检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Cheng, Sibo Bocquet, Marc Ding, Weiping Finn, Tobias Sebastian Fu, Rui Fu, Jinlong Guo, Yike Johnson, Eleda Li, Siyi Liu, Che Moro, Eric Newton Pan, Jie Piggott, Matthew Quilodran, Cesar Sharma, Prakhar Wang, Kun Xiao, Dunhui Xue, Xiao Zeng, Yong Zhang, Mingrui Zhou, Hao Zhu, Kewei Arcucci, Rossella CEREA ENPC EDF R&D Institut Polytechnique de Paris Île-de-France France School of Artificial Intelligence and Computer Science Nantong University Jiangsu Nantong226019 China School of Mathematical Sciences Key Laboratory of Intelligent Computing and Applications Tongji University Shanghai200092 China School of Engineering and Materials Science Faculty of Science and Engineering Queen Mary University of London LondonE1 4NS United Kingdom Zienkiewicz Centre for Modelling Data and AI Faculty of Science and Engineering Swansea University SwanseaSA1 8EN United Kingdom Department of Computer Science and Engineering Hong Kong university of science and technology Hong Kong Department of Earth Science & Engineering Imperial College London LondonSW7 2AZ United Kingdom Tianjin Key Laboratory of Imaging and Sensing Microelectronics Technology School of Microelectronics Tianjin University Tianjin300072 China Centre for Health Informatics Cumming School of Medicine University of Calgary CalgaryABT2N 1N4 Canada Department of Community Health Sciences Cumming School of Medicine University of Calgary CalgaryABT2N 1N4 Canada Undaunted Grantham Institute for Climate Change and the Environment Imperial College London LondonSW7 2AZ United Kingdom Culham Campus AbingdonOX14 3DB United Kingdom Centre for Computational Science Department of Chemistry University College London LondonWC1E 6BT United Kingdom Concordia Institute for Information Systems Engineering Concordia University MontrealQCH3G 1M8 Canada School of Mechanical Medical and Process Engineering Faculty of Engineering Queensland University of Technology BrisbaneQLD Australia Department of Chemical Engineering University College London LondonWC1E 6BT United Kingdom

Unstructured grid data are essential for modelling complex geometries and dynamics in computational physics. Yet, their inherent irregularity presents significant challenges for conventional machine learning (ML) techniques. This paper provides a comprehensive review of advanced ML methodologies designed to handle unstructured grid data in high-dimensional dynamical systems. Key approaches discussed include graph neural networks, transformer models with spatial attention mechanisms, interpolation-integrated ML methods, and meshless techniques such as physics-informed neural networks. These methodologies have proven effective across diverse fields, including fluid dynamics and environmental simulations. This review is intended as a guidebook for computational scientists seeking to apply ML approaches to unstructured grid data in their domains, as well as for ML researchers looking to address challenges in computational physics. It places special focus on how ML methods can overcome the inherent limitations of traditional numerical techniques and, conversely, how insights from computational physics can inform ML development. To support benchmarking, this review also provides a summary of open-access datasets of unstructured grid data in computational physics. Finally, emerging directions such as generative models with unstructured data, reinforcement learning for mesh generation, and hybrid physics-data-driven paradigms are discussed to inspire future advancements in this evolving field. © 2025, CC BY-NC-SA.

关键词： Mesh generation

来源：评论

学校读者我要写书评

暂无评论

Investigation of mechanical behavior of Ag/Cu bilayer using nanoindentation test

引用

AIP Conference Proceedings 2024年第1期3241卷

作者： Rachid Herbazi Hassane Mes-adi Meryem Taoufiki Amine El Harfouf Khalid Amechnoue Adil Chahboun Intelligent Systems and Applications Laboratory (LSIA) EMSI Tangier Morocco Laboratory of Process Engineering Computer Science and Mathematics National School of Applied Sciences of Khouribga Sultan Moulay Slimane University Beni-Mellal Morocco Sustainable Development Laboratory Faculty of Science and Technology of Beni-Mellal Sultan Moulay Slimane University Beni-Mellal Morocco Multidisciplinary Laboratory of Research and Innovation (LaMRI) Energy Materials Atomic and Information Fusion (EMAFI) Team Polydisciplinary Faculty of Khouribga Sultan Moulay Slimane University Beni-Mellal Morocco. ERMIA National School of Applied Sciences Abdelmalek Essaadi University Tangier Morocco. ERCMN Faculty of Sciences and Technology Abdelmalek Essaadi University Tangier Morocco.

