scholarly journals Further Analysis of Lorenz’s Maximum Simplification Equations

2006 ◽  
Vol 63 (11) ◽  
pp. 2673-2699 ◽  
Author(s):  
S. Lakshmivarahan ◽  
Michael E. Baldwin ◽  
Tao Zheng
Keyword(s):  
Initial Conditions ◽  
Complete Picture ◽  
Long Term Behavior

Abstract The goal of this paper is to provide a complete picture of the long-term behavior of Lorenz’s maximum simplification equations along with the corresponding meteorological interpretation for all initial conditions and all values of the parameter.

Visualising the invisible: performing chaos theory

Leonardo ◽  
2020 ◽  
pp. 1-8
Author(s):  
Emma Weitkamp
Keyword(s):  
Complex Systems ◽  
Chaos Theory ◽  
Initial Conditions ◽  
Starting Point ◽  
Weather And Climate ◽  
Butterfly Effect ◽  
Long Term Behavior ◽  
The Invisible

Edward Lorenz, the pioneering figure in the field of chaos theory coined the phrase “butterfly effect” and posed the famous question “Does the flap of a butterfly's wings in Brazil set off a tornado in Texas?” In posing the question, Lorenz sought to highlight the intrinsic difficulty of predicting the long term behavior of complex systems that are sensitive to initial conditions, like, for example, the weather and climate; these systems are often referred to as chaotic. Taking Lorenz' butterfly as a starting point, Chaos Cabaret sought to explore the nuances of chaos theory through performance and music.

Investigation of the Dynamic Behavior of Railway Ballast Using Molecular Dynamics Simulations

2001 ◽  
Author(s):  
Holger Kruse ◽  
Karl Popp
Keyword(s):  
Molecular Dynamics ◽  
Initial Conditions ◽  
Contact Forces ◽  
Contact Network ◽  
Railway Ballast ◽  
Particle Layer ◽  
Dynamics Simulations ◽  
Long Term Behavior ◽  
Overlap Area

Abstract The molecular dynamics method (MD method) is a powerful tool for the investigation of granular materials like the railway ballast. The characteristics of this method are explained in detail. In contrast to a continuum description, each single stone of the ballast is taken into account. Since the ballast settlement is strongly influenced by the shape of the stones, in the two-dimensional model polygonal particles are used. These particles are surrounded by fixed boundary walls. At the top of the ballast particle layer, a single sleeper is positioned which is loaded by forces occurring at the real track. The contact forces are calculated from the overlap area of the particle geometries. The paper includes information about the sensitivity of the model behavior on initial conditions and contact law parameters. Furthermore, the contact network, the quasi-static stiffness of the ballast layer and its long-term behavior are addressed. Particular emphasis is put on the description of current difficulties and challenges in applying the MD method.

Long-term behavior of positive solutions of an exponentially self-regulating system of difference equations

2017 ◽  
Vol 10 (03) ◽  
pp. 1750045 ◽  
Author(s):  
N. Psarros ◽  
G. Papaschinopoulos ◽  
K. B. Papadopoulos
Keyword(s):  
Asymptotic Behavior ◽  
Positive Solutions ◽  
Difference Equations ◽  
Initial Conditions ◽  
System Of Difference Equations ◽  
Long Term Behavior

In this paper, we study the asymptotic behavior of the positive solutions of a system of the following difference equations: [Formula: see text] where [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] are positive constants and the initial conditions [Formula: see text] and [Formula: see text] are positive numbers.

scholarly journals Solutions of the Difference Equation

2010 ◽  
Vol 2010 ◽  
pp. 1-13 ◽  
Author(s):  
Candace M. Kent ◽  
Witold Kosmala ◽  
Michael A. Radin ◽  
Stevo Stević
Keyword(s):  
Difference Equation ◽  
Initial Conditions ◽  
Boundedness Of Solutions ◽  
Real Numbers ◽  
Unbounded Solutions ◽  
The Difference ◽  
Long Term Behavior

Our goal in this paper is to investigate the long-term behavior of solutions of the following difference equation: , where the initial conditions and are real numbers. We examine the boundedness of solutions, periodicity of solutions, and existence of unbounded solutions and how these behaviors depend on initial conditions.

scholarly journals Modelling the second wave of COVID-19 infections in France and Italy via a Stochastic SEIR model

2021 ◽  
Author(s):  
Davide Faranda ◽  
Tommaso Alberti
Keyword(s):  
Initial Conditions ◽  
Asymptotic Estimates ◽  
Seir Model ◽  
Actual Knowledge ◽  
The World ◽  
Log Normal ◽  
Long Term Behavior ◽  
Second Wave ◽  
Log Normal Distribution

<p>COVID-19 has forced quarantine measures in several countries across the world. These measures have proven to be effective in significantly reducing the prevalence of the virus. To date, no effective treatment or vaccine is available. In the effort of preserving both public health as well as the economical and social textures, France and Italy governments have partially released lockdown measures. Here we extrapolate the long-term behavior of the epidemics in both countries using a Susceptible-Exposed-Infected-Recovered (SEIR) model where parameters are stochastically perturbed with a log-normal distribution to handle the uncertainty in the estimates of COVID-19 prevalence and to simulate the presence of super-spreaders. Our results suggest that uncertainties in both parameters and initial conditions rapidly propagate in the model and can result in different outcomes of the epidemics leading or not to a second wave of infections. Furthermore, the presence of super-spreaders adds instability to the dynamics, making the control of the epidemics more difficult. Using actual knowledge, asymptotic estimates of COVID-19 prevalence can fluctuate of order of ten millions units in both countries.</p>

scholarly journals Aircraft Maintenance Check Scheduling Using Reinforcement Learning

