# Rock Type Effects on Radio Signal Attenuation

Authors: Kai Kordelin; Johanna Virkki; Jaana Kordelin; Juhani Norokallio; Jari Heikkinen; Jyrki Liimatainen; Leena Ukkonen; Lauri Sydänheimo
Journal: International Journal of Geophysics
 (2023)

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## Abstract

This research work is aimed at studying different rock types and the effect of their mineral contents on an active 434 MHz RFID card’s radio signal attenuation. This research was done at the ONKALO nuclear waste storage facility using radio frequency identification (RFID) equipment. First, the studied area and research plan, including the used system and equipment, are explained. After this, the researched areas of rock types and their effects on radio signals are presented. This work focused mainly on occupational safety, but it also investigated whether it would be possible to use RFID technology in producing mines as well, especially in the boundary layer of the ore body. This research can help the design of communication frequencies for autonomous devices.


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## Body

## 1. Introduction

Today, companies are increasingly investing in occupational safety. From the point of view of occupational safety, it is important to know where people are working. Mines and other underground worksites have various solutions for monitoring persons. At first, Posiva used a so-called washer board (Figure1). The washer board was used to know how many people there are in ONKALO. Each person working in the tunnel had a hook with their name on the washer board. On the hook, they put a washer every time they went to ONKALO and took it out when they left ONKALO [1]. The problem with the washer board is that it is based on worker activity. From the point of view of occupational safety, an automatic system independent of personal activities is safer.Figure 1
Washer board [1].Posiva Oy is an expert organization in environmental technology, established in 1995, and the leading final disposal operator in the world. Posiva is preparing to start 2020’s final disposal of spent nuclear fuel in the ONKALO facility excavated deep in the bedrock. ONKALO’s layout and study area are shown in Figure2. Posiva is tasked with handling the final disposal of the spent nuclear fuel generated by its owners because Finnish law states that nuclear waste producers are responsible for all nuclear waste management measures and costs [2].Figure 2
Study area at the ONKALO tunnel system.This research was done at the ONKALO nuclear waste final storage facility [2, 3]. In other studies, signal attenuation has been studied, and measurements have been made in different environments, concrete tunnels, coal mines with rock dust and shotcrete, with and without conductive mesh, and hard rock mines [4–6]. Our previous study studies the effects of bedrock-sprayed concrete mixture that includes stainless steel fibers on antenna reading areas. During this study, it was found that the minerals in the bedrock affected the reading areas [7].Studies are being conducted to gain experience in the reliability of various systems. From the point of view of occupational safety, it is necessary to know what things can impair the readability of the system. This study is aimed at finding out how different rock types, their mineral contents, and grain size affect radio signal propagation. In the future, based on this gathered data, optimal antenna locations could be defined in the bedrock during the bedrock mapping phase. It would improve occupational safety. Occupational safety is always essential. However, it is even more vital to know who is in there in underground tunnels and mines, and this information must be extremely reliable. Also, companies can use this information for occupational safety in road and railway tunnel construction before spraying concrete during the construction phase. For companies doing productive mining, this information could help with cost savings. Cost savings occur, especially when mining near the ore body boundary layer.This study was performed using a Wavetrend active RX201-system. The ID (identification) card is an active transmitting unit in this system, and the reader is only the receiving unit (Figure3). The Wavetrend ID card is 85 mm long, 55 mm wide, and 5 mm thick sealed plastic casing that contains the electrical power source and an antenna. Each ID card is supplied with a unique ID number that the receiver system detects. The ID card transmits its unique ID number every 1.5 seconds at a frequency of 434 MHz [8]. All people and all vehicles have their ID cards [1].Figure 3
Active ID card transmits a unique ID number to the receiver unit.In this study, RSSI (received signal strength indicator) values and susceptibility values were used as measurement values. According to the RX201 manual, the reader’s RSSI can be adjusted between 60 and 120, where 60 is the weakest RSSI value. The RX201 sensitivity is -103 dBm, meaning RSSI 60 is equal to -103 dBm. No other dBm values are given, and thus, it is not possible to make a conversion chart between RSSI and received power [8].Magnetic susceptibility interferes with the propagation of radio signals. Magnetic susceptibilityK is defined by M=K×H, where M is the induced magnetization of the material and H is the inducing magnetic field. As both M and H are expressed in amperes per meter, volumetric susceptibility K is a dimensionless “SI unit,” while mass susceptibility X=K/p is in cubic meters per kilogram [9–11]. A KAPPAMETER model KT-6 instrument by SatisGeo (Figure 4(b)) was used for the susceptibility measurements. The instrument’s sensibility is 1×10−5 SI units, and the measurement range is -999 to 9999×10−3 SI units. The manufacturer of this meter is SatisGeo s.r.o. [12]. The susceptibility scale is logarithmic.Figure 4
View of the measurement (a), susceptibility measurement (b), and RSSI value measurement (c).
(a)(b)(c)The area selected for this study was the ONKALO tunnel system’s so-called Demo 3 in level –420 (Figure2). Demo 3 is a 25-meter-long tunnel whose bedrock is not covered because it is desired to monitor geological changes in the tunnel even more than 100 years. In this way, the tunnel geological changes can also be monitored in the future. The lithology of the tunnel is versatile, which makes it ideal for studying radio signals [13–15].


