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The effect of the plastic behavior of clay particles on LCPC abrasive coefficient
Tunnelling and Underground Space Technology 92 (2019) 103054
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The effect of the plastic behavior of clay particles on LCPC abrasive coefficient
T
Mohammad-Taghi Hamzabana, , Naimeh Hosseini Tavanaa, Pål Drevland Jakobsenb, Ali Reza Bagheriyana ⁎
a b
Mining Engineering Faculty, Sahand University of Technology, Tabriz, Iran Department of Civil and Transport Engineering, NTNU, N-7491 Trondheim, Norway
ARTICLE INFO
ABSTRACT
Keywords: Mechanized excavation Abrasivity LCPC test Clay
In mechanized excavation projects, the major part of feasibility studies includes predicting the lifetime of cutting tools. Estimating the required numbers of tools for excavating a certain length of a section, under defined geologic conditions, and assessing the cost and downtimes needed for tools replacement are the other important issues in the preliminary studies of these projects. Presently, there are several experimental models used to study the abrasive capacity of soil materials in mechanized tunneling applications. In this paper, the effect of plastic behavior of clay particles on the abrasivity of soil materials was studied using the results of LCPC abrasivity tests. The results showed that the rheological behavior of abrasive samples changes considerably with the change of the clay particles mineralogy and the dominant water content. These changes have a significant effect on recorded wear amounts. Based on the obtained results, the plastic limit and the liquid limit of the clay part can be used to predict the appeared abrasive trends in LCPC tests. Moreover, during performing the LCPC tests, the consumed power of the electromotor of the testing device was recorded. The obtained power graphs confirmed the effect of the mineralogy and the water content of the clay part on the rheological and abrasive behavior of the testing samples.
1. Introduction The increasing demand for mechanized excavation machines in different civil and mining projects, has led to several studies about soil abrasivity in the last years. Various experimental setups have been used to study the abrasive capacity of soil materials in mechanized tunneling applications. Some of the most well-known models are LCPC abrasimeter (AFNOR, 1990), NTNU SAT soil abrasivity testing method (Nilsen et al., 2007; Jakobsen et al., 2013a), soil abrasivity testing device developed in Penn State University – PSU (Alavi Gharahbagh et al., 2011), soft ground abrasivity test – SGAT (Jakobsen and Lohne, 2013; Jakobsen et al., 2013b), testing procedure developed in Turin Polytechnic (Peila et al., 2012), soil abrasivity testing chamber – SATC (Barzegari et al., 2013, 2015), and RUB tunneling device (Küpferle et al., 2016). These experimental models just provide a primary indication of soil abrasivity, and they do not consider the effect of some major factors on the wear of soil cutting tools. For instance, most of the mentioned models cannot control the density, cohesion, friction angle, or moisture content of the testing sample. These parameters are determined in pre-construction geotechnical explorations. Quantifying ⁎
the effect of these parameters in order to use in a tool wear prediction model is very complicated, especially in hybrid or EPB shields (Frenzel et al., 2008). Hamzaban et al. (2014a, 2014b) have classified the effecting factors on rock abrasivity into two main groups: geological parameters relevant to rock samples and technical parameters relevant to testing procedure. A similar approach can be used for soil abrasivity. However, there are some differences between the effective factors on rock and soil abrasivity. Moreover, the applied excavation technics and cutting tools are thoroughly different in hard rock and soft ground tunneling projects. Generally, the count of the effecting parameters on soil abrasivity is more than that of rock abrasivity. For example, in the category of geological parameters, the presence of groundwater, pore pressure, and the effect of relative density has not a considerable role in the wear of rock cutting tools. Similarly, in the category of technical parameters, the face stabilizing pressures and soil conditioning additives are not used in hard rock tunneling. Moreover, the laboratory simulation of soil in-situ conditions, especially in granular soil, is very difficult. Consequently, the study of soil abrasivity and predicting the wear of soil cutting tools are more complicated than the same issues in hard rocks.
Corresponding author. E-mail address: [email protected] (M.-T. Hamzaban).
https://doi.org/10.1016/j.tust.2019.103054 Received 28 March 2019; Received in revised form 23 June 2019; Accepted 20 July 2019 0886-7798/ © 2019 Elsevier Ltd. All rights reserved.
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Table 1 . Summary of previous studies on soil abrasivity for mechanized tunneling applications. Parameter
Testing model
References
The hardness of soil grains
LCPC
Thuro et al., 2006; Köhler et al., 2011; Hashemnejad et al., 2012, 2016; Barzegari et al., 2013, 2015; Düllmann et al., 2014; Kahraman et al., 2016, 2018 Rostami et al., 2012; Mosleh et al., 2013 Jakobsen et al., 2013a Barzegari et al., 2015 Thuro et al., 2006; Drucker 2011; Barzegari et al., 2015; Hashemnejad et al., 2012, 2016; Kahraman et al., 2016 Rostami et al., 2012 Jakobsen et al., 2013a Barzegari et al., 2015 Küpferle et al., 2016 Thuro et al., 2006; Hashemnejad et al., 2012, 2016; Düllmann et al., 2014; Kahraman et al., 2016 Alavi Gharahbagh et al., 2013 Jakobsen et al., 2013a Klemetsrud, 1985 Drucker, 2011; Hashemnejad et al., 2012 Rostami et al., 2012; Alavi Gharahbagh et al., 2013, 2014a Jakobsen et al., 2013b Rostami et al., 2012 Jakobsen et al., 2013b Barzegari et al., 2015 Hamzaban et al., 2019 Rostami et al., 2012 Jakobsen et al., 2013b Hamzaban et al., 2019 Barzegari et al., 2015 Barzegari et al., 2015 Drucker, 2011; Küpferle et al., 2015a, 2015b Rostami et al., 2012; Mosleh et al., 2013; Alavi Gharahbagh et al., 2013 Klemetsrud 1985 Alavi Gharahbagh et al., 2014b Jakobsen et al., 2012, 2013b. Küpferle et al., 2016 Bakar et al., 2014; Hamzaban et al., 2019 Jakobsen et al., 2013b Küpferle et al., 2016 Rostami et al., 2012
The diameter of soil grains
The Shape and angularity of soil grains Water content
Ambient pressure level Pore Pressure Compaction Effective stress level Shear strength parameters The hardness of wear parts Conditioning additives Penetration rate Rotation speed Mechanism of engagement
PSU NTNU SAT SATC LCPC PSU NTNU SAT SATC RUB LCPC PSU NTNU SAT Ball Mill LCPC PSU SGAT PSU SGAT SATC LCPC PSU SGAT LCPC SATC SATC LCPC PSU Ball Mill PSU SGAT RUB LCPC SGAT RUB PSU
The investigations on the effect of different geological and technical factors have been the main topic of many experimental and empirical studies on the soil abrasive properties. Table 1 summarizes a list of previous investigations performed to study the effect of different factors. In the investigations presented in this research paper, the effect of plastic behavior of fine particles on the abrasivity of soil materials is studied with the LCPC test. Natural soil deposits often have a considerable amount of clay particles with different mineralogy, which is expected to influence both the abrasivity and the consistency of the soil. Moreover, slurry shields, and sometimes EPB TBMs, use bentonite for soil conditioning purposes. The rheological behavior of clay containing soils changes considerably with the change of dominant water content. It appears that the rheological changes have a significant effect on the abrasive properties of soft grounds. In addition, the effect of the plastic behavior of the clay part in the soil mixture was investigated in this study. The findings of this research paper can be used to theoretically assess how the existing clay mineralogy and amount influences the abrasivity of soil.
