基于尺寸效应的粗粒土单颗粒破碎试验及数值模拟

在外荷载等因素作用下,粗粒土易发生颗粒破碎。对泥岩和砂岩颗粒进行了一系列的单颗粒破碎试验,基于尺寸效应和颗粒破碎分形模型,研究了单颗粒破碎强度、破碎能量及Weibull模量等与分形维数间的关系。利用PFC3D对单颗粒破碎过程进行分析,并与试验数据对比,验证了数值程序的可靠性;随后扩展到大颗粒粒径,分析了其单破碎强度及破碎能量。结果表明：在同类试验条件下,不同材料所得的分形维数是不同的;不同粒径砂岩的破碎程度均大于泥岩;单颗粒破碎强度具有明显的尺寸效应;单颗粒破碎强度与破碎能量均可通过分形维数与颗粒粒径预测得出;修正后的Weibull模量也可通过分形维数得出;数值模拟结果与试验结果及预测结果基本一致;大颗粒粒径单颗粒破碎强度模拟结果与预测结果基本一致,破碎能量稍有差异,需进一步试验验证。研究成果可为获取大粒径粗粒土的单颗粒强度与变形特性提供参考。     

A novel type of neural networks for feature engineering of geological data:Case studies of coal and gas hydrate-bearing sediments

The nature of the measured data varies among different disciplines of geosciences.In rock engineering,features of data play a leading role in determining the feasible methods of its proper manipulation.The present study focuses on resolving one of the major deficiencies of conventional neural networks(NNs) in dealing with rock engineering data.Herein,since the samples are obtained from hundreds of meters below the surface with the utmost difficulty,the number of samples is always limited.Meanwhile,the experimental analysis of these samples may result in many repetitive values and 0 s.However,conventional neural networks are incapable of making robust models in the presence of such data.On the other hand,these networks strongly depend on the initial weights and bias values for making reliable predictions.With this in mind,the current research introduces a novel kind of neural network processing framework for the geological that does not suffer from the limitations of the conventional NNs.The introduced single-data-based feature engineering network extracts all the information wrapped in every single data point without being affected by the other points.This method,being completely different from the conventional NNs,re-arranges all the basic elements of the neuron model into a new structure.Therefore,its mathematical calculations were performed from the very beginning.Moreover,the corresponding programming codes were developed in MATLAB and Python since they could not be found in any common programming software at the time being.This new kind of network was first evaluated through computer-based simulations of rock cracks in the 3 DEC environment.After the model's reliability was confirmed,it was adopted in two case studies for estimating respectively tensile strength and shear strength of real rock samples.These samples were coal core samples from the Southern Qinshui Basin of China,and gas hydrate-bearing sediment(GHBS) samples from the Nankai Trough of Japan.The coal samples used in the experiments underwent nuclear magnetic resonance(NMR) measurements,and Scanning Electron Microscopy(SEM) imaging to investigate their original micro and macro fractures.Once done with these experiments,measurement of the rock mechanical properties,including tensile strength,was performed using a rock mechanical test system.However,the shear strength of GHBS samples was acquired through triaxial and direct shear tests.According to the obtained result,the new network structure outperformed the conventional neural networks in both cases of simulation-based and case study estimations of the tensile and shear strength.Even though the proposed approach of the current study originally aimed at resolving the issue of having a limited dataset,its unique properties would also be applied to larger datasets from other subsurface measurements.     