## 2. Measurement Setup

The study protocol consists of four measurement sets. Measurement location choices were based on the composition of the rocks. The first and the second measurement sets had 17 measurement locations. The third measurement set had nine measurement locations, and the fourth measurement set had two measurement locations. The ID card was in the same position where employees held it in every measurement set. The study was conducted with Wavetrend’s system because these devices are part of Posiva’s occupational safety. The aim was to gain insight into situations where problems might arise in its operation.In the first measurement set, the ID card was attached to the bedrock of different rock types, and then, the RSSI value was measured. In addition to this, the susceptibility value was also measured. The 17 locations of the measurement were selected and marked to photos taken during the geological mapping. Figure4 demonstrates the measurements done at the Demo 3 tunnel. First, the RSSI and susceptibility values were measured from each location. Only one active ID card was used when measuring the RSSI values, so the ID card’s differences would not affect the results. During these measurements, the ID card was attached to the bedrock. The susceptibility measurements were done from the same locations.Susceptibility means the ratio of magnetization produced in a material to the magnetizing force [16]. Magnetic susceptibility, the ratio of induced magnetization to an applied magnetic field, is a function of strongly magnetic particle concentrations, grain sizes, grain shapes, and mineralogy [17]. Figure 5 demonstrates what susceptibility is. There are several theoretical studies of the progression of susceptibility and electromagnetic fields. However, most studies focus on homogenetic materials. As rock types are heterogenetic and their magnetic structure is complicated, this theoretical knowledge is difficult to apply [17, 18]. Rock cannot be magnetized in a solid state. Magnetization can only happen when rock is in a molten state. The change in magnetism has occurred more than 1300 million years ago [19]. This study does not take a position on what kind of type magnetism the bedrock material is. In the study area, the strength of the magnetic field of the bedrock is so weak that it does not significantly affect the receiver.Figure 5
(a) No external field, and the rock sample has zero net field. (b) Magnetic domains are oriented randomly. (c) If an external field H exists, magnetic domains will align to it [20].
(a)(b)(c)In the second measurement set, the difference in RSSI value was measured when the ID card was attached to the bedrock and then detached 50 mm from the bedrock surface. The purpose of the second measurement set was to confirm the reliability of the RSSI value of the first measurement set. The measurements were done at the same locations as the first measurement. First, the active ID card was against the bedrock, and then, the ID card was about 50 mm off the bedrock. This was to see how much the RSSI value changes once the card is not touching the bedrock. This measurement was carried out with four ID cards to see if differences in each ID card affected the RSSI value.The third measurement set was made because the advisor board suggested that an external surveyor makes the measurements. These procedure suds increase the reliability of the measurements. An external research assistant selected random locations in this measurement set. After this, the geologist reported the rock types, grain size, and amount of minerals at measurement locations.The fourth measurement set was also done in Demo 3. After the initial measurement sets, it was possible to measure two different rock types. The measurement results are good to know from the view of occupational safety. One measurement was done from a rock sample found in an inclusion (inclusion means, in geology, a body or particle of distinct composition embedded in a rock or other material) at ONKALO’s parking area. This specimen differs entirely from the rock type in the Demo 3 area and the Olkiluoto area lithology. Another measurement was done using a rock sample from the Kemi chrome mine [21]. Both examples differ entirely from the rock type used for the initial measurements. It was interesting to find out how a completely different type of rock affected the RSSI value.