In this paper, we employed molecular dynamics (MD) simulations to model the nanoindentation process, aiming to explore the mechanical characteristics of a silver (Ag) coating film on a copper (Cu) substrate. Three distinct bilayer configurations were selected, namely Ag (100)/Cu (111), Ag (110)/Cu (111), and Ag (111)/Cu (111), with the purpose of examining the impact of heterogeneous interfaces on deformation behaviors during nanoindentation. The results demonstrate that the Ag (111)/Cu (111) bilayer exhibits a higher force during the nanoindentation process when compared to the Ag (100)/Cu (111) and Ag (110)/Cu (111) bilayers. This suggests that interfaces with a smaller mismatch in the specified crystal plane between Ag and Cu are proven to be harder. To studied the correlation between indentation velocity and the interface, we considered various values of indentation velocities ranging from 120 m/s to 200 m/s, conducting indentations on the Ag (111)/Cu (111) bilayer. The findings indicate that variations in indentation velocity significantly impact the mechanical properties of Ag (111)/Cu (111) bilayers. Both force and hardness values exhibit a significant increase as indentation velocity rises, implying that the strength of Ag/Cu bilayers is more pronounced at higher indentation velocities. These observed trends were attributed to defect and dislocation formation at the interface, as confirmed through dislocation extraction analysis (DXA).

关键词：

来源：评论

学校读者我要写书评

暂无评论

Atomically Precise Nanometer-Sized Pt Catalysts with an Additional Photothermy Functionality

引用

Angewandte Chemie 2024年第25期136卷

作者： Runguo Wang Dr. Dong Chen Dr. Liang Fang Dr. Wentao Fan Dr. Qing You Guoqing Bian Yue Zhou Dr. Wanmiao Gu Dr. Chengming Wang Dr. Licheng Bai Prof. Dr. Jin Li Prof. Dr. Haiteng Deng Dr. Lingwen Liao Prof. Dr. Jun Yang Prof. Dr. Zhikun Wu Key Laboratory of Materials Physics Anhui Key Laboratory of Nanomaterials and Nanotechnology CAS Center for Excellence in Nanoscience Institute of Solid State Physics HFIPS Chinese Academy of Sciences Hefei 230031 China Key Laboratory of Precision and Intelligent Chemistry University of Science and Technology of China Hefei 230026 P. R. China Institute of Physical Science and Information Technology Anhui University Hefei 230601 P.R. China State Key Laboratory of Multiphase Complex Systems Institute of Process Engineering Chinese Academy of Sciences Beijing 100190 P. R. China Instruments' Center for Physical Science University of Science and Technology of China Hefei 230026 P. R. China Shenzhen Engineering Center for the Fabrication of Two-Dimensional Atomic Crystals Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 P. R. China Tsinghua University-Peking University Joint Center for Life Sciences School of Life Sciences Tsinghua University Beijing 100084 P.R.China MOE Key Laboratory of Bioinformatics School of Life Sciences Tsinghua University Beijing 100084 P.R.China

Atomically precise ~1-nm Pt nanoparticles (nanoclusters, NCs) with ambient stability are important in fundamental research and exhibit diverse practical applications (catalysis, biomedicine, etc.). However, synthesizing such materials is challenging. Herein, by employing the mixture ligand protecting strategy, we successfully synthesized the largest organic-ligand-protected (~1-nm) Pt 23 NCs precisely characterized with mass spectrometry and single-crystal X-ray diffraction analyses. Interestingly, natural population analysis and Bader charge calculation indicate an alternate, varying charge -layer distribution in the sandwich-like Pt 23 NC kernel. Pt 23 NCs can catalyze the oxygen reduction reaction under acidic conditions without requiring calcination and other treatments, and the resulting specific and mass activities without further treatment are sevenfold and eightfold higher than those observed for commercial Pt/C catalysts, respectively. Density functional theory and d -band center calculations interpret the high activity. Furthermore, Pt 23 NCs exhibit a photothermal conversion efficiency of 68.4 % under 532-nm laser irradiation and can be used at least for six cycles, thus demonstrating great potential for practical applications.

