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32 articles for “Nonlinear stability analysis”
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Study of Heat Transfer in a Time Dependent Vertically Oscillating Micropolar Liquid
Abstract: AbstractThe study involves the vertical time periodic vibration of the system. This leads to the appearance of a modified gravity term in basic equation, collinear with actual gravity, in the form of a time-periodic field perturbation and is termed as gravity modulation or g-jitter in the literature. The aim of this study is to find the effect of small amplitude of gravity modulation on the onset of thermal convection between …
Published in Recent Trends in Fluid Mechanics · Vol. 5, Issue 1, 2018 · pp. 63–74 Read article
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A Particle-Derived Nonlinear Dynamical Framework for Bubble Oscillations: Reduced-Order Modeling, Bifurcation Analysis, and Optimal Stabilization
Abstract: Particle-based fluid simulation has emerged as a powerful computational framework for modeling complex multiphase flows involving large deformations, moving interfaces, and nonlinear fluid interactions that challenge conventional mesh-based approaches. In this work, a nonlinear dynamical systems framework is developed for particle-resolved bubble oscillations by constructing a reduced-order model that preserves the dominant physical mechanisms governing bubble interface evolution. The formulation represents the bubble dynamics through coupled radial and shape deformation …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 2, 2026 · pp. 11–33 Read article
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Mathematical Approaches to Nonlinear Oscillatory Systems with Damping: Exact and Approximate Solutions
Abstract: The study of nonlinear oscillatory systems with damping is a key area of research in applied mathematics, particularly in the context of dynamical systems, stability analysis, and bifurcation theory. These systems, described by second-order nonlinear differential equations, exhibit a rich variety of behaviors, including periodic, quasi-periodic, and chaotic motions. The introduction of damping—representing energy dissipation—adds a layer of complexity, making the analytical and numerical solution of such systems a challenging …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 7–11 Read article
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AI-Assisted Gain Scheduling for Real-Time Temperature Control in Chemical Reactors
Abstract: Temperature control in continuous stirred-tank reactors (CSTR) represents a critical challenge in chemical process industries due to inherent nonlinearities, time-varying dynamics, and parametric uncertainties. Conventional proportional-integral-derivative (PID) controllers with fixed gains often fail to maintain optimal performance across varying operating conditions, leading to temperature excursions that compromise product quality and safety. This paper presents a novel AI-assisted gain scheduling framework that integrates artificial neural networks (ANN) with adaptive PID control …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 24–33 Read article
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Mathematical Analysis and Stability Analysis of Coupled Orbital–Attitude Dynamics for Autonomous Spacecraft under Perturbative Forces
Abstract: Autonomous spacecraft operating in Earth orbit are subjected to coupled translational and rotational dynamics influenced by gravitational and environmental perturbations. Accurate mathematical characterization of these interactions is essential for trajectory prediction, attitude stabilization, autonomous navigation, and mission reliability. This study develops a nonlinear mathematical framework for coupled orbital–attitude dynamics of an autonomous spacecraft under perturbative forces. The translational dynamics are formulated using the two-body gravitational model augmented by the second …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 2, 2026 Read article
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LQR-Based Optimal Control of Inverted Pendulum System with State Estimation and Stability Analysis
Abstract: The inverted pendulum on a cart is a canonical benchmark problem in control systems engineering, capturing the essential challenges of stabilizing an inherently unstable, underactuated, and nonlinear plant. Classical Proportional-Integral-Derivative (PID) controllers, while widely employed in industrial practice, exhibit fundamental performance limitations when applied to such systems, primarily due to their inability to account for multivariable coupling, process noise, and the absence of a systematic optimization framework. This paper presents …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 1, 2026 · pp. 31–43 Read article
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Structural Integrity Analysis of Reinforced Concrete Frames Under Progressive Collapse Scenarios
Abstract: This study examines how a tall reinforced concrete (RC) frame may gradually collapse under several column removal situations, such as edge, end, center, zigzag, and two-column failures. The study assesses the structural reaction based on displacement, inter-story drift, and Demand–Capacity Ratio (DCR) using nonlinear static pushover analysis carried out in ETABS. According to the analysis, the frame's stability is seriously jeopardized when two nearby columns and end columns are removed, …
