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The effect of graphene nano-platelets on the stability study and artistic design of engineering architectural honeycomb nanocomposite structures

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ADVANCES IN NANO RESEARCH 2025年第1期18卷 53-60页

作者： Xu, Qiang Fee, X. Shen, X. Yvaz, A. Honam Univ Dept Culture & Art Management Gwangju 62399 South Korea State Marine Tech Univ World Class Res Ctr Adv Digital Technol St Petersburg 190121 Russia

Nanotechnology has been integrated into architectural design, and the construction industry is experiencing new solutions that give better structural integrity, aesthetic value, and sustainability for buildings. This paper presents the stability behavior of an artistic design of engineering architectural structure consisting of a honeycomb nanocomposite annular plates reinforced by graphene platelets. A high-order deformation theory is used here for mathematical modeling of artistic design of engineering architectural structure, which can describe the behaviors of these annular plates. Then, a numerical procedure would be introduced to analysis of buckling characteristics of structure. Architectural structures with precisely constituted nanomaterials-carbon nanotubes and graphene derive strength and resilience unprecedented in their ability to withstand environmental stresses and human impacts. The results represent a valuable contribution to the continuing effort of improving our understanding of buckling phenomena in engineering architectural structure and provide a fundamental basis for designing their mechanical behavior, with the aim of enhancement in both geometry and material composition. It is the belief of the paper that in pointing out or highlighting the symbiotic relationship that exists between technology and artistry, it will be in a position to segue the community of architects to be more innovative, experiment with new ideas in the architectural design dimension.

关键词： annular plates artistic design of engineering architectural structure honeycomb nanocomposite numerical method stability

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digital Twin-Driven modeling and Application of High-Temperature Biaxial Materials Testing Apparatus

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Computers, Materials & Continua 2025年第3期82卷 4137-4159页

作者： Xiyu Gao Peng Liu Anran Zhao Guotai Huang Jianhai Zhang Liming Zhou School of Mechanical and Aerospace Engineering Jilin UniversityChangchun130025China

The High-Temperature Biaxial Testing Apparatus(HTBTA)is a critical tool for studying the damage and failure mechanisms of heat-resistant composite materials under extreme ***,existing methods for managing and monitoring such apparatus face challenges,including limited real-time modeling capabilities,inadequate integration of multi-source data,and inefficiencies in human-machine *** address these gaps,this study proposes a novel digital twin-driven framework for HTBTA,encompassing the design,validation,operation,and maintenance *** integrating advanced modeling techniques,such as finite element analysis and Long Short-Term Memory(LSTM)networks,the digital twin enables high-fidelity simulation,real-time predictive modeling,and robust remote monitoring of *** research contributes to bridging the knowledge gap in applying digital twin technology to high-temperature multi-axial testing *** existing solutions,the proposed approach achieves synchronization error,real-time monitoring with ms delay,and predictive accuracy for temperature<2%<100distributions under extreme conditions up to 2500℃.The findings highlight the effectiveness of the digital twin in improving system reliability,enhancing interaction efficiency,and reducing maintenance *** study not only advances the application of digital twin technology in high-temperature material testing but also establishes a foundation for broader adoption in aerospace,automotive,and other industrial *** research directions include exploring non-proportional loading scenarios,expanding multi-environment simulations,and integrating in-situ observation techniques.

关键词： digital twin HTBTA remote monitoring LSTM

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A digital-twin evaluation framework of zero carbon buildings for existing residential buildings based on scan-to-BIM

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ALEXANDRIA engineering JOURNAL 2025年 124卷 204-213页

作者： Zhao, Liang Zhang, Hong Wang, Haining Wang, Yue Li, Tianhao Hebei Univ Engn Sch Energy & Environm Engn Handan 056038 Hebei Peoples R China China Univ Min & Technol Sch Architecture & Design Xuzhou 221116 Peoples R China Southeast Univ Sch Architecture Nanjing 210096 Peoples R China Southeast Univ Sch Civil Engn Nanjing 210096 Peoples R China

To tackle the climate warming crisis together, reducing carbon emissions and achieving sustainable human development have become a global consensus. This paper focuses on evaluating zero-carbon retrofit schemes for existing buildings and proposes a digital twin evaluation framework that combines point cloud models and building information modeling. Based on the point cloud data, a 3D visualization model of the existing building is established as a virtual one, and different retrofit schemes are simulated. Then, comprehensively analyze the building energy consumption, building carbon emissions, predicted mean vote (PMV), and predicted percentage dissatisfied (PDD) of the retrofit schemes to find the optimal solution for zero carbon emissions of existing buildings. According to the results of the study, the zero-carbon building retrofit scheme suitable for the case study can reduce building energy use by 13.95 %, increase solar photovoltaic power generation by 27.80 %, and reduce carbon emissions by 18106.32 kgCO2/a.

