FALL CONE TEST CALIBRATION FOR SLOPE STABILITY ANALYSIS

1. Introduction

Fall cone test (FCT) has emerged as a prominent tool to evaluate the Atterberg limits of clayey materials (Spagnoli, 2012; Nini, 2014; Niazi et al., 2019; Vardanega et al., 2022; Marušić & Jagodnik, 2023; Malki & Abed, 2024; Marušić & Jagodnik, 2025). This method provides accuracy comparable to the Casagrande test while offering a key advantage by minimizing the human error associated with subjective blow count measurements (Shimobe & Spagnoli, 2020). Since the late 1950s, the FCT has evolved to serve as a valuable tool for estimating undrained shear strength ([TeX:] s_{u}$s_u$) and quantifying sensitivity of both disturbed and undisturbed cohesive soils (Wood, 1985; Tanaka et al., 2012). The [TeX:] s_{u}$s_u$ values derived from the FCT align well with those obtained from direct shear tests conducted at low moisture content, as well as from laboratory vane shear tests (Canelas et al., 2018).

The efficacy of the FCT performance is intrinsically linked to its physical setup. Factors such as shape and weight of the cone are rigorously studied and defined by established standards (Shimobe & Spagnoli, 2019). For example, the commonly used 30° cone weighing 80 grams is prevalent in the United Kingdom, New Zealand, Australia and France, whereas the 60° cone weighing 60 grams is more frequently employed in Scandinavian nations (Shimobe, 2010). Beyond these physical specifications, the accurate estimation of [TeX:] s_{u}$s_u$ relies heavily on the cone factor (K), which is known to be significantly influenced by additional parameters (Hansbo, 1957; Karlsson, 1961; Wroth & Wood, 1978; Houlsby, 1982; Koumoto & Houlsby, 2001). Research has demonstrated that these factors include; the shearing rate and clay sensitivity, as well as the cone's surface roughness and the intrinsic cone angle influence, which is explained through fundamental energy conservation principles (Wood, 1982; Wood, 1985; Sivakumar et al., 2015; Farias & Llano-Serna, 2016; Vardanega et al., 2018; Llano-Serna & Contreras, 2020; Zeng et al., 2020).

Despite extensive research, the literature presents a wide and inconsistent range of K values (Karlsson, 1961; Medhat & Whyte, 1986; Brown & Huxley, 1996; Sharma & Bora, 2003; Kyambadde, 2010). A value of 0.8 is currently recommended by (EN ISO 17892-6, 2017). This variability is largely attributed to the inexistence of a coherent and standardised methodology of cone factor calibration (Llano-Serna et al., 2018). Compounding this issue, the applicability of the Hansbo relationship (Hansbo, 1957) is itself questionable for highly consolidated samples (Stróżyk & Tankiewicz, 2013), with significant uncertainties remaining in the estimation of [TeX:] s_{u}$s_u$ for fine-grained soils (Llano-Serna & Contreras, 2020), even with proposed modifications to account for strain rate effects (Hazell, 2008).

A critical limitation in much of the existing research is the tendency to focus primarily on idealised pure clay samples. This approach fails to capture the complexity of in situ reality, where natural soils often contain varying amounts of silt and sand. This granulometric variability can markedly affect their geotechnical properties (Terzaghi, 1925; Gilboy, 1928; Lees, 1964; Olson & Mesri, 1970; Abbireddy et al., 2009; Clayton et al., 2009; Göktepe & Sezer, 2010; Cabalar et al., 2013a; Cabalar & Hasan, 2013; Cabalar, 2018), a challenge particularly evident in studies examining the impact of clay-sand mixtures on [TeX:] s_{u}$s_u$ (Cabalar et al., 2020). Given the research gaps, this investigation intends to examine the combined influence of soil texture (i.e., the fines content) and overconsolidation ratio on cone factor, and their implications for the accuracy of undrained shear strength estimation.

