Synthesis and Evaluation of The Service Limit State of Engineered Fills for Bridge Support

CHAPTER 6.
CONCLUSIONS

6.1 Conclusions

In the evaluation of five widely used methods of estimating immediate settlement of shallow foundations on granular soils, it was observed that four of the five methods (modified Schmertmann, Hough, Peck and Bazaraa, and Burland and Burbidge) overestimate immediate settlement, and the D’Appolonia method slightly underestimates immediate settlement. In comparison, the D’Appolonia method is the most accurate method with the mean λ the closest to unity and relatively small COV, followed by the Peck and Barazaa method and the Burland and Burbidge method. Both the modified Schmertmann method and the Hough method overestimate immediate settlement of shallow foundations on granular soils by a factor of approximately 2. It is noted that this conclusion is based on measured data whose population may be statistically small.

In the evaluation of six prediction methods for lateral displacements of GRS abutments and walls, it was concluded that the Adams method is the most accurate method for predicting the maximum lateral displacement of GRS walls and abutments with the mean λ the closest to unity and small COV. The Jewell-Milligan method is a conservative and relatively accurate method for predicting the lateral displacement of GRS walls and abutments with negligible facing rigidity. For predicting the displacement of GRS walls and abutments with CMU facing block, the CTI method may also be used, although it may overestimate lateral deformations by a factor of 1.69 with a relatively high COV. It is noted that this conclusion is based on measured data whose population may be statistically small.

Currently, there is only one method available in estimating elastic vertical deformation of GRS abutments and walls; it is an empirical equation proposed by Adams et al.⁽³²⁾ This method uses the composite Young’s modulus of the GRS composite. Although the field observation data that are used to evaluate this empirical method show that this method is highly unconservative, it should be noted that the accuracy of the prediction method depends on the accurate determination of the composite Young’s modulus, which lacks in the literature. It should also be noted that this conclusion is based on measured data whose population may be statistically small.

6.2 Knowledge Gaps and Data Needs For Bridge Supports using Engineered Fills

Based on the synthesis of the literature and current guidelines and methods on bridge supports using engineered fills, the following knowledge gaps and data needs for bridge supports using engineered fills were identified:

• The current analyses primarily predict immediate settlement only. While it is a common assumption that granular or engineered fills do not exhibit secondary deformation, it has been observed in in-service bridge abutment applications and large-scale piers in laboratory tests.^(27,32) Among the limited number of methods for predicting long-term (or time-dependent secondary post-construction) deformation of granular soils, long-term field observations or long-term PTs are needed to derive coefficients that are used in the prediction methods. Furthermore, long-term deformation data of bridge supports on engineered fills are rather limited, so that the evaluation of currently available long-term deformation prediction methods cannot be performed.
  
  
• There is a particular lack of prediction methods for vertical (for both immediate and long-term) deformations of MSE and GRS bridge abutments and piers.
  
  
• There is lack of comprehensive knowledge of the effects of soil characteristics and compaction efforts on the SLS performances of bridge supports using engineered fills. Accordingly, current design guides provide specific requirements on engineered fills for bridge support, and design is limited to the conditions and parameters under which testing has occurred. In addition, the parameters used (e.g., Φ, c, etc.) may vary depending on the measurement technique and the design method selected, which may have an impact on the SLS analysis. Other different types of fill materials are not being used due to a lack of data on their impact.
  
  
• Stress distribution in soils can be influenced by various soil conditions (i.e., grain size distribution, strength parameters, relative density, and fine content), reinforcement characteristics (i.e., T_f, stiffness, N, and S_v), and loading conditions. Some of these parameters were investigated previously.⁽⁹⁰⁾ However, the current literature suggests there is a lack of documentation and understanding of the effects of various parameters on the stress distribution in reinforced engineered fills as bridge supports in SLS.
  
  
• The dynamic effect of transient load on bridge supports using engineered fills has not been investigated. There is a lack of literature on the time-dependent and live (transient) load on the stress-deformation behaviors of bridge supports using engineered fills.