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Effective thermal conductivity estimation using a convolutional neural network and its application in topology optimization

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Energy and AI 2024年第1期15卷 236-247页

作者： Andre Adam huazhen fang Xianglin Li Department of Mechanical Engineering University of Kansas1530 W 15th St.Lawrence66045KSUSA Department of Mechanical Engineering and Materials Science Washington University in St.LouisOne Brookings DriveSt.Louis63130MOUSA

Topology optimization of heterogeneous structures can find significant use in a wide range of applications,and its fabrication has been made possible by recent advances in additive ***,the optimization procedure is computationally expensive,as each structural update requires the re-evaluation of the *** computational time is the major limiting factor in large-scale and complex structural *** this study,a convolutional neural network(CNN)model for predicting effective thermal conductivity inspired by the VGG networks is *** using 130,000 unique binary images,the model achieves high predictive ***,it shows a mean absolute percent error(MAPE)of 0.35%in testing when the thermal conductivity of the solid is ten times larger than the fluid,and when the thermal conductivities assigned are that of aluminum and water,the MAPE is 2.35%.The prediction time is 15 ms for a single image with 128×128 pixels,which is 3 to 5 orders of magnitude faster than a finite volume *** employed in topology optimization,the CNN retains a MAPE between 0.67%and 11.8%for different *** CNN model correctly predicts trends in effective thermal conductivity and improves the structure to close proximity of a theoretical maximum in all cases.

关键词： Machine learning Effective thermal conductivity Convolutional neural network VGG Numerical heat transfer Topology optimization

Nonlinear Bayesian Estimation： From Kalman Filtering to a Broader Horizon

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IEEE/CAA Journal of Automatica Sinica 2018年第2期5卷 401-417页

作者： huazhen fang Ning Tian Yebin Wang Meng Chu Zhou Mulugeta A. Haile IEEE Department of Mechanical Engineering University of Kansas Lawrence KS 66045 USA Mitsubishi Electric Research Laboratories Cambridge MA 02139 USA the Helen and John C. Hartmann Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ 07102 USA the Vehicle Technology Directorate US Army Research Laboratory Aberdeen MD 21005 USA

This article presents an up-to-date tutorial review of nonlinear Bayesian estimation. State estimation for nonlinear systems has been a challenge encountered in a wide range of engineering fields, attracting decades of research effort. To date,one of the most promising and popular approaches is to view and address the problem from a Bayesian probabilistic perspective,which enables estimation of the unknown state variables by tracking their probabilistic distribution or statistics(e.g., mean and covariance) conditioned on a system's measurement *** article offers a systematic introduction to the Bayesian state estimation framework and reviews various Kalman filtering(KF)techniques, progressively from the standard KF for linear systems to extended KF, unscented KF and ensemble KF for nonlinear systems. It also overviews other prominent or emerging Bayesian estimation methods including Gaussian filtering, Gaussian-sum filtering, particle filtering and moving horizon estimation and extends the discussion of state estimation to more complicated problems such as simultaneous state and parameter/input estimation.

关键词： Index Terms-Kalman filtering (KF) nonlinear Bayesian esti-mation state estimation stochastic estimation.

Data-Driven Discovery of Stochastic Differential Equations

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Engineering 2022年第10期17卷 244-252页

作者： Yasen Wang huazhen fang Junyang Jin Guijun Ma Xin He Xing Dai Zuogong Yue Cheng Cheng Hai-Tao Zhang Donglin Pu Dongrui Wu Ye Yuan Jorge Gonçalves Jürgen Kurths Han Ding School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Department of Mechanical Engineering University of KansasLawrenceKS 66045USA HUST-Wuxi Research Institute Wuxi 214174China Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China Department of Plant Sciences University of CambridgeCambridge CB23EAUK Luxembourg Centre for Systems Biomedicine University of LuxembourgBelvaux 4367Luxembourg Department of Physics Humboldt University of BerlinBerlin 12489Germany Department of Complexity Science Potsdam Institute for Climate Impact ResearchPotsdam 14473Germany

Stochastic differential equations(SDEs)are mathematical models that are widely used to describe complex processes or phenomena perturbed by random noise from different *** identification of SDEs governing a system is often a challenge because of the inherent strong stochasticity of data and the complexity of the system’s *** practical utility of existing parametric approaches for identifying SDEs is usually limited by insufficient data *** study presents a novel framework for identifying SDEs by leveraging the sparse Bayesian learning(SBL)technique to search for a parsimonious,yet physically necessary representation from the space of candidate basis *** importantly,we use the analytical tractability of SBL to develop an efficient way to formulate the linear regression problem for the discovery of SDEs that requires considerably less time-series *** effectiveness of the proposed framework is demonstrated using real data on stock and oil prices,bearing variation,and wind speed,as well as simulated data on well-known stochastic dynamical systems,including the generalized Wiener process and Langevin *** framework aims to assist specialists in extracting stochastic mathematical models from random phenomena in the natural sciences,economics,and engineering fields for analysis,prediction,and decision making.

