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Multi-model ensemble learning for battery state-of-health estimation:Recent advances and perspectives

Journal of Energy Chemistry 2025年第1期100卷 739-759页

作者： Chuanping Lin Jun Xu Delong Jiang Jiayang Hou Ying Liang Zhongyue Zou Xuesong Mei State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Shaanxi Key Laboratory of Intelligent Robots School of Mechanical Engineering Xi'an Jiaotong University Department of electrical Engineering and Automation Luoyang Institute of Science and Technology School of mechanical Engineering Hangzhou Dianzi University

The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational performance. Despite numerous data-driven methods reported in existing research for battery SOH estimation, these methods often exhibit inconsistent performance across different application scenarios. To address this issue and overcome the performance limitations of individual data-driven models,integrating multiple models for SOH estimation has received considerable attention. Ensemble learning(EL) typically leverages the strengths of multiple base models to achieve more robust and accurate outputs. However, the lack of a clear review of current research hinders the further development of ensemble methods in SOH estimation. Therefore, this paper comprehensively reviews multi-model ensemble learning methods for battery SOH estimation. First, existing ensemble methods are systematically categorized into 6 classes based on their combination strategies. Different realizations and underlying connections are meticulously analyzed for each category of EL methods, highlighting distinctions, innovations, and typical applications. Subsequently, these ensemble methods are comprehensively compared in terms of base models, combination strategies, and publication trends. Evaluations across 6 dimensions underscore the outstanding performance of stacking-based ensemble methods. Following this, these ensemble methods are further inspected from the perspectives of weighted ensemble and diversity, aiming to inspire potential approaches for enhancing ensemble performance. Moreover, addressing challenges such as base model selection, measuring model robustness and uncertainty, and interpretability of ensemble models in practical applications is emphasized. Finally, future research prospects are outlined, specifically noting that deep learning ensemble is poised to advance ens

关键词： Contrastive Learning

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Equivalent combined cycle modelling for three-heat-reservoir thermal Brownian heat pump with heat-transfer effect and its optimal performance

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Science China Technological Sciences 2025年

作者： Lingen CHEN Congzheng QI Yanlin GE Huijun FENG Hubei Provincial Key Laboratory of Chemical Equipment Intensification and Intrinsic Safety Wuhan Institute of Technology Hubei Provincial Engineering Technology research Center of Green Chemical Equipment Wuhan Institute of Technology institute of Thermal Science and Power Engineering Wuhan Institute of Technology School of mechanical & electrical Engineering Wuhan Institute of Technology

Because of the important role of the absorption heat pump in low-grade thermal energy utilization, this paper extends it to micro domain and performs a finite-time thermodynamic modelling for a three-heat-reservoir (THR) thermal Brownian heat pump with heat transfer effect by using an equivalent combined cycle method, which was applied for macro endoreversible THR heat pumps. The working principle and energy transformation rule are studied, and the coefficient of performance (COP) and heating load are derived. With a fixed overall thermal conductance of three heat exchangers, the maximal heating load is determined by optimizing thermal conductance distributions among three heat exchangers and barrier height, and the optimal working temperatures are also obtained. The impact of external heat transfer is elucidated to show the difference between this model and a non-equilibrium thermodynamic one. Results indicate that external heat transfer determines the energy transformation directly, and performance characteristics are closer to reality when external heat transfer is considered. The heating load has a maximal value about thermal conductance allocation ratios. About half the overall heat exchanger inventory needs to be assigned to the heat exchanger of the heating space for maximal heating load. When the cycle is with only heat transfer effect, the net particle numbers are zero, and the cycle fails to pump heat. The research results are expected to offer an idea for thermodynamic optimization and design of micro THR thermal Brownian heat pump devices.

