scholarly journals Deterministic chaos in pendulum systems with delay

2019 ◽  
Vol 4 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Aleksandr Shvets ◽  
Alexander Makaseyev
Keyword(s):  
Mathematical Model ◽  
Steady State ◽  
Differential Equations ◽  
Deterministic Chaos ◽  
Phase Portraits ◽  
Characteristic Exponents ◽  
Systems Of Differential Equations ◽  
Lyapunov Characteristic Exponents ◽  
The Mathematical Model ◽  
Equations With Delay

AbstractDynamic system "pendulum - source of limited excitation" with taking into account the various factors of delay is considered. Mathematical model of the system is a system of ordinary differential equations with delay. Three approaches are suggested that allow to reduce the mathematical model of the system to systems of differential equations, into which various factors of delay enter as some parameters. Genesis of deterministic chaos is studied in detail. Maps of dynamic regimes, phase-portraits of attractors of systems, phase-parametric characteristics and Lyapunov characteristic exponents are constructed and analyzed. The scenarios of transition from steady-state regular regimes to chaotic ones are identified. It is shown, that in some cases the delay is the main reason of origination of chaos in the system "pendulum - source of limited excitation".

scholarly journals Mathematical modeling of the functioning process of a single-cylinder air-cooled diesel engine taking into account the consumption of crankcase gases

2020 ◽  
Vol 1 (3) ◽  
pp. 75-82
Author(s):  
D.V. Pavlov ◽  
◽  
K.Yu. Platonov ◽  
R.N. Khmelev ◽  
◽  
...  
Keyword(s):  
Mathematical Model ◽  
Steady State ◽  
Diesel Engine ◽  
Differential Equations ◽  
Internal Combustion Engines ◽  
Computational Experiment ◽  
Working Fluid ◽  
Engine Operation ◽  
Single Cylinder ◽  
The Mathematical Model

At present, the most effective method for studying internal combustion engines (ICE) is mathe-matical modeling and computational experiment. The use of a computational experiment can signif-icantly reduce material and time costs in the research, design and refinement of the internal combus-tion engine. At the same time, despite the high level of the applied mathematical models, there are practically no studies aimed at establishing the regularities of the influence of the state of the cylin-der-piston group (CPG) on the crankcase gas consumption and other indicators of engine operation at steady-state and transient modes. This article is devoted to solving an urgent problem associated with the development of a theoretical base that provides a comprehensive simulation of steady-state and transient modes of diesel engine operation, taking into account the consumption of crankcase gases. The article presents a mathematical model of a diesel engine based on thermal mechanics, which reflects the main features of the engine as a system that converts energy in time. The system of equations of the mathematical model is based on the laws of conservation of energy, mass, equa-tions of motion of solid links and includes differential equations for the rates of change in the tem-perature and density of the working fluid in the cylinder and in the crankcase of the internal com-bustion engine, the ideal gas equation of state, as well as differential equations for the change in the angular speed and angle of motor shaft rotation. The mathematical model is tested on the example of a small-sized single-cylinder diesel engine 1Ch9.5 / 8.0 with air cooling. This type of engine is widely used for small-scale mechanization in agriculture, generator sets, etc. The article presents the results of calculations of a number of engine operating modes in comparison with the results of field tests carried out at the test bench.

Glycemia monitoring

1998 ◽  
Vol 2 ◽  
pp. 23-30
Author(s):  
Igor Basov ◽  
Donatas Švitra
Keyword(s):  
Diabetes Mellitus ◽  
Mathematical Model ◽  
Numerical Methods ◽  
Differential Equations ◽  
Blood Sugar ◽  
Self Regulation ◽  
Physiological System ◽  
Non Linear ◽  
The Mathematical Model

Here a system of two non-linear difference-differential equations, which is mathematical model of self-regulation of the sugar level in blood, is investigated. The analysis carried out by qualitative and numerical methods allows us to conclude that the mathematical model explains the functioning of the physiological system "insulin-blood sugar" in both normal and pathological cases, i.e. diabetes mellitus and hyperinsulinism.

scholarly journals Computational Study of the Coupled Mechanism of Thermophoretic Transportation and Mixed Convection Flow around the Surface of a Sphere

Molecules ◽  
2020 ◽  
Vol 25 (11) ◽  
pp. 2694
Author(s):  
Amir Abbas ◽  
Muhammad Ashraf ◽  
Yu-Ming Chu ◽  
Saqib Zia ◽  
Ilyas Khan ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Partial Differential Equations ◽  
Differential Equations ◽  
Mixed Convection ◽  
Computational Study ◽  
Convection Flow ◽  
Mixed Convection Flow ◽  
Partial Differential ◽  
Primitive Form ◽  
The Mathematical Model

