Bender Element Tests Research Articles

Measurement of Shear Wave Velocity During Microbial Grouting Based on Bender Element Tests

Measurement of Shear Wave Velocity During Microbial Grouting Based on Bender Element Tests

Comparative study on in-situ resilient modulus of subgrade estimated using in-situ modulus detector

This study presents a comprehensive evaluation of the resilient modulus of unsaturated subgrade soils using a novel in-situ modulus detector (IMD) along with various laboratory and field-testing methods. The current study employs several testing devices, including bender elements, standard dynamic cone penetrometer, and crosshole-type dynamic cone penetrometer (CDP), to assess the reliability of the IMD in estimating the resilient modulus profiles of small-scale homogeneous subgrade models in unsaturated conditions. The index properties, compaction and strength characteristics of the compacted soils, are evaluated. The resilient modulus values obtained from the IMD are compared with those obtained from repeated load triaxial tests under various stress states. Experimental results show a decrease in the penetration depth per blow with increased dry unit weight. In addition, elastic modulus and shear wave velocity increase with soil density. The resilient modulus estimated from the IMD increase with both depth and soil density. A robust correlation has been established between the resilient modulus values estimated from the IMD and those estimated from the CDP or bender element tests. Furthermore, the resilient moduli estimated from the universal model and the IMD demonstrate linear relationships with a coefficient of determination greater than 0.8. Thus, the IMD may be useful for the in-situ evaluation of resilient modulus in unsaturated subgrade soils, considering influencing factors such as soil density and confining pressure.

Small-strain stiffness of selected anthropogenic aggregates from bender element tests

Abstract This article presents a study on the stiffness of mixtures of anthropogenic materials derived from construction or demolition waste, specifically fine recycled concrete aggregates (fRCAs) with different fine fraction (FF) contents. The study investigated small-strain shear moduli via various signal interpretation methods, examining, above all, the time domain approaches and considering the influence of FF content. However, the inconclusive results from the bender element (BE) tests highlight the complexity of factors affecting shear wave velocity, which requires further research to refine the methodology and assess long-term performance in geotechnical applications. Selecting the correct test frequency and interpretation method is crucial to obtain accurate results. The BE test method should consider all relevant factors. At low input frequencies (≤5 kHz), the near-field effect affected the received signal for fRCA mixtures. At higher frequencies (around 14 kHz), the noise levels increased, thereby interfering with the S-wave travel time determination. Intermediate input frequencies (10.0 and 12.5 kHz) provided the representative shear modulus (G) values. The small-strain shear modulus (G max) of the fRCA compounds from the resonant column and BE tests was found to be in good agreement, despite differences in the test procedures themselves.

Maximum shear modulus anisotropy of rooted soils

The maximum shear modulus (G0(ij)) of rooted soils is crucial for assessing the deformation and liquefaction potential of vegetated infrastructures under seismic loading conditions. However, no data or theory is available to account for the anisotropy of G0(ij) of rooted soils. This study presents a new model that can predict G0(ij) anisotropy of rooted soils by incorporating the projection of the stress tensor on two independent tensors that describe soil fabric and root network. Bender element tests were conducted on bare and vegetated specimens under isotropic and anisotropic loading conditions. The presence of roots in the soil increased G0(VH) at all confining pressures (p′), as well as G0(HH) and G0(HV) at low p′. However, the trend was reversed at higher p′ because the roots reduced the effects of confinement on G0(ij) by replacing stronger soil–soil interfaces with weaker soil–root interfaces. Roots made the soil fabric and G0(ij) more anisotropic. The proposed model can effectively predict the observed anisotropy of G0(ij) under isotropic and anisotropic loading conditions. The new model also offers a new method for determining the fabric anisotropy of sand based on the anisotropy of shear modulus.

Evaluation of empirical and machine learning models for predicting shear wave velocity of granular soils based on laboratory element tests

