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This paper describes the use of the Material Point Method (MPM) to simulate cone penetrometer testing (CPT) in complex soil profiles. CPT-based liquefaction evaluation procedures have been shown to be inaccurate in highly interlayered soil stratigraphies. One contributing factor to this inaccuracy is that CPT measurements at discrete depths reflect the properties of all soils that fall within a zone of influence around the cone tip, not just the properties of the soil at a particular depth. Consequently, the CPT loses resolution in soil profiles with many thin, interbedded soil layers (multiple thin-layer effects) and provides inaccurate input data to liquefaction analyses. While several procedures have been proposed to correct for multiple thin-layer effects, they tend to decrease in efficacy as the thickness of soil layers decreases. Results from the MPM analyses detailed in this paper highlight limitations of (1) the CPT in characterizing complex soil stratigraphies and (2) procedures proposed to correct for multiple thin-layer effects in CPT data.
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A new shared miniature cone penetrometer for centrifuge testing
Cone penetrometers (CPTs) are commonly used for characterising the soil properties of centrifuge models; CPT data is useful for interpretation and quality control. This paper describes the development and design of a new robust CPT device for centrifuge testing. The new device consists of a 6mm cone, an outer sleeve, and an inner rod that transmits cone tip forces to a load cell above the ground surface. The design eliminates the need for a custom submerged strain gauge bridge near the tip, significantly reducing cost.A direct comparison was performed between this CPT device and another similar device developed at the University of Cambridge. CPTβs were manufactured using the new design and then shipped to eight different centrifuge facilities, for quality control of similar experiments performed for LEAP (Liquefaction Experiments and Analysis Projects). All the centrifuge tests simulated a 4 m deep deposit of soil, all consisting of Ottawa F-65 sand with relative densities ranging between about 45 to 80%. The results obtained have been extremely valuable as an independent assessment of the density calculated from mass and volume measurements at different laboratories.
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- Award ID(s):
- 1635307
- PAR ID:
- 10073579
- Date Published:
- Journal Name:
- International Conference on Physical Modeling in Geotechnics
- Volume:
- 1
- Page Range / eLocation ID:
- 293-298
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Cone penetration tests (CPTs) are a commonly used in situ method to characterize soil. The recorded data are used for various applications, including earthquake-induced liquefaction evaluation. However, data recorded at a given depth in a CPT sounding are influenced by the properties of all the soil that falls within the zone of influence around the cone tip rather than only the soil at that particular depth. This causes data to be blurred or averaged in layered zones, a phenomenon referred to as multiple thin-layer effects. Multiple thin-layer effects can result in the inaccurate characterization of the thickness and stiffness of thin, interbedded layers. Correction procedures have been proposed to adjust CPT tip resistance for multiple thin-layer effects, but many procedures become less effective as layer thickness decreases. To compare or improve these procedures and to develop new ones, it is critical to have pairs of measured tip resistance ( qm) and true tip resistance ( qt) data, where qmis the tip resistance recorded by the CPT in a layered profile, and qtrepresents the tip resistance that would be measured in the profile absent of multiple thin-layer effects. Unfortunately, data sets containing qmand qtpairs are extremely rare. Accordingly, this article presents a unique database containing laboratory and numerically generated CPT data from 49 highly interlayered soil profiles. Both qmand qtare provided for each profile. An accompanying Jupyter notebook is provided to facilitate the use of the data and prepare them for future statistical learning (or other) applications to support multiple thin-layer correction procedure development.more » « less
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Cone penetration testing (CPT) is a preferred method for characterizing soil profiles for evaluating seismic liquefaction triggering potential. However, CPT has limitations in characterizing highly stratified profiles because the measured tip resistance (ππ ) of the cone penetrometer is influenced by the properties of the soils above and below the tip. This results in measured ππ values that appear ββblurredββ at sediment layer boundaries, inhibiting our ability to characterize thinly layered strata that are potentially liquefiable. Removing this ββblurββ has been previously posed as a continuous optimization problem, but in some cases this methodology has been less efficacious than desired. Thus, we propose a new approach to determine the corrected ππ values (i.e. values that would be measured in a stratum absent of thin-layer effects) from measured values. This new numerical optimization algorithm searches for soil profiles with a finite number of layers which can automatically be added or removed as needed. This algorithm is provided as open-source MATLAB software. It yields corrected ππ values when applied to computer-simulated and calibration chamber CPT data. We compare two versions of the new algorithm that numerically optimize different functions, one of which uses a logarithm to refine fine-scale details, but which requires longer calculation times to yield improved corrected ππ profiles.more » « less
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A cone penetrometer was specifically designed for the LEAP project to provide an assessment of centrifuge model densities independent from mass and volume measurements. This paper presents the design of the CPT and analyses of the results. Due to uncertainty in the specifications about how to define zero depth of penetration, about 20% of the CPT profiles were corrected to produce more accurate results. The procedure for depth correction is explained. After these corrections, penetration resistances at the representative depths of 1.5, 2, 2.5, and 3 m (prototype depth) are correlated to the reported specimen dry densities by linear regression. Using the inverse form of the linear regression equations, the density of each specimen could be estimated from the penetration resistance. Kutter et al. (LEAP-UCD-2017 comparison of centrifuge test results. In Model Tests and Numerical Simulations of Liquefaction and Lateral Spreading: LEAP-UCD-2017, 2019b) found that the density determined from penetration resistance was a more reliable predictor of liquefaction behavior than the reported density itself. Finally, the centrifuge tests at different LEAP facilities modeled the same prototype in different containers using different length scale factors (1/20 to 1/44); thus the ratio of layer thickness to cone diameter was different in each experiment. It appears that the penetration resistances are noticeably affected by container width and, to a lesser extent, resistance is affected by the length scale factor.more » « less
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This study uses a data-driven approach to address the complexities associated with research focused multi-sleeve Cone Penetration Test (CPT) devices, particularly focusing on the multi-friction attachment (MFA) and multi-piezo-friction attachment (MPFA) CPT devices. Hindered by time-consuming assembly and susceptibility to sensor stream losses due to extensive electronic components, these advanced devices demand optimization to transform from research devices to practice-suitable devices. This study aims at optimizing the design of the multi-sleeve CPT devices using machine learning, with soil type classification performance as the primary metric for device configuration effectiveness. The research scope centers not on using machine learning for soil classification but on refining the design of multi-sleeve CPT devices. A two-phase data-driven approach is adopted, testing various feature combinations across eight machine learning models. The first phase involves identifying the most suitable model for the dataset, followed by a refinement of features to balance sensor number minimization and soil classification accuracy. The result is a proposed configuration for a multi-sleeve CPT device, simplifying the original design while maintaining robustness, thereby enhancing cost-efficiency and operational effectiveness in geotechnical practice. This work sheds light on how the integration of machine learning can guide the design optimization of geotechnical instruments.more » « less
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Accepted Manuscript1.0
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- The DOI is not currently available.
