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1128 articles for “Modelling”
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Adaptive Production Scheduling in Multi-Machine Manufacturing Environments
Abstract: For manufacturing processes to meet evolving market demands, they must be executed in the most efficient manner while maintaining flexibility against unanticipated disruptions. Often, traditional scheduling methods overlook dynamic variability and real-time interruptions. An inverse scheduling framework for a multi-machine flowshop system is proposed in this research with the primary objective of makespan minimisation. Several issue situations are analysed to validate the algorithmic efficacy, and metaheuristic techniques are used to …
Published in International Journal of Manufacturing and Materials Processing · Vol. 12, Issue 1, 2026 · pp. 32–42 Read article
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An Integrated Computer-Aided Approach for Fixture Design and Assembly
Abstract: Fixtures play a crucial role in ensuring dimensional accuracy, productivity, and repeatability in modern manufacturing systems. With the increasing adoption of flexible and computer-integrated manufacturing, there is a growing need for systematic and automated fixture design methodologies. This work presents a computer-aided fixture design and assembly approach that integrates CAD-based modeling, modular fixturing concepts, and virtual assembly techniques. The proposed methodology covers the complete fixture development cycle, including workpiece analysis, …
Published in International Journal of Computer Aided Manufacturing · Vol. 12, Issue 1, 2026 · pp. 24–39 Read article
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Conversion of Heat Absorbed (Waste Heat) in a Building for Electricity Generation Using a Thermoelectric Generator
Abstract: This study investigates the feasibility of thermoelectric generators (TEGs) for recovering waste heat from building systems and converting it into electrical energy through the Seebeck effect. A journal-scale simulation framework integrating ANSYS thermal modeling with MATLAB/Simulink electrical analysis was developed to evaluate TEG deployment on building envelope surfaces at the Federal Polytechnic Nyak Shendam, Nigeria. Results demonstrate a proportional increase in electrical output with rising temperature gradients, confirming predictable thermoelectric …
Published in International Journal of Renewable Energy and its Commercialization · Vol. 12, Issue 1, 2026 · pp. 8–16 Read article
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A Study on Machine-Learning-Driven Insight into theThermal Behavior of Polymers and Composite Materials
Abstract: The thermal performance of polymeric and composite systems underpins their suitability for aerospace, electronics, and energy‑storage applications, yet reliable prediction of temperature‑dependent properties remains a formidable challenge. In this work we present a data‑driven framework that harnesses modern machine‑learning (ML) techniques to forecast key thermal metrics – glass‑transition temperature (Tg), melting point (Tm), thermal conductivity (k), and decomposition onset (Td) – from a chemically informed descriptor space. A curated database …
Published in International Journal of Polymer Science and Engineering · Vol. 12, Issue 1, 2026 · pp. 1–11 Read article
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Deep Reinforcement Learning-Based MPPT for PV Systems Under Partial Shading: A Hybrid Metaheuristic-Optimized Control Framework.
Abstract: Partial shade and quickly changing environmental conditions make Maximum Power Point Tracking (MPPT) in photovoltaic (PV) arrays particularly difficult. In these situations, traditional algorithms frequently fail to find the global optimum or experience sluggish convergence and steady-state oscillations. To obtain reliable, real-time MPPT under non-uniform irradiance, this research suggests a hybrid control architecture that combines a deep recurrent reinforcement learning (DRL) agent with metaheuristic-based parameter optimization and a digital-twin training …
Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 1, 2026 · pp. 35–46 Read article
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Intelligent Trajectories: Harnessing Artificial Intelligence for Next Generation Missile and Propellant Design
Abstract: The rapid evolution of artificial intelligence (AI) has unlocked transformative pathways for high-performance aerospace engineering, yet its integration into missile and propellant design remains nascent. This study investigates a hybrid AI-driven framework that unites physics-based modeling, data-centric learning, and multi-objective optimization to accelerate the conception, validation, and refinement of missile airframes and solid-propellant formulations. First, a physics-informed neural network (PINN) is trained on a curated database of historic missile geometries, …
Published in International Journal of Energetic Materials · Vol. 12, Issue 1, 2026 · pp. 20–26 Read article
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Green Hubs in Working Spaces: A Case of IndianHabitat Center
Abstract: The rapid urbanization of cities has turned them into high-pressure environments where environmental and social challenges are increased and need innovative design solutions. This paper considers the Indian Habitat Center in New Delhi as a model for biophilic design in working spaces focusing on how architectural and landscape features influence sensory experiences. IHC is integrated with natural light, extensive greenery and water features that provide aesthetic appeal and also help …
