Solvent-free semihydrogenation of acetylene alcohols in a capillary reactor coated with a Pd-Bi/TiO2 catalyst

© 2016 Elsevier B.V. All rights reserved. A solvent-free semihydrogenation of 2-methyl-3-butyn-2-ol (MBY) to 2-methyl-3-buten-2-ol was performed in a capillary reactor (10 m long, 0.53 mm i.d.) coated with a titania supported Pd-Bi catalyst. Several coatings with different Pd/Bi ratio have been prepared. The catalysts have been characterized with SEM, TEM, EDX, XRD analysis and N 2 adsorption-desorption measurements. The maximum alkene yield of 90% was obtained at a molar Pd/Bi ratio of 11. The yield was increased to 95% in the presence of 10 mol.% pyridine in the reaction mixture. The alkene selectivity decreased with time due to leaching of Bi. The leaching was fully suppressed in the presence of 1 vol.% acetic acid in the reaction mixture. The catalyst remained stable for 100 h of continuous operation. The results demonstrate that capillary reactors provide alkene selectivity the same compared to ideal stirred tank batch reactors

MODELING PARTIAL IGNORANCE IN ARTIFICAL INTELLIGENCE APPLICATIONS

This study aims to extend and deepen a survey of modern extensions of probability theory represented in [6, 7]. The classical probability theory possesses rather limited possibilities and cannot cope with situations of partial ignorance. Other approaches are required allowing one to solve tasks of that kind. The given paper considers the generalised approach to modelling partial ignorance and its interpretation in the terms of upper and lower probabilities, second order probabilities and belief functions

UNCERTAIN PROBABILITIES

The uncertainty of probabilistic evaluations results from the lack of sufficient information and/or knowledge underlying those random events. Uncertainty representation in the form of second order probability distribution or interval evaluations does not cause any objections from the theoretical point of view. On the other hand, what is worthy in the second order probabilities is that they allow one to model a real uncertainty of subjective probabilistic evaluations resulting from the lack of information and/or knowledge. Processing of uncertain information regarding probabilistic evaluations can help make a validated decision about the collection of additional information aimed to remove completely or to reduce the existing uncertainty

Scale up study of capillary microreactors in solvent-free semihydrogenation of 2‐methyl‐3‐butyn‐2‐ol

A 2.5 wt.% Pd/ZnO catalytic coating has been deposited onto the inner wall of capillary reactors with a diameter of 0.53 and 1.6 mm. The coatings were characterised by XRD, SEM, TEM and elemental analysis. The performance of catalytic reactors was studied in solvent-free hydrogenation of 2-methyl-3-butyn-2-ol. No mass transfer limitations was observed in the reactor with a diameter of 0.53 mm up to a catalyst loading of 1.0 kg (Pd) m −3 . The activity and selectivity of the catalysts has been studied in a batch reactor to develop a kinetic model. The kinetic model was combined with the reactor model to describe the obtained data in a wide range of reaction conditions. The model was applied to calculate the range of reaction conditions to reach a production rate of liquid product of 10–50 kg a day in a single catalytic capillary reactor

SIMULATED ANNEALING METHOD IN THE CLASSIC BOLTZMANN MACHINES

The classical Boltzmann machine is understood as a neural network proposed by Hinton and his colleagues in 1985. They added noise interferences to the Hopfield model and called this network a Boltzmann machine drawing an analogy between its behaviour and physical systems with the presence of interferences. This study explains the definition of “simulated annealing” and “thermal equilibrium” using the example of a partial network. A technique for calculating the probabilities of transition states at different temperatures using Markov chains is described, an example of the application of the SA - travelling salesman problem is given. Boltzmann machine is used for pattern recognition and in classification problems. As a disadvantage, a slow learning algorithm is mentioned, but it makes it possible to get out of local minima. The main purpose of this article is to show the capabilities of the simulated annealing algorithm in solving practical tasks.

COMPARISON OF DIFFERENT FUZZY AHP METHODOLOGIES IN RISK ASSESSMENT

Being able to evaluate risks is an important task in many areas of human activity: economics, ecology, etc. Usually, environmental risk assessment is carried out on the basis of multiple and sometimes conflicting factors. Using multiple criteria decision-making (MCDM) methodology is one of the possible ways to solve the problem. Methodologies of analytic hierarchy process (AHP) are the most commonly used MCDM methods, which combine subjective and personal preferences in risk assessment process. However, AHP involves human subjectivity, which introduces vagueness type of uncertainty and requires the usage of decision making under those uncertainties. In this paper it was considered to deal with uncertainty by using the fuzzy-based techniques. However, nowadays there exist multiple Fuzzy AHP methodologies developed by different authors. In this paper, these Fuzzy AHP methodologies will be compared, and the most appropriate Fuzzy AHP methodology for the application in case of environmental risks assessment will be offered on the basis of this comparison

PROBABILISTIC INFERENCE FOR INTERVAL PROBABILITIES IN DECISION-MAKING PROCESSES

The present paper considers one approach to Bayes’ formula based probabilistic inference under interval values of relevant probabilities; the necessity of it is caused by the impossibility to obtain reliable deterministic values of the required probabilistic evaluations. The paper shows that the approach proves to be the best from the viewpoint of the required amount of calculations and visual representation of the results. The execution of the algorithm of probabilistic inference is illustrated using a classical task of decision making related to oil mining. For visualisation purposes, the state of initial and target information is modelled using probability trees.

FUZZY ROBUST ESTIMATES OF LOCATION AND SCALE PARAMETERS OF A FUZZY RANDOM VARIABLE

A random variable is a variable whose components are random values. To characterise a random variable, the arithmetic mean is widely used as an estimate of the location parameter, and variation as an estimate of the scale parameter. The disadvantage of the arithmetic mean is that it is sensitive to extreme values, outliers in the data. Due to that, to characterise random variables, robust estimates of the location and scale parameters are widely used: the median and median absolute deviation from the median. In real situations, the components of a random variable cannot always be estimated in a deterministic way. One way to model the initial data uncertainty is to use fuzzy estimates of the components of a random variable. Such variables are called fuzzy random variables. In this paper, we examine fuzzy robust estimates of location and scale parameters of a fuzzy random variable: fuzzy median and fuzzy median of the deviations of fuzzy component values from the fuzzy median.

PROPERTY INSURANCE DECISION-MAKING ON THE BASIS OF UTILITY FUNCTIONS

Property and other valuables insurance is widespread all over the world. An insurance company assumes the risk of damage or total destruction of the insured property. When this kind of damage or destruction is established, the company pays its client compensation (insurance premium) up to the amount specified in the insurance contract. For his part, the insured must pay a certain amount to the firm for the provision of insurance services. In any property insurance process, the question arises as to whether it is appropriate to insure the property for the price offered by the firm. The paper considers an approach to solving this problem based on expected utility theory