2. Investigated materials and methodology

2.1. Origin and identification

This geotechnical investigation primarily utilised two materials which are identical and reported previously (Chalabi et al., 2024). Sand, characterized by its granularity and absence of cohesion, is commonly integrated as a plasticity modulator in geotechnical engineering in line with various established study practices (Louafi & Bahar, 2012; Amri et al., 2019; Bhardwaj & Sharma, 2020; Meddah et al., 2022; Qusai et al., 2025). Clay, which is a cohesive, fine-grained material capable of undergoing significant consolidation. The combination of these two types of materials can effectively represent a mixture of clay, silt, and sand as described by (Gökalp, 2009).

The sandy material was procured from the Bouihi quarry located North West of Algeria (see Figure 1). This poorly graded sand (according to USCS (ASTM D2487-17e1, 2017)) is widely employed in construction applications, specifically for wall plastering. Meanwhile, The clayey soil utilised was collected adjacent to a ceramic tile manufacturing facility North West of Algeria (see Figure 2). This low plasticity clay (according to USCS (ASTM D2487-17e1, 2017)) locally designated as "blue clay," constitutes a base material of ceramic wall tiles. Figure 3 and Table 1, provide a summary of the comprehensive geotechnical properties of the employed materials.

Figure 1. Bouihi quarry (North West of Algeria) – Google Map (34.42166, -1.690772)

Figure 2. Clay deposit (North West of Algeria) – Google Map (35.11198, -1.427161)

Figure 3. Particle size analysis for all mixtures

Table 1. Geotechnical characteristics of clay and sand

2.2. Specimen formulations

This study employed six distinct mixtures for the experimental investigations in accordance with the protocol defined in Chalabi et al. (2024); M-1 (100% Clay + 0% Sand), M-2 (90% Clay + 10% Sand), M-3 (80% Clay + 20% Sand), M-4 (70% Clay + 30% Sand), M-5 (60% Clay + 40% Sand), and M-6 (50% Clay + 50% Sand). The investigation involved testing clay-sand mixtures at varying water contents (ω %) to pinpoint the optimal moisture level that achieves the required physical properties.

Specimens were meticulously fabricated by gradually incorporating water, subsequently statically compacting the resulting mixture into an oedometer ring with a predefined volume of 7.914 × 10⁻⁵ m³ (see Figure 7). Later analyses were conducted to assess key characteristics as illustrated in Figures 4a to 4c, which demonstrate the relationship between moisture content and material behaviour.

Figure 4. Variation of mixtures behaviour as function of moisture content a) Dry unit weight b) Void ratio c) Degree of saturation.

The findings illustrated in Figure 4a and Figure 4b reveal that a moisture content ranging from 15% to 20% is optimal for achieving peak density in the various formulations, underscoring the role of a specific amount of moisture in attaining the desired density within these mixtures. Conversely, Figure 4c shows that a moisture content of 25% induces full saturation in every specimen. Therefore, this consistent moisture content was selected and applied for the constitution of the testing samples. This decision supports the validation of the consolidation criterion based on Terzaghi's postulate (Terzaghi & Peck, 1967), enabling a more accurate observation and analysis of the samples' consolidation behaviour.

2.3. Stress history and consolidation protocols

Following the defined mixture moisture specification, cylindrical samples with a volume of 7.914 x10⁻⁵ m³ were prepared (see Figure 5) and subjected to a range of pressure conditions. The procedure implemented as described by (Chalabi et al., 2020) comprised imposing a consolidation pressure ([TeX:] {\sigma'}_{c}${\sigma \prime }_c$) to the samples, subsequently releasing this pressure to achieve a targeted vertical effective pressure ([TeX:] {\sigma'}_{v}${\sigma \prime }_v$) corresponding to the desired overconsolidation ratio (OCR).