The main goal of the current work was to study the coupled mechanism of thermophoretic transportation and mixed convection flow around the surface of the sphere. To analyze the characteristics of heat and fluid flow in the presence of thermophoretic transportation, a mathematical model in terms of non-linear coupled partial differential equations obeying the laws of conservation was formulated. Moreover, the mathematical model of the proposed phenomena was approximated by implementing the finite difference scheme and boundary value problem of fourth order code BVP4C built-in scheme. The novelty point of this paper is that the primitive variable formulation is introduced to transform the system of partial differential equations into a primitive form to make the line of the algorithm smooth. Secondly, the term thermophoretic transportation in the mass equation is introduced in the mass equation and thus the effect of thermophoretic transportation can be calculated at different positions of the sphere. Basically, in this study, some favorite positions around the sphere were located, where the velocity field, temperature distribution, mass concentration, skin friction, and rate of heat transfer can be calculated simultaneously without any separation in flow around the surface of the sphere.

scholarly journals New “Full-Bridge Buck Inverter–DC Motor” System: Steady-State and Dynamic Analysis and Experimental Validation

Electronics ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 1216 ◽  
Author(s):  
Eduardo Hernández-Márquez ◽  
Carlos Alejandro Avila-Rea ◽  
José Rafael García-Sánchez ◽  
Ramón Silva-Ortigoza ◽  
Magdalena Marciano-Melchor ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Steady State ◽  
Motor System ◽  
Circuit Simulation ◽  
Dc Motor ◽  
Matlab Simulink ◽  
Duty Cycles ◽  
System Variables ◽  
The Mathematical Model ◽  
Steady State Stability

A mathematical model of a new “full-bridge Buck inverter–DC motor” system is developed and experimentally validated. First, using circuit theory and the mathematical model of a DC motor, the dynamic behavior of the system under study is deduced. Later, the steady-state, stability, controllability, and flatness properties of the deduced model are described. The flatness property, associated with the mathematical model, is then exploited so that all system variables and the input can be differentially parameterized in terms of the flat output, which is determined by the angular velocity. Then, when a desired trajectory is proposed for the flat output, the input signal is calculated offline and is introduced into the system. In consequence, the validation of the mathematical model for constant and time-varying duty cycles is possible. Such a validation of this mathematical model is tackled from two directions: (1) by circuit simulation through the SimPowerSystems toolbox of Matlab-Simulink and (2) via a prototype of the system built by using Matlab-Simulink and a DS1104 board. The good similarities between the circuit simulation and the experimental results allow satisfactorily validating the mathematical model.

scholarly journals Distributed Control and the Lyapunov Characteristic Exponents in the Model of Infectious Diseases

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
M. Bershadsky ◽  
M. Chirkov ◽  
A. Domoshnitsky ◽  
S. Rusakov ◽  
I. Volinsky
Keyword(s):  
Infectious Diseases ◽  
Differential Equations ◽  
Ordinary Differential Equations ◽  
Distributed Control ◽  
Stationary Point ◽  
Treatment Time ◽  
Simulation Models ◽  
Characteristic Exponents ◽  
Data Comparison ◽  
Lyapunov Characteristic Exponents

The Marchuk model of infectious diseases is considered. Distributed control to make convergence to stationary point faster is proposed. Medically, this means that treatment time can be essentially reduced. Decreasing the concentration of antigen, this control facilitates the patient’s condition and gives a certain new idea of treating the disease. Our approach involves the analysis of integro-differential equations. The idea of reducing the system of integro-differential equations to a system of ordinary differential equations is used. The final results are given in the form of simple inequalities on the parameters. The results of numerical calculations of simulation models and data comparison in the case of using distributive control and in its absence are given.

scholarly journals Deployment/Retrieval Modeling of Cable-Driven Parallel Robot

2010 ◽  
Vol 2010 ◽  
pp. 1-10 ◽  
Author(s):  
Q. J. Duan ◽  
J. L. Du ◽  
B. Y. Duan ◽  
A. F. Tang
Keyword(s):  
Mathematical Model ◽  
Boundary Condition ◽  
Steady State ◽  
Differential Equations ◽  
Parallel Robot ◽  
Lumped Mass ◽  
Dynamic Motion ◽  
Long Span ◽  
System A ◽  
Lumped Mass Method

A steady-state dynamic model of a cable in air is put forward by using some tensor relations. For the dynamic motion of a long-span Cable-Driven Parallel Robot (CDPR) system, a driven cable deployment and retrieval mathematical model of CDPR is developed by employing lumped mass method. The effects of cable mass are taken into account. The boundary condition of cable and initial values of equations is founded. The partial differential governing equation of each cable is thus transformed into a set of ordinary differential equations, which can be solved by adaptive Runge-Kutta algorithm. Simulation examples verify the effectiveness of the driven cable deployment and retrieval mathematical model of CDPR.

