含砂量对水泥土强度影响的试验研究

天然软土尤其三角洲地区的淤泥或淤泥质黏土常含砂,以含细砂或粉细砂为主,系统研究水泥土强度与含砂量的关系,为水泥土性能改良、强度设计及水泥土搅拌法施工提供直接依据。选取珠江三角洲两处典型的淤泥、淤泥质黏土,按天然含水率配制试验用土,掺加不同含量的细砂制成含砂水泥土试件,养护到不同龄期,对其进行无侧限抗压强度试验,得到了水泥土强度与含砂量及其他关联影响因素关系的变化规律。主要结论是：细砂颗粒在水泥土中起到了细骨料的作用,有利于提高水泥土强度;考虑水泥土的含砂量、水土质量比、水泥掺入比和实际水灰比等因素,得到了含砂淤泥水泥土强度估算公式;在不含砂淤泥水泥土中掺入2 %干细砂时其强度约提高25 %,掺入15 %~25 %干细砂则可提高40 %~60 %。     

Application of Artificial Intelligence to Maximum Dry Density and Unconfined Compressive Strength of Cement Stabilized Soil

This paper describes two artificial intelligence techniques for prediction of maximum dry density (MDD) and unconfined compressive strength (UCS) of cement stabilized soil. The first technique uses various artificial neural network (ANN) models such as Bayesian regularization method (BRNN), Levenberg- Marquardt algorithm (LMNN) and differential evolution algorithm (DENN). The second technique uses the support vector machine (SVM) that is firmly based on the theory of statistical learning theory, uses regression technique by introducing ε-insensitive loss function has been adopted. The inputs of both models are liquid limit (LL), plasticity index (PI), clay fraction (CF)%, sand (S)%, gravel Gr (%), moisture content (MC) and cement content (Ce). The sensitivity analyses of the input parameters have been also done for both models. Based on different statistical criteria the SVM models are found to be better than ANN models for the prediction of MDD and UCS of cement stabilized soil.     

Some applications of Adaptive Neuro-Fuzzy Inference System (ANFIS) in geotechnical engineering

This paper presents a review of the Adaptive Neuro-Fuzzy Inference System (ANFIS) in current use for geotechnical engineering-based studies, as well as some applications employed in resonant column testing, triaxial testing, and liquefaction triggering. Over the last few years, ANFIS has been used in many geotechnical engineering problems. A review of published literature reveals that ANFIS has been used successfully in footing response prediction, modeling of the friction angle of soils, tunnel stability analysis, estimating current-induced scour depth around pile groups, prediction of unconfined compressive strength, swelling potential of soils and permeability estimation. Some works have been selected to be described, as the others are acknowledged. The paper also presents ANFIS based models for coarse rotund sand–mica mixtures tested in triaxial and resonant column testing apparatuses and a modeling for liquefaction triggering.     

A comparative assessment of sand and lime stabilization of residual micaceous compressible soils for road construction

Summary The presence of mica in pavements can be detrimental due to the effects of high compressibility and low compacted density it imparts to the soils. Three residual micaceous compressible soils derived from granite, granitic gneiss and phyllite can neither be used as base nor sub-base course in their untreated form. In this study, these soils have been treated with a range of lime and sand contents to determine their effects on consistency, compactability, bearing and compressive strengths and volume stability against swell. With 6–8% lime, soils derived over phyllite and granitic gneiss were rendered suitable for use as sub-base course as their plasticity index, 96 hour soaked CBR values and unconfined compressive strengths (UCS) were improved to satisfy existing local criteria. Similarly, with 30% sand both soils became suitable for sub-base course construction. The use of both additives markedly improved the volume stability of all the soils against swell.     

