Intelligent prediction of the stress–strain response of intact and jointed rocks

An application of Artificial Neural Networks for predicting the stress–strain response of jointed rocks under different confining pressures is presented in this paper. Rocks of different compressive strength with different joint properties (frequency, orientation and strength of joints) are considered in this study. The database for training the neural network is formed from the results of triaxial compression tests on different intact and jointed rocks with different joint properties tested at different confining pressures reported by various researchers in the literature. The network was trained using a three-layered network with the feed-forward back propagation algorithm. About 85% of the data was used for training and the remaining 15% was used for testing the network. Results from the analyses demonstrated that the neural network approach is effective in capturing the stress–strain behaviour of intact rocks and the complex stress–strain behaviour of jointed rocks. A single neural network is demonstrated to be capable of predicting the stress–strain response of different jointed rocks, whose intact strength varies from 11.32 MPa to 123 MPa, spacing of joints varies from 10 cm to 100 cm, and confining pressures range from 0 to 13.8 MPa.     

巨型山东龙的系统分类、生活习性与生态环境研究

简要回顾了我国山东省诸城市吕标乡库沟村龙骨涧晚白垩世早期辛格庄组中产出的巨型山东龙的研究历史,并讨论了巨型山东龙与"巨大诸城龙"的系统分类关系。对比两者的产出状况、骨骼结构和个体发育特征,作者认为两者为同物异名。依据古生物命名法规的优先律,巨型山东龙命名在先,合法有效;"巨大诸城龙"命名较晚,是一无效名称,应予取消。还讨论了巨型山东龙的生活习性和生态环境,认为巨型山东龙属陆栖性、群居性、植食性恐龙,生活在气候温暖、雨水充沛、植被繁茂的低山或丘陵地区。此外研究了巨型山东龙赋存地层的沉积特征,认为是一套辫状河流相或冲积扇相沉积,而不是湖相沉积。恐龙化石的密集产出是非正常集群死亡于突发性灾害事件的结果,而与国际上的K/T事件无关。     

岩石破裂行为的实验研究

岩样的破裂行为、破坏过程和参数测试是裂隙断裂构造研究的基础和依据。实验岩石样品采自四川东部和新疆北部地区,为测试准确起见,对岩样进行了应力等值线的有限元法计算。通过单轴和三轴实验的岩样破坏观察和应力应变曲线对比,将岩石的破裂行为、应力应变划分为四个阶段,即裂隙压密阶段、弹性变形阶段、微观劈裂阶段和宏观破裂阶段。基于单轴抗压实验岩石劈裂—破裂—碎裂发展过程的微观分析,可以看出宏观破裂主要是沿岩样原有的隐裂隙、临界裂隙发育的,许多新裂隙则主要是在宏观破裂阶段产生的。     

内蒙古乌奴格吐山铜—钼矿床稀土元素的行为及意义

以热液作用为联结点，将斑岩和围岩作为一个整体系统来考虑，对乌奴格吐山特大型斑岩铜－钼矿床热液蚀变矿化过程中ＲＥＥ行为进行了研究，首次发现热液蚀变过程中母岩与围岩ＲＥＥ变化具互补性，铕亏损对斑岩矿化具指示意义。分析ＲＥＥ的赋存矿物及其在蚀变过程中的变化，推断成矿流体具有贫ＲＥＥ，相对富ΣＹ，强烈亏损铕的性质在中强蚀变带斑岩和围岩基本上是以等比质量参与热液蚀变交代的。稀土元素，液体包裹体和氢，氧同位素     

Assessing the EU ETS with a bottom-up,multi-sector model

The European Emissions Trading System (EU ETS) is the central pillar of the EU response against climate change. This trading mechanism is considered, from the theoretical point of view, as the most cost-effective method to reduce GHG. However, previous studies show that the agents who participate in these markets may behave in a way that may lead to inefficient CO₂ prices, creating doubts about the static and dynamic efficiency of the system. This article analyses these possible anomalies by first trying to model the ETS in a more realistic way, addressing some of the limitations of previous models, and second, by comparing the results with real market transactions. For this, a bottom-up, multi-sector model has been built, which represents the EU ETS in an integrated, cross-sectoral way, paying particular attention to the interactions among the most emissions intensive industries. The results show the benefits of this modelling approach and how it better reflects real market conditions. Some preliminary conclusions regarding the behaviour of the agents in the ETS market are also presented.

