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62 articles for “nonlinear materials”
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A REVIEW PAPER ON BENDING ANALYSIS OF SHEET METAL WITH VARIOUS PROCESS PARAMETERS
Abstract: Sheet metal forming is a mostly use and expensive developed process. decrease of response time and costs, increases of the efficiency and superiority of the manufactured goods are very important for survival in the competitive manufacturing industry. Using Finite element analysis as a simulation Technique we can evaluate the performance of components, equipment’s and structures for various loading conditions. A categorization of managing geometry and material nonlinearity with regards to …
Published in Journal of Automobile Engineering and Applications · Vol. 5, Issue 2, 2018 · pp. 41–46 Read article
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Non-linear Photonic Crystals and their Applications: A Review
Abstract: The nonlinear photonic crystals (NLPCs) are periodic material structures in which nonlinear materials are used for photonic structure formation. In nonlinear photonic crystals, the optical response mainly depends on the intensity of the light beam that propagates through the photonic crystal. These structures show new optical properties with improved or enhanced or new functionalities that cannot be observed in linear photonic crystals. In addition to this, using nonlinear materials in …
Published in Trends in Opto-electro & Optical Communication · Vol. 12, Issue 2, 2022 · pp. 36–39 Read article
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Modelling of Large Elasto-plastic Deformations by EFGM
Abstract: Current work reports modelling and simulation of geometric and material nonlinearities arising due large elasto-plastic displacements in structural specimens by invoking enriched element free Galerkin method (EFGM). The displacement approximations are constructed by using moving least square approach. Standard displacement based approximations are modified by incorporating suitable enrichment functions depending on the nature of interfaces present in the components. Large deformations give rise to geometric nonlinearities which have been modelled …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 130–143 Read article
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Hybrid Quantum–Machine Learning Framework for Nonlinear Rheological Modeling of Polymer and Composite Materials
Abstract: In polymer and composite materials, a major challenge lies in predicting their nonlinear rheological response, owing to complex multiscale interactions that are not captured by traditional constitutive laws or conventional machine learning approaches. In this study, a hybrid Quantum–Machine Learning (QML) model comprising Quantum Support Vector Machine (QSVM) and Quantum Neural Network (QNN) architectures is proposed for viscosity prediction without requiring any specific rheological equation. To train and test the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 · pp. 19–35 Read article
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A Hybrid Multi-Physics Ensemble Deep Learning Framework for Simultaneous Prediction of Thermal and Electrical Conductivity in Functional Polymer-Based Nanocomposites
Abstract: Polymer-based nanocomposites have become promising materials for applications in energy storage, flexible electronics, biomedical devices, aerospace components, and advanced engineering because of their tunable thermal and electrical properties. Reliable prediction of these properties is essential for accelerating material design; however, existing analytical models and conventional machine learning techniques often fail to represent the complex interactions among filler characteristics, polymer matrices, processing conditions, and interfacial transport phenomena. This work presents HMEP-Net, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1062–1082 Read article
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Seismic-Resilient Structural Systems: Geotechnical Engineering
Abstract: Earthquakes represent one of the most destructive natural hazards, capable of causing severe structural damage, loss of life, and substantial economic disruption. Seismic waves propagating through the ground can induce excessive forces and deformations in buildings, often leading to partial or complete collapse. Statistical records indicate that thousands of earthquakes occur globally each year, including several major events that result in significant damage. Past earthquake disasters have repeatedly demonstrated that …
Published in Journal of Geotechnical Engineering · Vol. 13, Issue 1, 2026 · pp. 55–63 Read article
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Structure and Crystal Growth of Urea Doped P- Block Element
Abstract: Nonlinear optical (NLO) materials exhibiting second harmonic generation have attracted considerable attention over the past few decades because of their technological significance in areas such as optical communication, signal processing, and instrumentation. Urea, being an important NLO material, presents challenges in crystal growth and handling due to its highly hygroscopic nature. Various derivatives of urea have been investigated for NLO applications, and some have shown promising potential in this field. …
Published in International Journal of Crystalline Materials · Vol. 3, Issue 2, 2026 · pp. 08–13 Read article
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Sensitivity of Rigid Pavement Responses to Pavement Layer Thickness Due to Wheel Load: A Nonlinear Finite Element Study
Abstract: The behavior of a jointed plain concrete pavement (JPCP) has been investigated under single wheel load for interior loading using finite element technique to predict the critical pavement responses for both linear and nonlinear geometrical characterization. The idealized pavement system is analyzed using 3D finite element analysis with the general purpose finite element software ABAQUS. The developed 3D model was analyzed for four combinations of material characterizations- (1) linear base …
Published in Trends in Transport Engineering and Applications · Vol. 1, Issue 1, 2014 · pp. 1–9 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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Speed Estimation of High-Speed Hysteresis Motor Based on Extended Kalman Filter
