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Actuated Rotational Adaptive Optics in Shaping the Next Generation of Optical Systems: An In-Depth Analysis

Arabian Journal for Science and engineering 2025年 1-33页

作者： Alzaydi, Ammar Sarhan, Ahmed A. D. Khalifa, Mohamed Department of Mechanical Engineering King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Center for Biosystems and Machines King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Centre for Intelligent Manufacturing and Robotics King Fahd University of Petroleum and Minerals Dhahran 31261 Saudi Arabia Department of Mechanical and Aerospace Engineering Carleton University Ottawa K1S-5B6 ON Canada

Actuated rotational adaptive optics has emerged as a pivotal advancement in the realm of optical engineering, particularly enhancing the capability to correct complex wavefront aberrations more effectively than traditional adaptive optics systems. This study provides a comprehensive examination of these advancements through detailed theoretical modeling complemented by empirical analyses across various practical applications, including astronomical observation and medical imaging. Our findings indicate that actuated rotational adaptive optics significantly enhances image resolution and adaptability of systems under dynamic operational conditions, leading to improved performance in both typical and extreme environmental scenarios. These results underscore the transformative potential of this technology, suggesting extensive applications that could redefine the boundaries of current optical systems and offer substantial improvements in fields requiring high-precision optical corrections. © King Fahd University of Petroleum & Minerals 2025.

关键词： Actuated rotational adaptive optics (ARAO) Astronomical observations Medical imaging Optical distortions Real-time adjustments Telecommunications

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ANN-based analysis of thin film Maxwell fluid dynamics with electro-osmotic and nonlinear thermal effects

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Alexandria engineering Journal 2025年 127卷 392-410页

作者： Din, Irfan Saif Ud Siddique, Imran Zahid, Zohaib Nadeem, Muhammad Islam, S. Department of Mathematics University of Management and Technology Lahore54770 Pakistan Department of Mathematics University of Sargodha Sargodha40100 Pakistan Mathematics in Applied Sciences and Engineering Research Group Scientific Research Center Al-Ayen University Nasiriyah64001 Iraq Federal University of Technology Paran UTFPR Mechanical Engineering Department DAMEC Postgraduate Program in Mechanical and Materials Engineering PPGEM Research Center for Rheology and Non-Newtonian Fluids CERNN R. Deputado Heitor Alencar Furtado 5000 - Bloco N - Ecoville PR Curitiba81280-340 Brazil Department of Mechanical Engineering Prince Mohammad Bin Fahd University P.O Box 1664 Al Khobar31952 Saudi Arabia

An intelligent Levenberg-Marquardt Technique (LMT) with artificial neural network (ANN) backpropagation (BP) has been used to analyze the thermal heat and mass transfer of unsteady magnetohydrodynamics (MHD) thin film Maxwell fluid flow in a porous inclined sheet with an emphasis on the influence of electro-osmosis. The activation energy, chemical reaction, mixed convection, melting heat, joule heating, nonlinear thermal radiation, variable thermal conductivity and thermal source/sink effect are taken into account for transport expressions. Appropriate similarity transformations were used to translate partial differential equations (PDEs) into ordinary differential equations (ODEs). After that, the built-in MATLAB BVP4C method was used for a data set assessed using the LMT-ANN strategy to solve these ODEs. The physical significance of the designed parameters is thoroughly discussed in both tabular and graphical form. The observed R-squared value is 1, and the mean square error up to 10−15 demonstrates the LMT-ANN's precise and accurate computing capability. The model's validity is also confirmed by the strong agreement between the obtained predicted findings and numerical results, which shows a high degree of accuracy within the range of 10−8 to 10−11. It was revealed that radiative heat considerably increases surface heat energy through accumulation, improving heat transfer qualities, whereas fluid temperature is raised by Joule dissipation, variable thermal conductivity, and heat source. Electro-osmosis and magnetic fields reduce fluid velocity by generating opposing forces that resist the flow. This problem works best in microscale fluid transport systems and drilling operations, where magnetic and electro-osmotic control are crucial. These systems include micro-electromechanical systems, lab-on-a-chip devices, porous geological formations, and thin film coating technologies. © 2025 The Authors

