Influence of artificial freezing onliquefaction characteristics of Nanjing sand

Purpose–This study purposes to study the influence of artificial freezing on the liquefaction characteristics of Nanjing sand,as well as its mechanism.Design/methodology/approach–was studied through dynamic triaxial tests by means of the GDS dynamic triaxial system on Nanjing sand extensively discovered in the middle and lower reaches of the Yangtze River under seismic load and metro train vibration load,respectively,and potential hazards of the two loads to the freezing construction of Nanjing sand were also identified in the tests.Findings–The results show that under both seismic load and metro train vibration load,freeze-thaw cycles will significantly reduce the stiffness and liquefaction resistance of Nanjing sand,especially in the first freezethaw cycle;the more freeze-thaw cycles,the worse structural behaviors of silty-fine sand,and the easier to liquefy;freeze-thaw cycles will increase the sensitivity of Nanjing sand’s dynamic pore pressure to dynamic load response;the lower the freezing temperature and the effective confining pressure,the worse the liquefaction resistance of Nanjing sand after freeze-thaw cycles;compared to the metro train vibration load,the seismic load in Nanjing is potentially less dangerous to freezing construction of Nanjing sand.Originality/value–The research results are helpful to the construction of the artificial ground freezing of the subway crossing passage in the lower reaches of the Yangtze River and to ensure the construction safety of the subway tunnel and its crossing passage.

Application of artificial neural network for calculating anisotropic friction angle of sands and effect on slope stability

The anisotropy effect is one of the most prominent phenomena in soil mechanics. Although many experimental programs have investigated anisotropy in sand, a computational procedure for determining anisotropy is lacking. Thus, this work aims to develop a procedure for connecting the sand friction angle and the loading orientation. All principal stress rotation tests in the literatures were processed via an artificial neural network. Then, with sensitivity analysis, the effect of intrinsic soil properties,consolidation history, and test sample characteristics on enhancing anisotropy was examined. The results imply that decreasing the grain size of the soil increases the effect of anisotropy on soil shear strength. In addition, increasing the angularity of grains increases the anisotropy effect in the sample. The stability of a sandy slope was also examined by considering the anisotropy in shear strength parameters. If the anisotropy effect is neglected, slope safety is overestimated by 5%-25%. This deviation is more apparent in flatter slopes than in steeper ones. However, the critical slip surface in the most slopes is the same in isotropic and anisotropic conditions.

Plant water use strategies in the Shapotou artificial sand-fixed vegetation of the southeastern margin of the Tengger Desert, northwestern China

Stable oxygen and hydrogen isotopic compositions(δ^(18)O and δD) of plant xylem water and its potential water sources can provide new information for studying water sources, competitive interactions and water use patterns of plants. The contributions of different water sources to three plants, Hedysarum scoparium(HS), Caragana Korshinskii(CK) and Artemisia ordosica(AO), were investigated in the artificial sand-fixed vegetation of Shapotou, the southeastern margin of the Tengger Desert of northwestern China, based on meteorological data and δ^(18)O and δD values of precipitation, groundwater, soil water and xylem water of HS, CK and AO. Our results indicated that soil water infiltration through precipitation was the main water source of the artificial sand-fixed vegetation. Obvious differences in soil water content and in δ^(18)O of soil water and xylem water were found among different seasons. No relationship was found between the δ^(18)O in plant xylem water and in soil water in January. The same water use patterns were found in CK, HS and AO in May, suggesting they have the same water sources. The different water sources of CK, HS and AO in August indicate that water competition occurred. In addition, the main water sources of CK, HS and AO in August mainly come from shallow soil water, while they use relatively deep soil water in May. This phenomenon is related to the differences of soil water content throughout soil profile, precipitation, transpiration and water competition under different growth periods. The water use patterns of CK, HS and AO respond to soil water content throughout the soil profile and their competition balance for water uptake during different growth season. The results indicate that these sandfixed plants have developed into a relatively stable stage and they are able to regulate their water use behavior as a response to the environmental conditions, which reinforces the effectiveness of plantation of native shrubs without irrigation in degraded areas.