wear on steel due to abrasivity of rock aggregates and coarse soil grains, especially in central Europe. The abrasimeter has a 750 W electromotor to rotate a propeller. The propeller is a steel plate of 50 mm × 25 mm × 5 mm size and is made of a standard steel with a hardness of 60–75 Rockwell-B. The steel propeller is placed at a defined position in a sample container and is replaced after each test (Thuro et al., 2006). In the standard testing procedure, an air-dried soil sample with a mass of 500 ± 2 g and a particle size range of 4.0–6.3 mm is added in the sample container. The rectangular-shape propeller rotates for 5 min in the container, which is filled with testing sample. Here, the rotation speed is 4500 RPM. In order to determine the abrasivity of the soil sample, the propeller is weighted before and after the test. The LCPC abrasivity coefficient, that is LAC, is calculated as follows:
LAC = (m 0
(1)
where m0 is the mass of propeller before the test, m is the mass of propeller after the test, and M is the mass of the soil sample (=0.0005 t) (Thuro et al., 2006). In the conducted investigations, five weights were designed and made to study the impact of effective stress levels on the wear of steel propellers. The details of the design of loading weights have been published elsewhere (Hamzaban et al., 2019). The AFNOR standard recommends using XC12 steel grade with the hardness of 60–75 HRB in making propellers. However, regarding to inaccessibility to this grade of steel, the propellers were made of St-37 structural steel. The hardness of used steel parts was measured in the range of 63 ± 5 Rockwell B (HRB) that is in line with the recommended hardness in the standardized test. During a part of the experimental investigations, in addition to measure the weight loss of the steel propeller, the consumed power of
2. Testing materials and procedure LCPC abrasivity tests were applied in the studies. The central laboratory of bridges and roads1 in France has developed the test in the 1980s, and their standard of P18-579 describes the testing device (AFNOR, 1990). It was originally developed to measure rock aggregates resistance against crushing. However, it is also used to measure the 1
m)/ M
Laboratoire Central des Ponts et Chaussées. 2
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Fig. 1. . (a) 3-Phase power meter to measure the consumed power of the electromotor, (b) A recorded real-time power signal during a LCPC test on a dry crushed silica sample (size range = 4–6.3 mm with no surface load) (c) the general set up of the testing device and its accessories.
Fig. 2. . (a) The crushed silica grains, (b) The particle size distribution curve of crushed silica grains.
the electromotor was recorded. A 3-phase power meter was designed and manufactured (Fig. 1a), and it was installed parallel to the main power supply line of the testing device. Consequently, the power meter provided a real-time measurement of the consumed power of the electromotor. The output signal of the power meter was transmitted to a
data logger, and finally, the recorded power signal was saved in a PC. Fig. 1b shows an example of the recorded power signal obtained in an LCPC test performed on dry crushed silica grains (4–6.3 mm) without applying surface loads. The general set up of the testing device along with the added accessories to control testing duration time, propeller 3
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Fig. 3. . Different clay materials used in the testing program, (a) talc, (b) kaolinite, (c) bentonite.
conditions with no surface loading weights. The absence of water means that the clay parts do not show plastic behavior, and the graphs just reveal the effect of fine particles. All graphs start from the same point where the percentage of fine particles is zero. However, adding different fine particles changes the obtained LAC values at the same mixing ratios. The mixtures of crushed and fine silica grains show a quite different trends in Fig. 4. Due to the same hardness of components in these mixtures, the different abrasive samples have the same hardness. Therefore, in the graph relevant to the fine–coarse silica grains, we can just see the effect of particles size distribution. The average hardness of abrasive mixtures changes in addition to particles size distribution curves, when the different ratios of clay minerals are mixed with crushed silica grains. Consequently, different trend lines are obtained for silica – talc and silica – kaolinite mixtures. However, the trend lines for clay mixtures are more similar. As one can see from Fig. 4, pure fine particles show nearly zero LAC values. It is important that despite the significant hardness of fine silica particles, the relevant LAC values are quite small and very close to those of talc and kaolinite. This means that decreasing the size of soil particles decreases the importance of their hardness in soil abrasivity measured in the LCPC test. Figs. 5 and 6 shows the variations of LAC with the changes in water content for the different abrasive mixtures of silica–talc and silica–kaolinite, respectively. Fig. 5a and 6a are the same and show the results for pure silica samples. The authors have discussed these graphs previously (Hamzaban et al., 2019). Adding clay minerals to the abrasive samples and changing the share of clay minerals change the LAC – w curves drastically (Figs. 5b–f and 6b–f). It seems that in the presence of talc particles (Fig. 5b–f), the general trend is the decrease of LAC values with the increase of water content at the first stage. However, after passing a minimum value, LAC shows an ascending trend if the increase of water content is continued. The observed trend for silica–kaolinite abrasive mixtures is different, especially in the graphs of 6c, d, and e. LAC values show an ascending trend in the first part of these graphs. Consequently, comparing the same graphs of Figs. 5 and 6 reveals that the type of clay component affects the abrasive behavior of the tested mixtures at the same water contents. The principals of soil mechanics can describe the trends of Figs. 5 and 6. Based on the theory of consistency of fine-grained soils, at a very low moisture content, soil behaves more like a solid. When the moisture content is very high, the soil and water may flow like a liquid. Hence, on an arbitrary basis, depending on the moisture content, the behavior of soil can be divided into four basic states: solid, semisolid, plastic, and liquid, as shown in Fig. 7. The moisture content, in percent, at which the transition from solid to semisolid state takes place, is defined as the shrinkage limit (SL). The moisture content at the point of transition from semisolid to plastic state is the plastic limit (PL), and from plastic to liquid state is the liquid limit (LL) (Das and Sobhan, 2014). Considering the very low water absorption of silica particles in the abrasive samples, one can assume that the whole added water into the sample is absorbed with clay particles. Moreover, Fig. 7 shows ideally
Table 2 . Plastic limit, liquid limit, and plasticity index of different clay materials. Clay mineral type
Plastic limit (%)
Liquid limit (%)
Plasticity index (%)
bentonite kaolinite talc
40 31 22
328 45 29
288 14 7
Fig. 4. . The variations of LCPC abrasivity coefficient with the percentage of fine particles in different abrasive mixtures.
