Dynamical Systems Approach Research Articles

Evolution of ion-acoustic shock waves in magnetized plasma with hybrid Cairns–Tsallis distributed electrons

Abstract The propagation of nonlinear electrostatic ion-acoustic (IA) shock waves in presence of external magnetic field having Cairns–Tsallis distributed electrons and ion kinematic viscosity is investigated. In the linear regime, the dispersion relation of the ion acoustic shock wave is found to be modified by the external magnetic field. Adopting reductive perturbation approach, it is shown that the dynamics of shocks is modeled by a hybrid Ostrovsky–Burgers’ equation. The influence of relevant physical parameters such as nonthermality and nonextensivity of electrons, magnetic field strength, and ion kinematic viscosity on the time evolution of the shock structure is numerically examined. It is observed the present plasma system supports both compressive and rarefactive shock waves. Furthermore, the analysis is performed through dynamical system approach to elucidate the various aspects of the phase-space shock dynamics.

Prediction of Wind Speed by Using Chaotic Approach: A Case Study in Istanbul

Renewable energy sources have gained great popularity due to the increasing importance given to a sustainable environment and economic development. Because of the environmental friendliness of renewable energy compared to fossil fuels, the tendency and investments in this field have increased. Wind energy comes into prominence among renewable energy sources because of its potential power that is used in various areas currently. Wind energy having stochastic nature is more sensitive to the extreme values of wind speed. Therefore, in order to create wind energy effectively, an accurate wind speed forecast is needed. In this study, nonlinear dynamical system approaches have been implemented by using reconstructing of phase space based on specifying minimum embedded dimension and delay time. In order to find out performance, different error metrics (MSE, RMSE, MAE, and MAPE) have been implemented. According to results, RMSE has been found 0.47 and 0.85 in hourly and daily dataset, respectively. Also, the correlation coefficient between the measurement and the obtained data set was as high as 0.92 in the hourly wind variable. In addition, a lesser correlation coefficient of 0.62 was found in the daily wind speed.

Designing an investment model and developing irrigation systems for sustainable management of water resources using a dynamic systems approach

Designing an investment model and developing irrigation systems for sustainable management of water resources using a dynamic systems approach

The Resource Pool is Dry: A Model for Surfing the Waves of Energy

Exhaustion impedes all humans from achieving their goals, be they during experiments or in daily life. The notion of mental resources has provided substantive discourse on attentional failures and operational mishaps. However, without empirical validation, we cannot assess whether the “resource” is an emergent or contrived phenomenon. We must refute the notion that it is an unspoken Law of Resources. In this paper we celebrate the contributions of the resource and issue a long-needed challenge – grounding it in psychophysiological reality. We outline the initial developments of a dynamic neural energetics model towards that goal. The fundamental question we pose is this – can we expand the capacity of resource theory? Emerging methods are discussed to measure energy waves, a more intuitive and testable metaphor. Our theory merges thermodynamic, information-theoretic, neuroscientific, and dynamical systems approaches into a single framework that argues “limitations” stand in paradox with energization methods.

A Backstepping Approach to Nonlinear Model Predictive Horizon for Optimal Trajectory Planning

This paper presents a novel trajectory planning approach for nonlinear dynamical systems; a multi-rotor drone, built on an optimization-based framework proposed by the authors named the Nonlinear Model Predictive Horizon. In the present work, this method is integrated with a Backstepping Control technique. The goal is to remove the non-convexity of the optimization problem in order to provide real-time computation of reference trajectories for the vehicle which respects its dynamics while avoiding sensed static and dynamic obstacles in the environment. Our method is applied to two models of multi-rotor drones to demonstrate its flexibility. Several simulation and hardware flight experiments are presented to validate the proposed design and demonstrate its performance improvement over earlier work.