关键词： Pt nanocluster atomically precise ambient stability ORR photothermy

来源：评论

学校读者我要写书评

暂无评论

Titelbild: Atomically Precise Nanometer-Sized Pt Catalysts with an Additional Photothermy Functionality (Angew. Chem. 25/2024)

引用

Angewandte Chemie 2024年第25期136卷

来源：评论

学校读者我要写书评

暂无评论

Cover Picture: Atomically Precise Nanometer-Sized Pt Catalysts with an Additional Photothermy Functionality (Angew. Chem. Int. Ed. 25/2024)

引用

Angewandte Chemie International Edition 2024年第25期63卷

来源：评论

学校读者我要写书评

暂无评论

Time Series Forecasting of New Cases and New Deaths Rate for COVID-19 using Deep Learning Methods

arXiv

引用

arXiv 2021年

作者： Ayoobi, Nooshin Sharifrazi, Danial Alizadehsani, Roohallah Shoeibi, Afshin Gorriz, Juan M. Moosaei, Hossein Khosravi, Abbas Nahavandi, Saeid Chofreh, Abdoulmohammad Gholamzadeh Goni, Feybi Ariani Klemeš, Jiří Jaromír Mosavi, Amir Department of Mathematics Savitribai Phule Pune University Pune411007 India Department of Computer Engineering School of Technical and Engineering Shiraz Branch Islamic Azad University Shiraz Iran Institute for Intelligent Systems Research and Innovation Deakin University GeelongVIC3216 Australia Computer Engineering Department Ferdowsi University of Mashhad Mashhad Iran Faculty of Electrical and Computer Engineering Biomedical Data Acquisition Lab K. N. Toosi University of Technology Tehran Iran Department of Signal Theory Networking and Communications Universidad de Granada Spain Department of Mathematics Faculty of Science University of Bojnord Iran Sustainable Process Integration Laboratory - SPIL NETME Centre Faculty of Mechanical Engineering Brno University of Technology - VUT Brno Technická 2896/2 Brno616 69 Czech Republic Department of Management Faculty of Business and Management Brno University of Technology VUT Brno Kolejní 2906/4 Brno612 00 Czech Republic Faculty of Civil Engineering Technische Universität Dresden Dresden01069 Germany John von Neumann Faculty of Informatics Obuda University Budapest1034 Hungary School of Economics and Business Norwegian University of Life Sciences 1430 Norway

The first known case of Coronavirus disease 2019 (COVID-19) was identified in December 2019. It has spread worldwide, leading to an ongoing pandemic, imposed restrictions and costs to many countries. Predicting the number of new cases and deaths during this period can be a useful step in predicting the costs and facilities required in the future. The purpose of this study is to predict new cases and deaths rate one, three and seven-day ahead during the next 100 days. The motivation for predicting every n days (instead of just every day) is the investigation of the possibility of computational cost reduction and still achieving reasonable performance. Such a scenario may be encountered real-time forecasting of time series. Six different deep learning methods are examined on the data adopted from the WHO website. Three methods are LSTM, Convolutional LSTM, and GRU. The bidirectional extension is then considered for each method to forecast the rate of new cases and new deaths in Australia and Iran countries. This study is novel as it carries out a comprehensive evaluation of the aforementioned three deep learning methods and their bidirectional extensions to perform prediction on COVID-19 new cases and new death rate time series. To the best of our knowledge, this is the first time that Bi-GRU and Bi-Conv-LSTM models are used for prediction on COVID-19 new cases and new deaths time series. The evaluation of the methods is presented in the form of graphs and Friedman statistical test. The results show that the bidirectional models have lower errors than other models. Several error evaluation metrics are presented to compare all models, and finally, the superiority of bidirectional methods is determined. This research could be useful for organizations working against COVID-19 and determining their long-term plans. Copyright © 2021, The Authors. All rights reserved.

关键词： Coronavirus

来源：评论

学校读者我要写书评

暂无评论

Meshless approach based on MLS with additional constraints for large deformation analysis

引用

Journal of Physics: Conference Series 2021年第1期1743卷

作者： R. El Kadmiri Y. Belaasilia A. Timesli M. S. Kadiri Sultan Moulay Slimane University National School of Applied Sciences of Khouribga (ENSAK) Laboratory of Process Engineering Computer Science and Mathematics Bd Beni Amir BP 77 Khouribga Morocco Hassan II University of Casablanca National Higher School of Arts and Crafts of Casablanca (ENSAM Casablanca) Laboratory of Structural Engineering Intelligent Systems and Electrical Energy 150 Avenue Nile Sidi Othman Casablanca 20670 Morocco Hassan II University of Casablanca Faculty of Sciences of Ben M'Sik LIMAT Laboratory B. P 7955 Sidi Othman Casablanca Morocco