The Concert between Geology and Artificial Intelligence:Automatic Identification of Heavy Minerals from River Sand

Heavy minerals with densities higher than 2.8 g.cm-3 are generally considered minor components of sand or sandstone,typically forming 1%of the weight in the samples(Mange and Wright,2007).Heavy-mineral analysis is an effective tool for studying the sedimentary provenance of siliciclastic rocks,reconstructing sedimentary sources to sink routes,subdividing and correlating non-fossiliferous siliciclastic strata.

Soil restoration research advances of artificial sand-binding vegetation ecosystem in the Tengger Desert, Northern China

Soil plays an important role in desert ecosystem, and is vital in constructing a steady desert ecosystem. The management and restoration of desertified land have been the focus of much discussion. The soil in Shapotou desert region has developed remarkably since artificial sand-binding vegetation established in 1946. The longer the period of dune stabilization, the greater the thickness of microbiotic crusts and subsoil. Meanwhile, proportion of silt and clay increased significantly, and soil bulk density declinced. The content of soil organic matter, N, P, and K similarly increased. Therefore, soil has developed from aeolian sand soil to Calcic-Orthic aridisols. This paper discusses the effects brought about by dust, microbiotic soil crust and soil microbes on soil-forming process. Then, we analyzed the relation between soil formation and sand-binding vegetation evolution, in order to provide a baseline for both research on desert ecosystem recovery and ecological environment governance in arid and semi-arid areas.

The Feasibility of Basalt Rock Powder and Superfine Sand as Partial Replacement Materials for Portland Cement and Artificial Sand in Cement Mortar

The research gap on the feasibility of basalt rock powder(BRP)and superfine sand(SS)in preparation of cement mortar is significant.This study examines probable changes occurred in the modified cement mortar due to incorporation of certain quantity of basalt rock powder and superfine sand in mixture proportion.The cement mortar included Portland cement,artificial sand and water as principal mixture constituents.Then,basalt rock powder and superfine sand were added as partial replacement materials for Portland cement and artificial sand respectively.Therefore,replacement percentages were 10%,15%,20%,25%and 30%when the basalt rock powder replaced Portland cement and in case the artificial sand was replaced by superfine sand,10%,20%,30%,40%and 50%.Then,the strength indexes such as flexural strength,compressive strength,ultrasonic pulse velocity and dynamic elastic modulus were investigated.The results show that the presence of basalt rock powder in mixture proportion increased the flexural and compressive strengths of cement mortar however the cement mortar that contained superfine sand illustrated inadequate mechanical performance as flexural and compressive strengths decreased remarkably.Moreover,when basalt rock powder and superfine sand were included together in mixture proportion,the cement mortar’s mechanical performance declined compared to that of the reference cement mortar.Despite the fact that basalt rock powder and superfine sand weakened the cement mortar’s mechanical properties,it was found that they can be added into the cement mortar as partial replacement of Portland cement and artificial sand in the following ratios:from 10%to 25%when basalt rock powder replaces Portland cement and from 10%to 20%when artificial sand is replaced by superfine sand.

Predicting standard penetration test N-value from cone penetration test data using artificial neural networks

Standard Penetration Test（SPT） and Cone Penetration Test（CPT） are the most frequently used field tests to estimate soil parameters for geotechnical analysis and design.Numerous soil parameters are related to the SPT N-value.In contrast,CPT is becoming more popular for site investigation and geotechnical design.Correlation of CPT data with SPT N-value is very beneficial since most of the field parameters are related to SPT N-values.A back-propagation artificial neural network（ANN） model was developed to predict the N6o-value from CPT data.Data used in this study consisted of 109 CPT-SPT pairs for sand,sandy silt,and silty sand soils.The ANN model input variables are：CPT tip resistance（qc）,effective vertical stress（σ’v）,and CPT sleeve friction（fs）.A different set of SPT-CPT data was used to check the reliability of the developed ANN model.It was shown that ANN model either under-predicted the N60-value by 7-16%or over-predicted it by 7-20%.It is concluded that back-propagation neural networks is a good tool to predict N60-value from CPT data with acceptable accuracy.

