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Method to Reduce Variability of S-Wave Profiles in Seismic Cone Penetration Tests Missouri University of Science and Technology Scholars' Mine International Conferences on Recent Advances 2010 - Fifth International Conference on Recent in Geotechnical Earthquake Engineering and Advances in Geotechnical Earthquake Soil Dynamics Engineering and Soil Dynamics 26 May 2010, 4:45 pm - 6:45 pm Method to Reduce Variability of S-Wave Profiles in Seismic Cone Penetration Tests Lou Areias Belgian Nuclear Research Centre/ Vrije Universiteit Brussel, Belgium Follow this and additional works at: https://scholarsmine.mst.edu/icrageesd Part of the Geotechnical Engineering Commons Recommended Citation Areias, Lou, "Method to Reduce Variability of S-Wave Profiles in Seismic Cone enetrP ation Tests" (2010). International Conferences on Recent Advances in Geotechnical Earthquake Engineering and Soil Dynamics. 17. https://scholarsmine.mst.edu/icrageesd/05icrageesd/session01b/17 This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License. This Article - Conference proceedings is brought to you for free and open access by Scholars' Mine. It has been accepted for inclusion in International Conferences on Recent Advances in Geotechnical Earthquake Engineering and Soil Dynamics by an authorized administrator of Scholars' Mine. This work is protected by U. S. Copyright Law. Unauthorized use including reproduction for redistribution requires the permission of the copyright holder. For more information, please contact [email protected]. METHOD TO REDUCE VARIABILITY OF S-WAVE PROFILES IN SEISMIC CONE PENETRATION TESTS Lou Areias ESV Euridice/SCK•CEN Belgian Nuclear Research Centre and Vrije Universiteit Brussel 2400 Mol, Belgium, [email protected] ABSTRACT The pseudo method used to calculate shear wave velocity (Vs) in seismic cone penetration (SCP) tests often generates high variability of Vs values at shallow depths. This occurs when travel paths are small and signal variability large to allow accurate arrival time differentiation between successive signals. The offset distance between the source and receivers has the largest influence on signal variability. A method described in this paper shows good results in reducing Vs variability of SCP tests during post processing. The method consists of increasing the sampling interval to calculate Vs and then regrouping the data to provide its original test-depth profile. The method is illustrated with a case study. INTRODUCTION There are three main methods to calculate and display SCPT As a result, lower signals, which normally have longer travel test data: the pseudo-interval; the true-interval; and the times than upper signals, can appear to have shorter travel assumed travel path (ATP) methods. In each of the methods, times. In other cases, wave-velocity profiles will display the main objective is to generate seismic velocity and moduli seemingly abnormal velocity variations when the differences profiles in soil. The steps taken to accomplish this include: in successive travel paths are small, and signal variability identifying arrival times; calculating travel-path length, large, to allow proper differentiation between signals. velocity and moduli; and plotting the data using an appropriate method. Often this arises when both the test interval and offset distance are made small. Choosing small test intervals may be The pseudo-method generates high variability in shear Vs and important to increase measurement resolution. On the other compression Vp velocity profiles at shallow depths when hand, offset distance usually depends on the type of equipment relatively small differences in ATP values exist in this zone. used and is usually fixed. The discussion in this paper focuses Small ATP differences result when selected test-depth primarily on these two parameters. The objective is to intervals and/or offset distances are incompatible with both demonstrate how to reduce apparent signal variability by wave-velocity and accuracy of the data acquisition (DAQ) changing the test-depth interval during post-processing. system. In theses cases, signal variability (Areias & Van Impe, 2005) may be high enough to influence the outcome of arrival-time measurements. PSEUDO-INTERVAL METHOD This happens, for example, when the statistical range The pseudo-interval method (Patel, 1981 and Rice, 1984) (difference between statistical maximum and minimum) of converts ATPs into their vertical-equivalent ray-path travel measured arrival times, which depends on setup and DAQ distances values. ATPs are straight paths between the source system characteristics, approaches the difference in travel-time and receivers. This is not always correct (Areias & Van Impe, between signals from succeeding depths. 