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Journal of Iron and Steel Research International 2024年第7期31卷 1763-1777页

作者： Chen-yang Jiang Xiao-qiang Li Jin-tao Wang Hao Luo sheng-qing Gao sheng-guan Qu Chao Yang National Engineering Research Centre of Near-Net-Shape Forming for Metallic Materials South China University of TechnologyGuangzhou 510640GuangdongChina Institute of New Materials Guangdong Academy of ScienceGuangzhou 510650GuangdongChina

To address the inhomogeneous microstructure and improve the mechanical properties of DT300 ultra-high strength steel specimens fabricated by laser powder bed fusion,different post-heat treatment schedules are *** the increase in austenitizing temperature and time,the migration rate of austenite grain boundaries continuously increases with the dissolution of nano-carbides,and the formation of nano-oxides and twin martensite is also inhibited *** rapid growth in the size of prior austenite grains and martensite laths,as well as the decrease in the content of nano-oxides and twin martensite,led to a rapid decrease in the strength(yield strength and ultimate tensile strength)from HT2 to HTF *** HT1 specimens(austenitizing at 830℃for 30 min,then oil quenching and tempering at 300℃for 120 min and finally air cooling)display excellent mechanical properties of yield strength of 1572 MPa,ultimate tensile strength of 1847 MPa,elongation of 9.84%,and fracture toughness of 106 MPa m^(1/2),which are counterparts to those of conventional DT300 steel forgings after heat treatment.

关键词： DT300 ultra-high strength steel Laser powder bed fusion-Short-time low-temperature austenitizing Microstructure Mechanical property

High Speed Sintering:Assessing the Influence of Energy Input on Microstructure and Mechanical Properties of Polyether Block Amide(PEBA)Parts

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Chinese Journal of Polymer Science 2024年第5期42卷 675-682,I0004,I0010页

作者： Jiang-tao Sun Zhi-Yong Fan Yi-Wei Mao Wei Li Wei Zhu Dao-sheng Cai qing-Song Wei State Key Laboratory of Materials Processing and Die&Mould Technology Huazhong University of Science and TechnologyWuhan430074China State Key Laboratory of Refractories and Metallurgy Wuhan University of Science and TechnologyWuhan430074China National Engineering Research Centre for High Efficiency Grinding Hunan UniversityChangsha410082China Wuhan EasyMFG Technology CO. LTDWuhan430074China

High speed sintering,a new powder-bed fusion additive manufacturing technology,utilizes infrared lights(IR)to intensely heat and melt polymer *** presence of defects such as porosity,which is associated with particle coalescence,is highly dependdent on the level of energy *** study investigate the influcence of energy input on porosity and its subsequent effects on the mechanical properties and microstructures of PEBA *** parts were manufactured with a variety of lamp powers,resulting in a range of energy input levels spanning from low to ***,they underwent testing using Archimedes’method,followed by tensile *** porosity,mechanical characteristics,and energy input exhibit a strong correlation;inadequate energy input was the primary cause of pore *** the reduced IR light power resulted in the following outcomes:porosity,ultimate tensile strength,and elongation of 1.37%,7.6 MPa,and 194.2%,*** the energy input was further increased,the porosity was reduced to as low as 0.05%and the ultimate tensile strength and elongation were increased to their peak values of 233.8%and 9.1 MPa,respectively.

关键词： High speed sintering Additive manufacturing Energy input Powder bed fusion PEBA

Limits of Riemann Solutions for Isentropic MHD in a Variable Cross-Section Duct as Magnetic Field Vanishes

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Chinese Annals of Mathematics,Series B 2024年第4期45卷 637-660页

作者： Wancheng sheng tao XIAO Department of Mathematics Shanghai University Shanghai Aircraft Design and Research Institute

The stability for magnetic field to the solution of the Riemann problem for the polytropic fluid in a variable cross-section duct is discussed. By the vanishing magnetic field method, the stable solutions are determined by comparing the limit solutions with the solutions of the Riemann problem for the polytropic fluid in a duct obtained by the entropy rate admissibility criterion.

