Increasing the mechanical properties of structural cast iron for machine-building parts by combined Mn – Al alloying

The object of research in this work was cast iron for machine-building parts, alloyed with Al. The possibility of improving the mechanical properties of cast iron by choosing the optimal Mn – Al combinations, depending on the carbon content in the cast iron, was determined. The study was carried out on the basis of available retrospective data of serial industrial melts by constructing the regression equation for the ultimate strength of cast iron in the three-factor space of the input variables C – Mn – Al. The optimization problem was solved by the ridge analysis method after reducing the dimension of the factor space by fixing the carbon content at three levels: C = 3 %, C = 3.3 %, and C = 3.6 %. It was found that the maximum values of the ultimate strength are achieved at the minimum level of carbon content (C = 3%) and are in the range of values close to 300 MPa. In this case, the Al content is in the range (2.4–2.6) %, and the Mn content is about 0.82 %. With an increase in the carbon content, there is a tendency to a decrease in the content of Mn and Al in the alloy, which is necessary to ensure the ultimate strength close to 300 MPa. The results of the ridge analysis of the response surface also showed that at the upper limit of the carbon content (C = 3.6%), it is not possible to reach the ultimate strength of 300 MPa in the existing range of Mn and Al variation. All solutions are verified for the following ranges of input variables C = (2.94–3.66) %, Mn = (0.5–1.1) %, Al = (1.7–2.9) %. Graphical-analytical descriptions of the optimal Mn – Al ratios are obtained, depending on the actual content of carbon in the alloy, which make it possible to purposefully select the optimal melting modes by controlling the tensile strength of the alloy

METHOD OF THEORY OF DIMENSIONS IN EXPERIMENTAL RESEARCH OF SYSTEMS AND PROCESSES

The method and parameters of experimental modelling of systems and processes in mechanical engineering are substantiated. The theory of similarity and dimensionality is used as an intermediate link between theory and experiment. The dimension of the factor space depends on the number of factors. The set of factors is grouped into dimensionless similarity criteria. The selected criteria are in certain dependence, such as the Galileo test, Euler and Reynolds numbers. Examples of application in experimental studies are given. The use of dimension theory in a factor-planned experiment allows reducing the number of factors, simplifies the mathematical interpretation of the response criterion and provides a graphical representation in the form of 3-D model.

Calderón–Zygmund operators on multiparameter Lipschitz spaces of homogeneous type

The purpose of this paper is to establish a necessary and sufficient condition for the boundedness of general product singular integral operators introduced by Han, Li and Lin [Y. Han, J. Li and C.-C. Lin, Criterion of the L 2 L^{2} boundedness and sharp endpoint estimates for singular integral operators on product spaces of homogeneous type, Ann. Sc. Norm. Super. Pisa Cl. Sci. (5) 16 2016, 3, 845–907] on the multiparameter Lipschitz spaces of homogeneous type M ~ = M 1 × ⋯ × M n {\tilde{M}=M_{1}\times\cdots\times M_{n}} . Each factor space M i {M_{i}} , 1 ≤ i ≤ n {1\leq i\leq n} , is a space of homogeneous type in the sense of Coifman and Weiss. These operators generalize those studied by Journé on the Euclidean space and include operators studied by Nagel and Stein on Carnot–Carathéodory spaces. The main tool used here is the discrete Littlewood–Paley–Stein theory and almost orthogonality together with a density argument for the product Lipschitz spaces in the weak sense.

Optimization of automatic control of the speed of rotation of a marine diesel engine

