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Effects of calendering state on coupled electrochemical-mechanical performance of silicon based composite electrodes

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Green Energy and Intelligent Transportation 2024年第5期3卷 34-41页

作者： Dawei Li Hongfei Wan Jiahui Liu Hainan Jiang Yikai Wang Junqian Zhang Yuejiu Zheng School of Mechanical Engineering University of Shanghai for Science and TechnologyShanghai 200093China Department of Engineering Physics Tsinghua UniversityBeijing100084China Department of Chemical and Materials Engineering University of KentuckyLexingtonKY 40506USA Shanghai Institute of Applied Mathematics and Mechanics School of Mechanics and Engineering ScienceShanghai UniversityShanghai 200444China

The super volume changes and severe mechanical degradation have been a hindrance in the wide application of silicon based composite electrodes in commercial lithium-ion batteries(LIBs).Calendering,one procedure in producing LIBs'electrodes,is indispensable to ensure low porosity and energy ***,the repercussions of the calendering process on the physical characteristics related to the behavior of silicon(Si)based electrodes during the electrochemical reaction have not been well ***,on account of the deformation characteristic of cantilever electrodes,an in-situ technique is employed to analyze the repercussions of calendering status on the coupled electro-chemo-mechanical *** the electrochemical cycling,Young's modulus and diffusion-induced stress in composite electrodes are *** results show that the swelling strain,the stress and the modulus of the Si-based electrode and the calendering degree are positively ***,the stress induced by diffusion in the active layer tends to increase in the stage of lithiation and reverses during the delithiation *** with the SEM analysis,we conclude that the calendering process can induce larger stress,driving the formation of cracks in *** findings can help understand how the calendering process could affect the capacity dissipating and lifetime of Si based electrodes.

关键词： Calendering degree In situ measurement Coupled electro-mechan-chemical properties Si composite electrode Stress evolution

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CyberSCADA Network Security Analysis Model for Intrusion Detection Systems in the Smart Grid

CyberSCADA Network Security Analysis Model for Intrusion Det...

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作者： Efiong, John E. Akinyemi, Bodunde O. Olajubu, Emmanuel A. Aderounmu, Ganiyu A. Degila, Jules Department of Computer Science and Engineering African Centre of Excellence Obafemi Awolowo University Ile-Ife Nigeria Institute of Mathematics and Physics African Centre of Excellence in Applied Mathematics and Computer Science University of Abomey-Calavi Godomey Benin

CyberSCADA is a soft target for industrial cyber attackers. The success of such attacks on the Smart Grid can be devastating owing to the countless processes and systems that depend on the Grid for daily operations. This paper demonstrates techniques and provides insights to help detect intrusions in the mission-critical business network as they target Cyber-Physical Systems. Several Machine Learning algorithms (ML) have been implemented at different phases of the ML pipeline in the study in view of identifying suitable models for the prediction and classifications. Ensemble classifiers have been found very potent for feature extraction and model boosting. Adaboost, GradientBoost and XGboost all yielded 99% for accuracy, precision, recall and F1-Score. During Training and Testing using 75% trainSet and 25% testSet ORNL Electric Testbed dataset, both Decision Tree (DT) and K-Neighbor (KNN) yielded the Accuracy, Precision, Recall and F1-Score 99% with a Detection Rate 63% and 80% respectively. Gaussian Naïve Bayes (GNB) produced the best Detection Rate 99% though with significantly low values for other metrics. At k-fold of 10 for cross-validation, RF yielded the best accuracy 100%, followed by DT 99%, KNN 98% and LogReg 92% with low False Positive Rates. The Area under ROC Curve shows RF 99%, KNN 99%, DT 96% and LogReg 95%. DT and KNN are considered suitable for the effective classification of attacks and prediction while GNB offers better attack detection for intrusion detections in the Grid network. Adaboost, GradientBoost and XGboost are crucial in boosting performances of ML algorithms in attack classification problems. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Decision trees

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The periodic product recommendation system based on deep reinforcement learning and the multi-objective framework 12

The periodic product recommendation system based on deep rei...