Shear wave velocity (Vs) is crucial for designing geotechnical systems subjected to dynamic loads, especially in seismically active regions. The shear wave velocity of geomaterials can be determined using in situ and laboratory tests. However, due to time and cost limitations, the Vs is not easily available in most projects. Various empirical models have been developed by researchers for predicting the shear wave velocity of geomaterials. However, most of these models have been developed for specific soil types and loading characteristics. In this work, for predicting the shear wave velocity of granular soils using various combinations of input parameters, various empirical models were proposed. Furthermore, machine learning (ML) methods were utilized to predict the Vs. The suggested models consider the impact of grading characteristics such as fine content (FC), gravel content (GC), median particle size (D50), uniformity coefficient (Cu), and coefficient of curvature (Cc), as well as void ratio (e), mean effective confining pressure (σm′), consolidation stress ratio (KC), and specimen preparation techniques for reconstitution of specimens. To achieve this, a series of bender element tests were performed on various sand and gravel mixtures. Furthermore, data from previous studies were also used. So, the study utilized 513 data points from laboratory element experiments conducted on granular soils. For predicting the Vs of granular soils, four empirical models and three ML models, namely Artificial Neural Network (ANN), Support Vector Regression (SVR), and Gradient Boosting Regression (GBR), were developed in this study. The findings showed that the ANN model outperforms the other comparative models in terms of accuracy and error. While the empirical models may serve as useful tools for initial Vs estimation in construction projects, the study primarily highlights the significance of using ML methods to enhance the prediction accuracy of Vs based on the available soil properties.

Small-strain shear modulus and liquefaction resistance of calcareous sand with non-plastic fines

Incorporation of non-plastic fines can dramatically affect the liquefaction resistance and stiffness of sands. In this study, the aim is to evaluate the influence of non-plastic fines on the liquefaction resistance and small-strain shear modulus of calcareous sand under cyclic loading. Forty-seven sets of undrained cyclic triaxial tests and companion bender element tests are conducted on reconstituted specimens. The cyclic behaviour of clean sand and silty sand with varying fines content is examined with respect to the global void ratio, relative density and granular skeleton void ratio. The findings demonstrate that the microscopic contacts between coarse and fine grains have a significant impact on the macroscopic behaviour of sand–fines mixtures. The experimental findings are evaluated using the equivalent granular skeleton void ratio, which has been recognised as a suitable parameter to describe the overall effect of fines. The findings on calcareous sand with fines are supplemented and compared with published data in accordance with the semiempirical simplified approach for liquefaction triggering based on shear wave velocity.

Liquefaction resistance and small strain stiffness of silty sand: Effects of host sand gradation and fines content

In this paper, a well designed experimental study comprising undrained cyclic triaxial and bender element tests was carried out on five sand-silt mixtures with three grain size ratios (Rd) and three sand uniformity coefficients (Cus). The results reveal that at given fines content (FC) and void ratio, the liquefaction resistance (CRR) of the mixtures decreases as Rd increases from 9.7 to 27.8 or Cus from 1.50 to 4.46, and the CRR of the mixture at the highest Rd or Cus becomes as low as nearly 50% of that at the lowest Rd or Cus. The equivalent relative density (Dr*) based on the binary packing theory can be utilized to capture the coupled effects of host sand gradation and FC on the CRR of sand-silt mixtures. A novel finding is that a universal relationship exists between the liquefaction resistance and the shear modulus normalized by the minimum void ratio function of host sand (GN') for different FCs, initial effective confining pressures, sample preparation methods (SPMs), and host sand gradations. Based on the comprehensive laboratory test data, the empirical CRR15-GN' correlation is proposed and further adjusted for the field liquefaction triggering analysis based on the shear wave velocity (Vs). Soil can be considered non-liquefiable when its equivalent shear wave velocity exceeds 225 m/s or the applied cyclic stress ratio (CSR) is below 0.088. Comparisons with the previously established liquefaction triggering boundary curves validate the applicability of the proposed curve for initial evaluation of the liquefaction resistance of sandy soils, indicating laboratory studies can complement in-situ investigations for Vs-based liquefaction assessment.

Machine Learning Models for Predicting Shear Wave Velocity of Soils

As regards regions prone to seismic activity, shear wave velocity (Vs) is a design parameter for geotechnical systems exposed to dynamic loads. Evaluating Vs for geomaterials involves on-site and laboratory assessments; however, its availability is often limited in projects owing to resource and time constraints. Various mathematical and empirical models have been proposed to predict Vs for cohesive or granular soils; however, a majority of these models are specific to certain soil types and loading conditions. In this study, machine learning techniques were used for Vs prediction. These models encompass factors such as grading attributes, void ratio (e), mean effective confining pressure (σ’m), consolidation stress ratio (KC), and specimen preparation methods. To achieve this, a series of bender element tests was performed on various sand and gravel mixtures supplemented with culled data from earlier investigations. This study facilitated the development of three machine learning models aimed at predicting the Vs for granular soils: artificial neural networks (ANN), support vector regression (SVR), and gradient boosting regression (GBR), aimed at predicting Vs for granular soils. The findings of the study demonstrated that the ANN model exhibited enhanced precision and reduced error compared with the other models.

