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Broaching Performance of Superalloy GH4169 Based on FEM

Journal of Materials Science & Technology 2011年第12期27卷 1178-1184页

作者： xiangwei kong bin li zhibo jin wenran geng. School-of Mechanical Engineering ＆ Automation Northeastern University Shenyang 110004 China

The nickel-based superalloy GH4169 is an important material for high temperature applications in the aerospace industry. However, due to its poor machinability, GH416g is hard to be cut and generates saw-tooth chips during high speed machining, which could significantly affect the dynamic cutting force, cutting temperature fluctuation, tool life, and the surface integrity of the parts. In this paper, the saw-tooth chip formation mechanism of superalloy GH4169 was investigated by the elasto-viscoplastic finite element method （FEM）. Using the finite element software of ABAQUS/Explicit, the deformation of the part during high speed machining was simulated. The effective plastic strain, the temperature field, the stress distribution, and the cutting force were analyzed to determine the influence of the cutting parameters on the saw-tooth chip formation. The study on broaching performance has great effect on selecting suitable machining parameters and improving tool life.

关键词： Machining Superalloy Saw-tooth chip Finite element method (FEM)

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Science with the 2.5-meter Wide Field Survey Telescope(WFST)

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Science China(Physics,Mechanics & Astronomy) 2023年第10期66卷 155-202页

作者： Tinggui Wang Guilin liu Zhenyi Cai jinjun geng.Min Fang Haoning He Ji-an Jiang Ning Jiang Xu kong bin li Ye li Wentao Luo Zhizheng Pan Xuefeng Wu Ji Yang Jiming Yu Xianzhong Zheng Qingfeng Zhu Yi-Fu Cai Yuanyuan Chen Zhiwei Chen Zigao Dai Lulu Fan Yizhong Fan Wenjuan Fang Zhicheng He Lei Hu Maokai Hu Zhiping jin zhibo Jiang Guoliang li Fan li Xuzhi li Runduo liang Zheyu lin Qingzhong liu Wenhao liu Zhengyan liu Wei liu Yao liu Zheng Lou Han Qu Zhenfeng Sheng Jianchun Shi Yiping Shu Zhenbo Su Tianrui Sun Hongchi Wang Huiyuan Wang Jian Wang Junxian Wang Daming Wei Junjie Wei Yongquan Xue jingzhi Yan Chao Yang Ye Yuan Yefei Yuan Hongxin Zhang Miaomiao Zhang Haibin Zhao Wen Zhao Department of Astronomy University of Science and Technology of ChinaHefei 230026China Institute of Deep Space Sciences Deep Space Exploration LaboratoryHefei 230026China Purple Mountain Observatory Chinese Academy of SciencesNanjing 210023China CAS Key Laboratory for Research in Galaxies and Cosmology Department of AstronomyUniversity of Science and Technology of ChinaHefei 230026China State Key Laboratory of Particle Detection and Electronics University of Science and Technology of ChinaHefei 230026China National Astronomical Observatory of Japan National Institutes of Natural SciencesTokyo 181-8588Japan

The Wide Field Survey Telescope(WFST) is a dedicated photometric surveying facility being built jointly by University of Science and Technology of China(USTC) and the Purple Mountain Observatory(PMO). It is equipped with a 2.5-meter diameter primary mirror, an active optics system, and a mosaic CCD camera with 0.73 gigapixels on the primary focal plane for highquality image capture over a 6.5-square-degree field of view. The installation of WFST near the summit of Saishiteng mountain in the Lenghu region is scheduled in summer of 2023, and the operation is planned to start three months later. WFST will scan the northern sky in four optical bands(u, g, r and i) at cadences from hourly/daily in the deep high-cadence survey(DHS) program, to semi-weekly in the wide field survey(WFS) program. During a photometric night, a nominal 30 s exposure in the WFS program will reach a depth of 22.27, 23.32, 22.84, and 22.31(AB magnitudes) in these four bands, respectively, allowing for the detection of a tremendous amount of transients in the low-z universe and a systematic investigation of the variability of Galactic and extragalactic objects. In the DHS program, intranight 90 s exposures as deep as 23(u) and 24 mag(g), in combination with target of opportunity follow-ups, will provide a unique opportunity to explore energetic transients in demand for high sensitivities, including the electromagnetic counterparts of gravitational wave events, supernovae within a few hours of their explosions,tidal disruption events and fast, luminous optical transients even beyond redshift of unity. In addition, the final 6-year co-added images, anticipated to reach g■25.8 mag in WFS or 1.5 mags deeper in DHS, will be of fundamental importance to general Galactic and extragalactic science. The highly uniform legacy surveys of WFST will serve as an indispensable complement to those of the Vera C. Rubin Observatory's Legacy Survey of Space and Time(LSST) that monitors the southern sky.

关键词： optical telescope time domain astronomy photometric survey supernovae multi-messenger events tidal disruption event

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Study design of deep learning based automatic detection of cerebrovascular diseases on medical imaging: a position paper from Chinese Association of Radiologists

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Intelligent Medicine 2022年第4期2卷 221-229页

