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Structural evolution and high-temperature sensing performance of polymer-derived SiAlBCN ceramics

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Journal of Advanced Ceramics 2024年第4期13卷 478-485页

作者： Chao Ma Kun Liu Pengfei Shao Daoyang Han Kang Wang Mengmeng Yang Rui Zhao Hailong Wang Rui Zhang Gang Shao School of Materials Science and engineering Zhengzhou UniversityZhengzhou 450001China Zhongyuan Critical Metal lab.ratory Zhengzhou UniversityZhengzhou 450001China State key lab.ratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentZhengzhou UniversityZhengzhou 450002China

In situ temperature monitoring has become extremely imperative in high-temperature harsh environments and polymer-derived ceramics(PDCs)as sensing materials have attracted great ***,the stability and oxidation/corrosion resistance of PDCs cannot be simultaneously achieved at the moment,limiting their practical ***,polymer-derived SiAlBCN ceramics were synthesized via polymer conversion method under different pyrolysis *** microstructure evolution,high temperature sensing properties,and stability were investigated in *** results show that the amorphous SiAlBCN phase grows more orderly and the size of the free carbon phase enlarges with the increasing *** defect concentration displays a decreasing ***,the SiAlBCN ceramics as sensing materials exhibit a good temperature-resistance property from roo temperature to 1100℃.The fabricated SiAlBCN temperature sensor possesses excellent stability,repeatability,and ***,SiAlBCN ceramics exhibit distinguished oxidation/corrosion resistance after 100 h treatment at 1200℃in a water/oxygen environment,which is attributed to their low corrosive rate constant(0.57 mg/(cm^(2)·h))and oxidative rate constant(3.43 mg^(2)/(cm^(4)·h)).Therefore,polymer-derived SiAlBCN ceramics as sensing materials,which possess outstanding stability and oxidation/corrosion resistance,have great potential for in-situ monitoring of extreme environmental temperatures in the future.

关键词： polymer-derived SiAlBCN ceramics temperature sensor harsh environments oxidation and corrosion resistance

SMEC:Scene Mining for E-Commerce

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Journal of Computer Science & Technology 2024年第1期39卷 192-210页

作者：王罡李翔郭子义殷大伟马帅 State key lab.ratory of software Development Environment Beihang UniversityBeijing 100191China School of Data Science and engineering East China Normal UniversityShanghai 200062China *** Inc.Beijing 100176China Baidu Inc.Beijing 100085China

Scene-based recommendation has proven its usefulness in E-commerce,by recommending commodities based on a given ***,scenes are typically unknown in advance,which necessitates scene discovery for *** this article,we study scene discovery for E-commerce *** first formalize a scene as a set of commodity cate-gories that occur simultaneously and frequently in real-world situations,and model an E-commerce platform as a heteroge-neous information network(HIN),whose nodes and links represent different types of objects and different types of rela-tionships between objects,*** then formulate the scene mining problem for E-commerce as an unsupervised learning problem that finds the overlapping clusters of commodity categories in the *** solve the problem,we pro-pose a non-negative matrix factorization based method SMEC(Scene Mining for E-Commerce),and theoretically prove its *** six real-world E-commerce datasets,we finally conduct an extensive experimental study to evaluate SMEC against 13 other methods,and show that SMEC consistently outperforms its competitors with regard to various evaluation measures.

关键词： graph clustering E-commerce heterogeneous information network(HIN) scene mining

Enhancement of ionic conductivity and fracture toughness by infiltrating porous Li_(0.33)La_(0.56)TiO_(3) pellets

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Journal of Rare Earths 2024年第2期42卷 392-398,I0006页

作者： Xiaojuan Lu Mingyang Duan Jingyu Xiang Yuning Liang Songtao Liu Hebei key lab.of Power Plant Flue Gas Multi-Pollutants Control Department of Environmental Science and EngineeringNorth China Electric Power UniversityBaoding071003China