rotation speed, and record power signal are shown in Fig. 1c. In order to investigate the effect of the plasticity of fine particles on the wear capacity of soil deposits, synthetic soil samples were made with mixing the crushed angular Silica grains and clay particles. The size range of the used silica grains (Fig. 2a) was between 4.0 and 6.3 mm. Fig. 2b shows the particle size distribution curve of the silica grains. These coarse grains were mixed with three different types of clay materials: talc, kaolinite, and bentonite particles, which are shown in Fig. 3a–c respectively. The percentage of clay part in the abrasive mixture was zero, 20, 40, 60, 80, and 100. Adding different amounts of water to the different abrasive mixtures creates different plastic behaviors in the clay part. In order to study the appeared plastic behaviors accurately, Plastic and Liquid limits of clay materials were determined with Atterberg limits tests (ASTM D4318, 2005). Table 2 shows the results of these tests. LCPC tests were performed with the water contents of zero, 5, 10, 15, 20, 25, and 30 percent under the surface stress levels of zero, 1.0, 1.7, 2.3, 2.9, and 3.5 kPa. Consequently, the testing program included performing more than 470 LCPC tests. 3. Results and discussion In the first step, in order to see the effect of fine particles on the abrasive behavior of soil mixtures, the variations of LAC against the percentage of fine particles were plotted in Fig. 4. The abrasive mixtures are the combinations of crushed angular silica grains with fine silica, talc, and kaolinite. The data are the results of LCPC tests in dry 4
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Fig. 5. . The changes of LAC values with water contents under the different normal stress levels and talc shares of, (a) zero, (b) 20%, (c) 40%, (d) 60%, (e) 80%, (f) 100% (White, light grey, and dark grey backgrounds show the ranges of liquid, plastic, and semi-solid/solid behavior of clay part respectively).
how moisture content influence the stress-strain relationships of soils, which is influencing the rheology. Therefore, it seems that there is a correlation between the plastic behavior of the clay part and the results of LCPC tests, and using the water contents relevant to plastic and liquid limits, the fitted trend lines of Figs. 5 and 6 can be described. Table 2 represents the values of PL and LL for talc and kaolinite. As mentioned before, it is assumed that the clay part (talc or kaolinite) absorbs completely the added water to the sample. The horizontal axes in the graphs of Figs. 5 and 6 show the moisture content calculated based on the dry mass of whole sample (=500 g). Considering the mentioned assumption, the moisture contents can be calculated only based on the dry mass of the clay with using simple weight – volume relationships. This will be in line with the assumption that the clay part absorbs completely the added water to the testing mixture. Using this way one can calculate the water contents, which are relevant to the plastic and liquid limits of the clay part, on the horizontal axes of the graphs in Figs. 5 and 6. These values for the different talc and kaolinite shares are calculated and summarized in Table 3. The vertical lines in
Figs. 5 and 6 show the plastic and liquid limits in the abrasive mixtures. It is evident that if w < PL, the clay part behaves as a semisolid/solid material. For the range of PL < w < LL, the behavior is plastic, and finally in the range of w > LL the clay part show a liquid behavior. In Figs. 5 and 6, the mentioned behavior ranges are shown with dark grey, light grey, and white backgrounds respectively. Using the specified ranges for the behavior of the clay part in the graphs of Figs. 5 and 6, the obtained trends can easily be described. In silica–talc samples, in the range of semisolid/solid behavior (w < PL), increasing water content decreases the resulting LAC values. At the completely dry condition, silica and clay parts behave independently. The impaction of the hard silica grains to the rotating propeller creates considerable wear amounts. Adding water to the abrasive mixture, the clay particles start to cohere themselves and Silica particles. Nevertheless, due to low moisture content, a continuous matrix of clay does not create. However, a thin clay layer covers abrasive silica grains and reduces their mobility and apparent surface hardness. Consequently, LAC values decrease and the more the added water the higher the 5
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Fig. 6. . The changes of LAC values with water contents under the different normal stress levels and kaolinite shares of, (a) zero, (b) 20%, (c) 40%, (d) 60%, (e) 80%, (f) 100% (White, light grey, and dark grey backgrounds show the ranges of liquid, plastic, and semi-solid/solid behavior of clay part respectively).