Annotation – The well-established method of tuning the speed governors (SG) of diesel engines during their operation under conditions of step disturbances, which are characteristic of diesel-generators, cannot be used for the main marine engines, the dynamic modes of which are associated, first of all, with heavy seas, because disturbances cannot change stepwise both along the channel for setting the rotational speed and along the load channel. In this regard, the practical need for the development of a method for tuning the SG of the main engines, which takes into account the peculiarities of their operation in heavy seas, has been determined. The study simulates the automatic speed control system (ASC) of the main marine engine HYUNDAI – MAN B&W 6G70ME-C9.2 of the large crude carrier "GOLDWAY" with the AutoChief 600 electronic SG. The minimum of instability of the controlled parameter was used as an optimality criterion, i.e. the amplitude of the oscillations of the rotational speed of the diesel engine shaft, with the most probable values of the amplitude and period of oscillations (rolling) of the disturbing effect. The study has established that changing the tuning parameters of the governor may lead to local extrema of the optimality criterion when using an electronic governor in the ACS in the factor space of disturbances on a diesel engine, which are typical for heavy seas. It means that the task, requiring finding local extrema using specialized methods, can be set when using an electronic governor in the ACS. However, a significant decrease in the instability of the rotational speed was achieved by carrying out a simple enumeration of the tuning parameters of the SG. It was also found that with a "heavy" propeller, the rotational speed stability can be increased by decreasing the proportional gain, as well as increasing the integrator time.

Methodological approaches and algorithms for recognizing and counting animals in aerial photographs

Introduction: The complexity of recognition and counting of objects in a photographic image is directly related to variability of related factors: physical difference of objects from the same class, presence of images similar to objects to be recognized, non-uniform background, change of shooting conditions and position of the objects when the photo was taken. Most challenging are the problems of identifying people in crowds, animals in natural environment, cars from surveillance cameras, objects of construction and infrastructure on aerial photo images, etc. These problems have their own specific factor space, but the methodological approaches to their solution are similar. Purpose: The development of methodologies and software implementations solving the problem of recognition and counting of objects with high variability, on the example of reindeer recognition in the natural environment. Methods: Two approaches are investigated: feature-based recognition based on binary pixel classification and reference-based recognition using convolutional neural networks. Results: Methodologies and programs have been developed for pixel-by-pixel recognition with subsequent binarization, image clustering and cluster counting and image recognition using the convolutional neural network of Mask R-CNN architecture. The network is first trained to recognize animals as a class from the array of MS COCO dataset images and then trained on the array of aerial photographs of reindeer herds. Analysis of the results shows that feature-based methods with pixel-by-pixel recognition give good results on relatively simple images (recognition error 10–15%). The presence of artifacts on the image that are close to the characteristics of the reindeer images leads to a significant increase in the error. The convolutional neural network showed higher accuracy, which on the test sample was 82%, with no false positives. Practical relevance: А software prototype has been created for the recognition system based on convolutional neural networks with a web interface, and the program itself has been put into limited operation.

Gradient structure and properties of steel castings

The influence of melt overheating in the range of 50-150 °C on the equilibrium liquidus and its cooling rate during crystallization of castings on the formation of macrostructural zones along their cross section, on the change of grain dispersion, dendritic structure characteristics and mechanical properties was investigated on the example of 25L steel. It is established that the macrostructure of castings in the direction of unilateral heat removal as it moves away from the cooled surface consists of four main structural zones - small coaxial crystals, columnar, branched and large coaxial crystals, the length and morphology of which naturally change depending on thermokinetic conditions of crystallization. The decisive role of the cooling rate at significant overheating of the melt to increase the number of crystallization nuclei, the formation of a more dispersed cast structure by increasing the degree of supercooling of the melt during crystallization is shown. The regularities of quantitative characteristics change of microstructure and dendritic structure depending on change of temperature-time parameters of crystallization in different structural zones of castings and their connection with characteristics of mechanical properties of steel are established. On the basis of mathematical processing of experimental data by linear regression analysis interpolation models and their graphical interpretations are obtained, which allow to quantify and predict the change of mechanical properties in different structural zones of gradient castings depending on melt overheating temperature and cooling modes within the investigated factor space. Keywords: gradient structure, structural zones, melt, mechanical properties.

