沁水煤田15号煤中氟的赋存状态及其沉积环境分析

氟是煤中有害元素之一,燃煤型氟排放造成的污染已经对人类的健康安全构成威胁。研究煤中氟赋存状态及其沉积环境,对掌握高氟煤分布规律及控制燃煤造成的氟排放具有重要意义。通过对沁水煤田内6座煤矿15号煤样品的分析发现:煤中氟含量与灰分显著相关,与黄铁矿硫、有机硫无相关关系,表明煤中氟主要以无机物形式赋存,且与含硫矿物无关;与钾、镁、硅、铝等元素含量具有显著的相关关系,表明氟有可能的主要赋存形式为金云母、氟金云母等矿物,以及以吸附存在于高岭石、勃姆石、伊蒙混层等黏土矿物中;与钙、磷元素含量无显著相关性,表明氟不以氟磷灰石、含氟羟基磷灰石等矿物大量赋存。此外,通过对沁水煤田15号煤的沉积环境分析发现,弱还原环境、较低盐度、偏酸性、较强的水动力条件有利于该区域煤中氟的富集。     

煤炭地质勘查产业转型发展的思考与探讨

煤炭地质勘查工作关系国家能源安全,在国民经济发展中具有重要的战略地位。伴随煤炭行业绿色转型和新能源革命新形势,及时调整产业结构,向大地质、大资源、大生态方向拓展服务领域,为国家生态文明建设和煤炭产业绿色安全高效发展提供坚实的地质技术保障,成为煤炭地质勘查产业转型发展必然趋势和未来发展方向。结合煤田地质勘查工作发展历程及现状、发展趋势,对煤炭地质勘查产业转型发展方向进行深入剖析和探讨。     

Predicting rock size distribution in mine blasting using various novel soft computing models based on meta-heuristics and machine learning algorithms

Blasting is well-known as an effective method for fragmenting or moving rock in open-pit mines. To evaluate the quality of blasting, the size of rock distribution is used as a critical criterion in blasting operations. A high percentage of oversized rocks generated by blasting operations can lead to economic and environmental damage. Therefore, this study proposed four novel intelligent models to predict the size of rock distribution in mine blasting in order to optimize blasting parameters, as well as the efficiency of blasting operation in open mines. Accordingly, a nature-inspired algorithm (i.e., firefly algorithm – FFA) and different machine learning algorithms (i.e., gradient boosting machine (GBM), support vector machine (SVM), Gaussian process (GP), and artificial neural network (ANN)) were combined for this aim, abbreviated as FFA-GBM, FFA-SVM, FFA-GP, and FFA-ANN, respectively. Subsequently, predicted results from the abovementioned models were compared with each other using three statistical indicators (e.g., mean absolute error, root-mean-squared error, and correlation coefficient) and color intensity method. For developing and simulating the size of rock in blasting operations, 136 blasting events with their images were collected and analyzed by the Split-Desktop software. In which, 111 events were randomly selected for the development and optimization of the models. Subsequently, the remaining 25 blasting events were applied to confirm the accuracy of the proposed models. Herein, blast design parameters were regarded as input variables to predict the size of rock in blasting operations. Finally, the obtained results revealed that the FFA is a robust optimization algorithm for estimating rock fragmentation in bench blasting. Among the models developed in this study, FFA-GBM provided the highest accuracy in predicting the size of fragmented rocks. The other techniques (i.e., FFA-SVM, FFA-GP, and FFA-ANN) yielded lower computational stability and efficiency. Hence, the FFA-GBM model can be used as a powerful and precise soft computing tool that can be applied to practical engineering cases aiming to improve the quality of blasting and rock fragmentation.     

一次极端寒潮天气过程等熵位涡分析

利用2016年1月1日至31日的FNL资料,对一次极端寒潮天气过程进行了等熵位涡分析。结果表明:高位涡主体由极涡分裂而来,前面低位涡区的阻挡与后侧低位涡大气的北上加强了位涡的经向交换,高位涡空气不断由极地向南输送,使得高位涡主体不断加强维持。高位涡在由北向南移动的同时,也由对流层顶向下输送。此次寒潮过程主要有3股冷空气由上而下发展,位置均在高空急流轴的北侧,最南端的一股下沉气流最旺盛,这是其与高空急流相互作用的结果。强盛的冷空气下沉使得寒潮影响范围触及我国华南地区。随着高位涡的向南向下传输,一方面引起对流层中高层低涡系统迅速发展,当它移到中国东部地区时,东亚大槽迅速加深,使槽后强冷空气迅速向南爆发;另一方面,在高位涡输送的过程中,其后侧有强烈的下沉运动,使得地面冷高压快速发展,导致强寒潮天气的爆发。     