A two-group epidemiological model: Stability analysis and numerical simulation using neural networks

This work has two principal goals. First, we investigate the asymptotic behavior of a two-group epidemiological model and determine the expression of its basic reproduction number using the dynamical systems approach based on the spectral radius of the relative matrix. Second, we simulate the obtained analytical results using a new deep learning method that associates the ordinary differential equations governing the model to neural networks. A general disease-free equilibrium is considered and sufficient conditions of stability and convergence are formulated. A detailed description of the neural network model used in the simulation is provided. Moreover, the proposed deep learning simulation algorithm is compared to the simulation provided by “odeint”, a function from “SciPy” which is a Python library of mathematical routines.

Evolving black hole with scalar field accretion

We obtain approximate analytical solutions of the Einstein equations close to the trapping horizon for a dynamical spherically symmetric black hole in the presence of a minimally coupled self-interacting scalar field. This is made possible by a new parametrization of the metric, in which the displacement from the horizon as well as its expansion rate feature explicitly. Our results are valid in a neighbourhood of the horizon and hold for any scalar field potential and spacetime asymptotics. An exact equation for the accretion rate is also obtained, which generalizes the standard Bondi formula. We also develop a dynamical system approach to study near-equilibrium black holes; using this formalism, we focus on a simple model to show that the near-equilibrium dynamics is characterised by scaling relations among dynamical variables. Moreover, we show that solutions with purely ingoing energy-momentum flux never reach equilibrium.

Improved Adaptive Fuzzy Control for Non-Strict Feedback Nonlinear Systems: a Dynamic Compensation System Approach

This paper investigates the tracking control problem for uncertain nonlinear non-strict feedback systems (NSFSs) in the presence of full-state constraints and unmeasured disturbances. It is of great practical significance to realize the full-state constraint under disturbed conditions. In view of the non-strict feedback problem, a novel design framework of the state feedback control is given based on the newly proposed dynamic compensation system (DCS). Different from the traditional backstepping, the estimated signal based on the adaptive fuzzy system is indirectly introduced into the virtual and actual control laws through the DCS, which has the advantage of avoiding the algebraic-loop problem in NSFSs. Accordingly, the disturbance observer (DO) design method is improved based on this framework. Integrating the DCS into the DO design avoids the coupling problem between the disturbance and the unknown nonlinear function. An improved barrier Lyapunov function (BLF) is designed by introducing the concept of the inducible factor, and full-state constraints can be guaranteed after a transitional period for any initial state. By combining the DCS, the DO and the improved BLF, a novel adaptive fuzzy tracking control law is constructed, and all the signals in the closed-loop system are semiglobally uniformly ultimately bounded. Finally, the theoretical analysis and simulation results show that all states meet the corresponding constraints while meeting the stability.

Segregation patterns in three-dimensional granular flows.

Flow of size-bidisperse particle mixtures in a spherical tumbler rotating alternately about two perpendicular axes produces segregation patterns that track the location of nonmixing islands predicted by a dynamical systems approach. To better understand the paradoxical accumulation of large particles in regions defined by barriers to transport, we perform discrete element method (DEM) simulations to visualize the three-dimensional structure of the segregation patterns and track individual particles. Our DEM simulations and modeling results indicate that segregation pattern formation in the biaxial spherical tumbler is due to the interaction of size-driven radial segregation with the weak spanwise component of the advective surface flow. Specifically, we find that after large particles segregate to the surface, slow axial drift in the flowing layer, which is inherent to spherical tumblers, is sufficient to drive large particles across nominal transport barriers and into nonmixing islands predicted by an advective flow model in the absence of axial drift. Axial drift alters the periodic dynamics of nonmixing islands, turning them into "sinks" where large particles accumulate even in the presence of collisional diffusion. Overall, our results indicate that weak perturbation of chaotic flow has the potential to alter key dynamical system features (e.g., transport barriers), which ultimately can result in unexpected physical phenomena.

