Evidences of the Influence of Particle Size on the Incidence of Micro-Fractures in Blast-Conditioned Rock

Introduction

Figure 3. Reduction ow the W.I. of blasted rock at the increase of the specific explosive charge. At laboratory scale. (Analysis of data by [21,25,26]).

Figure 3. Reduction ow the W.I. of blasted rock at the increase of the specific explosive charge. At laboratory scale. (Analysis of data by [21,25,26]).

Materials and Methods

Point Load Tests

Point Load Strength Test

The point load strength test is used to estimate the σc of rocks without having to prepare perfectly machined cylindrical samples. Irregular fragments have been used to perform this test and the indications of [27] have been followed. The geometric conditions that this test must meet for each fragment are that the cross-sectional area is greater than 500 mm², the relationship between the distance D and the width of the cross section W is between 0.3 and 1 (0.3<D/W<1) and that the distance from the point of application of the load to the free face in a direction perpendicular to the cross section is greater than half of D (L>0.5 D), as shown in Figure 3.

Figure 3. Condiciones geométricas de los fragmentos de roca para el ensayo de fragmentos irregulares (ISMR, 2007).

Figure 3. Condiciones geométricas de los fragmentos de roca para el ensayo de fragmentos irregulares (ISMR, 2007).

The procedure for estimating σ_c consists of calculating the corrected point load index, Is (50) (Equation 1) and multiplying it by a factor F that varies between 0 and 1 (Equation 2). To determine the value of the factor F, the Brook size correction (1985) was used using equations 3 and 4.

$${\mathrm{I}}_{\mathrm{s}\left(50\right)}={10}^3·{\displaystyle \frac{P}{D_e^2}}$$

(1)

$${\mathsf{\sigma }}_{\mathrm{c}}=22,6·\mathrm{F}·{\mathrm{I}}_{\mathrm{s}\left(50\right)} \mathrm{where}0\le \mathrm{F}\le 2$$

(2)

$${\mathrm{T}}_{500}=211,5·{\displaystyle \frac{\mathrm{P}}{{\mathrm{A}}^{0,75}}}$$

(3)

$$3{\mathsf{\sigma }}_{\mathrm{c}}=12,5·{\mathrm{T}}_{500}4$$

(4)

where I_{s (50)} is the corrected point load index (MPa), P is the breaking load (kN), De the equivalent diameter of the fragment (mm), T500 is the point load index (MPa), A the area of the loaded section (mm2) and L the distance between the contact points and the free face in a direction perpendicular to the cross section (mm).

Samples for Point Load Tests

To begin with, rock fragments were collected from the debris produced by two different blasts carried out inside the site. These fragments were prepared so that they had flat faces. For this, the Controls Group cutting saw was used, thus providing a better contact surface at the loading points. In addition, the size of the fragment was regulated so that it could be tested. The samples were classified according to the blast with the following nomenclature:

• First blast (T1)
• Second blast (T2)

A total of thirty-one samples were obtained for the first blast (T1) and thirty samples for the second blast (T2).

To obtain the load that the fragments can withstand, it was used a Franklin press (Digital Rock Strength Index Apparatus from the Controls Group brand). The sample must be placed with high precision between the two conical tips to ensure that the load is applied in the center. The conical tips exert pressure by pumping from the hydraulic jack. This equipment has sensors that record oil pressure. The results obtained can be viewed on a real-time digital screen, which are stored for later analysis. The pressure is applied until the sample fractures and the digital screen stops the test, triggering an alarm indicating that the breaking force has been found. To validate the test, the breaking conditions of the samples were observed. Those samples that break in one or two breaking planes were considered valid, as shown in Figure 4.

Both regular-shaped samples and irregular ones of different sizes were used.

Results of Point Load Tests

Figure 5 and Figure 6 show the graphs of resistance to simple compression Vs. respect to the mass of the samples for blast 1 and blast 2. It is evident the lack of correlation.

Work Index Tests

Work Index of Material, Work Index (Wi)

This is the value calculated in kWh/t required to reduce a material of infinite particle size by 80% passing 100 microns, which is approximately equivalent to 65% passing 200 mesh. This index establishes the relative resistance to reduction of a material within the range of sizes tested, as well as the relative mechanical efficiencies of different machines and processes. It can be determined from any commercial or laboratory operation where the applied work and the size distribution of the feed material and the product are known (Bond F. C, 1952). The following equation is used for its calculation:

$$Wi={\displaystyle \frac{44.5}{{(Pi)}^{0.23}*Gb{p}^{0.82}*\left(\frac{10}{P80}-\frac{10}{F80}\right)}}$$

(1)

Pi: Sieve mesh through which 100% of the product's weight passes

P80: Sieve mesh through which 80% of the product's weight passes

F80: Sieve mesh through which 80% of the product's weight passes

Gbp: Grindability index in g/revolutions for the considered cut-off mesh

Specific Energy Consumption, W

This is the work or energy applied, expressed in kW-h per short ton, to a machine that reduces material from a defined feed size to a defined product size [22]. Its calculation is as follows:

$$W=Wi*10*\left({\displaystyle \frac{1}{P80}}-{\displaystyle \frac{1}{F80}}\right)\left({\displaystyle \frac{Kwh}{TonC}}\right)$$

(2)

Wi: SPecific Work Index of the material being grinded.