Effects of particle size on crushing and deformation behaviors of rockfill materials

Strength and deformation behaviors of rockfill materials,key factors for determining the stability of dams,pertain strongly to the grain crushing characteristics.In this study,single-particle crushing tests were carried out on rockfill materials with nominal particle diameters of 2.5 mm,5 mm and 10 mm to investigate the particle size effect on the single-particle strength and the relationship between the characteristic stress and probability of non-failure.Test data were found to be described by the Weibull distribution with the Weibull modulus of 3.24.Assemblies with uniform nominal grains were then subjected to one-dimensional compression tests at eight levels of vertical stress with a maximum of 100 MPa.The yield stress in one-dimensional compression tests increased with decreasing the particle size,which could be estimated from the single-particle crushing tests.The void ratio-vertical stress curve could be predicted by an exponential function.The particle size distribution curve increased obviously with applied stresses less than 16 MPa and gradually reached the ultimate fractal grading.The relative breakage index became constant with stress up to 64 MPa and was obtained from the ultimate grading at the fractal dimension(a?2:7).A hyperbolical function was also found useful for describing the relationship between the relative breakage index and input work during one-dimensional compression tests.     

Identification of failure slip surfaces for landslide risk assessment using smoothed particle hydrodynamics

ABSTRACT

Location of failure slip surfaces plays a critical role in landslide risk assessment and mitigation, particularly for unstable slopes, because it is a key input to design of stabilisation measures for unstable slopes and it determines the volume of the sliding soil mass (i.e. landslide consequence). The failure slip surfaces in the numerical analysis (e.g. finite element/different method, FEM/FDM) are often identified using shear strength reduction (SSR) method. A careful examination of FEM results showed that, although the SSR method performs well for stable slopes, it might provide misleading results for unstable slopes. To properly locate failure slip surfaces for unstable slopes, this paper presents a particle-based numerical method called smoothed particle hydrodynamics (SPH), which is mesh-free, immune to the mesh distortion problem in FEM/FDM, and able to directly simulate large deformation of soils that occurs during landslides. A series of slope stability analyses is performed using an in-house SPH programme. Failure slip surfaces are properly identified by SPH for both stable and unstable slopes. Furthermore, because SPH provides a spatial distribution of the post-landslide large displacement of soils, the failure slip surfaces can be identified conveniently using soil displacement. A displacement-based criterion is proposed to locate the failure slip surfaces.     

冻结粉质黏土-桩基接触面剪切特性试验研究

在寒区工程中, 建筑物的冻拔病害和冻土-桩基接触面间的剪切特性密切相关。借助自制的试验模具, 采用压桩法对冻结粉质黏土中埋置的混凝土桩、 钢桩以及木桩进行了不同负温条件下的剪切试验。结果表明： 在负温下随着剪切位移的增加, 剪切力经历线性增长、 骤降的脆性破坏、 维持恒定三阶段。温度越低, 桩与冻土间的冰胶结力越大, 冻结强度越大, 残余强度越大, 破坏允许位移也越大。在-30 ℃时, 木桩与冻土间的冻结强度最大, 混凝土桩与冻土间的冻结强度次之, 钢桩与冻土间的冻结强度最小。混凝土桩、 钢桩对应的冻结强度及残余强度与温度的关系可用线性拟合, 木桩对应的冻结强度及残余强度与温度的关系可用二次多项式拟合, 三种桩的破坏允许位移与温度的关系均呈现线性规律。研究成果可为寒区结构物抗冻拔病害防治提供参考。     

冻结作用下粉土-混凝土接触面抗拉强度试验研究

为探究冻结作用下土与结构接触面抗拉强度的影响因素及变化规律, 开展了冻结状态下多种含水率、 温度及干密度的粉土-混凝土接触面抗拉强度正交试验研究。试验结果表明： 在试验温度下,粉土-混凝土接触面的冻结抗拉强度约为饱和黄土的1/10, 粉质黏土的1/10 ~ 1/7; 含水率对接触面的冻结抗拉强度影响最大, 其次是温度、 干密度; 在试验含水率范围内, 接触面的冻结抗拉强度与含水率正相关; 温度降低会增大接触面冻结抗拉强度, 在-2 ℃至-6 ℃, 冻结抗拉强度迅速增长, 在-6 ℃以后, 冻结抗拉强度的增长速率显著减小。结果证明： 低温、 高含水率、 低干密度条件下, 接触面冻结抗拉强度达到最佳; 三种因素对接触面冻结抗拉强度具有不同的影响程度, 其中含水率、 温度影响显著, 干密度影响不显著; 在试验含水率区间内, 接触面冻结抗拉强度随含水率增长呈线性增长态势, 且含水率、 温度之间存在交互作用; 随温度降低, 存在一临界负温, 接触面冻结抗拉强度由迅速增长转为缓慢增长。     