## 3. Rock Types at Measurement Locations

In the following, the Olkiluoto rock types, resistivity range, and the measurement location’s rock types, grain sizes, and minerals are explained in general.The bedrock of Olkiluoto consists mainly of migmatites, i.e., they are mixtures of different rock types. Migmatites commonly show clear striping. Lighter and darker rock types alternate in different thickness layers (Figures6–8). The grain size of the rock varies. The grain size is divided into four groups: fine-grained (<1 mm), medium-grained (1-5 mm), coarse-grained (5-50 mm), and large-grained (>50 mm).Figure 6
Demo 3 left wall.Figure 7
Demo 3 back wall.Figure 8
Demo 3 right wall.The resistivity measurements have been made in ONKALO from rock samples taken between 2005 and 2008. Resistivity measurements used three frequencies, 0.1 Hz, 10 Hz, and 50 Hz, which have also been used to compute the frequency effect of induced polarization (IP value). Values are slightly dispersive, i.e., decreasing with increasing frequency [21].Conductivity is contributed by rock constituents of metallic conductors, nonconductors, insulators, semiconductors, and electrolytes. Most rock-forming minerals are semiconductors (oxides and sulfides, of weak to moderate conductivity) or insulators (most silicates, of high resistivity). Rock mass resistivity is formed as a mixture of these components, will express similar behavior under dry conditions, and has a very high range of variation from 10-8 to 1017 Ωm [22].Most of the electrical conductivity contribution is created or enhanced by the electrolyte in pore space and fractures. Resistivity is considered a rather indicative parameter of lithology in sedimentary rocks (defined as grain size and, e.g., clay content). It will correlate strongly with porosity and texture in metamorphic rocks. Resistivity decreases with increasing pore space and fracturing. Accessory semiconductor minerals (graphite and sulfides) will decrease resistivity [23].The lighter bands and areas are mainly pegmatitic granite, which is coarse- and large-grained. The mica amount, especially dark biotite (biotite is a mineral in the mica group), is small, but quartz and feldspar quantities are high. The darker bands in the rock are very mica-rich, and the grain size is typically medium-grained. The darker areas can also contain fine-grained and quartz-rich areas [13–15, 24, 25]. In Table 1, the Olkiluoto bedrock stone species are shown with their resistivity range [22]. In this study, the most common rock types are on the top and descending to the bottom.Table 1
Resistivity ranges for the different rock types [21].
Rock typeResistivity median (Ωm)Resistivity min (Ωm)Resistivity max (Ωm)Mode(s) (Ωm)Range(s) (Ωm)Std. dev (Ωm)VGNVeined gneiss22800.002020427722-3 k6-8 k20-25 k60-100 k250 k4-40 k60-100 k151097PGRPegmatitic granite16300.001884721706-8 k16-20 k25-30 k3-30 k145948DGNDiatextic granite15500.009.469425383-4 k4-5 k10-12 k20-25 k40-50 k5-65 k106169SGNStromatic gneiss18800.002459623413MGNMica gneiss20400.003586661924-5 k20-25 k60-100 k3-30 k60-200 k110824QGNQuartz gneiss55800.001060047592510-15 k20-160 k250-320 k10-500 k183258KFPK-feldspar porphyry5730.00350030300MFGNMafic gneiss18900.005344657401-1,5 k6-10 k20-100 k6-100 k108686TGGTonalitic granitic Granodioritic gneiss24400.00219046006310-12 k20-32 k6-40 k102174MDBMetadiabase113000.0016200463038All19366.509.4620427726-8 k16-32 k4-100 k118614Altered12386.509.4620427722-3 k5-6 k10-12 k25-32 k40-50 k5-50 k143048Deformed1-2 k5-6 k4-30 k88168The resistivity distribution of PGR (pegmatitic granite) is very close to the resistivity distribution of all the samples. However, PGR has only a few highest resistivity values (>50000Ωm). Therefore, its median resistivity is lower than the median of all the values. Resistivity distributions of VGN (veined gneiss) and MGN (mica gneiss) are very close to the resistivity distribution of all the samples. TGG (tonalitic granitic granodioritic gneiss) has the highest resistivity of all the samples. QGN (quartz gneiss) has a very high resistivity as well [22].In the first measurement set, the aim was to select the measurement locations in such a way that they give the most representative samples. These 17 locations were marked on the photos taken during the geological mapping. Figures6–8 also show the locations where the Posiva leading geologist had reported the measurement of rock type, grain size, and mineral amount.Figure6 shows the left-side measurement locations of the Demo 3 area. The rock types and structure of the measurement location are given.
(i)
LW 1: coarse- and large-grained PGR(ii)
LW 2: coarse-grained PGR(iii)
LW 3: medium- and fine-grained QGN that also consists of some dark biotite(iv)
LW 4: coarse- and large-grained PGR(v)
LW 5: coarse- and large-grained PGR(vi)
LW 6: coarse-grained PGR(vii)
LW 7: coarse-grained biotite-rich area and mica gneiss MGN(viii)
LW 8: fine-grained quartz-gneiss QGN, but next to this point also biotite-rich mica gneiss MGN(ix)
LW 9: medium- and coarse-grained PGRFigure7 shows the rear measurement locations of the Demo 3 area. The rock types and structure of the measurement location are given.
(i)
BW 1: medium-grained biotite-rich mica gneiss MGN(ii)
BW 2: medium-coarse-grained PGR(iii)
BW 3: inside PGR biotite-rich area(iv)
BW 4: coarse-grained PGRFigure8 shows the right-side measurement locations of the Demo 3 area. The rock types and structure of the measurement location are given.
(i)
RW 1: coarse-grained and quartz-rich PGR(ii)
RW 2: medium-grained mica-rich dark band and in the same area medium-grained, fine-grained mica- and quartz-rich area(iii)
RW 3: medium-grained and fine-grained mica- and quartz-rich area edges contain some biotite-rich mica gneiss(iv)
RW 4: coarse- and large-grained PGR and quartz-rich areaThe third measurement set locations have not been marked in pictures. The third measurement set had nine measurement locations, of which eight measurement locations contained the same rock types as the first and the second measurement sets. Only one measurement location differed significantly from the first and the second measurement sets. This rock was fine- to medium-grained VGN (veined gneiss) that contained a mica-rich band.The reason why the fourth measurement set was done was occupational safety. Sample 1 is a rock originating from an inclusion found inside a VGN. The rock is very mineral-rich and consists of quartz, plagioclase, chlorite, and pyrrhotite. Also, a rock core sample 2 received from the Kemi chrome mine was measured. The rock sample consists of chromitite, and its main mineral is the chromite.