Although solid-state lithium electrolytes have the potential to reduce the safety issues associated with organic liquid electrolytes,disadvantages such as low total conductivity,large interface impedance,and delamination of the interface due to cyclic stress still need to be *** solid-state lithium-ion conductor Li_(0.33)La_(0.56)TiO_(3)(LLTO) was prepared via a hydrothermal route by using CTAB as templates in this *** LLTO with micro-porous channels was obtained and the total conductivity is comparable to the non-porous *** LLTO pellets are infiltrated with the non-porous LLTO precursor solution,and the total conductivities of the infiltrated porous LLTO are all higher than those without *** infiltration,the porous LLTO calcined at 600℃ achieves the highest total conductivity,7.88×10^(-5) S/*** fracture toughness of the infiltrated LLTO is higher than that of the non-porous *** results demonstrate a new way to prepare solid-state lithium-ion conductors with high ionic conductivity and great tolerance to cyclic stress.

关键词： Perovskite Porous material Infiltration Ionic conductors Fracture toughness Rare earths

TSCND:Temporal Subsequence-Based Convolutional Network with Difference for Time Series Forecasting

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Computers, Materials & Continua 2024年第3期78卷 3665-3681页

作者： Haoran Huang Weiting Chen Zheming Fan MOE Research Center of software/Hardware Co-Design engineering East China Normal UniversityShanghai200062China

Time series forecasting plays an important role in various fields, such as energy, finance, transport, and weather. Temporal convolutional networks (TCNs) based on dilated causal convolution have been widely used in time series forecasting. However, two problems weaken the performance of TCNs. One is that in dilated casual convolution, causal convolution leads to the receptive fields of outputs being concentrated in the earlier part of the input sequence, whereas the recent input information will be severely lost. The other is that the distribution shift problem in time series has not been adequately solved. To address the first problem, we propose a subsequence-based dilated convolution method (SDC). By using multiple convolutional filters to convolve elements of neighboring subsequences, the method extracts temporal features from a growing receptive field via a growing subsequence rather than a single element. Ultimately, the receptive field of each output element can cover the whole input sequence. To address the second problem, we propose a difference and compensation method (DCM). The method reduces the discrepancies between and within the input sequences by difference operations and then compensates the outputs for the information lost due to difference operations. Based on SDC and DCM, we further construct a temporal subsequence-based convolutional network with difference (TSCND) for time series forecasting. The experimental results show that TSCND can reduce prediction mean squared error by 7.3% and save runtime, compared with state-of-the-art models and vanilla TCN.

关键词： Difference data prediction time series temporal convolutional network dilated convolution

Probabilistic analysis of tunnel face seismic stability in layered rock masses using Polynomial Chaos Kriging metamodel

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Journal of Rock Mechanics and Geotechnical engineering 2024年第7期16卷 2678-2693页

作者： Jianhong Man Tingting Zhang Hongwei Huang Daniel Dias Department of Geotechnical engineering Key Laboratory of Geotechnical and Underground Engineering of Ministry of EducationCollege of Civil EngineeringTongji UniversityShanghai200092China Grenoble Alpes 3SR LabCNRS UMR 5521Grenoble38000France

Face stability is an essential issue in tunnel design and *** rock masses are typical and ubiquitous;uncertainties in rock properties always *** view of this,a comprehensive method,which combines the Upper bound Limit analysis of Tunnel face stability,the Polynomial Chaos Kriging,the Monte-Carlo Simulation and Analysis of Covariance method(ULT-PCK-MA),is proposed to investigate the seismic stability of tunnel faces.A two-dimensional analytical model of ULT is developed to evaluate the virtual support force based on the upper bound limit *** efficient probabilistic analysis method PCK-MA based on the adaptive Polynomial Chaos Kriging metamodel is then implemented to investigate the parameter uncertainty *** input parameters,including geological strength indices,uniaxial compressive strengths and constants for three rock formations,and the horizontal seismic coefficients,are treated as random *** effects of these parameter uncertainties on the failure probability and sensitivity indices are *** addition,the effects of weak layer position,the middle layer thickness and quality,the tunnel diameter,the parameters correlation,and the seismic loadings are investigated,*** results show that the layer distributions significantly influence the tunnel face probabilistic stability,particularly when the weak rock is present in the bottom *** efficiency of the proposed ULT-PCK-MA is validated,which is expected to facilitate the engineering design and construction.

