Incorporating the Stress History Parameter of DMT into the Liquefaction Correlations in Clean Uncemented Sands
Publication: Journal of Geotechnical and Geoenvironmental Engineering
Volume 142, Issue 2
Abstract
This paper analyzes the possibility of reducing the uncertainty of the cyclic resistance ratio (CRR) estimates by incorporating stress history into the liquefaction correlations. A way of obtaining this objective stems from the combination of two well-recognized notions: (1) sensitivity of the flat dilatometer test (DMT) parameter to stress history, and (2) necessity of stress history information to obtain better estimates of the liquefaction resistance. The main aim of this paper is to develop a framework providing CRR estimates based not on the one-to-one correlations or , but on a correlation based at the same time on both and . A correlation has been constructed by combining the current and correlations. It is expectable that an estimate based at the same time on two measured parameters is more accurate than estimates based on just one parameter. 'A chart is presented providing estimates of CRR based at the same time on both and .
Introduction
It is widely recognized that the cyclic resistance ratio (CRR) estimates by cone penetration test (CPT) are not always of a satisfactory reliability. For example, Robertson and Wride (1998) wrote “CRR by CPT may be adequate for low-risk projects. For high-risk projects estimate CRR by more than one method,” and Idriss and Boulanger (2006) wrote “The allure of relying on a single approach (e.g., CPT-only) should be avoided.” This uncertainty has stimulated a large number of studies, which however do not consider the addition of fresh collateral independent easily measured information on stress history.
This paper analyzes the possibility of reducing said uncertainty using the flat dilatometer (DMT) horizontal stress index (often alternatively called stress history index).This possibility stems from the combination of two notions that are well recognized today: (1) sensitivity of to stress history, and (2) necessity of stress history information to obtain better estimates of the liquefaction resistance.
1.
The higher sensitivity to stress history of , compared with the sensitivity of (normalized cone tip resistance), has been observed by numerous researchers, either in the calibration chamber (e.g., Jamiolkowski and Lo Presti 1998) or in the field (e.g., Schmertmann et al. 1986; Jendeby 1992; Marchetti 2010). An expressive example, clearly illustrating the different sensitivity, is shown in Fig. 1 (Lee et al. 2011). CPT and DMT were executed in the calibration chamber on 40 large specimens of Busan silica sand, partly normally consolidated (NC) and partly previously preconsolidated to overconsolidation ratio (OCR) in the range 1–8. Then the and obtained before and after the preconsolidation were compared. The two diagrams in Fig. 1 confirm that is considerably more reactive to OCR than . A consequence of Fig. 1 is that the same can correspond to various values of , as shown in the schematic example in Fig. 2. In the example Site 2 has the same profile as Site 1, but has a higher , suggesting higher stress history, and hence higher CRR. This benefit would not be detected by just the two identical profiles of . Another interesting consequence of Fig. 1 is the necessity of both and to evaluate OCR in sand. If only is known and is entered in Fig. 1(b), its value could be due to a low relative density and a high OCR or to a high and a low OCR. In order to evaluate OCR, must also be available to provide an indication of on the horizontal axis.
2.
The necessity of stress history information for assessing liquefaction resistance CRR has long since been recognized (e.g., Youd and Idriss 2001; Salgado et al. 1997; Monaco and Schmertmann 2007; Harada et al. 2008). Even before, Jamiolkowski et al. (1985), based on extensive calibration chamber studies, had warned “Reliable predictions of liquefaction resistance of sand deposits having complex stress-strain history require the development of some new in situ device [other than CPT or SPT] much more sensitive to the effects of past stress-strain histories, because stress history produces a small increase in penetration resistance, but a significant increase in CRR and in stiffness of a cohesionless soil.”
Construction of a Correlation
The main aim of this paper is to develop a framework providing CRR estimates based not on the one-to-one correlations of or , but on a correlation based at the same time on both and . This correlation, as shown in this section, has been constructed by combining the current and correlations.
Correlation
Today’s standard practice for evaluating the liquefaction resistance CRR is to use the well-known correlations described in numerous papers (e.g., Youd and Idriss 2001; Robertson and Wride 1998; Idriss and Boulanger 2006). The correlations, despite various uncertainties, are the result of a large number of documented real earthquake data. The correlation adopted in this paper, Eq. (1a) ahead in the paper, is the Idriss and Boulanger (2006) correlation (somewhat more conservative than the previous Robertson and Wride correlation).
