由测风资料推算局地环流速度的方法

山区或湖区实际观测到的风速，往物证理自然风速和局地环流风速综合的结果，很难将二者抠分开来。本文根据理论分析，提出了根据我资料推避地风速的方法，可纠正过去确定局地环流速度的一些不当的做法。     

铁路工程地质环境对气候变化的反应

本文论述了气候自然变化及其异常、对盐湖、黑海沿岸、里海西岸和贝阿铁路的工程地质条件，带来的盐溶、斜坡作用活化，海侵和路基热融变形等工程地质灾害的现实性和严重性。指出今后进行铁路工程地质勘测设计时，必须考虑未来气候自然变化的重要意义。     

西宁盆地黄土区不同草本植物和坡形条件下坡面产流产沙特征

为进一步研究不同草本植物和边坡坡面形态对坡面产流产沙的影响,本项研究以西宁市毛鸡湾流域长岭绿化区作为试验区,设计了直形和阶梯形2种坡形,选取3种优势草本老芒麦（Elymus sibiricus Linn.）、垂穗披碱草（Elymus nutans Griseb.）和细茎冰草(Agropyron trachycaulum Linn. Gaertn.)作为试验供试种,通过人工模拟降雨试验,探讨了种植不同草本和坡形条件下,边坡坡面的产流、产沙和入渗特征。结果表明：在直形边坡中,裸坡坡面的产流时间小于种植草本植物坡面,且垂穗披碱草坡面和老芒麦坡面的形成产流时间相对较长,为4min,与直形边坡相比,垂穗披碱草阶梯形坡面产流时间相对最长,为8min;在直形边坡中,垂穗披碱草坡面和老芒麦坡面累积径流量、累积产沙量和径流系数相对最小,分别为51.42 L/min、160 g、14.98%,51.25 L/min、210 g、14.93%,细茎冰草坡面的累积径流量、累积产沙量和径流系数分别为96.97 L/min,700 g,28.25 %;垂穗披碱草坡面和老芒麦坡面稳定入渗速率相对最大,其值为0.38~0.44 mm/min,细茎冰草坡面的稳定入渗率为0.29~0.36 mm/min。在阶梯形边坡中,垂穗披碱草坡面的累积径流量、累积产沙量和径流系数相对最小,其值分别为5.62 L/min、110 g、1.64 %,且垂穗披碱草坡面入渗速率相对最大,为0.50~0.52 mm/min,这反映出种植草本植物可增大其坡面的入渗率,有效减少坡面径流和土壤侵蚀,其中垂穗披碱草和老芒麦的固土保水作用相对最为显著,且与直形边坡相比,阶梯形边坡能有效延长坡面土壤水分入渗时间,减少坡面地表径流,从而提高边坡坡面土壤的抗侵蚀能力。     

临界滑动场技术在排土场边坡设计中的应用

边坡临界滑动场技术是近年发展起来的一种边坡稳定性分析方法。它能准确快速确定多层介质、多台阶边坡任意形状的临界滑动面,全面评价边坡整体和局部稳定性。文章首先应用临界滑动场技术对原设计15坡角时的龙桥排土场边坡进行临界滑动面搜寻,确定边坡整体安全系数为1.42,证明原设计的15坡角取值过于保守。然后再应用临界滑动场技术的扩展方法进行反向分析,在给定安全系数为1.30的条件下,求得最佳设计坡角为17。研究成果为将来矿山的排土工作提供指导,具有一定的工程实用性。     

三维激光扫描测量在汶川地震后都汶公路快速抢通中的应用

都（江堰）汶（川）公路是一条高等级山区公路,同时是连接都江堰与汶川县城的主要干道,溯岷江而北上,全长108km。强烈的汶川地震导致了公路两侧大量崩塌、滑坡等地质灾害发生,严重阻断了交通生命线,由于公路沿线河谷狭窄、山高坡陡、表部岩石破碎,又适逢雨季来临,崩塌、滑坡、泥石流等次生地质灾害为震后抢险救灾及地质调查工作带来极大挑战。本文通过三维激光扫描测量技术在都汶公路快速抢通中的应用,讨论其在抢险救灾快速反应中与传统地质调查方法相结合的适用性与可行性,从中不难看出该项技术具有精度高、速度快、真实反映原型并能快速提取相关信息,其势必成为传统地质调查方法的有益补充。     