POLICY RELEVANCE

Low allowance prices in the EU ETS have put into question the dynamic efficiency of the EU ETS system, prompting various ideas for structural reform. However, determining the right reform also requires estimating correctly how agents will respond to it. This article proposes a tool to realistically simulate the EU ETS under the assumption of rational agents, and compare it to real market outcomes, in order to understand better the behaviour of agents in this carbon market, and therefore how to design better policies.     

原位低温拉曼光谱技术在人工合成CaCl2-H2O和MgCl2-H2O体系流体包裹体分析中的应用Ⅱ:低温下流体包裹体相变行为的研究

本文利用低温原位拉曼技术,对CaCl2-H2O体系和MgCl2-H20体系人工合成流体包裹体进行了研究.结果表明:对于盐浓度不同的溶液而言,可采用不同的冷冻方式有效采集低温拉曼光谱;通过系统采集不同温度下的拉曼光谱,可以直接准确地测定包裹体中流体的成分和低温相变过程.人工合成包裹体原位低温拉曼光谱的研究,为将该技术应用于天然包裹体分研究奠定了理论基础,可以预见,该技术必将在流体包裹体研究领域发挥其它方法不可替代的重要作用.     

考虑围岩软化特性和应力释放的圆形隧道黏弹塑性解

将围岩的塑性应变软化特性引入到考虑应力释放的圆形隧道黏弹塑性解中,并且在围岩的软化和残余强度阶段考虑围岩的塑性体积膨胀特性,提出了考虑塑性软化以及塑性体积膨胀和围岩应力释放的圆形隧道弹塑性解。当软化系数k = ∞、膨胀系数h = s时,该解转化为黏弹-脆塑性解;当k = 0、h = s时,则转化为黏弹-理想塑性解,进一步令h = s = 1,则转化为不考虑塑性体积膨胀的黏弹-理想塑性解。通过具体实例计算,分析了掌子面与研究断面间距x、围岩的软化系数k、膨胀系数h和s、支护结构等对围岩塑性区、破碎区半径和变形的影响。当开挖面与研究断面间距x在(0~4)D（D为隧道直径）范围内,随着时间增加塑性圈和破碎区迅速增大;超过4D,塑性区和破碎区半径增量逐渐变小,趋于稳定值;围岩中包含塑性区和破碎区时,二者半径的比值只取决于围岩的性质,与支护结构无关,但支护结构可以限制塑性区及破碎区的范围;考虑应变软化和塑性体积膨胀时,围岩径向位移和塑性区及破碎区半径均大于不考虑应变软化和塑性体积膨胀时的结果;软化系数k增大,围岩位移、塑性区和破碎区半径增加、塑性区半径和破碎区半径之间的比值变小。得到的结果对于隧道工程设计和施工具有一定的指导性和参考价值。     

Three-dimensional quantitative analysis on granular particle shape using convolutional neural network

To identify all desired shape parameters of granular particles with less computational cost, this study proposes a three-dimensional convolutional neural network (3D-CNN) based model. Datasets are made of 100 ballast and 100 Fujian sand particles, and the shape parameters (i.e., aspect ratio, roundness, sphericity, and convexity) obtained by conventional methods are used to label all particles. For the model training, by feeding the slice images of particles into the model, the contour of particles is automatically extracted, thereby the shape parameters can be learned by the model. Thereafter, the model is applied to predict shape parameters of new particles as model testing. All results indicate the model trained based on slice images cut from three orthogonal planes presents the highest prediction accuracy with an error of less than 10%. Meanwhile, the accuracy for concave and angular particles can be guaranteed. The rotation-equivariant of the model is confirmed, in which the predicted values of shape parameters are roughly independent of orientations of the particle when cutting slice images. Superior to conventional methods, all desirable shape parameters can be obtained by one unified 3D-CNN model and its prediction is independent of particle complexity and the number of triangular facets, thus saving computation cost.