Fig. 7. . Shrinkage limit, Plastic limit, and Liquid limit (Das and Sobhan, 2014). 6
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silica grains in lower viscosities leads to the appearance of an ascending trend in LAC – w data. However, the ascending trend stops at high water contents in Figs. 5b, c and 6b, c. When the percentage of clay is 20 in Figs. 5b and 6b (40% of clay particles in Figs. 5c and 6c), increasing water content beyond 15% (beyond 20% in Figs. 5c and 6c) results in a very low viscosity mixture which easily drains under the applied loading weights (Fig. 10). A careful look at the relevant photos of Figs. 8 and 9 reveals the signs of the drainage. Hence, despite the different amounts of added water, due to drainage under the same applied normal load, the moisture content of the testing sample is indeed constant, and therefore the obtained LAC values are more or less similar. However, as Figs. 8 and 9 show, increasing clay percentage beyond 40 creates such a heavy mixture, which cannot drain. Therefore, the horizontal fitted segment of LAC – w trend lines is disappeared from these samples. As mentioned in Section 2, the consumed power of the electromotor of the testing device was measured during LCPC tests. The measured data provide more information about soil – steel interaction. Using the power data recorded during the performed tests (Fig. 1b), the total consumed energy during performing a LCPC test can be calculated as follows (Petrica et al., 2013):
Table 3 . The required water contents to reach liquid and plastic limits in the different silica–talc and silica–kaolinite mixtures. Clay part content (%)
MS(C) wPL (%)
20 40 60 80 100
4.4 8.8 13.2 17.6 22
100 200 300 400 500
wLL (%)
Talc (LL = 29, PL = 22) wPL (%)
Kaolinite (LL = 45, PL = 31) wLL (%)
5.8 11.6 17.4 23.2 29
6.2 12.4 18.6 24.8 31
9 18 27 36 45
cohesion of clay particles and the lower the LAC values. When the water content is within the range between PL and LL (PL < w < LL) the clay part exhibits a plastic behavior. In this condition, a plastic matrix of clay is formed, and it traps the abrasive silica grains. Consequently, the interaction between abrasive particles and steel part is removed, and as Figs. 5 and 6 show, the lowest LAC values are obtained in this range of moisture content (the areas marked with light grey background). Passing the moisture content relevant to liquid limit (w > LL), the behavior of the clay part becomes similar to a viscous liquid in which silica particles float in a clay–water suspension. Therefore, the silica grains regain mobility and create wear on the steel propeller. The more the water content in this range the lower the viscosity of the suspension and the greater the mobility of the abrasive grains. Consequently, unlike the previous moisture ranges, there is a direct correlation between water contents and LAC values. However, when the percentage of clay part is 20 or 40, it seems that the higher water contents have no effect on the abrasivity of the testing mixtures, and LAC – w trends become horizontal. Figs. 5f and 6f reveal that pure talc and kaolinite samples, regardless of their water contents, are non-abrasive, and the LAC values are very close to zero. However, as the other graphs of Figs. 5 and 6 show, the presence of these clay particles along with abrasive grains, like silica, in wet conditions has a drastic effect on the abrasivity of the mixture and cause huge changes in the resulting LAC values. In Figs. 8 and 9, the photos of abrasive mixtures at the end of LCPC tests are shown along with the LAC – w trends, respectively for silica–talc and silica–kaolinite samples. The figures do not include the photos of dry mixtures, and the relevant applied normal stress level is 1.7 kPa. The bolded rectangles specify the samples which their water contents are in the range between PL and LL (PL < w < LL). As it mentioned before, the clay part in these samples shows a plastic behavior and results in the lowest LAC values. In the photos in the left hand of the bolded rectangles w < PL, and in the right-hand photos w > LL. Comparing the photos of these two groups clearly shows the difference between their rheological behavior. When w < PL, completely separate pieces can be recognized in the abrasive sample. In the higher water contents, due to the higher cohesion in clay phase, the pieces become greater. In these conditions, a greater volume of clay particles surrounds the silica grains and reduces the probability of direct impacts between the steel part and hard silica grains. Therefore, lower wear amounts are created and the descending trend continues until the clay part converts to an entirely plastic paste, which fully traps the silica grains. However, in this range of w, silica–kaolinite mixtures show a different behavior which will be discussed later. When w > LL, the abrasive mixture exhibits a liquid rheological behavior. In this moisture range, the more the water content the lower the viscosity of the abrasive suspension. Increasing the mobility of hard
E=
T 0
P (t ) dt
(2)
where P(t) is the power signal recorded during LCPC test, T is the time interval of the performed test (=300 s), and E is the total consumed energy during the test. Figs. 11 and 12 show the variations of energy (E) with the water content of testing samples in a group of tests, respectively for silica–talc and silica–kaolinite abrasive mixtures. The LAC – w graphs are plotted in the figures as well. Comparing the E – w graphs (dashed lines in Figs. 11 and 12) with the LAC – w graphs (bold lines in Figs. 11 and 12) reveals very good conformity between the obtained trends. This means that the higher the LAC value of the sample the greater the resistance against the motion of the steel propeller and therefore the higher the required energy (E) to rotate the propeller. Moreover, the trends of the consumed energy graphs show correlations with the different moisture content ranges that are similar to those described for LAC – w changes previously. The E – w trends reveal that rotating the steel propeller inside a dry abrasive sample needs to consume a high level of energy. This is equivalent to a high resistance against the motion of the propeller inside the sample and therefore a high degree of engagement between the steel and sample particles. The consequence of this engagement is reflected in the high levels of measured wear amounts in the relevant LAC graphs. Adding water to the abrasive samples and increasing it in the range of w < PL, leads to the coherence of clay particles and reduces the steel – soil engagement in the formed mixture. The relevant LAC values are reduced similarly. The lowest calculated E values are recorded in the range of PL < w < LL. This is entirely in line with the LAC – w trends. When the water content passes the liquid limit of the clay part, the calculated E values exhibit an ascending trend. This increase can be considered as the result of the greater degree of steel – soil engagement that again shows conformity with the increase of relevant LAC values. However, it seems that the increase of E values are smaller than LAC values. The greater increase of the recorded wear amounts is likely due to the higher mobility of silica particles when they float in a clay – water suspension. The high degree of conformity between the trends of E – w and LAC – w graphs confirms the effect of rheological behavior of testing samples on the recorded wear amounts. However, in the graphs of Fig. 12b, c, and d, a discrepancy between the trends of E – w and LAC – w is observed in the first part of the graphs, and it seems that a different
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Fig. 8. . The photos of abrasive samples at the end of the tests along with LAC – w graphs in silica–talc mixtures (the applied normal stress is 1.7 kPa).
