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高速铁路简统化接触网铝合金零件制备工艺及质量分析

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机械研究与应用 2024年第2期37卷 170-172,177页

作者：余兆国中铁建电气化局集团轨道交通器材有限公司江苏常州213179

高速铁路简统化接触网铝合金零部件简单统一标准化,具有“三统、一提高”的特性,即“统一技术参数、统一并简化装备结构形式、统一并减少零部件种类,提高关键零部件服役性能”,是拥有完全自主知识产权的中国标准件。目前,该类产品已在... 详细信息

高速铁路简统化接触网铝合金零部件简单统一标准化,具有“三统、一提高”的特性,即“统一技术参数、统一并简化装备结构形式、统一并减少零部件种类,提高关键零部件服役性能”,是拥有完全自主知识产权的中国标准件。目前,该类产品已在国内的京哈高铁北京至沈阳试验段、京张高铁崇礼支线、浩吉铁路、盐通高铁等铁路项目中使用。通过铁路应用发现,该合金零件稳定可靠,各项指标均符合相关标准要求。该文从锻造工艺、固溶及时效、机加工工艺、铆接装配工艺分析、质量控制要点等五个主要环节对铝合金简统化零件制备技术与质量控制展开探讨和分析,体现了目前简统化接触网铝合金零件制备技术和质量管控的完善及提升,为接触网系统装备国产化的技术储备奠定了坚实基础。

关键词：简统化接触网铝合金制备技术

Modification of Nano-alumina Surface by Michael Addition Reaction

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Chinese Chemical Letters 2006年第2期17卷 251-252页

作者： Jie ZHANG Jian yu zhao Xia guo Institute of Polymer Science and Engineering Department of Chemical EngineeringSchool of Materials Science and Engineering Tsinghua University Beijing 100084

A general method for modification of nano-alumina surface is investigated using Michael addition reaction with α,β-unsaturated carbonyl compounds.

关键词： Alumina surface modification Michael addition reaction carbonyl compounds ester.

Soil Taxonomy and Distribution Characteristics of the Permafrost Region in the Qinghai-Tibet Plateau, China

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Journal of Mountain Science 2015年第6期12卷 1448-1459页

作者： FANG Hong-bing zhao Lin WU Xiao-dong zhao yu-guo zhao Yong-hua HU guo-jie Cryosphere Research Station on the Qinghai-Tibetan Plateau State Key Laboratory of Cryospheric Sciences Cold and Arid Regions Environmental and Engineering Research Institute Chinese Academy of Sciences Graduate University of Chinese Academy of Sciences School of Environmental and Municipal Engineering Lanzhou Jiaotong University State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil Science Chinese Academy of Sciences

Understanding the soil taxonomy and distribution characteristics of the permafrost region in the Qinghai-Tibet Plateau(QTP) is very important. On the basis of extensive field surveys and experimental analysis, this study carries out soil taxonomic classification of the permafrost region in the QTP. According to Chinese Soil Taxonomy, the soil of the permafrost region in the QTP can be divided into 6 Orders(Histosols, Aridosols, Gleyosols, Isohumosols, Cambosols, Primosols), 11 Suborders, 19 Groups and 24 Subgroups. Cambosols are the dominant soil type in the permafrost region, followed by Aridosols. From the east to the west of the permafrost region in the QTP, the soil type gradually changes from Cambosols to Aridosols, showing a meridional zonality. The eastern region is dominated by Cambosols, with no obvious latitudinal zonality. From the south to the northwest of the western region, the dominance of Aridosols and Cambosols gradually transited to Aridosols, presenting a latitudinal zonality. The soil in the western region shows a poor vertical zonality, while the distribution of suborders of Cambosols in the eastern region shows a more obvious vertical zonality. The result indicates that precipitation and vegetation are the main factors that influence the zonal distribution of soil. The permafrost in the east has some effect on the vertical soil zonality, but the effect is weakened in the west.

关键词： Qinghai-Tibet Plateau Permafrost region Soil taxonomy Soil distribution

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土壤农业利用适宜性评价方法与规范编制说明

土壤通报 2024年第5期55卷 1201-1204页

作者：吴克宁康龙李潇陈章全赵玉国毕如田赵华甫冯喆中国地质大学(北京)土地科学技术学院北京100083 农业农村部农田建设管理司北京100125 国务院第三次全国土壤普查领导小组办公室北京100125 中国科学院南京土壤研究所土壤与农业可持续发展国家重点实验室江苏南京210008 山西农业大学资源环境学院山西太古030801

土壤农业利用适宜性评价是第三次全国土壤普查工作的重要内容之一。为确保评价工作的科学有效性,保障土壤普查工作全面开展的顺畅性,文章对土壤农业利用适宜性评价的工作内容和评价方法进行了介绍,对土壤农业利用适宜性评价技术规范编... 详细信息