关键词： Data-driven method System identification Sparse Bayesian learning Stochastic differential equations Random phenomena

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自动驾驶车辆换道意图识别研究现状

工程科学学报 2024年第10期46卷 1845-1855页

作者：方华珍刘立顾青肖小凤孟宇北京科技大学机械工程学院北京100083

近年来基于数据驱动的自动驾驶车辆换道意图识别研究取得了显著进展,学者们发布了大量的研究成果.针对该领域面临的一些共性的技术挑战,如换道过程的认定、换道标签的缺失以及数据类别不均衡等问题,从不同的数据驱动方法进行分类,主要... 详细信息

近年来基于数据驱动的自动驾驶车辆换道意图识别研究取得了显著进展,学者们发布了大量的研究成果.针对该领域面临的一些共性的技术挑战,如换道过程的认定、换道标签的缺失以及数据类别不均衡等问题,从不同的数据驱动方法进行分类,主要包括基于传统机器学习、基于深度学习和基于集成学习的换道意图识别方法,对近年来这些方法的研究成果进行了回顾和总结.关于换道行为的认定,存在两种主流方案,即车辆穿越车道线和未穿越车道线.对于未穿越车道线的车辆,主要应用于驾驶者换道意图的早期识别方法;而当车辆穿越过车道线时,则通常被用于完整的换道过程的识别.在换道意图标注的研究中,研究者们针对固定时间窗口和航向角阈值对标注精度的影响进行了深入探讨.为了找到最优参数,如最佳的固定时间窗口和航向角阈值,研究者们采用了网格搜索进行寻优.虽然这种方法在固定的驾驶场景中表现良好,但在不同的驾驶场景中,如何实现参数的自适应调节仍然是一个挑战.针对换道数据类别不均衡的问题,研究者采用两种策略:一是调整数据采样方法,利用欠采样和过采样技术平衡各类别样本数量;二是采用对不均衡数据适应性强的分类模型,如集成学习算法或代价敏感学习,以维持较好的分类性能.

关键词：交通工程自动驾驶车辆数据驱动换道意图识别

Synthesis of ternary geopolymers using prediction for effective solidification of mercury in tailings

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Journal of Environmental Sciences 2025年第1期147卷 392-403页

作者： Xuan Lu Jinfa Guo fang Chen Mengkui Tian School of Chemistry and Chemical Engineering Guizhou UniversityGuiyang 550025China

This study used steel slag,fly ash,and metakaolin as raw materials(SFM materials)to create silica-alumina-based geopolymers that can solidify Hg^(2+)when activated with sodiumbased water *** experiments began with a triangular lattice point mixing design experiment,and the results were fitted,analyzed,and *** optimum SFM material mass ratio was found to be 70%steel slag,25%fly ash,and 5%*** optimum modulus of the activator was identified by comparing the unconfined compressive strength and solidifying impact on Hg^(2+)of geosynthetics with different *** SFM geopolymer was then applied in the form of potting to cure the granulated mercury *** inclusion of 50%SFM material generated a geosynthetic that reduced mercury transport to the surface soil by roughly 90%.The mercury concentration of herbaceous plant samples was also reduced by 78%.It indicates that the SFM material can effectively attenuate the migration transformation of ***,characterization methods such as XPS and FTIR were used to investigate the mechanism of Hg^(2+)solidification by geopolymers generated by SFM *** possible solidification mechanisms were proposed as alkaline environment-induced mercury precipitation,chemical bonding s,surface adsorption of Hg^(2+)and its precipitates by the geopolymer,and physical encapsulation.

关键词： Mercury Geopolymer Solidification Tailings

On Halmos'third problem on Banach spaces

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Science China Mathematics 2025年第2期68卷 399-420页

作者： Lixin Cheng Junsheng fang Chunlan Jiang School of Mathematical Sciences Xiamen UniversityXiamen 361005China School of Mathematical Sciences Hebei Normal UniversityShijiazhuang 050016China

In 1970,Halmos posed ten open problems in Hilbert *** third problem asks:If an intransitive operator T has an inverse,is its inverse also intransitive?This question is closely related to the invariant subspace *** Enflo's celebrated counterexample on l_(1)provided a negative answer to the invariant subspace problem,the Banach space version of Halmos'third problem has attracted increasing *** this paper,we provide an affirmative answer to this problem under certain spectral *** an application,we show that for an invertible operator T with Dunford's property(C),if T-1is intransitive and there exists a connected componentΩof intσ(T-1)^(^)off the origin and satisfiesΩ∩ρF(T-1)≠φ,then T is also ***,we show that a necessary and sufficient condition for the existence of a bounded linear operator without nontrivial invariant subspaces on the infinite-dimensional space L1(Ω,Σ,μ)(resp.C(K),the space of bounded continuous functions on a complete metric space K)is that(Ω,Σ,μ)isσ-finite(resp.K is compact).