In this regard, consolidation cells were employed (see Figure 6), designed with mechanical linkages that magnify the applied load tenfold. The overconsolidation ratios OCR selected were 1, 2, 4, and 8. Their corresponding stress paths, defined by ([TeX:] {\sigma'}_{c}${\sigma \prime }_c$ [kPa], [TeX:] {\sigma'}_{v}${\sigma \prime }_v$ [kPa]), were set as follows; (25,25), (50,25), (100,25), (200,25) as previously established by (Chalabi et al., 2024). Throughout the consolidation stage, the imposed pressure exerted upon the soil specimens was systematically incremented by a factor of two at every loading step. This consistent consolidation stress escalation facilitated the meticulous monitoring and evaluation of the soil′s behaviour under elevated stress states.

Figure 5. Soil filled in the cylindrical mold

Figure 6. Sample under consolidation

Each transition between loading and unloading increments within the consolidation cells was allotted a duration of 24 hours. This timeframe was crucial for allowing the samples to stabilise and achieve an equilibrium condition under the newly imposed load. Throughout this 24-hour period, the specimens experienced consolidation mechanisms, characterised by a reduction in voids between particles and a reorganisation of particles to accommodate the new pressure conditions.

3. Results and discussion

The samples of the six consolidated mixtures were subsequently subjected to two types of laboratory experiments; the pocket shear vane (see Figure 7) and the fall cone test (see Figure 8). These tests are primarily employed to assess [TeX:] s_{u}$s_u$, that is to be considered and further examined in subsequent sections of this paper.

Figure 7. Pocket shear vane test

Figure 8. Fall cone test

3.1. Influence of overconsolidation ratio and fines content on cone penetration

The FCT (see Figure 8) is performed by releasing the standardised steel cone, which then penetrates the soil sample by gravitational force alone. Resulting vertical displacement is measured using an integrated dial gauge. The cone used for this test has a 30° angle and a mass of 80 g.

As shown in Figure 9, cone penetration decreases with an increase in the overconsolidation ratio, irrespective of the mixture composition. This relationship is found to follow a power law, with greater penetration observed in mixtures containing a lower fine content. Furthermore, the results presented in Figure 10 corroborate that cone penetration is higher for mixtures with a lower fine content, regardless of the overconsolidation ratio. Specifically, an inverse power-law relationship is demonstrated between cone penetration and the fine content, confirming that increasing the proportion of fines leads to a reduction in penetration.

Figure 9. Variation of cone penetration with respect to overconsolidation ratio

Figure 10. Variation of cone penetration with respect to fines content

3.2. Comparison of [TeX:] \mathbf{s}_{\mathbf{u}}${𝐬}_{𝐮}$ from pocket shear vane and fall cone tests

The pocket shear vane (see Figure 7) is a portable instrument equipped with different-sized vanes designed to adapt various soil consistencies. During testing, the selected vane is inserted perpendicularly within the specimen, then subsequently rotated slowly at a uniform speed until failure takes place. The torque at the point of failure is displayed on a dial, and this measurement is then converted to undrained shear strength using a calibration chart.

On the other hand, undrained shear strength by FCT is calculated using the empirical formula (Equation 1) proposed by (Hansbo, 1957), which correlates it with the penetration depth as follows :

[TeX:] s_{u} = \ \frac{K\ m\ g}{H^{2}}$s_u=\frac{Kmg}{H^2}$ (1)

With:

g- Acceleration due to gravity (9.81 [TeX:] m.s^{- 2}$m.s^{-2}$),

m- Cone masse (80 grams),

H- Penetration (in millimeters),

K- Cone factor.

In this study, K is set to 0.8 as recommended by (EN ISO 17892-6, 2017).

Figure 11 demonstrates that the undrained shear strength values derived out of FCT are significantly important compared to the measurements yielded by pocket shear vane test. Assuming that the pocket shear vane test provides more appropriate measurements, the RMSE (Root Mean Square Error, as assessed using Equation 2) of 1.6 indicates that the estimated values are significantly high, particularly given the narrow range of undrained shear strength (1 to 33 kPa). This discrepancy as quantified by NRMSE (Normalized Root Mean Square Error,estimated using Equation 3) of 10%, is attributed to the cone factor K, which is typically set at 0.8—a value deemed inappropriate for overconsolidated soils with varied textures.