作者： Longjiang Zhang Zhao Shi Min Chen Yingmin Chen jingliang Cheng li Fan Nan Hong Wenxiao Jia Guihua Jiang Shenghong Ju Xiaogang li Xiuli li Changhong liang Weihua liao Shiyuan liu Zaiming Lu lin Ma Ke Ren Pengfei Rong bin Song Gang Sun Rongpin Wang zhibo Wen Haibo Xu Kai Xu Fuhua Yan Yizhou Yu Yunfei Zha Fandong Zhang Minwen Zheng Zhen Zhou Wenzhen Zhu Guangming Lu Zhengyu jin on behalf of Chinese Association of Radiologists Department of Radiology Affiliated Jinling HospitalMedical School of Nanjing UniversityNanjingJiangsu 210002China Department of Radiology Beijing HospitalNational Center of GerontologyBeijing 100005China Department of Radiology Hebei General HospitalShijiazhuangHebei 050199China Department of Magnetic Resonance Imaging The First Affiliated Hospital of Zhengzhou UniversityZhengzhouHenan 450052China Department of Medical Imaging and Nuclear Medicine Changzheng Hospital of Naval Medical UniversityShanghai 200072China Department of Radiology Peking University People’s HospitalBeijing 100044China Imaging Center First AffiliatedHospital of Xinjiang Medical UniversityUrumqiXinjiang Uygur Autonomous Region 830054China Department of Medical Imaging Guangdong Second Provincial General HospitalGuangzhouGuangdong 510050China Department of Radiology Zhongda HospitalSchool of MedicineSoutheast UniversityNanjingJiangsu 211189China Department of Radiology General Hospital of Northern Theater CommandShenyangLiaoning 110011China DeepWise AI lab.Beijing 100089 China Department of Radiology Guangdong Provincial People’s HospitalGuangdong Academy of Medical SciencesGuangzhouGuangdong 519041China Department of Radiology Xiangya HospitalCentral South UniversityChangshaHunan 410008China Department of Radiology Shengjing Hospital of China Medical UniversityShenyangLiaoning 110001China Department of Radiology Chinese PLA(People’s Liberation Army)General HospitalBeijing 100853China Department of Radiology Xiang’an Hospital of Xiamen UniversitySchool of MedicineXiamen UniversityXiamenFujian 361005China Department of Radiology Third Xiangya HospitalCentral South UniversityChangshaHunan 410013China Department of Radiology Functional and Molecular Imaging Key Laboratory of Sichuan ProvinceWest China HospitalSichuan UniversityChengduSichuan 610044China Department of Nuclear Medicine 960 Hospital of PLAJi’nanShandong 250012China Department of Radiology Guizhou Provincial People’s Hosp

In recent years,with the development of artificial intelligence,especially deep learning technology,researches on automatic detection of cerebrovascular diseases on medical images have made tremendous progress and these models are gradually entering into clinical ***,because of the complexity and flexibility of the deep learning algorithms,these researches have great variability on model building,validation process,performance description and results *** lack of a reliable,consistent,standardized design protocol has,to a certain extent,affected the progress of clinical translation and technology development of computer aided detection *** reviewing a large number of literatures and extensive discussion with domestic experts,this position paper put forward recommendations of standardized design on the key steps of deep learning-based automatic image detection models for cerebrovascular *** further research and application expansion,this position paper would continue to be updated and gradually extended to evaluate the generalizability and clinical application efficacy of such tools.

关键词： Cerebrovascular diseases Deep learning Study design Medical imaging

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生态实践中的传承与创新--中国城市科学研究会景观学与美丽中国建设专业委员会座谈会纪实

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景观设计学（中英文） 2018年第3期6卷 46-57页

作者：白伟岚陈利顶方胜浩高静华韩辉姜斌孔祥伟李迪华李建伟李锦生李润楠李宗礼刘瑜罗涛吕焕来庞伟孙善坤唐艳红汤敏王君王小保王鑫王志芳卫超魏玉栋邢磊俞孔坚余洋张坪邹裕波张晶蕊(整理) 佘依爽(整理) 王颖(整理/译) 张健(译) 中国城市建设研究院中国科学院生态环境研究中心中国科学院城市与区域生态国家重点实验室浙江省景观设计和建设行业协会重庆纬图景观设计有限公司睿景文旅投资管理有限公司香港大学建筑学院园境建筑学部香港大学城市环境与大众健康虚拟现实实验室北京观筑景观规划设计院北京大学建筑与景观设计学院北京东方艾地景观设计有限公司山西省住房和城乡建设厅林产工业规划设计院城市规划设计三所水电水利规划设计总院北京大学地球与空间科学学院遥感与地理信息系统研究所福州大学建筑学院丹麦安博戴水道公司中国区市场部广州土人景观顾问有限公司中国文化景观集团易兰规划设计院古村之友太原市建筑设计研究院园林景观二所湖南省建筑设计院景观设计研究中心一方国际环境景观设计安徽省城乡规划设计研究院设计二所安徽省海绵城市建设研究中心中国美丽乡村研究中心北京正和恒基滨水生态环境治理股份有限公司研究院美国艺术与科学院哈尔滨工业大学建筑学院景观系重庆蓝调城市景观规划设计有限公司阿普贝思(北京)建筑景观设计咨询有限公司不详

2018年1月21日,中国城市科学研究会景观学与美丽中国建设专业委员会座谈会于北京大学建筑与景观设计学院举办。来自景观、生态、水利、规划等领域的30余位学者、设计师、教育者及其他从业人士参加了会议,并围绕美丽中国建设、生态文明... 详细信息

2018年1月21日,中国城市科学研究会景观学与美丽中国建设专业委员会座谈会于北京大学建筑与景观设计学院举办。来自景观、生态、水利、规划等领域的30余位学者、设计师、教育者及其他从业人士参加了会议,并围绕美丽中国建设、生态文明建设、景观设计学科建设、行业融合等议题展开讨论。座谈会最终达成共识,提出了跨界生态实践的迫切性和必要性,同时探讨了在教育和实践层面跨界的难点与问题——不同行业的优势、职责以及在"跨界"中的作用尚不明确,学科教育也未能很好地构建并明晰自身的核心竞争力——呼吁应积极促进学科与行业融合,使其适应当代需求。

关键词：景观设计学美丽中国生态文明建设跨学科协作行业融合

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