Stability Analysis Techniques Research Articles

Exploring dynamic behaviors of diverse electrical soliton pulses in lossy nonlinear electrical transmission lines: Insights from analytical method and linear stability analysis technique

Exploring dynamic behaviors of diverse electrical soliton pulses in lossy nonlinear electrical transmission lines: Insights from analytical method and linear stability analysis technique

A Unified Technique for Stability Analysis of an Embedded FG Porous Nano/Microbeam via Modified Couple Stress Theory

A Unified Technique for Stability Analysis of an Embedded FG Porous Nano/Microbeam via Modified Couple Stress Theory

Lyapunov stability of fuzzy dynamical systems based on fuzzy-number-valued function granular differentiability

Lyapunov stability theory provides a powerful technique for stability analysis of dynamical systems, particularly for the stability of nonlinear dynamical system. This paper deals with the stability of fuzzy dynamical systems using a novel notion called granular fuzzy Lyapunov function. In order to analyze the stability, some new notions are introduced such as fuzzy equilibrium point, the ball of fuzzy state space, granular fuzzy 2-norm and etc. Based on the concept of fuzzy-number-valued function granular differentiability, two theorems are proved for calculation. Moreover, using granular fuzzy Lyapunov function, the granular fuzzy local stability theorem is proposed, and two definitions of exponential stability and like-Lyapunov stability are generalized. Finally, several examples are given to illustrate the proposed theorems.

SUM OF PRIME NUMBERS

The design and assessment of closed loop control systems must include accurate and stable accuracy analysis and simulation. An overview of the significance of closed loop control systems and its uses in several engineering disciplines is given in this paper. The paper then explores the different techniques used for evaluating the accuracy and stability of closed loop control systems, including steady-state error analysis, stability analysis, and simulation techniques. It also discusses the design and tuning of control algorithms to optimize the performance of the system, and identifies the different factors that can affect the accuracy and stability of closed loop control systems, such as sensor noise, model inaccuracies, and environmental disturbances.

Prediction of debris flow initiation points using high resolution DEM and GIS analysis in South Korea

This study presents a GIS analysis model that utilizes high-resolution Digital Elevation Map data to predict the initiation points of debris flow through the overlap of slope stability analysis techniques and rainfall flow analysis. The debris flow that occurred on Mount Woomyun in Seoul, South Korea in 2011 was selected as the case study for comparing and analyzing the prediction model against the actual case. In South Korea, occurrences of debris flow mostly happen during the summer monsoon season. When a substantial amount of rainfall accumulates and heavy rainfall events occur, the pore water pressure within slopes reaches saturation. Consequently, flow is initiated along “temporary streams.” In this study, areas with a combination of low slope stability and abrupt changes in velocity vectors were assumed to have the highest probability of debris flow occurrence due to the overlapping of these factors. The research model was conducted under this assumption. To evaluate the performance of the model, 3D coordinates of the model’s result point, and actual occurrence points were obtained, and a Pearson correlation analysis was conducted to compare them. With these results, R2 values of X = 0.9147, Y = 0.8625, and H = 0.8942 were obtained. These high R2 indicate a strong correlation between the model’s predictions and actual occurrences.

Meshless numerical manifold method with novel subspace tracking and CSS locating techniques for slope stability analysis

The meshless numerical manifold method (MNMM) inherits the advantages of handling continuous and discontinuous problems uniformly, improving interpolation precision, and avoiding linear dependence issues. This paper refines the MNMM method for slope stability analysis to overcome the dependence and sensitivity of the strength reduction method of the finite element method on the number of finite element meshes and the algorithm for solving the nonlinear equations when calculating slopes with soft and weak interlayers. First, the strength reduction method (SRM) was incorporated into MNMM to create the numerical model called MNMM-SRM. Based on the MNMM-SRM, a complementary Mohr-Coulomb (M−C) control equation compliant with Koiter's rule of multi-yielding surfaces was established. In the principal stress space, the subspace tracking method was used to track the eigenvalues and eigenvectors of the stress tensor, thereby addressing the corner problem of M−C multi-yield surfaces. Combining the k-means clustering algorithm with wavelet transformation and employing the slope's total nodal displacement field as an input variable, an intelligent and efficient critical slip surface (CSS) automatic extraction method was developed. Three typical cases were used to validate the accuracy of the numerical model. This numerical model has a wide range of potential applications in slope stability research.