Feasibility of measuring moisture content of green sand by a low frequency multiprobe detector based on dielectric characteristics

Green sand is a mixture of silica sand,bentonite,water and coal powder,and other additives.Moisture content is an important index to characterize the properties of green sand.Based on the dielectric characteristics of green sand and transmission line theory,a method for rapidly measuring the moisture content of green sand by means of a low frequency multiprobe detector was proposed.A system was constructed,where six detectors with different arrangements and probes were designed.The experimental results showed that the voltage difference of transmission line increases with the increasing frequency before 29 MHz while decreases after 35 MHz.A voltage difference platform occurs in the range of 29-35 MHz,which is suitable for measuring the moisture content due to its insensitivity to frequency.The electric field intensity gradually decreases with the increase of the probe depth,and the intensity of central probe is always greater than that of the edge probe.When the distance of the probe away from the sand sample surface is 80 mm,the electric field intensity of the edge probe is found to be very weak.The optimal excitation frequency for measuring the moisture content of green sand is 29-33 MHz.The optimal detector is the one with one center probe and three edge probes,and their lengths are 80 mm and 60 mm,respectively.The distance between the center and edge probes is 25 mm,and the diameter of probes is 5 mm.Taking the voltage difference of transmission line,bentonite content,coal powder content and compactability as parameters of the input layer,and the moisture content as a parameter of the output layer,a three-layer BP artificial neural network model for predicting the moisture content of green sand was constructed according to the experimental results at 33 MHz.The prediction error of the model is not higher than 3.3% when the moisture content of green sand is within the range of 3wt.%-7wt.%.

Erosion hotspot identified along the sandy coast of Shanwei: characteristics and origin

Based on the measured beach profile data of Sanzhou Bay from 2015 to 2019,an erosion hotspot was identified along the Shanwei coastline of eastern Guangdong,where the maximum retreat distance of the shoreline exceeded 80 m and the erosion rate was more than 20 m/a.To determine the time at which the erosion hotspot started and the potential causes of its formation,this study used 63 Landsat satellite images from 1986 to 2019 to construct a time series of shoreline positions over the past 30 years by extracting their high-tide shorelines.Next,the M-K trend test method was introduced to evaluate the non-linear shoreline behavior based on the single-transect method.The results showed that the time of approximately 2013 marked the start of the erosion hotspot,the erosion hotspot was characterized by erosion rates of more than 2 m/a(a maximum rate of 31.6 m/a),and the affected shoreline more than 4.3 km from 2013 to 2019.Furthermore,this erosion hotspot was proved to be caused by artificial sand mining in the nearshore zone,which destroyed the original beach’s morphodynamic equilibrium.With the aid of storm events,soil cliffs composed of loose sediment on the backshore were sacrificed to achieve a new equilibrium,resulting in an extremely significant retreat parallel to the coast on the west side of the study area,which reflects the combined effect of human and natural processes.This study provides a concrete example of the rapid response of shorelines to artificial sand mining activities,and the associated finding is a stark warning about the cautious development and utilization of coastal zones and the strict regulation of human activities.