[TeX:] RMSE = \sqrt{\frac{1}{n}\sum_{i = 1}^{n}\left( A_{i} - B_{i} \right)^{2}}$RMSE=\sqrt{\frac{1}{n}{\sum }_{i=1}^n{(A_i-B_i)}^2}$ (2)

Where:

[TeX:] A_{i}$A_i$- i^th value of derived [TeX:] s_{u}$s_u$by FCT,

[TeX:] B_{i}$B_i$- i^th value of estimated [TeX:] s_{u}$s_u$ by pocket shear vane test,

[TeX:] n$n$- Total of measurements.

[TeX:] NRMSE = \frac{RMSE}{Y_{\max} - Y_{\min}}$NRMSE=\frac{RMSE}{Y_{max}-Y_{min}}$ (3)

Where:

[TeX:] Y_{\max}$Y_{max}$- Maximum value of [TeX:] s_{u}$s_u$ by pocket shear vane test,

[TeX:] Y_{\min}$Y_{min}$- Minimum value of [TeX:] s_{u}$s_u$ by pocket shear vane test.

Figure 11. [TeX:] s_{u}$s_u$ derived by FCT versus pocket shear vane tests.

3.3. Correlation of cone factor with OCR and fines content

As previously observed, FCT significantly overestimates [TeX:] s_{u}$s_u$ values when compared to the pocket shear vane test. To achieve a reliable estimation of this strength, a back-calculation for K factor (see Equation 6) is performed for all mixtures, assuming that [TeX:] s_{u}$s_u$ values estimated by both FCT and pocket shear vane test are equal :

[TeX:] s_{u}(Pocket\ shear\ vane) = s_{u}(Fall\ cone)$s_u\left(Pocketshearvane\right)=s_u\left(Fallcone\right)$ (4)

[TeX:] s_{u}(Pocket\ shear\ vane) = \frac{K\ m\ g}{H^{2}}$s_u\left(Pocketshearvane\right)=\frac{Kmg}{H^2}$ (5)

[TeX:] K = \frac{s_{u}(Pocket\ shear\ vane)\ H^{2}}{m\ g}$K=\frac{s_u\left(Pocketshearvane\right)H^2}{mg}$ (6)

The back-calculation yielded highly dispersed values, as there are six different cone factor values for each overconsolidation ratio depending on the mixture, making interpretation challenging. Therefore, two specific cone factors are defined. On one hand, the average of the cone factors for all mixtures sharing the same OCR is calculated, denoted as [TeX:] K_{OCR}$K_{OCR}$. On the other hand, the average of the cone factors across the entire OCR range is calculated for a given mixture, denoted as [TeX:] K_{Fc}$K_{Fc}$.

[TeX:] K_{OCR}$K_{OCR}$ is plotted against OCR in Figure 12. A strong quadratic correlation is observed across the paired parameters, achieving a very good [TeX:] R^{2}$R^2$ (coefficient of determination) corresponding to 0.977. The expression for the cone factor as a function of the OCR is represented in Equation 7. [TeX:] K_{Fc}$K_{Fc}$ is plotted against the fines content in Figure 13. A good power law correlation is observed among the last enumerated parameters, yielding a [TeX:] R^{2}$R^2$ value of 0.782. The resulting empirical expression for the cone factor as a function of fines content is given in Equation 8.