Hydro-mechanical model for small-strain stiffness of unsaturated soil

This study aims to investigate a novel method for predicting the small-strain stiffness of unsaturated soil. A hydro-mechanical model is proposed to estimate the small-strain stiffness of unsaturated soil with various matric suction and stress states. A series of saturated and unsaturated bender element tests are conducted, and the test results indicate that the small-strain stiffnesses of saturated and unsaturated soil have similar changing trends with the variation of the stress state. The small-strain stiffness of unsaturated soil is calculated by the proposed model based on the test results of saturated soil. The model has two parameters that have a physical meaning and can be measured by tests. Thus, combined with the mature prediction model and measurement method of saturated soil and the proposed hydro-mechanical model, the complex unsaturated bender element tests are unnecessary. The proposed model is anticipated to be of practical value for solving engineering problems during the determination of small-strain parameters in the design of pits and foundations.

Measurements of Shear Wave Velocity for Collapsible Soil

This paper examines the effects of collapsible soil structure on shear wave velocity. The study attempts to simulate hydraulic fill sand deposits, which represent a natural soil deposition process that can result in a collapsible soil structure. A series of resonant column tests and bender element tests on Ottawa sand was conducted on sand specimens and prepared by dry pluviation and simulated hydraulic fill methods subjected to various confining pressures. Shear wave velocities measured from both methods of deposition are compared and discussed. Results from this study show that for soil specimens with the same void ratio, samples prepared by simulated hydraulic fill have a lower shear modulus and shear wave velocity than the specimens prepared by dry pluviation, and the differences are more pronounced at higher confining pressures. The resonant column test results performed in this study were consistent with results from the discrete element analysis, full-scale testing, and centrifuge testing. The discrete element analysis suggests that soil fabric and number of particle contacts are the key factors affecting the shear wave velocity. These factors are dependent on the methods of deposition. Results from this study examining hydraulic fill collapsible structure shear wave velocity provide a step forward toward a better correlation between soil dynamic properties measured in field and laboratory tests.

An experimental study to investigate the mechanical behaviour of low plasticity fine-grained soil stabilized with different contents of lime and fly ash

ABSTRACT Shear strength, small and large strain stiffness moduli, and cyclic stiffness degradation of fine-grained soil with low plasticity (CL-ML) stabilized with different contents of lime and fly ash were investigated in this work. The results of static triaxial tests showed that adding fly ash to the soil-lime mixture increases significantly the compressive strength of the samples due to an increase in pozzolanic reactions. By varying fly ash up to 15% and lime up to 7%, an optimal composition with 5% lime and 15% fly ash was achieved, in which the shear strength was maximum. The results of the bender element tests also showed that the mixture of 5% lime and 15% fly ash has the highest maximum shear modulus. The results of the cyclic triaxial tests on the samples with the optimal composition; showed cyclic degradation of the stiffness due to the failure of cement bonds.

Assessment of liquefaction potential based on shear wave velocity: Strain energy approach

Liquefaction assessment based on strain energy is significantly superior to conventional stress-based methods. The main purpose of the present study is to investigate the correlation between shear wave velocity and strain energy capacity of silty sands. The dissipated energy until liquefaction occurs was calculated by analyzing the results of three series of comprehensive cyclic direct simple shear and triaxial tests on Ottawa F65, Nevada, and Firoozkuh sands with varying silt content by weight and relative densities. Additionally, the shear wave velocity of each series was obtained using bender element or resonant column tests. Consequently, for the first time, a liquefaction triggering criterion, relating to effective overburden normalized liquefaction capacity energy (WL/σc’) to effective overburden stress-corrected shear wave velocity (Vs1) has been introduced. The accuracy of the proposed criteria was evaluated using in situ data. The results confirm the ability of shear wave velocity as a distinguishing parameter for separating liquefied and non-liquefied soils when it is calculated against liquefaction capacity energy (WL/σc’). However, the proposed WL/σc’-Vs1 curve, similar to previously proposed cyclic resistance ratio (CRR)-Vs1 relationships, should be used conservatively for fields vulnerable to liquefaction-induced lateral spreading.