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Data-Driven Healthcare:The Role of Computational Methods in Medical Innovation

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 1-48页

作者： Hariharasakthisudhan Ponnarengan Sivakumar Rajendran Vikas Khalkar Gunapriya Devarajan Logesh Kamaraj Department of mechanical Engineering Dr.Mahalingam College of Engineering and TechnologyPollachiCoimbatoreTamil Nadu642003India Department of mechanical Engineering JKKN College of Engineering and TechnologyKumarapalayamNamakkalTamil Nadu637209India Department of mechanical Engineering Gharda Institute of TechnologyLavelMaharashtra415708India Department of electrical and Electronics Engineering Sri Eshwar College of EngineeringCoimbatoreTamilnadu641202India Department of mechanical Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai600062India

The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical *** review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health *** findings indicate that computational models have significantly enhanced the understanding of complex biological systems,while machine learning algorithms have improved the accuracy of disease prediction and *** synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment ***,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease *** review emphasizes the need for interdisciplinary collaboration to further advance this *** research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and *** fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.

关键词： Computational models biomedical engineering bioinformatics machine learning wearable technology

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Nano-Enhanced Dairy Scum Biodiesel Blends:Unleashing the Power of Aluminium Oxide for Sustainable and Efficient Engine Performance

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Journal of Thermal Science 2025年第1期 283-302页

作者： Veeranna MODI Prasad B.RAMPURE Sunil Kumar SHETTY Madeva NAGARAL Channa Keshava NAIK N Johar MGM Muhammad Irsyad ABDULLAH Abdullah I.AL-MANSOUR Shamshad ALAM KLE College of Engineering and Technology ChikodiVisvesvaraya Technological University Nitte (Deemed to be University) NMAM Institute of Technology (NMAMIT)Department of Mechanical Engineering Aircraft research and design Centre HAL Department of mechanical Engineering BGS College of Engineering and TechnologyBengaluruAffiliated to Visvesvaraya Technological University Management and Science University Department of Civil Engineering College of EngineeringKing Saud University

This study investigates the effect of aluminium oxide nanoparticlesaddition to biodiesel blends made from dairy milk scum on performance and combustion characteristics of the diesel *** dispersion of Al2O3nanoparticles in B20 blends at different concentrations was done with the help of *** number of blends were prepared for the *** Machine learning algorithms(Random Forest（RF）and CatBoost) was used for the *** results show that in comparison to biodiesel blends without nanoparticles,the kinematic viscosity and density is higher for fuel blends with *** these Fuel blends have higher calorific *** blends exhibited reduced Brake Specific Fuel Consumption（BSFC） of2.85% than the blends without nano particles(Dairy Scum Methyl Ester Biodiesel 20%+Neat Diesel 80%（in volume）,DSMEB20),57.14% less CO,40.8% less hydrocarbon,and increased NOxemissions compared to conventional diesel,contributing to the development of environmentally friendly and renewable biofuel blends with *** B20NP30 is the optimal blend for performance and emission *** study concludes with findings on enhanced Brake Thermal Efficiency（BTE） of 26.29% in 3×10-5（in volume） Al2O3nanoparticle-blended DSME B20 and other DSME B20 fuel blends,emphasizing the importance of optimal nanoparticle *** correlation matrix shows how engine load,efficiency measures（BTE,BSFC）,and emissions（CO,CO2,NOx,Smoke） are connected in complex *** results help us understand the complicated dynamics of engine performance and emission characteristics ***'s diagram for BTE and BSFC shows that CatBoost-based BTE models perform superior to RF-based models during the training as well as testing *** results were obtained for CO and CO2emission results.

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Broadband low-frequency sound absorption of multifunctional composite metastructure

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Science China Technological Sciences 2025年

作者： Yilong YANG Shanshan LIU Yan LI Tong GAO Yongdong PAN Yong LI Yabin JIN School of Aerospace Engineering and Applied Mechanics Tongji University institute of Acoustics School of Physics Science and Engineering Tongji University Shanghai institute of Aircraft Mechanics and Control State International Joint research Center of Aerospace design and Additive Manufacturing Northwestern Polytechnical University Shanghai Key Laboratory of Intelligent Sensing and Detection Technology School of Mechanical and Power Engineering East China University of Science and Technology

In this study, we fabricated multifunctional metastructures from carbon fiber-reinforced plastic composites using additive manufacturing technology. These metastructures are characterized by their lightweight, load-bearing capacity, and broadband low-frequency sound absorption properties. The metastructure consists of 36 unit cells, and non-local coupling mechanism was considered for designing the sound absorption performance. We developed an acoustic impedance theory tailored for the metastructure, facilitating an analysis of thermal and viscous dissipation mechanisms. It is proven theoretically and experimentally that the proposed composite metastructure can achieve a noise reduction with an average sound absorption coefficient greater than 0.9 across frequencies in the rage of 330–1500 Hz. We also studied the metastructure’s quasi-static and cyclic compression performance, confirming its efficient absorption capabilities after cyclic compression. The proposed design and additive manufacturing method for composite metastructures provides a novel pathway for creating lightweight, multifunctional structures with diverse applications, such as aerospace engineering.