## 4. Measurement Results

Table2 shows the results of the first measurement set and second measurement set. These 17 measurement locations are shown in Figures 6–8. The table illustrates the connection between RSSI value and susceptibility. The reference RSSI value shown in the table has been measured in the middle of the tunnel, approximately four meters from the reader antenna, which only acts as a receiver.Table 2
Measurement location rock types, RSSI, and susceptibility value.
Measure pointTag IDFirst measurement setSecond measurement set122412321232123312331234123412351235Rock typeSusceptibilityRSSI valueRSSI on bedrockRSSI 50 mm off bedrockRSSI on bedrockRSSI 50 mm off bedrockRSSI on bedrockRSSI 50 mm off bedrockRSSI on bedrockRSSI 50 mm off bedrockLW 1PGR0.03135135134134134135135134135LW 2PGR0.05131131130131131131131130131LW 3QGN0.15126123126124127126127126126LW 4PGR0.05130130131129130130130129130LW 5PGR0.04132132133134135133134132132LW 6PGR0.04129129129127128129130130131LW 7Biotite-rich MGN0.2599991111001089910698107LW 8QGN+biotite-rich MGN0.15120120126118122119124120124LW 9PGR0.03125125124126126125126125126BW 1Biotite+MGN0.27111111125110128111128111126BW 2PGR0.07122122122120121122123122122BW 3Biotite0.19116116126114126114127116132BW 4PGR0.05125125125125125125125125125RW 1PGR0.04111111110111112110110112112RW 2Mica-rich0.229493106931089611194109RW 3Mica-rich0.339393107941109511093107RW 4PGR0.07116116115116117115116116116Reference value0135Figure9 shows the RSSI and the susceptibility values of the first measurement set as a histogram. You can also see the average of the RSSI and susceptibility values. Circles have marked the points where the susceptibility values exceed the average. Figure 9 shows when the susceptibility value grows and the RSSI value decreases.Figure 9
Measured RSSI and susceptibility values and their averages.Table3 shows the results of the third measurement set and fourth measurement set RSSI values. One italic result in Table 3 shows that in the third measurement set, only one measurement location contained a different rock type than the first and second measurement sets.Table 3
The third measurement set and the fourth measurement set rock types and RSSI value.
(a)Third measurement setRSSIRock typeLocation 1134PGRLocation 2127QGNLocation 3100Biotite-rich MGNLocation 4132PGRLocation 5130PGRLocation 6122VGN - mica-richLocation 7126PGRLocation 8117BiotiteLocation 9120QGN+biotite-rich MGN(b)Fourth measurement setRSSIRock typeSample 1105-120VGN+quartz+plagioclase+chlorite+pyrrhotiteSample 275-90ChromititeTable4 shows the results of the second measurement set, the third measurement set, and the fourth additional measurement set results. Table 4 contains the measurement results by rock type. Table 4 shows the change of RSSI value in different rock types when the ID card is on the bedrock and then 50 mm of the bedrock.Table 4
RSSI value changes by rock types.
Rock typeChange of RSSI valuePGR±1QGN+1–+4Biotite-rich MGN+6–+12QGN+biotite-rich MGN+2–+6Mica-rich+10–+15Biotite+MGN+12–+18Biotite+10–+16VGN+mica-rich+6–+10VGN+quartz+plagioclase+chlorite+pyrrhotite+15–+30Chromitite+40–+60