Compaction, strength, and volume change characteristics of excavated clayey soil stabilized with composite admixture of cement and autoclaved aerated concrete powder

Low-strength and highly compressible excavated clayey soils are common in geotechnical engineering, which cannot serve as a bearing stratum and typically end up being disposed of in landfills. Autoclaved aerated concrete powder (AACP) is a lightweight and porous waste material, with its stockpiles rapidly accumulating worldwide. To promote sustainable development in geotechnical engineering, a type of composite admixture consisting of cement and AACP was developed to modify clayey soils in this study. The physical and mechanical properties of untreated and the composite admixture-treated soil samples were investigated via Atterberg limits, compaction, bender element, constraint compression, free swell, and unconfined compressive strength (UCS) tests. The physicochemical and microstructural observations, including soil pH, scanning electron microscopy, and mercury intrusion porosimetry analyses, were conducted to interpret the macroscopic mechanical behaviors. Test results showed that the incorporation of AACP improved the workability of clayey soils, while cement further enhanced their mechanical properties. Hydration compounds primarily filled the voids with a diameter ranging from 0.1 to 1 µm. From the perspective of volume change behavior, 8% cement content was recommended. Shear wave velocity showed a strong correlation with the UCS, demonstrating that the bender element technique was an effective non-destructive tool for assessing the strength of compacted samples.

Influence of time on the small strain shear modulus of an allophanic volcanic ash

The small strain shear modulus is an important parameter in the assessment of soil dynamics problems. Studies on the small strain shear stiffness of volcanic ash remain rare probably because globally they cover just under 1% of the land surface. However, on a regional scale, this figure may be consequential as in the case of Japan, where about one third of its total land surface is covered by andosols. In this research, we aimed at understanding the influence of confinement time, a non-negligible parameter, contingent on the soil type, which needs to be accounted for when assessing the shear modulus. Bender element tests were conducted on allophanic volcanic ash, kuroboku soil sampled from the southern island of Kyushu in Japan. The allophanic ashes present all the characteristics of a non-textbook soil, notably high natural water content, high liquid and plastic limits and high void ratios. From the micrographic images, it was observed that the soil structure consisted of different types of porous particles (allophane, imogolite, volcanic glass and so on) at different internal spatial scales. Strong electrostatic bonding between the allophane particles means that in normal conditions the soil material exist as aggregates. The consequence is that the end of the consolidation stage is reached within a few minutes. Thus, the threshold demarcating the onset of the creep stage is different compared to sedimentary materials or other clayey soils. Based on the test results, empirical equations for predicting the time-dependent behaviour of the shear modulus were proposed.

Use of machine learning in determining Gmax from bender element tests

The use of bender element is one of the most popular methods of determining shear wave velocity, and hence elastic shear modulus due to its relatively straightforward experimental set-up. While several analysis methods have been proposed, manual interpretation using the first arrival continues to be favoured owing to its simplicity. This paper presents a novel automated program for determining the shear wave velocity and associated maximum shear modulus. The proposed new method involves the use of Convolutional Neural Networks (CNNs) to predict the most probable shear wave velocity using a range of input frequencies as the inputs. Estimates made by the trained CNN are compared to values determined using more traditional interpretation methods (first-arrival, cross-correlation and frequency domain). The program is able to autonomously determining the shear modulus in the three principal orientations (Gvh, Ghv, and Ghh) at a range of stress levels. The shear modulus determined using the range of techniques showed great agreement. Statistical analysis of the determined shear modulus regression of over 0.99 between interpretations made using first arrival and that estimated using the new CNN approach.

Relation between liquefaction resistance and shear modulus of crushable volcanic soils

Pumice-rich soils originating from volcanic eruptions are deposited in various parts of the world, such as in the central region of North Island, NZ. The pumice sand components of these natural pumiceous (NP) soils are known to be crushable and lightweight, resulting in a significant difference in their cyclic resistance ratio (CRR) and small-strain shear modulus (Gmax) when compared to hard-grained (quartz) sands. In this paper, the results of a number of cyclic triaxial and bender element tests performed on reconstituted specimens of three types of NP sands having different pumice contents (PC), as well as on quartz-type Toyoura sand specimens, are discussed. Then, the concept of modified cyclic yield strain, εay,m, which relates the CRR of the specimen to its Gmax, is used. The results indicate that εay,m appears to be dependent only on the soil type, and independent of the confining pressure applied and the relative density of the specimen. All NP sand specimens show higher εay,m when compared to Toyoura sand because of their higher CRR and lower Gmax, with values of εay,m increasing as the PC of the specimen increases. Based on the results obtained, an empirical chart is developed to estimate the CRR of NP sands from their shear wave velocity (Vs) values under field conditions.

