黄土洞室掘进深度与围岩位移变化规律研究

应用PLAXIS 2D/3D有限元分析软件,对某黄土洞室进行了二维、三维分步掘进、三维一次掘进等工况的弹塑性有限元分析,研究分析了不同工况下洞室围岩位移的变化规律,并对掌子面的空间效应进行了分析。分析结果表明,二维与三维分步计算的最终位移基本一致,可以用二维的计算结果来估算洞室开挖的最终位移。三维分步掘进的分析表明,不同埋深的洞室其位移比的变化规律基本一致,当L/B<1时(L为掘进深度,B为洞室跨度),位移比呈线性增加;当L/B>1时,位移比呈非线性增加;当L/B>3时,其最大位移接近最终位移。掌子面的空间效应分析表明,在掌子面处的位移约为最终位移的1/3,距掌子面0.5倍跨度处的位移约为最终位移的2/3,距掌子面2.5倍跨度处的位移基本达到了最终位移。     

《古地理学报》的立体办刊模式

网络技术为科技期刊的发展提供了动力和渠道,促进了《古地理学报》办刊模式的转变。通过建立独立网站、为读者提供多样化的文章获取渠道、多样化的沟通方式、个性化的文章精准推送、加入OSID开放科学计划等,逐步形成了适应期刊发展的立体办刊模式。     

Trends and risk evolution of drought disasters in Tibet Region,China

Journal of Geographical Sciences - The risk posed by natural disasters can be largely reflected by hazard and vulnerability. The analysis of long-term hazard series can reveal the mechanisms by...     

青藏高原凯蒙蛇绿混杂岩中碱性火山岩的发现及意义

班公湖-怒江洋的关闭时间直接制约青藏高原早期构造演化的认识。最近,在班公湖-怒江缝合带南侧凯蒙蛇绿混杂岩中发现一碱性火山岩,岩性主要是橄榄粗安岩,具粗面结构,斑晶主要是更长石和少量普通辉石,基质主要由更长石、普通辉石和少量填隙的碱性长石组成,有的具辉绿结构。岩石化学成分较一致,Si O2含量介于51.34%~53.91%之间,Ti O2含量为1.02%~1.55%,具有高Al2O3(17.06%~18.46%)和Na2O(4.90%~6.36%)、低K2O(0.05%~0.88%)含量特点,大多数Mg#大于60,最高68.62,里特曼指数(σ)介于3.65~4.47之间,为碱性系列火山岩;富集Sr、Rb、Ba等大离子亲石元素,亏损Nb、Y、Yb等高场强元素,相对富集Zr、Ti,Nb/U、Zr/Nb、La/Yb等比值稳定,分别为7.45~8.51、15.92~17.26和7.26~8.06;(87Sr/86Sr)i值变化范围较小,介于0.706~0.707之间,(143Nd/144Nd)t值在0.512 368~0.512 548之间,说明源区较为一致,结合Ce/Pb-Si O2图解判断结果,认为凯蒙碱性火山岩具有原始地幔、陆壳和深海沉积物源区混合特征。锆石U-Pb同位素定年结果表明该火山岩年龄为101.8±1.1 Ma,可能形成于洋壳俯冲阶段末期,由大陆边缘陆壳与俯冲洋壳板片断离导致软流圈地幔上涌诱发部分熔融所致,推测班公湖-怒江洋大约在早白垩世晚期关闭。     

Fully coupled hydraulic fracture simulation using the improved element partition method

The improved element partition method (IEPM) is a newly developed fracture simulation approach. IEPM allows a fracture to run across an element without introducing extra degrees of freedom. It can also simulate any number of fractures in a prescribed mesh without remeshing. In this study, the IEPM is extended to hydraulic fracture simulation. First, the seepage and volumetric storage matrix of a cracked element are derived using virtual nodes (the intersection points of a crack with element edges). Subsequently, the fully coupled hydromechanical equation is derived for this cracked element. To eliminate the extra degrees of freedom (virtual nodal quantities), the water pressure and displacement of the virtual nodes are associated with their adjacent nodes through least squares interpolation. Finally, the fully coupled equation in terms of nodal quantities is obtained. The verification cases validate the method. By using this method, the field-scale hydraulic fracturing process is well simulated. The proposed approach is simple and efficient for field-scale hydraulic fracture simulation.     