Aerospace ◽  
2021 ◽  
Vol 8 (4) ◽  
pp. 113
Author(s):  
Pedro Andrade ◽  
Catarina Silva ◽  
Bernardete Ribeiro ◽  
Bruno F. Santos
Keyword(s):  
Reinforcement Learning ◽  
Time Horizon ◽  
Learning Algorithm ◽  
Initial Conditions ◽  
Q Learning ◽  
Scheduling Policy ◽  
Real Scenario ◽  
Maintenance Plan ◽  
Small Disturbances

This paper presents a Reinforcement Learning (RL) approach to optimize the long-term scheduling of maintenance for an aircraft fleet. The problem considers fleet status, maintenance capacity, and other maintenance constraints to schedule hangar checks for a specified time horizon. The checks are scheduled within an interval, and the goal is to, schedule them as close as possible to their due date. In doing so, the number of checks is reduced, and the fleet availability increases. A Deep Q-learning algorithm is used to optimize the scheduling policy. The model is validated in a real scenario using maintenance data from 45 aircraft. The maintenance plan that is generated with our approach is compared with a previous study, which presented a Dynamic Programming (DP) based approach and airline estimations for the same period. The results show a reduction in the number of checks scheduled, which indicates the potential of RL in solving this problem. The adaptability of RL is also tested by introducing small disturbances in the initial conditions. After training the model with these simulated scenarios, the results show the robustness of the RL approach and its ability to generate efficient maintenance plans in only a few seconds.

Effects of acute seizures on cell proliferation, synaptic plasticity and long-term behavior in adult zebrafish

2021 ◽  
Vol 1756 ◽  
pp. 147334
Author(s):  
Charles Budaszewski Pinto ◽  
Natividade de Sá Couto-Pereira ◽  
Felipe Kawa Odorcyk ◽  
Kamila Cagliari Zenki ◽  
Carla Dalmaz ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Synaptic Plasticity ◽  
Adult Zebrafish ◽  
Acute Seizures ◽  
Long Term Behavior

Using Generalized Cell Mapping to Approximate Invariant Measures on Compact Manifolds

1997 ◽  
Vol 07 (11) ◽  
pp. 2487-2499 ◽  
Author(s):  
Rabbijah Guder ◽  
Edwin Kreuzer
Keyword(s):  
Dynamical Systems ◽  
Invariant Measures ◽  
Nonlinear Dynamical Systems ◽  
Powerful Method ◽  
Cell Mapping ◽  
Generalized Cell Mapping ◽  
Nonlinear Dynamical ◽  
Long Term Behavior ◽  
Mapping Theory

In order to predict the long term behavior of nonlinear dynamical systems the generalized cell mapping is an efficient and powerful method for numerical analysis. For this reason it is of interest to know under what circumstances dynamical quantities of the generalized cell mapping (like persistent groups, stationary densities, …) reflect the dynamics of the system (attractors, invariant measures, …). In this article we develop such connections between the generalized cell mapping theory and the theory of nonlinear dynamical systems. We prove that the generalized cell mapping is a discretization of the Frobenius–Perron operator. By applying the results obtained for the Frobenius–Perron operator to the generalized cell mapping we outline for some classes of transformations that the stationary densities of the generalized cell mapping converges to an invariant measure of the system. Furthermore, we discuss what kind of measures and attractors can be approximated by this method.

scholarly journals Simulation of MASPn Experiments in MISTRA Test Facility with COCOSYS Code

2008 ◽  
Vol 2008 ◽  
pp. 1-7 ◽  
Author(s):  
Mantas Povilaitis ◽  
Egidijus Urbonavičius
Keyword(s):  
Boundary Conditions ◽  
Nuclear Power ◽  
Power Plants ◽  
Volume Fraction ◽  
Characteristic Length ◽  
Initial Conditions ◽  
Test Facility ◽  
Work Package ◽  
Acceptable Agreement

An issue of the stratified atmospheres in the containments of nuclear power plants is still unresolved; different experiments are performed in the test facilities like TOSQAN and MISTRA. MASPn experiments belong to the spray benchmark, initiated in the containment atmosphere mixing work package of the SARNET network. The benchmark consisted of MASP0, MASP1 and MASP2 experiments. Only the measured depressurisation rates during MASPn were available for the comparison with calculations. When the analysis was performed, the boundary conditions were not clearly defined therefore most of the attention was concentrated on MASP0 simulation in order to develop the nodalisation scheme and define the initial and boundary conditions. After achieving acceptable agreement with measured depressurisation rate, simulations of MASP1 and MASP2 experiments were performed to check the influence of sprays. The paper presents developed nodalisation scheme of MISTRA for the COCOSYS code and the results of analyses. In the performed analyses, several parameters were considered: initial conditions, loss coefficient of the junctions, initial gradients of temperature and steam volume fraction, and characteristic length of structures. Parametric analysis shows that in the simulation the heat losses through the external walls behind the lower condenser installed in the MISTRA facility determine the long-term depressurisation rate.

Long-Term Behavior of Wood-Concrete Composite Floor/Deck Systems with Shear Key Connection Detail

2007 ◽  
Vol 133 (9) ◽  
pp. 1307-1315 ◽  
Author(s):  
M. Fragiacomo ◽  
R. M. Gutkowski ◽  
J. Balogh ◽  
R. S. Fast
Keyword(s):  
Shear Key ◽  
Long Term Behavior
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