几种粉末型吸湿性催化剂的试验研究

在云雾中播撒吸湿性催化剂是进行暖云催化降水或消暖雾的重要手段之一,而寻找高效、适宜的吸湿性催化剂仍然是当前人工影响天气领域的重要研究目标。本研究对6种具有吸湿性的粉末型稀土盐催化剂在云室中的消暖雾性能进行了对比试验。试验采用一个43m3的暖云室,在云室中分别进行无催化的空白试验和6种催化剂的消暖雾催化试验,并使用FM-100雾滴谱仪、透光度仪以及温湿度仪等仪器对云室中雾的整个发展过程进行全程观测。通过对比空白试验与催化试验的观测数据,分析了5种吸湿性催化剂在播撒后对暖雾的影响,对它们的消雾效果和催化剂作用机理进行了分析。研究结果表明:6种催化剂中有5种起到了消雾作用,其中氯化铈、硝酸镧、碳酸镧的消雾效果较好,氯化镧、碳酸铈次之,硝酸铈则没有达到消雾目的;催化剂的引入使雾的含水量、雾滴有效直径、雾滴谱等微物理特征发生明显变化,并最终对雾的发展进程造成很大影响,使雾的消散速度加快或延缓。     

Controls on erosion patterns and sediment transport in a monsoonal,tectonically quiescent drainage,Song Gianh,central Vietnam

The Song Gianh is a small‐sized (~3500 km²), monsoon‐dominated river in northern central Vietnam that can be used to understand how topography and climate control continental erosion. We present major element concentrations, together with Sr and Nd isotopic compositions, of siliciclastic bulk sediments to define sediment provenance and chemical weathering intensity. These data indicate preferential sediment generation in the steep, wetter upper reaches of the Song Gianh. In contrast, detrital zircon U‐Pb ages argue for significant flux from the drier, northern Rao Tro tributary. We propose that this mismatch represents disequilibrium in basin erosion patterns driven by changing monsoon strength and the onset of agriculture across the region. Detrital apatite fission track and ¹⁰Be data from modern sediment support slowing of regional bedrock exhumation rates through the Cenozoic. If the Song Gianh is representative of coastal Vietnam then the coastal mountains may have produced around 132 000–158 000 km³ of the sediment now preserved in the Song Hong‐Yinggehai Basin (17–21% of the total), the primary depocenter of the Red River. This flux does not negate the need for drainage capture in the Red River to explain the large Cenozoic sediment volumes in that basin but does partly account for the discrepancy between preserved and eroded sediment volumes. OSL ages from terraces cluster in the Early Holocene (7.4–8.5 ka), Pre‐Industrial (550–320 year BP) and in the recent past (ca. 150 year BP). The older terraces reflect high sediment production driven by a strong monsoon, whereas the younger are the product of anthropogenic impact on the landscape caused by farming. Modern river sediment is consistently more weathered than terrace sediment consistent with reworking of old weathered soils by agricultural disruption.     

Development of statistical prediction models for Changma precipitation: An ensemble approach

An ensemble statistical forecast scheme with a one-month lead is developed to predict year-to-year variations of Changma rainfall over the Korean peninsula. Spring sea surface temperature (SST) anomalies over the North Atlantic, the North Pacific and the tropical Pacific Ocean have been proposed as useful predictors in a previous study. Through a forward-stepwise regression method, four additional springtime predictors are selected: the northern Indian Ocean (NIO) SST, the North Atlantic SST change (NAC), the snow cover anomaly over the Eurasian continent (EUSC), and the western North Pacific outgoing longwave radiation anomaly (WNP (OLR)). Using these, three new prediction models are developed. A simple arithmetic ensemble mean produces much improved forecast skills compared to the original prediction model of Lee and Seo (2013). Skill scores measured by temporal correlation and MSSS (mean square error skill score) are improved by about 9% and 17%, respectively. The GMSS (Gerrity skill score) and hit rate based on a tercile prediction validation scheme are also enhanced by about 19% and 13%, respectively. The reversed NIO, reversed WNP (OLR), and reversed NAC are all related to the enhancement of a cyclonic circulation anomaly to the south or southwest of the Korean peninsula, which induces southeasterly moisture flux into the peninsula and increasing Changma precipitation. The EUSC predictor induces an enhancement of the Okhotsk Sea high downstream and thus strengthening of Changma front.     