关键词： Activation energy

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Advancing Acoustic Droplet Vaporization for Tissue Characterization Using Quantitative Ultrasound and Transfer Learning

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IEEE Transactions on Biomedical engineering 2025年第6期72卷 1897-1908页

作者： Kaushik, Anuj Fabiilli, Mario L. Myers, Daniel D. Fowlkes, J. Brian Aliabouzar, Mitra University of Michigan Department of Radiology Ann ArborMI48109 United States University of Michigan Department of Radiology Biomedical Engineering and Applied Physics Program Ann ArborMI48109 United States University of Michigan Department of Surgery Ann ArborMI48109 United States Ann Arbor MI48109 United States University of Michigan Department of Radiology and Mechanical Engineering Ann ArborMI48105 United States

Acoustic droplet vaporization (ADV) is an emerging technique with expanding applications in biomedical ultrasound. ADV-generated bubbles can function as microscale probes that provide insights into the mechanical properties of their surrounding microenvironment. This study investigated the acoustic and imaging characteristics of phase-shift nanodroplets in fibrin-based, tissue-mimicking hydrogels using passive cavitation detection and active imaging techniques, including B-mode and contrast-enhanced ultrasound. The findings demonstrated that the backscattered signal intensities and pronounced nonlinear acoustic responses, including subharmonic and higher harmonic frequencies, of ADV-generated bubbles correlated inversely with fibrin density. Additionally, we quantified the mean echo intensity, bubble cloud area, and second-order texture features of the generated ADV bubbles across varying fibrin densities. ADV bubbles in softer hydrogels displayed significantly higher mean echo intensities, larger bubble cloud areas, and more heterogeneous textures. In contrast, texture uniformity, characterized by variance, homogeneity, and energy, correlated directly with fibrin density. Furthermore, we incorporated transfer learning with convolutional neural networks, adapting AlexNet into two specialized models for differentiating fibrin hydrogels. The integration of deep learning techniques with ADV offers great potential, paving the way for future advancements in biomedical diagnostics. © 1964-2012 IEEE.

关键词： Ultrasonic imaging

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Intra-Operative 3-D Modeling of Side Branch Vessels for IVUS-Guided Catheter Navigation

IEEE Transactions on Medical Robotics and Bionics

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IEEE Transactions on Medical robotics and Bionics 2025年第2期7卷 443-454页

作者： Farola Barata, Beatriz Beckers, Wim-Alexander Borghesan, Gianni Dall'Alba, Diego Bennett, Johan McCutcheon, Keir Fiorini, Paolo Vander Sloten, Jos Vander Poorten, Emmanuel KU Leuven Robot-Assisted Surgery Group Department of Mechanical Engineering Leuven3001 Belgium University of Verona Altair Robotics Laboratory Department of Computer Science Verona Verona37129 Italy Flanders Make KU Leuven Leuven3001 Belgium KU Leuven Department of Cardiovascular Sciences Leuven3000 Belgium UZ Leuven Department of Cardiovascular Diseases Leuven3000 Belgium

Despite continuous advances in three-dimensional (3D) fusion imaging, two-dimensional (2D) X-ray-based fluoroscopy is still the gold standard intra-operative image guidance tool in endovascular interventions. The adoption of robotic technology offers the potential to bring intra-operative radiation exposure down to a minimum, or even eliminate it. Non ionizing approaches, such as Intravascular Ultrasound (IVUS), are progressively explored as standalone or fluoroscopy-adjunct techniques for 3D vasculature reconstruction. We have previously demonstrated the feasibility of real-time 3D Main Vessel (MV) modeling from the fusion of IVUS and EM pose data obtained from sensors embedded at the tip of a robotic catheter. This paper proposes to advance MV modeling towards a comprehensive radiation-free 3D guidance framework by means of intra operative Side Branch (SB) detection and modeling. Two models are proposed to approximate the geometry of SB vessel ostia: a sphere and a cylinder. An Unscented Kalman Filter (UKF) recursively estimates the state of these models considering the MV model, while the catheters navigates through the vessel. In silico and in vitro validation results show the potential clinical value of the proposed strategy for facilitating safer robotic catheter steering. © 2018 IEEE.