关键词： Building Information modeling digital Twin Zero-carbon Buildings Point Cloud Building Energy Model

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design and Torque Control of a Modular Reconfigurable Variable Stiffness Exoskeleton for Improved Transparency

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IEEE-ASME TRANSACTIONS ON MECHATRONICS 2025年

作者： Zhu, Yanghui Wu, Qingcong Chen, Bai Tang, Qirong Zeng, Hong Wu, Hongtao Nanjing Univ Aeronaut & Astronaut Coll Mech & Elect Engn Nanjing 210016 Peoples R China Tongji Univ Coll Mech & Energy Engn Shanghai 201804 Peoples R China Southeast Univ Sch Instrument Sci & Engn State Key Lab Digital Med Engn Jiangsu Key Lab Robot Percept & Control Nanjing 210096 Peoples R China

Exoskeletons play a huge role in increasing the strength of normal people and assisting people with weak mobility. High mechanical robustness, low output impedance, reconfigurable hardware structure, and accurate torque control are essential for exoskeletons to enable safe and transparent physical human-robot interaction. In this article, first, a reconfigurable variable stiffness actuator with passive nonlinear variable stiffness and active variable stiffness characteristics is proposed to improve the adaptability and transparency of the exoskeleton. Second, a modular reconfigurable variable stiffness exoskeleton (MRVS-EXO) is proposed. The MRVS-EXO accommodates various configurations through reconfigurable and modular design, addressing the diverse needs of users. Then, a hysteresis modeling method based on "virtual deformation" is proposed to enable online torque estimation. This method employs the linearization method of "virtual deformation" to model hysteresis as segmented straight lines and curves, reducing computational performance requirements. Utilizing the hysteresis model, a cascade torque control method based on hysteresis compensation is employed to achieve precise torque control. Finally, the performance of the torque estimation and control method is experimentally verified, and the transparency of the exoskeleton is tested by going upstairs, downstairs, and walking outdoors experiments on subjects. Experimental results show that the proposed MRVS-EXO design and the torque control method enhance the transparency of the exoskeleton.

关键词： Torque Hysteresis Load modeling Torque control Springs Exoskeletons Computational modeling Actuators Adaptation models Pulleys Physical human-robot interaction (pHRI) reconfigurable design torque control transparent actuation variable stiffness actuator (VSA)

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A digital Twin Driven human-Centric Ecosystem for Industry 5.0

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND engineering 2025年 22卷 11291-11303页

作者： Villani, Valeria Picone, Marco Mamei, Marco Sabattini, Lorenzo Univ Modena & Reggio Emilia Dept Sci & Methods Engn DISMI I-42121 Reggio Emilia Italy

Industry 5.0 embodies the vision for the future of factories, emphasizing the importance of sustainable industrialization and the role of industry in society, through the key concept of placing the well-being of workers at the center of the production process. Building upon this vision, we propose a new paradigm to design human-centric industrial applications. To this end, we exploit digital Twin (DT) technology to build a digital replica for each entity on the shop floor and support and augment interaction among workers and machines. While so far DTs in automation have been proposed for machine digitalization, the core element of the proposed approach is the Operator digital Twin (ODT). In this scenario, biometrics allows to build a reliable model of those operator's characteristics that are relevant in working contexts. Biometric traits are measured and processed to detect physical, emotional, and mental conditions, which are used to define the operator's state. Perspectively, this allows to manage and monitor production and processes in an operator-in-the-loop manner, where not only is the operator aware of the state of the plant, but also any technological agent in the plant acts and reacts according to the operator's needs and conditions. In this paper, we define the modeling of the envisioned ecosystem, present the designed DT's blue-print architecture, discuss its implementation in relevant application scenarios, and report an example of implementation in a collaborative robotics scenario. Note to PractitionersuThis paper was motivated by the problem of designing human-cyber-physical systems, where production processes are managed by concurrently taking into account operators, machines and plant status. This answers the needs of the novel Industry 5.0 paradigm, which aims to enhance social sustainability of modern factories. To this end, we propose an architecture based on digital twins that allows to develop a digital layer, detached from the physical one, w

