Success Stories

I) A study on the saturation degree dependency of the seismic behavior of retaining walls

In this study, a finite difference code was employed to perform a series of equivalent linear analyses in order to investigate the effect of the degree of saturation on the response of the retaining structures. For this purpose, the required equations for the soil water retention function and the change of the soil shear modulus with the mean effective stress for both saturated and unsaturated zones were employed so as to the required hydro-mechanical coupling in unsaturated and saturated zone is directly introduced in the code. The results, indicate that in the unsaturated state, the increase in the effective stress, and hence, the shear modulus considerably affects the seismic forces on the retaining wall [1]. Shear modulus versus height in dry and unsaturated backfill conditions is presented in Figure 1. Soil water retention properties of soil no. 10700 and soil no. 18719 from SVSOILS™ were assigned to the backfill soil and the soil under foundation, respectively. Figure 2 depicts. Variation of resultant force applied on the wall during earthquake in dry and unsaturated backfill conditions.

Figure 1. Shear modulus versus height in dry and unsaturated backfill conditions (a. Wall=5m, b.Wall=6m)

Figure 2. Variation of resultant force applied on the wall during earthquake in dry and unsaturated backfill conditions. (a. Wall=5m, b. Wall=6m)

II) Application of AI-based methods in unsaturated soil mechanics

The progress in artificial intelligence methods has led to the development of new models for soil constitutive behavior. The unsaturated soil mechanics laboratory of Shiraz University has used such models in unsaturated soil mechanics for capturing the unsaturated soil hydraulic and mechanical properties. As an example Genetic Programming (GP) has been utilized for predicting Soil–Water Characteristic Curve (SWCC). In order to employ artificial intelligence methods, one has to have many data-points for the AI-based method to recognize and extract the required features. SVSOILS™ is one of the most complete databases of unsaturated hydraulic properties containing many soil types and several data-points thus providing a valuable database crucial for such research. Figure 3 compares performance of GP with the experimental data of a test case as well as those of a state-of-the-art model (Fredlund et al. 1997).

Figure 3. Average simulation results among tests used for validation (void ratio: 0.852; initial water content: 31.57%; clay content: 70.33%; silt content: 23.7%; dry density: 1457.7 kg/m3 ; specific gravity, Gs:2.7)

III) Application of pore network modeling (PNM) in unsaturated soil mechanics

The pore network modelling (PNM) is a powerful simulation technique which has been first introduced in petroleum engineering for modeling two phase flow, addressing problems in enhanced oil recovery. Since then, it has been used in many other disciplines from modeling porous structure of apple fruit (Ho et al. 2014) to gas diffusion layer of fuel cells (Hinebaugh and Bazylak 2010). A pore network model is used to portray the porous structure of a porous medium in form of a network consisting of pores and throats. In a natural or industrial porous medium, pores depict main void bodies of the soil, and throats specify the narrow void space connecting two adjacent pores (Figure 4). In unsaturated soil mechanics, pore networks can thus be used in order to model the hydraulic properties of unsaturated soils and any process happening inside the porous structure (e.g., transport of contaminates and colloids) (e.g., see Khaksar et al. 2013 and Rostami et al. 2013). Figure 5 presents the results of a pore network modeling of SWCC performed at unsaturated soil mechanics laboratory of Shiraz University (as compared with the classic SWCC equations and experimental data points).

Figure 4. A typical pore network model

Figure 5. The results of a pore network model as compared with experimental data and other available relationships (experimental data: soilvision soil No. 10974)

In conclusion, SVSOILS™ has provided us with a valuable database required for model development and research in various areas of unsaturated soils mechanics as expressed in this short success story. Our sincere gratitude is expressed to SOILVISION team for their continuous support. A list of the relevant references is provided, hereafter, for further details.

Some of the representative references

Fredlund, M. D., Fredlund, D. G., and Wilson, G. W. (1997). “Prediction of the soil-water characteristic curve from grain size distribution and volume-mass properties.” Proc., 3rd Brazilian Symp. on Unsaturated Soils, Rio de Janeiro, Brazil, 13–23.

Hinebaugh, J., & Bazylak, A. (2010). Condensation in PEM fuel cell gas diffusion layers: a pore network modeling approach. Journal of the Electrochemical Society, 157(10), B1382-B1390.

Ho, Q. T., Verboven, P., Fanta, S. W., Abera, M. K., Retta, M. A., Herremans, E., ... & Nicolaï, B. M. (2014). A multiphase pore scale network model of gas exchange in apple fruit. Food and bioprocess technology,7(2), 482-495.

Johari, A., Habibagahi, G., & Ghahramani, A. (2006). Prediction of soil–water characteristic curve using genetic programming. Journal of Geotechnical and Geoenvironmental Engineering, ASCE, 132(5), 661-665.

Khaksar, H., Habibagahi, G., & Nikooee, E. (2013). SWRC modeling in unsaturated soils: A pore network approach. In Poromechanics V: Proceedings of the Fifth Biot Conference on Poromechanics (pp. 1570-1579).

Momeni, M. J., Habibagahi, G., & Nikooee, E. (2016). A study on the saturation degree dependency of the seismic behaviour of retaining walls. In E3S Web of Conferences (Proceedings of Unsat 2016) (Vol. 9, p.05001). EDP Sciences.

Rostami, A., Habibagahi, G., Ajdari, M., & Nikooee, E. (2013). Pore network investigation on hysteresis phenomena and influence of stress state on the SWRC. International Journal of Geomechanics, ASCE, 15(5), 04014072.


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