关键词： Medical robotics

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Raise Damping in Electro-Hydraulic Systems with Observed Pressure

Raise Damping in Electro-Hydraulic Systems with Observed Pre...

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Mechatronics and robotics engineering (ICMRE), International Conference on

作者： Xieli Zhang Damiano Padovani Department of Mechanical Engineering (Robotics) Guangdong Technion-Israel Institute of Technology Shantou China

ISBN: (数字)9798331509293

ISBN: (纸本)9798331509309

The growing interest in energy efficiency points the research for hydraulic systems to electro-hydraulic drives, specifically hydraulic actuators directly coupled to pumps driven by electric motors. This design eliminates functional energy dissipations and enables energy recovery but leads to inherently low damping. The consequence is that harmful payload oscillations deteriorate the position control's accuracy of the actuator. Therefore, raising the drive damping via pressure feedback is crucial and requires knowledge of the pressure in both actuator chambers. This paper investigates using pressure observation to that end (i.e., a virtual pressure sensor implemented via software replaces two physical pressure transducers). High-passed pressure feedback is introduced using a model-based design for setting up closed-loop position control. This approach is simulated numerically on a heavy-duty robotic manipulator. The results confirm that the payload oscillations are significantly reduced without affecting position tracking.

关键词： Damping Transducers Soft sensors Position control Observers Robot sensing systems Manipulators Sensor systems Oscillators Payloads

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Digital Twin-Based Smart Manufacturing: Dynamic Line Reconfiguration for Disturbance Handling

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IEEE Transactions on Automation Science and engineering 2025年 22卷 14892-14905页

作者： Fu, Bo Bi, Mingjie Umeda, Shota Nakano, Takahiro Nonaka, Youichi Zhou, Quan Matsui, Takaharu Tilbury, Dawn M. Barton, Kira Department of Robotics University of Michigan Ann ArborMI48109 United States Amazon Robotics North ReadingMA01864 United States Beijing Institute for General Artificial Intelligence Beijing100080 China Hitachi Ltd. Tokyo100-8280 Japan Hitachi America Ltd. Farmington HillsMI48355 United States Department of Mechanical Engineering University of Michigan Ann ArborMI48109 United States

The increasing complexity of modern manufacturing, coupled with demand fluctuation, supply chain uncertainties, and product customization, underscores the need for manufacturing systems that can flexibly update their configurations and swiftly adapt to disturbances. However, current research falls short in providing a holistic reconfigurable manufacturing framework that seamlessly monitors system disturbances, optimizes alternative line configurations based on machine capabilities, and automates simulation evaluation for swift adaptations. This paper presents a dynamic manufacturing line reconfiguration framework to handle disturbances that result in operation time changes. The framework incorporates a system process digital twin for monitoring disturbances and triggering reconfigurations, a capability-based ontology model capturing available agent and resource options, a configuration optimizer generating optimal line configurations, and a simulation generation program initializing simulation setups and evaluating line configurations at approximately 400x real-time speed. A case study of a battery production line has been conducted to evaluate the proposed framework. In two implemented disturbance scenarios, the framework successfully recovers system throughput with limited resources, preventing the 26% and 63% throughput drops that would have occurred without a reconfiguration plan. The reconfiguration optimizer efficiently finds optimal solutions, taking an average of 0.03 seconds to find a reconfiguration plan for a manufacturing line with 51 operations and 40 available agents across 8 agent types. Note to Practitioners - This research is motivated by the need for an advanced framework that automates the reconfiguration of manufacturing lines in response to increasing disturbances within dynamic production environments. Existing approaches lack a holistic framework that automates disturbance monitoring, data management, line structure optimization, and pre-imple