mechanism governs in these samples. Figs. 13–15 reveal the steel – soil interaction in LCPC tests from another point of view. The figures plot the real-time consumed power signal (P(t)) during some of the LCPC tests on silica–talc and silica–kaolinite samples. Fig. 13a and b show the recorded signal in the dry silica–talc and silica–kaolinite samples respectively. The amplitude of consumed power signals changes between 400 and 500 W in silica–talc
samples and 350–400 W in silica–kaolinite mixtures. Some fluctuations are recognizable on the signals which likely reflect the effect of impacts between the steel propeller and sample grains. Fig. 14a and b shows the recorded P(t) signals when the water content of the testing samples is in the range between PL and LL. Comparing Figs. 13 and 14 reveals that when PL < w < LL, the average consumed power for rotating the steel propeller reduces to about 250 W. Moreover, the range of recorded 8
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Fig. 9. . The photos of abrasive samples at the end of the tests along with LAC – w graphs in silica–kaolinite mixtures (the applied normal stress is 1.7 kPa).
fluctuations on the P(t) signals becomes very small when the sample water content is in the range between plastic and liquid limits. This means that when the clay part of the sample behaves as a plastic medium, the steel propeller rotates in the sample much more easily with no impacts between the propeller and sample grains. Fig. 15a and b show an entirely different steel – soil interaction when w > LL. The amplitude of P(t) signals shows great sudden increases which reflect the effect of severe impacts between coarse silica grains and the steel propeller.
The P(t) signals shown in Figs. 13–15 confirm the described steel – soil interaction mechanisms and their changes in different water content ranges of w < PL, PL < w < LL, and w > LL discussed in the previous paragraphs. The silica–kaolinite mixtures in the moisture range of w < PL shows a different behavior compared to the silica–talc mixtures. As Fig. 6c, d, and e (and Fig. 12b, c, and d) show, in this range, the LAC results show an increase when the water content increases. The trend does not match with the expected descending trends based on the 9
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abrasive Silica grains segregates from the sticking clay phase and concentrates at the bottom of the testing container. Therefore, the steel propeller rotates in a part of the sample, which has more abrasive silica grains than the average of whole sample. It is evident that this leads to the development of more intense wears. Another important point in the figures of 6c, d, and e is that when w < PL, the obtained LAC values decrease with the increase of the applied normal stress levels. This is thoroughly inconsistent with the expected direct correlation between the prevailing stress levels and the intensity of the developed wears (Hamzaban et al., 2019). It seems that placing the loading weights on the surface of the abrasive sample reduces the amount of sticking clay on the container’s wall. Therefore, the percentage of clay in the part of the sample concentrated at the bottom of the container increases in the presence of loading weights, and this lead to decrease the wear amounts. The greater the applied normal load, the smaller the volume of sticking clay on the container’s wall. Hence, a descending trend appears between the applied stress levels and LAC values. The graphs of Fig. 5 do not show the increase of LAC values in the range of w < PL. Moreover, comparing Figs. 8 and 9 reveals that despite silica–kaolinite samples the sticking of the clay part does not occur in silica–talc mixtures. This implies that the provided interpretation for the abrasive behavior of silica–kaolinite mixture in the range of w < PL is correct. Clay particles and moist, are both normally present in the natural soil deposits. Based on the results, the plastic behavior of clay has a considerable effect on the abrasivity of soil mixture. The results also show that the plastic and liquid limit of the clay part can be used to predict the abrasive behavior of soil mixture, at least in the results of LCPC tests. It seems that in dry conditions, the hard and coarse grains play a major role in the abrasive capacity. However, in the presence of water, the kind, and percentage of clay particles, and in the other word,
Fig. 10. . The drainage of clay – water suspension during testing on an abrasive mixture containing 40% talc, 20% water, and under normal stress level of 1.7 kPa.
described rheological behavior of abrasive mixtures. In order to clarify the reason, Fig. 16 shows the photos of all silica–kaolinite mixtures at the end of LCPC tests, which show an increase of LAC in the range of w < PL. Some of the photos appeared in Fig. 9 as well. The common point in all photos of Fig. 16 is the sticking of the major part of the sample to the container’s wall. A more accurate look reveals that the sticking part is composed of the clay phase. However, due to the lower amount of water content, and therefore lower cohesion, the clay phase cannot sustain the whole silica grains inside. Hence, a major part of
Fig. 11. . The graphs of the consumed energy of the electromotor (E) along with LAC – w graphs in different silica–talc shares of (a) 20%, (b) 40%, (c) 60%, (d) 80% (the applied normal stress is 2.3 kPa).
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Fig. 12. . The graphs of the consumed energy of the electromotor (E) along with LAC – w graphs in different silica–kaolinite shares of (a) 20%, (b) 40%, (c) 60%, (d) 80% (the applied normal stress is 2.3 kPa).
Fig. 13. . Consumed power signals (P(t)) during the LCPC test on the dry abrasive samples of (a) silica–talc, (b) silica–kaolinite (the applied normal stress is 2.3 kPa).
the rheological behavior of the clay part is determinant. The most important moisture range is the water contents between plastic limit and liquid limit, which results in nearly zero LAC values. In geotechnical engineering, the difference between liquid and plastic limit is known as the plasticity index (PI):
PI = LL
PL
will be correct. In order to approve the correctness of the presented prediction, a new set of LCPC tests were performed using a completely different kind of clay particles. Silica–bentonite mixtures with a ratio of 80:20 were tested under different moisture contents. As Table 2 shows, the plastic and liquid limits of bentonite are respectively 40 and 328 percent, which result in a plasticity index of 288 percent. Based on weight – volume relationships, the total water content of the samples, which are relevant to plastic and liquid limits of bentonite part, are respectively 8 and 65.6 percent. Therefore, it is expected that the testing samples give very small LAC values within the water content percentages of 8–65.6. Fig. 17 shows the obtained LAC – w graph. As one can see, the dry sample results in a LAC value of 1622 g/t. However, the LCPC coefficients decrease in higher moistures and become nearly zero when the water content is greater than 10 percent.