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Ultra‑High Sensitivity Anisotropic Piezoelectric Sensors for Structural Health Monitoring and Robotic Perception

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Nano-Micro Letters 2025年第2期17卷 432-446页

作者： Hao Yin Yanting Li Zhiying Tian Qichao Li Chenhui Jiang Enfu Liang Yiping Guo State Key Laboratory of Metal Matrix Composites School of Materials Science and EngineeringShanghai Jiao Tong UniversityShanghai 200240People’s Republic of China Beijing Vacuum Electronics research institute Beijing 100015People’s Republic of China Fundamental Science On Vibration Shock and Noise LaboratoryState Key Laboratory of Mechanical System and VibrationSchool of Mechanical EngineeringShanghai Jiao Tong UniversityShanghai 200240People’s Republic of China

Monitoring minuscule mechanical signals,both in magnitude and direction,is imperative in many application scenarios,e.g.,structural health monitoring and robotic sensing ***,the piezoelectric sensor struggles to satisfy the requirements for directional recognition due to the limited piezoelectric coefficient matrix,and achieving sensitivity for detecting micrometer-scale deformations is also ***,we develop a vector sensor composed of lead zirconate titanate-electronic grade glass fiber composite filaments with oriented arrangement,capable of detecting minute anisotropic *** as-prepared vector sensor can identify the deformation directions even when subjected to an unprecedented nominal strain of 0.06%,thereby enabling its utility in accurately discerning the 5μm-height wrinkles in thin films and in monitoring human pulse *** ultra-high sensitivity is attributed to the formation of porous ferroelectret and the efficient load transfer efficiency of continuous lead zirconate titanate ***,when integrated with machine learning techniques,the sensor’s capability to recognize multi-signals enables it to differentiate between 10 types of fine textures with 100%*** structural design in piezoelectric devices enables a more comprehensive perception of mechanical stimuli,offering a novel perspective for enhancing recognition accuracy.

关键词： Flexible piezoelectric filaments Anisotropic Ultra-high sensitivity Structural health detection Texture recognition

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Modeling tactile perceived intensity for vibration from a coin eccentric rotating mass motor

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Science China Technological Sciences 2025年

作者： Yun FANG Jingchen HUANG Yujun WU Jiaqi DONG Weichao GUO Xinjun SHENG State Key Laboratory of mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University Meta Robotics institute Shanghai Jiao Tong University

Establishing the relationship between vibrotactile parameters and perceived intensity（PI） is of great significance in the regulation of desired sensations, which contribute to haptic interfaces in practical applications. Coin eccentric rotating mass（ERM） motors are routinely utilized due to their lightweight design and efficient ability to evoke strong tactile sensations. By adjusting input voltages, ERMs can yield different stimuli, but the effects of their physical properties on PI remain ***, we developed the physical model of the ERM-skin system and optimized the parameters affecting PI. Moreover, the relationship between stimulus and perception was derived based on Fechner?s law. Three experiments were conducted on fifteen subjects（ten males and five females, aged 24.40 ± 2.87 years） to identify the vibration parameters and corresponding PI to verify the proposed PI model. ERMs in this study were attached to phantom skin/forearm with slim adhesive tape to minimize the interference. Experiment 1 performed vibration calibration with ERM attached to the skin phantom to simulate the actual configuration. Then, the relative and absolute PI of subjects on specific stimuli were acquired in Experiments 2 and *** fitting reliability of the proposed PI model was evaluated on fifteen subjects with R2of 0.73 ± 0.07 and root mean squared error（RMSE） of 1.35 ± 0.28. Overall, the proposed PI model established the quantitative relationship between stimulus parameters（vibration parameters and physical parameters） and subjective PI, which provided theoretical support for ERM optimization and vibrotactile modulation.

