Analysis of void space
As noted above, previous researchers have carefully considered how to calculate e in gap-graded materials. The relationship between \({\hbox {F}}_\mathrm{fine}\) and e is presented for each \(\chi \) value in Fig. 2. For the \({\hbox {F}}_\mathrm{fine}\) values presented here there is little overall variation of e with \({\hbox {F}}_\mathrm{fine }\)for a given size ratio. For each \(\chi \) a minimum void ratio can be identified \(({\hbox {e}}_\mathrm{min})\) and the \({\hbox {F}}_\mathrm{fine}\) at which \({\hbox {e}}_\mathrm{min}\) is obtained decreases with increasing \(\chi \), in agreement with experimental observations [18].
McGeary [28] carried out experiments on bimodal mixtures of glass beads with \({\hbox {F}}_\mathrm{fine}\) varying between 10 and 50 % to investigate the maximum densities that could be obtained; the data from these experiments was considered by Lade et al. [18]. The \({\hbox {e}}_\mathrm{min}\) values for each \(\chi \) value observed in Fig. 2 are compared with the experimental data in Fig. 3. There is good agreement between the simulations and experiments, although the DEM data give a slightly denser packing at a given \(\chi \). This observed difference is to be expected as the DEM particles are perfectly spherical and frictionless (during the isotropic compression stage); physical glass ballotini deviate from this ideal [29]. As \(\chi \) increases, the rate at which \({\hbox {e}}_\mathrm{min}\) decreases reduces. Lade et al. [18] concluded the relationship had a bi-linear shape, with a distinct change in the gradient of the experimental data at \(\chi \approx 6.5\). The DEM data show a reduction in the gradient of the \({\hbox {e}}_\mathrm{min}-\chi \) plot with increasing \(\chi \), but the relationship does not replicate the distinct bi-linear shape attributed to the experimental data.
Lade et al. [18] hypothesized that the change in gradient of the \({\hbox {e}}_\mathrm{min}-\chi \) plot at \(\chi \approx 6.5\) occurs because the fines pack more efficiently between the coarse particles when the size ratio increases, as illustrated schematically in Fig. 1. The void sizes between the coarse particles for the bimodal materials with \({\hbox {F}}_\mathrm{fine}>0\) were determined by considering only the coarse particles in void partitioning. Voids were identified using the Delaunay method proposed by Reboul et al. [30], which considers a void to be defined by the tetrahedra formed by a Delaunay tessellation of particle centers, as shown schematically in Fig. 4. The diameter (size) of a void, \({\hbox {D}}_\mathrm{void}\), is defined by the largest sphere which can be inscribed between the particles forming the tetrahedra. The resultant coarse particle void size distributions (VSDs) for four bimodal samples are given on Fig. 5. Figure 5 also includes the VSD for the monodisperse sample and these data agree with that of Bryant et al. [31] for a similar analysis of monodisperse spheres. The binary samples contain only 100 coarse particles and therefore have a less smooth distribution than the monodisperse sample, which contains 600 particles. Analytically known values of \({\hbox {D}}_\mathrm{void}\) for regular packings of monodisperse spheres (close-packed cubical/hexagonal, body-centred cubical/tetragonal and orthorhombic) are also included for reference.
The smallest voids in the monodisperse random packing are \({\hbox {D}}_\mathrm{void}=0.2245 \,{\hbox {D}}_\mathrm{coarse}\), which is equal to the minimum void between the densest possible regular packings (close-packed cubical and hexagonal). However, the majority of the voids are larger than this, with most (\(\sim \)70 %) falling within the range of \({\hbox {D}}_\mathrm{void}=0.3{-}0.5\,{\hbox {D}}_\mathrm{coarse}\). 15 % of the voids have \({\hbox {D}}_\mathrm{void} > 0.5\,{\hbox {D}}_\mathrm{coarse}\). When \(\chi =2, {\hbox {D}}_\mathrm{fine}=0.5 {\hbox {D}}_\mathrm{coarse}\), and therefore \({\hbox {D}}_\mathrm{fine} > {\hbox {D}}_\mathrm{void}\) for the majority of the voids, meaning that the fines will not be able to sit between the coarse particles under reduced stress, confirming that materials with \(\chi = 2\) should not be considered to be gap-graded. As \(\chi \) increases, \({\hbox {D}}_\mathrm{fine} < {\hbox {D}}_\mathrm{void}\) meaning single fines and groups of fines are able to fit more efficiently within voids. When the gap-ratio is large \((\chi =10)\) and \({\hbox {F}}_\mathrm{fine} \approx S^*\,({\hbox {F}}_\mathrm{fine}= 25\,\%)\) the void size distribution is similar to the sample containing no fines indicating that the coarse particles form a dense network very similar to that if there were no fines present.