Published in International Journal of Sustainable Building Technology · Vol. 9, Issue 1, 2026 · pp. 1–12 Read article
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A Machine Learning-Based Framework for Urban Traffic Congestion Prediction and Control Using Intelligent Transportation Systems
Abstract: Abstract Traffic congestion remains a critical challenge in rapidly expanding urban areas, causing increased travel delays, excessive fuel consumption, environmental degradation, and economic inefficiencies. Traditional traffic management approaches are often insufficient, as they lack the ability to respond dynamically to continuously changing traffic conditions. This study proposes a novel data-driven framework for the prediction and management of traffic congestion using Intelligent Transportation Systems (ITS). The methodology integrates real-time and historical …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 1, 2026 · pp. 12–17 Read article
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A Machine Learning-Based Framework for Urban Traffic Congestion Prediction and Control Using Intelligent Transportation Systems
Abstract: Abstract Traffic congestion remains a critical challenge in rapidly expanding urban areas, causing increased travel delays, excessive fuel consumption, environmental degradation, and economic inefficiencies. Traditional traffic management approaches are often insufficient, as they lack the ability to respond dynamically to continuously changing traffic conditions. This study proposes a novel data-driven framework for the prediction and management of traffic congestion using Intelligent Transportation Systems (ITS). The methodology integrates real-time and historical …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 1, 2026 Read article
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Deep Reinforcement Learning-Based MPPT for PV Systems Under Partial Shading: A HybridMetaheuristic-Optimized Control Framework.
Abstract: Partial shade and quickly changing environmental conditions make Maximum Power Point Tracking (MPPT) in photovoltaic (PV) arrays particularly difficult. In these situations, traditional algorithms frequently fail to find the global optimum or experience sluggish convergence and steady-state oscillations. To obtain reliable, real-time MPPT under non-uniform irradiance, this research suggests a hybrid control architecture that combines a deep recurrent reinforcement learning (DRL) agent with metaheuristic-based parameter optimization and a digital-twin training …
Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 1, 2026 Read article
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Hybrid Machine Learning and Deep Learning approach for Adaptive congestion control in 5G/6G Network
Abstract: The rapid growth of data traffic, fueled by emerging applications such as autonomous systems, augmented reality (AR), virtual reality (VR), and the Internet of Things (IoT), poses major challenges for modern communication networks. With the rollout of 5G and the continuous transition to 6G, sophisticated congestion control techniques are needed to satisfy the demanding requirements of massive machine-type communication (mMTC), ultra-reliable low-latency communication (URLLC), and improved mobile broadband (eMBB). Conventional …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 11, Issue 2, 2025 · pp. 1–8 Read article
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AI-Optimized Reconfigurable Microstrip Bandpass Filters for DynamicSpectrum Access in 6G Networks
Abstract: The evolution toward sixth generation (6G) wireless networks introduces unprecedented demands on spectral efficiency, ultra-low latency, and real-time adaptability to dynamic radio environments. Central to this transformation is the requirement for intelligent, spectrum-agile radio front ends that can seamlessly operate across heterogeneous frequency bands. Dynamic Spectrum Access (DSA) addresses this challenge by enabling transceivers to autonomously detect, evaluate, and utilize the most suitable spectrum opportunities. The realization of DSA in …
Published in International Journal of Microwave Engineering and Technology · Vol. 11, Issue 2, 2025 · pp. 30–38 Read article
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The Principal role of Carbon nanostructures and quantum size effect onquantum Gravity wave and Space applications
Abstract: Carbon bears several important nanostructures including carbon quantum dots, Carbon nanotube,fullerene, and Graphene. These nanomaterials are sensitive and wide area of research innanotechnology era and nanomedicine. The possibility of sensing, simulating, and performingquantum computation at nanoscale makes carbon nanostructures quit suitable in quantumteleportation, space probe studies, and artificial breathing. This research is focused on the impactof such carbon based structure and quantum size effect on the quantum gravity waves. Thus, …
Published in International Journal of Nanomaterials and Nanostructures · Vol. 11, Issue 2, 2025 Read article
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Artificial Intelligence for the Art and Science of Separation: Optimizing Chemical Systems
