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This dataset comprises a subsurface characterization of key liquefaction areas in Golbasi, Türkiye, following the February 6, 2023, Kahramanmaraş earthquake sequence. Field testing was conducted from October 30th to November 10th, 2023. The dataset includes Cone Penetration Tests (CPT) as well as borehole sampling and incorporates pore pressure dissipation measurements and standard CPT readings. High-quality subsurface investigations, such as this dataset, are a key component of liquefaction case histories. As such, this data is vital for future analyses of liquefaction-induced building settlements, building-ground interactions, and liquefaction-induced ground deformations resulting from the Kahramanmaraş earthquake sequence. 

This dataset comprises a subsurface characterization of key liquefaction areas in İskenderun, Türkiye, following the February 6, 2023, Kahramanmaraş earthquake sequence. Field testing was conducted from March 18 to March 27, 2024. The dataset includes Cone Penetration Tests (CPT) as well as seismic CPTs (SCPT) and incorporates pore pressure dissipation measurements, shear wave velocities, and standard CPT readings. High-quality subsurface investigations, such as this dataset, are a key component of liquefaction case histories. As such, this data is vital for future analyses of liquefaction-induced building settlements, building-ground interactions, and liquefaction-induced ground deformations resulting from the Kahramanmaraş earthquake sequence. 

The Global Industry Standard on Tailings Management (GISTM) promotes performance-based approaches in geotechnical assessments. Hence, characterizing the spatial variability of deposited tailings is expected to be a key input for some tailings storage facilities(TSFs); however, it has seldom been investigated. In this study, we assess the spatial variability of thickened and conventional tailings, which have been deposited into the same TSF, providing a unique opportunity to investigate two tailings technologies. A dense array of 15 cone penetration tests (CPTus) with an average offset of 1.5 m has been conducted to collect data. In addition to evaluating the spatial variability, the collected information is also used to assess the potential of machine learning (ML) for detrending when deriving random fields. Using a new proposed stationarity score, we find that an ML-based detrending outperforms traditional procedures for most scenarios. In terms of correlation lengths, we find similar ranges for thickened and conventional tailings (vertical: δwv ¼ 0.2–0.6 m, horizontal δwh ¼ 1.5–4.5 m)and similar distributions, likely influenced by the depositional processes. In contrast, the variance in the conventional tailings is higher, which we attribute to its segregating nature. Finally, by inspecting previous studies on natural soils, we find that the variability of mine tailings(δwh=δwv ¼ 2–21) resembles that observed in alluvial deposits, which we attribute to the parallels in the depositional process 

This study assesses the robustness of a framework based on critical state soil mechanics (CSSM) principles in evaluating earthquake-induced liquefaction manifestation. The assessment is motivated by the contrasting procedures in evaluating static and cyclic liquefaction, where mechanical properties commonly inform the former, whereas the latter often relies on semiempirical-based methods. The framework discussed in this study considers as ingredients (1) laboratory-based mechanical properties that are an average representation of soil’s microstructure, (2) state inversion, (3) the link of state with cyclic resistance ratio (CRR), and (4) the seismic demand, represented by the cyclic stress ratio (CSR). The framework is assessed using ~5000 cone penetration tests (CPTus) conducted after the Canterbury earthquake sequence, where each CPTu is associated with liquefaction manifestation levels. The discussed framework is used to estimate safety factors, which are then combined with several liquefaction severity indexes (LSIs) to evaluate liquefaction manifestation in the context of a classification problem (i.e., “Yes” and “No”). The framework’s performance is assessed using machine learning by estimating receiver operating characteristic curves (ROC). Different state inversion procedures are also considered, and recommendations based on their performance are provided. In particular, a calibrated cavity expansion-based inversion for New Zealand is proposed. We find that the discussed framework offers comparable performance to state-of-practice procedures, even when general considerations for mechanical properties based on CSSM are made, which is encouraging. Moreover, by including mechanical properties, it can better inform extrapolations for regions without significant data and non-typical soils as long as adequate properties are considered. In this context, it shares conceptual similarities with non-ergodic approaches in earthquake engineering. 

Significant and widespread liquefaction occurred in İskenderun during the 2023 Mw 7.8 Kahramanmaraş earthquake. Liquefaction effects on buildings were observed in several areas of İskenderun, predominantly in areas of reclaimed land and near historic shorelines. Liquefaction-induced building settlements were particularly concentrated in the Çay District, which is almost entirely reclaimed land. Liquefaction-induced ground and building settlements were either marginal or not apparent in areas away from the historical shorelines. Building settlement and ground deformation were documented at 26 buildings in İskenderun through lidar scans and laser-level hand measurements. Liquefaction-induced building settlements ranged from 0 to 740 mm. Building-ground interactions were evident from hogging ground deformations, including cases where buildings deformed nearby ground and damaged nearby buildings, and sagging buildings. Historic land development affected the spatial extent of observed liquefaction-induced building damage. Representative liquefaction-induced building settlement and building interaction case histories are discussed and key insights are shared. 