关键词： Industry 5.0 digital twins human-centric automation

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Generative AI for Analog Integrated Circuit design: Methodologies and Applications

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IEEE ACCESS 2025年 13卷 58043-58059页

作者： Noori Zadeh, Danial Elamien, Mohamed B. McMaster Univ Dept Elect & Comp Engn Hamilton ON L8S 4L8 Canada

Electronic design Automation (EDA) in analog Integrated Circuits (ICs) has been the focus of extensive research;however, unlike its digital counterpart, it has not achieved widespread adoption. In this systematic review, we discuss recent contributions in the last five years, highlighting methods that address data scarcity, topology exploration, process-voltage-temperature (PVT) variations, and layout parasitics. Our goal is to support researchers new to this domain by creating a comprehensive collection of references and practical application guidelines. We provide a methodological review of state-of-the-art machine learning (ML) approaches, including graph neural networks (GNNs), large language models (LLMs), and variational autoencoders (VAEs), which have been successfully applied to analog circuit sizing tasks. To the best of authors' knowledge, this is the first review to comprehensively explore the application of generative AI models in analog IC circuit design. We conclude that future research could focus on few-shot learning with domain-adaptation training of generative AI methods to simplify the design tasks such as human-tool interaction or guided design space exploration.

关键词： Integrated circuit modeling Automation Reviews Layout Topology Computational modeling Data models Generative AI Voltage Training Analog integrated circuits (ICs) electronic design automation (EDA) layout-aware sizing machine learning (ML) large language models (LLM) graph neural networks (GNN) variational auto-encoders (VAE) artificial intelligence (AI)

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Artificial intelligence-based displacement capacity prediction tool for three-dimensional printed concrete walls

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STRUCTURAL CONCRETE 2025年第0期

作者： Ozalp, Abdulkadir Aldemir, Alper Hacettepe Univ Dept Civil Engn Univ St TR-06800 Ankara Turkiye

digital technology applications such as three-dimensional printers offer novel avenues for automating the construction of concrete structures. The process of 3D printing concrete structures involves designing in an office setting and printing on-site. This sequential approach to 3D printing makes achieving fully automated practice unfeasible. To address the goal of achieving fully automated 3D concrete printing, this study proposes an automated design tool utilizing artificial intelligence (AI) techniques to ascertain the capacities of 3D-printed concrete walls and conduct the necessary design tasks for each wall. Moreover, this automated design tool is capable of determining the most efficient section geometry for the intended 3D-printed wall geometry. Consequently, the AI model identifies the most cost-effective and lightweight cross-section topology with the desired strength without requiring trial and error, thus eliminating the need for human intervention in the design process.

关键词： convolutional neural network fully automated construction printing multilayer perceptron numerical modeling topology optimization

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A Robust Autoencoder HBC Transceiver With CGAN-Based Channel modeling

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IEEE Sensors Journal 2025年第9期25卷 15935-15949页

作者： Ali, Abdelhay Abdelrahman, Amr N. Celik, Abdulkadir Fouda, Mohammed E. Eltawil, Ahmed M. King Abdullah University of Science and Technology Computer Electrical and Mathematical Sciences and Engineering Division Thuwal23955-6900 Saudi Arabia Compumacy for Artificial Intelligence Solutions Cairo22303-2839 Egypt

human body communication (HBC) offers a promising alternative for efficient and secure data transmission in wearable healthcare systems by leveraging the body’s conductive properties. Using the conductive properties of the human body, HBC offers significant advantages over conventional radio frequency wireless communication methods, including ultralow power consumption and minimal interference. However, HBC systems face key challenges in energy efficiency, data rate optimization, channel adaptability, and accurate body channel modeling. In this article, we present a novel dual-mode HBC transceiver architecture designed to overcome these challenges by integrating autoencoder-based signal processing with generative adversarial network (GAN)-driven channel modeling framework to enhance communication reliability. Operating in both broadband and narrowband modes, the transceiver dynamically adjusts its data rate and power efficiency based on application-specific demands. The design process involves first developing a conditional GAN (CGAN)-based channel model from real HBC measurements, and then using this model to train an autoencoder-based transceiver architecture. Our CGAN framework generates realistic synthetic channel responses for training, enabling the autoencoder to learn optimal encoding and decoding strategies that are robust to channel variations. Subsequently, we developed a low-power hardware architecture that supports flexible data rates of the proposed design while ensuring robust performance in diverse scenarios. This systematic approach provides key advantages: improved channel modeling accuracy achieving a 0.9 correlation coefficient between generated and real channels and mean squared error (mse) of 0.0071, reduced hardware complexity through elimination of digital-to-analog converter (DAC)/analog-to-digital converter (ADC), and flexible operation with dual-mode support. Operating at a clock speed of 42 MHz in the narrowband mode, the transceiver achie

