Snow avalanche susceptibility evaluation in the central Shaluli Mountains of Tibetan Plateau based on machine learning method北大核心CSCD

Snow avalanches,which are widely and frequently developed at high elevations,seriously threatens the built traffic corridors in the Tibetan Plateau. Susceptibility evaluation of snow avalanche via machine learning model with a high forecast accuracy can be appled to quickly and effectively assess the regional avalanche risk. This paper took the central Shaluli Mountain region as the study area,in which the snow avalanche inventory was established through remote sensing interpretation and field investigation verification. We quantitatively extracted 17 evaluation factors via GIS-based analysis,and these factors were selected through the variance expansion factor（VIF）. Four machine learning models containing SVM,DT,MLP and KNN were used to compile the susceptibility index map of snow avalanches,and kappa coefficient and ROC curve were used to verify the accuracy. The results suggested that the susceptibility indexes obtained from SVM,DT,MLP and KNN were in the range of［0,0. 964］,［0,815］,［0,0. 995］and［0,1］,respectively. The accuracy test results show that these four models all have good prediction accuracy. Among them,the SVM model is the best. The results also indicated that the areas with the high snow avalanche susceptibility mainly distributed in Genie Mountain and Rigong Mountain,most of which were above the planation surface of the Tibetan Plateau. The average altitude of the extremely high snow-avalanche-prone areas is 4 939 m,while the average altitude of the high snow avalanche-prone areas is 4 859 m. The snow avalanche has low perniciousness on the Sichuan-Tibet Highway and the Sichuan-Tibet Railway in the study area. This study can provide theoretical basis and method reference for disaster prevention and mitigation of snow avalanche along Sichuan-Tibet Railway and other major projects across Shaluli Mountains region. © 2022 Science Press (China).     

软土地区超长抗拔桩成桩选型研究

对软土地区长抗拔桩中常用的常规直桩、扩底桩、注浆直桩的承载力性状进行了比较分析,研究了不同桩型的荷载传递规律和承载力提高机理,并引出其荷载一位移的理论计算公式,认为抗拔桩存在“有效桩长”。通过对某沿海城市不同超长抗拔桩的现场抗拔试验,分析比较了各种桩型在30mm上拔位移控制值下的单桩承载力和桩侧摩阻力分布规律,认为超过“有效桩长”的设计是不经济的,注浆直桩可以提高安全系数,宜优先选用注浆直桩。     

渝东北黑色页岩元素迁移特征及化学风化程度

黑色页岩是富含有机质和硫化矿物的特殊沉积岩,但人们对其风化过程的元素活动性及矿物风化机制关注较少.为探讨不同地形位置的黑色页岩化学风化过程,采集了渝东北城口某山脊 (A)、近山顶 (B) 和沟谷 (C) 的下寒武统水井沱组黑色页岩风化剖面岩样,利用XRD、XRF和化学分析手段对采集样品的矿物成分、主量元素进行测定分析.元素和矿物的质量迁移系数 (τ) 和质量迁移通量 (M_{j, flux}) 的计算结果表明,黑色页岩风化过程中Ca、Mg和Na元素具有明显的贫化现象,近地表处存在Al元素的富集现象;矿物成分方面,黄铁矿和有机质氧化后形成的酸性水环境,造成方解石、白云石、斜长石等不稳定矿物溶解,并生成含水石膏、铁质氧化物、黏土矿物等次生矿物.不同赋存位置的黑色页岩风化程度有所差异,Na/K-CIA、K/Ca*-Al/Na、A-CN-K和A-CNK-FM图解显示:A剖面处于脱Ca过程的初级风化阶段,B剖面处于脱Ca、Na初期的初等-中等风化阶段,C剖面已发生脱Ca、Na过程,并伴随脱Si作用的中等-强烈风化阶段,结合不同风化指数 (如:CIA、CIW、PIA、MWPI等),得出各剖面的化学风化强弱程度依次为C＞B＞A.      

崇陵流域土石山区坡面优先流发育路径研究

大孔隙优先流对山坡产汇流过程有重要影响。为摸清太行山土石山坡不同坡位点(坡顶、坡中上、坡中、坡中下、坡脚)的大孔隙优先流发育路径规律,以崇陵流域的典型山坡为研究对象,采用亮蓝染色剂开展了野外双环入渗染色剂示踪试验,并从水平方向与垂直方向对比分析大孔隙优先流发育路径。结果表明:(1)从坡顶到坡脚,垂直方向优先流发育减弱,水平方向优先流增强。(2)坡中以下,大孔隙优先流水平发育明显;而坡中以上,垂直方向优先流发育明显,水平方向大孔隙优先流鲜有发育。(3)崇陵流域土山区坡面表层深度20 cm以上很少出现水平方向的优先流侧向补给,为垂直向下的活塞式下渗方式。20 cm以下开始出现水平方向的大孔隙优先流,30～70 cm为优先流发育显著区。以上结论可以为基于优先流的山坡产汇流模拟提供参考。     

黑色页岩水岩化学作用实验研究

水岩作用是黑色页岩化学风化的重要途径,并与岩体矿物组分、工程性质及地质环境有着密切的联系。利用自制的流通实验装置对取自三江县团结电站附近的寒武系清溪组黑色页岩与富含溶解氧去离子水的化学反应进行试验模拟研究,并利用离子分析仪、电感耦合等离子体质谱仪对反应后溶液离子浓度进行分析,使用扫描电子显微镜观察反应前后岩样微观特征,结合岩样渗透系数的变化监测,对岩样中黄铁矿氧化动力学速率以及受黄铁矿氧化影响形成的酸性环境下硅元素释放速率进行计算分析。结果表明,黄铁矿氧化行为使得岩体渗透率降低约70%,在黑色页岩自身矿物化学组分和岩石物理性质的共同影响下,所含黄铁矿氧化速率与纯黄铁矿颗粒的氧化速率非常接近,同时黄铁矿氧化形成的酸性溶液可溶蚀岩体中石英和伊利石,由于两者含量未能精确测定,因此所测得硅元素释放速率仅表示两者溶解的总反应速率。