土壤农业利用适宜性评价是第三次全国土壤普查工作的重要内容之一。为确保评价工作的科学有效性,保障土壤普查工作全面开展的顺畅性,文章对土壤农业利用适宜性评价的工作内容和评价方法进行了介绍,对土壤农业利用适宜性评价技术规范编制过程中的重要修改内容进行了说明。

关键词：第三次全国土壤普查土壤调查与评价农业利用适宜性评价

Predicting soil depth in a large and complex area using machine learning and environmental correlations

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Journal of Integrative Agriculture 2022年第8期21卷 2422-2434页

作者： LIU Feng YANG Fei zhao yu-guo ZHANG Gan-lin LI De-cheng State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008P.R.China University of the Chinese Academy of Sciences Beijing 100049P.R.China Key Laboratory of Watershed Geographic Science Nanjing Institute of Geography and LimnologyChinese Academy of SciencesNanjing 210008P.R.China

Soil depth is critical for eco-hydrological modeling,carbon storage calculation and land ***,its spatial variation is poorly understood and rarely *** a limited number of sparse samples,how to predict soil depth in a large area of complex landscapes is still an *** study constructed an ensemble machine learning model,i.e.,quantile regression forest,to quantify the relationship between soil depth and environmental *** model was then combined with a rich set of environmental covariates to predict spatial variation of soil depth and straightforwardly estimate the associated predictive uncertainty in the 140000 km^(2)Heihe River basin of northwestern China.A total of 275 soil depth observation points and 26 covariates were *** results showed a model predictive accuracy with coefficient of determination(R)of 0.587 and root mean square error(RMSE)of 2.98 cm(square root scale),i.e.,almost 60% of soil depth variation *** resulting soil depth map clearly exhibited regional patterns as well as local *** deep soils occurred in low lying landscape positions such as valley bottoms and plains while shallow soils occurred in high and steep landscape positions such as hillslopes,ridges and *** oases had much deeper soils than outside semi-desert areas,the middle of an alluvial plain had deeper soils than its margins,and the middle of a lacustrine plain had shallower soils than its *** predictive uncertainty mainly occurred in areas with a lack of soil survey *** pedogenic and geomorphic processes contributed to the shaping of soil depth pattern of this basin but the latter was *** findings may be applicable to other similar basins in cold and arid regions around the world.

关键词： digital soil mapping spatial variation uncertainty machine learning soil-landscape model soil depth

Mapping Soil Texture of a Plain Area Using Fuzzy-c-Means Clustering Method Based on Land Surface Diurnal Temperature Difference

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Pedosphere 2012年第3期22卷 394-403页

作者： WANG De-Cai ZHANG Gan-Lin PAN Xian-Zhang zhao yu-guo zhao Ming-Song WANG Gai-Fen State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008(China) Graduate University of Chinese Academy of Sciences Beijing 100049(China)

The use of landscape covariates to variability of soil properties in similar estimate soil properties is not suitable topographic and vegetation conditions. for the areas of low relief due to the high A new method was implemented to map regional soil texture （in terms of sand, silt and clay contents） by hypothesizing that the change in the land surface diurnal temperature difference （DTD） is related to soil texture in case of a relatively homogeneous rainfall input. To examine this hypothesis, the DTDs from moderate resolution imagine spectroradiometer （MODIS） during a selected time period, i.e., after a heavy rainfall between autumn harvest and autumn sowing, were classified using fuzzy-c-means （FCM） clustering. Six classes were generated, and for each class, the sand （〉 0.05 mm）, silt （0.002-0.05 mm） and clay （〈 0.002 mm） contents at the location of maximum membership value were considered as the typical values of that class. A weighted average model was then used to digitally map soil texture. The results showed that the predicted map quite accurately reflected the regional soil variation. A validation dataset produced estimates of error for the predicted maps of sand, silt and clay contents at root mean of squared error values of 8.4%, 7.8% and 2.3%, respectively, which is satisfactory in a practical context. This study thus provided a methodology that can help improve the accuracy and efficiency of soil texture mapping in plain areas using easily available data sources.

关键词： digital soil mapping land surface temperature low relief area MODIS remote sensing

An integrated method of selecting environmental covariates for predictive soil depth mapping

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Journal of Integrative Agriculture 2019年第2期18卷 301-315页

作者： LU yuan-yuan LIU Feng zhao yu-guo SONG Xiao-dong ZHANG Gan-lin State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008P.R.China University of Chinese Academy of Sciences Beijing 100049P.R.China

