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109 articles for “nonlinear parameter”
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Evaluation of Thermal Damage in Pipe by Nonlinear Guided Wave
Abstract: This work investigates the evaluation of thermal damage in aluminum pipe by using nonlinear guided wave. Thermal loading was imposed on the specimens to cause thermal degradation. Flexible Polyvinylidene Fluoride (PVDF) comb transducers are used to generate and receive the ultrasonic waves. The second harmonic wave generation technique was used to check the material nonlinearity change after different heat loading. Conventional linear ultrasonic approach based on the acoustic attenuation was …
Published in Journal of Nuclear Engineering & Technology · Vol. 3, Issue 1, 2013 · pp. 22–27 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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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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Motors Using a Deep Learning-Based Torque Control with Torque Ripple Reduction under Nonlinear Magnetic Conditions
Abstract: This research discusses a deep learning strategy for torque management to minimize the effect of torque ripple in a nonlinear electric motor. Nonlinear electric motor losses may include: magnetic saturation, harmonic flux losses and inverter losses. In many cases when the system parameters deviate and/or instability issues occur, the traditional method with a model-based approach or PI control may encounter challenges. In this case, the authors proposed a hybrid approach …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 2, 2026 Read article
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AI-Enabled Optimization of Additively Manufactured Composite Materials for Enhanced Mechanical and Thermal Performance
Abstract: This paper discusses the optimization of multi-objective optimization of enhanced coupling of heat and mechanical properties of 3D printed polymer composite materials by artificial intelligence (AI), as a component of a multi-objective optimization framework. It aims at development of nonlinear printing parameters and material properties relationships to achieve maximum tensile strength and thermal conductivity in polymer composites produced through fused deposition modeling (FDM). Short carbon fiber reinforcement was used to …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 867–891 Read article
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Parameter Estimation of Software Reliability Growth Model
Abstract: Reliability normally covers each and every part of the device thinking about hardware, software program and processes but software program reliability paperwork an important factor as we are continually worried with efficient and quality software program. Software reliability is a crucial characteristic of software, nice for predicting the diploma of creditability of the precise software for the specified time frame and in particular surroundings. Software reliability models are categorized into …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 1, 2020 · pp. 15–22 Read article
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Effect MFD Viscosity on Bénard–Marangoni Ferroconvection in a Rotating Ferrofluid Layer with Convective Surface Boundary Condition
Abstract: AbstractThe combined effect of Coriolis force due to rotation and magnetic field dependent (MFD) viscosity on the onset of Bénard–Marangoni convection in a horizontal layer of ferrofluid is investigated theoretically. The lower boundary is taken to be rigid–isothermal, while the upper free boundary open to the atmosphere is flat and subject to a convective surface boundary condition. The Galerkin technique is employed to extract the critical stability parameters numerically. It …
Published in Recent Trends in Fluid Mechanics · Vol. 7, Issue 2, 2020 · pp. 12–32 Read article
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Wind Forecasting Using Various Neural Networks in Machine Learning
Abstract: Wind Power Forecasting, as the name applies is a process in which data of past is used to tell what kind of output can be expected from a wind turbine in the foreseeable future. Machine learning, can be said to be a derivation of artificial intelligence that makes it possible for the system to learn automatically and improve upon itself from faults, without needing to tell the system to do …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 8, Issue 2, 2021 · pp. 32–43 Read article
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Bayesian Optimization–Driven Operating Parameter Tuning for Maximizing Methane Yield in Anaerobic Digestion
Abstract: To achieve maximum methane production in an anaerobic digestion (AD) process, a combination of various operational parameters must be tuned nonlinearly in the digestion ecosystem. The conventional trial and error optimization methods are slow, resource consuming, and in most instances, cannot model the intricate parameter interaction in biogas production. The current work introduces a Bayesian Optimization-based model to optimize the set of conditions to maximize the level of methane produced …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 1–8 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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Investigations on Piezoactuator-Based Active Vibration Isolation for Tool-Based Micromachining Applications
Abstract: Stacked piezoactuators are suitable actuators for active vibration isolation systems due to their high stiffness and fast response. However, they exhibit hysteresis nonlinearity between applied voltage and the resulting displacement. In this paper, Bouc-Wen model is used to model the hysteresis nonlinearity of stacked piezoactuator. The model parameters are estimated from the experimental voltage-displacement data of a stacked piezoactuator using “Trust-region nonlinear least square method” in MATLAB Simulink. The resulting …
Published in Journal of Mechatronics and Automation · Vol. 2, Issue 1, 2015 · pp. 41–49 Read article
