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34 articles for “constitutive modeling”
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Artificial Intelligence and Constitutive Modeling Equations for Predictive Design of High-Performance Polymer Composites
Abstract: Growing polymer composite applications demand accurate mechanical prediction, yet complex interactions and conventional constitutive models limit predictive capability and require extensive calibration. To report these challenges, this research recommends a combined Artificial Intelligence (AI) and constitutive modeling approach based on an Enhanced Tasmanian Devil Optimizer-tuned Residual Neural Network with Multilayer Perceptron (ETDO-ResNet-MLP) for the predictive design of high-performance polymer composites. The study uses a publicly available Polymer Composite Property Dataset …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Dynamic deformation and microstructural characteristics of AA5083 under the influence of electrochemical behaviour using equal channel angular pressing
Abstract: Large-scale Equal channel angular pressing is a great engineering material that has more potential for AA5083 industrial applications. Uniaxial dynamic compressive tests across a temperature of 448 K were conducted for the ECAP technique AA5083 in order to create such a design framework. The microstructure was described using transmission electron microscopy and scanning electron microscope both before and after dynamic loading. The plastic flow behaviour of the AA5083 was described …
Published in Journal of Polymer & Composites · Vol. 12, Issue 1, 2024 · pp. 95–112 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
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Innovative Risk Aperture Manipulation Model for Risk Management in Mega Project Construction
Abstract: The complexities associated with the technical, managerial and financial interventions in mega project implementation accommodates greater risks, encapsulating the complete project period from inception to closure. Consideration of risks in mega project scope is of paramount importance as it delineates either threat or opportunity in the guise of uncertainty at each and every phase of the project. The absence of innovative and rigorous risk management structure imparts a perplexing scenario …
Published in Trends in Transport Engineering and Applications · Vol. 2, Issue 1, 2015 · pp. 11–24 Read article
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Smart Urban Traffic Management System
Abstract: In recent years, the ownership of private vehicles has increased many folds, which is causing difficulty in management of urban traffic. Traffic management is the focus area for most urban dwellers and planners. Some of the main concerns for traffic management of big cities is traffic congestion and avoidance, as these issues cause huge damages on both personal and environmental level. Moreover, in many cities traffic signal lights at crossing …
Published in Trends in Transport Engineering and Applications · Vol. 4, Issue 1, 2017 · pp. 56–65 Read article
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AI-Driven Topology Optimization of Woven Fiber-Reinforced Composite Chassis Structures for Electric Vehicles Under Crash Loading
Abstract: The structural design of an electric vehicle (EV) chassis represents a unique engineering challenge to achieve minimal weight while meeting occupants' safety requirements during high-energy crash conditions without compromise to the battery housing's integrity or the geometrical constraints of the electric powertrain package. In this paper, a single framework is proposed to integrate physics-based artificial intelligence (AI) surrogate models using PINNs, CNN-accelerated topology optimization, and FEA to design woven fiber-reinforced …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 72–89 Read article
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Activation Energy in Photochemical and Thermally Driven Reactions: Mechanistic Insights, Kinetic Modelling and Photocatalytic Applications
Abstract: Chemical reactions constitute fundamental processes in which reactants are transformed into products through the breaking and formation of chemical bonds. In photochemical systems, these transformations are initiated or influenced by the absorption of light, making energy transfer mechanisms particularly significant. A key parameter governing reaction kinetics is activation energy, defined as the minimum energy required for reactant molecules to undergo a successful transformation. This article focuses on the role of …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 4, Issue 1, 2026 · pp. 21–26 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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Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Method: A Comprehensive Review
Abstract: Structural health monitoring (SHM) has a critical role in ensuring civil infrastructure safety, reliability, and durability through real-time, condition-based monitoring. Traditional SHM systems employ hundreds of sensors such as accelerometers, strain gauges, and displacement transducers for monitoring vast amounts of data for structural inspection, but do not effectively manage complicated nonlinear data. This research paper, “Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Methods,” investigates …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 1, 2026 · pp. 23–33 Read article
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Effect of Chronic Inescapable Footshock and Antidepressant Treatment on BDNF/TrkB Levels in Rat Hippocampus
Abstract: Depression is a major health problem globally. Chronic stress arising out of life style or social factors may trigger depression, the molecular basis of which has been attributed to alterations of brain chemicals like neurotrophins. Among these neurotrophins, brain-derived neurotrophic factor regulates many physiological functions in the brain, alteration of which has been well associated with the pathogenesis of depression. Stress-induced helplessness in rodents constitutes a well-defined model to investigate …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 2, Issue 2, 2012 · pp. 12–21 Read article
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Polymer Composite-Integrated Food Waste Management Across the Supply Chain: Quantification, Process Modelling, and Techno-Economic Valorization