关键词： Tunnel face stability Layered rock masses Polynomial Chaos Kriging(PCK) Sensitivity index Seismic loadings

XRL-SHAP-Cache:an explainable reinforcement learning approach for intelligent edge service caching in content delivery networks

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Science China(Information Sciences) 2024年第7期67卷 46-71页

作者： Xiaolong XU Fan WU Muhammad BILAL Xiaoyu XIA Wanchun DOU Lina YAO Weiyi ZHONG School of software Nanjing University of Information Science and Technology School of Computing and Communications Lancaster University School of Computing Technologies Royal Melbourne Institute of Technology State key lab.ratory for Novel software Technology Nanjing University School of Computer Science and engineering University of New South Wales Data 61 Commonwealth Scientific and Industrial Research Organization School of Computer Science Qufu Normal University

Content delivery networks(CDNs) play a pivotal role in the modern internet infrastructure by enabling efficient content delivery across diverse geographical regions. As an essential component of CDNs, the edge caching scheme directly influences the user experience by determining the caching and eviction of content on edge servers. With the emergence of 5G technology, traditional caching schemes have faced challenges in adapting to increasingly complex and dynamic network environments. Consequently, deep reinforcement learning(DRL) offers a promising solution for intelligent zero-touch network governance. However, the blackbox nature of DRL models poses challenges in understanding and making trusting decisions. In this paper,we propose an explainable reinforcement learning(XRL)-based intelligent edge service caching approach,namely XRL-SHAP-Cache, which combines DRL with an explainable artificial intelligence(XAI) technique for cache management in CDNs. Instead of focusing solely on achieving performance gains, this study introduces a novel paradigm for providing interpretable caching strategies, thereby establishing a foundation for future transparent and trustworthy edge caching solutions. Specifically, a multi-level cache scheduling framework for CDNs was formulated theoretically, with the D3QN-based caching scheme serving as the targeted interpretable model. Subsequently, by integrating Deep-SHAP into our framework, the contribution of each state input feature to the agent's Q-value output was calculated, thereby providing valuable insights into the decision-making process. The proposed XRL-SHAP-Cache approach was evaluated through extensive experiments to demonstrate the behavior of the scheduling agent in the face of different environmental *** results demonstrate its strong explainability under various real-life scenarios while maintaining superior performance compared to traditional caching schemes in terms of cache hit ratio, quality of service(QoS),a

关键词： deep reinforcement learning (DRL) explainable artificial intelligence (XAI) multi-level cache content delivery network (CDN) D3QN algorithm Deep-SHAP

Anti-saturation fault-tolerant adaptive torsional vibration control with fixed-time prescribed performance for rolling mill main drive system

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Journal of Iron and Steel Research International 2024年第3期31卷 660-669页

作者： Shuang Liu Chen Du Cong Zhang Zhen-hua Bai key lab.of Industrial Computer Control engineering of Hebei Province Yanshan UniversityQinhuangdao 066004HebeiChina National engineering Research Center for Equipment and Technology of Cold Strip Rolling Yanshan UniversityQinhuangdao 066004HebeiChina

An anti-saturation fault-tolerant adaptive torsional vibration control method with fixed-time prescribed performance for the rolling mill main drive system(RMMDS)was investigated,which is affected by control input saturation,actuator faults,sensor measurement errors,and parameter ***,we gave a continuously differentiable saturation function to approximate the control input saturation characteristic of the RMMDS,translating the saturation characteristic into the matched uncertainty and unknown time-varying gain in the ***,an RMMDS mathematical model with unmatched uncertainty and unknown time-varying gain was developed,taking into account the presence of control input saturation,actuator faults,sensor measurement errors,and parameter *** on the established mathematical model,an error transformation model of the roll speed tracking was constructed by the equivalent error transformation *** to the error transformation model,a barrier Lyapunov function and a novel adaptive controller were studied to ensure that the roll speed tracking error always evolves inside a fixed-time asymmetric ***,numerical simulations were performed in Matlab.Simulink to verify the effectiveness and superiority of the proposed control method in suppressing the RMMDS torsional vibration.