支撑剂回流对页岩人工裂缝导流能力影响试验

支撑剂回流对页岩人工裂缝导流能力的伤害不容忽视,须对实际应力加载条件下支撑剂回流进行定量表征。利用自主研发的导流能力测试系统,通过添加支撑剂回流腔体模块,实现压裂液返排过程中支撑剂回流的定量表征,在实验室尺度下开展不同应力加载方式(变围压测试和变流压测试)下的页岩人工裂缝长期导流能力对比试验。结果表明:不同应力加载方式对支撑剂破碎量和嵌入量的影响相似,但变围压测试下支撑剂回流量随围压变化维持在约4.46%,与现场支撑剂回流数据不符;变流压测试下支撑剂回流量在流压20 MPa时的支撑剂回流量为20.53%,且随着流压的降低,回流量下降,与现场支撑剂的回流变量变化规律一致;忽略支撑剂的回流会导致对裂缝导流能力伤害率的计算值偏低,不利于制定施工方案;页岩人工裂缝导流能力的准确测试,应采用与实际应力加载更符合的变流压测试方法,以便更好地体现支撑剂回流对导流能力的影响。

智能机械臂在沙画创作中的辅助创新实践

目的随着智能技术在人机交互领域的发展,设计学科创作领域的智能协同更加多样化,沙画需要依靠智能技术的力量突破创作技法上的困境。方法本文结合人工智能的发展和在设计方面的应用技术,分析了和沙画相结合的技术基础,梳理了沙画创作的流程,并确定了沙画领域中的应用需求及创作主体与人工智能的关系,结合机械臂辅助沙画师创作,以人机协同《沙画颂祖国》项目对可行性进行论证。结果本研究将形成人机认知共生、智能技术支撑、创意主体协作、智能互动创作的体系,不仅切实解决了沙画行业辅助创作的难题,而且增加了设计学科交互的多样性,提供了未来融合的新方向。

利用条件生成对抗网络建立曲流河地质模型

【目的】在传统的河道建模方法中,基于目标的方法难以刻画曲流河点坝且条件化困难,多点地质统计学则难以再现河道的连续形态。条件生成对抗网络可以生成满足一定条件的复杂图形,可解决曲流河地质模型建立过程中点坝、河流形态刻画困难及难以条件化的问题。【方法】以鄂尔多斯盆地苏里格气田南部地区某气田为例,开展了基于条件生成对抗网络的曲流河三维建模方法研究。在建模过程中,首先采用Alluvsim建模方法根据工区曲流河特征建立了200个曲流河模型;再通过卷积神经网络对200个模型进行深度学习,提取模型的特征矩阵,利用条件生成对抗网络建立可以生成曲流河模型的生成器;最后以工区井点数据作为输入数据,利用生成器建立满足曲流河复杂形态和井点数据的三维模型。【结果与结论】所建立的模型可以很好地展现曲流河中河道与点坝的三维形态及对应关系。为明确影响模型结果的关键因素,通过对比训练次数与输入数据发现,适当的训练次数(160次)与大量地输入样本(200个)是建立满足工区条件模型的前提。另外,通过对比传统地质建模方法,条件生成对抗网络建模方法可以很好地再现河道沉积体的空间形态,克服传统曲流河建模方法在条件化方面的困难,为曲流河沉积环境的河道砂体建模提供了新的解决思路,建立的曲流河模型可为油田开发阶段提供参考。

