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№3

Publication date:

16 September 2019

## Articles of journal № 3 at 2018 year.

Order result by: Public date | Title | Authors |

31. Modeling traffic flows in AnyLogic

*[№3 за 2018 год]*

**Authors:**Ya.I. Shamlichky, A.S. Okhota, S.N. Mironenko

**Visitors:**1633

The article proposes a technique for modeling traffic flows in a simulation environment. The goal was to simulate a section of the road network in Krasnoyarsk. The goal included the following tasks: to gather data on the traffic flow intensity at a site, to develop a simulation model of an intersection. The authors have chosen the AnyLogic modeling environment to solve the problems. The simulation experiment requires the input parameters. I this case, they are the intensity of vehicles arrival and the distribution of vehicles by a direction. The developed simulation model has the following structural elements: road network elements, model agent generation system, vehicle traffic logic blocks, model parameters control elements, and an agent statistics gathering module. The model execution mode allows displaying animation, which is a two-dimensional plan of the simulated system with moving vehicles. In addition, there is a functional for switching between a two-dimensional and three-dimensional system plan. The statistical data take into account the time a vehicle passes a road network segment, as well as the total intersection traffic capacity. The procedure of performing the experiment is a preliminary tuning of a simulation model to the average traffic capacity of the intersection (this usually occurs after a number of vehicles exiting the model using the Sink component reaches 20 or more thousands). Then while changing the time of the traffic lights, the simulation model is started alternately. After finishing a series of runs, follows the calculation of the difference in the mean delay of hard and adaptive regulation, construction of the graphs, and making the conclusions. As a result, we get a simulation model with an experimental technique that can be useful in determining the maximum traffic capacity at traffic intersections, planning road infrastructure, etc.

32. A program for calculation of controller settings by the method of advanced frequency characteristics

*[№3 за 2018 год]*

**Authors:**Margolis B.I., G.A. Mansour

**Visitors:**1477

The paper considers the problem of calculating settings of typical general industrial controllers in automatic control systems for technological objects. It shows the possibility of applying the Nyquist stability criterion for extended system frequency characteristics. It also formulates the problem of ensuring the necessary quality of a transient process in a closed system due to the provision of the given degree of oscillation. The obtained condition for the given system oscillation ensures that the controller settings are located on the equal damping line. The paper considers the extended frequency characteristic of the PID controller for the case when a component is introduced into it as a real differentiating element. The authors have obtained the formulas for finding PID controller settings using extended frequency characteristics in the form of parametric dependencies. There are also relations obtained from general formulas for PI and PD controllers. A program developed in MatLab based on the proposed method allows calculating optimal controller settings by the criterion of minimum deviation of transient time and overshoot from the set values. There are also the results of calculating PID controller settings for a control example and the obtained equal damping lines. The paper presents the best transient processes for each of the equal damping lines and the optimal process satisfying the required quality characteristics. It also shows the disadvantages of the method of extended frequency characteristics in the proposed formulation. The paper considered the possibilities of alternative formulation of the problem of synthesizing controller settings and the application of the proposed methods for finding controller settings in multi-loop systems for automatic control of technological objects.

33. Multi-agent simulation of epidemics' distribution on supercomputers

*[№3 за 2018 год]*

**Author:**S.Yu. Lapshina

**Visitors:**1151

The paper considers the possibility of using modern supercomputers to solve resource-intensive problems of multi-agent simulation of the advance of mass epidemics based on the percolating cluster growth theory. In the problems of determining quarantine zones in advance of epidemics a multi-agent percolation model supposes the formation of an interaction grid of population representatives, modeling of a disease distribution medium, the collection of information on the population size, the implementation of a parallel algorithm for multiple marking of percolating clusters with a tagging mechanism, and result visualization. The article describes an improved variant of the algorithm of multiple marking of Hoshen-Kopelman percolation clusters for a multiprocessor system, as well as a working prototype of its implementation developed at the JSCC RAS (Branch of SRISA). This algorithm can be used in any area as a tool for differentiating large-size lattice clusters, since it has the input in a format that is independent of the application. The paper demonstrates the possibility of revealing the dependencies of latent periods of epidemic spread on the probability of infecting aggregates of population representatives and the formation of threshold values for the transition of local epidemics into large-scale pandemics. After setting a latent period, the chance and the source of infection one can determine the range of cities where infection can be expected. This information is used to determine the radius of a quarantine zone. If a hotbed of disease is found in some city and the latent period has already ended, then this tool might help to determine a zone to be isolated from the outside world. The article also provides estimates of the execution time of the multiple-labeling algorithm for Hoshen-Kopelman percolating clusters for different values of input parameters in two high-performance computing systems installed in the MSC RAS – MVS-100K and MVS-10P.

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