[TeX:] K_{OCR} = 0.0012{\ OCR}^{2} - 0.0019\ OCR + 0.4864$K_{OCR}=0.0012{OCR}^2-0.0019OCR+0.4864$ (7)

[TeX:] K_{Fc} = 0.0092\ {Fc\ (\%)}^{0.926}$K_{Fc}=0.0092{Fc\left(\%\right)}^{0.926}$ (8)

Figure 12. Cone factor expressed by overconsolidation ratio

Figure 13. Cone factor expressed by fines content (%)

3.4. Application of the proposed cone factors

The evaluation methodology for calculating the undrained shear strength via FCT employed three distinct approaches, incorporating the combinations of [TeX:] K_{OCR}$K_{OCR}$ and [TeX:] K_{Fc}$K_{Fc}$ ; the minimum (K_Min), the maximum (K_Max), and the mean (K_Mean) of the two factors. The FCT calculations for each approach were performed according to Equation 1 for other cone penetration measurements. The results of this comparative assessment are presented in Figure 14, which demonstrates a significant improvement in [TeX:] s_{u}$s_u$ estimation compared to the use of the conventional constant factor (K = 0.8).

Figure 15 shows that the combination utilising the maximum of the two factors (K_Max) yields the lowest RMSE among the other combinations with a value of 0.21. This finding is further validated by the NRMSE, which decreased significantly from 10% for the conventional factor to 1.2%. This outcome clearly validates the reliability and significant predictive accuracy of this combined approach.

Figure 14. Undrained shear strength by fall cone using combined cone factors versus pocket shear vane tests

Figure 15. Root Mean Square Error comparison implementing different cone factors

4. Conclusions

FCT is commonly employed to evaluate the consistency of clayey materials. However, since the late 1950s, scientific studies have increasingly focused on its application to estimate [TeX:] s_{u}$s_u$ for stability analysis. A notable gap in previous existing literature is rooted in the limited research on estimating [TeX:] s_{u}\ $s_u$for consolidated soils with varied textures. This study aims to address this by proposing a simple and rapid method using the fall cone for the estimation of short-term strength parameters for slope stability analysis. To achieve this, a testing program was conducted on specimens composed of clay and sand, consolidated at various overconsolidation ratios. The subsequent inferences were developed based on the observed findings:

This study did not investigate the effects of unloading or, more broadly, changes in the soil's confinement state. Therefore, future research should focus on exploring the influence of soil sensitivity within this framework. Furthermore, while the pocket shear vane test was used to calibrate the cone factor in FCT approach for undrained shear strength estimation, the implementation of CPTU (Cone Penetration Test with pore water pressure measurement) inside the scope of this analysis, is highly recommended for rigorous geotechnical studies. The K_Max combination suggested in this study could be used with reasonable certainty to evaluate [TeX:] s_{u}$s_u$ for slope stability analysis.

References

Abbireddy, C. O. R., Clayton, C. R. I., & Huvenne, V. A. I. (2009). A method of estimating the form of fine particulates. Géotechnique, 59(6), 503–511.https://doi.org/10.1680/geot.2008.p.009

American Society for Testing and Materials. (2017). Standard Practice for Classification of Soils for Engineering Purposes: Unified Soil Classification System (ASTM D2487-17e1). West Conshohocken, PA, USA: Author.

Amri, S., Akchiche, M., Bennabi, A., & Hamzaoui, R. (2019). Geotechnical and mineralogical properties of treated clayey soil with dune sand. Journal of African Earth Sciences, 152, 140–150.https://doi.org/10.1016/j.jafrearsci.2019.01.010

Bhardwaj, A., & Sharma, R. K. (2020). Effect of industrial wastes and lime on strength characteristics of clayey soil. Journal of Engineering, Design and Technology, 18(6), 1749–1772.https://doi.org/10.1108/jedt-12-2019-0350

Brown, P. J., & Huxley, M. A. (1996). The cone factor for a 30° cone. Ground Engineering, 29(12), 34–36.

