Soil deformation under slow periodic load is of particular importance to predict the functionality of soil structure in a variety of engineering practices. However, lacking quantification on plastic deformation hinders the deformation analysis of soil subjected to slow periodic load. The axial component of plastic modulus is pivotal and is determined to calculate axial plastic strain and overall soil deformation. In this study, a static triaxial compression system was designed to perform a series of static cyclic triaxial tests and cyclic confined compression tests on a silica sand. The results showed that plastic strain increments decreased gradually, as the loading cycle proceeded, and finally only the elastic strain increment existed. The empirical equation of axial component of plastic modulus was formulated considering the effects of stress states, void ratios, and loading cycles. In combination with the description of elastic modulus, the axial strain increment in each loading cycle was formulated. In addition, in the unloading process of loading cycle, the volume contraction phenomenon was explained by unloading plastic strain and microscopic particle motion based on the present results.
The expansive soil and sand dunes are abundant in desert areas at which new cities have been constructed. One of the effectively mitigation techniques for the expansive soil is to mix it with a non-swelling soil. This paper aims to study the influence of different sand dunes fractions, varying from zero to 50%, on the behaviour of the highly expansive clay. The clay-sand mixtures were also chemically stabilized by 10% of lime. The samples were remoulded according to the modified AASHTO compaction tests results. Swelling and strength tests were performed on each mixture. The results showed that mixing sand dunes with expansive clay reduced its swell potential and swelling pressure. The reductions increased as the increment of sand fraction. The swell potential and swelling pressure of the clay reduced to approximately the one-third when utilizing 50% sand. But mixing lime and sand with clay caused further significant reductions in swell properties. The swell potential and the swelling pressure of the clay were approximately suppressed when it was stabilized by 50% sand and 10% lime. Adding sands to clays had a negative effect on the strength. The CBR and UCS values of the clay-sand mixture decreased with increasing sand fractions. Once adding lime to the clay-sand mixtures, the CBR and UCS after 8-weeks curing time increased. The increments raised with increasing of sand fraction. The existence and the increment of sand dunes in clay influenced effectively on the chemical reactions with lime.
The stresses generated from rock expansion in a confined underground environment will exert additional loads to the existing support system resulting in severe damage during tunnel construction. In this study numerical investigations were carried out for Zagros tunnel in Iran, where swelling has been reported to be an inherent formation property. The presence of expandable clay was investigated using X-ray diffraction mineralogical analyses. The swelling volume strain was used to estimate the amount of stress increased due to swelling. The stress path method is used to obtain the location of swelling stresses. The stress relief zone (SRZ) was considered as the criterion to define the area around the tunnel where swelling stresses exist. In doing so, in the areas where the first stress invariant after excavation becomes lesser than its corresponding value before excavation, the swelling pressure can be built up. Then tunnel stability was investigated by numerical simulations using FLAC2D. The swelling stresses calculated from the free swelling test were applied to those elements around the tunnel within the stress relief zone. A comparison between the results of numerical investigations with field observation indicates that the proposed approach is successful in simulating swelling stress in swelling rocks.
Data-driven site characterization (DDSC) is defined as any site characterization methodology that relies solely on measured data, both site-specific data collected for the current project and existing data of any type collected from past stages of the same project or past projects at the same site, neighboring sites, or beyond. One key complication is that real data is “ugly”. A useful mnemonic is MUSIC-3X (Multivariate, Uncertain and Unique, Sparse, Incomplete, and potentially Corrupted with “3X” denoting three dimensional spatial variations). It is an open question whether DDSC can solve real world subsurface mapping problems based on real world MUSIC-3X data from routine projects with minimum ad-hoc assumptions. The computational challenges are very significant, but some reasonable partial solutions have been obtained recently. One promising solution is Sparse Bayesian Learning (SBL). It is nearly data-driven and it can handle a large scale 3D problem without incurring excessive cost. However, it can only handle one type of field test data. Nonetheless, it is already useful for practice. A 3D SBL version would be made available in Rocscience’s Settle3 (three-dimensional soil settlement analysis) in the near future to generate subsurface maps based on cone penetration test data. The second solution is based on a variant of the Gaussian Process Regression (GPR-MUSIC-3X). It can handle multiple field test data by learning the cross-correlation behavior among different soil parameters at a single site of interest. GPRMUSIC-3X can be enhanced to learn cross-correlation behaviors at multiple sites and thus bring information from “similar” sites in a larger generic database to bear on improving predictions at a single site. Both 3D SBL and GPR-MUSIC-3X are cross validated using a 2D virtual ground and an actual 3D site in Texas. The hunt is on for a “holy grail” mapping approach that is fully datadriven, MUSIC-3X compliant, and is able to exploit all available data including data from similar sites. This is Project DeepGeo (inspired by DeepMind that produces AlphaGo), which constitutes one major research effort in the emerging field of data-centric geotechnics.