Published in Journal of Geotechnical Engineering · Vol. 12, Issue 3, 2025 · pp. 1–15 Read article
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AI-Driven Prediction of Mechanical and Thermal Properties in Polymer-Based Functionally Graded Composites
Abstract: The proposed architecture of the current paper is an artificial intelligence (AI)-driven model of forecasting mechanical and thermal aspects of polymer-based functionally-graded composites (FGCs). Traditional micromechanical and finite element models, which are practical in homogeneous composites, might not be able to account in nonlinear interaction that is caused by compositional gradient. To overcome the challenge, machine learning (ML) models like artificial neural network (ANN), support vectors regression (SVR), and gradient-boosted …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 70–89 Read article
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POLYMER AND COMPOSITE-BASED GEOSYNTHETIC REINFORCEMENTS FOR SEISMIC STABILITY OF SOIL RETAINING STRUCTURES: MATERIALS, MECHANICS, AND PERFORMANCE REVIEW
Abstract: Geosynthetic materials based on polymer and composites have become important items for the structural performance and seismic resilience of the reinforced soil retaining systems. Mechanically stabilized earth walls in recent geotechnical engineering practice are increasingly based on enhanced polymeric reinforcements for enhanced tensile strength, durability, flexibility, and energy dissipation under dynamic loading. High-density polyethylene, polypropylene, polyester, and fiber-reinforced polymer composites are usually used. The present review focus on the recent …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Control and Stabilization of Maglev System Using 2-DOF PID Controller and its Comparative Analysis with Other PID Controller
Abstract: AbstractA Magnetic air suspension or a magnetic levitation has turned out to be a very capable technique in the fast common transport system because of its frictionless motion. Due to open-loop system, the elevation in magnetic air is an extremely unstable system; and hence to stabilise this it desire a controller in order to its stabilization and position-tracing. Because of its nonlinear behaviour, its controller implementation is a tough task. …
Published in Journal of Electronic Design Technology · Vol. 11, Issue 2, 2020 · pp. 1–6 Read article
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Data-Driven Material Design and Performance Improvement: Constructing Sustainable Polymer Nanocomposites Using Deep Learning
Abstract: In the formation of sustainable polymer nanocomposites, the effective material techniques are required to balance the mechanical qualities, environmental compatibility and processing efficiency. The optimization of polymer matrix, nanofiller loading, processing conditions and material properties is typically time consuming, resource intensive and highly dependent on trial-error methodology using standard experimental techniques. The present work provides a data-driven approach that combines deep learning with sustainable polymer nanocomposite design for predicting and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Mathematical Modeling of Tumor Growth and Immune System Interaction Incorporating Time Delays and Suppression Effects for Tumor Control
Abstract: Cancer growth is a complex biological process influenced by various factors, including the dynamic interaction between tumor cells and the host immune system. Mathematical modeling serves as a powerful tool to understand these interactions and predict the outcomes of different therapeutic strategies. This study presents a mathematical framework that captures the essential dynamics of tumor-immune interactions, specifically incorporating the effects of time delay and immune suppression mechanisms. Time delay accounts …
Published in Research and Reviews : A Journal of Immunology · Vol. 15, Issue 3, 2025 · pp. 25–34 Read article
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Expanding Hicks Contraction Theory, Multi-Valued Mappings in Generalized b-Menger Spaces
Abstract: This paper extends the Hicks contraction theory to multi-valued mappings within generalized b-Manger spaces, a class of metric-like structures that accommodate more flexible distance functions. By introducing new definitions, such as generalized admissibility conditions and weak compatibility in the multivalued sense, we provide a comprehensive analysis of how these contractions behave in broader topological and metric contexts. Our approach systematically generalizes classical contraction principles by relaxing conventional constraints, thereby broadening …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 1–05 Read article
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ANN-Based Adaptive Rotor Current Control for DFIG Wind Systems: A Comparative Dynamic Analysis
