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171 articles for “simulation framework”
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An Integrated Simulation Framework for Predicting Dielectric Breakdown and Electrical Aging in Epoxy-Silica Composite Insulation Systems
Abstract: This paper provides a combined computation approach in forecasting the dielectric breakdown and electrical aging within epoxy-silica composite of insulation system. The approach will consist of a three-complementary methodology (a combination of computing electric field using the finite element analysis, estimation of the probability of failures or breakdowns using Weibull statistics, and prediction of degradation tendencies using artificial neural networks). The epoxy-silica composites are of 10-40 volumes fillers. The simulations …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 339–376 Read article
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Advanced Graph Editor and World Building Tool for Autonomous Vehicle Collision Avoidance Simulation
Abstract: The rise of autonomous vehicles (AVs) signifies a paradigm shift in transportation, but ensuring their safety is paramount. Collision avoidance stands out as a critical concern, demanding advanced simulation frameworks for rigorous testing. This paper introduces an integrated simulation framework explicitly designed for AV collision avoidance. It encompasses precise graph editing capabilities, realistic simulation environments, seamless neural network integration, and access to real-world data sources. By addressing these challenges, this …
Published in Journal of Automobile Engineering and Applications · Vol. 11, Issue 2, 2024 · pp. 16–24 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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Physics-Informed Generative and Tensor-Based Framework for DNA Sequence Simulation and Genomic Structure Discovery
Abstract: In this paper, we explore the intersection of artificial intelligence (AI) and mathematical physics to propose advanced methods for DNA sequence generation and analysis. Specifically, we investigate how physics-informed Generative Adversarial Networks (GANs) and tensor network representations can be harnessed to restructure DNA for applications in genetic science. The proposed methodology offers a unique integration of concepts of thermodynamic modeling with innovative GAN architecture in order to allow the creation …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Dielectric Breakdown and Electrical Aging of Insulating Polymer Materials in High Voltage Systems
Abstract: In this paper, a detailed analysis of dielectric breakdown and electrical aging behavior of high-voltage insulating polymer material has been proposed through sophisticated MATLAB simulation. The research involves electric field modeling, aging life prediction, partial discharge (PD) behavior and uncertainty modeling using Monte Carlo analysis. Electric field hotspots causing critical behavior, sensitivity of the lifespan to electric stress, and the stochastic PD build-up allow predictive diagnostics of the health of …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 173–187 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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Numerical Simulation of Crack Growth in Dynamic Loading Conditions
Abstract: Because it is crucial for forecasting structural failures in engineering applications, crack formation in materials under dynamic loading circumstances has become a crucial study topic. In this work, finite element methods (FEM) are used to numerically simulate fracture propagation in dynamic stress situations. The impact of loading rates, material characteristics, and crack geometries on crack growth patterns are assessed in a thorough parametric research. The work uses sophisticated computational methods …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 2, Issue 2, 2024 · pp. 30–34 Read article
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PI and Fuzzy Logic Controller Based Analysis of Load Frequency Control for Thermal-nuclear Hybrid Energy Systems
Abstract: In this paper a two-area system: area-1, which has a thermal power plant, and area-2, which contains a nuclear power plant. By combining these domains, two area thermal-nuclear systems are developed in the MATLAB Simulink framework. To ensure the quality of power generated and to feed the load, generation should be raised in tandem with the growth in load demand, or the network should be connected. Using various controllers, LFC …
Published in Trends in Electrical Engineering · Vol. 14, Issue 1, 2024 · pp. 1–9 Read article
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Collaborative Robotics and Smart Automation: Enhancing Human–Robot Synergy in Industry 5.0
Abstract: Industry 5.0 marks a paradigm shift from efficiency-centric automation to a human-centred, sustainable, and collaborative production environment . In this context, collaborative robots, commonly referred to as cobots, play a central role by enabling direct and safe interaction between humans and machines within shared workspaces. These systems are designed to support human operators by undertaking repetitive, precision-intensive, and physically demanding tasks, thereby allowing humans to focus on supervisory control, problem-solving, …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 22–29 Read article
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A New Computational Method for Dust and Gas Dynamics in Protoplanetary Discs
Abstract: The simultaneous evolution of dust and gas in protoplanetary discs regulates essential events in planet formation, such as dust accumulation, migration, and the initiation of gravitational instabilities. Nevertheless, precisely modelling this interaction continues to provide a significant computing problem owing to the extensive variety of spatial and temporal scales involved. In this study, we introduce an innovative computational framework for simulating dust-gas dynamics in protoplanetary discs, integrating a two-fluid hydrodynamical …
Published in International Journal of Universe · Vol. 1, Issue 2, 2025 · pp. 35–46 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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A Parametric Approach for Decision Making of Low-carbon Building Envelope Design
Abstract: Buildings are major contributors of total carbon emissions than all other categories globally. to reduce these emissions by some quantity must propose the better design before construction. For that, this study proposed a different combinations of building envelope analyzed. From that the best configuration can be implemented for construction to reduce emissions from building at different stages. Through the use of e-QUEST version 3.65, a total of some wall construction …