Cabalar, A. F. (2018). Influence of grain shape and gradation on the shear behavior of sand mixtures. Scientia Iranica, 25(6), 3101–3109.https://doi.org/10.24200/sci.2017.4223

Cabalar, A. F., & Hasan, R. A. (2013). Compressional behaviour of various size/shape sand–clay mixtures with different pore fluids. Engineering Geology, 164, 36–49.https://doi.org/10.1016/j.enggeo.2013.06.011

Cabalar, A. F., Dulundu, K., & Tuncay, K. (2013). Strength of various sands in triaxial and cyclic direct shear tests. Engineering Geology, 156, 92–102.https://doi.org/10.1016/j.enggeo.2013.01.011

Cabalar, A. F., Khalaf, M. M., & Isik, H. (2020). A comparative study on the undrained shear strength results of fall cone and vane shear tests in sand–clay mixtures. Arabian Journal of Geosciences, 13(11), 395.https://doi.org/10.1007/s12517-020-05351-5

Canelas, D., Fernandes, I., & Lopes, M. da G. (2018). Use of Fall Cone Test for the determination of undrained shear strength of cohesive soils. MATEC Web of Conferences, 251, 04067.https://doi.org/10.1051/matecconf/201825104067

Chalabi, Y., Mimoune, A. E. h., Aissaoui, S., Mouaissa, M. S., & Brixi, A. (2024). Soil density effects on compressibility and expansion behavior. Journal of Fundamental and Applied Sciences, 16(3), 229–241.https://doi.org/10.4314/jfas.1378

Chalabi, Y., Reiffsteck, P., & Zadjaoui, A. (2020). Applicability of shansep method in evaluation of preconsolidation pressure. Elektronički časopis građevinskog fakulteta Osijek, 13–24.https://doi.org/10.13167/2020.20.2

Clayton, C. R. I., Abbireddy, C. O. R., & Schiebel, R. (2009). A method of estimating the form of coarse particulates. Géotechnique, 59(6), 493–501.https://doi.org/10.1680/geot.2007.00195

EN ISO 17892-6. (2017). Geotechnical investigation and testing – Laboratory testing of soil – part 6 : Fall cone test (EN ISO) [Standard]. Geneva: Author.

Farias, M. M., & Llano-Serna, M. A. (2016). Simple Methodology to Obtain Critical State Parameters of Remolded Clays Under Normally Consolidated Conditions Using the Fall-Cone Test. Geotechnical Testing Journal, 39(5), 855–864.https://doi.org/10.1520/gtj20150207

Gilboy, G. (1928). The compressibility of sand-mica mixtures. Proceedings of the American Society of Civil Engineers, 555–568.

Gökalp, Z. (2009). Engineering characteristics of sand-clay mixtures used for clay cores of earth-fill dams. Clay Minerals, 44(3), 319–326.https://doi.org/10.1180/claymin.2009.044.3.319

Göktepe, A. B., & Sezer, A. (2010). Effect of particle shape on density and permeability of sands. Proceedings of the Institution of Civil Engineers - Geotechnical Engineering, 163(6), 307–320.https://doi.org/10.1680/geng.2010.163.6.307

Hansbo, S. (1957). A New Approach to the Determination of the Shear Strength of Clay by the Fall-Cone Test (Royal Swedish Geotechnical Institute Proceedings No. 14). Stockholm, Sweden.

Hazell, E. (2008). Numerical and experimental studies of shallow cone penetration in clay (Doctoral thesis). University of Oxford, Oxford.

Houlsby, G. T. (1982). Theoretical analysis of the fall cone test. Géotechnique, 32(2), 111–118.https://doi.org/10.1680/geot.1982.32.2.111

Karlsson, R. (1961). Suggested improvements in the liquid limit test, with reference to flow properties of remoulded clays. In Proceedings of the Fifth International Conference on Soil Mechanics and Foundation Engineering. Paris, France.

Koumoto, T., & Houlsby, G. T. (2001). Theory and practice of the fall cone test. Géotechnique, 51(8), 701–712.https://doi.org/10.1680/geot.51.8.701.40475

Kyambadde, B. S. (2010). Strength and Consistency Limits from Quasi-Static Cone Tests (Doctoral dissertation). University of Brighton, Brighton.

