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142 articles for “Hybrid machining”
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Role of Machine Learning Principles for Efficient Nuclear Fuel Management and Design
Abstract: The introduction of machine learning (ML) and evolutionary computation methods in addressing complex nuclear fuel management challenges has brought a significant positive change in the domain of nuclear fuel management. Key applications include fuel assembly design optimization, core loading pattern determination, burnup calculation acceleration, fuel performance prediction, and spent fuel characterization. The analysis reveals significant improvements in computational efficiency, prediction accuracy, and optimization capabilities when ML techniques are properly integrated …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 22–33 Read article
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Optimization of Surface Roughness and Material Removal Rate in Turning of Al-6061 Using Taguchi Methodology, Fuzzy Logic, and Measurement System Analysis
Abstract: The optimization of machining parameters please a crucial role in improving product quality and productivity in manufacturing processes. This study focuses on the turning of aluminium 6061 alloy, aiming to optimize two key performance measures: Surface Roughness and Material Removal Rate. An integrated approach combining to Taguchi methodology, fuzzy logic and measurement system analysis (MSA) is proposed to achieve this objective. Taguchi design of experiments using and L9 orthogonal array …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 Read article
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Polymer Nanocomposites and Functional Materials for Lithium-Ion Battery Supercapacitor Hybrid Energy Storage Systems: Materials, Interfaces, and Performance Perspectives
Abstract: The growing need for high-performance energy storage solutions in electric vehicles, renewable energy applications, portable electronics, and other sectors has accelerated research and development efforts in Lithium-Ion Battery–Supercapacitor Hybrid Energy Storage Systems (HESS). By combining the high energy density of lithium-ion batteries with the high power density and fast charge/discharge characteristics of supercapacitors, HESS offers a promising approach to meeting diverse energy storage requirements. Nevertheless, several critical challenges remain that …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 96–113 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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Axial Compression Behavior of Aluminum (Al), Glass/Epoxy (GFRP) and Hybrid Al-GFRP Crash-box: An Experimental and Digital Image Correlation Approach
Abstract: The study aims to understand the axial compression characteristics and fracture of cylindrical Aluminum (Al), Glass/epoxy (GFRP) composite and Hybrid Al-GFRP crash-boxes. The hollow Al tubes are fabricated by rolling and bonding a thin aluminum sheet followed by rivet joints. The GFRP samples are manufactured using the wet-hand layup technique followed by the vacuum bagging method. Hybrid samples are manufactured by covering GFRP tubes with aluminum sheets on the outer …
Published in Journal of Polymer & Composites · Vol. 12, Issue 1, 2024 · pp. 304–313 Read article
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A Review on Integrated Acoustic Emission and Piezoelectric Sensing for Real-Time Damage Characterization of Polymer Composite-Enhanced Concrete: Advances, Challenges, and Future Perspective
Abstract: Polymer composite reinforced concrete has been identified as an efficient material system that can enhance the mechanical properties, durability, and service life of modern structures. The combination of fiber reinforced polymers (FRPs), polymer modifiers, and hybrid composite reinforcements increases structural effectiveness. However, these systems are still vulnerable to damage processes, including matrix cracking, fiber breaking, interfacial debonding, and delamination. Thus, there is a need for structural health monitoring (SHM) strategies …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 930–939 Read article
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Advanced Lithium-Ion Battery Prognostics: A Comprehensive Review of Machine Learning Approaches for Remaining Useful Life Prediction
Abstract: The lithium-ion battery (LIB), as one of the main sources for portable power systems, has been increasingly popular owing to its widespread applications in electric vehicles, consumer electronics, aerospace and renewable energy. Despite their advantages in high energy density and long cycle life, LIBs suffer from degradation over time of aging and cycling, resulting in loss of performance, safety issues, and economic bottlenecks. Predicting their Remaining Useful Life (RUL) is …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 2, 2025 · pp. 12–27 Read article
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Environmental Impact Assessment of Ocean Energy Converters Using Quantum Machine Learning
Abstract: The accelerating deployment of ocean energy converters (OECs) across tidal, wave, osmotic, and thermal domains necessitates rigorous, data-intensive environmental impact assessment (EIA) frameworks capable of modelling multi-stressor marine ecosystems in real time. Classical machine learning approaches, while operationally mature, encounter scalability bottlenecks and feature correlation limitations when applied to the high-dimensional, non-linear datasets characteristic of offshore monitoring networks. This paper presents a comprehensive quantum machine learning (QML) framework for the …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 16, Issue 1, 2026 · pp. 22–31 Read article
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Renewable Solar Energy Prediction in India : 2025-2030
Abstract: As India endeavors to realize its objective of achieving 500 GW of renewable energy capacity by the year 2030, the precise forecasting of solar power generation is rendered increasingly essential. This scholarly article conducts a comprehensive review of the utilization of machine learning (ML) methodologies in the prediction of solar energy across diverse Indian states, underscoring their potential to address the complexities associated with the variability of solar irradiance. Conventional …
Published in Journal of Power Electronics and Power Systems · Vol. 14, Issue 3, 2024 · pp. 41–46 Read article
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Enhancing Delamination Resistance in CFRP Composites through surface Functionalization of Woven carbon Fiber by CuO Nanostructures
Abstract: In order to produce a nanostructured interphase that improves the interfacial interaction with an epoxy resin matrix, copper oxide (CuO) nanostructures were hydrothermally formed onto woven carbon fibers (WCF). Hexagonal CuO nanorods were created using a two-step, seed-assisted solvothermal technique on plain woven carbon fiber. This study investigates the effects of surface modification of carbon fibers by the formation of CuO nanostructures using a hydrothermal technique on the mechanical properties …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 589–602 Read article
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Multifunctional Materials for Electro-Mechanical Applications: Synergistic Integration of Strength and Conductivity