Stability Analysis and Navigational Techniques of Wheeled Mobile Robot: A Review

Wheeled mobile robots (WMRs) have been a focus of research for several decades, particularly concerning navigation strategies in static and dynamic environments. This review article carefully examines the extensive academic efforts spanning several decades addressing navigational complexities in the context of WMR route analysis. Several approaches have been explored by various researchers, with a notable emphasis on the inclusion of stability and intelligent capabilities in WMR controllers attracting the attention of the academic community. This study traces historical and contemporary WMR research, including the establishment of kinetic stability and the construction of intelligent WMR controllers. WMRs have gained prominence in various applications, with precise navigation and efficient control forming the basic prerequisites for their effective performance. The review presents a comprehensive overview of stability analysis and navigation techniques tailored for WMRs. Initially, the exposition covers the basic principles of WMR dynamics and kinematics, explaining the different wheel types and their associated constraints. Subsequently, various stability analysis approaches, such as Lyapunov stability analysis and passivation-based control, are discussed in depth in the context of WMRs. Starting an exploration of navigation techniques, the review highlights important aspects including path planning and obstacle avoidance, localization and mapping, and trajectory tracking. These techniques are carefully examined in both indoor and outdoor settings, revealing their benefits and limitations. Finally, the review ends with a comprehensive discussion of the current challenges and possible routes in the field of WMR. The discourse includes the fusion of advanced sensors and state-of-the-art control algorithms, the cultivation of more robust and reliable navigation strategies, and the continued exploration of novel WMR applications. This article also looks at the progress of mobile robotics during the previous three decades. Motion planning and path analysis techniques that work with single and multiple mobile robots have been discussed extensively. One common theme in this research is the use of soft computing methods to give mobile robot controllers cognitive behaviors, such as artificial neural networks (ANNs), fuzzy logic control (FLC), and genetic algorithms (GAs). Nevertheless, there is still a dearth of applications for mobile robot navigation that leverage nature-inspired algorithms, such as firefly and ant colony algorithms. Remarkably, most studies have focused on kinematics analysis, with a small number also addressing dynamics analysis.

Field-free self-oscillation of magnetization enabled by the fieldlike spin-orbit torque

Fieldlike spin-orbit torque, which behaves like a torque from a magnetic field, but relies on the current together with the damplike one, was recognized to influence magnetization switching. However, its role on magnetic oscillations remains to be explored. By linear stability analysis and energy averaging technique, we obtain analytic formulas for the stable boundaries of various states. Then, a phase diagram is constructed, which is controlled by the current and a tunable ratio β of the fieldlike torque to the dampinglike one. We find that some new stable, bistable and dynamic states come forth. Especially, a bias-field-free self-oscillation emerges for negative β, which enables the average energy balance between the dampinglike torque and the intrinsic damping. There occur two kinds of oscillations, analogous to the usual in-plane and out-of-plane precessions. If increasing the current, the frequency declines for the former, and subsequently rises for the latter. Varying β slightly affects the frequency range, but dramatically alters the adjustable range of current. In addition, the phase diagram indicates that the switching direction reverses with β stepping over −1/α with α being the damping constant, and the switching current decreases with ∣β∣ increasing.

Linear or non-linear stability monitor in BWRs? Introducing a new non-linear monitor based on the fractal spectrum

The stability phenomenon in nuclear boiling water reactors (BWRs) continues to be of scientific and technological interest contributing to the development of advanced stability monitors. The Mexican scientific community over the course of more than two decades (in the world more than four decades) has developed innovative techniques for stability analysis in BWRs, both online and offline; inspired in the first instance by the Laguna Verde NPP instability event occurred on January 24, 1995. Under this perspective, an extensive discussion of linear and non-linear techniques for stability analysis of BWRs is included in this work as well a novel method of stability analysis in BWR based on a Higuchi Fractal Spectrum for the design of a non-linear monitor. This methodology, based on a generalization of the Higuchi Fractal Dimension (HFD), permits to determine in real-time, the stability of a BWR. Hence, real challenging cases in which the instability of the reactor is not evident, were used to test this proposed stability indicator. In general, this proposal gives a better forecast than that based on the simple HFD.