2006), although it holds approximately in most cases (Areias, 2007). Paper No. 1.20b 1 The pseudo-interval method needs only two geophones, one oriented horizontally to measure shear (S) waves and another in the vertical direction to detect compression (P) waves. Jacobs & Butcher (1996) refer to this setup as incremental SCPT testing. A schematic illustrating the pseudo-interval method appears in Fig. 1. The assumed (straight) ray-travel path of ray n (ATPn) in Fig. 1 is the Pythagorean length of the hypotenuse formed by the right triangle with offset distance (X) and vertical length Zn, expressed as: 2 2 ATPn Zn X (1) where: X = horizontal offset distance between source and SCPT cone rods; and Z Zn = vertical distance between surface and receiver of ray n. T The corrected total travel time (Tcorr) for a given ray n becomes: Z n (2) Tcorr Tmeas ATPn where: Fig. 1. Ray-path geometry for pseudo-interval method Tmeas = total travel time measured from SCPT test. The values of ∆Z and ∆T are then: z Zn1 Z n is the test-interval depth (3) INFLUENCE OF OFFSET DISTANCE AND TEST INTERVAL T T T (4) corr, n1 corr, n with Zn+1, Tcorr, n and Tcorr, n+1 as defined in Figure 1. The offset distance (Fig. 1) has the largest effect on signal variability when combining large offset distances with small Substituting gives the pseudo-interval velocity Vs, p of S or P ∆Z test intervals, as illustrated by the solid-line curves in waves: Fig. 2. The figure plots changes in ATP distance between two z Z Z V n1 n (5) successive test depths for two cases of offset distances of s, p 1.0 m and 4.0 m and two test-depth intervals of 0.5 and 1.0 m. T Tcorr,n 1 Tcorr,n Layering also influences ray-path distance but its influence is The terms Tcorr,n and Tcorr,n+1 in Equation 5 are the total travel generally small and ignored in the calculations. It depends times for signals n and n+1, respectively. Therefore, velocities mainly on velocity contrast between soil interfaces calculated by Equation 5 are average velocities for test interval (Areias, 2007). ∆Z. The corrected test depth (Zcorr,n) corresponding to these velocities is then: It is evident from Fig. 2 that a setup represented by the solid- Z -line curves is preferable to the one described by the dashed Z Z (6) corr,n n 2 lines. It shows that the solid-line curves, which represent a This is the test depth reported when plotting the SCPT test source with an offset of 1.0 m and two different test intervals data. of 0.5 and 1.0 m, reach a maximum difference in ATP length at a depth of 5.0 m, approximately. These differences in ATP Alternatively, one can express Equation 5 in terms of total length correspond to the respective ∆Z values of 0.5 m and ATPs and travel times to give: 1.0 m. ATP ATP n1 n The solid lines give the greatest travel-time difference Vs, p (7) Tmeas,n1 Tmeas,n between signals when compared with the setups represented by the dashed lines. In the first case, the maximum change in ATP reaches its maximum value at a depth of approximately This method provides V(s,p) values directly without first having to convert arrival times to their vertical equivalent, as is the 2.5 m, as shown. case for the first method. Paper No. 1.20b 2 Change in ATP [m] Table 1. Proposed method to change ∆Z values during n post-processing 0.00 0.20 0.40 0.60 0.80 1.00 0.0 Field Regrouped signals (original) 1.0-m intervals signals 5.0 Non- sampled at Integral integral 0.5-m depths depths intervals [m] 10.0 [m] [m] 0.0 0.0 - 15.0 0.5 - 0.5 1.0 1.0 - Depth [m] Depth 1.5 - 1.5 20.0 2.0 2.0 - 2.5 - 2.5 3.0 3.0 - 25.0 1.0m offset & 0.5m interval 3.5 - 3.5 4.0m offset & 0.5m interval 1.0m offset & 1.0m interval . 4.0m offset & 1.0m interval . 30.0 . Fig. 2. Changes in ATPn with depth for 1.0 and 4.0 m offsets . i.0 . at 0.5 and 1.0 m test-depth intervals i.5 i.5 By contrast, the setups shown by the dashed lines, which are Each of the re-sampled subgroups, therefore, gives velocity for a 4.0-m offset, require a depth of at least 15 m to reach profiles equivalent to those obtained using 1.0-m-depth ATP differences close to their respective test-interval values intervals in the field. Similarly, combining the results from of 0.5 m and 1.0 m. It is evident that these setups will both subgroups gives velocity profiles for the original depth potentially result in greater signal variability than the first two interval of 0.5 m. An illustration of this method appears in cases because they represent shorter differences in ATP Fig. 3, which shows velocity profiles for two SCPT tests. length. V [m/s] Vs [m/s] s Test-depth interval ∆Z thus plays an important role in 0.00 100.00 200.00 300.00 400.00 0.00 100.00 200.00 300.00 400.0 0.0 0.0 determining differences in ATP length between SCPT tests.
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