Abstract: The variability of rotor current management in Doubly Fed Induction Generator (DFIG)-based wind energy conversion systems is crucial for maintaining stability in power extraction under fluctuating wind and grid circumstances. Traditional proportional-integral (PI) controllers, despite their ease of use, frequently exhibit diminished performance when faced with parameter uncertainty, nonlinear behaviors, and rapid wind fluctuations.This paper presents an adaptive rotor current control strategy, which is an Artificial Neural Network (ANN)-based approach …
Published in Journal of Power Electronics and Power Systems · Vol. 16, Issue 1, 2026 · pp. 41–53 Read article
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Artificial Intelligence–Assisted Reduced-Order Modeling and Stability Control in Granular Couette Flow
Abstract: This study develops a reduced-order and stability-aware modeling framework for dense granular Couette flow by integrating continuum mechanics, bifurcation analysis, and data-driven stability estimation. Starting from coupled governing equations for momentum, granular temperature, and microstructural evolution, the system is nondimensionalized and reduced using a Galerkin projection consistent with shear-driven boundary conditions. This yields a low-dimensional nonlinear dynamical system that preserves the essential coupling between velocity, fluctuation energy, and structural relaxation. …
Published in Emerging Trends in Chemical Engineering · Vol. 13, Issue 3, 2026 Read article
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The Onset of Rayleigh-Bénard-Marangoni Convection in a Ferromagnetic Fluid Layer
Abstract: This study examined the implications of magnetic boundary conditions, which are vertical in nature, on buoyancy and surface tension–driven ferrothermal convection (FTC) in a ferrofluid layer. While the upper surface is stress-free and susceptible to general thermal boundary issues, the bottom surface is stiff and insulating against temperature changes. The eigenvalue issue is solved analytically using the regular perturbation method and numerically using the Galerkin technique. According to analysis, raising …
Published in Journal of Experimental & Applied Mechanics · Vol. 16, Issue 1, 2025 · pp. 1–9 Read article
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AI-Optimized Nano-Silica Reinforced PCM Composites for Predictive Solar-Thermal Energy Storage Networks
Abstract: This study presents an AI-optimized nano-silica reinforced polymer composite phase change material (PCM) for predictive solar-thermal energy storage networks. The proposed composite combines paraffin wax, high-density polyethylene (HDPE), and uniformly dispersed nano-silica particles to improve thermal conductivity, structural stability, leakage resistance, and long-term cycling performance. The composite was fabricated through melt blending and ultrasonication-assisted nanoparticle dispersion, followed by comprehensive morphological, chemical, thermal, and thermophysical characterization using scanning electron microscopy (SEM), …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Stretchable Elastomer–Phase Change Composites for Passive Thermal Management in Wearable Electronics
Abstract: Elastomer-embedded phase change material (EPCM) composites are developed as stretchable, leakage-free, and electrically insulating thermal regulation layers for wearable electronics operating under stringent skin-safety requirements. The EPCM architecture comprises microencapsulated organic phase change materials (μPCM, 30–70 wt%) uniformly dispersed within soft elastomer matrices based on PDMS or SEBS-type thermoplastic elastomers, together with low loadings (1–8 wt%) of electrically insulating hexagonal boron nitride (h-BN) fillers to enhance lateral heat transport. Differential …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 30–41 Read article
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Analysis of Power Quality Disturbances in Distribution Systems with Renewable Energy Integration
Abstract: The growing integration of renewable energy sources within the electrical distribution systems has greatly altered the working dynamics of the contemporary power grids. The introduction of intermittent and nonlinear sources (solar photovoltaic and wind energy systems) leads to a wide range of power quality disturbances, however. The current paper includes the in-depth examination of the problem of power quality in the distribution systems with the integration of renewable energy. The …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 Read article
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Machine Learning Based Optimization of Polymer Structure Property Relationships in Composite Material Systems
Abstract: In modern engineering applications, polymer-based composite materials have garnered a lot of attention because of their lightweight nature, high strength-to-weight ratio, and changing physical features. In order to maximize the relationships between polymer structure and properties in composite materials, this study suggests a strategy based on reinforcement learning (RL). The research utilized the Polymer Composite Properties Dataset, which contains 12,700 records associated with polymer matrices, reinforcement fillers, interfacial bonding characteristics, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 242–255 Read article