The effect of changes in saddle height on coordination and its variability during pedalling cycle

ABSTRACT Modifications in saddle height affect the range of movement of the lower limb’s joints during pedalling. Although its effect on movement patterns is poorly understood. The purpose of this study was to analyse the acute effects of small changes in bicycle saddle height on pedalling coordination and its variability. Lower extremity kinematic data were collected in random order for ten well-trained cyclists while pedalling at three different saddle heights: preferred, 2% higher and 2% lower than preferred position. A dynamical systems approach was used to quantify the coordination and its variability for selected joint couplings. Modifications in saddle height produced large changes in the frequency of movement patterns, although they were not enough to alter the coordination classification. Lowering the saddle height increased the frequency of the proximal coordinative hip-ankle pattern (F = 11.77, p < .01) and knee-ankle couplings (F = 14.39, p < .01), while decreasing inphase coordination (F > 11.03, p < .01) during the propulsive phase. Pedalling coordination variability was not affected, being greatest during the movement transitions and when the ankle joint was included in the coupling. This study demonstrated that pedalling pattern coordination and coordination variability were generally stable to acute small changes in saddle height in well-trained cyclists.

Pemodelan Sistem Dinamik Eco-Drainage di Wilayah Tanah Basah (Studi Kasus Kawasan Kelapa Gading DKI Jakarta)

An Ecological drainage becomes an application in this development project in the Kelapa Gading area. The drainage concept that is applied is a drainage system in which rainwater that falls on road surface runoff will flow directly into the water infiltration system and directly fill the ground surface water. G eologically, it can be seen that North Jakarta is an area with a fairly high ground water level (MAT), and has an average MAT elevation of 2 - 2.5 m. This study intends to determine the ability of this ecodrainage to reduce runoff/floods that often occur in areas with a fairly high MAL. What direct benefits can be felt in the use of ecodrainage in these flood-prone areas, thus making the basic reason for applying this ecodrainage. This study uses a dynamic systems approach. In the preparation of the dynamic system model, Powersim Studio Version 10 software will be assisted. The simulation results show that an increase in rainfall every year will provide an increasing flood potential. By using eco-drainage, it is felt that it is not optimal enough to reduce runoff in areas that have high MAT levels. However, this ecodrainage still provides broad sustainability benefits. The quantity of groundwater will slowly be filled up to the aquier layer through this ecodrainage. This step is considered to be able to help prevent the aquifer layer from being exposed and have an impact on the rate of land subsidence so that the potential for flooding will decrease.

Coordination dynamics of thoracic and abdominal movements during voluntary breathing

Thoracic and abdominal movements can be tightly coupled during voluntary breathing, such as when singing and playing wind instruments. The present study investigated the coordination of thoracic and abdominal movements during voluntary breathing using a dynamical systems approach. We examined whether there are two stable coordination patterns, and if the coordination pattern would abruptly change when the breathing frequency increased, which is known as phase transition. The participants inhaled and exhaled repeatedly at 7.5, 15, 30, 60, or 120 breaths per minute. At the beginning and end of the experiment, the participants performed breathing at their preferred frequency. As a result, the coordination pattern at the lower and preferred frequencies exhibited an in-phase pattern. When breathing frequency increased, participants showed deviated coordination patterns from the in-phase pattern to either a thoracic-leading pattern, an abdominal-leading pattern, or an anti-phase pattern depending on the individual. These deviations occurred gradually; thus, phase transition was not observed. Our findings suggest that thoracic and abdominal movements are tightly coupled at lower frequencies, but their patterns vary depending on the breathing frequency and individuals. Therefore, the present study suggests the importance of viewing breath control in terms of coordination of thoracic and abdominal movements.

Phytoremediation Dynamic Models of Radionuclides 134Cs and 60Co in Sunflowers Plants (Helianthus annuus. L) Using Matlab