Contact density
The extent to which the finer particles carry a reduced stress, i.e. the \(\alpha \) value, is influenced by the contact network, and the connectivity (i.e. number of contacts per particle) of the finer particles. Pinson et al. [19] identified contacts between coarse and fine particles in bimodal packings of spheres with \(\chi = 2\) and 4 using a liquid bridge technique. The resultant connectivity data can be compared with the DEM data generated in this study. The DEM samples are somewhat denser than the experimental samples. However, while the experimental void ratio was measured for the whole sample, connectivity was measured away from the sides of the container in order to avoid wall effects and therefore void ratio is probably overestimated in the experiments.
The distributions of connectivity for \(\chi = 2\) and 4 are given in Fig. 6. Figure 6a, b give the connectivity for fine to fine \(({\hbox {C}}^\mathrm{fine-fine})\) and fine to coarse \(({\hbox {C}}^\mathrm{fine-coarse})\) contacts respectively for \(\chi = 2\) and \({\hbox {F}}_\mathrm{fine} = 25\), 30 and 35 % for the DEM simulations. Equivalent data for \(\chi = 4\) are presented in Fig. 6c, d. For both \(\chi \) values experimental data are included in the figures; for \(\chi = 2\) the experimental data considers \({\hbox {F}}_\mathrm{fine}=28\,\%\), while experimental data for \({\hbox {F}}_\mathrm{fine}=28\) and 50 % were available for \(\chi = 4\). In all cases the experimental and DEM data show the same upper limits to the distribution of connectivities and the proportions of particles with 0 contacts are broadly similar for equivalent \({\hbox {F}}_\mathrm{fine}\) values. For \(\chi =2\) the experimental \({\hbox {C}}^\mathrm{fine-fine }\) distribution with \({\hbox {F}}_\mathrm{fine}=28\,\%\) is similar to the DEM distributions for \({\hbox {F}}_\mathrm{fine} = 30\) and 35 % (Fig. 6a), although the experimental data has a greater proportion of particles with C\(^\mathrm{fine-fine} > 4\) and fewer with \({\hbox {C}}^\mathrm{fine-fine} = 0\). The DEM sample with \({\hbox {F}}_\mathrm{fine}=25\,\%\) shows fewer fine to fine contacts per particle, specifically there are many more particles with \({\hbox {C}}^\mathrm{fine-fine}=0\) in this sample. The particles with \({\hbox {C}}^\mathrm{fine-fine}=0\) are likely to be either trapped between two coarse particles or isolated within the voids between the coarse particles. As shown in Fig. 6b, the experimental and DEM distributions of \({\hbox {C}}^\mathrm{fine-coarse}\) show good agreement for all three DEM samples despite the difference in void ratio.
As shown in Fig. 6c, for \(\chi =4,\,{\hbox {C}}^\mathrm{fine-fine}\) increases as \({\hbox {F}}_\mathrm{fine}\) attains and then exceeds the critical fines content at which the fines fill the voids. For \({\hbox {F}}_\mathrm{fine} = 50\,\%\), the \({\hbox {C}}^\mathrm{fine-fine}\) distributions are very similar for both experimental and DEM data. While the DEM data for \({\hbox {F}}_\mathrm{fine}=25\,\%\) and \({\hbox {F}}_\mathrm{fine} = 30\,\%\) show far fewer fine to fine contacts per particle than the experimental data for \({\hbox {F}}_\mathrm{fine}= 28\,\%\), there is a close agreement between the experimental data for \({\hbox {F}}_\mathrm{fine}=28\,\%\) and the DEM data for \({\hbox {F}}_\mathrm{fine} =35\,\%\).
As well as looking at the connectivity data, it is useful to consider the overall coordination number, given as :
$$\begin{aligned} Z=2N_c /N_p \end{aligned}$$
(7)
where \({\hbox {N}}_\mathrm{c}\) is the number of interparticle contacts in the system and \({\hbox {N}}_\mathrm{p}\) is the number of particles in the system. Figure 7a and Table 2 show the variation of Z with \(\chi \) and \({\hbox {F}}_\mathrm{fine}\) for each of the samples. For \({\hbox {F}}_\mathrm{fine}= 20\,\%\) there is a steep reduction from Z = 5.04 at \(\chi = 2\) to Z = 0.17 at \(\chi = 6\). In the DEM data Z < 1 is possible as gravity has been neglected. In a bimodal material the number of fine particles far exceeds the number of coarse particles, even when accounting for only a fraction of the total volume (when \(\chi = 10\), one coarse particle has the same volume as 1000 fine particles). This means that the coordination number is largely determined by contacts involving the fines. The reduction of Z between \(\chi = 2\) and \(\chi = 6\) for the \({\hbox {F}}_\mathrm{fine} = 20\,\%\) material is evidence that the fines transition from being well connected to being predominantly unconnected and non-stress transmitting. This supports the argument of Lade et al. [18] that as \(\chi \) increases, fines are better able to fit within voids and so play a reduced role in stress transfer.