Instability analysis of vibrated thermo-convection in Casson nanofluid suspension

This work is motivated by the importance of vertical vibration in nanofluids suspension, because of its wide applications in heat exchangers from one fluid to another, controlling the mixing in microvolumes, pharmaceutical industry, and engineering. The current study analyzes the effects of high-frequency vertical vibration on a horizontal Casson nanofluid layer heated from below saturated between rigid-rigid, rigid-free, and free-free boundary conditions. Field equations are derived by using time-average method, which describes the vibrational thermo-convection. These field equations are solved by utilizing linear stability analysis and Galerkin technique to obtain the thermal stability curve. By using this curve, the impacts of vertical vibration and physical governing factors on temperature profile are discussed. High-frequency vertical vibration is observed to have a stabilizing effect on Casson nanofluid suspension, thereby reducing thermo-convective heat transfer from one fluid to another. Stability threshold of vibrated suspension is increased approximately as [Formula: see text] and [Formula: see text] when [Formula: see text] and [Formula: see text], respectively. The significance of Brownian motion and thermophoretic force on convective heat transfer with vertical vibration is discussed. The resisting nature of Casson nanofluid on vibrational convective heat transfer is also tabulated.

Stability analysis in a couple-stress fluid layer with variable viscosity heated from below: Different conducting boundaries

The Linear stability analysis technique and non-linear stability analysis technique are applied for couple stress fluid layer with having variable viscosity depending on temperature and pressure. The linear and nonlinear threshold that encapsulates the physics of the onset for convection is found to be same. Eigenvalue problems for free-free (FF), rigid-free (RF) and rigid-rigid (RR) conducting boundaries are solved with the help of a single term Galerkin technique. The couple stress is seen to have a stabilizing impact while the viscosity variation has destabilizing impact on the system.

Photorefractive four-wave mixing cannot be treated perturbatively. Revisiting the undepleted-pump approximation

We theoretically consider photorefractive degenerate four-wave mixing oscillators and show that, for this particular system, the linear stability analysis technique leads to incorrect results. The reason for this astonishing failure lies in the unphysical predictions of the undepleted-pump approximation, which appear naturally during the linearization process of the full model. As a consequence, photorefractive four-wave mixing does not seem to permit a perturbative treatment that allows the derivation of mean-field models, and one is forced to use the full model in order to make sensible predictions.

Investigation on nonlinear buckling performance of the optimized wing structure under the realistic flight cases

The nonlinear finite element simulation is a standard technique for structural stability analysis, whereas it still has disadvantages of highly computational cost and poor convergence, especially for the large and complex wing structure. In this paper, nonlinear buckling analysis of a wing structure is performed and focused on the local region that is prone to instability, the boundary conditions of which are determined using the sub-modeling technique and realistic flight conditions of an aircraft. Firstly, the flight envelope is calculated based on the preliminary parameters of a large aircraft. Three typically flight cases of the aircraft are selected and the corresponding aerodynamic loads are achieved. Then, an optimization problem with strength and deformation constraints is defined to minimize the weight of the wing structure under the design limit load. A significant reduction in structural weight is achieved by considering three typically flight cases in the optimization process. Next, linear structural analyses come to a conclusion that the upper skin of the wing butt box located between the inner and outer wings is easy to lose stability. The sub-modeling technique is used to extract the local model of the wing butt box from the global model of the wing structure. A nonlinear buckling analysis is performed on the local model by applying the realistic boundary conditions solved from the global model. The skin depressions produced by buckling are carefully studied. Finally, the wing upper skin is reinforced by assigning the stringers to increase the buckling resistance of the structure. The appearance of the skin depressions is significantly postponed, meanwhile the depth is largely reduced.

