Simulation of mixing flows with different temperatures in a T-junction using OpenFOAM code

This paper aims to evaluate the frequency of velocity and temperature fluctuations in the mixing region using OpenFOAM code. Turbulent mixing of fluids at different temperatures can lead to temperature fluctuations at the pipe material. These fluctuations, or thermal striping, inducing cyclical thermal stresses and resulting thermal fatigue, may cause unexpected failure of pipe material. Therefore, an accurate characterization of temperature fluctuations is important in order to estimate the lifetime of pipe material. Thermal fatigue of the coolant circuits of nuclear power plants is one of the major issues in nuclear safety. To investigate thermal fatigue damage, the OECD/NEA-Vattenfall T-Junction Benchmark was initiated to test the ability of state-of-the-art Computational Fluid Dynamics (CFD) codes to predict the important parameters affecting high-cycle thermal fatigue in mixing tees. In this study, to simulate the standard problem described above, the OpenFOAM code is used, which is an open integrated platform for numerical simulation of problems in continuum mechanics. At the first with Salome-meca code, a computational grid was created, consisting of about 450,000 nodes, and k-eps model and RANS models were used to simulate turbulence. OpenFOAM code results were compared with the available experimental results. The results were found to be in well-agreement with the experimental results in terms of amplitude and frequency of temperature and velocity fluctuations.

Sensitivity of functionals in variational data assimilation for a sea thermodynamics model

The sensitivity of functionals of the optimal solution to a variational data assimilation problem for the sea thermodynamics model is studied. The variational data assimilation problem is formulated as an optimal control problem to find the initial state and the boundary condition. The sensitivity of the response functions as functionals of the optimal solution with respect to the observation data is determined by the gradient of the response function and reduces to the solution of a non-standard problem being a coupled system of direct and adjoint equations with mutually dependent initial and boundary values. The algorithm to compute the gradient of the response function is presented, based on the Hessian of the original cost functional. The sensitivity analysis of the response function with respect to errors of observation data is carried out. Numerical examples are presented for the Black Sea thermodynamics model.

Self-Determination and Self-Realization of the Youth of Russia: Socio-Moral and Psychological-Pedagogical Aspects of the Problem

Introduction. The complex problems of upbringing and education of young people, their choice of landmarks in their life path, occupations and self-realization, which are relevant for the progress of the modern world, are studied by scholars from many countries. However, the existing specialization of sciences and the prevailing system of preferences of different scientific schools serve as an obstacle to inter- and transdisciplinary research. The purpose of the article is to present the results of the analysis of the vast problematic field of self-determination and self-realization of modern Russian youth. Materials and Methods. To study the problem, an analysis of statistical data and the results of sociological surveys, a cluster grouping of threats-problems in the sphere of self-determination and self-realization of youth was used for subsequent topological modeling. It was done by constructing and analyzing an oriented (causeand- effect) graph of threats as undesirable effects in order to identify key problems. When constructing a directed graph from threat-problems, the method of functional analysis of cause-and-effect chains tested in the study of a variety of non-standard problem situations in the theory of inventive problem solving was used. Results. Based on the results of the analysis of the cause-and-effect multigraph, built on the basis of 33 threatsproblems as troubles, four reasons of the first level were identified: “brain drain”, violation of the principle of social justice in the country, lack of ideological unity of society due to the ban on state ideology, low religiosity of society. This is followed by three reasons of the second level: the lack of a coherent state youth policy, the ineffectiveness of the existing model of such a policy, a unified state exam as one of the key reasons for the random choice of vocational training for young people. Discussion and Conclusion. The results obtained add up to the development of comprehensive research on the problems of youth self-determination and self-realization that are extremely important for the countryʼs optimistic future.

CASE STUDY APPROACH TO TEACHING AND LEARNING ENGLISH FOR MEDICAL PURPOSES

The expression case study implies a wide range of issues presented for analysis, based on actual or simulated events that could logically occur. Besides, it involves profound research of phenomena or events. In medical education and practice, a case study represents an essential diagnostic procedure and investigation method used to create a profound understanding of an intricate problem in its real context. The implementation of the case study approach is of great importance in teaching English for medical purposes because the medical topics presented to students are familiar to them and medical terminology is applied to language learning. The case study is so structured as to serve the communicative function and provides the necessary content. It comprises the most relevant aspects in the field of medicine such as presenting signs and symptoms, performing different types of examinations, treatment, and health care management. The standard problem that needs to be solved is the patient’s problem, and establishing an adequate diagnosis is the goal. In this way, students develop critical thinking and reflective learning, improve organizational skills, as well as the ability to see the complexity of real-world events and understand the perspective of others. This method has proven to be highly practical preparing students for reality, not theory workplace. In this way integration of language and the professional setting is enabled.

