. It is explained that monoliths belong to the class of the catalytic reaction systems, where usual differences between catalysts and reactors, arising from their action level, are diminishing. Second part of paper is devoted to the preparation of monolithic catalysts. Next part deals with their commercial application with particular emphasis on the less known applications, and those which are still under development. The paper concludes with forecast of potential monoliths applications and ends up with the future research priorities and directions.
Photocatalytic oxidation of toluene in the gas phase over UV-illuminated thin layer of titanium dioxide was studied. The reaction was performed in the annular photocatalytic reactor at the room ...temperature and at various space times. The inlet reacting mixture consisted of air containing toluene and water vapors. Dependence of the reaction rate on various operating variables (water content, inlet toluene concentration and gas flow rate) was examined. The catalytic activity for toluene removal was evaluated by measuring the inlet and outlet toluene concentrations with GC/FID at the steady-state conditions. The additional XRD and FTIR measurements were carried out to get better understanding of the catalytic properties.
Modelling analysis was carried out to investigate effect of the key parameters on the reactor performance. To understand complex interaction between the chemical reaction and mass transfer phenomena, experimental data were analysed and compared with three different mathematical models (one-dimensional (1D) model and two-dimensional (2D) models based on ideal flow and laminar flow conditions). The proposed models were verified by comparing the computer simulation data with the experimental laboratory results. It was found out that behaviour of the annular photocatalytic reactor was mainly limited by the interphase mass transfer. Finally, the 2D heterogeneous model, based on the assumed laminar flow through the reactor, appeared to be the most suitable model for a detailed description of the annular photocatalytic reactor used for air pollution remediation.
This work presents a Safety by Design (SbD)-driven approach to the evaluation of process safety and reaction modeling that was effective in obtaining enhanced process knowledge and defining a design ...space for chemical reaction hazards. The SbD approach is presented for a case study involving the process development of the Duff reaction of phenol derivative with hexamine as a formylation reagent in polyphosphoric acid as a solvent. The starting materials were characterized by a thermal scan, and reactions were explored by different calorimetric methods. The enthalpies of physical and chemical rates of starting materials were determined using an isoperibol reaction calorimeter. The adiabatic calorimeter data provided experimental knowledge of possible side and decomposition reactions. The parameters of these reactions were estimated, which is of significant importance for scaling up the processes. The engineering aspects of the process were explored by process modeling using computer process simulators. On the basis of the proposed reaction mechanism and the combination of the heat and mass transfer and the reaction’s thermodynamics and kinetics, the safety risk was described by modeling of the process space through safety parameters (e.g., adiabatic time to maximum rate, maximum temperature, and pressure rise) under practical operating conditions of a plant and its equipment limitations (reactor batch size, time of reagent addition, and/or initial jacket temperature).
► Photocatalytic oxidation of toluene was used as the model reaction. ► Stimulus- response technique was applied. ► Different reactor models were used and appropriate reactor parameters are ...estimated. ► The reactor hydrodynamics has important influence on the mathematical model.
This study deals with the modelling of non-ideal flow in a tubular photocatalytic reactor with thin layer of TiO2 photocatalyst. The objective was to analyse different level of mixing in the photoreactor applying basic principles of chemical reaction engineering. For this purpose photocatalytic oxidation of toluene was used as the model reaction. Photocatalytic reactor was operated in two different flow modes: classic type of an annular reactor with basically ideal (plug) flow with some extent of dispersion and annular flow reactor acted as stirred tank reactor with mixing of reaction mixture accomplished by recirculation. A series of experiments with step input disturbance at the entrance of the reactor with different air flow was performed in order to achieve better understanding of the reactor hydrodynamics. Several reactor models are applied, such as one dimensional model of tubular reactor at the steady state conditions, axial dispersion model at non-stationary conditions and the model of the continuous non-stationary stirred tank reactor. Numerical methods necessary for solving model equations and parameter estimation were described.
•Alphabet entropy (AlphEn), a symbolic dynamics method was applied in HRV analysis.•Feature selection method symmetrical uncertainty was used to find relevant features.•Sensitivity of arrhythmia ...classification for common feature combinations is improved.•Single best AlphEn feature outperforms other entropies for arrhythmia classification.
Symbolic dynamics’ methods provide a description of time series variability that allows inference of new predictive markers. Classification of disorders using symbolic dynamics is accomplished through the use of nonlinear entropies, measured upon encoded series.
This work applies a recently developed symbolic dynamics method, alphabet entropy (AlphEn) to heart rate variability (HRV) analysis in order to improve automatic classification of cardiac arrhythmias. Experiments are conducted on PhysioNet MIT-BIH Arrhythmia Database. The approach is experimentally compared with other HRV linear and nonlinear feature combinations established in literature. AlphEn is experimentally compared with other common nonlinear entropies: Shannon’s entropy, approximate entropy, sample entropy, etc. Feature selection using symmetrical uncertainty is used for discovering relevant AlphEn features and random forest algorithm is used for arrhythmia classification.
The best classification result obtained for six heart rhythms on 20s segments is achieved for AlphEn no-change threshold θ=100ms. AlphEn features improved mean sensitivity of other feature combinations by 2% on average, with the best results achieved: SENS: 91.2%, SPEC: 97.1%, AUC: 99.0%. AlphEn may be used efficiently by adding top 10 ranking features, obtained with symmetrical uncertainty, to other established combinations. AlphEn provides the best incremental result to linear feature combination with respect to the inspected entropies.
