Rapid estimation of maximum and minimum void ratios of granular soils

Maximum and minimum void ratios (e_max and e_min) of granular soils are commonly used as indicators of many engineering properties. However, few methods, apart from laboratory tests, are available to provide a rapid estimation of both e_max and e_min. In this study, we present a theoretical model to map the densest and the loosest packing configurations of granular soils onto the void space. A corresponding numerical procedure that can predict both e_max and e_min of granular soils with arbitrary grain size distributions is proposed. The capacity of the proposed method is evaluated by predicting the maximum and minimum void ratios of medium to fine mixed graded sands with different contents of fines. The influence of the grain size distribution, characterized quantitatively by uniformity parameter and the fractal dimension, on e_max and e_min is discussed using the proposed method. Moreover, application of this method in understanding the controlling mechanism for the void ratio change during grain crushing is presented.

     

Multi-step ahead short-term predictions of storm surge level using CNN and LSTM network

Storm surges pose significant danger and havoc to the coastal residents' safety, property, and lives, particularly at offshore locations with shallow water levels. Predictions of storm surges with hours of warning time are important for evacuation measures in low-lying regions and coastal management plans. In addition to experienced predictions and numerical models, artificial intelligence (AI) techniques are also being used widely for short-term storm surge prediction owing to their merits in good level of prediction accuracy and rapid computations. Convolutional neural network (CNN) and long short-term memory (LSTM) are two of the most important models among AI techniques. However, they have been scarcely utilised for surge level (SL) forecasting, and combinations of the two models are even rarer. This study applied CNN and LSTM both individually and in combination towards multi-step ahead short-term storm surge level prediction using observed SL and wind information. The architectures of the CNN, LSTM, and two sequential techniques of combining the models (LSTM–CNN and CNN–LSTM) were constructed via a trial-and-error approach and knowledge obtained from previous studies. As a case study, 11 a of hourly observed SL and wind data of the Xiuying Station, Hainan Province, China, were organised as inputs for training to verify the feasibility and superiority of the proposed models. The results show that CNN and LSTM had evident advantages over support vector regression (SVR) and multilayer perceptron (MLP), and the combined models outperformed the individual models (CNN and LSTM), mostly by 4％–6％. However, on comparing the model computed predictions during two severe typhoons that resulted in extreme storm surges, the accuracy was found to improve by over 10％ at all forecasting steps.     

Estimate of contribution of near-inertial waves to the velocity shear in the Bay of Bengal based on mooring observations from 2013 to 2014

Near-inertial motions contribute most of the velocity shear in the upper ocean. In the Bay of Bengal (BoB), the annual-mean energy flux from the wind to near-inertial motions in the mixed layer in 2013 is dominated by tropical cyclone (TC) processes. However, due to the lack of long-term observations of velocity profiles, our knowledge about interior near-inertial waves (NIWs) as well as their shear features is limited. In this study, we quantified the contribution of NIWs to shear by integrating the wavenumber-frequency spectra estimated from velocity profiles in the upper layers (40?440 m) of the southern BoB from April 2013 to May 2014. It is shown that the annual-mean proportion of near-inertial shear out of the total is approximately 50%, and the high contribution is mainly due to the enhancement of the TC processes during which the near-inertial shear accounts for nearly 80% of the total. In the steady monsoon seasons, the near-inertial shear is dominant to or at least comparable with the subinertial shear. The contribution of NIWs to the total shear is lower during the summer monsoon than during the winter monsoon owing to more active mesoscale eddies and higher subinertial shear during the summer monsoon. The Doppler shifting of the M₂ internal tide has little effect on the main results since the proportion of shear from the tidal motions is much lower than that from the near-inertial and subinertial motions.     

