Support vector machines applied to uniaxial compressive strength prediction of jet grouting columns

Learning from data is a very attractive alternative to “manually” learning. Therefore, in the last decade the use of machine learning has spread rapidly throughout computer science and beyond. This approach, supported on advanced statistics analysis, is usually known as Data Mining (DM) and has been applied successfully in different knowledge domains. In the present study, we show that DM can make a great contribution in solving complex problems in civil engineering, namely in the field of geotechnical engineering. Particularly, the high learning capabilities of Support Vector Machines (SVMs) algorithm, characterized by it flexibility and non-linear capabilities, were applied in the prediction of the Uniaxial Compressive Strength (UCS) of Jet Grouting (JG) samples directly extracted from JG columns, usually known as soilcrete. JG technology is a soft-soil improvement method worldwide applied, extremely versatile and economically attractive when compared with other methods. However, even after many years of experience still lacks of accurate methods for JG columns design. Accordingly, in the present paper a novel approach (based on SVM algorithm) for UCS prediction of soilcrete mixtures is proposed supported on 472 results collected from different geotechnical works. Furthermore, a global sensitivity analysis is applied in order to explain and extract understandable knowledge from the proposed model. Such analysis allows one to identify the key variables in UCS prediction and to measure its effect. Finally, a tentative step toward a development of UCS prediction based on laboratory studies is presented and discussed.     

耀变体亮温度与黑洞喷流能量的相关性讨论

耀变体(Blazars)的亮温度与黑洞喷流能量和吸积率有重要关系。搜集了53个耀变体源样本,包括22个蝎虎天体(BL Lacs)和31个平谱射电类星体(Flat Spectrum Radio Quasars,FSRQs),研究了耀变体亮温度与黑洞喷流能量的分布,并对子类中亮温度与黑洞喷流能量的相关性进行了讨论。研究结果表明:(1)蝎虎天体与平谱射电类星体的亮温度与黑洞喷流能量的分布存在明显差异,这可能与蝎虎天体与平谱射电类星体的内禀性质有关,也可能与其有无发射线及发射线的强弱有关;(2)蝎虎天体的亮温度与黑洞喷流能量之间的相关性较强,亮温度可以在一定程度上描述蝎虎天体的黑洞喷流能量,亮温度大的蝎虎天体喷流携带的能量也较大;(3)平谱射电类星体的亮温度与黑洞喷流能量之间有弱相关性,平谱射电类星体的亮温度不能清楚地描述黑洞喷流能量,黑洞喷流能量受亮温度影响较小,平谱射电类星体的黑洞喷流能量可能受到其他因素的影响;(4)耀变体的亮温度与黑洞吸积率之间有弱的相关性。     

二维界面流的稳定性及相路方程的椭圆型条件

针对天气实践的一些问题,本文改变了文献[1]的某些作法,分别就上、下行波的稳定性情况,切变邻近区域相路方程的类型条件作了较细致的讨论。结果表明:不稳定极易发生在背急流方向而立的左侧,并在不连续界面的两侧其稳定性是不同的,其相路方程也是有条件的——急流轴及其左侧邻近地区,一般满足椭圆型条件,而其右侧则有可能出现双曲型,从而揭示了扰动沿东西向传播时不稳定易于维持的原因,并与天气实践吻合。     

2022 年初冬伊犁河谷一次极端暴雪过程诊断分析

为了更全面地伊犁河谷极端暴雪发生发展的机制,利用常规探空和地面观测资料、FY-2H长波辐射资料(Outgoing Long-wave Radiation,OLR)和NCEP/NCAR１°×１°再分析资料,采用天气动力学分析方法对2022年11月22日-24日出现在伊犁河谷极端暴雪过程的成因和动力结构演变特征进行分析,结果表明:(1)此次降雪为强锋区降雪,锋区内不断有短波东移,是暴雪发生的大尺度环流背景；300hPa极锋急流、500hPa强锋区、700hPa强偏西急流的流场配置起至关重要作用。(2)低层冷空气入侵,迫使暖湿空气抬升、气温下降,形成了下冷上暖的强逆温层结,而导致降水相态转变。降雪持续时间长,导致强降雪发生。(3)低层偏西急流把水汽输送到暴雪区,并在暴雪区上方产生强的水汽辐合中心,为本次暴雪提供了有利的水汽条件。散度场对大暴雪的发生有较好的先兆意义,双辐合-辐散结构的散度场特征可以作为预报降雪加大的指标。(4)暴雪过程发生时大气处于对流稳定状态,但存在对称不稳定能量的释放。(5)OLR特征分析表明OLR３ｈ平均值与３ｈ降雪量存在明显的负相关关系。