氯盐和冻融耦合下水泥土的强度和破坏特征

为了研究氯盐侵蚀和冻融循环耦合下水泥土无侧限抗压强度和破坏特征, 进行了不同浓度氯化钠溶液下的水泥土冻融循环试验, 得到了冻融前后的冻融腐蚀因子、 体积变化率和变形模量, 分析了微观结构特征。结果表明： 在氯盐侵蚀和冻融循环耦合下, 水泥土的无侧限抗压强度、 冻融腐蚀因子均随着冻融循环次数的增加而呈现下降趋势; 氯盐浓度越高, 水泥土的无侧限抗压强度、 冻融腐蚀因子下降的幅度越大。随着冻融循环次数的增加, 在同种浓度溶液中, 水泥土的体积变化率增大, 变形模量减小; 氯盐浓度增大, 水泥土体积膨胀变大, 内部结构松散, 抵抗变形的能力减弱。相同冻融循环次数下, 氯盐溶液产生的损伤要大于清水中的损伤, 随着氯盐溶液浓度的增加, 水泥土内部微观结构损伤越严重。     

外加剂对低温水泥浆性能的影响试验研究

为解决在普通硅酸盐水泥（P.O42.5）或混凝土施工中遭遇低温环境而不能顺利凝固的问题。对普遍使用的硅酸盐水泥进行了基础性能测试试验,使用早强剂与高效减水剂对水泥进行调整性能,寻找出最佳的调整方案,对比调整前后水泥浆及水泥石强度等各项数据。结果表明10%早强剂、2‰JSS高效减水剂的调整方案较好地改善了水泥浆的流动性、凝结时间、水化热放热速率、结石率及水泥石的早期强度等问题。研究成果对低温条件下的混凝土施工有一定的参考价值。     

微波照射下矿物升温特性与岩石弱化效果研究综述

随着经济的快速发展,工程领域面对坚硬岩石的情况越来越多,传统机械开挖方式的效率和经济性难以保障,而微波辅助破岩具有较好的工程应用前景。岩石是由不同矿物组成的,不同矿物对微波的敏感程度不同,其敏感程度与矿物的族类、晶型和铁元素含量有关。当岩石处于微波场中时,不同敏感性矿物间的差异性膨胀能够在矿物边界和内部产生热应力,从而有效弱化岩石。影响岩石弱化效果的主要因素可分为微波条件和岩石条件两大类。一般而言,岩石强度随着微波功率与照射时间的增加而降低;相同能量条件下,高功率短时间的微波照射能够产生更好的弱化效果。岩石所含矿物的微波敏感性越高,敏感矿物的颗粒尺寸越大,及含量适当时,微波照射岩石的弱化效果越好;含水状态的岩石受到微波照射后,能够比干燥状态产生更大的损伤。微波的热效应有时还会使岩石中的矿物发生较大的物理或化学变化,进而对其升温特性及弱化效果产生影响。面照射试验表明微波能使大尺寸岩样在照射区域产生放射状裂纹,从而有效降低岩石强度,提高破岩效率。     

黄泛区粉砂土动强度与抗液化强度试验研究

因黄泛区粉砂土与其他地区有较大区别,对其动强度和抗液化强度的研究相对较少.对开封地区粉砂土的动强度和抗液化强度进行研究,选定围压、干密度、细粒含量作为影响因素,通过动三轴试验得到其动强度曲线和抗液化强度曲线,分别分析三个影响因素对黄泛区粉砂土动强度和抗液化强度的影响.结果表明:黄泛区粉砂土的动强度和抗液化强度随围压和干...