(3)
Therefore, the bigger the plasticity index, the greater the range of water contents in which the clay part shows plastic behavior. The PI values of talc and kaolinite are 7 and 14 respectively (Table 2). Therefore, kaolinite-containing mixtures will show non-abrasive behavior in a wider range of moisture content. The graphs of Figs. 5 and 6 do not exhibit such behavior at the first look. Nevertheless, if one ignores the effect of sticking kaolinite on the container’s wall, the prediction 11
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Fig. 14. . Consumed power signals (P(t)) during the LCPC test on the abrasive samples of (a) silica–talc, (b) silica–kaolinite when PL < w < LL (the applied normal stress is 2.3 kPa).
Fig. 15. . Consumed power signals (P(t)) during the LCPC test on the abrasive samples of (a) silica–talc, (b) silica–kaolinite when w > LL (the applied normal stress is 2.3 kPa).
Increasing moisture contents up to 30 percent have no sensible effect on the LAC values, and this is completely in line with the addressed prediction. The ascending trend of LAC – w data will start in the moisture contents greater than 65.6 percent. However, adding such volume of water into the abrasive sample is not possible because of the limited volume of the sample container. Fig. 18 shows the photos of some silica–kaolinite and silica–bentonite samples at the end of LCPC tests. The relevant water contents are within the range of plastic and liquid limits and the obtained LAC values are very small. In the presented photos, the creation of a hollow space due to the rotation of the steel propeller is obvious clearly. Because of the high cohesion of the samples, the space is completely stable during the test and silica grains have not enough mobility to move toward the steel propeller and to create wear on it. The photos confirm the described rheological behavior of abrasive mixtures in the water content range of PL < w < LL. The photos of Fig. 18 reveals a great difference between the prevailing mechanism in LCPC tests and real cutting tools. Regardless of the difference between the velocity of rotating propellers and cutting tools, another important difference is due to the conditions of relative motions. In LCPC tests, the steel propeller rotates at a fixed position and abrasive particles move toward it and create wear. However, in real cutting tools, the abrasive (soil) particles have a fixed position and the cutting tool itself moves toward the ground and removes it. During performing LCPC tests, any factor which affects the mobility of particles
(i.e. the type and percentage of clay particles along with water content), can change the resulting LAC values. However, the observed trends in real cutting tools will likely be different. Therefore, when PI increases, LAC values become nearly zero in a greater range of water contents. There is no doubt that the wear on soil cutting tools and other parts of shield TBMs depends on the rheological behavior of ground. However, considering the different mechanisms of relative motions, the impact between soil particles and real cutting tools always happen, unlike LCPC tests. Hence, the general conclusion is that the wear of soil cutting tools in addition to grain size, grain shape and grain mineralogy, is highly affected by the existing water content, clay minerals type, and the percentage of clay particles. However, it seems that the LCPC test is not an appropriate testing model to investigate the correlations. In the testing models like SGAT and RUB simulator, wear parts move toward soil grains. Therefore, they will likely produce different results from those of LCPC tests. The authors believe that the results of SGAT and RUB tests will likely show more conformity with the wear of real cutting tools. However, the only way to verify these predictions is to compare the results of laboratory tests with the real wear amounts recorded on cutting tools. 4. Conclusions In this paper, the effect of plastic behavior of fine particles on the abrasivity of soil materials has been studied. Natural soil deposits
12
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Fig. 16. . The photos of silica–kaolinite mixture at the end of LCPC tests in the moisture range of w < PL (the obtained LAC values have shown an increase in the tested samples).
normally contains clay particles with different mineralogy. Moreover, slurry TBMs and sometimes EPB TBMs use bentonite for soil conditioning purposes. The rheological behavior of clay materials changes considerably with the change of dominant water content. LCPC tests were performed on the synthetic soil samples, which include different percentages and types of clay particles. Water contents and surface stress levels were changed in the testing program. The results showed that:
• •
• Adding fine particles to the abrasive mixture has considerable effect on the obtained LAC values. Moreover, the type of fine particles
13
results in different LAC values in the same mixing ratios. In the dry conditions, decreasing the size of abrasive grains decreases the importance of their hardness on the resulting wear amounts. When clay particles are added to hard and coarser silica grains, the average hardness of the testing sample decreases and therefore lower LAC values are measured in general. However, the presence of moisture in the abrasive mixtures totally changes the consequent trends. When the water content is below the soils plastic limit (w < PL), increasing water content results in lower LAC values. Increasing the moisture, clay particles not only stick together but also stick to silica
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•
• Fig. 17. . The variations of LAC against water contents for silica–bentonite (80.20) mixtures.
•
grains. Therefore, in one hand, the movement possibilities of abrasive silica particles within the soil sample decreases. On the other hand, the impact of silica particles, which are covered with a clay layer, leads to lower wear amounts. A continuous plastic matrix of clay forms when the water content is
•
between the plastic limit and liquid limit (PL < w < LL). The matrix traps the abrasive silica particles and therefore the lowest LAC values are observed in this range of moisture content. When the prevailing water content is greater than the liquid limit (w > LL), the coarse silica grains float in a viscos suspension of clay – water. Therefore, the silica grains again retrieve mobility, and they can hit to the steel propeller and cause wear. This leads to higher LAC values in this range of moisture content. Moreover, there is a direct correlation between LAC and water content in this range. Recording the power consumption of the electromotor of the testing device reveals the interaction between the abrasive mixture and the steel propeller. Adding water to the dry samples decreases the level of consumed energy. The lowest level of consumed energy is always relevant to the water contents within the range of plastic and liquid limits. Entering into the range of liquid behavior of clay part not only increases the consumed power level but also severe fluctuations appear on the real-time power signals. These changes are thoroughly in line with the recorded trends of LAC values, and they reveal the correlation between the steel – soil interaction and the rheological behavior of the abrasive sample. The cohesion of the clay particles to the sample container wall can cause inconsistent trends in the obtained LAC values. The effect is due to the change of the composition of the sample, which engages
Fig. 18. . The photos of some abrasive mixtures at the end of LCPC tests. 14
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with the steel propeller.