In the development of phytoremediation this method can be simulated quite concisely and precisely. Simulations are carried out to predict plant behavior towards several different treatments, for example plant species, also types and concentrations of contaminants. In this study a dynamic model of phytoremediation has been made using sunflower plants and 134Cs and 60Co radionuclides. This study was developed by mimicking the interaction of soil and plants to be simulated into Phytoremediation Dynamic Model (PDM). Diverse mathematical algorithms implemented to characterize phytoremediation, systems such as differential equation, statistical correlation, and dynamic system approach. The error value obtained is different for each contaminant for each variation in concentration, which ranges from 0,0006-0,6349 for 134Cs contaminants and 0,0089-0,4157 for 60Co contaminants. The error value is quite small, and the overall simulation data has approached the experimental data. Factors that influence the results of calculated data include saturation point values, as well as the absorption rate of each part of the plant obtained from calculations and estimates. This model has proven to be able to mimic plant responses to contaminants

Semiogenesis: A Dynamic System Approach to Agency and Structure

Semiogenesis: A Dynamic System Approach to Agency and Structure

Recognition of wastes from value co-creation in industrial services in startups

Objective of the study: This study aims to identify the wastes from the value co-creation in industrial services in the startups context. In addition, through the dynamic systems approach, to analyze the interaction among the wastes in the startups' value co-creation.Design/methodology/approach: First, we conducted a systematic literature review based on the Systematic Search Flow method (SSF) and the content analysis following Bardin (2011), then, through the dynamic systems approach, this step, we verify the interaction and behavior among these wastes in the value co-creation context.Findings: Based on the finds, we recognized six wastes from the value co-creation in startups. We evidenced that waste "Personal Characteristics" was pointed was the greatest impact on co-creation concerning other wastes.Originality: This is the first paper that recognizes and behavior evaluates the wastes from value cocreation in industrial service based on the dynamic of systems approach for the startups.Research limitations/implications: The wastes recognized were based on current literature. An empirical test can be a way to identify other wastes and evaluation these finds in the practice.Practical implications: The listed wastes can serve as a basis to guide strategies for mitigating or eliminating these losses in the value co-creation process in startups. In addition, directing players in decision-making anticipated way from different perspectives to improve collaboration among multiple companies without wastes.Social implications: Once the value cocreation process is more efficient, the societal can receive more benefits and enhance well-being, through services new or services improved offerings for society via startups.

Specified QoS based networked observer and PI controller design with disturbance and noise rejection under random packet dropout

In this paper, a novel observer based networked PI controller has been designed by considering bounded disturbance and measurement noise under specified probability of random packet dropouts in networked control systems (NCSs). Lyapunov stability condition of the NCS with an observer and PI controller has been derived using an asynchronous dynamical system (ADS) approach as a linear matrix inequality (LMI) with nonconvex constraints to improve its quality-of-service (QoS) and quality-of-control (QoC). In order to improve QoC and QoS for NCS under process and measurement disturbance, we have used H∞ norm bound, and random packet drop rate in the NCS design. The algorithm has been tested and validated on four test-bench models of energy conversion systems. Confidence intervals and the mean responses of the state variables, state estimation errors of the observer and control signals have been reported using 100 Monte Carlo simulations. Our proposed NCS with PI controller and observer design method can be employed on a wide range of state space models of energy conversion systems. The specified probability of packet dropouts in the communication network between the sensor, observer, PI controller and actuator has been considered in the design which allows design of the NCS with guaranteed Lyapunov stability. We consider a switched linear dynamical system structure of the NCS with bounded noise and disturbance inputs while jointly searching for PI controller and observer gains. Using the controller and observer designed with 90% packet drop rate, we show the system performance degradation at 97%–99% QoS using phase portraits of the error dynamical system around the equilibrium as well as through univariate and multivariate hypothesis tests for equal dispersion around the equilibrium of the error dynamical system.

Untangling role of cooperative hunting among predators and herd behavior in prey with a dynamical systems approach

In the real world, group formation is ubiquitous. This group behavior is according to the species' needs; some species use it for hunting and some for protection from predators. In this paper, we proposed a prey-predator model with cooperative hunting among predators and herd behavior in prey, and we studied the temporal and spatiotemporal analysis. We first examine the system's positivity, boundedness, and then analyze the local stability criterion of equilibrium points. We perform Hopf–bifurcation analysis at feasible equilibrium points by considering s and α as the bifurcation parameters. With the incorporation of diffusion into the system, we derive the diffusion-driven instability of the prey-predator system. Then we performed a weakly nonlinear analysis and derived amplitude equations by considering self-diffusion as Turing bifurcation parameters. The stability analysis of these amplitude equations leads to the identification of various Turing patterns, such as spots, stripes, and mixed. Employing numerical simulations, we present the main types of patterns observed for parameters in the Turing domain. Our findings reveal that cooperative hunting, interspecific competition, and self-diffusion have important implications in the prey-predator system.