Abstract: Chemical separation processes play a critical role across chemical manufacturing, energy production, pharmaceuticals, and environmental remediation, yet they remain among the most energy-intensive operations in modern industry. Recent advancements in artificial intelligence (AI) offer transformative opportunities to significantly improve the efficiency, selectivity, and sustainability of these systems by leveraging computational power and data-driven insight. This article reviews the emerging integration of machine learning, data-driven modeling, and advanced optimization algorithms with …
Published in International Journal of Chemical Separation Technology · Vol. 11, Issue 2, 2025 · pp. 1–7 Read article
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Review of Anomaly Detection Techniques in MANETs: AMachine Learning Approach to Intrusion Detection, Attack Prediction, and Routing Security
Abstract: Mobile Ad hoc Networks (MANETs) are decentralized, self-organizing networks that offer flexibility and scalability for a variety of applications. However, their dynamic topology and limited resources make them highly susceptible to security threats. Traditional security measures often struggle to address the complexities of evolving and sophisticated attacks within such networks. This paper reviews the role of machine learning (ML) techniques in enhancing anomaly detection capabilities in MANETs, focusing on their …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 2, 2026 · pp. 1–5 Read article
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Effect of Soil-Structure Interaction Effects and Mitigation Strategies for RC Structures - A Review
Abstract: Abstract – Soil-structure interaction (SSI) significantly influences the seismic performance of structures, necessitating advanced modeling and mitigation strategies to address dynamic responses across various structural configurations and soil types. This review synthesizes recent research on SSI effects in reinforced concrete (RC) frames, tall buildings, and subway stations, employing nonlinear finite element modeling, shaking table tests, and probabilistic fragility analyses. Studies highlight that SSI alters natural frequencies, damping, and seismic demands, …
Published in International Journal of Geological and Geotechnical Engineering · Vol. 11, Issue 2, 2025 · pp. 36–42 Read article
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Comparative Analysis of Equity Considerations in Heritage Preservation Policies Across Different Cultural Contexts: A Case Study with Indian Context
Abstract: This paper offers a comprehensive and multi-layered analysis of how equity principles are robustly integrated into heritage preservation policies across diverse international and national cultural contexts, with a focused and detailed emphasis on India. The core objective is to move significantly beyond conventional, site-focused conservation paradigms to meticulously assess the extent to which existing heritage frameworks actively address fundamental issues of social justice, inclusive governance, and the equitable distribution of …
Published in International Journal of Architectural Heritage · Vol. 8, Issue 2, 2025 · pp. 1–6 Read article
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A Review of Real-Time Human Detection
Abstract: The real-time human detection and counting system leverages deep learning and computer vision to detect individuals, classify gender, and estimate age from live video feeds or CCTV footage. Implemented using flask as a lightweight web framework, the system manages user authentication, detection control, and real-time result display. A Python-based detection script operates asynchronously, ensuring smooth execution, while results – including counts of males, females, and total individuals – are stored …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 2, 2025 · pp. 29–39 Read article
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Performance Evaluation of 45kW Low Temperature Proton Exchange Membrane Fuel Cell System Using Simulation Techniques
Abstract: AbstractThe Low-Temperature Proton Exchange Membrane Fuel Cell (LT-PEMFC) has gained prominence as a promising solution for clean and efficient energy generation, particularly in the automotive industry, where stringent emission norms and sustainability goals are driving innovation. LT-PEMFC systems offer several inherent advantages, including high energy conversion efficiency, low operational temperature, rapid start-up capability, and compatibility with hydrogen as a renewable fuel source. These characteristics make them attractive for commercial vehicle …
Published in International Journal of I.C. Engines and Gas Turbines · Vol. 11, Issue 2, 2025 · pp. 25–39 Read article
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Numerical Investigation of Hybrid Composite Armors: Cost-Effective Solutions for Ballistic ProtectionUsing ANSYS
Abstract: This study presents a detailed numerical investigation of hybrid composite armors as a cost-effective and lightweight solution for ballistic protection. With increasing the demand of protective systems that ensure high mobility with light weight and cost-effective armor without compromising safety. Traditional steel armor has already proven to be a reliable protection system but the main problem is its mobility. To address this issue, the work focuses on composite material as …
Published in International Journal of Structural Mechanics and Finite Elements · Vol. 11, Issue 2, 2025 · pp. 1–11 Read article