The cumulative characteristics of PAEs in PM2.5 in Changji,Northwest China

ABSTRACT

This paper discusses characteristics of the seasonal variation in phthalate acid esters (PAEs) in the PM_2.5 in the city of Changji, which is located an arid area of Xinjiang Province, northwest China. Samples were collected using a Laoying 2030 median discharge intelligent total suspended particulate (TSP) sampler and analyzed by a Shimadzu GC-2010 gas chromatograph. The results showed that PAEs in PM_2.5 were mainly composed of phthalic acid dibutyl phthalate (DBP) and phthalic acid (2-)ethyl hexyl ester (DEHP). DBP and DEHP are the most commonly used plasticizers, accounting for the majority of plasticizers used, and have large environmental emissions. Compared with the proportions of TSPs, proportions of DBP and DEHP in the PM_2.5 were lower, while the proportions of DMP and DEP were higher. A correlation exists between the distribution of PAEs and the particle size and concentration of atmospheric particulates. Seasonal variations in DBP and DEHP were the same, with lowest concentrations in the summer. Although seasonal variation in DMP was not the same as those of DBP and DEHP, the general trend was similar. Seasonal variation in DEP was different from those of other PAEs. This pattern is related to PAE characteristics and seasonal variations in their sources.     

Rutile inclusions in garnet from a dissolution‐reprecipitation mechanism

Metamorphic garnet commonly contains needle‐like rutile inclusions as well as equant rutile inclusions that surround quartz inclusions and range in size from submicrometer to nanometer. Although the origin of these equant rutile inclusions, that is, exsolution or non‐exsolution, has important implications for petrological and tectonic processes, the crystallographic characteristics of these inclusions have rarely been studied because of the small sizes and analytical difficulties involved. Here, we report the crystallographic characteristics pertinent to the genetic origin of minute equant rutile inclusions in cloudy, nearly spherically shaped garnet domains with Ti‐depleted compositions surrounding quartz inclusions in ultrahigh‐pressure garnet from several diamondiferous Erzgebirge quartzofeldspathic gneissic rock samples. TEM analyses show that the equant rutile crystals in cloudy garnet domains are partially bounded by the low‐energy {100}_rt ± {110}_rt ± {101}_rt facets and have rather random crystallographic orientation relationships (CORs) with the garnet host, with preferential alignment of low‐energy lattice planes, for example, {100}_rt//{112}_grt, for some rutile crystals. Although the rather random CORs are unlikely to be attributed to solid‐state exsolution subjected to the stringent topotactic garnet lattice constraints, the characteristic subhedral {100}_rt ± {110}_rt ± {101}_rt crystal forms of rutile can be rationalized by a metasomatic dissolution‐reprecipitation mechanism via a fluid phase. In this scenario, the quartz+fluid inclusions in garnet were first subjected to decompression microcracking during rock exhumation, followed by dissolution of Ti‐bearing garnet matrix at the crack tips or along the crack surfaces and subsequent reprecipitation of rutile, apatite, gahnite, akdalaite, and Ti‐depleted garnet. The rapid coalescence between rutile and garnet crystals in fluid or direct attachment of rutile crystals onto the dissolving crack surfaces would then yield the rather random CORs as reported here. These results, along with previous work on rutile needles, indicate rather diverse genesis of rutile inclusions in various crystal forms, thus shedding light on the controversial exsolution origin for other inclusion suite/microstructure in minerals.     

北京零售业的空间分布及影响因素

零售业是生活性服务业的重要组成部分,传统零售业通常通过零售商业网点形式展开。零售商业网点具有数量多、分布广、差异大等特点,其区位选择不仅影响居民的生活品质,也关乎商业网点空间布局的合理性。北京中心城区的零售业整体及其各细分行业均呈现出显著的空间集聚态势,集聚中心主要沿长安街及其延长线分布。影响零售业的区位选择因素包括交通通达性、地价成本、消费市场规模、消费偏好、政策引导、城市商业发展历史等。近年来,随着零售业与互联网的深度融合,零售业区位选择的影响因素及其作用方式不断发生变化,需要更多关注“新零售时代”对零售业空间布局的影响。     

Ionospheric and receiver DCB-constrained multi-GNSS single-frequency PPP integrated with MEMS inertial measurements