The Effect of Leakage on Railroad Brake Pipe Steady State Behavior

1988 ◽  
Vol 110 (3) ◽  
pp. 329-335 ◽  
Author(s):  
K. Abdol-Hamid ◽  
D. E. Limbert ◽  
G. A. Chapman
Keyword(s):  
Mathematical Model ◽  
Steady State ◽  
Transmission Lines ◽  
Computation Time ◽  
State Behavior ◽  
Implicit Finite Difference Scheme ◽  
Inlet Flow Rate ◽  
Model Equations ◽  
The Mathematical Model ◽  
Steady State Behavior

A mathematical model for pneumatic transmission lines containing leakage is developed. This model is used to show the effect of leakage size and distribution on the steady state behavior of the brake pipe on a train brake system. The model equations are solved using the implicit finite difference scheme without neglecting any terms. The model is presented in a nonlinear continuous network form, consisting of N sections. Each of the network sections represents one car and may contain one leakage. A computer program was developed to solve the model equations. This program is capable of simulating a train with cars of various lengths and takes a minimum amount of computation time as compared with previous methods. Through analysis and experimentation, the authors have demonstrated that pressure gradient and inlet flow rate are very sensitive to leakage locations as compared with leakage size. The results, generated by the mathematical model, are compared with the experimental data of two different brake pipe set-ups having different dimensions.

scholarly journals Mathematical Model of Spatial Motion of the Controlled Parachute-Tether System of the Wind Kite Type

2021 ◽  
Vol 24 (4) ◽  
pp. 17-24
Author(s):  
V.M. Churkin ◽  
T.Yu. Churkina ◽  
A.M. Girin
Keyword(s):  
Mathematical Model ◽  
Differential Equations ◽  
Solid Body ◽  
Equations Of Motion ◽  
Vertical Plane ◽  
Spatial Motion ◽  
Mathematical Task ◽  
Spatial Movement ◽  
Elastic Thread ◽  
The Mathematical Model

Mathematical modeling is created for the mathematical task of spatial motion of the controlled parachute-tether system of the “wind kite” type. The mathematical model parachute-tether system consists of a model of the main parachute and a model of the braking parachute. The parachutes are connected by the tether. The model of the main parachute is supposed to be the solid body. This solid body has two planes of symmetry. The braking parachute is the solid body with axial symmetry. The tether model is an absolutely flexible elastic thread. The tether is connected by ideal hinges with the main parachute and braking parachute. The control of the main parachute is carried out by changing the length of the control slings. Changing the length causes deformation of the dome. This is the reason for the change in its aerodynamics. Maneuvering of the main parachute occurs in the vertical plane, when the length of the control slings changes simultaneously. Maneuvering of the main parachute in space is carried out when the length of the control slings changes, when the slings are given a travel difference. The system of dynamic and kinematic equations is designed for calculating the controlled spatial movement of the main parachute, braking parachute and tether. The option exists when the mass of the tether and the forces applied to the tether cannot be neglected. The motion of the tether is represented by the equations of motion of an absolutely flexible elastic thread in projections on the axis of a natural trihedron. The mathematical model is represented by a system of ordinary differential equations and partial differential equations. The problem is solved using various numerical methods. The solution is possible with the help of an integrated numerical and analytical approach as well.

scholarly journals Sensitivity analysis and practical identifiability of the mathematical model for partial differential equations

2021 ◽  
Vol 2092 (1) ◽  
pp. 012012
Author(s):  
O Krivorotko ◽  
D Andornaya
Keyword(s):  
Mathematical Model ◽  
Partial Differential Equations ◽  
Differential Equations ◽  
Sensitivity Matrix ◽  
Partial Differential ◽  
Identifiability Analysis ◽  
Practical Identifiability ◽  
Eigenvalue Method ◽  
Simulation Results ◽  
The Mathematical Model

Abstract A sensitivity-based identifiability analysis of mathematical model for partial differential equations is carried out using an orthogonal method and an eigenvalue method. These methods are used to study the properties of the sensitivity matrix and the effects of changes in the model coefficients on the simulation results. Practical identifiability is investigated to determine whether the coefficients can be reconstructed with noisy experimental data. The analysis is performed using correlation matrix method with allowance for Gaussian noise in the measurements. The results of numerical calculations to obtain identifiable sets of parameters for the mathematical model arising in social networks are presented and discussed.

scholarly journals Mass transfer during electrodeposition of metals at a periodically changing rate

1999 ◽  
Vol 64 (5-6) ◽  
pp. 317-340 ◽  
Author(s):  
Miodrag Maksimovic ◽  
Konstantin Popov
Keyword(s):  
Mathematical Model ◽  
Mass Transfer ◽  
Steady State ◽  
Layer 4 ◽  
Millisecond Range ◽  
The Mathematical Model ◽  
Pulsating Current ◽  
Pulsating Overpotential ◽  
Changing Rate ◽  
Electrodeposition Of Metals

1. Introduction 2. Mass transfer in the steady state periodic condition 2.1. Reversing current 2.2. Pulsating current 2.3. Alternating current superimposed on direct current 3. The influence of the charge and discharge of the electrical double layer 4. The validity of the mathematical model 4.1. Reversing current in the millisecond range 4.2. Reversing current in the second range 4.3. Pulsating current 4.4. Pulsating overpotential 5. Conclusion

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