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12th International Conference on Awareness science and Technology, iCAST 2023

作者： Dat, Dang Tien Thang, Tran Ngoc Minh, Nguyen Anh Chen, Rung Ching Ngoc Anh, Nguyen Thi School of Applied Mathematics and Informatics Hanoi University of Science and Technology Viet Nam Big Data Lab CMC Institute of Science and Technology Viet Nam Department of Information Management Chaoyang University of Technology Taiwan

ISBN: (纸本)9798350324693

The primary objective of the recommendation system is to suggest suitable products to users. The need for a personalized recommendation system has become essential with the continuous growth in the number of users and the increasing diversity of products. In this paper, we proposed a novel approach that combines a reinforcement learning algorithm with user clustering to address the recommendation challenge for periodic products. Additionally, we extend our framework to accommodate multi-objective scenarios. Our contributions encompass the development of meaningful representation vectors for actions and states, along with the definition of reward vector aligning with users’ long-term preferences and optimizing profits. We apply our proposed method to the problem of recommending mobile packages in Vietnam. Notably, our approach yields favorable recommendation results and exhibits superior performance compared to alternative methods. © 2023 IEEE.

关键词： Reinforcement learning

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Stress-induced multiple quantum phase transitions in the B1 and B2 phases of CeN

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Physical Review B 2024年第12期109卷 125114-125114页

作者： Min Liu Yuanji Xu College of Mathematics and Physics Beijing University of Chemical Technology Beijing 100029 China Institute for Applied Physics University of Science and Technology Beijing Beijing 100083 China

The quantum phase transition in Ce-based compounds has attracted significant attention in strongly correlated systems, primarily due to the dual nature of f electrons. Rare-earth nitride (Re-N) compounds are particularly intriguing, as they exhibit major physical mechanisms such as the Kondo effect or mixed-valence behavior. Notably, CeN is anomalously small in lattice parameter compared with other Re-N compounds and there is a structure phase transition from B1-type (NaCl-type) to B2−type (CsCl-type) at approximately 77 GPa. Hence, we study the electronic structures of B1-type and B2−type CeN by tuning stress, employing the DFT+DMFT method. Our results clarify the B1-type CeN is in a mixed-valence state at ambient pressure. However, as the system experiences compression and tension, CeN undergoes multiple quantum phase transitions, transitioning from a mixed-valence state to a Kondo metal and ultimately to an insulator. Importantly, it is observed that the number of occupied 4f electrons nf of Ce increases as the temperature and pressure increase within the mixed-valence regime, contrasting with the behavior observed in the Kondo regime, the nf is very stable, nearly one. Furthermore, we also investigate the high-pressure phase of B2−type CeN, it also presents mixed-valence and Kondo metal phases transition by tuning stress. Our paper illustrates stress as a clean method to tune quantum phase transitions in CeN by changing the states of f electrons and clarifying the physical driving force of phase transitions.

关键词： Density of states Electrical properties Fermi surface First-principles calculations Flat bands Kondo effect Phase transitions Pressure effects Quantum phase transitions

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On the Uncrossed Number of Graphs 32

On the Uncrossed Number of Graphs

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32nd International Symposium on Graph Drawing and Network Visualization, GD 2024

作者： Balko, Martin Hliněný, Petr Masařík, Tomáš Orthaber, Joachim Vogtenhuber, Birgit Wagner, Mirko H. Department of Applied Mathematics Faculty of Mathematics and Physics Charles University Prague Czech Republic Faculty of Informatics Masaryk University Brno Czech Republic Institute of Informatics Faculty of Mathematics Informatics and Mechanics University of Warsaw Poland Institute of Software Technology Graz University of Technology Austria Institute of Computer Science Osnabrück University Germany