关键词： Recovery

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Self SOC Estimation for Second-Life Lithium-Ion Batteries

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IEEE Access 2025年 13卷 75033-75042页

作者： Gotz, Joelton Deonei Viana, Emilson Ribeiro Galvão, José Rodolfo Corrêa, Fernanda Cristina Borsato, Milton Badin, Alceu André Paraná Curitiba81280-340 Brazil Department of Computer Science Paraná Curitiba80215-901 Brazil Department of Physics Paraná Curitiba81280-340 Brazil Paraná Ponta Grossa80230-901 Brazil Postgraduate Program in Mechanical and Materials Engineering Paraná Curitiba81280-340 Brazil

Lithium-ion batteries (LIB) are the mainstream technology for energy storage in several industrial segments, such as mobility and stationary systems for solar, wind, or other alternative energy source. This technology has a long lifetime, low self-discharge, high capacity and density, and can store energy longer. Despite that, LIB is suitable to supply power for electric mobility if its state of health (SOH) is higher than 80%. Then, an alternative for batteries with SOH below that is recycling or second-life batteries (SLB). The first is expensive and complex;only some companies retain the technology. Still, the SLB can be an excellent solution to maintaining LIBs in operation for slow vehicles or stationary systems. However, SLB requires intelligent battery management systems (BMS) because the packs are composed of cells with different characteristics, which makes the operation more difficult. This work presents a system consisting of two Machine Learning (ML) layers to automatically estimate the state of charge (SOC) of SLB independent of the battery’s capacity or age. In the first phase, a Random Forest (RF) model was built and trained to discover the curve capacity of different SLB characteristics and capacities. After the capacity curve selection, in the second phase, a new RF model was built and trained for each capacity curve to make SOC inferences of the batteries. The discharge data curve of one hundred batteries was used for the development, whereas eighteen were used for the training and eighty-two for tests. The results indicated a root square mean error (RSME) below 45 mAh for the capacity estimation (phase 1), and an RSME below 0.87% was found in the second phase for the SOC estimation. Finally, the capacity and SOC models have been inserted in a Raspberry system to measure the main parameters of SLB (voltage and current) and make inferences in real time independent of the cell’s age. The results showed an RSME below 100 mAh for the first layer and be

关键词： Lithium-ion batteries

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Analysis of VSC-HVDC System in the Asynchronously Operating Grids During AC Line Faults

Analysis of VSC-HVDC System in the Asynchronously Operating ...

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Smart and Sustainable Developments in Electrical engineering (SSDEE), IEEE International Conference on

作者： Ravi Shankar Tiwari Ashish Kumar Sinha Prashant Kumar Department of Electrical Engineering GLA University Mathura India Department of Mechanical Robotics and Energy Engineering Dongguk University Seoul Republic of Korea

ISBN: (数字)9798331542108

ISBN: (纸本)9798331542115

The growing energy demand and ruler electrification accelerates the integration of synchronously and asynchronously operating grids. Generation based on hydro, wind or solar may operate at a frequency slightly different than the national grid due to its intermittent nature and operational constraints. It is important to integrate the generation of various sources to improve grid reliability. Wind energy farms are usually integrated into the grid using VSC (voltage source converters)-HVDC systems. Faults on either side of the HVDC link may create operational and stability issues for interconnecting the HVDC link. The fault ride-through is the ability of the VSC-HVDC system to remain connected with the grid during faults. This paper explores and analyzes the fault ride-through ability of $\mathbf{a}\pm \mathbf{100}\ \mathbf{kV}$ , 200 MW two-level VSC-HVDC to maintain interconnections between grids, especially during the presence of intermittent sources like wind farms at one end of the VSC-HVDC system.