关键词： 35L50 35L65 35L80 76J20 76N10 Magnetogasdynamics Riemann problem Stability Vanishing magnetic field method Variable duct

A deep learning model based on contrast-enhanced computed tomography for differential diagnosis of gallbladder carcinoma

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Hepatobiliary & Pancreatic Diseases International 2024年第4期23卷 376-384页

作者： Fei Xiang qing-tao Meng Jing-Jing Deng Jie Wang Xiao-Yuan Liang Xing-Yu Liu sheng Yan Department of Hepatobiliary Pancreatic Surgery Second Affiliated HospitalZhejiang University School of MedicineHangzhou 310003China Department of Radiology Affiliated Chuzhou First People’s HospitalAnhui Medical UniversityChuzhou 239000China

Background:Gallbladder carcinoma(GBC)is highly malignant,and its early diagnosis remains *** study aimed to develop a deep learning model based on contrast-enhanced computed tomography(CT)images to assist radiologists in identifying ***:We retrospectively enrolled 278 patients with gallbladder lesions(>10 mm)who underwent contrast-enhanced CT and cholecystectomy and divided them into the training(n=194)and validation(n=84)*** deep learning model was developed based on ResNet50 *** and clinical models were built based on support vector machine(SVM)*** comprehensively compared the performance of deep learning,radiomics,clinical models,and three ***:Three radiomics features including LoG_3.0 gray-level size zone matrix zone variance,HHL firstorder kurtosis,and LHL gray-level co-occurrence matrix dependence variance were significantly different between benign gallbladder lesions and GBC,and were selected for developing radiomics *** regression analysis revealed that age≥65 years[odds ratios(OR)=4.4,95%confidence interval(CI):2.1-9.1,P37 U/mL(OR=4.0,95%CI:1.6-10.0,P=0.003)were significant clinical risk factors of *** deep learning model achieved the area under the receiver operating characteristic curve(AUC)values of 0.864(95%CI:0.814-0.915)and 0.857(95%CI:0.773-0.942)in the training and validation datasets,which were comparable with radiomics,clinical models and three *** sensitivity of deep learning model was the highest both in the training[90%(95%CI:82%-96%)]and validation[85%(95%CI:68%-95%)]***:The deep learning model may be a useful tool for radiologists to distinguish between GBC and benign gallbladder lesions.

关键词： Gallbladder carcinoma Computed tomography Deep learning Radiomics

Day-ahead P2P Energy Sharing Strategy Among Energy Hubs Considering Flexibility of Energy Storage and Loads

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CSEE Journal of Power and Energy Systems 2024年第3期10卷 1105-1118页

作者： Penghua Li Wanxing sheng qing Duan Jun Liang Cunhao Zhu China Electric Power Research Institute Beijing 100192China School of Engineering Cardiff UniversityUK IEEE

Multi-energy systems are one of the key technologies to tackle energy crisis and environmental *** energy hub(EH)is a minimum multi-energy *** of multiple EHs through energy routers(ERs)can realize mutual energy *** paper proposes a peer-to-peer(P2P)energy sharing strategy between EHs including ERs in an interconnected system,which is divided into two *** the lower level,a method of determining the charging/discharging constraints of energy storage devices is *** on the Lyapunov optimization method,virtual queues are used to model the energy storage devices and flexible loads in the *** objective is to minimize the overall operating cost of the interconnected *** the upper level,a non-cooperative game model is introduced to minimize the cost of purchasing power from other EHs for each EH.A best response-based method is adapted to find the Nash *** simulation outcomes demonstrate that application of the proposed strategy can reduce operating costs of an interconnected system and each *** basis of a real-world dataset of interconnected EHs,both analytical and numerical results show the effectiveness of the proposed strategy.

关键词： Energy hub energy router Lyapunov optimization non-cooperative game peer to peer virtual queue

Atomic-Scale Insights into Damage Mechanisms of GGr15 Bearing Steel Under Cyclic Shear Fatigue

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Acta Metallurgica Sinica(English Letters) 2024年第7期37卷 1265-1278页

作者： Qiao-sheng Xia Dong-Peng Hua qing Zhou Ye-Ran Shi Xiang-tao Deng Kai-Ju Lu Hai-Feng Wang Xiu-Bing Liang Zhao-Dong Wang State Key Laboratory of Solidification Processing Center of Advanced Lubrication and Seal MaterialsNorthwestern Polytechnical UniversityXi’an710072China State Key Laboratory of Rolling and Automation Northeastern UniversityShenyang110819China Defense Innovation Institute Academy of Military ScienceBeijing100071China