A comparative study of various commercially available programs in slope stability analysis

The objective of this paper is to study the effect of different slip surface search techniques on the factors of safety obtained using the limit equilibrium (LE) slope stability methods. This objective is accomplished by comparing results from the finite element method, the linear grid method, the rectangular grid method, and the Monte-Carlo searching techniques using different commercially available programs. The results showed that the LE methods are very efficient methods when coupled with a robust searching technique namely the Monte-Carlo method. In addition, the selected slip surface search technique highly influenced the location of the critical slip surfaces as well as the value of the calculated factors of safety.     

Slope reliability analysis using a support vector machine

The first-order second-moment method (FOSM) reliability analysis is commonly used for slope stability analysis. It requires the values and partial derivatives of the performance function with respect to the random variables for the design. Such calculations can be cumbersome when the performance functions are implicit. Implicit performance functions are normally encountered when the slope is geologically complicated and the limit equilibrium method (LEM) is used for the stability analysis.

To address this issue, this paper presents a support vector machine (SVM)-based reliability analysis method which combines the SVM with the FOSM. This method employs the SVM method to approximate the implicit performance functions, thus arriving at SVM-based explicit performance functions. The SVM method uses a small set of the actual values of the performance functions obtained via the LEM for complicated slope engineering. Using the SVM model, a large number of values and partial derivatives of the performance functions can be obtained for conventional reliability analysis using the FOSM. Examples are given to illustrate the proposed SVM-based slope reliability analysis. The results show that the proposed approach is applicable to slope reliability analysis which involves implicit performance functions.     

Optimize taxi driving strategies based on reinforcement learning

The efficiency of taxi services in big cities influences not only the convenience of peoples’ travel but also urban traffic and profits for taxi drivers. To balance the demands and supplies of taxicabs, spatio-temporal knowledge mined from historical trajectories is recommended for both passengers finding an available taxicab and cabdrivers estimating the location of the next passenger. However, taxi trajectories are long sequences where single-step optimization cannot guarantee the global optimum. Taking long-term revenue as the goal, a novel method is proposed based on reinforcement learning to optimize taxi driving strategies for global profit maximization. This optimization problem is formulated as a Markov decision process for the whole taxi driving sequence. The state set in this model is defined as the taxi location and operation status. The action set includes the operation choices of empty driving, carrying passengers or waiting, and the subsequent driving behaviors. The reward, as the objective function for evaluating driving policies, is defined as the effective driving ratio that measures the total profit of a cabdriver in a working day. The optimal choice for cabdrivers at any location is learned by the Q-learning algorithm with maximum cumulative rewards. Utilizing historical trajectory data in Beijing, the experiments were conducted to test the accuracy and efficiency of the method. The results show that the method improves profits and efficiency for cabdrivers and increases the opportunities for passengers to find taxis as well. By replacing the reward function with other criteria, the method can also be used to discover and investigate novel spatial patterns. This new model is prior knowledge-free and globally optimal, which has advantages over previous methods.     

纵向加固技术在人工挖孔桩中的应用

采用纵向加固技术处理大直径人工挖孔桩的持力层软弱、桩端承载力不足,根据工程实例,其加固方法和施工工艺可推广到其它多种人工挖孔桩质量不良情况的处理。     

陶瓷基复合材料及其制造工艺

就陶瓷基复合材料的增韧机理、基体和增强增韧纤维的选择、陶瓷基复合材料的制造工艺,尤其是ＣＶＩ工艺作了较为全面的总结和介绍,并提出了陶瓷基复合材料亟待解决的问题和发展方向。