ISBN: (纸本)9783959773430

Visualizing a graph G in the plane nicely, for example, without crossings, is unfortunately not always possible. To address this problem, Masařík and Hliněný [GD 2023] recently asked for each edge of G to be drawn without crossings while allowing multiple different drawings of G. More formally, a collection D of drawings of G is uncrossed if, for each edge e of G, there is a drawing in D such that e is uncrossed. The uncrossed number unc(G) of G is then the minimum number of drawings in some uncrossed collection of G. No exact values of the uncrossed numbers have been determined yet, not even for simple graph classes. In this paper, we provide the exact values for uncrossed numbers of complete and complete bipartite graphs, partly confirming and partly refuting a conjecture posed by Hliněný and Masařík [GD 2023]. We also present a strong general lower bound on unc(G) in terms of the number of vertices and edges of G. Moreover, we prove NP-hardness of the related problem of determining the edge crossing number of a graph G, which is the smallest number of edges of G taken over all drawings of G that participate in a crossing. This problem was posed as open by Schaefer in his book [Crossing Numbers of Graphs 2018]. © Martin Balko, Petr Hliněný, Tomáš Masařík, Joachim Orthaber, Birgit Vogtenhuber, and Mirko H. Wagner.

关键词： Graph theory

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BIFURCATIONS AND INVARIANT SETS FOR A FAMILY OF REPLICATOR MAPS FROM EVOLUTIONARY GAMES

arXiv

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arXiv 2024年

作者： Kryzhevich, Sergey Zhang, Yiwei Chmara, Magdalena Institute of Applied Mathematics Faculty of Applied Physics and Mathematics Gdansk University of Technology Gdansk80-233 Poland School of Mathematical Sciences and Big Data Anhui University of Science and Technology Anhui Huainan232001 China

We study the dynamics of a family of replicator maps, depending on two parameters. Such studies are motivated by the analysis of the dynamics of evolutionary games under selections. From the dynamics viewpoint, we prove the existence of hyperbolic chaos for the considered map. Moreover, we also give a partial solution of an open problem formulated in [7]: to describe all the one-dimensional maps with all the periodic orbits having the same mean *** Codes 37E05 Copyright © 2024, The Authors. All rights reserved.

关键词： Bifurcation (mathematics)

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Efficiency Assessment of an institute Through Parallel Network data Envelopment Analysis 11th

Efficiency Assessment of an Institute Through Parallel Netwo...

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11th International Conference on Soft Computing for Problem Solving, SocProS 2022

作者： Kumar, Atul Panwar, Ankita Pant, Millie Department of Applied Mathematics and Scientific Computing Indian Institute of Technology Roorkee Roorkee247667 India Mehta Family School of Data Science and Artificial Intelligence Indian Institute of Technology Roorkee Roorkee247667 India

ISBN: (纸本)9789811965241

Conventional data envelopment analysis (DEA) is a non-parametric approach to examine the efficiency of similar decision-making units (DMUs) as a whole system without considering its internal structure, i.e., the system is considered as a black box. Therefore, a network DEA (NDEA) is needed to study the internal structure of a system. By allowing for the measurement of individual components, an NDEA model can reveal inefficiencies that a traditional DEA ignores. In this study, we use the parallel network DEA to calculate the efficiency of a higher education institute with 19 decision-making units (DMUs) using two parallel processes (teaching and research) and compare it with the conventional DEA, CCR model through a numerical example. The main advantages of the parallel NDEA model are (i) to identify which DMUs are inefficient and make necessary adjustments, and (ii) the parallel DEA model has a lower efficiency score than the traditional DEA model. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Efficiency

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A Mathematical Model to Minimize the Total Cultivation Cost of Sugarcane 11th

A Mathematical Model to Minimize the Total Cultivation Cost ...