Alternating shear stress is a critical factor in the accumulation of damage during rolling contact fatigue,severely limiting the service life of ***,the specific mechanisms responsible for the cyclic shear fatigue damage in bearing steel have not been fully *** the mechanical response and microstructural evolution of a model GGr15 bearing steel under cyclic shear loading are investigated through the implementation of molecular dynamics *** samples undergo 30 cycles under three different loading conditions with strains of 6.2%,9.2%,and 12.2%,*** findings indicate that severe cyclic shear deformation results in early cyclic softening and significant accumulation of plastic damage in the bearing ***,samples subjected to higher strain-controlled loading exhibit higher plastic strain energy and shorter fatigue ***,strain localization is identified as the predominant damage mechanism in cyclic shear fatigue of the bearing steel,which accumulates and ultimately results in fatigue ***,simulation results also revealed the microstructural reasons for the strain localization(e.g.,BCC phase transformation into FCC and HCP phase),which well explained the formation of white etching *** study provides fresh atomic-scale insights into the mechanisms of cyclic shear fatigue damage in bearing steels.

关键词： Cyclic shear fatigue Molecular dynamic simulation Bearing steels Plastic damage accumulation

Joint Probability Analysis and Prediction of Sea Ice Conditions in Liaodong Bay

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Journal of Ocean University of China 2024年第1期23卷 57-68页

作者： LIAO Zhenkun DONG sheng tao Shanshan HUA Yunfei JIA Ning College of Engineering Ocean University of ChinaQingdao 266100China Shuifa Planning and Design Co. Ltd.Jinan 250100China National Hazards Mitigation Service Beijing 100194China

Sea ice conditions in Liaodong Bay of China are often described by sea ice grades,which classify annual sea ice conditions based on the annual maximum sea ice thickness(AM-SIT)and annual maximum floating ice extent(AM-FIE).The joint probability distribution of AM-SIT and AM-FIE was established on the basis of their data pairs from 1949/1950 to 2019/2020 in Liaodong *** joint intensity index of the sea ice condition in the current year is calculated,and the joint classification criteria of the sea ice grades in past years are established on the basis of the joint intensity index series.A comparison of the joint criteria with the 1973 and 2022 criteria revealed that the joint criteria of the sea ice grade match well,and the joint intensity index can be used to quantify the sea ice condition over the years.A time series analysis of the sea ice grades and the joint intensity index sequences based on the joint criteria are then *** show a decreasing trend of the sea ice condition from 1949/1950 to 2019/2020,a mutation in 1990/1991,and a period of approximately 91 years of the sea ice *** addition,the Gray-Markov model(GMM)is applied to predict the joint sea ice grade and the joint intensity index of the sea ice condition series in future years,and the error between the results and the actual sea ice condition in 2020/2021 is small.

关键词： sea ice grade ice thickness floating ice extent Liaodong Bay copula

Enhancing Evolutionary Algorithms With Pattern Mining for Sparse Large-Scale Multi-Objective Optimization Problems

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1786-1801页

作者： sheng Qi Rui Wang tao Zhang Weixiong Huang Fan Yu Ling Wang College of Systems Engineering National University of Defense TechnologyChangsha 410073China College of Systems Engineering National University of Defense TechnologyChangsha 410073and also with the Xiangjiang LaboratoryChangsha 410205China College of Transportation and Engineering Central South UniversityChangsha 410073China Department of Automation Tsinghua UniversityBeijing 100084China

Sparse large-scale multi-objective optimization problems(SLMOPs)are common in science and ***,the large-scale problem represents the high dimensionality of the decision space,requiring algorithms to traverse vast expanse with limited computational ***,in the context of sparse,most variables in Pareto optimal solutions are zero,making it difficult for algorithms to identify non-zero variables *** paper is dedicated to addressing the challenges posed by *** start,we introduce innovative objective functions customized to mine maximum and minimum candidate *** substantial enhancement dramatically improves the efficacy of frequent pattern *** this way,selecting candidate sets is no longer based on the quantity of nonzero variables they contain but on a higher proportion of nonzero variables within specific ***,we unveil a novel approach to association rule mining,which delves into the intricate relationships between non-zero *** novel methodology aids in identifying sparse distributions that can potentially expedite reductions in the objective function *** extensively tested our algorithm across eight benchmark problems and four real-world *** results demonstrate that our approach achieves competitive solutions across various challenges.