Abstract: High-speed hysteresis motors are used in special industries such as medical centrifuges and gyroscopes. In spite of that, they are synchronous motors in some situations they may work in asynchronous speed. So, for reliable performance of hysteresis motor, closed loop control strategies are employed. On this way, speed/position of rotor must be known. Due to difficulty of using the speed sensors in high-speed hysteresis motor drives, employing the speed estimation …
Published in Journal of Power Electronics and Power Systems · Vol. 6, Issue 1, 2016 · pp. 34–44 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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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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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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Nonlinear Finite Element Analysis of Reinforced Concrete Exterior Beam Column Joint Subjected to Monotonic Loading
Abstract: A numerical analysis of exterior beam-column joint subjected to constant axial load on the column top and monotonic load applied at the beam tip is presented in this work. A strain-based nonlinear finite element program is developed in MATLAB R2009a. The nonlinear analysis of reinforced concrete structural member is carried out considering it as a two-phase system. The concrete in nonlinear range is considered as orthotropic material having different stress-strain …
Published in Recent Trends in Civil Engineering & Technology · Vol. 4, Issue 2, 2014 · pp. 12–21 Read article
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Total-internal-reflection-based optical rotation quasi-phase-matching for efficient second-harmonic generation in Cadmium Germanium Arsenide crystal
Abstract: This study investigates a total-internal-reflection (TIR)-based optical rotation quasi-phase-matching (ORQPM) approach for second harmonic generation within a cadmium germanium arsenide crystal slab. The crystal is coated with a thin film of yttrium oxide to facilitate precise control over phase shifts between p- and s-polarized light upon reflection at the slab-film interface. By leveraging the interplay between TIR- induced optical rotation and fractional QPM effects at designated bounce points, the configuration …
Published in International Journal of Crystalline Materials · Vol. 3, Issue 1, 2026 · pp. 01–09 Read article
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Machine Learning-Based Quantification of Polymer Structure Property Relationships for Predictive Material Design
Abstract: Polymer structures exhibit complex, hierarchical arrangements that strongly influence macroscopic properties, yet consistent quantification remains challenging due to nonlinear interactions and limited unified modeling strategies. Existing approaches inadequately capture generalized structure–property mappings across diverse polymer systems. This research aims to establish a machine learning-based quantification model for polymer structure–property relationships to support predictive material design. A Polymer Structure Property Dataset of 5,000 polymer samples includes structural descriptors and experimentally measured …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 737–754 Read article
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Synthesis and Applications of Copper- Doped Pyridine Precipitate
Abstract: A metal organic nonlinear optical single crystal, copper doped pyridine material, was created at room temperature using the slow evaporation solution growth technique (SEST). The developed material's crystalline nature was revealed by a powder X-ray diffraction (XRD) analysis. Single crystal XRD study shows that the material synthesized possesses monoclinic system of cell parameters, a = 11.44 Å, b = 7.92 Å, C = 11.74 Å and alpha and gamma is …
Published in Journal of Materials & Metallurgical Engineering · Vol. 15, Issue 1, 2025 · pp. 51–60 Read article
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Mechanical Performance Assessment of Hybrid FRP Laminates with Carbon Fiber Core Using Experimental and Numerical Approaches
Abstract: The high strength-to-weight ratio, corrosion resistance and design flexibility of Fiber-reinforced polymer (FRP) composites have attracted considerable attention in aerospace, automotive and structural applications. This work presents an experimental and finite element study on the tensile and flexural behavior of epoxy-based hybrid FRP laminates. Five laminate configurations were manufactured, including a unidirectional carbon fiber laminate and four hybrid laminates, Kevlar–Carbon–Kevlar (K/C/K), Glass–Carbon–Glass (G/C/G), Kevlar–Carbon–Glass (K/C/G), and Glass–Carbon–Kevlar (G/C/K). For all …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Numerical Prediction of Shear Modulus of Multi-Layer PUF Cored Sandwich Composites
Abstract: The present numerical investigation was mainly concerned with the evaluation of apparent shear modulus (Gc) of multi-layered polyurethane foam cored sandwich beams using a novel approach through the medium of general purpose program i.e. FEM/ANSYS. Aiming to the goal, three-point bending analysis was performed on sandwich beam models made up of composite face sheets and multi-layer polyurethane foam cores of different layer densities. Finite element models of sandwich beams were …
Published in Journal of Polymer & Composites · Vol. 5, Issue 3, 2017 · pp. 53–61 Read article
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Multimodal Data Fusion with Hybrid Machine Learning for Enhanced Prediction of Li-Ion Battery Remaining Useful Life and State of Charge
Abstract: Lithium-ion battery materials used in modern energy storage systems are required to exhibit high reliability, safety, and long lifecycle performance under varying operational and environmental conditions. Accurate prediction of Remaining Useful Life (RUL) and State of Charge (SoC) is therefore essential for understanding material degradation behavior, improving manufacturing quality, and enabling effective lifecycle management. However, nonlinear electrochemical aging, load variability, and thermal uncertainty significantly complicate accurate estimation of these parameters. …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 4, Issue 1, 2026 · pp. 11–23 Read article