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research status and prospects of the fractal analysis of metal material surfaces and interfaces

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International Journal of Minerals,Metallurgy and Materials 2025年第1期32卷 20-38页

作者： Qinjin Dai Xuefeng Liu Xin Ma Shaojie Tian Qinghe Cui Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology BeijingBeijing 100083China Beijing Laboratory of Metallic Materials and Processing for Modern Transportation University of Science and Technology BeijingBeijing 100083China Laboratory for Advanced Materials Processing of Ministry of Education University of Science and Technology BeijingBeijing 100083China School of mechanical and electrical Engineering Xinjiang Institute of EngineeringUrumqi 830023China

As a mathematical analysis method,fractal analysis can be used to quantitatively describe irregular shapes with self-similar or self-affine *** analysis has been used to characterize the shapes of metal materials at various scales and *** methods make it difficult to quantitatively describe the relationship between the regular characteristics and properties of metal material surfaces and ***,fractal analysis can be used to quantitatively describe the shape characteristics of metal materials and to establish the quantitative relationships between the shape characteristics and various properties of metal *** the perspective of two-dimensional planes and three-dimensional curved surfaces,this paper reviews the current research status of the fractal analysis of metal precipitate interfaces,metal grain boundary interfaces,metal-deposited film surfaces,metal fracture surfaces,metal machined surfaces,and metal wear *** relationship between the fractal dimensions and properties of metal material surfaces and interfaces is *** from three perspectives of fractal analysis,namely,research scope,image acquisition methods,and calculation methods,this paper identifies the direction of research on fractal analysis of metal material surfaces and interfaces that need to be *** is believed that revealing the deep influence mechanism between the fractal dimensions and properties of metal material surfaces and interfaces will be the key research direction of the fractal analysis of metal materials in the future.

关键词： metal material surfaces and interfaces fractal analysis fractal dimension homogeneity

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Metal-organic frameworks (MOFs) in aqueous batteries (ABs):unlocking potential through innovative materials design

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Science China Chemistry 2025年

作者： Bo Han Erhai Hu Bei-Er Jia Ziyang Liu Shuen Tso Afriyanti Sumboja Ivandini T.Anggraningrum Anne Zulfia Syahrial Qingyu Yan SCARCE Laboratory Energy Research Institute NTU (ERIN) Nanyang Technological University School of Materials Science and Engineering Nanyang Technological University Material Science and Engineering research Group Faculty of Mechanical and Aerospace Engineering Institut Teknologi Bandung Department of Chemistry University of Indonesia Metallurgical & Materials Engineering Department Fakultas Teknik Universitas Indonesia

Metal-organic frameworks (MOFs) represent a revolutionary class of materials in the field of energy storage,particularly for aqueous batteries (ABs).Distinguished by their large surface area,tuneable porosity,and adaptable chemical activity,MOFs offer significant advantages over conventional materials in battery *** article provides a thorough analysis of the crucial role that MOFs play in improving the efficiency of *** includes a concise review of the current research progress,emphasizing the fundamental processes by which MOFs enhance electrochemical ***,the review examines the synthesis and design strategies for the structure of MOFs to maximize ion transport,improve conductivity,and enhance *** structural advantages,chemical versatility,stability,durability and functionalization potential of MOFs are comprehensively ***,we explore the distinct advantages of MOFs in overcoming common challenges encountered in ABs,such as declining capacity,inadequate cycling stability,and limited energy *** paper also highlights the future research directions needed to fully harness their *** goal is to develop a fundamental understanding and stimulate further progress in the use of MOFs for advanced energy storage solutions.

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mechanical Properties,Purifying Techniques and Processing Methods of Metal Yttrium

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Journal of Rare Earths 2006年第z2期24卷 362-366页

作者：金红孙国强 Beijing research institute of mechanical and electrical Technology

The mechanical properties of metal yttrium such as strength, plasticity, hardness and elasticity were introduced . The purifying techniques of yttrium were discussed in detail. The processing methods for metal yttrium including extruding, forging, rolling, wiredrawing and welding were also introduced. Finally, the potential use of yttrium and its alloys were prospected.

关键词： metal yttrium mechanical properties purifying processing rare earths

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