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108 articles for “Thermal Prediction”
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Deep Learning-Based Thermal Prediction Models for Solid-State Electronic Devices
Abstract: The rapid advancement of solid-state electronic devices in high-performance computing, communication systems, automotive electronics, and renewable energy applications has significantly increased concerns related to thermal management and device reliability. Excessive heat generation in semiconductor devices adversely affects operational efficiency, switching performance, lifespan, and overall system stability. Traditional thermal prediction methods often require complex numerical computations and extensive simulation time, making them less suitable for real-time monitoring and adaptive control applications. …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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Inverse Model for Predicting Thermal Abnormality of the Transient Process Triggered by Defective Electronics Element
Abstract: The paper presents a model for predicting thermal abnormalities in Printed Circuit Boards (PCBs) by approximating the thermal process of electric elements with heating from point sources. Circuit board heat sources are defined as point and non-point. The point heat source is a small electronic heating element that can be approximated as having originated from one point on the circuit board. A non-point source is one with heat distributed over …
Published in International Journal of Energy and Thermal Applications · Vol. 3, Issue 2, 2025 · pp. 24–31 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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A Physics-Informed Graph Neural Network Framework for Real- Time Thermal-Aware Fault Prediction and Adaptive Power Optimization in Heterogeneous System-on-Chip Architectures
Abstract: Heterogeneous System-on-Chip (SoC) architectures are increasingly adopted in edge computing, artificial intelligence, autonomous systems, and high-performance embedded platforms due to their superior computational efficiency and flexibility. However, increasing integration density and workload diversity introduce severe thermal hotspots, accelerated device degradation, and unexpected hardware faults that adversely affect system reliability and energy efficiency. This study proposes a Physics-Informed Graph Neural Network (PI-GNN) framework for real-time thermal- aware fault prediction and adaptive …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 Read article
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Prediction and Comparative Analysis of Thermal Conductivity of Jatropha Oil-based Hybrid Nanofluid by Multivariable Regression and ANN
Abstract: In the present study, a multivariable regression (MR) and artificial neural network (ANN) method was used to predict the thermal conductivity of Jatropha oil-based ZnO-Ag hybrid nanofluid. Firstly, the ZnO-Ag hybrid nanoparticles were synthesized and mixed in the jatropha oil to prepare various nanofluids at different volume concentrations (F) ranging from 0.05 to 0.20%. The stability and thermal conductivity of the prepared nanofluids were investigated. Wide ranges of temperature and …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 32–39 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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Development of a Generative AI Model for Early Detection and Prevention of Electrical Faults in Thermal Power Plants
Abstract: Electrical faults in thermal power plants can lead to severe equipment damage, production downtime, and safety hazards if not detected in advance. This study presents the development of a Generative Artificial Intelligence (GenAI) model for the early detection and prevention of electrical faults using predictive analytics. The proposed framework integrates Generative Adversarial Networks (GANs) with deep learning (CNN) and machine learning algorithms (Random Forest, Logistic Regression) to enhance data diversity, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 1–10 Read article
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An Overview Mechatronics Systems Design of Modelica-Based Model Predictive Control Strategies for CO₂ Heat Pump Systems
Abstract: The growing adoption of renewable energy technologies poses challenges to energy supply stability, necessitating increased flexibility in energy demand. This paper introduces a Modelica-based Model Predictive Control (MPC) strategy aimed at keeping the supply water temperature within the range of 55°C to 75°C while minimizing energy consumption and electricity expenses throughout a year. A comprehensive, high-fidelity model representing a school building in Oslo, Norway, was developed using Modelica and exported …
Published in Journal of Mechatronics and Automation · Vol. 13, Issue 1, 2026 · pp. 15–27 Read article
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Enhancing Maintenance Decision-Making in Thermal Power Plants Using Generative AI-Based Fault Diagnosis
Abstract: The growing complexity of operation and power consumption of thermal power stations involve the need to have intelligent fault diagnosis systems that can be used to guarantee reliability and safety in operation. In this research, a Generative AI (GenAI)-based hybrid architecture of early fault detection and predictive maintenance is proposed to improve the decision-making process of the maintenance team. The data-driven analytic approach combines methods of data-driven analytics, Generative AI …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 25–33 Read article
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Simulation and Experimental Analysis of Abuse Testing for Prediction of Life Cycle for Lithium Ion Battery Cell and Pack Level
Abstract: Lithium-ion batteries play a crucial role in contemporary technology, serving as the power source for everything from consumer gadgets to electric vehicles. However, their safety and longevity are significant influenced by the reperformance under extreme conditions, commonly referred to as ab use testing .This paper explores the simulation and analysis of ab use testing and life cycle prediction for lithium-ion batteries at both the cell and pack levels. Abuse testing …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 2, Issue 2, 2024 · pp. 1–24 Read article
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Simulation and Analysis of Battery Pack Using the Multi Scale Multi-Domain Battery Model
Abstract: The creation of sophisticated simulation models has been made necessary by the need for reliable and effective battery packs in energy storage systems and electric vehicles. This study focuses on the simulation and analysis of battery packs using a multi-scale multi-domain battery model. The model enables a thorough knowledge of battery pack behavior across a range of operating situations by integrating the electricity, thermal, and mechanical domains. Multi-scale modeling bridges …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 2, 2024 · pp. 31–46 Read article