腾格里沙漠固沙植被区蚂蚁群落分布特征及其对土壤理化性质的影响

为了阐明固沙过程中蚂蚁群落结构分布特征及其对土壤性质的影响,在腾格里沙漠固沙植被区选取流动沙地以及5 a、8 a、34 a和57 a固沙植被区为研究样地,对不同样地蚂蚁群落的个体数、类群数以及蚁丘内外土壤理化性质进行测定,进而分析了不同样地蚂蚁群落分布特征及其与土壤因子间的关系。结果表明:(1)固沙植被区蚂蚁群落中的优势类群为掘穴蚁(Formica cunicularia),个体数占比为78.87%。(2)57 a固沙植被区蚂蚁密度显著低于8 a和34 a固沙植被区(P<0.05);5 a固沙植被区蚂蚁类群数显著低于其他植被区(P<0.05)。(3)57 a固沙植被区蚁丘中土壤含水量、土壤黏粒和土壤全钾显著高于非蚁丘,而土壤电导率和土壤粉粒显著低于非蚁丘(P<0.05)。8 a和57 a固沙植被区蚁丘中土壤pH显著高于非蚁丘,8 a固沙植被区蚁丘中土壤有机碳显著高于非蚁丘,8 a和34 a固沙植被区蚁丘中土壤全氮显著高于非蚁丘(P<0.05)。(4)蚂蚁群落组成与土壤粒径、电导率、pH、有机碳、全氮、全磷和有效磷含量的相关关系显著;偏RDA结果表明,蚂蚁类群数是影响固沙区土壤理化性质的主要限制因子。综合表明,腾格里沙漠不同固沙年限植被区蚂蚁群落组成差异较大,更丰富的蚂蚁群落有利于改善土壤质地,促进土壤理化性质向良好的方向发展,对实现荒漠生态系统恢复起到推进作用。

Using deep neural networks coupled with principal component analysis for ore production forecasting at open-pit mines

Ore production is usually affected by multiple influencing inputs at open-pit mines.Nevertheless,the complex nonlinear relationships between these inputs and ore production remain unclear.This becomes even more challenging when training data(e.g.truck haulage information and weather conditions)are massive.In machine learning(ML)algorithms,deep neural network(DNN)is a superior method for processing nonlinear and massive data by adjusting the amount of neurons and hidden layers.This study adopted DNN to forecast ore production using truck haulage information and weather conditions at open-pit mines as training data.Before the prediction models were built,principal component analysis(PCA)was employed to reduce the data dimensionality and eliminate the multicollinearity among highly correlated input variables.To verify the superiority of DNN,three ANNs containing only one hidden layer and six traditional ML models were established as benchmark models.The DNN model with multiple hidden layers performed better than the ANN models with a single hidden layer.The DNN model outperformed the extensively applied benchmark models in predicting ore production.This can provide engineers and researchers with an accurate method to forecast ore production,which helps make sound budgetary decisions and mine planning at open-pit mines.

人工砂游离云母含量对混凝土性能的影响

云母含量影响着许多地区机制砂应用,由于目前云母含量对混凝土性能的影响研究不够完善,考虑到工程安全问题,国内标准对机制砂中云母含量的限制过于保守,导致许多水电工程中高云母含量人工骨料无法使用。为了使高云母含量的机制砂得到广泛应用,使用高云母含量原岩轧制的人工砂,通过外掺游离云母的方式,研究人工砂中不同游离云母含量对混凝土力学性能、拉伸性能、抗冻性能、抗渗性能的影响。由试验结果可以得出:云母含量对混凝土抗压强度、劈拉强度、抗渗性能影响较小,随着云母含量增加,混凝土单位用水量增加,轴拉强度和极限拉伸值略有降低,抗冻性能变差。

超耐污高耐候多彩花岗岩涂料的制备及研究

系统地研究了不同保护胶、纤维素和乳胶的种类、用量对水包砂多彩花岗岩涂料的彩点、稳定性、耐水白性、耐沾污性和耐人工老化性的影响。结果表明:当造粒保护胶Hatorite S482溶液浓度在4.0%~6.0%,纤维素醚250HHBR用量在0.5%(质量分数,后同)、HE10K用量在0.1%,基础涂料乳胶选用AP-4765,添加量在14%~18%,连续相乳胶选择8087与RS-3765进行复配,总量控制在70%~80%,其制得的水包砂多彩花岗岩涂料,彩点不仅具有优异的韧性、均匀度、丰满度、抗渗色性,而且具有优异的贮存稳定性、耐水白、耐沾污性和耐人工老化性。