Mechanical Properties and Microscopic Mechanism of Basic Oxygen Furnace (BOF) Slag-Treated Clay Subgrades

Civil engineering faces a substantial challenge when dealing with soft and compressible clayey soils. Conventional soil stabilization techniques involving ordinary Portland cement (OPC) result in notable CO2 emissions. This study explores the utilization of basic oxygen furnace (BOF) slag, a by-product of steel production, for strengthening kaolin clay. This research investigates the influence of BOF slag particle size, BOF slag content, and the use of activators such as lime and ground granulated blast-furnace slag (GGBFS) on the stabilization of kaolin clay. The strength development is assessed through unconfined compressive strength (UCS) test, bender element (BE) test, and scanning electron microscopy (SEM). The findings reveal that higher BOF content and extended curing periods enhance soil strength, and lime and GGBFS effectively augment the stabilizing properties of BOF slag. Stabilizing kaolin clay with a 30% BOF/GGBFS mixture in a 50/50 ratio with 1% lime and curing for 7 days yielded a compressive strength of 753 kPa, meeting the Federal Highway Administration’s requirement for lime-treated soil. These combined measures contribute to developing a more robust and stable material with enhanced geotechnical properties.

Investigation on the properties of compacted silty clay subjected to electro-osmosis using bender element

The moisture content of subgrade soil in seasonally frozen regions is often higher than its optimum value, leading to a decline in mechanical properties and a reduction in subgrade bearing capacity. Electro-osmosis has shown promise as a technology for controlling subgrade moisture, but significant heterogeneity has also been observed in treated soil. This study investigates the impact of electro-osmosis on soil stiffness through a series of bender element tests of compacted clay. The effects of dry density and supply voltage on the performance of electro-osmosis treatment and the layered structure and anisotropy of the soil were analyzed. The results show that electro-osmosis treatment increased the shear wave velocity of the soil by 140% compared to untreated saturated soil and by 70% compared to soil with optimum water content. It has also been found that layered compaction of soil resulted in a layered structure, with electro-osmosis having a more prominent impact on soil near the cathode, resulting in a more pronounced layered structure. Besides, electro-osmosis was found to enhance soil anisotropy, particularly near the anode. Increasing the dry density and voltage levels can help improve soil uniformity. These findings provide insights into the potential use of electro-osmosis in improving soil stiffness, which could benefit various engineering applications.

Prediction model for small-strain shear modulus of non-plastic fine–coarse-grained soil mixtures based on extreme void ratios

The small-strain shear modulus G0 is a fundamental parameter for characterizing the dynamic behavior of soils. In this study, bender element tests were performed to investigate how the effective confining stress σ'c, relative density Dr, void ratio e, and a wide range of fines content FC (0%–100%) influence the G0 of soil mixtures containing both fine and coarse grains. The results show that under the same e and σ'c, G0 first decreases and then increases with increasing FC. Furthermore, as characteristic state parameters, the extreme void ratios (i.e., the maximum void ratio emax and the minimum void ratio emin) reflect comprehensively the particle size distribution and shape of fine–coarse-grained soil mixtures. Under the same σ'c, the lower limit of G0 (G0min) decreases with increasing emax and the upper limit (G0max) decreases with increasing emin, and the extrapolated upper and lower limits of the normalized G0/(σ'c/Pa) show a negative power-law relationship with emin and emax, respectively. Empirical formulas are established for the G0max and G0min of fine–coarse-grained soil mixtures, and G0 under various Dr can be interpolated according to G0min (for Dr = 0) and G0max (for Dr = 1). Finally, a G0 prediction model that offers reasonable characterization of fine–coarse-grained soil mixtures with different FC is established based on emin and emax.

Anisotropic small-strain stiffness of lightly biocemented sand considering grain morphology

Small-strain stiffness and stiffness anisotropy of a sand are sensitive to the sand fabric, which can be significantly affected by particle shape and cementation. In this study, multidirectional bender element and isotropic compression tests were performed on glass sands with different particle shapes and biocementation levels. The small-strain stiffness and stiffness anisotropy of the untreated and biotreated sands were systematically investigated. A natural cementation process is used to investigate the small-strain stiffness of cemented sand; this might be a potential way to replicate the mechanical behaviour of undisturbed sand with weak cementation. Test results showed that the small-strain stiffness increases with increasing sand angularity. It is proposed that shear wave velocity has different sensitivities to particle shape parameters for uncemented sands. The stiffness anisotropy increases with the increase in sand angularity and decreases with increasing stress levels at an identical void ratio state. For the lightly biocemented sands, the small-strain stiffness can be improved significantly after the biotreatment reaction with the calcite bonds among grains. The development of small-strain stiffness with stress is different for specimens with different cementation levels. The stiffness anisotropy ratio first increases and then decreases with the increase of the biocementation level, which cannot be changed even with normalisation using the parameter A in the Hardin equation.