唐山地区波速比变化特征研究

选取唐山地区2008~2018年震相数据，利用单台多震和达法和多台多震和达法分别计算波速比，结合研究区内的地震活动对波速比的变化特征进行研究。结果显示，多台多震和达法得到的波速比结果较为稳定，而单台多震和达法得到的结果变化幅度大，显示更多细节；唐山地区ML≥4.5地震发生前单台波速比存在不同程度的异常，异常台站的方位与地震具有一定的对应性。     

印尼贯穿流源区马鲁古海与哈马黑拉海水团来源的季节和年际变化

So far, large uncertainties of the Indonesian throughflow(ITF) reside in the eastern Indonesian seas, such as the Maluku Sea and the Halmahera Sea. In this study, the water sources of the Maluku Sea and the Halmahera Sea are diagnosed at seasonal and interannual timescales and at different vertical layers, using the state-of-the-art simulations of the Ocean General Circulation Model(OGCM) for Earth Simulator(OFES). Asian monsoon leaves clear seasonal footprints on the eastern Indonesian seas. Consequently, the subsurface waters(around 24.5σ_θ and at ～150 m) in both the Maluku Sea and the Halmahera Sea stem from the South Pacific(SP) during winter monsoon, but during summer monsoon the Maluku Sea is from the North Pacific(NP), and the Halmahera Sea is a mixture of waters originating from the NP and the SP. The monsoon impact decreases with depth, so that in the Maluku Sea, the intermediate water(around 26.8σ_θ and at ～480 m) is always from the northern Banda Sea and the Halmahera Sea water is mainly from the SP in winter and the Banda Sea in summer. The deep waters(around27.2σ_θ and at ～1 040 m) in both seas are from the SP, with weak seasonal variability. At the interannual timescale,the subsurface water in the Maluku Sea originates from the NP/SP during El Ni?o/La Ni?a, while the subsurface water in the Halmahera Sea always originates from the SP. Similar to the seasonal variability, the intermediate water in Maluku Sea mainly comes from the Banda Sea and the Halmahera Sea always originates from the SP. The deep waters in both seas are from the SP. Our findings are helpful for drawing a comprehensive picture of the water properties in the Indonesian seas and will contribute to a better understanding of the ocean-atmosphere interaction over the maritime continent.     

The galaxy luminosity function in the LAMOST Complete Spectroscopic Survey of Pointing Area at the Southern Galactic Cap

We present optical luminosity functions(LFs) of galaxies in the~(0.1) g,~(0.1) r,~(0.1) i bands, calculated using data in~40 deg~2 sky area of the LAMOST Complete Spectroscopic Survey of Pointing Area(LaCoSSPAr) in the Southern Galactic Cap. Redshifts for galaxies brighter than r = 18.1 were obtained mainly with LAMOST. In each band, LFs derived using both parametric and non-parametric maximum likelihood methods agree well with each other. In the0.1 r band, our fitting parameters of the Schechter function are φ_*=(1.65 ± 0.36) × 10~(-2) h~3 Mpc~(-3), M_*=-20.69 ± 0.06 mag and α =-1.12 ± 0.08,which agree with previous studies. Separate LFs are also derived for emission line galaxies and absorption line galaxies. The LFs of absorption line galaxies show a dip at~(0.1) r ~18.5 and can be fitted well by a double-Gaussian function, suggesting a bimodality in passive galaxies.     

耦合土地利用回归与人口加权模型的PM2.5暴露风险评估

PM_2.5已成为人群健康的重要威胁之一,科学精准的暴露评估是PM_2.5风险防控的前提,为提升PM_2.5暴露精准评估,本文利用土地利用数据、道路数据、气象数据等构建PM_2.5土地利用回归反演模型,实现了2013年12月1日-2014年2月8日（冬季）广佛都市区PM_2.5时空动态演变监测,在此基础上将PM_2.5反演结果与人口密度数据耦合,分别从PM_2.5污染浓度与人口加权PM_2.5浓度2个方面,评估广佛都市区PM_2.5污染暴露风险。研究结果表明：① 土地利用回归模型能够较好的反映研究区域内PM_2.5的空间分布特征,R²大于0.78;② 2013年12月1日-2014年2月8日,广佛都市区PM_2.5浓度平均值呈现波动变化趋势,研究时段内,最高平均浓度为97.91 μg/m³ （12月29日-1月11日）,最低平均浓度为53.40 μg/m³ （1月26日-2月8日）,全时段PM_2.5浓度超WHO健康标准的面积占比达99.8%;③ 广佛都市区PM_2.5的空间分布具有异质性规律,其高值区分别位于广州市天河区、越秀区、番禺区北部、花都区北部及佛山市禅城区、南海区中部、三水区中部,低值区主要位于广州市白云区、番禺区东南部及佛山市顺德区南部。人口加权暴露风险存在2个高值中心,分别位于广州市和佛山市的主城区;④ 耦合人口加权模型前后,广佛都市区PM_2.5暴露风险高风险区空间分布发生变化,未考虑人口加权模型时,广佛深高值区较为分散,主要位于南海区、天河区、越秀区、禅城区,考虑人口加权模型后,高值区更加集中于广州市和佛山市的主城区。