Effect of particle size distribution on the bio-cementation of coarse aggregates

The effect of grain size distribution on the unconfined compressive strength (UCS) of bio-cemented granular columns is examined. Fine and coarse aggregates were mixed in various percentages to obtain five different grain size distributions. A four-phase percolation strategy was adopted where a bacterial suspension and a cementation solution (urea and calcium chloride) were percolated sequentially. The results show that a gap-graded particle size distribution can improve the UCS of bio-cemented coarser granular materials. A maximum UCS of approximately 575 kPa was achieved with a particle size distribution containing 75% coarse aggregate and 25% fine aggregate. Furthermore, the minimum UCS obtained has applications where mitigation of excessive bulging of stone/sand columns, and possible slumping that might occur during their installation, is needed. The finding also implies that the amount of biochemical treatments can be reduced by adding fine aggregate to coarse aggregate resulting in effective bio-cementation within the pore matrix of the coarse aggregate column as it could substantially reduce the cost associated with bio-cementation process. Scanning electron microscopy results confirm that adding fine aggregate to coarse aggregate provides more bridging contacts (connected by calcium carbonate precipitation) between coarse aggregate particles, and hence, the maximum UCS achieved was not necessarily associated with the maximum calcium carbonate precipitation.     

固化铅污染土的干湿循环耐久性试验研究

在商用高岭土、膨润土与商业黄砂混合物中加入硝酸铅溶液,添加水泥和石灰两种固化剂,采用室内压实制样方法获得固化的铅污染土试样。进行干、湿循环试验,测试固化体的质量损失和无侧限抗压强度等参数随干、湿循环次数的变化规律,评价固化铅污染土的干、湿耐久性。测试结果表明,本试验8种配比的试样都满足干、湿循环的要求;黏土矿物为膨润土的试样干、湿循环耐久性比黏土矿物为高岭土的试样要差;水泥固化土的干、湿循环耐久性要略优于石灰固化土;加入 8 000 mg/kg的铅可略增大土体的抗干、湿循环耐久性。水泥和石灰固化/稳定化重金属污染土时,土体中含水率是保证加固效果的关键参数之一。土体中含水率应能满足固化剂充分水化、水解、火山灰和碳酸化反应之需要。     

用固化剂GX08加固杭州海湖相软土的强度特性研究

为了验证固化剂GX08加固杭州海湖相软土的效果及考察有机质对水泥固化的不利影响,对固化土的强度特性进行了试验研究。结果表明,有机质的添加会显著阻碍固化土强度的增长,而固化剂GX08能有效增强固化土的强度;固化土强度与有机质含量存在二次函数关系,与水泥掺量呈线性关系,与固化剂GX08掺量和龄期都以对数函数的形式相关;将总灰水比C/W用于固化土强度模型的建立,通过对试验数据的分析与整理,建立了同时考虑固化土中有机质含量、水泥掺量、固化剂掺量和龄期影响的固化土综合强度预测模型。最后对模型进行了推广使用,验证了模型的适用性。     

Vertical transport of polycyclic aromatic hydrocarbons in different particle-size fractions of sandy soils

Vertical transport of selected polycyclic aromatic hydrocarbons (PAHs) in different particle-size fractions of sandy soils was investigated by simulation experiments in soil columns. Tested soil samples were fractionized into three particle-sizes including sand, coarse silt and fine silt (2,000–50, 50–20 and <20 μm). Rainfall simulations were conducted in artificially PAHs contaminated soil columns with 30 cm length and 5 cm diameter in 40 days. PAHs were extracted from soil samples and determined by high performance liquid chromatography (HPLC). Results showed that the residue level of PAHs in fine silt fraction reached 35.85 mg/kg, which was significantly higher than those in sand and coarse silt fraction (16.28 and 11.80 mg/kg, respectively), probably because PAHs in macroporous fractions were prone to volatilize or degrade compared with that in microporous fractions. Linear relationship between the residue levels of individual PAH (R _PAHs) and the value of partition coefficient (log K _oc) was regressed as R _PAHs = 1.55 × log K _oc − 5.86, R ² = 0.91, n = 9. These results indicated that vertical transport of the mixed PAHs in soils were controlled both by the nature of PAHs (i.e. log K _oc, molecular weight), soil particle size and soil organic contents, which could influence the transport of PAHs.     