关键词： invariant subspace bounded linear operator Banach space

Understanding the iodine electrochemical behaviors in aqueous zinc batteries

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Journal of Energy Chemistry 2025年第2期101卷 402-415页

作者： Xuefang Xie Xiaoxin Xu Shuquan Liang Guozhao fang College of Physical Science and Technology Xinjiang University Xinjiang Key Laboratory of Solid State Physics and Devices Xinjiang University School of Materials Science & Engineering Key Laboratory of Electronic Packaging and Advanced Functional Materials of Hunan Province Central South University National Energy Metal Resources and New Materials Key Laboratory Central South University

Iodine is widely used in aqueous zinc batteries（ZBs） due to its abundant resources,low cost,and active redox *** addition to the active material in zinc-iodine batteries,iodine also plays an important role in other ZBs,such as regulating the electrochemical behavior of zinc ions,promoting the reaction kinetic and reversibility of other redox pairs,catalytic behaviors related to iodine reactions,coupling with other halogen ions,shuttle behaviors of polyiodides,***,there is currently a lack of comprehensive discussion on these ***,this review provides a comprehensive overview of the electrochemical behaviors of iodide in the aqueous *** effect of iodine ions on the Zn2+desolvation behaviors and the interfacial behaviors of Zn anode was *** redox pairs boosting other redox pairs,such as MnO2/Mn2+redox pair and vanadium redox pair to obtain high reversibility and capacity was also ***,the catalytic behaviors related to iodine reactions in aqueous ZBs,synergistic reaction with other halogen ions and suppression of shuttle behaviors for high performance zinc-iodine batteries were systematically ***,future prospects for designing effective iodine electrochemical behaviors with practicability are proposed,which will provide scientific guidance for the practical application of iodine-related aqueous ZBs.

关键词： Catalytic behavior Iodide ion Redox pairs Shuttle effect Zinc batteries

Improved activity and stability of noble metal-free oxygen reduction reaction electrocatalysts

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Science China Materials 2025年第2期68卷 677-678页

作者： Shurui Xu Guoyu Zhong Baizeng fang School of Chemical Engineering and Energy Technology Dongguan University of TechnologyDongguan 523808China

The wider commercialization of Proton Exchange Membrane Fuel Cells(PEMFCs)has been significantly hampered by the expensive noble metal catalysts[1],slow oxygen reduction reaction(ORR)and low electrochemical stability of the electrocatalyst[2].The development of noble metal-free electrocatalysts can significantly reduce the manufacturing cost of *** nitrogen-coordinated FeN4 sites are considered to be active for ORR[3,4],their catalytic performance and durability need to be significantly ***,Wu et al.

关键词： noble stability catalysts

Zooplankton community composition in summers of 2021and 2022 in the northern East China Sea and Yellow Sea,and their linkage with abiotic and biotic factors

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Journal of Oceanology and Limnology 2025年第1期43卷 159-176页

作者： Dongjie GUO fang ZHANG Shuangyan ZHANG Song SUN CAS Key Laboratory of Marine Ecology and Environmental Sciences Institute of OceanologyChinese Academy of SciencesQingdao 266071China College of Marine Science University of Chinese Academy of SciencesQingdao 266071China Jiaozhou Bay National Marine Ecosystem Research Station Institute of OceanologyChinese Academy of SciencesQingdao 266071China

The northern East China Sea and Yellow Sea are highly dynamic marginal seas,serving as important fishing grounds and primary areas for *** zooplankton community structure,including abundance,biovolume,and normalized biovolume size spectra(NBSS)within this ecosystem in summers 2021 and 2022 was assessed through ZooScan digital imaging *** abundances of zooplankton in summers 2021 and 2022 were 3364.22±2190.53 and 4435.52±2520.06 inds./m^(3),respectively,whereas the corresponding biovolumes were 649.10±519.63 and 1064.86±1254.87 mm^(3)/m^(3),*** copepods as the dominant zooplankton functional group in terms of abundance in both years,while chaetognath and medusae were the dominant groups in terms of *** dominance of medusae and chaetognath in terms of biovolume,along with the flatter slopes of NBSS compared to a stable community,indicated that more energy accumulated in gelatinous organisms within the study *** were significant positive relationships between temperature and tunicates or medusae,with a significantly higher population size observed in summer 2022 than in *** lower abundance and biovolume of zooplankton,mainly of small copepods,in summer 2021 may be related to the larger population size of the large jellyfish and the proliferation of green *** investigation provided basic data and fundamental insights for achieving a comprehensive understanding of zooplankton community structure and their long-term dynamics.

关键词： zooplankton community spatial distribution global warming Nemopilema nomurai Ulva prolifera