某水电站工程人工堆积砂砾石特性研究与处理

汉江新集水电站泄水闸地基部分因人工堆积砂砾石而扰动,为确定其工程特性,基于常规勘察手段并综合运用室内大型压缩试验、三轴剪切试验、渗透变形试验及原位大型抗剪强度试验,系统研究了人工堆积砂砾石层的物理、力学及渗透特性,取得了较为安全、可靠的岩土参数,为工程设计、施工提供了重要技术支撑,制定了较为经济、合理的处理措施。可供类似工程地质条件的勘测、设计与施工借鉴。

人工砂中石粉含量对混凝土物理力学性能的微观影响

通过总结人工砂的应用现状及背景,从人工砂的特点出发,对人工砂中不同石粉含量对混凝土物理力学性能的影响进行研究。以河南商丘石屑人工砂制品为例,进行电镜扫描试验分析,研究结果表明:石粉含量(质量分数)在6%~15%时,和易性变好、混凝土强度高、强灰比大;当石粉含量超过20%时,和易性虽变好但强度变低、强灰比变小。放大2000倍电镜显示,混凝土中人工砂与水泥凝胶C-S-H间结合良好,人工砂界面无裂缝,达到了良好的效果。

Damage by wind-blown sand and its control measures along the Taklimakan Desert Highway in China

Desertification is one of the most serious environmental problems in the world,especially in the arid desert regions.Combating desertification,therefore,is an urgent task on a regional or even global scale.The Taklimakan Desert in China is the second largest mobile desert in the world and has been called the''Dead Sea''due to few organisms can exist in such a harsh environment.The Taklimakan Desert Highway,the longest desert highway(a total length of 446 km)across the mobile desert in the world,was built in the 1990s within the Taklimakan Desert.It has an important strategic significance regarding oil and gas resources exploration and plays a vital role in the socio-economic development of southern Xinjiang,China.However,wind-blow sand seriously damages the smoothness of the desert highway and,in this case,mechanical sand control system(including sand barrier fences and straw checkerboards)was used early in the life of the desert highway to protect the road.Unfortunately,more than 70%of the sand barrier fences and straw checkerboards have lost their functions,and the desert highway has often been buried and frequently blocked since 1999.To solve this problem,a long artificial shelterbelt with the length of 437 km was built along the desert highway since 2000.However,some potential problems still exist for the sustainable development of the desert highway,such as water shortage,strong sandstorms,extreme environmental characteristics and large maintenance costs.The study aims to provide an overview of the damages caused by wind-blown sand and the effects of sand control measures along the Taklimakan Desert Highway.Ultimately,we provide some suggestions for the biological sand control system to ensure the sustainable development of the Taklimakan Desert Highway,such as screening drought-resistant species to reduce the irrigation requirement and ensure the sound development of groundwater,screening halophytes to restore vegetation in the case of soil salinization,and planting cash crops,such as Cistanche,Wolfberry,Apocynum and other cash crops to decrease the high cost of maintenance on highways and shelterbelts.

Selection of candidate wells for re-fracturing in tight gas sand reservoirs using fuzzy inference

An artificial-intelligence based decision-making protocol is developed for tight gas sands to identify re-fracturing wells and used in case studies. The methodology is based on fuzzy logic to deal with imprecision and subjectivity through mathematical representations of linguistic vagueness, and is a computing system based on the concepts of fuzzy set theory, fuzzy if-then rules, and fuzzy reasoning. Five indexes are used to characterize hydraulic fracture quality, reservoir characteristics, operational parameters, initial conditions, and production related to the selection of re-fracturing well, and each index includes 3 related parameters. The value of each index/parameter is grouped into three categories that are low, medium, and high. For each category, a trapezoidal membership function all related rules are defined. The related parameters of an index are input into the rule-based fuzzy-inference system to output value of the index. Another fuzzy-inference system is built with the reservoir index, operational index, initial condition index and production index as input parameters and re-fracturing potential index as output parameter to screen out re-fracturing wells. This approach was successfully validated using published data.