AlphEn improves the results of established HRV feature combinations on the problem of automatic cardiac arrhythmia classification. The method enables the extraction of a number of potentially significant, domain-oriented features. It can be used as an accurate first-hand screening for arrhythmia problems.
A laboratory laser beam drying method for com grain kemels is presented and the corresponding energy transfer is analysed. The proposed drying method enables fast and efficient decrease in grain ...humidity while preserving grain sprouting. Laser beam was directed to the thin grain layer with powers of 10 kW/m super(2) and 20 kW/m super(2). Grains were illuminated from one side during a period of 30 s with 100 mW, 655 nm and 200 mW, 660 nm collimated laser beam. The method exhibits at least an order of magnitude higher energy transfer compared to the classical drying method that uses hot air as drying medium. The energy savings increase, compared to classical hot air drying, both in laboratory conditions, was between 23,56 and 58,70 % (100 mW laser) and 10,62 % (200 mW laser), depending on grain wet basis and decreasing with decrease of moisture content.Original Abstract: Ovaj rad analizira metodu susenja zrna kukuruza laserskim zracenjem u laboratorijskim uvjetima i prijenos energije tijekom procesa. Predlozena metoda susenja omogucuje brzo i ucinkovito smanjenje vlaznosti zrna pri cemu ne dolazi do ostecenja reproduktivnog dijela zrna. Elementarni (tanki) sloj zrna tretiran je laserskom svjetloscu snage 10 kW/m super(2) i 20 kW/m super(2). Zrna kukuruza osvjetljivana su s jedne strane tijekom 30 sekundi sa 100 mW laserom valne duljine 655 nm i 200 mW laserom valne duljine 660 nm. Postupak susenja laserskim zracenjem pokazuje veci prijenos energije u odnosu na klasicni postupak susenja koristenjem vruceg zraka. Ustede u potrosnji energije ostvarene u laboratorijskim uvjetima u odnosu na klasicni nacin susenja zagrijanim zrakom, iznosile su izmedu 23,56 i 58,70 % (100 mW laser) i 10,62 % (200 mW laser), ovisno o vlaznosti zrnatog materijala. Snizavanjem vlage materijala doslo je do smanjenja kolicina energije potrebne za susenje.
Low-density polyethylene, one of the most important polymer products, is commonly produced in high-pressure free radical polymerization processes. A dynamic model of the high-pressure polymerization ...of ethylene initiated by oxygen in tubular reactor is introduced, and a dynamic optimization problem is formulated for process start-up strategies. The present study proposes a kinetic model based on an assumed reaction mechanism. The model describes the rates of oxygen decomposition and propagation of free radical ethylene polymerization. The mass and heat balance equations in an adiabatic tubular reactor operated at a constant pressure of 2.4 kbars and a temperature range of 110–300°C are presented. Simulations of polymerization process predict temperature of the reaction mixture, response time for cooling water, and also conversion along the reactor length. Response time was obtained using different inputs of controlled variables. Values obtained from these simulations are compared with real data from the process unit (Polietilen, Dioki
®, Zagreb, Croatia) and a model validation is confirmed. Improvement in reactor productivity and better understanding of few different start-up procedures is achieved.
In knowledge discovery and data mining from time series the goal is to detect interesting patterns in the series that may help a human to better recognize the regularities in the observed variables ...and thereby improve the understanding of the system. Ideally, knowledge discovery algorithms use time series representations that are close to those that are used by a human. The impressive pattern recognition capabilities of the human brain help to establish connections between different time series or different parts of a single time series on the basis of their visual appearance. When dealing with time series data there are two main objectives: (i) prediction of future behavior based on past behaviors and (ii) description (explanation) of time series data. Description of time series data can be used for generalization, clustering and classification.
In this paper, a novel time series classification method based on Qualitative Space Fragmentation is presented. The main characteristics of the presented method are expansion and coding of quantitative time series data together with extraction of symbolic and numeric features based on human visual perception. The expansion and coding process results in the creation of a qualitative difference vector. The qualitative difference vector conveys full information on the variation of the particular time series and can be seen as a single point in
m-dimensional qualitative-space. Symbolic and numeric features based on human visual perception are extracted from the qualitative space and used for the decision tree construction that is later employed in time series classification. The application of the proposed method is demonstrated through two different case studies. In the first case study, the method was tested in the context of synthetic Control Chart Pattern data, which are time series developed for the assessment of the statistical process control. The obtained results were compared with the standard Qualitative Similarity Index method. In the second case study the method was tested in the field of analytic chemistry – polarography, an electrochemical method for analyzing solutions containing reducible or oxidizable substances.
Brain-computer interfaces (BCI) are devices that enable communication between a computer and humans by using brain activity as input signals. Brain imaging technology used in a BCI system is usually ...electroencephalography (EEG). In order to properly interpret brain activity, acquired signals from the brain have to be classified correctly. In this paper EEG signals are transformed by means of discrete wavelet transform. Thus the obtained signal features are used as inputs for a neural network classifier that should separate five different sets of EEG signals representing various mental tasks. Mean classification accuracy for the recognition of all five tasks was 90.75% and mean classification accuracy for the recognition of two tasks (baseline and any other mental task) was 99.87%. The same procedure was also used on the motor imagery dataset. A mean classification accuracy of 68.21% suggests alternative methods of feature extraction for motor imagery tasks.
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