Environmental covariates are the basis of predictive soil *** selection determines the performance of soil mapping to a great extent,especially in cases where the number of soil samples is limited but soil spatial heterogeneity is *** this study,we proposed an integrated method to select environmental covariates for predictive soil depth ***,candidate variables that may influence the development of soil depth were selected based on pedogenetic ***,three conventional methods(Pearson correlation analysis(PsCA),generalized additive models(GAMs),and Random Forest(RF))were used to generate optimal combinations of environmental ***,three optimal combinations were integrated to produce a final combination based on the importance and occurrence frequency of each environmental *** tested this method for soil depth mapping in the upper reaches of the Heihe River Basin in Northwest China.A total of 129 soil sampling sites were collected using a representative sampling strategy,and RF and support vector machine(SVM)models were used to map soil *** results showed that compared to the set of environmental covariates selected by the three conventional selection methods,the set of environmental covariates selected by the proposed method achieved higher mapping *** combination from the proposed method obtained a root mean square error(RMSE)of 11.88 cm,which was 2.25–7.64 cm lower than the other methods,and an R^2 value of 0.76,which was 0.08–0.26 higher than the other *** results suggest that our method can be used as an alternative to the conventional methods for soil depth mapping and may also be effective for mapping other soil properties.

关键词： environmental covariate selection integrated method predictive soil mapping soil depth

Application of a Digital Soil Mapping Method in Producing Soil Orders on Mountain Areas of Hong Kong Based on Legacy Soil Data

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Pedosphere 2011年第3期21卷 339-350页

作者： SUN Xiao-Lin zhao yu-guo ZHANG Gan-Lin WU Sheng-Chun MAN yu-Bon WONG Ming-Hung Croucher Institute for Environmental Sciences and Department of Biology Hong Kong Baptist University Hong KongSpecial Administrative Region (China) State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil Science Chinese Academy of Sciences Nanjing210008 (China) joint Open Laboratory of Soil and Environment Institute of Soil Science Chinese Academy of Sciences and Hong KongBaptist University (China)

Based on legacy soil data from a soil survey conducted recently in the traditional manner in Hong Kong of China, a digital soil mapping method was applied to produce soil order information for mountain areas of Hong Kong. Two modeling methods （decision tree analysis and linear discriminant analysis） were used, and their applications were compared. Much more effort was put on selecting soil covariates for modeling. First, analysis of variance （ANOVA） was used to test the variance of terrain attributes between soil orders. Then, a stepwise procedure was used to select soil covariates for linear discriminant analysis, and a backward removing procedure was developed to select soil covariates for tree modeling. At the same time, ANOVA results, as well as our knowledge and experience on soil mapping, were also taken into account for selecting soil covariates for tree modeling. Two linear discriminant models and four tree models were established finally, and their prediction performances were validated using a multiple jackknifing approach. Results showed that the discriminant model built on ANOVA results performed best, followed by the discriminant model built by stepwise, the tree model built by the backward removing procedure, the tree model built according to knowledge and experience on soil mapping, and the tree model built automatically. The results highlighted the importance of selecting soil covariates in modeling for soil mapping, and suggested the usefulness of methods used in this study for selecting soil covariates. The best discriminant model was finally selected to map soil orders for this area, and validation results showed that thus produced soil order map had a high accuracy.

关键词： decision tree analysis linear discriminant analysis soil covariate selection

降水对新疆维吾尔自治区北天山长尾黄鼠动物鼠疫影响的研究

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中国媒介生物学及控制杂志 2024年第3期35卷 323-328页

作者：孙静魏文宇詹尚李芳赵国玉王启果雒涛吴海燕张渝疆新疆医科大学公共卫生学院新疆乌鲁木齐830054 新疆维吾尔自治区疾病预防控制中心消毒与感染控制中心/应急鼠防所新疆乌鲁木齐830002 新疆病媒传染病重点实验室新疆乌鲁木齐830002

目的探讨降水对新疆维吾尔自治区北天山长尾黄鼠鼠疫传播媒介及其动物鼠疫流行的影响。方法采用Spearman秩相关分析和广义可加模型(GAM)分析降水量对长尾黄鼠鼠疫传播媒介和动物鼠疫流行的影响,以及媒介与鼠疫流行的效应关系。结果当年... 详细信息

目的探讨降水对新疆维吾尔自治区北天山长尾黄鼠鼠疫传播媒介及其动物鼠疫流行的影响。方法采用Spearman秩相关分析和广义可加模型(GAM)分析降水量对长尾黄鼠鼠疫传播媒介和动物鼠疫流行的影响,以及媒介与鼠疫流行的效应关系。结果当年和前1年年降水量、春末夏秋和秋末冬春降水量均与长尾黄鼠蚤指数和鼠疫血清阳性率呈负相关,其中前1年年降水量、前1年春末夏秋降水量与蚤指数相关关系均有统计学意义(均P0);前1年春末夏秋降水量对蚤指数呈非线性关系,当年和前1年秋末冬春降水量均与鼠疫血清阳性率亦呈非线性关系,当年和前1年蚤指数均与鼠疫血清阳性率呈线性正相关。结论降水对长尾黄鼠蚤指数和动物鼠疫流行的影响是一个复杂的过程,表现为降水增多会抑制体蚤数量的增长,对鼠疫影响表现为先促进后抑制,并存在一定的滞后性。

关键词：降水鼠疫蚤长尾黄鼠新疆