Effects of Non-Plastic Silts on Liquefaction Potential of Solani Sand

Loose saturated cohesionless soils are most susceptible to liquefaction, however there are strong historical evidence suggesting that soils containing fines such as silty sands are also prone to liquefaction during earthquakes. The liquefaction of silty sands has been observed in a number of recent case studies. This paper presents the effects of fine silts on liquefaction potential of sandy soil. Tests have been conducted on the vibration table at different accelerations and pore water pressure is measured. During the lab investigation, locally (Roorkee, India) available Solani Sand and Dhanauri Silt have been used. The soil samples have been prepared by varying silt content and the initial relative density. The results of the study performed are used to clarify the effects of non-plastic fines content on the Solani sand. As the silt content increases, the number of cycles required to produce maximum pore water pressure increases. For a particular level of excitation, rate of pore water pressure generation is maximum at critical silt content. It is observed that critical silt content to generate maximum pore water pressure is different for different accelerations. Further, effect of silt content is very much dependent on relative density.     

Physico-Chemical and Shrinkage Properties of Highly Organic Soil Treated with Non-traditional Additives

The changes in the shrinkage and physicochemical properties of untreated and treated organic soil using several chemical additives were investigated. In order to evaluate the effect of each chemical solution on the peaty soil environment different experiments namely; shrinkage limit, unconfined compressive strength (UCS), pH test, and water content were undertaken. The results of the laboratory experiments are further proved and interpreted using the X-ray diffraction, scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy tests. The result unveils the structure of the treated soil significantly changed depending upon the used additive type and concentrations. The rate of shrinkage largely decreased when sodium silicate additives are used. In addition, it was observed that UCS value increased up to 500% and water content reduced up to 50% in comparison with untreated samples, depend on the amount of used non-traditional additives. The SEM micrographs of the sample before and after treatment validate the results obtained and analyzed from experiments.     

Mechanical behavior and micro-structure of cement kiln dust-stabilized expensive soil

In this study, the effects of cement kiln dust (CKD) on the swelling properties, strength properties, and microstructures of CKD-stabilized expansive soil were investigated. Samples were prepared and stabilized with different CKD content ratios, ranging from 0 to 18% by dry mass. The results obtained show that the maximum swelling pressures decrease exponentially with increases in CKD content. Both the cohesion and unconfined compressive strength (UCS) increase at ratios below 10% CKD and then decrease slightly, above that ratio. CKD can also improve the strength of saturated, expansive soil. There is no visible change of UCS for soil without CKD when cured, while the UCS of a sample with 10% CKD content after curing for 90 days is higher than that after curing for only 1 day. This indicates that CKD can improve the long-term strength of expansive soil. Finally, microstructure analysis reveals that the addition of CKD reduces the montmorillonite content of expansive soil and decreases its swelling properties. The addition of CKD also changes the pore volume distribution, both the size and amount of macro-pores and micro-pores decrease with increase in CKD content. For saturated samples, the size of macro-pores is obviously reduced, while that of micro-pores is slightly increased for both treated and untreated soils. Hydration and saturation processes make the soil structure become dispersive which results in a lower strength, and adding CKD can restrain this process. The suggested optimal CKD content is between 10 and 14% and with a curing time of more than 27 days.     

Artificial Neural Network Prediction Models for Soil Compaction and Permeability

This paper presents Artificial Neural Network (ANN) prediction models which relate permeability, maximum dry density (MDD) and optimum moisture content with classification properties of the soils. The ANN prediction models were developed from the results of classification, compaction and permeability tests, and statistical analyses. The test soils were prepared from four soil components, namely, bentonite, limestone dust, sand and gravel. These four components were blended in different proportions to form 55 different mixes. The standard Proctor compaction tests were adopted, and both the falling and constant head test methods were used in the permeability tests. The permeability, MDD and optimum moisture content (OMC) data were trained with the soil’s classification properties by using an available ANN software package. Three sets of ANN prediction models are developed, one each for the MDD, OMC and permeability (PMC). A combined ANN model is also developed to predict the values of MDD, OMC, and PMC. A comparison with the test data indicates that predictions within 95% confidence interval can be obtained from the ANN models developed. Practical applications of these prediction models and the necessary precautions for using these models are discussed in detail in this paper.     