Several case history failures of slope systems have highlighted that the instability onset in loose materials can be triggered under prevailed drained conditions and stress paths that can be represented by constant shear drained (CSD) loading. This study uses the anisotropic critical state theory (ACST) to assess the effect of fabric anisotropy and loading characteristics (e.g., Lode angle and principal stress direction) on the instability onset under CSD stress paths, comparing our numerical-based observations with available experimental information. Towards this end, the ACST-based SANISAND-F model’s performance under CSD stress paths is also assessed. In addition, multiaxial conditions are incorporated through the estimation of instability surfaces. The numerical simulations are useful in explaining that the instability onset under CSD loading is dictated by a trade-off of volumetric strain components. Moreover, the results show an important effect of fabric anisotropy on the instability stress ratio (𝜂𝑓 ). For conditions representative of common experimental setups, 𝜂𝑓 decreases with the increase of the Lode angle and the major principal stress inclination, and 𝜂𝑓 increases with the increase of initial fabric intensity, consistent with available experimental evidence. However, these trends can change based on the interaction between the Lode angle and loading/fabric directions; hence, departing from typical experimental observations. Finally, we discuss the potential of a simplified approach to estimate 𝜂𝑓 analytically, including fabric effects. 

Understanding the cyclic response of mine tailings is key for areas with moderate to high seismicity and an active mining industry (e.g. the United States, Peru, and Chile). However, assessing the cyclic response of mine tailings still relies on procedures and correlations developed for natural soils (i.e. sands and clays). This is due to information on the cyclic response of mine tailings being rather scarce compared to natural soils. Hence, it remains unclear if more efficient approaches can be implemented. This study presents an experimental database focused on the cyclic response of mine tailings compiled from various sources. The database is organized considering three classes, where all three contain cyclic simple shear (CSS) information. Class A also includes triaxial (Tx) and cone penetration testing (CPTu) information, Class B has Tx or CPTu information, and Class C contains no additional information beyond CSS. Most materials belong to Class A. It is worth noting that Class C (only cyclic information) is comparable with most databases for natural soils, hence highlighting the uniqueness of our database. In total, the database contains 129 CSS tests on 20 materials that represent a broad range of mine tailings. Thirteen materials belong to Class A, 5 to Class B, and 2 to Class C. In discussing the database, key information (e.g. the range of liquefaction resistance curves) is shared. In addition, potential assessments that can be conducted with the database are illustrated. The study closes by presenting the database organization and discussing potential uses. The database is available under the following DOI: https://doi.org/10.17603/ds2-1k0a-dt17 

The onset of static liquefaction in anisotropically consolidated soils is of relevance in assessing the performance of geotechnical systems. Previous studies have also highlighted the role of inherent soil fabric. This study derives an analytical instability criterion for granular materials under undrained loading by using the relatively new anisotropic critical state theory (ACST). The criterion is established using the SANISAND-F model, and it is amenable to incorporating consolidation anisotropy and fabric effects. We assess different numerical strategies for simulating the instability onset on materials sheared from initially anisotropic conditions. Our assessments indicate that simulations that consider consolidation followed by shear better represent the response observed in laboratory tests. It is observed that the degree of anisotropic consolidation has no significant effect on the instability stress ratio, but a very high degree of anisotropic consolidation results in a spontaneous collapse. It is also observed that the anisotropic consolidated specimens have a higher instability stress ratio in triaxial compression than in triaxial extension, highlighting the effect of loading direction relative to the existing fabric. 

Arguably, critical state soil mechanics (CSSM) is now the preeminent methodology for understanding static liquefaction of mine tailings, having been used in the mining industry by the expert panels retained to investigate recent TSF failures. One of the key ingredients of the CSSM framework is the assessment of a critical state line, which separates contractive from dilative states. A critical state line is often defined by a linear relationship and two parameters, namely the altitude of the critical state line at 1 kPa (􀟁) and its slope (􀟣). In this study, we use the TAILENG mine tailings database to investigate potential relationships between the particle features and the particle size distribution, and the critical state properties. Towards this end, the critical state line is evaluated for a range of mine tailings with broad gradations and compressibility, defining 􀟁and 􀟣, with known particle size distributions. This information is subsequently used to investigate potential correlations. Insights from the observations are shared, and potential fundamental mechanisms in explaining correlations between the critical state properties and particle features are discussed.