For \({\hbox {F}}_\mathrm{fine} \ge 25\,\%\) there is little variation of Z with \(\chi \). This is because the fines completely fill the voids between the coarse particles and so have many interparticle contacts, regardless of \({\hbox {F}}_\mathrm{fine}\) or \(\chi \). With reference to Skempton and Brogan [4], for materials at their highest relative density, the critical fines content S* at which fines just fill the voids between coarse particles occurs at \({\hbox {F}}_\mathrm{fine} \approx 24\,\%\) and can be identified by an increase in Z with \({\hbox {F}}_\mathrm{fine}\).
Stress reduction in finer particles, \(\alpha \).
Figure 7b and Table 2 show the variation of the stress-reduction factor, \(\alpha \), with \(\chi \) and \({\hbox {F}}_\mathrm{fine}\). In samples with \({\hbox {F}}_\mathrm{fine} \ge 30\,\%, \alpha \approx 1\), indicating that the coarse and fine particles contribute approximately equally to stress transfer. The same is true of samples with \(\chi = 2\) regardless of \({\hbox {F}}_\mathrm{fine}\), as the fines are unable to completely fit within the voids. For samples with \({\hbox {F}}_\mathrm{fine} = 20\,\%\) and \(\chi \ge 6, \alpha \approx 0\) and the fines are completely loose within the voids and play almost no role in stress transfer, hence \({\hbox {F}}_\mathrm{fine}< S^*\).
For the samples at \({\hbox {F}}_\mathrm{fine} = 25\,\%\), which is just above the critical fines content S*, \(\alpha \) reduces steeply with increasing \(\chi \). Comparing Fig. 7a, b, it can be seen that for \({\hbox {F}}_\mathrm{fine} = 25\,\%, \alpha \) falls rapidly with \(\chi \), whereas Z does not. This supports the hypothesis that although fines are not carrying the same proportion of stress as the coarse particles, they are still in contact with the coarse particles and therefore forming weak lateral force chains to support the main strong force chains [6, 32]. Although these fines are under low stress, they still perform an important supporting role to the more highly stressed particles and their removal, for example due to internal instability under seepage, could lead to the collapse of the stress-transferring matrix [6, 32].
Figure 8a shows the relationship between the stress-reduction factor, \(\alpha \), and the coarse to coarse coordination number, \({\hbox {Z}}^\mathrm{coarse-coarse}\) [33]:
$$\begin{aligned} Z^\mathrm{coarse-coarse}=2\left( {N_\mathrm{c,coarse-coarse} } \right) /N_\mathrm{p,coarse} \end{aligned}$$
(8)
where \(N_\mathrm{c,coarse-coarse }\)is the number of contacts between coarse particles, and \(N_\mathrm{p,coarse}\) is the number of coarse particles.
The value \({\hbox {Z}}^\mathrm{coarse-coarse}< 4\) has been highlighted on Figure 8a, as when \(Z^\mathrm{coarse-coarse }< 4\) coarse particles cannot be considered to be forming a mechanically stable matrix on their own and must therefore be separated from one another by fines (i.e. be overfilled). Figure 8a shows that the fine and coarse particles carry approximately equal stress (i.e. \(\alpha \approx 1\)) in every sample with \({\hbox {Z}}^\mathrm{coarse-coarse}< 4\), confirming the hypothesis that overfilled samples must be internally stable. The stress-reduction \(\alpha \) values drop rapidly as \({\hbox {Z}}^\mathrm{coarse-coarse}\) increases beyond 4 and the coarse particles are able to form a stress-transmitting primary matrix, leaving fines transmitting little stress.