In the present work, we are interested to develop a meshless approach, based on the strong form MLS approximation with additional constraints, to solve the nonlinear elastic and elsto-plastic problems for regular and irregular distribution of points. We adopt a plastic behavior law based on the total deformation theory, which is very convenient when the physical nonlinearity is more important than the effect of irreversible process and the loading history. In plasticity, one encounters discontinuities of rigidity where the application of asymptotic developments seems difficult or impossible. To apply the Taylor series expansion, regularization methods have been adapted. The strong form MLS approximation allows us to avoid the inconvenient of the numerical integration, while the asymptotic developments help us to reduce the computation cost observed in the incremental law of plasticity and the iterative methods. For irregular points distribution, we can get an ill-posed least squares problems due to a singular moment matrix of MLS approximation. To avoid this difficulty, we propose a modified MLS approximation by introducing additional constraints which allows to increase the error functional used in the derivation of the shape functions.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A coupled Meshless-FEM method based on strong form of Radial Point Interpolation Method (RPIM)

引用

Journal of Physics: Conference Series 2021年第1期1743卷

In this present work, we are implementing a novel hybrid method based on the coupling of RPIM in strong form and Finite Element Method (FEM). The basic idea is to ensure the coupling between the two methods through the collocation technique based on RPIM interpolation. This technique is used to evaluate the local equations of the problem at the interface between FEM and RPIM regions. We can avoid numerical integrations of a big part of nodes using the strong form of RPIM. Numerical studies show that this method gives reasonably accurate results consistent with the theory.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Secure analysis of dynamic networks under pinning attacks against synchronization

arXiv

引用

arXiv 2019年

作者： Li, Yuzhe Shi, Dawei Chen, Tongwen State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110004 State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 1H9 Canada

In this paper, we first consider a pinning node selection and control gain co-design problem for complex networks. A necessary and sufficient condition for the synchronization of the pinning controlled networks at a homogeneous state is provided. A quantitative model is built to describe the pinning costs and to formulate the pinning node selection and control gain design problem for different scenarios into the corresponding optimization problems. Algorithms to solve these problems efficiently are presented. Based on the developed results, we take the existence of a malicious attacker into consideration and a resource allocation model for the defender and the malicious attacker is described. We set up a leader-follower Stackelberg game framework to study the behaviour of both sides and the equilibrium of this security game is investigated. Numerical examples and simulations are presented to demonstrate the main results. Copyright © 2019, The Authors. All rights reserved.

关键词： Complex networks

来源：评论

学校读者我要写书评

暂无评论

Determination of time-and size-dependent fine particle emission with varied oil heating in an experimental kitchen

引用

Journal of Environmental Sciences 2017年第1期29卷 157-164页

作者： Shuangde Li Jiajia Gao Yiqing He Liuxu Cao Ang Li Shengpeng Mo Yunfa Chen Yaqun Cao State Key Laboratory of Multi-phase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China Key Laboratory of Healthy&Intelligent Kitchen System Integration ZhejiangNingbo315336China University of Chinese Academy of Sciences Beijing 100049China

Particulate matter（PM） from cooking has caused seriously indoor air pollutant and aroused risk to human *** is urged to get deep knowledge of their spatial-temporal distribution of source emission characteristics,especially ultrafine particles（UFP ＆lt; 100 nm） and accumulation mode particles（AMP 100-555 nm）.Four commercial cooking oils are auto dipped water to simulate cooking fume under heating to 255℃ to investigate PM emission and decay features between 0.03 and 10 μm size dimension by electrical low pressure impactor（ELPI） without *** and sunflower produced high PM_（2.5） around5.1 mg/m^3,in comparison with those of soybean and corn（5.87 and 4.55 mg/m^3,respectively）at peak emission time between 340 and 450 sec since heating oil,but with the same level of particle numbers 6-9 × 10~5/cm^*** values of PM_（1.0）/PM_（2.5） and PM_（2.5）/PM_（10） at peak emission time are around 0.51-0.55 and *** 15 min naturally deposition,decay rates of PM_（1.0）,PM_（2.5） and PM_（10） are 13.3%-29.8%,20.1%-33.9%and 41.2%-54.7%,which manifest that PM_（1.0） is quite hard to decay than larger particles,PM_（2.5） and PM_（1.0）.The majority of the particle emission locates at 43 nm with the largest decay rate at 75%,and shifts to a larger size between137 and 555 nm after 15 min *** decay rates of the particles are sensitive to the oil type.

关键词： Cooking fume Ultrafine particle Number concentration Size distribution Emission character

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：