Lees, G. (1964). A new method for determining the angularity of particles. Sedimentology, 3(1), 2–21.https://doi.org/10.1111/j.1365-3091.1964.tb00271.x

Llano-Serna, M. A., & Contreras, L. F. (2020). The effect of surface roughness and shear rate during fall-cone calibration. Géotechnique, 70(4), 332–342.https://doi.org/10.1680/jgeot.18.p.222

Llano-Serna, M. A., Farias, M. M., Pedroso, D. M., Williams, D. J., & Sheng, D. (2018). Considerations on the Experimental Calibration of the Fall Cone Test. Geotechnical Testing Journal, 41(6), 1131–1138.https://doi.org/10.1520/gtj20170205

Louafi, B., & Bahar, R. (2012). SAND: An Additive for Stabilzation of Swelling Clay Soils. International Journal of Geosciences, 3(4), 719–725.https://doi.org/10.4236/ijg.2012.34072

Malki, K., & Abed, Y. (2024). Liquid limit determination of medium to high plasticity Algerian soils using fall-cone vs Casagrande percussion cup methods. Acta Geodynamica et Geomaterialia, 21(1), 121–130.https://doi.org/10.13168/agg.2024.0011

Marušić, D., & Jagodnik, V. (2023). Determination of the Atterberg limits using a Fall cone device on low plasticity silty sands. Rudarsko-Geološko-Naftni Zbornik, 38(3), 133–145.https://doi.org/10.17794/rgn.2023.3.11

Marušić, D., & Jagodnik, V. (2025). Atterberg limits determination and soil classification using Fall cone device on the silty sands and sandy silts. International Journal of Geotechnical Engineering, 19(1–3), 78–87.https://doi.org/10.1080/19386362.2025.2454655

Meddah, A., Goufi, A. E., & Pantelidis, L. (2022). Improving Very High Plastic Clays with the Combined Effect of Sand, Lime, and Polypropylene Fibers. Applied Sciences, 12(19), 9924.https://doi.org/10.3390/app12199924

Medhat, F., & Whyte, I. L. (1986). An Appraisal of Soil Index Tests. Geological Society, London, Engineering Geology Special Publications, 2(1), 317–323.https://doi.org/10.1144/gsl.1986.002.01.55

Niazi, F. S., Pinan-Llamas, A., Cholewa, C., & Amstutz, C. (2019). Liquid limit determination of low to medium plasticity Indiana soils by hard base Casagrande percussion cup vs. BS fall-cone methods. Bulletin of Engineering Geology and the Environment, 79(4), 2141–2158.https://doi.org/10.1007/s10064-019-01668-y

Nini, R. (2014). Effect of the silt and clay fractions on the liquid limit measurements by Atterberg cup and fall cone penetrometer. International Journal of Geotechnical Engineering, 8(2), 239–241.https://doi.org/10.1179/1939787913y.0000000018

Olson, R. E., & Mesri, G. (1970). Mechanisms Controlling Compressibility of Clays. Journal of the Soil Mechanics and Foundations Division, 96(6), 1863–1878.https://doi.org/10.1061/jsfeaq.0001475

Qusai, A., Szendefy, J., & Vásárhelyi, B. (2025). Effect of Changing Sand Content on Liquid Limit and Plasticity Index of Clay. Geotechnics, 5(1), 4.https://doi.org/10.3390/geotechnics5010004

Sharma, B., & Bora, P. K. (2003). Plastic Limit, Liquid Limit and Undrained Shear Strength of Soil—Reappraisal. Journal of Geotechnical and Geoenvironmental Engineering, 129(8), 774–777.https://doi.org/10.1061/(asce)1090-0241(2003)129:8(774)

Shimobe, S. (2010). Determination of index properties and undrained shear strength of soils using the fall cone test. In Proceedings of the 7th International Symposium on Lowland Technology (pp. 51–59). Saga University.