关键词： Fixed-time prescribed performance Control input saturation Actuator fault Unknown time-varying gain Adaptive control Asymmetric constraint

Potential application of radiant floor cooling systems for residential buildings in different climate zones

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Building Simulation 2024年第4期17卷 543-560页

作者： Mengying Cui Yang Song Yudong Mao Kaimin Yang Jiying Liu Zhe Tian School of Thermal engineering Shandong Jianzhu UniversityJinan250101China School of Environmental Science and engineering Tianjin UniversityTianjin300072China key lab.of Building Environment and Energy of Tianjin Tianjin UniversityTianjin300072China

A radiant floor cooling system(RFCS)is a high-comfort and low energy consumption system suitable for residential *** floor systems usually work with fresh air,and their operating performance is affected by climatic *** and outdoor environmental disturbances and the system’s control strategy affect the indoor thermal comfort and energy efficiency of the ***,a multi-story residential building model was established in this *** system simulation program was used to study the operation dynamics of three control strategies of the RFCS based on the calibrated ***,the performance of the control strategies in five climate zones in China were compared using multi-criteria decision-making in *** results show that control strategy has a negligible effect on condensation risk,but the thermal comfort and economic performance differ for different control *** adaptability of different control strategies varies in different climate zones based on the consideration of multiple *** performance of the direct-ground cooling source system is better in Hot summer and warm winter *** variable air volume control strategy scores higher in Serve cold and Temperate zones,and the hours exceeding thermal comfort account for less than 3%of the total simulation ***,it is suggested to choose the RFCS control strategy for residential buildings according to the climate zone characteristics,to increase the energy *** results provide a reliable reference for implementing RFCSs in residential buildings.

关键词： control strategy radiant floor cooling system residential building energy efficiency climate zones

Toughened (Ti_(0.2)Zr_(0.2)Hf_(0.2)Nb_(0.2)Ta_(0.2))B_(2)–SiC composites fabricated by one-step reactive sintering with a unique SiB_(6) additive

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Journal of Advanced Ceramics 2024年第1期13卷 86-100页

作者： Wei Hao Xinzhe Lu Ling Li Tao Wang Guoliang Ren Huangyue Cai Xiaofeng Zhao Dongyun Wang Na Ni Zhejiang Provincial key lab.ratory of Urban Rail Transit Intelligent Operation and Maintenance Technology&Equipment Zhejiang Normal UniversityZhejiang 321004China key lab.of Education Ministry for Power Machinery and engineering School of Mechanical EngineeringShanghai Jiao Tong UniversityShanghai 200240China School of Materials Science and engineering Shanghai Jiao Tong UniversityShanghai 200240China

High-entropy diboride has been arousing considerable interest in recent ***,the low toughness and damage tolerance limit its applications as ultra-high-temperature structural *** we report that a unique SiB_(6) additive has been first incorporated as boron and silicon sources to fabricate a high-entropy boride(Ti_(0.2)Zr_(0.2)Hf_(0.2)Nb_(0.2)Ta_(0.2))B_(2)–SiC composite though one-step boro/carbothermal reduction reactive sintering.A synergetic effect of high-entropy sluggish diffusion and SiC secondary phase retarded the grain growth of the(Ti_(0.2)Zr_(0.2)Hf_(0.2)Nb_(0.2)Ta_(0.2))B_(2)–51SiC *** small grain size was beneficial to shorten the diffusion path for mass transport,thereby enhancing the relative density to~99.3%.These results in an increase of fracture toughness from~5.2 in HEBS-1900 to~7.7 MPa·m^(1/2) in HEBS-2000,which corresponded to a large improvement of 48%.The improvement was attributed to a mixed mode of intergranular and transgranular cracking for offering effective pinning in crack propagation,resulting from balanced grain boundary strength collectively affected by improved densification,solid solution strengthening,and incorporation of SiC secondary phase.

关键词： high-entropy diboride silicon hexaboride boro/carbothermal reduction reactive sintering fracture toughness