太湖蓝藻水华形成的适宜气象指标

根据2005—2017年卫星遥感反演的太湖蓝藻水华信息,利用区域气象观测数据分析各类气象因子对太湖蓝藻深水华形成的影响,结果表明:①在日平均气温为0～35℃区间内会出现蓝藻聚集现象,其中最适宜气温区间为15.1～35℃,该区间内累计出现蓝藻水华的面积占比达90%、出现大面积蓝藻水华占比达93%;②在卫星观测到蓝藻前6h,平均风速为0.2～4.8m/s区间内能观测到蓝藻水华,其中最适宜的平均风速区间为0.5～3.4m/s,该区间内蓝藻水华累计出现次数占比达94.7%,大面积蓝藻水华主要出现在平均风速2.0m/s的情况下,占比89%;③降水总体上呈负效应,但在观测到有大面积蓝藻水华的情况下,前24h有小雨(10mm)的情形与总降水次数之比达88%,说明小雨的适度扰动有利于形成大面积蓝藻水华;④日照充足有利于蓝藻生长,但并非蓝藻水华形成的必要条件。在此基础上建立的多元回归综合气象指数模型,拟合结果较好,通过了0.001的显著性检验。     

百色气候变化特征及城市适应策略建议

利用气候观测数据分析表明,近60a来,百色出现了与全球气候变化背景一致的增暖变化,主要变化特征有:气温明显升高,年降水日数减少,冬季降水量增多,年日照时数减少;高温和干旱频率高,20世纪90年代以来暴雨日数偏多。与广西平均气候变化状况相比,百色的气候变化程度风险低于广西平均水平。预估到本世纪中期,百色气温仍将缓慢升高,干旱和强降水的强度可能加剧。建议科学规划,统筹协调,科学评估城市气候承载力,开展城市适应气候变化风险管理,提升生态气候环境监测及自然灾害预警应急能力,建设生态气候宜居城市。     

基于小波分析的场地波速测量方法

在场地波速测量中,由于噪声等因素的影响很难准确识别P、S波的初至时刻,致使波速结果存在很大的误差。本文给出了一种基于小波变换的波速测量的新方法。该方法利用波动信号的小波变换与弹性波群速度的关系准确识别弹性波初至时刻。弹性波小波变换的峰值时刻代表着以群速度传播的弹性波的初至时刻,使P波、S波的初至时刻的确定具有明确的物理意义,波速的结果准确、可靠、稳定。此外,波动信号的小波多尺度分析还可以确定地层中传播的弹性波的频散特性。最后,该方法在场地波速测量的实测信号的应用表明该方法可准确确定P、S波速。     

Study on inelastic displacement ratio spectra for near-fault pulse-type ground motions

In displacement-based seismic design, inelastic displacement ratio spectra (IDRS) are particularly useful for estimating the maximum lateral inelastic displacement demand of a nonlinear SDOF system from the maximum elastic displacement demand of its counterpart linear elastic SDOF system. In this study, the characteristics of IDRS for near-fault pulse-type ground motions are investigated based on a great number of earthquake ground motions. The in? uence of site conditions, ratio of peak ground velocity (PGV) to peak ground acceleration (PGA), the PGV, and the maximum incremental velocity (MIV) on IDRS are also evaluated. The results indicate that the effect of near-fault ground motions on IDRS are signifi cant only at periods between 0.2 s - 1.5 s, where the amplifi cation can approach 20%. The PGV/PGA ratio has the most signifi cant in? uence on IDRS among the parameters considered. It is also found that site conditions only slightly affect the IDRS.     

基于“葵花8号”气象卫星的陇东南地区强对流识别跟踪技术研究

利用常规观测资料、区域自动站资料和“葵花8号”气象卫星资料,对2016年4—9月甘肃省陇东南地区出现的43次强对流天气过程进行分析,确立了强对流云团识别指标、追踪方法及预报指标,并对2018年部分个例进行效果检验。结果表明：（1）利用卫星B13通道（10.4μm）亮温值TBB≤238 K或B08通道（6.2μm）与B13通道亮温差△TBB<0 K双阈值作为强对流云团识别指标,可以准确识别出陇东南地区的强对流天气云团;（2）利用“逆向搜索法”、“面积重叠法”及对云团重心的计算,可以对强对流云团进行准确定位、追踪及移动路径外推预报;（3）建立的强对流天气落区判别指标对该地区短时强降水及冰雹落区具有一定的预报能力。     

中国滑雪场可达性及市场潜力测度

利用可达性分析方法与潜力模型对中国滑雪场空间分布格局与市场潜力进行了系统分析,全面认识了滑雪场在交通可达性方面的优劣势,并针对不同区域提出了相应的发展或改进方向.研究表明:中国滑雪场距离城市中心的平均最短旅行时间为1.24 h,南方可达性普遍较差,北方同一城市内部差异较大.全国各城市到达某一滑雪场的最短时间呈圈层式分布...