Abstract: The integration of mechanical strength and electrical conductivity within a single material system has emerged as a critical requirement in the development of next-generation multifunctional materials. These materials are increasingly sought after in fields such as aerospace, flexible electronics, energy storage, and structural health monitoring, where the traditional separation of structural and functional materials leads to inefficiencies in weight, space, and overall performance. The convergence of these properties enables compact …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 1–6 Read article
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Thin Film Technology in Sensor Manufacturing – A Technical Discussion
Abstract: Thin‑film technology has become the cornerstone of modern sensor manufacturing, enabling the convergence of miniaturisation, multifunctionality, and cost‑effective mass production. This paper surveys the latest advances in deposition techniques—ranging from magnetron sputtering and chemical vapour deposition to atomic‑layer deposition (ALD) and ink‑jet‑printed sol‑gel processes—and examines how their unique material‑control capabilities translate into performance gains across the sensor spectrum (chemical, physical, and bio‑sensing). By integrating nanoscale thickness control (≤ 10 nm) …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 13, Issue 1, 2026 · pp. 48–58 Read article
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Multi-functional UAV for Disaster Response and Management
Abstract: Unmanned Aerial Vehicles (UAVs), commonly known as drones, have become integral across diverse fields such as agriculture, surveillance, and defense, with expanding roles in critical operations like search and rescue and post-disaster management. Despite their versatility, current UAVs encounter challenges in disaster response due to limitations in flight time, costs, and accuracy, particularly in dynamic weather conditions. The UAV is equipped with features essential for disaster site surveillance, human detection, …
Published in Journal of Aerospace Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 1–6 Read article
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AI-Based Threat Detection in Cloud Platforms
Abstract: This research work delves into the transformative role AI has come to assume for enhanced threat detection in the cloud ecosystem. The conventional security frameworks, which form the basis for many architectures, are several steps behind actualizing the rapidly evolving cyber threat landscape, exposing critical weaknesses in the areas of accuracy, adaptability, and speed of response. Initially, the study sets forth the problems with the old-school approaches to threat detection …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 01–10 Read article
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Overview AI-Driven Antenna Technologies and Privacy- Preserving Methods for Next-Generation 6G Wireless Systems
Abstract: The next generation of wireless communications, 6G, will be built on the convergence of artificial intelligence (AI) and advanced antenna systems. AI-driven antennas are poised to address the unprecedented requirements for data rate, reliability, adaptability, and ubiquity in future networks. An overview of current advancements in AI-enabled antenna systems for 6G networks is provided in this study. From traditional base station deployments to distributed, cell-free, and user-centric frameworks, it examines …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 1, 2026 · pp. 28–34 Read article
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Intelligent Earth: AI As A Catalyst For Climate Action
Abstract: Artificial Intelligence (AI) is assuming an increasingly influential role in climate science, providing advanced tools capable of interpreting vast, complex, and multi-dimensional environmental datasets. Traditional climate modeling approaches, while grounded in physical principles, frequently struggle to deliver high-resolution, real-time, and region-specific forecasts because of heavy computational demands, incomplete observations, and uncertainties in representing small -- scale processes. Artificial intelligence (AI) techniques, especially machine learning and deep learning, provide strong substitutes …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 48–52 Read article
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ML-Enhanced Smart Sensing Framework for IoT- Based Structural Health Monitoring Using Conductive Polymer Composites
Abstract: The growing demand for intelligent structural health monitoring (SHM) in dynamic infrastructures necessitates flexible sensing systems that are not only mechanically robust but also capable of real-time interpretation. Conventional SHM frameworks often rely on brittle sensor configurations and cloud-dependent processing pipelines, which suffer from latency, limited durability, and poor adaptability under variable loading conditions. Despite recent advances in composite materials and machine learning, current approaches lack a unified framework that …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 348–369 Read article
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Wear and Tribological Characteristics of Novel Metal Matrix Composites
Abstract: The development of advanced metal matrix composites (MMCs) with enhanced tribological performance has become increasingly important due to the premature failure of critical engineering components operating under severe wear conditions in automotive, aerospace, marine, defense, and power generation systems. Conventional composites such as Copper–Alumina and Aluminium–Silicon Carbide have demonstrated improved mechanical and wear characteristics; however, their widespread application is often limited by issues including particle agglomeration, non-uniform reinforcement distribution, porosity …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1326–1346 Read article
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Comparative Evaluation of Fiber-Reinforced Composite and Elastic Fiber Posts in Reinforcing Peri-Cervical Dentin: an In-Vitro Study
Abstract: This study evaluates the fracture resistance of short-fiber reinforced composite and elastic fiber posts compared to conventional hybrid composites in reinforcing peri-cervical dentin of endodontically treated teeth. Methods: The crowns of thirty single-canal mandibular premolars were resected to achieve a dimension of 4mm from 1mm below the highest point of the proximal cervical line. In Group 1, teeth underwent endodontic treatment with gutta-percha filled up to the cement-enamel junction (CEJ) …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 143–149 Read article
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Machine Learning Pipelines: A Survey on Automation, Scalability, and Deployment Strategies
Abstract: Machine learning (ML) has become a critical enabler of intelligent applications across domains, requiring robust, efficient, and scalable deployment workflows. This review paper provides an in-depth overview of machine learning pipelines, emphasizing three key dimensions: automation, scalability, and deployment methodologies. It begins by exploring automation techniques that reduce manual effort in data ingestion, preprocessing, model selection, and hyperparameter tuning. Tools such as AutoML, TFX, and workflow orchestration platforms are examined …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 17–28 Read article