关键词： Renewable energy sources Wind energy HVDC transmission Power system stability Wind farms Stability analysis Power conversion Reliability Voltage control Sustainable development

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Towards Local Minima-free Robotic Navigation: Model Predictive Path Integral Control via Repulsive Potential Augmentation

Towards Local Minima-free Robotic Navigation: Model Predicti...

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IEEE/SICE International Symposium on System Integration

作者： Takahiro Fuke Masafumi Endo Kohei Honda Genya Ishigami Department of Mechanical Engineering Space Robotics Group Keio University Yokohama Japan Department of Mechanical Systems Engineering Mobility System Group Nagoya University Nagoya Japan

ISBN: (数字)9798331531614

ISBN: (纸本)9798331531621

Model-based control is a crucial component of robotic navigation. However, it often struggles with entrapment in local minima due to its inherent nature as a finite, myopic optimization procedure. Previous studies have addressed this issue but sacrificed either solution quality due to their reactive nature or computational efficiency in generating explicit paths for proactive guidance. To this end, we propose a motion planning method that proactively avoids local minima without any guidance from global paths. The key idea is repulsive potential augmentation, integrating high-level directional information into the Model Predictive Path Integral control as a single repulsive term through an artificial potential field. We evaluate our method through theoretical analysis and simulations in environments with obstacles that induce local minima. Results show that our method guarantees the avoidance of local minima and outperforms existing methods in terms of global optimality without decreasing computational efficiency.

关键词： Analytical models Costs Three-dimensional displays Navigation Computational modeling System integration Predictive models Planning Computational efficiency Robots

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Meaningful human control of partially automated driving systems: Insights from interviews with Tesla users

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Transportation Research Part F: Traffic Psychology and Behaviour 2025年 113卷 213-236页

作者： Suryana, Lucas Elbert Nordhoff, Sina Calvert, Simeon Zgonnikov, Arkady van Arem, Bart Department of Transport and Planning Faculty of Civil Engineering and Geosciences Delft University of Technology Delft Netherlands Electric Vehicle Research Center Institute of Transportation Studies University of California Davis United States Department of Cognitive Robotics Faculty of Mechanical Engineering Delft University of Technology Delft Netherlands Centre for Meaningful Human Control Delft University of Technology Delft Netherlands

Partially automated driving systems are designed to perform specific driving tasks—such as steering, accelerating, and braking—while still requiring human drivers to monitor the environment and intervene when necessary. This shift of driving responsibilities from human drivers to automated systems raises concerns about accountability, particularly in scenarios involving unexpected events. To address these concerns, the concept of meaningful human control (MHC) has been proposed. MHC emphasises the importance of humans retaining oversight and responsibility for decisions made by automated systems. Despite extensive theoretical discussion of MHC in driving automation, there is limited empirical research on how real-world partially automated systems align with MHC principles. This study offers two main contributions: (1) an empirical evaluation of MHC in partially automated driving, based on 103 semi-structured interviews with users of Tesla's Autopilot and Full Self-Driving (FSD) Beta systems;and (2) a methodological framework for assessing MHC through qualitative interview data. We operationalise the previously proposed tracking and tracing conditions of MHC using a set of evaluation criteria to determine whether these systems support meaningful human control in practice. Our findings indicate that several factors influence the degree to which MHC is achieved. Failures in tracking—where drivers' expectations regarding system safety are not adequately met—arise from technological limitations, susceptibility to environmental conditions (e.g., adverse weather or inadequate infrastructure), and discrepancies between technical performance and user satisfaction. Tracing performance—the ability to clearly assign responsibility—is affected by inconsistent adherence to safety protocols, varying levels of driver confidence, and the specific driving mode in use (e.g., Autopilot versus FSD Beta). These findings contribute to ongoing efforts to design partially automated driving

关键词： Human engineering

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