 
          1214
        
        
          Proceedings of the 18
        
        
          th
        
        
          International Conference on Soil Mechanics and Geotechnical Engineering, Paris 2013
        
        
          aggregates (Fonseca et al. 2013) applied to transport
        
        
          infrastructure are also presented and discussed.
        
        
          Adam et al. (2013) introduced a finite element modeling
        
        
          framework for analyzing the performance and efficiency of an
        
        
          impact compactor in relation to the surface velocity, weight of
        
        
          impact compactor and number of passes. Field observations
        
        
          indicate that the impact compactor is suitable for treating a wide
        
        
          variety of loose soils and fills, but the effective treatment depth
        
        
          is dictated by the grain size, typically ranging from 4.5m to 10m
        
        
          depth. Experience of two case studies suggests that Dynamic
        
        
          Probing Tests (Figure 1) are adequate for evaluating the
        
        
          efficiency of compaction.
        
        
          
            depth [m]
          
        
        
          4.5 m
        
        
          12.0 m
        
        
          4.0 m
        
        
          gravel
        
        
          core
        
        
          (loess / loam)
        
        
          
            compacted zone
          
        
        
          
            N
          
        
        
          
            10
          
        
        
          
            BEFORE RIC
          
        
        
          
            AFTER
          
        
        
          
            RIC
          
        
        
          Figure 1. Test dike and correspondent dynamic probing test results.
        
        
          (Source: Fig 8, Adam et al. 2013).
        
        
          Kuo et al. (2013) have described the effectiveness of Rolling
        
        
          Dynamic Compaction (RDC) by the combination of field
        
        
          studies with numerical modeling (Figure 2). At the ground
        
        
          surface, there are noticeable large deformations, and RDC
        
        
          proves to be most effective between the depths of 0.8m and
        
        
          3.0m. The preliminary parametric study showed that most
        
        
          significant factors were soil cohesion, Poisson’s ratio and shear
        
        
          modulus, as well as the width and mass of the RDC module.
        
        
          An interesting study on the feasibility of a stiffness-based
        
        
          specification for embankment soil compaction quality control is
        
        
          discussed by Conde et al. (2013). An array of instruments are
        
        
          adopted for compaction control, which measures soil stiffness
        
        
          and then discussed on the basis of an earth dam construction.
        
        
          Among the different equipment used, the DCP (dynamic cone
        
        
          penetrometer) equipment showed greater promise as a
        
        
          compaction control tool, partly attributed to the strong negative
        
        
          correlation with water content values.
        
        
          Figure 2. FEM model (Source: Fig 3, Kuo et al. 2013).
        
        
          Kirstein et al. (2013) have described the application of a
        
        
          combination of ground improvement techniques to stabilize a
        
        
          recently placed brown coal landfill embankment for supporting
        
        
          a new road. Owing to significant stability problems and the
        
        
          small settlement tolerance of the structure (15 m deep),
        
        
          “floating” stone columns were also installed. The design and the
        
        
          associated settlements were significantly influenced by the
        
        
          combination of different soil improvement techniques. The
        
        
          settlement predictions were obtained using a finite element
        
        
          model (Figure 3) and successfully verified against the results of
        
        
          pressuremeter tests.
        
        
          Figure 3. Representation of the predicted total settlements obtained with
        
        
          Plaxis (Source Fig 10, Kirstein et al. 2013).
        
        
          Fonseca et al. (2013) presented some intriguing results
        
        
          obtained through laboratory studies performed on compacted
        
        
          mixtures of cement and limestone aggregates. The results
        
        
          indicated that the differences observed in dynamic and static
        
        
          stiffness properties and shear strength parameters were directly
        
        
          associated with the variation of porosity/cement ratio. As
        
        
          expected, a higher stiffness and strength were obtained by
        
        
          increasing the cement content and the degree of compaction.
        
        
          While a hardening soil model could be employed to adequately
        
        
          describe the observed stress-strain behaviour, the volumetric
        
        
          predictions and the post-peak strain softening response could
        
        
          not be reproduced satisfactorily.
        
        
          3 LABORATORY TESTING
        
        
          This section includes 6 articles. Two papers demonstrate the
        
        
          results of California Bearing Ratio (CBR) tests performed on
        
        
          the subbase (Ishikawa et al. 2013) and the subgrade (Moayed et
        
        
          al. 2013). Some studies focus on cyclic loading tests on ballast
        
        
          (Kumara and Hayano 2013) and subgrade (Mohanty and
        
        
          Chandra 2013), while the others investigate the overall
        
        
          performance of railway track (Calon et al. 2013, Hayano et al.
        
        
          2013).
        
        
          Ishikawa et al. (2013) examined the effects of freeze-thaw
        
        
          and water content on the deformation-strength properties of
        
        
          granular base materials. Two types of tests are conducted on
        
        
          these materials under various water contents. One test is based
        
        
          on the newly developed CBR equipment (Figure 4), and the
        
        
          other using medium-size triaxial apparatus. The freeze-thaw of
        
        
          granular base showed a strong influence on the fatigue life of
        
        
          pavement structures. When number of freeze-thaw process
        
        
          cycles increased, CBR values decreased regardless of the water
        
        
          content. Resilient modulus showed a decreasing tendency with
        
        
          the increasing water content.
        
        
          
        
        
          150
        
        
          Surcha
        
        
          rge
        
        
          Water supply
        
        
          / drainage
        
        
          Coolant
        
        
          circulating line
        
        
          Insulation
        
        
          Acrylic cell
        
        
          Base cooling plate
        
        
          Temperature
        
        
          sensor (pt100)
        
        
          Porous metal
        
        
          with filter paper
        
        
          O-ring
        
        
          Water supply
        
        
          / drainage
        
        
          Porous metal
        
        
          with filter paper
        
        
          Top cooling plate
        
        
          Coolant
        
        
          circulating line
        
        
          Coolant
        
        
          circulating line
        
        
          Coolant
        
        
          circulating line
        
        
          Figure 4. Freeze-thawing CBR test apparatus. (Source: Fig 1, Ishikawa
        
        
          et al. 2013).