P80: Sieve mesh through which 80% of the product's weight passes

F80: Sieve mesh through which 80% of the product's weight passes

Material and mMethods for W.I.

The rock fragments collected for this part of the study come from a single blast. Fragments were classified into four groups according to size:

• Group 1 and 2: quartered from a particle size fraction 5cm<D<20cm
• Group 3 and 4: quartered from a particle size fraction 20cm<D<25cm

Each of the group of fragments corresponded to an amount of about 10 kg of material, considered representative. Then, all the groups were crushed separately, to obtain a particle size of the fragments finer than 6#. The 10 kg of each sample were homogenized and quartered into 20 sub-samples through a rotary sampler, as can be seen in Figure 7.

Then, one of the sub-samples is subjected to a granulometric analysis with a series of Tyler mesh sieves. This analysis is performed with the following mesh sizes: 8#, 14#, 20#, 30#, 40#, 50#, 70#, 100#, 140#, 200#, 325#, -325#.

To obtain the work index values, tests must be carried out in the bond mill (Figure 8).

An average of fragments size is considered for each group to generate the correlation shown in the graph of Figure 9. For groups one and two, a value of 12.5 cm was averaged, since the sizes of their fragments range from 5 to 20 cm, for groups three and four, a value of 22.5 cm was averaged, since the sizes range from 20 to 25 cm.

It appears to be a correlation between the average size of the fragments and the specific energy consumption, since the larger the fragments, the greater the amount of energy needed to reduce their size.

Microscope Analysis

a)

Fracture Density

Fracture density is the number of fractures in a given area. For practical cases:

$${\displaystyle \frac{\mathrm{Nro}\mathrm{deNumber}\mathrm{of}\mathrm{fracNumber}\mathrm{of}\mathrm{fractures}}{\mathrm{Selected}\mathrm{areaa}}}\left[{\displaystyle \frac{\mathrm{Fractures}}{{\text{µ}\mathrm{m}}^2}}\right]$$

(1)

b)

Diameter of the visual field of the Microscope

The actual diameter of the observed surface is calculated by dividing the diameter of the field of view by the magnification of the objective and eventually by the tube factor, where the formula is:

$${\mathrm{D}}_{\mathrm{FV}}={\displaystyle \frac{\mathrm{FN}}{{\mathrm{M}}_{\mathrm{O}}{*\mathrm{M}}_{\mathrm{T}}}}$$

(2)

$D_{\mathit{FV}}$: Diameter of the visual field in the plane of the specimen.

$FN$: Field number in millimeters.

$M_O$: Objective lens zoom.

$M_T$: Tube lens magnification factor.

c)

Samples

The samples come from the same blast of the previous experiments. Approximately five kilograms of samples were collected, then sieved, starting # 4 to # 325.

Once the samples have been separated by size, four mesh sizes are selected (Figure 10).

In order to carry out a correct observation under the microscope, the selected samples must be placed in polished briquettes. In this case, the MAINI® scientific team helped to create four polished briquettes reassociated with each selection mesh..

Figure 11. Polished briquettes for each sample.

Figure 11. Polished briquettes for each sample.

The polished briquettes are placed in a MCS-IM100 Microscope, obtaining images like the one of Figure 12. Between 4 and 5 images are necessary for each zoom and for each mesh sample to be representative, for a total of 26 pictures taken.

Once the images required for the study have been obtained, the diameter of the visual field is calculatedaccordin to Equation 2, giving the results as diameters expressed in Table 4. Figure 13 shows an example of a visual diameter with scale.

Subsequently, it is determined the area of ​​the mineral particles observed in the images. The area corresponds to the maximum width by the length of particle in the sample: this is a way of standardizing the calculation of the area for all the samples.

Figure 14. Representation of the calculation of the area of ​​each sample.

Figure 14. Representation of the calculation of the area of ​​each sample.

Results from Microscope Analysis

Figure 15 show a typical result observed: the presence of a net of induced discontinuities (microfractures), which are not typical of the mineral. This was the case for all sample sizes.

Figure 16, Figure 17, Figure 18 and Figure 19 show the correlation sample size vs. number of fractures for each microscope lens zoom.

It appears to exist a correlation between particle size and the density of microfractures. The tendency is visible until the 20x zoom. The most evident is at the 10x zoom. In the largest zoom increment, one loses the perception of special distribution of fractures. Further studies will analyze more samples to address the influence of the zoom-size of visual field effect on the measurements.

Discussions

Conclusions

References

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