Prediction of unconfined compressive strength of carbonate rocks using artificial neural networks

The unconfined compressive strength (UCS) of intact rocks is an important geotechnical parameter for engineering applications. Determining UCS using standard laboratory tests is a difficult, expensive and time consuming task. This is particularly true for thinly bedded, highly fractured, foliated, highly porous and weak rocks. Consequently, prediction models become an attractive alternative for engineering geologists. The objective of study is to select the explanatory variables (predictors) from a subset of mineralogical and index properties of the samples, based on all possible regression technique, and to prepare a prediction model of UCS using artificial neural networks (ANN). As a result of all possible regression, the total porosity and P-wave velocity in the solid part of the sample were determined as the inputs for the Levenberg–Marquardt algorithm based ANN (LM-ANN). The performance of the LM-ANN model was compared with the multiple linear regression (REG) model. When training and testing results of the outputs of the LM-ANN and REG models were examined in terms of the favorite statistical criteria, which are the determination coefficient, adjusted determination coefficient, root mean square error and variance account factor, the results of LM-ANN model were more accurate. In addition to these statistical criteria, the non-parametric Mann–Whitney U test, as an alternative to the Student’s t test, was used for comparing the homogeneities of predicted values. When all the statistics had been investigated, it was seen that the LM-ANN that has been developed, was a successful tool which was capable of UCS prediction.     

中膨胀土CMA改性室内试验研究

CMA是一种新型膨胀土生态改性剂,依托合(肥)－六(安)－叶(集)高速公路工程,对CMA改性后中膨胀土的基本物理性质、击实特性、胀缩特性、力学特性等进行了3种配方的室内对比试验研究。结果表明,中膨胀土经CMA改性后,其自由膨胀率由改性前的71 %下降到20 %左右,液限和塑性指数也显著降低,亲水能力大幅度下降;胶粒含量明显下降,粉粒含量增加,说明改性后粒度组成已接近粉土;各项胀缩性指标较改性前也有大幅度下降,无荷膨胀率约为改性前的2 %,膨胀力约为改性前的5 %;改性土的CBR值可达50 %,浸水变形不到1 %;在非饱水和饱水状态下,改性土都具有较高的抗剪强度和无侧限抗压强度,说明改性后其水稳定性较好。经对比分析,认为1#配方改性效果最好,较适用于合肥膨胀土的改性处理。     

Adaptive neuro-fuzzy modeling for the swelling potential of compacted soils

This paper aims to present the usability of an adaptive neuro fuzzy inference system (ANFIS) for the prediction swelling potential of the compacted soils that are important materials for geotechnical purposes such as engineered barriers for municipal solid waste, earth dams, embankment and roads. In this study the swelling potential that is also one of significant parameters for compacted soils was modeled by ANFIS. For the training and testing of ANFIS model, data sets were collected from the tests performed on compacted soils for different geotechnical application in Nigde. Four parameters such as coarse-grained fraction ratio (CG), fine-grained fraction ratio (FG), plasticity index (PI) and maximum dry density (MDD) were presented to ANFIS model as inputs. The results obtained from the ANFIS models were validated with the data sets which are not used for the training stage. The analyses revealed that the predictions from ANFIS model are in sufficient agreement with test results.     