New Results on the Aggregation of Norms

It is a natural question if a Cartesian product of objects produces an object of the same type. For example, it is well known that a countable Cartesian product of metrizable topological spaces is metrizable. Related to this question, Borsík and Doboš characterized those functions that allow obtaining a metric in the Cartesian product of metric spaces by means of the aggregation of the metrics of each factor space. This question was also studied for norms by Herburt and Moszyńska. This aggregation procedure can be modified in order to construct a metric or a norm on a certain set by means of a family of metrics or norms, respectively. In this paper, we characterize the functions that allow merging an arbitrary collection of (asymmetric) norms defined over a vector space into a single norm (aggregation on sets). We see that these functions are different from those that allow the construction of a norm in a Cartesian product (aggregation on products). Moreover, we study a related topological problem that was considered in the context of metric spaces by Borsík and Doboš. Concretely, we analyze under which conditions the aggregated norm is compatible with the product topology or the supremum topology in each case.

The Moderating Role of Geographical Diversification among the Nexus of Institutional, Power and Space Factor on Economic Geography

The present paper aims to explore the relationships among the institutional factor, power factor, space factor and economic geography in Poland. The goal of the study also consists of the examination of the moderating role of geographical diversification among the nexus of institutional factor, power factor, space factor and economic geography in Poland. The data has been gathered by using primary data collection methods and used survey questionnaires for data collection along with simple random sampling to select the respondents and PLS-SEM for data analysis. The results revealed that institutional factor, power factor, space factor have a positive association with economic geography in Poland. The outcomes also concluded that the geographical diversification is moderating among the nexus of institutional factor, power factor, space factor and economic geography in Poland. These findings are suitable for the regulators that they should focus on institutional power and space factor that would improve the economic geography in Poland.

Relationship Between Multi-Factors and Short-Term Changes in Fishery Resources

The objective of this research is to explore the relationships among various multidimensional factor groups and the density of fishery resources of ecosystems in offshore waters and to expand the application of deep machine learning algorithm in this field. Based on XGBoost and random forest algorithms, we first conducted regulatory importance ranking analysis on the time factor, space factor, acoustic technology factor, abiotic factor, and acoustic density of offshore fishery resources in the South China Sea. Based on these analyses, data slicing is carried out for multiple factors and acoustic density, and the relationship between multidimensional factor group and the density of marine living resources in the ecosystem of offshore waters is elaborately compared and analyzed. Importance ranking shows that the concentration of active silicate at 20 m depth, water depth, moon phase perfection, and the number of pulses per unit distance (Ping) are the first-order factors with a cumulative contribution rate of 50%. The comparative analysis shows that there are some complex relationships between the multidimensional factor group and the density of marine biological resources. Within a certain range, one factor strengthens the influence of another factor. When Si20 is in the range of 0–0.1, and the moon-phase perfection is in the range of 0.3–1, both Si20 and moon-phase perfection strengthened the positive influence of water depth on the density of fishery biological resources.

Risk modeling at the pre-investment phase of nuclear powerplant construction on the international market

Involvement in the construction of nuclear power plants worldwide is a promising direction for developing the re-search and technological potential of engineering and general contracting companies in Russia. Nevertheless, Russian companies, involved in the construction of nuclear power plants (NPPs) abroad, need to adapt to foreign jurisdictions, their requirements and rules applied to the construction of hazardous industrial facilities, as well as unique social, economic and physical environments. In this regard, international activities, performed by Russian companies, are associated with uncertainty and risks that require the study and systematization of risk factors and development of risk management models. The statistical data, covering the recent ten-year period, illustrates the level of uncertainty and problems arising in this area. Over 60 % of nuclear reactors worldwide are built with a delay in construction. The consequences of such delays boost project costs. Major international corporations, implementing nuclear power plant construction projects abroad, consider the insufficient pre-project study of project organization and management issues at the stage of entering into an EPC (M) contract to be the risk factors arising in the pre-investment phase. Risk management modeling is considered as the main element of the system designated for managing the organizational and economic reliability of the pre-investment phase of NPP construction in the international market. It includes: (a) structuring a multiparametric risk factor space based on four sources, including, on the part of the customer, the EPC (M) contractor, the contract and the external environment; (b) a pre-investment risk management model, applicable to NPP construction abroad, to be based on the overall project risk P(rt1); (c) a mathematical model for selecting a project implementation option based on the multicriterial optimization of the future-oriented project plan-schedule.