Published in Journal of Polymer & Composites · Vol. 11, Issue 5, 2023 · pp. 35–43 Read article
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Investigation to Enhance Performance of Finned U-Tube Shell-and-Tube Heat Exchangers Using Epoxy Based Polymer Composite Material
Abstract: Shell-and-tube heat exchangers remain indispensable in thermal engineering systems; however, conventional metallic configurations often face challenges related to corrosion, weight, and limited thermal optimization. In this study, a novel approach is proposed by integrating epoxy-based polymer composite materials with finned U-tube geometries to enhance thermo-hydraulic performance while addressing material limitations of traditional systems. The work focuses on the development and evaluation of a hybrid heat exchanger comprising a mild steel …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 618–633 Read article
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Intelligent Design Approaches in Microwave Engineering Using Machine Learning Techniques
Abstract: In microwave engineering, machine learning (ML) has become a potent technology allowing quicker design cycles, improved modelling accuracy, and automatic optimisation of complicated systems. Recent developments in the use of ML methods to microwave components and systems, including antennas, filters, and high-frequency circuits, are summarised in this study. In the framework of electromagnetic simulation, surrogate modelling, and parameter extraction, supervised and unsupervised learning algorithms are addressed. Moreover, the study looked …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 2, 2025 · pp. 31–38 Read article
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Electromechanical Modeling of Microscale Fluidic Systems with Electro Kinetic
Abstract: Due to their capacity to carry out complex fluid manipulations at the microscale, microfluidic systems have become more popular in a variety of applications. For a variety of industries, including biomedical diagnostics, chemical analysis, and environmental monitoring, achieving precise and effective fluid control is essential. The electromechanical modeling of microscale fluidic systems using electro kinetic actuation is the main topic of this research study. We propose a thorough framework for …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 1, Issue 1, 2023 · pp. 18–22 Read article
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Bridging the Gap Between Product Development and Entrepreneurship in Engineering Curriculum: A Framework-Based Approach Aligned with NEP 2020
Abstract: Despite advancements in technical education, Indian engineering graduates frequently enter the workforce lacking critical competencies in product development (PD) and entrepreneurship. This imbalance has drawn scrutiny from industry and policymakers alike, with national directives such as the National Education Policy (NEP 2020) emphasizing a shift toward “experiential, holistic, integrated and inquiry-driven” learning models. Similarly, the All-India Council for Technical Education (AICTE) has embedded innovation labs, internship mandates and entrepreneurship courses …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 87–100 Read article
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Mathematical Modelling of Semiconductor Device Physics: An Analytical Approach
Abstract: Semiconductor device physics forms the foundation of modern electronic and optoelectronic technologies. Mathematical modelling provides a rigorous framework for understanding, predicting, and optimizing the behavior of semiconductor devices by linking physical principles with device-level performance. This work presents an analytical approach to the mathematical modelling of semiconductor devices, emphasizing the derivation and interpretation of governing equations that describe charge transport and electrostatic behavior. The model is based on fundamental physical …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 36–42 Read article
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Framework-Based Optimization of Catalysis Efficiency through Reaction Pathway Engineering
Abstract: The rational design of heterogeneous catalysts through framework-based approaches has emerged as a transformative strategy for controlling reaction pathways and enhancing catalytic efficiency. This paper examines recent advances in the optimization of catalytic performance through engineered frameworks, including metal-organic frameworks (MOFs), zeolites, and related porous materials. By integrating computational methods with experimental validation, researchers have achieved unprecedented control overactive site architecture, reactant confinement, and elementary reaction steps. This work reviews …
Published in Emerging Trends in Chemical Engineering · Vol. 13, Issue 2, 2026 · pp. 88–99 Read article
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Machine Learning Assisted Optimization of Nanoscale MOSFET Parameters Using TCAD Simulation
Abstract: This paper presents a machine learning (ML) assisted framework for the multi-objective optimization of nanoscale bulk n-channel metal-oxide-semiconductor field-effect transistors (nMOSFETs) with a 10 nm physical gate length, high-k HfO₂ gate dielectric, and TiN metal gate. Technology computer-aided design (TCAD) simulations employing drift-diffusion transport, Shockley-Read-Hall recombination, Lombardi mobility degradation, and density- gradient quantum correction models are used to generate a parametric dataset of 2,400 device configurations spanning gate length (L), …
Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 10–19 Read article
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Advancements in Machine Learning: A Comprehensive Review of Algorithms, Applications, and Future Directions
Abstract: Gaining knowledge of Machine learning (ML)-guided format algorithms leverage predictive models to generate novel devices with optimized properties across several domains, which include drug discovery, fabric synthesis, and biomolecular engineering. Selecting an effective format set of policies consists of identifying appropriate hyperparameters, predictive models, and generative mechanisms to maximize format fulfilment. This study introduces an established method for set of policies requirements, ensuring that generated designs meet predefined fulfilment criteria, …
Published in Recent Trends in Programming languages · Vol. 12, Issue 2, 2025 · pp. 17–33 Read article