## 5. IAEA Measurements in This Research Area

Investigation of the GPR (ground-penetrating radar) technique uses electromagnetic radiation pulses in the radio spectrum’s microwave band (10 MHz to 3 GHz). It reads the reflected signal to detect subsurface structures and objects without drilling, probing, or otherwise breaking the ground surface. GPR uses transmitting and receiving antennae. The transmitting antenna radiates short pulses of high-frequency radio waves into the ground. When the wave hits a buried object or a boundary with different electrical properties, the receiving antenna records variations in the reflected return signal. Using the time differences in the reflected waves, it is possible to reconstruct images of subsurface structure and look for voids, cracks, or other inhomogeneities [26].GPR has been used by the IAEA (International Atomic Energy Agency) since 2006 for design information verification and inspection of concrete during the construction of new nuclear facilities but has never been used in a GR (ground radar) on a bare rock before [26].GPR signal attenuation is challenging in the Finnish bedrock, which is a mix of pegmatitic and gneissic rock. Rock type, fracture zones, fracture intensity, fracture fillings, and water content strongly affect signal attenuation. Generally, the high conductivity and high dielectric value (permittivity) of the medium (rock) strongly attenuate the GPR signal [26].Geovisor executed low-frequency ground-penetrating radar measurements in ONKALO for IAEA. The main goal of the measurements was to carry out GSSI’s (Geophysical Survey Systems Inc.) GPR equipment feasibility test in detecting voids in ONKALO rock conditions. The campaign consisted of measurements with four low-frequency antennas 100, 270, 350, and 400 MHz [26].As assumed, the very low-frequency antennas (100 and 270 MHz) do not work ideally in tunnel conditions. Large dimensions of antennas, very low frequencies, intensive ringing effect, and old technology are the weaknesses of these antennas. Based on the testing, 350 MHz and 400 MHz are the most suitable antennas for ONKALO rock and overall tunnel conditions [26].


## 6. Analysis of Measurements

### 6.1. Susceptibility Effect and RSSI Value

Without question, the first measurement set indicated the mineral’s effect on the RSSI values. Table2, together with Figure 9, provides a good illustration of how mica and minerals weaken the RSSI value and increase the susceptibility compared to PGR, which does not contain mica. The grain size of the rock did not have any effect on the RSSI value or the susceptibility. Figure 9 circles those points when the susceptibility is above average, and the RSSI value is low.


