Vestnik of Samara State Technical University. Technical Sciences Series

Abstract. The aim of this paper is to describe existing approaches to automation in enterprise management systems of invoice factoring operations. The relevance of this problem is estimated by the volume and dynamics of growth of the invoice factoring market in the Russian Federation. The existing performance problems inherent in software built on the basis of classical algorithms are considered, and their optimization by using quantum algorithms is proposed. Attention is focused on the problem of parallel computing as the main feature, which allows to achieve a significant increase in computing power. Possible way of solution, based on the joint use of quantum and classical approach within one software complex is given. Application of quantum Monte Carlo method for the purpose of improvement of the automated information system of the enterprise is described. The received result allows to draw a conclusion about perspective of use of the given technique for construction of the combined quantum and classical algorithms in systems of management of factoring operations.

The paper discusses the experience of developing and identifying a model of a waste heat boiler as a distributed parameters plant. The waste heat boiler is considered as a heat exchanger with cross flows of interacting media. The first order hyperbolic equation acts as a mathematical model of water flow heating with a variable rate. Using the spectral method of distributed systems, a representation of the problem is obtained in the form of an expansion into a series in an orthonormalized basis, which makes it possible to represent the solution in the form of a vector-matrix model of the state space. The state-space representation is used to implement the model in a dynamic systems simulation package. The heater temperature calculation is based on the energy balance equation. The temperature of the media separator wall is determined by the heat fluxes between the exhaust gas, the wall, and the heated water. The wall temperature is assumed to be constant along the entire length of the heat exchanger. The paper presents a block diagram of the model, which takes into account the mutual influence of the wall temperatures and the heated water flow. The heat flux from the exhaust gas is calculated directly from the known parameters of the exhaust gas at the inlet and outlet of the waste heat boiler. Based on the design parameters of the heat exchanger, the dynamic characteristics of the heat transfer process are determined. The data obtained during the operation of the waste heat boiler are used to identify the heat transfer coefficient between the walls of the heat exchanger and the water flow. The result of the heat transfer coefficient identification agrees with the reference data. The article presents graphs of the original data, simulation results. It is shown that the maximum mismatch between the model and real data does not exceed two degrees, and the mean absolute error is less than 0.2 degrees.

The passage of streaming video traffic through the backbone switch of the communication node is considered. The features of video traffic, which has a pronounced burst character, are analyzed. The influence of the characteristics of such flows on the sizes of queues in the nodes of telecommunication networks is studied. The results of analytical consideration and simulation modeling are presented. The generalized Khinchin-Pollachek formula is considered and for group flows a linear dependence of the numerator of this formula on the load factor is shown. It is shown that, in contrast to Poisson flows, the queue sizes in multichannel queuing systems with video traffic flows practically do not decrease with an increase in the number of channels.

The article presents the functionality and architecture of the software laboratory for ontological analysis and through this “prism” – the methodology of this analysis. The methodological complex of ontological analysis and the procedure for its application provide extraction from the data of multidimensional observations and measurements of the knowledge domain of its semantic model in the form of a formal ontology – a set of formal concepts, each of which is determined by extent and intent. In the set of formal concepts, a partial order is revealed (a binary relation of generalization) and intensional relations are revealed that reflect the connections between the elements of the concepts extents. The developed software laboratory differs from the well-known tools for constructing formal ontologies based on empirical object-feature data (i.e., based on data presented in the generally recognized form of a measurement results registration protocol), first of all, by taking into account the realities of accumulating information about the knowledge domain under study. In the general case, they cause the incompleteness and inconsistency of the initial data, for the processing of which the apparatus of multi-valued vector logic is involved. Another unique difference of the software laboratory is the consideration of a priori known (i.e., known before measurements) constraints on the properties existence during the primary processing of empirical data – binary relations of conditionality and incompatibility of objects properties of the studied knowledge domain. The presented software laboratory is implemented on the Excel table processor platform and the programming language Visual Basic for Application. The main motive for this choice was to ensure the availability and facilitate the familiarization of ontological data analysis technology by a very wide range of users who use Excel in their professional work.

The detection of the wear particles in the engines’ lubrication systems is one of the most effective ways to assess the state of the bearing assemblies of machines and mechanisms. The most promising existing systems for online monitoring of wear particles are based on the eddy current methods for monitored parameters conversion. The reason is that such systems have the ability not only to determine the particle size, but also to recognize its magnetic properties, which makes it possible (under certain conditions) to localize the place of the defect development. At the same time, it is known that the ambient temperature changes in the monitored zone are one of the main external factors that have a significant impact on the informative parameters of eddy current converters. This is of particular importance for debris monitoring systems in high-power plants’ lubrication systems (e.g. gas turbine engine), where the oil temperature can vary widely (-50...+160 °C). The temperature impact on the parameters of the electrical circuit of sensing element in the cluster single-coil eddy current sensor of metal chips, which is a part of the debris continuous monitoring system prototype for high-thrust aviation gas turbine engine, is studied in the article. A typical design of the single-coil sensing element is considered. The study results of the temperature effect on the sensing element inductance, as well as on the parameters of the current lead that connects the sensing element to the matching transformer and to the measuring circuit are presented. Methods for reducing the impact of temperature changes in the monitored area on the parameters of the electrical circuit of the sensing element are proposed, too.

According to the rules of the Wholesale Electricity and Capacity Market, a power plant is both a producer of electricity and its consumer, is obliged to form a forecast of electricity consumption to form an energy balance, and is financially responsible for the deviation of actual consumption from that given in the forecast. The first part of the article analyzes the accuracy of the existing method for predicting the auxiliary power consumption of one of the operating nuclear power plants. The calculation of various estimates of the forecasting error has been performed and it is shown that the method used in certain time intervals has insufficient accuracy. The second part analyzes the factors that potentially affect the auxiliary power consumption, evaluates the quality of the regression relationship between these factors and power consumption, and concludes that they are significant for the development of a new forecasting technique.