Shimobe, S., & Spagnoli, G. (2019). Some relations among fall cone penetration, liquidity index and undrained shear strength of clays considering the sensitivity ratio. Bulletin of Engineering Geology and the Environment, 78(7), 5029–5038.https://doi.org/10.1007/s10064-019-01478-2

Shimobe, S., & Spagnoli, G. (2020). Fall cone tests considering water content, cone penetration index, and plasticity angle of fine-grained soils. Journal of Rock Mechanics and Geotechnical Engineering, 12(6), 1347–1355.https://doi.org/10.1016/j.jrmge.2020.02.005

Sivakumar, V., O’Kelly, B. C., Henderson, L., Moorhead, C., & Chow, S. H. (2015). Measuring the plastic limit of fine soils: an experimental study. Proceedings of the Institution of Civil Engineers - Geotechnical Engineering, 168(1), 53–64.https://doi.org/10.1680/geng.14.00004

Spagnoli, G. (2012). Comparison between Casagrande and drop-cone methods to calculate liquid limit for pure clay. Canadian Journal of Soil Science, 92(6), 859–864.https://doi.org/10.4141/cjss2012-011

Stróżyk, J., & Tankiewicz, M. (2013). Undrained shear strength of the heavily consolidated clay. Annals of Warsaw University of Life Sciences - SGGW Land Reclamation, 45(2), 207–216.https://doi.org/10.2478/sggw-2013-0017

Tanaka, H., Hirabayashi, H., Matsuoka, T., & Kaneko, H. (2012). Use of fall cone test as measurement of shear strength for soft clay materials. Soils and Foundations, 52(4), 590–599.https://doi.org/10.1016/j.sandf.2012.07.002

Terzaghi, K. (1925). Erdbaumechanik auf bodenphysikalischer grundlage. Deuticke.

Terzaghi, K., & Peck, R. B. (1967). Soil mechanics in engineering practice (2nd ed.). John Wiley & Sons.

Vardanega, P. J., Haigh, S. K., & O’Kelly, B. C. (2022). Use of fall-cone flow index for soil classification: a new plasticity chart. Géotechnique, 72(7), 610–617.https://doi.org/10.1680/jgeot.20.p.132

Vardanega, P. J., O’kelly, B. C., Haigh, S. K., & Shimobe, S. (2018). Classifying and characterising fine‐grained soils using fall cones. ce/papers, 2(2–3), 821–826.https://doi.org/10.1002/cepa.772

Wood, D. M. (1982). Cone penetrometer and liquid limit. Géotechnique, 32(2), 152–157.https://doi.org/10.1680/geot.1982.32.2.152

Wood, D. M. (1985). Some fall-cone tests. Géotechnique, 35(1), 64–68.https://doi.org/10.1680/geot.1985.35.1.64

Wood, D. M., & Wroth, C. P. (1978). Use of the cone penetrometer to determine the plastic limit of soils. International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, 15(3), 51.https://doi.org/10.1016/0148-9062(78)90033-5

Wroth, C. P., & Wood, D. M. (1978). The correlation of index properties with some basic engineering properties of soils. Canadian Geotechnical Journal, 15(2), 137–145.https://doi.org/10.1139/t78-014

Zeng, X., Li, Y., Liu, X., Yao, J., & Lin, Z. (2020). Relationship between the Shear Strength and the Depth of Cone Penetration in Fall Cone Tests. Advances in Civil Engineering, 2020, 8850430.https://doi.org/10.1155/2020/8850430

Author’s contribution

Youssouf Chalabi (PhD, Associate Professor) defined the overarching research objectives through conceptualisation and designed the specific experimental and analytical framework, alongside conducting the laboratory testing and interpretation. Soufyane Aissaoui (PhD, Associate Professor) provided essential equipment and materials, contributed to investigation through meticulous sample preparation, and provided critical intellectual feedback during writing—review & editing. Abdeldjalil Zadjaoui (Full Professor) was responsible for data curation, performed the formal analysis of the experimental results, and contributed to the critical review process. Sidi Mohammed Aissa Mamoune (Full Professor) managed secondary data curation and generated the initial manuscript draft.

All authors have read and agreed to the published version of the manuscript.