Figure 8b, considers the relationship between \(\alpha \) and the skeleton void ratio, e\(_\mathrm{sk}\) (Eq. 1). When \({\hbox {e}}_\mathrm{sk} \ge {\hbox {e}}_\mathrm{coarse,max}\), the experimental maximum void ratio for monodispersed spheres alone [34], the coarse particles must be separated from one another by fine particles and \(\alpha \approx 1\). The \({\hbox {e}}_\mathrm{sk} = {\hbox {e}}_\mathrm{coarse,max}\) condition was termed the limit void ratio by Salgado et al. [1]. who found a distinct change in the stress-strain response of silty sands when this was exceeded. Considering effective stress transfer, when \({\hbox {e}}_\mathrm{sk} < {\hbox {e}}_\mathrm{coarse,max}\) the coarse particles must be in contact with one another and therefore dominate stress transfer, as shown by \(\alpha < 1\). This effect becomes more prominent as \({\hbox {e}}_\mathrm{sk}\) reduces further below \({\hbox {e}}_\mathrm{coarse,max}\). Considering both Fig. 8a and b, it is clear that even at low fines contents (20 %) samples with \(\chi = 2\) cannot form a stable fabric comprised of coarse particles alone, whereas samples with \(\chi = 4\) form an intermediate fabric in which the coarse particles transfer more stress than fine.
As noted above the void size distributions (Fig. 5) suggest that for large \(\chi \) values and when \({\hbox {F}}_\mathrm{fine} \approx {\hbox {S}}^*\) (i.e. \(\chi = 10\) and \({\hbox {F}}_\mathrm{fine}=25\,\%)\), the coarse matrix is similar to a monodisperse material. This is confirmed by the very low stress in the fines (\(\alpha = 0.09)\). The high coordination number (Z \(=\) 5.35), suggests that this is just at the point where the fines fill the voids. As \({\hbox {F}}_\mathrm{fine}\) increases to 30 % the void diameters between the coarse particles increase noticeably as fines begin to separate them and the stress in the fines also increases to \(\alpha = 1.02\). For the samples with \(\chi = 2\) the coarse voids are significantly larger because, as discussed in Sect. 3.2, the fines are larger than the majority of the voids in the monodisperse sample. For these samples \(\alpha \approx 1\).
Thornton and Antony [17] showed that columns or chains of “strong” contact forces (i.e. forces of above average magnitude) transfer almost all the deviatoric load through granular materials. It is therefore reasonable to take the probability of a fine particle forming part of a strong force chain, \({\hbox {P}}{\hbox {(strong)}}_\mathrm{fine}\) as an indicator of the extent to which the finer particles form part of the load-transferring matrix. For internal instability to occur the load-transferring matrix should be formed predominantly of coarse particles. Therefore the greater the extent to which the fines contribute to the load-transferring matrix, the higher the internal stability of the soil will be.
The variation of \({\hbox {P}}{\hbox {(strong)}}_\mathrm{fine}\) with \(\chi \) and \({\hbox {F}}_\mathrm{fine}\) is shown in Fig. 9. The pattern is similar to the relationship between \(\alpha , \chi \) and \({\hbox {F}}_\mathrm{fine}\) presented in Fig. 7b, where for \({\hbox {F}}_\mathrm{fine} \ge 30\,\%, {\hbox {P}}{\hbox {(strong)}}_\mathrm{fine} > 0.5\) and therefore fines play a significant role in supporting the fabric of the samples. For samples with \({\hbox {F}}_\mathrm{fine} \le 25\,\%, {\hbox {P}}{\hbox {(strong)}}_\mathrm{fine}\) reduces with increasing \(\chi \) as the fines are able to fit more efficiently in the voids and so are less likely to interact with the coarse particles, which dominate the strong force chains (for each sample the probability of a coarse particle forming part of a strong force chain is greater than 80 %).
This supports the hypothesis of Rahman et al. [22] that the role which cohesionless fines play in stress transfer diminishes with both \(\chi \) and \({\hbox {F}}_\mathrm{fine}\) when \({\hbox {F}}_\mathrm{fine} < {\hbox {S}}^*\), (they refer to a threshold fines content equivalent to S*). For soils with \(\chi = 2\) the concept of a threshold fines content has little meaning. For soils with \(\chi \ge 4\) care must be taken in defining this threshold content—when \({\hbox {F}}_\mathrm{fine} < {\hbox {S}}^*\) the role of the fines is primarily dependent on \(\chi \), in particular for the range \(4< \chi < 6\). However, for \({\hbox {S}}^*< {\hbox {F}}_\mathrm{fine} < {\hbox {S}}_\mathrm{max}\) the fines play a lesser role in stress transfer and this is dependent on both \(\chi \) and \({\hbox {F}}_\mathrm{fine}\) as shown in Fig. 9 for \({\hbox {F}}_\mathrm{fine} = 25\,\%\). An added complication is also that the values of S* and \({\hbox {S}}_\mathrm{max}\) are density-dependent [6].