stress, and rotation speed impact on the abrasivity of granular soils in mechanized excavation applications. Tunn. Undergr. Space Technol. 87, 41–55. https://doi.org/ 10.1016/j.tust.2019.02.003. Hashemnejad, H., Ghafoori, M., Lashkaripour, G.R., Tariq Azali, S., 2012. Effect of geological parameters on soil abrasivity using LCPC machine for predicting LAC. Int. J. Emerg. Technol. Adv. Eng. 2, 71–75. Hashemnejad, A., Ghafoori, M., Tarigh, Azali S., 2016. Utilizing water, mineralogy and sedimentary properties to predict LCPC abrasivity coefficient. Bull. Eng. Geol. Environ. 75, 841–851. https://doi.org/10.1007/s10064-015-0779-9. Jakobsen, P.D., Bruland, A., Dahl, F., 2013a. Review and assessment of the NTNU/SINTEF soil abrasion test (SAT) for determination of abrasiveness of soil and sot ground. Tunn. Undergr. Space Technol. 37, 107–114. https://doi.org/10.1016/j.tust.2013. 04.003. Jakobsen, P.D., Langmaack, L., Dahl, F., Breivik, T., 2013b. Development of the soft ground abrasion tester (SGAT) to predict TBM tool wear, torque and thrust. Tunn. Undergr. Space Technol. 38, 398–408. https://doi.org/10.1016/j.tust.2013.07.021. Jakobsen, P.D., Lohne, J., 2013. Challenges of methods and approaches for estimating soil abrasivity in soft ground TBM tunneling. Wear 308, 166–173. https://doi.org/10. 1016/j.wear.2013.06.022. Jakobsen, P.D., Langmaack, L., Dahl, F., Breivik, T., 2012. Predicting the abrasivity of insitu like soils. Tunn. Tunn. Int. 41–44 (June). Kahraman, S., Fener, M., Käsling, H., Thuro, K., 2016. The influences of textural parameters of grains on the LCPC abrasivity of coarse-grained igneous rocks. Tunn. Undergr. Space Technol. 58, 216–223. https://doi.org/10.1016/j.tust.2016.05.011. Kahraman, S., Fener, M., Käsling, H., Thuro, K., 2018. Investigating the effect of strength on the LCPC abrasivity of igneous rocks. Geomech. Eng. 15, 805–810. https://doi. org/10.12989/gae.2018.15.2.805. Klemetsrud, K., 1985. Soil Abrasion in Shield Tunneling. Civil and Transport Engineering. NTNU, Trondheim. Köhler, M., Maidl, U., Martak, L., 2011. Abrasiveness and tool wear in shield tunneling in soil. Geomech. Tunnel. 4, 36–53. https://doi.org/10.1002/geot.201100002. Küpferle, J., Röttger, A., Alber, M., Theisen, W., 2015a. Assessment of the LCPC abrasiveness test from the view of material science. Geomech. Tunnel. 8, 211–220. https://doi.org/10.1002/geot.201500002. Küpferle, J., Röttger, A., Theisen, W., Alber, M., 2015b. Abrasivity of rock and soil. In: International Conference on Stone and Concrete Machining (3rd ICSCM). Ruhr University, Bochum, pp. 262–271. Küpferle, J., Röttger, A., Theisen, W., Alber, M., 2016. The RUB tunneling device – a newly developed test method to analyze and determine the wear of excavation tools in soils. Tunn. Undergr. Space Technol. 59, 1–6. https://doi.org/10.1016/j.tust.2016. 06.006. Mosleh, M., Alavi Gharahbagh, E., Rostami, J., 2013. Effect of relative hardness and moisture on tool wear in soil excavation operation. Wear 302, 1555–1559. https:// doi.org/10.1016/j.wear.2012.11.041. Nilsen, B., Dahl, F., Holzhäuser, J., Raleigh, P., 2007. New test methodology for estimating the abrasiveness of soils for TBM tunneling. In: Rapid Excavation and Tunneling Conference, pp. 104–116. Peila, D., Picchio, A., Chieregato, A., Barbero, M., Dal N.E., Boscaro, A., 2012. Test procedure for assessing the influence of soil conditioning for EPB tunneling on the tool wear. In: World Tunneling Congress, Bangkok, pp. 1–9. Petrica, M., Badisch, E., Peinsitt, T., 2013. Abrasive wear mechanisms and their relation to rock properties. Wear 308, 86–94. https://doi.org/10.1016/j.wear.2013.10.005. Rostami, J., Alavi Gharahbagh, E., Palomino, A.M., Mosleh, M., 2012. Development of soil abrasivity testing for soft ground tunneling using shield machines. Tunn. Undergr. Space Technol. 28, 245–256. https://doi.org/10.1016/j.tust.2011.11.007. Thuro, K., Singer, J., Kasling, H., Bauer, M., 2006. Soil abrasivity assessment using the LCPC testing device. Felsbau 24, 37–45.
• An overall review of the results shows that there are considerable
differences between the interactional mechanisms prevailing in LCPC tests and real cutting tools. Moreover, it seems that the discrepancy increases when the rheological behavior of the testing sample changes due to the presence of clay and moisture. Based on this, it can be indicated that the LCPC test is not a proper experimental setup for studying prevailing trends and correlations in the wear of soil cutting tools.