Single-frequency precise point positioning (SF-PPP) is a potential precise positioning technique due to the advantages of the high accuracy in positioning after convergence and the low cost in operation. However, there are still challenges limiting its applications at present, such as the long convergence time, the low reliability, and the poor satellite availability and continuity in kinematic applications. In recent years, the achievements in the dual-frequency PPP have confirmed that its performance can be significantly enhanced by employing the slant ionospheric delay and receiver differential code bias (DCB) constraint model, and the multi-constellation Global Navigation Satellite Systems (GNSS) data. Accordingly, we introduce the slant ionospheric delay and receiver DCB constraint model, and the multi-GNSS data in SF-PPP modular together. In order to further overcome the drawbacks of SF-PPP in terms of reliability, continuity, and accuracy in the signal easily blocking environments, the inertial measurements are also adopted in this paper. Finally, we form a new approach to tightly integrate the multi-GNSS single-frequency observations and inertial measurements together to ameliorate the performance of the ionospheric delay and receiver DCB-constrained SF-PPP. In such model, the inter-system bias between each two GNSS systems, the inter-frequency bias between each two GLONASS frequencies, the hardware errors of the inertial sensors, the slant ionospheric delays of each user-satellite pair, and the receiver DCB are estimated together with other parameters in a unique Kalman filter. To demonstrate its performance, the multi-GNSS and low-cost inertial data from a land-borne experiment are analyzed. The results indicate that visible positioning improvements in terms of accuracy, continuity, and reliability can be achieved in both open-sky and complex conditions while using the proposed model in this study compared to the conventional GPS SF-PPP.     

Discovering spatial and temporal patterns from taxi-based Floating Car Data: a case study from Nanjing

Floating Car Data (FCD) refers to the trajectories of vehicles equipped with Global Positioning System-enabled devices that automatically record location-related data within a short time interval. As taxies in Chinese cities continually drive along the streets seeking passengers, FCD can easily traverse the entire street network in a city on a daily basis. Taking advantage of this situation, this study extracted passenger pickup and drop-off locations from FCD sourced from 6445 taxis over a 2-week period in Nanjing, China to discover human behavioral patterns and the dynamics behind them. In this study, road nodes are converted to the points, based on which Thiessen polygons are generated to divide the study area into small areas with the goal of exploring the spatial distribution of pickup and drop-off locations. Moran’s I index is used to calculate the spatial autocorrelation of the spatial distribution of pickup and drop-off locations, and hot spot analysis is used to identify statistically significant spatial clusters of hot and cold spots. The spatial and temporal patterns of FCD in the study area are investigated, and the results show that: (1) the temporal patterns show a strong daily rhythm, (2) the spatial patterns show that the number of pickup and drop-off locations gradually diminish from the downtown areas to the outer suburbs, (3) the spatiotemporal patterns exhibit large differences over time, and (4) the driving forces explored by regression models indicate that population density and transportation density are consistent with the population distribution, but per capita disposable income is not consistent with the population distribution.     

城镇化与房价变动的空间计量——基于省级面板数据分析

基于2001—2015年中国31个省份(不含港澳台地区)的面板数据,运用空间面板模型,分析了城镇化对房地产价格水平的影响。研究发现:在考察期内,人口城镇化率、产业城镇化率、房屋施工面积对房地产价格水平产生显著的正向影响,城镇化投资额对房地产价格水平产生显著的负向影响;人口城镇化率、产业城镇化率、城镇化投资额、人均GDP、绿化面积、房屋施工面积的空间滞后项对房地产价格水平产生显著的正向影响,空间溢出效应显著。为此,需要优化城镇化投资结构,提高人口城镇化质量,强化产城融合,促进房地产价格合理稳定运行。     

青藏高原沙漠化土地空间分布及区划

利用野外调查数据、遥感影像和已有研究成果,构建了一套适用于青藏高原沙漠化土地的分类分级指标体系及遥感解译标志。以此为基础,选取目视解译法监测青藏高原沙漠化土地的空间分布特征。结果表明：2015年青藏高原沙漠化土地面积392 913km²,占高原土地总面积的15.1%,主要包括沙质沙漠化土地、砾质沙漠化土地和风蚀残丘3种类型。沙漠化土地以中度和轻度沙漠化土地为主,重度和极重度沙漠化土地面积仅占沙漠化土地总面积的12.2%。空间上,沙漠化土地集中分布在高原的北部和西部地区,其他地区零散分布。自东南向西北,沙漠化土地面积逐渐增大,沙漠化程度不断加重。以沙漠化土地空间分布数据（面积、类型、程度、空间特征和驱动因素）为基础,结合气候、地貌、第四纪沉积物和人类活动等数据,将青藏高原沙漠化区划分为雅鲁藏布江半干旱高山宽谷沙漠化区、藏北青南高寒高原面沙漠化区、柴达木干旱盆地沙漠化区、黄河上游半干旱河流盆地沙漠化区和“三江”流域湿润半湿润高山沙漠化区。