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11th International Conference on Soft Computing for Problem Solving, SocProS 2022

作者： Kumar, Sumit Pant, Millie Department of Applied Mathematics and Scientific Computing Indian Institute of Technology Roorkee Uttarakhand Roorkee India Mehta Family School for Data Science and Artificial Intelligence Indian Institute of Technology Roorkee Uttarakhand Roorkee India

ISBN: (纸本)9789811965241

In the present study, a non-linear mathematical model is proposed to minimize the total expenditure made on sugarcane cultivation. The objective here is to optimize the costs involved in transportation, cultivation, and management of the deterioration of sugarcane. The optimization tools used are Differential Evolution (DE) and Particle Swarm Optimization (PSO). Further, the model is validated by comparing the actual expenditure of sugarcane cultivation with results obtained by PSO and DE, which indicates that the application of optimization methods may help in reducing the expenditure made on sugarcane cultivation. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deterioration

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Rayleigh-Taylor instability under multimode perturbation:Discrete Boltzmann modeling with tracers

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Communications in Theoretical physics 2022年第11期74卷 180-198页

作者： Hanwei Li Aiguo Xu Ge Zhang Yiming Shan Laboratory of Computational Physics Institute of Applied Physics and Computational MathematicsBeijing 100088China HEDPS Center for Applied Physics and TechnologyCollege of EngineeringPeking UniversityBeijing 100871China State Key Laboratory of Explosion Science and Technology Beijing Institute of TechnologyBeijing 100081China Energy Resources Engineering Department Stanford University367 Panama StStanfordCA 94305-2220United States of America

The two-dimensional Rayleigh-Taylor Instability(RTI)under multi-mode perturbation in compressible flow is probed via the Discrete Boltzmann Modeling(DBM)with *** distribution of tracers provides clear boundaries between light and heavy fluids in the position ***,the position-velocity phase space offers a new perspective for understanding the flow behavior of RTI with intuitive geometrical *** effects of viscosity,acceleration,compressibility,and Atwood number on the mixing of material and momentum and the mean nonequilibrium strength at the interfaces are investigated separately based on both the mixedness defined by the tracers and the non-equilibrium strength defined by the *** mixedness increases with viscosity during early stage but decreases with viscosity at the later ***,compressibility,and Atwood number show enhancement effects on mixing based on different *** the system relaxes from the initial state,the mean non-equilibrium strength at the interfaces presents an initially increasing and then declining trend,which is jointly determined by the interface length and the macroscopic physical quantity *** conclude that the four factors investigated all significantly affect early evolution behavior of an RTI system,such as the competition between interface length and macroscopic physical quantity *** results contribute to the understanding of the multi-mode RTI evolutionary mechanism and the accompanied kinetic effects.

关键词： Rayleigh-Taylor instability multi-mode perturbation Discrete Boltzmann modeling tracers non-equilibrium effects kinetic modeling

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Htem: High-Throughput Toolkit for Elasticity Modeling

SSRN

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SSRN 2025年

作者： Yang, Zhen Xian, Jiawei Xu, Yuanji Lin, De-Ye Wang, Qingchun Gao, Xingyu Tian, Fuyang Song, Haifeng Institute for Applied Physics University of Science and Technology Beijing Beijing100083 China National Key Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Beijing100094 China CAEP Software Center for High Performance Numerical Simulation Institute of Applied Physics and Computational Mathematics Beijing100094 China

The elasticity under varying temperatures and pressures is particularly significant for understanding mechanical properties and structural phase transitions. Consequently, there is an increasing demand for tools capable of determining elasticity across wide temperature and pressure ranges, either numerically or analytically. We propose HTEM, a comprehensive toolkit that automates the workflow for input generation, elastic calculations, modeling, and visualization within an integrated framework. HTEM performs simulations with four computational modes, allowing users to balance accuracy and efficiency. It incorporates a semi-analytic model for robust, high-precision elastic modeling with finite data combinations, even using sparse elasticity at high temperatures. To validate the workflows of calculation and modeling, we perform HTEM to study the elasticity of Si across wide temperature and pressure ranges. Results show the high precision and high efficiency of HTEM. And modeling mitigates noise from constant pressure ensemble simulations. Furthermore, HTEM provides detailed visualizations of elasticity and its anisotropy as functions of temperature and pressure, providing comprehensive insights into how the intrinsic properties of materials evolve under varying conditions. © 2025, The Authors. All rights reserved.

关键词： Elasticity

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