Correlation
CRR estimates are also made using correlations. This section provides some background on these correlations. The first correlations go back to Marchetti (1982) and Robertson and Campanella (1986). Since then, numerous updated curves have been produced (e.g., Reyna and Chameau 1991; Monaco et al. 2005; Tsai et al. 2009; Robertson 2012). These research efforts have been stimulated by the fact that the factors increasing of a sand also increase its liquefaction resistance. For example, Robertson and Campanella (1986) listed the following factors: (1) relative density, (2) in situ , (3) stress history and prestressing, (4) aging, and (5) cementation. Robertson and Campanella (1986) also pointed out that it is not possible to identify the individual contribution of each factor to . On the other hand, when is low, none of these factors is high, that is the sand is loose, uncemented, in a low horizontal stress environment, and has little stress history. A sand under these conditions may be prone to liquefaction. In this paper, the term stress history is meant to globally include any factor making the sand more stable than a freshly deposited sand.
•
Sensitivity of to OCR: Schmertmann et al. (1986) observed that, upon compaction (which increases OCR), the percentage increase of (the constrained modulus by DMT) was twice the percentage increase of (the increase of is primarily due to the increase of ). More recently numerous compaction jobs include before-after CPTs and DMTs. The presentation of the comparisons often includes the before-after versus profiles [Figs. 3(a and b)]. The fact that increases with compaction indicates that (and hence ) increases with OCR at a faster rate than , confirming the Schmertmann et al. (1986) observation, and is in agreement with Fig. 1. The profiles also permit an evaluation of the achieved OCR increase, using, e.g., the Monaco et al. (2014) equation OCR - in Fig. 3(c).
•
Sensitivity of to pure prestressing: has been found to be substantially more sensitive than penetration resistance to pure prestressing, consisting in cycles of loading-unloading along the line, followed by unloading to the initial vertical and horizontal stress, without locked-in horizontal stresses (Jamiolkowski and Lo Presti 1998; Marchetti 1982).
Combining the Correlation and the Correlation
Relation
Eq. (1b), suggested by Robertson (2012), used in the previous sections, is highly approximate. It was obtained by Robertson by interpolating a straight line through the Tsai et al. (2009) data points [Fig. 5(a)]. Figs. 5(b–d) have been added in Fig. 5 as additional examples of the correlation in clean sand. All data are for a DMT material index , i.e., for clean sand. The three added figures essentially confirm both the average value 25, and the considerable dispersion. The high observed dispersion in the relation is, to a large extent, the consequence of the higher reactivity of to stress history (Fig. 1). If the scatter were small, it would mean that and contain equivalent information, which is negated by Fig. 1. The high scatter indicates that contributes fresh collateral independent information to the characterization of the sand.
Comments on the Chart in Fig. 4
•
A plot similar to Fig. 4 was proposed by Harada et al. (2008), who suggested using as a parameter in the curves. It is observed that in sand can be estimated, e.g., by the correlations developed by Baldi et al. (1986) expressing as a function of and , but these estimates are often uncertain and subjective, while is accurately, easily, and unequivocally determined. Moreover, is a cumulative parameter reflecting, besides , other stress history factors increasing CRR.
•
The essence of Fig. 4 is to estimate CRR from by the everyday CPT correlations. Then if is higher than average (), increase CRR; if is lower than average, reduce CRR. Described in this way Fig. 4 appears to be common sense, supporting the expectation that the real earthquake data points will plot not far from the curves.
•
The = constant lines have a limited length because, for any given , only a limited range of exists, as can be seen in Fig. 5.
•
•
Fig. 4 requires considerable real earthquake verification. It is to be regarded as an initial framework for initiating the accumulation of colocated data points.
Concluding Remarks
•
Numerous studies have shown that is an effective indicator of stress history and that information on stress history is necessary to obtain reasonable estimates of CRR. This paper analyzes the possibility of reducing the uncertainty in estimating CRR by incorporating the DMT stress history index into the liquefaction correlations.
•
By combining the commonly used and correlations to estimate CRR, a plot has been constructed (Fig. 4) providing estimates of CRR based at the same time on both and . It is expectable that an estimate based at the same time on two measured parameters is more accurate than estimates based on just one parameter.
•
The essence of Fig. 4 is estimating CRR from by the everyday CPT correlations. Then, if is higher than average (), increase CRR; if is lower than average, reduce CRR. Described in this way Fig. 4 appears to be common sense, supporting the expectation that the real earthquake data points will plot not far from the curves.
•
Fig. 4 was constructed with clean uncemented sand in mind. If the sand contains fines or is cemented, estimating CRR is much more complex. For example, the cementation can be ductile (toothpastelike) or fragile (glasslike), a quality that affects either or and the sand liquefaction behavior. Fine content may possibly have effects similar to a ductile cementation. Clearly the unknowns are too many and it may be not sufficient to add the information to . The knowledge of (small-strain shear modulus) could possibly help, because high and/or high (Schnaid et al. 2004; Cruz et al. 2012) are also indicators of cementation. Even the dilatometer modulus from DMT could possibly help. Considerable additional study is clearly necessary if the sand is not a clean uncemented sand.
References
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History
Received: Nov 6, 2014
Accepted: Jun 4, 2015
Published online: Aug 12, 2015
Discussion open until: Jan 12, 2016
Published in print: Feb 1, 2016
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