Application of neuro evolution tools in automation of technical control systems

Reinforced learning is a field of machine learning based on how software agents should perform actions in the environment to maximize the concept of cumulative reward. This paper proposes a new application of machine reinforcement learning techniques in the form of neuro-evolution of augmenting topologies to solve control automation problems using modeling control problems of technical systems. Key application components include OpenAI Gym toolkit for develop-ing and comparing reinforcement learn-ing algorithms, full-fledged open-source implementation of the NEAT genetic al-gorithm called SharpNEAT, and inter-mediate software for orchestration of these components. The algorithm of neu-roevolution of augmenting topologies demonstrates the finding of efficient neural networks on the example of a simple standard problem with continu-ous control from OpenAI Gym.

Analysis of Computer Modelling Results on Fuel Rods Strength and Condition at Reduced or Absent Cooling Caused by Accident

The paper describes the phenomenology of fuel rod behaviour in severe accident. As an example, an experiment is described resulting in severe damage of 19 fuel rod assembly of VVER type; it was carried out in the CORA facility in 1993 (Research Centre, Karlsruhe, Germany). Testing conditions and results of post-test investigations of fuel assembly are given. The fuel rod code RAPTA-SFD is briefly dealt with; the code was a participant in the International Standard Problem ISP-36. The basic results are presented acquired by computer modelling CORA-W2 experiment using RAPTA-SFD code. Among the presented experimentally acquired and calculated results, the scope of the data on stainless steel component behaviour is substantial. The tested CORA-W2 fuel assembly contained a significant quantity of steel components, viz., spacer grids, a guide thimble, and a cladding of an absorber element. It is to be borne in mind that the spacer grids and a guide thimble of the updated and upgraded fuel assembly of VVER-1000 are fabricated from Zr-alloy, hence, the relative quantitative characteristics of chemical interactions between materials and stainless steel (Cr-Ni alloy) will be much lower for the up-to-date upgraded fuel assembly under identical conditions.

Solving non-standard problems by a computer system

On the one hand, modern psychology presents a wide range of opinions from the complete denial of the possibility of an adequate theoretical description of the mental in mathematical terms to the recognition of the timeliness and even inevitability of such a description. On the other hand, many developers of traditional AI, i.e. systems based on rules, as well as systems based on deep learning networks of artificial neurons, and their various hybrids either use, most often subconsciously, the most primitive psychological concepts, or believe that they do not need psychological knowledge at all. Therefore, the problem consists of two interrelated parts. The first is whether it is possible to create algorithms of human thinking that are adequate to the facts known in psychology on the basis of the general theory of the psyche, which widely uses the mathematical apparatus. The second is whether it is possible to create a computer system based on these algorithms that can solve the most difficult (non-standard) problems in different fields of knowledge, using what most researchers refer to as "common sense". The goal of the article is to create a computer system capable of solving non-standard problems in natural Russian, using algorithms of human thinking and check its basic parameters. AlNikOr – computer system is created. AlNikOr can solve non-standard problems in natural Russian, using algorithms of human thinking. Its efficiency is shown by the example of solving a non-standard problem in physics. Computer systems based on AlNikOr can be used to solve real non-standard problems in various fields of science and technology.

Policy adaptation for vehicle routing

Nested Rollout Policy Adaptation (NRPA) is a Monte Carlo search algorithm that learns a playout policy in order to solve a single player game. In this paper we apply NRPA to the vehicle routing problem. This problem is important for large companies that have to manage a fleet of vehicles on a daily basis. Real problems are often too large to be solved exactly. The algorithm is applied to standard problem of the literature and to the specific problems of EDF (Electricité De France, the main French electric utility company). These specific problems have peculiar constraints. NRPA gives better result than the algorithm previously used by EDF.