### 6.2. Mineral Effect and RSSI Value

The second, third, and fourth measurement sets confirmed the first measurement set results. The results of Tables4 and 2show that rock types strongly affect RSSI values. The ID card RSSI value change on the bedrock to 50 mm off the bedrock varied according to rock types.In the first and second measurement sets, when the rock type was PGR, the RSSI value did not change.(i)
When the rock type was QGN, the RSSI value change was 1-4 units(ii)
When the rock type was biotite-rich MGN, the RSSI value change was 6-12 units(iii)
When the rock type was QGN+biotite-rich MGN, the RSSI value change was 2-6 units(iv)
When the rock types were mica- and quartz-rich (mica-rich, biotite+MGN, and biotite), the RSSI value change was up to 18 unitsIn the third measurement set, one measurement location contained a different rock type than the first measurement set. This rock type was fine to moderately grained VGN veined gneiss that contained a mica-rich band. In this location, the RSSI value change was 6-10 units.The fourth measurement set was done with a rock that originates from an inclusion found inside a VGN. The rock is mineral-rich and consists of quartz, plagioclase, chlorite, and pyrrhotite. These minerals weakened the ID card’s RSSI value by up to 30 units. The most significant measured differences in values were recorded when measuring a rock core sample from the Kemi mine. This rock sample consists of chromitite, and its main mineral is chromite. This rock specimen measurement changed the RSSI value by up to 60 units.


### 6.3. Analysis of Measurements

The IAEA measurements give the same kind of conclusion as our measurements. The bedrock of ONKALO absorbs low-frequency radio waves. The absorption of radio frequencies must also be considered if autonomous means of transport are to be used in the final disposal of nuclear waste.


## 6.1. Susceptibility Effect and RSSI Value

Without question, the first measurement set indicated the mineral’s effect on the RSSI values. Table2, together with Figure 9, provides a good illustration of how mica and minerals weaken the RSSI value and increase the susceptibility compared to PGR, which does not contain mica. The grain size of the rock did not have any effect on the RSSI value or the susceptibility. Figure 9 circles those points when the susceptibility is above average, and the RSSI value is low.


## 6.2. Mineral Effect and RSSI Value

The second, third, and fourth measurement sets confirmed the first measurement set results. The results of Tables4 and 2show that rock types strongly affect RSSI values. The ID card RSSI value change on the bedrock to 50 mm off the bedrock varied according to rock types.In the first and second measurement sets, when the rock type was PGR, the RSSI value did not change.(i)
When the rock type was QGN, the RSSI value change was 1-4 units(ii)
When the rock type was biotite-rich MGN, the RSSI value change was 6-12 units(iii)
When the rock type was QGN+biotite-rich MGN, the RSSI value change was 2-6 units(iv)
When the rock types were mica- and quartz-rich (mica-rich, biotite+MGN, and biotite), the RSSI value change was up to 18 unitsIn the third measurement set, one measurement location contained a different rock type than the first measurement set. This rock type was fine to moderately grained VGN veined gneiss that contained a mica-rich band. In this location, the RSSI value change was 6-10 units.The fourth measurement set was done with a rock that originates from an inclusion found inside a VGN. The rock is mineral-rich and consists of quartz, plagioclase, chlorite, and pyrrhotite. These minerals weakened the ID card’s RSSI value by up to 30 units. The most significant measured differences in values were recorded when measuring a rock core sample from the Kemi mine. This rock sample consists of chromitite, and its main mineral is chromite. This rock specimen measurement changed the RSSI value by up to 60 units.


## 6.3. Analysis of Measurements

The IAEA measurements give the same kind of conclusion as our measurements. The bedrock of ONKALO absorbs low-frequency radio waves. The absorption of radio frequencies must also be considered if autonomous means of transport are to be used in the final disposal of nuclear waste.


## 7. Conclusion

This research provides an understanding of how different rock types and minerals within them affect the RSSI values at 434 MHz. Based on this research, the grain size of the rock type did not affect the RSSI value, but the type of rock and its mineral content had an effect. The mineral’s magnetism had a strong impact. The higher the susceptibility value was, the lower the RSSI value correspondingly was. Future measurements should be performed with different radio frequencies. This would further help us understand how different radio frequencies react with different rock types and minerals contained within.These results will help occupational safety by better determining where to locate antennas. The antenna should not be placed in an area containing a lot of mica and quartz, as they both decrease the reading reliability. However, from the point of view of occupational safety, it is good to note that when the ID card is off the bedrock, the RSSI value increases fast. This provides reliable information on employees existing in tunnels and increases occupational safety.This research also supports the theory that it is possible to detect minerals in rocks using radio waves. Results could be used in the mining industry with production quarries.The change caused by chromitite was so significant that it must be considered for occupational safety in production mines.



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*Source: 1209844-2023-02-01.xml*