Abstract: Food waste produced throughout the global food supply chain constitutes one of the most impactful forms of inefficiency within the current food production system, producing roughly 931 million tons per year and resulting in economic losses above $1 trillion worldwide each year. One aspect that has not been sufficiently studied systematically is how polymer composite materials, such as membrane separation systems, polymer-coated extraction equipment, fiber-reinforced polymer (FRP) biorefinery infrastructure, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 819–836 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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An Empirical Study of Hyperparameter Impact on Deep Learning Models for Cardamom Leaf Disease Classification
Abstract: Recent advancements in deep learning models like convolutional neural networks and self- attention mechanisms have achieved great success in the field of plant disease classification. This study investigates the efficacy of two pre-trained models, ConvNeXT-Tiny and Swin Transformer-Tiny, for leaf disease classification in cardamom using a publicly available dataset constituting three categories of leaves, namely Healthy, Colletotrichum Blight and Phyllosticta Leaf Spot. The effectiveness of the models highly depends on …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 48–60 Read article
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AI-Driven Prediction of Square-Hole Laser Trepanning Performance in AA7075/15%SiC/15% Glass Fiber Hybrid Composites Using Taguchi–ANOVA and Deep Neural Networks
Abstract: Hybrid AA7075 composites reinforced with 15% silicon carbide (SiC) and 15% glass fiber were fabricated via the stir casting technique to improve machining and structural performance. The addition of dual reinforcements into the aluminum matrix was aimed at enhancing hardness, thermal stability, and surface quality during non-traditional drilling operations. Square-hole drilling was performed using a laser trepanning process, and the key responses—hole size accuracy, surface roughness, and taper angle—were systematically …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1932–1943 Read article
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Strength Evaluation of Uniaxial Loaded Rectangular Confined RC Column under Static Load
Abstract: AbstractIS 456:2000 provides the guideline for RC column design and IS 13920:2016 provides the guideline for ductile design and detailing of RC columns to be provided in buildings to be constructed in seismic zones. The confining steel is provided to achieve the desired ductility in RC columns. The constitutive law under monotonic axial compression is proposed by researchers for confined concrete. It gives larger stress and strain values compared to …
Published in Journal of Structural Engineering and Management · Vol. 4, Issue 3, 2017 · pp. 7–12 Read article
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Utilizing Artificial Intelligence and Remote Sensing to Predict Flooding in Real-Time and Address Climate Resilience Policy in South Asia
Abstract: South Asia, a region characterized by hydro-climatic instability, faces an intensifying risk from devastating flooding, aggravated by human-induced climate change and intricate river basin interactions. Traditional flood prediction systems, based on limited in-situ data and resource-intensive physical models, have serious delays and resolution problems that make it harder to reduce disaster risk. The combined applications of Artificial Intelligence (AI) and high-resolution remote sensing (RS) constitute a paradigm shift in real-time …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 1, 2026 · pp. 45–61 Read article
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Calculating SAR Distribution and RF Electromagnetic Field Due To MRI Coil at Human Model
Abstract: AbstractMRI (magnetic resonance imaging) is an effective method for diagnosis of diseases. The MRI system is made of some important units including RF (radio frequency) devices [1]. The RF coil is one of the important parts in the RF unit. During the imaging, the RF coil radiates EM (electromagnetic) pulse to the human body and in response receives the NMR (nuclear magnetic resonance) signals emitted from the nuclei, which constitutes …
Published in Journal of Communication Engineering & Systems · Vol. 3, Issue 2, 2013 · pp. 1–8 Read article
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ML-Enhanced Self-Healing Fiber-Reinforced Polymer Composites with Embedded IoT Sensors for Damage Prediction
Abstract: Fiber-reinforced polymer (FRP) composites are widely used in aerospace and structural systems; nevertheless, the potential for microcracking and fatigue-induced performance degradation remains an obstacle with respect to improved service life. Traditional self-healing methods, while performing well on a chemical level, often lack real-time diagnostic awareness and adaptive control. To circumvent this, we developed a machine-learning augmented self-healing FRP composite, in which a DCPD–Grubbs catalytic matrix was combined with IoT sensor …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 188–208 Read article
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Numerical Modeling of Elastoviscoplastic Material Model in Strain Space
Abstract: Conventional material non-linear analysis works with stress-space plasticity. It uses yield function, loading-unloading criteria, and flow rule in terms of stress parameters. It shows ambiguity in loading-unloading criteria for softening materials. During such situations, an alternative strain-space formulation becomes quite useful to carry out analysis of such materials. The viscoplastic response of materials requires the time integration of system of non-linear first order differential equations. In viscoplasiticy, the constitutive equation …
Published in Journal of Experimental & Applied Mechanics · Vol. 9, Issue 1, 2018 · pp. 9–14 Read article
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Viscoelastic Behavior, Interfacial Mechanics, and Reliability of Polymer Interlayers in Laminated Glass Composites: A Comprehensive Review
Abstract: The laminated glass systems are regarded as hybrid polymer–glass composites where the viscoelastic behavior of polymer interlayers mostly controls mechanical response. These interlayers (polyvinyl butyral (PVB), ionoplast, ethylene-vinyl acetate (EVA), etc.) have time-, temperature- and rate-dependent properties which significantly affect shear transfer, energy dissipation, and fracture resistance. But the baseline polymer-relevant processes at the molecular and interfacial level are to a large extent unknown [1]. This review provides a materials-focused …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 258–268 Read article