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Anti-synchronization of Bhalekar–Gejji Chaotic System via Nonlinear Active Control
Abstract: AbstractIn this paper, a scheme of global anti-synchronization between two identical newly developed Bhalekar–Gejji chaotic system is proposed. This anti-synchronization scheme is achieved by using nonlinear active control since the parameters of both the systems are known and states are measurable. Lyapunov stability theory is used to ensure stability of error dynamics. Controller is designed by using the sum of relevant variables in master and slave chaotic systems. Simulation results …
Published in Research & Reviews : Journal of Physics · Vol. 4, Issue 1, 2015 · pp. 1–6 Read article
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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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Machine Learning Assisted Design and Analysis of Polymer Composite Materials for Sustainable Renewable Energy Systems
Abstract: Accurate prediction and optimization of polymer composite properties is of paramount importance in the design of these lightweight, durable, and sustainable materials within renewable energy technologies. This work will provide a holistic machine learning-assisted framework that unites materials informatics with domain-specific features and state-of-the-art ML methodologies in the prediction of the mechanical properties of polymer composites, such as tensile strength. This includes embedding several ensemble models, including Random Forest and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 391–402 Read article
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Hybrid Machine Learning and Finite Element Framework for Predicting Damage Behavior in Fiber-Reinforced Polymer Composites
Abstract: Fiber Reinforced Polymer (FRP) composites have broad spread use in aerospace, automotive, marine and structural applications due to its high specific strength, stiffness and corrosion resistance. The various damage mechanisms such as matrix cracking, fiber breakage, delamination and interfacial failure, however, make the forecasting of damage particularly complex. In this work, a hybrid machine learning (ML) and finite element (FE) system is proposed for predicting the damage behavior of FRP …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Computational Intelligence and Neuro-Fuzzy Modelling of Polymer Composites: A Critical Review of Performance Prediction and Optimization
Abstract: The increased variety in polymer matrices, reinforcements, fillers, and processing parameters has led to the need to better understand the structure-property, process-property relationships in order to accurately predict and optimize the performance of polymer composites. This paper reviews the applications of computational intelligence methods in polymer composites, with special focus on artificial neural networks, adaptive neuro-fuzzy inference systems, machine learning techniques, and hybrid optimization. The literature is analyzed based on …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Artificial Intelligence for Polymer and Nanocomposite Materials: Performance Prediction, Manufacturing Optimization, and Future Perspectives
Abstract: The exceptional mechanical properties, design flexibility, and lightweight nature of polymer composite and nanocomposite materials make them indispensable in a wide range of applications, including aerospace, automotive, construction, biomedical, and energy sectors. The optimization of the strength, durability, and manufacturing efficiency of polymer composite and nanocomposite materials is highly challenging because their performance depends on matrix composition, reinforcement type, fiber or nanoparticle distribution, interfacial interactions, processing conditions, and environmental factors. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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A Multivariate Adaptive Regression Splines Based Study of Soil Parameters and Their Impact on Onion Yield in Bhavnagar District
Abstract: Bhavnagar district is one of the prominent onion-growing areas in the Saurashtra region of Gujarat, encompassing key talukas such as Mahuva, Talaja, Ghogha, Jesar, and Palitana. Onion cultivation in the district is carried out across three distinct seasons: rabi, kharif, and late kharif with harvesting periods extending from April to May for the rabi crop and from October to March for the kharif and late kharif crops. The productivity of …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 53–64 Read article
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Controller Performance Assessment (CPA) of Intelligent Control for Non-linear System
Abstract: The objective of this paper is to design and undertake comparative analysis of classical and intelligentcontrollers for nonlinear system. These controllers are compared based on controller performanceassessment in which the different parameters as overshoot, steady-state error, rise time, settling time,response of reference change and output variance are analyzed. To achieve these objectives, the water tankcontrol problem as nonlinear system has been built in Simulink and implementations traditionally classicalcontroller and advance …
Published in Journal of Control & Instrumentation · Vol. 1, Issue 1-2-3, 2011 · pp. 25–33 Read article
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Estimation of Burger Model Parameters by Inverse Analysis of Oedometer Data
Abstract: Contrary to the forward analysis, inverse analysis can be effectively utilized to determine the parameters of a constitutive model commonly used to represent the stress-strain-time behavior or the load-deformation-time behavior of the soil. This paper reports the development of a generalized inverse analysis formulation for the parameter estimation of four-parameter Burger model. The analysis is carried out by formulating the problem as that of mathematical programming in terms of identification …
Published in Recent Trends in Civil Engineering & Technology · Vol. 2, Issue 1-3, 2012 · pp. 37–54 Read article