关键词： Radio transceivers

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Evaluating the Benefits and Drawbacks of Visualizing Systems modeling Language (SysML) Diagrams in the 3D Virtual Reality Environment

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SYSTEMS 2025年第4期13卷 221-221页

作者： Lutfi, Mostafa Valerdi, Ricardo Univ Arizona Dept Syst & Ind Engn Tucson AZ 85721 USA

Model-Based Systems engineering (MBSE) prioritizes system design through models rather than documents, and it is implemented with the Systems modeling Language (SysML), which is the state-of-the-art language in academia and industry. Virtual Reality (VR), an immersive visualization technology, can simulate reality in virtual environments with varying degrees of fidelity. In recent years, the technology industry has invested substantially in the development of head-mounted displays (HMDs) and related virtual reality (VR) technologies. Various research has suggested that VR-based immersive design reviews enhance system issue/fault identification, collaboration, focus, and presence compared to non-immersive approaches. Additionally, several research efforts have demonstrated that the VR environment provides higher understanding and knowledge retention levels than traditional approaches. In recent years, multiple attempts have been made to visualize conventional 2D SysML diagrams in a virtual reality environment. To the best of the author's knowledge, no empirical evaluation has been performed to analyze the benefits and drawbacks of visualizing SysML diagrams in a VR environment. Hence, the authors aimed to evaluate four key benefit types and drawbacks through experiments with human subjects. The authors chose four benefit types-Systems Understanding, Information Sharing, modeling and Training Experience, and digital Twin based on the MBSE value and benefits review performed by researchers and benefits claimed by the evaluations for similar visual formalism languages. Experiments were conducted to compare the understanding, interaction, and knowledge retention for 3D VR and conventional 2D SysML diagrams. The authors chose a ground-based telescope system as the system of interest (SOI) for system modeling. The authors utilized a standalone wireless HMD unit for a virtual reality experience, which enabled experiments to be conducted irrespective of location. Students an

关键词： MBSE SysML virtual reality systems understanding digital twin

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Calibration of RAFM Micromechanical Model for Creep Using Bayesian Optimization for Functional Output

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JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN engineering 2025年第3期25卷 031007页

作者： Huang, Chaofan Aduloju, Sunday Fritz, John Joseph, V. Roshan Messner, Mark Truster, Timothy Georgia Inst Technol H Milton Stewart Sch Ind & Syst Engn Atlanta GA 30332 USA Oak Ridge Natl Lab Fus Energy Div Oak Ridge TN 37831 USA Univ Tennessee Dept Civiland Environm Engn Knoxville TN 37996 USA Argonne Natl Lab Appl Mat Div Lemont IL 60439 USA Univ Tennessee Dept Civil & Environm Engn Knoxville TN 37996 USA

and system behavior. The computational efficiency gained using such twins is critical for real-time machine monitoring and diagnostics with timely and interactive human intervention. One of the fundamental challenges in the current data-driven digital twins is a lack of understanding of how different data synthesis strategies of the same sensor data affect the predictive power of the twin models typically obtained through statistical learning. As a result, the interactive support for enabling human intervention and machine health monitoring is not generalized for different machine configurations and fault conditions. Using turbomachinery as a concrete demonstrative context, we investigate two fundamentally different data synthesis strategies, namely, integrated and combinatorial, as digital twins for a rotating machine. Specifically, we consider a rotor kit as a machine component, develop a synthetic dataset using simulations, and conduct systematic studies on the predictive performance of reduced-order models trained using the different data synthesis strategies. Our experiments show that the combinatorial dataset offers higher prediction accuracy in comparison to randomized data generation. Moreover, we created a cloud- based augmented reality (AR) mobile tool to show the feasibility of our methodology in developing potential machine monitoring applications with human-in-the-loop components. [DOI: 10.1115/1.4067600] Keywords: artificial intelligence, cyber physical system design and operation, industrial internet of things, virtual and augmented reality environments

关键词： model calibration crystal plasticity Bayesian optimization generalized chi-square distribution inverse methods for engineering applications multiscale modeling and simulation physics-based simulations

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