关键词： Evolutionary algorithms pattern mining sparse large-scale multi-objective problems(SLMOPs) sparse large-scale optimization.

Hybrid model for BOF oxygen blowing time prediction based on oxygen balance mechanism and deep neural network

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International Journal of Minerals,Metallurgy and Materials 2024年第1期31卷 106-117页

作者： Xin Shao qing Liu Zicheng Xin Jiangshan Zhang tao Zhou Shaoshuai Li State Key Laboratory of Advanced Metallurgy University of Science and Technology BeijingBeijing 100083China Engineering Research Center of MES Technology for Iron&Steel Production Ministry of EducationBeijing 100083China Laiwu Iron and Steel Group Yinshan Section Steel Co. Ltd.Jinan 271104China

The amount of oxygen blown into the converter is one of the key parameters for the control of the converter blowing process,which directly affects the tap-to-tap time of converter. In this study, a hybrid model based on oxygen balance mechanism (OBM) and deep neural network (DNN) was established for predicting oxygen blowing time in converter. A three-step method was utilized in the hybrid model. First, the oxygen consumption volume was predicted by the OBM model and DNN model, respectively. Second, a more accurate oxygen consumption volume was obtained by integrating the OBM model and DNN model. Finally, the converter oxygen blowing time was calculated according to the oxygen consumption volume and the oxygen supply intensity of each heat. The proposed hybrid model was verified using the actual data collected from an integrated steel plant in China, and compared with multiple linear regression model, OBM model, and neural network model including extreme learning machine, back propagation neural network, and DNN. The test results indicate that the hybrid model with a network structure of 3 hidden layer layers, 32-16-8 neurons per hidden layer, and 0.1 learning rate has the best prediction accuracy and stronger generalization ability compared with other models. The predicted hit ratio of oxygen consumption volume within the error±300 m^(3)is 96.67%;determination coefficient (R^(2)) and root mean square error (RMSE) are0.6984 and 150.03 m^(3), respectively. The oxygen blow time prediction hit ratio within the error±0.6 min is 89.50%;R2and RMSE are0.9486 and 0.3592 min, respectively. As a result, the proposed model can effectively predict the oxygen consumption volume and oxygen blowing time in the converter.

关键词： basic oxygen furnace oxygen consumption oxygen blowing time oxygen balance mechanism deep neural network hybrid model

Geometric quality evaluation of three-dimensional printable concrete using computational fluid dynamics

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Frontiers of Structural and Civil Engineering 2024年第7期18卷 963-976页

作者： Weijiu CUI Haijun SUN Jiangang ZHOU sheng WANG Xinyu SHI Yaxin tao Department of Civil Engineering Qingdao University of TechnologyQingdao 266000China Innovation Institute for Sustainable Maritime Architecture Research and Technology Qingdao University of TechnologyQingdao 266000China Intelligent Construction Lab Qingdao University of TechnologyQingdao 266000China Shandong Zhaojin Industrial Development Co. Ltd.Yantai 264000China Architectural Engineering Institute Weifang Engineering Vocational CollegeWeifang 261000China qingjian Group Co. Ltd.Qingdao 266000China College of Architecture and Urban Planning Qingdao University of TechnologyQingdao 266000China Department of Structural Engineering and Building Materials Ghent UniversityGhent 9000Belgium Institute of Building Materials ETH ZurichZurich 8064Switzerland

The importance of geometrical control of three dimensional(3D)printable concrete without the support of formwork is widely *** this study,a numerical model based on computational fluid dynamics was developed to evaluate the geometrical quality of a 3D printed *** numerical results were compared,using image analysis,with physical cross-sectional sawn *** influence of printing parameters(printing speed,nozzle height,and nozzle diameter)and the rheological behavior of printed materials(yield stress),on the geometrical quality of one printed layer was *** addition,the yield zone of the printed layer was analyzed,giving insights on the critical factors for geometrical control in 3D concrete *** indicated that the developed model can precisely describe the extrusion process,as well as the cross-sectional quality.

关键词： digital fabrication 3D concrete printing geometric quality computational fluid dynamics printing parameters yield stress