Mathematical modeling on chaotic convection in a hybrid nanofluids

This study focused on investigating the chaotic behavior of thermal convection in hybrid nanofluids in a fluid layer heated from below based on a dynamical systems approach. The solution of a nonlinear coupled system of partial differential equations was obtained through the application of a truncated Galerkin expansion, which then a system of ordinary differential equations with a low dimensional Lorenz-like model was generated by reduction. The effect of hybrid nanofluids on chaotic convection was studied. For the numerical solution, the nonlinear ordinary differential equation system was solved using the fourth-order Runge–Kutta technique. A transition from order to the chaos was discovered in the system.

The System Dynamic of Mangrove Ecotourism of “Kampung Blekok” Situbondo East Java Indonesia: Economic and Ecological Dimension

Mangroves that grow in coastal areas have ecological and economic values. Research on the behavior of a mangrove ecotourism system is needed as a basis for management to provide sustainable benefits. This study aimed to describe the conceptualization of a mangrove ecotourism system, formulate a mangrove ecotourism model and formulate a scenario for Kampung Blekok mangrove ecotourism in Situbondo Regency. This study used a quantitative analysis with a dynamic system approach to see the behavior of the ecotourism system on the economic and ecological dimensions. The research results on the conceptualization of the ecotourism system with causal loop diagrams showed that the economic subsystem was composed of response variables in the form of ecotourism management income and community business income in ecotourism areas and gross regional domestic product. Meanwhile, the ecological subsystem consisted of response variables in mangroves’ death, planting, and rehabilitation. Model formulation with stock-flow diagrams demonstrated the relationship between response variables to explain the system. In the economic subsystem, the variable of community business acceptance had the highest sensitivity that could affect ecotourism income. While in the ecological subsystem, the highest sensitivity was on the variable of mangrove planting, which could affect the density of mangroves. The combination of economic subsystem scenarios optimized tourist visits and streamlined spending. The combination of ecological subsystem scenarios that became the priority was the addition of mangrove seedlings and controlling pests that caused the death of mangrove seedlings. Stakeholders are expected to synergize with each other in managing activities in ecotourism. Apart from exploiting their economic potential, the community and the private sector are also expected to participate in maintaining compliance with regulations to preserve mangroves. The government should monitor and enforce regulations related to ecotourism and support the development of mangrove ecotourism so that its benefits are sustainable.

Flexibility Versus Routineness in Multimodal Health Indicators: A Sensor-based Longitudinal in Situ Study of Information Workers

Although some research highlights the benefits of behavioral routines for individual functioning, other research indicates that routines can reflect an individual's inflexibility and lower well-being. Given conflicting accounts on the benefits of routine, research is needed to examine how routineness versus flexibility in health-related behaviors correspond to personality traits, health, and occupational outcomes. We adopt a nonlinear dynamical systems approach to understanding routine using automatically sensed health-related behaviors collected from 483 information workers over a roughly two-month period. We utilized multidimensional recurrence quantification analysis to derive a measure of health regularity (routineness) from measures of daily step count, sleep duration, and heart rate variability (which relates to stress). Participants also completed measures of personality, health, and job performance at the start of the study and for two months via Ecological Momentary Assessments. Greater regularity was associated with higher neuroticism, lower agreeableness, and greater interpersonal and organizational deviance. Importantly, these results were independent of overall levels of each health indicator in addition to demographics. It is often believed that routine is desirable, but the results suggest that associations with routineness are more nuanced, and wearable sensors can provide insights into beneficial health behaviors.