城市河道淤泥特性及改良试验初探

以南京内秦淮河疏浚淤泥为例,通过土工试验、XRD和X射线荧光光谱试验等方法,研究了城市河道淤泥的物理性质、矿物成分、化学成分等特性。试验结果显示:秦淮河淤泥粘粒含量低、有机质含量极高,矿物成分主要有石英和少量粘土矿物等。为了实现淤泥的资源化处理,运用水泥、石灰无机固化材料对淤泥进行固化改良试验及改性土无侧限抗压强度试验,结果表明随着水泥掺量增加,水泥固化土由塑性破坏向脆性破坏过渡,破坏应变在1.8%~2.2%,而石灰固化土均表现为脆性破坏,且破坏应变小于水泥土,为1%左右。水泥固化土28d强度为670kPa,固化效果优于石灰,但略低于处理一般软土的固化土强度。研究结果对处置城市河道淤泥有一定参考价值。     

Laboratory Study on the Relative Performance of Silty-Sand Soils Reinforced with Linen Fiber

Randomly distributed fibers have been successfully used for the reinforcement of soils to improve their properties. However, the technique requires extensive testing on samples before it can be implemented. Therefore, the purpose of this paper is to identify and quantify the influence of variables of linen-fiber (content and aspect ratio) on the performance of linen-fiber reinforced silty-sand specimens. The linen fibers have filament textures with special properties such as: low costs, plenitude in the region, lightweight, tension capacity and relative strength against deterioration. Linen fibers with diverse fiber contents (0.25, 0.50, 0.75 and 1.0% of dry weight) and ratio aspect (50, 100 and 150) were used. The composite soils were laboratory tested for compaction, unconfined compression strength (UCS), California Bearing Ratio (CBR) and direct shear tests. The test results indicated that adding linen fiber in silty-sand soil resulted in increasing in unconfined compression strength, California Bearing Ratio values, peak friction angle and cohesion values. Furthermore, adding linen fibers have the dual benefit of increasing the stiffness (modulus of elasticity) and the ductility of the reinforced soil. However, this study suggests that the optimum fiber content for silty-sand samples reinforced with linen fibers is approximately 0.75% of the dry weight of the soil and a maximum performance was achieved at aspect ratio of 100 to avoid fiber balling. The laboratory results were used for the development of linear regression equation that best relates the UCS and CBR of a reinforced soil to the aforementioned parameters.     

微生物胶结在防治堤坝破坏中的应用研究

为防治漫顶引起侵蚀造成堤坝破坏,将微生物诱导碳酸钙沉淀即MICP技术应用于加固堤坝表层。通过向堤坝表层喷洒微生物细胞以及营养盐,最终在砂土孔隙中快速析出碳酸钙胶凝结晶,以改善堤坝表层砂的力学性能。首先,采用喷洒法处理堤坝表层;其次,对处理好的堤坝模型进行水槽试验,研究其抗侵蚀性;最后,对堤坝表层的试样进行强度与渗透试验。试验结果表明,采用MICP技术加固堤坝模型表层可有效提高其抗侵蚀力,防治由漫顶引起的堤坝破坏。对加固后的表层取样进行测试,结果表明：无侧限抗压强度可高达9 MPa,渗透系数从4×10?4 m/s 降低至7.2×10?7 m/s。试验说明,微生物胶结技术在加固堤坝表层方面具有潜在的工程实用价值和广阔的应用前景。     

磷酸镁水泥固化铅污染土的力学特性试验研究及微观机制

采用磷酸镁水泥（MPC）对铅污染土进行固化/稳定化处理。基于无侧限抗压强度试验和渗透试验,研究了MPC添加量、水土比对固化污染土强度及渗透特性的影响规律。结果表明,固化土的强度随MPC添加量增加而增大,渗透系数减小;水土比对固化土的强度及渗透特性的影响均存在临界值,为0.45。低于临界值时,固化土的强度随着水土比的增加而增加,渗透系数随着水土比的增加而减小。压汞试验（MTP）结果表明,随MPC添加量的增大,固化土孔隙体积减小,水土比不超过临界值时,固化土孔隙体积随着水土比的增大而减小。扫描电镜试验结果表明,随着MPC添加量的增加,土颗粒团聚化越明显,胶结程度加强;水土比不超过临界值时,土颗粒团聚体增多。镁钾磷酸盐晶体（MKP）主要通过减少孔径大于1 ?m的孔隙体积来影响固化土的强度和渗透特性。