Search
10 articles for “electromechanical modeling”
-
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
-
Advancements in Electromechanical Modeling for Energy Harvesting and Actuators in Robotics and Design Engineering
Abstract: This article examines the expanding field of electromechanical modeling, highlighting the integration of energy harvesting, actuator behavior, and magnetic/electromagnetic analyses in the design and production of electromechanical systems. It discusses the application of the Galerkin method for modeling intricate vibrations and torque generation, with a particular focus on its use in actuators for robotics and induction motors. Significant advancements in energy harvesting methods, especially those utilizing mechanical vibrations, have led …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 2, 2024 · pp. 21–25 Read article
-
Dielectric Elastomers in Actuation and Energy Applications: Material Behavior and Design Strategies
Abstract: Dielectric elastomers (DEs), a class of electroactive polymers, have attracted significant attention for their ability to undergo large, reversible deformations under electric stimulation. This unique capability makes them highly suitable for a range of actuation and energy harvesting applications, especially in the emerging fields of soft robotics, flexible electronics, artificial muscles, and sustainable power generation systems. DEs offer compelling advantages such as low weight, mechanical flexibility, high energy density, and …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 13–18 Read article
-
Synergistic Integration of MEMS and Spintronics for Precision Data Analytics in Cheminformatics
Abstract: The transformational potential of merging spintronics and Micro-Electromechanical Systems (MEMS) technologies in cheminformatics is investigated in this work. Recent advancements in MEMS, particularly through the use of microbeam sensors and accelerometers, enhance the precision of data collection and processing, especially in biomedical applications such as drug delivery systems and chemical sensing. The synchronization of oscillations in MEMS devices leads to improved reliability and data accuracy, enabling the development of sophisticated …
Published in International Journal of Cheminformatics · Vol. 2, Issue 1, 2024 · pp. 20–26 Read article
-
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
-
DC Motor Control using Deep Reinforcement Learning for Enhanced Robustness and Precision
Abstract: DC motors remain the workhorse of industrial automation and mobile robotics, but achieving simultaneous high-speed transient response and negligible steady-state error under variable load conditions continues to challenge classical Proportional-Integral-Derivative (PID) controllers. These model-dependent systems often require extensive tuning and struggle to maintain optimal performance when confronted with parametric uncertainties, non-linear friction, or sudden voltage fluctuations. This study presents a novel, model-free control paradigm utilizing Deep Reinforcement Learning (DRL)—specifically, a …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 2, 2025 · pp. 22–29 Read article
-
A Study on Precision Blood Propulsion in Motor-Driven Artificial Hearts
Abstract: The development of biocompatible, energy-efficient pumping mechanisms is pivotal for advancing artificial heart (AH) technology. This study explores a motor-driven centrifugal pump designed to replicate the physiological dynamics of natural ventricles while mitigating complications associated with conventional axial and pulsatile systems. The proposed system employs a brushless DC motor with closed-loop control, integrated with pressure and flow sensors to modulate rotational speed (RPM) and generate biomimetic cardiac output. The suggested …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 53–59 Read article
-
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
-
Perturb and Observe Maximum Power Point Tracking Technique with PID Controller for a Wind Power System
Abstract: The wind power generation system has a significant growth worldwide over the past four decades. The wind power generation system has strong coupling and linear characteristics which makes it a complicated electromechanical system. The power control strategy has a higher impact on the overall performance as the wind power generation is operated at variable and random wind speed conditions. PID control is the most used control algorithm in industrial applications. …
Published in International Journal of Advanced Control and System Engineering · Vol. 1, Issue 1, 2023 · pp. 15–25 Read article
-
Optimization of Process Parameters for AISI 304 Using Micro-EDM Drilling Process Through Response Surface Method
Abstract: The increasing demand for micro-parts in high-tech products, such as micro-electromechanical systems (MEMS) applications and micro-electronic devices, has driven significant advancements in micromachining technologies. Among the various micromachining processes, the fabrication of accurate microholes and pins is critical for the performance and reliability of miniature components. Micro-hole drilling plays a vital role by enabling the production of deep holes with excellent straightness, roundness, and surface quality. It is widely used …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 1, 2025 · pp. 37–47 Read article