A Novel Hunger Games Search Optimization-Based Artificial Neural Network for Predicting Ground Vibration Intensity Induced by Mine Blasting

Innovation efforts in developing soft computing models (SCMs) of researchers and scholars are significant in recent years, especially for problems in the mining industry. So far, many SCMs have been proposed and applied to practical engineering to predict ground vibration intensity (BIGV) induced by mine blasting with high accuracy and reliability. These models significantly contributed to mitigate the adverse effects of blasting operations in mines. Despite the fact that many SCMs have been introduced with promising results, but ambitious goals of researchers are still novel SCMs with the accuracy improved. They aim to prevent the damages caused by blasting operations to the surrounding environment. This study, therefore, proposed a novel SCM based on a robust meta-heuristic algorithm, namely Hunger Games Search (HGS) and artificial neural network (ANN), abbreviated as HGS–ANN model, for predicting BIGV. Three benchmark models based on three other meta-heuristic algorithms (i.e., particle swarm optimization (PSO), firefly algorithm (FFA), and grasshopper optimization algorithm (GOA)) and ANN, named as PSO–ANN, FFA–ANN, and GOA–ANN, were also examined to have a comprehensive evaluation of the HGS–ANN model. A set of data with 252 blasting operations was collected to evaluate the effects of BIGV through the mentioned models. The data were then preprocessed and normalized before splitting into individual parts for training and validating the models. In the training phase, the HGS algorithm with the optimal parameters was fine-tuned to train the ANN model to optimize the ANN model's weights. Based on the statistical criteria, the HGS–ANN model showed its best performance with an MAE of 1.153, RMSE of 1.761, R² of 0.922, and MAPE of 0.156, followed by the GOA–ANN, FFA–ANN and PSO–ANN models with the lower performances (i.e., MAE?=?1.186, 1.528, 1.505; RMSE?=?1.772, 2.085, 2.153; R²?=?0.921, 0.899, 0.893; MAPE?=?0.231, 0.215, 0.225, respectively). Based on the outstanding performance, the HGS–ANN model should be applied broadly and across a swath of open-pit mines to predict BIGV, aiming to optimize blast patterns and reduce the environmental effects.

     

Estimation of Ground Vibration Intensity Induced by Mine Blasting using a State-of-the-Art Hybrid Autoencoder Neural Network and Support Vector Regression Model

Natural Resources Research - In surface mining, blasting is an indispensable method for fragmenting rock masses. Nevertheless, it can inherently induce many side effects like ground vibrations. At...     

Predicting Blast-induced Ground Vibration in Quarries Using Adaptive Fuzzy Inference Neural Network and Moth–Flame Optimization

Natural Resources Research - Blasting is a first preparatory stage that plays a fundamental role in the subsequent operations of an open pit mine. However, its adverse effects can seriously affect...     

北京城市居住空间形态对居民通勤方式的影响

借助GIS分析和多项式逻辑回归模型,基于5 066份大规模问卷调查数据对北京进行了实证分析,考察北京城市居住空间形态特征在城市空间上的差异,及其对居民通勤方式的影响程度。结果显示：北京城区和郊区的居住空间形态的空间分异显著,并且对居民的通勤方式造成了重大影响,超大街区不利于步行,而高容积率对小汽车出行有显著的抑制作用,高度混合的土地利用形态则能够显著促进居民选择步行通勤。性别、年龄、收入对北京居民的通勤方式具有影响,女性、中老年及低收入群体选择绿色出行方式的概率更高。结论表明居住空间形态规划是引导居民通勤方式的重要途径之一,据此提出了减少居民小汽车出行、促进绿色出行的规划建议。     

Micromechanical Modelling of the Complete Stress–Strain Relationship for Crack Weakened Rock Subjected to Compressive Loading

Summary  A micromechanics-based model, able to quantify the effect of various parameters on the complete stress–strain relationship, is described. The closed-form explicit expression for the complete stress–strain relationship of a rock material containing an echelon cracks arrangement subjected to compressive loading is obtained. The complete stress–strain relationship including the stages of linear elasticity, non-linear hardening and strain softening is established. The results show that the complete stress–strain relationship and the strength of rock with echelon cracks depend on the crack interface friction coefficient, the sliding crack spacing, the perpendicular distance between the two adjacent rows, the fracture toughness of rock material and orientation of the cracks. The present model is used to evaluate the complete stress–strain relationship and strength for crack-weakened rock at the underground cavern complex of the Ertan Hydroelectric Project. The predicted strength is in agreement with that obtained by the Hoek–Brown criterion. The numerical results obtained with the complete stress–strain relationship seem to be in good agreement with the measured values. Author’s address: Xiao-Ping Zhou, School of Civil Engineering, Chongqing University, 443002 Chongqing, P.R. China     

几种碘化银焰剂成冰性能检测

碘化银焰剂是人工影响天气作业中重要的冷云催化剂,目前国内使用的碘化银焰剂有多种配方,有必要对它们的成冰性能进行统一评估。本研究采用1m^3等温云室,对我国人影作业中使用的7种碘化银焰剂(编号为1~7号)进行了统一检测。结果表明:7种焰剂成核率的量级按每克催化剂计算在10^(10)~10^(13)g^(-1)(-8^-18℃)之间,用指数函数拟合能较好地反映成核率随温度的变化;在低温段(≤-16℃),各焰剂成核率较高,不同焰剂之间的成核率差异相对于高温段(>-16℃)要小;在高温段,3、4、7号焰剂也具有较高的成核率,成冰性能要好于其他焰剂;7种焰剂的核化速率不同,-8℃时90%的冰核完成核化的时间在7.8~18min之间,推断该温度下的成核机制以接触核化等慢过程为主。