On a Novel Dynamics of a SIVR Model Using a Laplace Adomian Decomposition Based on a Vaccination Strategy

In this paper, we introduce a SIVR model using the Laplace Adomian decomposition. This model focuses on a new trend in mathematical epidemiology dedicated to studying the characteristics of vaccination of infected communities. We analyze the epidemiological parameters using equilibrium stability and numerical analysis techniques. New mathematical strategies are also applied to establish our epidemic model, which is a pandemic model as well. In addition, we mathematically establish the chance for the next wave of any pandemic disease and show that a consistent vaccination strategy could control it. Our proposal is the first model introducing a vaccination strategy to actively infected cases. We are sure this work will serve as the basis for future research on COVID-19 and pandemic diseases since our study also considers the vaccinated population.

Stability and Dynamics of Active Distribution Networks (ADNs) With D-PMU Technology: A Review

Massive integration of converter-interfaced distributed energy resources (CDERs) has resulted in many emerging stability issues and significantly complicated the dynamics of active distribution networks (ADNs). Large quantities of CDER systems with complex structures, time-varying parameters and ‘black-box’ controllers not only make the system modelling nearly an impossible task, but also considerably increase the dimension of dynamic models and thus the computational burden for the model-based stability analysis and control. Distribution-level phasor measurement unit (D-PMU) technology has a superior capability of monitoring, analyzing and controlling the real-time system dynamics. This paper provides a comprehensive overview on the state-of-the-art techniques of dynamics monitoring, analysis and control based on D-PMU technology in ADNs. A special emphasis is placed on the emerging instability incidents induced by CDERs. Although stability monitoring, analysis and control techniques based on PMU technology are well established in the transmission systems, substantial research efforts are required to extend these techniques to deal with the different dynamic characteristics of distribution systems. The application of big-data analytics in analyzing D-PMU data streams becomes prevalent, which can dig more information and thus provide more effective measures for stability analysis and control of ADNs.

Numerical Modelling Techniques for Stability Analysis of Slopes Reinforced with Shallow Roots

It is well recognised that plant vegetation and roots are capable of improving the shear strength of hillslopes by reinforcing soil shear resistance. Several key factors influencing the level of slope reinforcement include root geometry, orientation and strength. To assess the mechanical performance of vegetated slopes using numerical methods, root structures can be represented by beam and pile elements to mirror root behaviour. In contrast, root reinforcement can be modelled indirectly through a root cohesion factor, supplying additional strength to the soil surrounding the root zone. In this paper, correlations between these two numerical methods are presented, highlighting the applicability of each technique based on various root characteristics. Three types of root geometries are presented, consisting of a primary tap root, a secondary cohesion zone surrounding the main root and a root branching process. The results of the finite element analysis demonstrate the variation in the slope factor of safety for both methods, with a set of correlations between the two modelling approaches. A series of stability charts are presented for each method, quantifying the effects of root characteristics on slope reinforcement.

Transient Stability Analysis and Enhancement Techniques of Renewable-Rich Power Grids

New techniques and approaches are constantly being introduced to analyze and enhance the transient stability of renewable energy-source-dominated power systems. This review article extensively discusses recent papers that have proposed novel and innovative techniques for analyzing and enhancing the renewable source-dominated power system’s transient stability. The inherent low-inertia characteristics of renewable energy sources combined with fast-acting power electronic devices pose new challenges in power systems. Different stability concerns exist for grid-following and subsequent grid-forming converter/inverter connections to power grids; hence, distinct solutions for enhancing the transient stability have been devised for each. Moreover, the fundamental concepts and characteristics of converter/inverter topologies are briefly discussed in this study. Recent discussions and reviews of analysis and enhancement techniques in transient stability could lead to new ways to solve problems in power systems that rely primarily on renewable energy sources.

Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology

This work employs machine learning methods to develop and test a technique for dynamic stability analysis of the mathematical model of a power system. A distinctive feature of the proposed method is the absence of a priori parameters of the power system model. Thus, the adaptability of the dynamic stability assessment is achieved. The selected research topic relates to the issue of changing the structure and parameters of modern power systems. The key features of modern power systems include the following: decreased total inertia caused by integration of renewable sources energy, stricter requirements for emergency control accuracy, highly digitized operation and control of power systems, and high volumes of data that describe power system operation. Arranging emergency control in these new conditions is one of the prominent problems in modern power systems. In this study, the emergency control algorithms based on ensemble machine learning algorithms (XGBoost and Random Forest) were developed for a low-inertia power system. Transient stability of a power system was analyzed as the base function. Features of transmission line maintenance were used to increase accuracy of estimation. Algorithms were tested using the test power system IEEE39. In the case of the test sample, accuracy of instability classification for XGBoost was 91.5%, while that for Random Forest was 81.6%. The accuracy of algorithms increased by 10.9% and 1.5%, respectively, when the topology of the power system was taken into account.

Energy, exergy and economic (3E) analysis of flat-plate solar collector using novel environmental friendly nanofluid

The use of solar energy is one of the most prominent strategies for addressing the present energy management challenges. Solar energy is used in numerous residential sectors through flat plate solar collectors. The thermal efficiency of flat plate solar collectors is improved when conventional heat transfer fluids are replaced with nanofluids because they offer superior thermo-physical properties to conventional heat transfer fluids. Concentrated chemicals are utilized in nanofluids' conventional synthesis techniques, which produce hazardous toxic bi-products. The present research investigates the effects of novel green covalently functionalized gallic acid-treated multiwall carbon nanotubes-water nanofluid on the performance of flat plate solar collectors. GAMWCNTs are highly stable in the base fluid, according to stability analysis techniques, including ultraviolet–visible spectroscopy and zeta potential. Experimental evaluation shows that the thermo-physical properties of nanofluid are better than those of base fluid deionized water. The energy, exergy and economic analysis are performed using 0.025%, 0.065% and 0.1% weight concentrations of GAMWCNT-water at varying mass flow rates 0.010, 0.0144, 0.0188 kg/s. The introduction of GAMWCNT nanofluid enhanced the thermal performance of flat plate solar collectors in terms of energy and exergy efficiency. There is an enhancement in efficiency with the rise in heat flux, mass flow rate and weight concentration, but a decline is seen as inlet temperature increases. As per experimental findings, the highest improvement in energy efficiency is 30.88% for a 0.1% weight concentration of GAMWCNT nanofluid at 0.0188 kg/s compared to the base fluid. The collector's exergy efficiency increases with the rise in weight concentration while it decreases with an increase in flow rate. The highest exergy efficiency is achieved at 0.1% GAMWCNT concentration and 0.010 kg/s mass flow rate. GAMWCNT nanofluids have higher values for friction factor compared to the base fluid. There is a small increment in relative pumping power with increasing weight concentration of nanofluid. Performance index values of more than 1 are achieved for all GAMWCNT concentrations. When the solar thermal collector is operated at 0.0188 kg/s and 0.1% weight concentration of GAMWCNT nanofluid, the highest size reduction, 27.59%, is achieved as compared to a flat plate solar collector with water as a heat transfer fluid.

A hybrid control technique for small signal stability analysis for microgrids under uncertainty

Distributed generators (DG) with inverter based on renewable sources are generally utilized in microgrids. Most of these sources work in droop control mode to effectively share the load. Higher droop is chosen on these systems to recover dynamic power sharing. This paper proposes a Hybrid Control Technique for Small Signal Stability Analysis for Microgrids under Uncertainty. The proposed topology is to recover the capacity of power system is used to restore the normal operating condition. The proposed hybrid technique is the combination of chaotic Henry gas solubility optimization (CHGSO) and recalling-enhanced recurrent neural network (RENNN) and therefore called the CHGSO-RENNN technique. The proposed technique is used to optimally predict the internal and external current loop control parameters in light and the variety of power and current parameters. The small stability is revealed through the working conditions of the whole machine. The overall stability of the small signal is investigated in a linear model so that both source and load are used to characterize the state matrix of the frame that is used for eigenvalue examination. The PI controller gain parameters are optimally tuned and the controller offers reliable frame operation. The proposed technique is performed on MATLAB/Simulink work platform.