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Thermal Performance Analysis and Optimization of Pin-Fin Heat Sink Using CFD, Taguchi Method, and Machine Learning
Abstract: Efficient thermal management is essential for improving the performance and reliability of modern engineering systems and electronic devices. This study presents the design, simulation, and optimization of a pin-fin heat sink using SolidWorks for three-dimensional modeling and ANSYS for thermal and computational fluid dynamics (CFD) analysis. Four different pin-fin geometries, namely square, pentagon, octagon, and circular fins, are considered to evaluate their thermal performance under varying operating conditions. Aluminum is …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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Metamaterial-Based Thermal Shielding Structures for Reusable Hypersonic Space Transportation Systems
Abstract: The rapid development of reusable hypersonic space transportation systems has intensified the need for advanced thermal protection technologies capable of withstanding extreme aerodynamic heating conditions encountered during atmospheric re-entry and sustained hypersonic flight. Conventional thermal shielding materials often suffer from high structural weight, limited adaptability, thermal fatigue, and degradation under repeated thermal cycling. This study proposes a novel Metamaterial-Based Thermal Shielding Structure for Reusable Hypersonic Space Transportation Systems, integrating engineered …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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Multi-Scale Analysis of Polymer Based Energy Storage Systems for High Performance Battery Applications
Abstract: The energy storage systems based on polymers are becoming promising materials for the next generation of high performance batteries because of their excellent mechanical flexibility, improved safety, and favorable electrochemical properties. Even with computational tools in Python, polymer-based energy storage systems remain plagued by poor ionic conductivity, complicated electrochemical reactions and potential thermal runaway. Therefore, a multi-scale model is proposed to improve battery performance, thermal stability, reliability, and large-scale deployment …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1035–1048 Read article
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Hybrid Quantum-Classical Reinforcement Learning Enabled Thermal-Aware Electronic Design Automation Framework for Energy-Efficient Next-Generation VLSI Systems Applications
Abstract: Modern Very Large-Scale Integration (VLSI) systems are becoming more complicated, which has increased need for sophisticated Electronic Design Automation (EDA) frameworks that can concurrently optimise thermal behaviour, power consumption, and performance. This study proposes a Hybrid Quantum-Classical Reinforcement Learning (HQCRL) Enabled Thermal-Aware EDA Framework for next-generation energy- efficient VLSI systems. The proposed framework integrates quantum-inspired optimization techniques with classical reinforcement learning algorithms to address the challenges of placement, routing, and …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 2, 2026 Read article
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Detailed review on adsorption refrigeration system for different adsorbent/adsorbate working pair green composite materials – An environmental aspect
Abstract: Adsorption refrigeration is one of the greatest encouraging system for the refrigeration applications due to use of low grade energy. Present study deals with detailed review of adsorption refrigeration system. This article mainly concern with adsorption refrigeration arrangement by the utilization of most appropriate operational pairs namely activated carbon/methanol, silica gel/water and zeolite/water. Detail review carried out to predict thermal analysis and performance of the system. Mechanical properties of the …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 1–9 Read article
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Quasi-Static Thermal Stress Analysis in a Thin Circular Cylinder Due To Internal Heat Generation Under Transient Temperature Conditions
Abstract: This paper is concerned with inverse quasi-static thermal stress analysis in a thin circular cylinder due to internal heat generation under transient temperature conditions. The internal heat generation is modeled as a cylindrical surface heat source located in the annular region along the axial length of the cylinder. This source is placed concentrically inside the cylinder and begins releasing heat spontaneously at a specific point in time. The thin circular …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 2, 2025 · pp. 17–28 Read article
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Generative AI for Designing Sustainable Polymer Composites for Renewable Energy Applications
Abstract: Sustainable polymer composites are increasingly required for renewable energy devices, yet conventional trial-and-error formulation cannot efficiently balance performance, processability, recyclability, and environmental constraints. This study proposes a generative artificial intelligence framework for designing polymer composites for photovoltaic encapsulation, dielectric energy storage, polymer electrolytes, and thermal-management systems. Public polymer-property and composite datasets were curated from open databases and published supplementary records. Chemical descriptors, molecular fingerprints, polymer embeddings, processing variables, and sustainability …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Enhancement of Horizontal Jet Impingement Heat Transfer Analysis on Vertical Flat Plate
Abstract: This research investigates the heat transfer characteristics and heat flux distribution associated with parallel jet impingement on a vertical flat plate. A comprehensive computational fluid dynamics (CFD) analysis is carried out and systematically validated against available experimental data to ensure the accuracy and reliability of the numerical model. The jet length is maintained constant at 12 mm, while the jet-to-plate separation distance is varied at 6, 12, 18, and 24 …
Published in Journal of Experimental & Applied Mechanics · Vol. 17, Issue 1, 2026 · pp. 65–80 Read article
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The Role of AI in Modern Circuit Design and Simulation
Abstract: The integration of artificial intelligence (AI) in circuit design and simulation is revolutionizing the electronics industry by enabling faster, more efficient, and innovative design processes. This article explores the transformative role of AI in automating tasks traditionally reliant on manual expertise, such as schematic generation, component optimization, and fault detection. It highlights how machine learning algorithms and generative AI tools are improving design accuracy, reducing time-to-market, and enabling cost-effective prototyping. …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 1, 2025 · pp. 9–14 Read article