References AFNOR P18-579, Essai d’ abrasivite’ et de broyabilite’, 1990. Alavi Gharahbagh, E., Rostami, J., Palomino, A.M., 2011. New soil abrasion testing method for soft ground tunneling applications. Tunn. Undergr. Space Technol. 26, 604–613. https://doi.org/10.1016/j.tust.2011.04.003. Alavi Gharahbagh, E., Qiu, T., Rostami, J., 2013. Evaluation of granular soil abrasivity for wear on cutting tools in excavation and tunneling equipment. J. Geotech. Geoenviron. Eng. 139, 1718–1726. https://doi.org/10.1061/(ASCE)GT.1943-5606. 0000897. Alavi Gharahbagh, E., Qiu, T., Rostami, J., 2014a. Effect of water content on the abrasivity of granular soils in soft ground tunneling applications. ASCE Geo-congress 485–494. https://doi.org/10.1061/9780784413272.046. Alavi Gharahbagh, E., Rostami, J., Talebi, K., 2014b. Experimental study of the effect of conditioning on abrasive wear and torque requirement of full face tunneling machines. Tunn. Undergr. Space Technol. 41, 127–136. https://doi.org/10.1016/j.tust. 2013.12.003. ASTM D4318, 2005. Standard Test Methods for Liquid Limit, Plastic Limit, and Plasticity Index of Soils. ASTM International. Bakar, M.Z.A., Iqbal, M.M., Majeed, Y., Zahoor, M.K., Fowell, R.J., 2014. Reduced propeller speed effects on LCPC rock abrasivity test. Pak. J. Sci. 66, 25–28. Barzegari, G., Uromeihy, A., Zhao, J., 2013. A newly developed soil abrasion testing method for tunneling using shield machines. Q. J. Eng. Geol. Hydrogeol. 46, 63–74. https://doi.org/10.1144/qjegh2012-039. Barzegari, G., Uromeihy, A., Zhao, J., 2015. Parametric study of soil abrasivity for predicting wear issue in TBM tunneling project. Tunn. Undergr. Space Technol. 48, 43–57. https://doi.org/10.1016/j.tust.2014.10.010. Das, B.M., Sobhan, K., 2014. Principles of Geotechnical Engineering, eighth ed. Cengage Learning, Stamford. Drucker, P., 2011. Validity of the LCPC abrasivity coefficient through the example of a recent Danube gravel. Geomech. Tunnel. 6, 681–691. https://doi.org/10.1002/geot. 201100051. Düllmann, J., Alber, M., Plinninger, R.J., 2014. Determining soil abrasiveness by use of index tests versus using intrinsic soil parameters. Geomech. Tunnel. 7, 87–97. https://doi.org/10.1002/geot.201310028. Frenzel, C., Käsling, H., Thuro, K., 2008. Factors influencing disc cutter wear. Geomech. Tunnel. 1, 55–60. https://doi.org/10.1002/geot.200800006. Hamzaban, M.T., Memarian, H., Rostami, J., 2014a. Continuous monitoring of pin tip wear and penetration into rock surface using a new Cerchar abrasivity testing device. Rock Mech. Rock Eng. 47, 689–701. https://doi.org/10.1007/s00603-013-0397-4. Hamzaban, M.T., Memarian, H., Rostami, J., Ghasemi, H., 2014b. Study of rock–pin interaction in Cerchar abrasivity test. Int. J. Rock Mech. Min. Sci. 72, 100–108. https:// doi.org/10.1016/j.ijrmms.2014.09.007. Hamzaban, M.T., Jakobsen, P.D., Shakeri, H., Najafi, R., 2019. Water content, effective
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The effect of the plastic behavior of clay particles on LCPC abrasive coefficient
T
Mohammad-Taghi Hamzabana, , Naimeh Hosseini Tavanaa, Pål Drevland Jakobsenb, Ali Reza Bagheriyana ⁎
a b
Mining Engineering Faculty, Sahand University of Technology, Tabriz, Iran Department of Civil and Transport Engineering, NTNU, N-7491 Trondheim, Norway
ARTICLE INFO
ABSTRACT
Keywords: Mechanized excavation Abrasivity LCPC test Clay
In mechanized excavation projects, the major part of feasibility studies includes predicting the lifetime of cutting tools. Estimating the required numbers of tools for excavating a certain length of a section, under defined geologic conditions, and assessing the cost and downtimes needed for tools replacement are the other important issues in the preliminary studies of these projects. Presently, there are several experimental models used to study the abrasive capacity of soil materials in mechanized tunneling applications. In this paper, the effect of plastic behavior of clay particles on the abrasivity of soil materials was studied using the results of LCPC abrasivity tests. The results showed that the rheological behavior of abrasive samples changes considerably with the change of the clay particles mineralogy and the dominant water content. These changes have a significant effect on recorded wear amounts. Based on the obtained results, the plastic limit and the liquid limit of the clay part can be used to predict the appeared abrasive trends in LCPC tests. Moreover, during performing the LCPC tests, the consumed power of the electromotor of the testing device was recorded. The obtained power graphs confirmed the effect of the mineralogy and the water content of the clay part on the rheological and abrasive behavior of the testing samples.
1. Introduction The increasing demand for mechanized excavation machines in different civil and mining projects, has led to several studies about soil abrasivity in the last years. Various experimental setups have been used to study the abrasive capacity of soil materials in mechanized tunneling applications. Some of the most well-known models are LCPC abrasimeter (AFNOR, 1990), NTNU SAT soil abrasivity testing method (Nilsen et al., 2007; Jakobsen et al., 2013a), soil abrasivity testing device developed in Penn State University – PSU (Alavi Gharahbagh et al., 2011), soft ground abrasivity test – SGAT (Jakobsen and Lohne, 2013; Jakobsen et al., 2013b), testing procedure developed in Turin Polytechnic (Peila et al., 2012), soil abrasivity testing chamber – SATC (Barzegari et al., 2013, 2015), and RUB tunneling device (Küpferle et al., 2016). These experimental models just provide a primary indication of soil abrasivity, and they do not consider the effect of some major factors on the wear of soil cutting tools. For instance, most of the mentioned models cannot control the density, cohesion, friction angle, or moisture content of the testing sample. These parameters are determined in pre-construction geotechnical explorations. Quantifying ⁎
the effect of these parameters in order to use in a tool wear prediction model is very complicated, especially in hybrid or EPB shields (Frenzel et al., 2008). Hamzaban et al. (2014a, 2014b) have classified the effecting factors on rock abrasivity into two main groups: geological parameters relevant to rock samples and technical parameters relevant to testing procedure. A similar approach can be used for soil abrasivity. However, there are some differences between the effective factors on rock and soil abrasivity. Moreover, the applied excavation technics and cutting tools are thoroughly different in hard rock and soft ground tunneling projects. Generally, the count of the effecting parameters on soil abrasivity is more than that of rock abrasivity. For example, in the category of geological parameters, the presence of groundwater, pore pressure, and the effect of relative density has not a considerable role in the wear of rock cutting tools. Similarly, in the category of technical parameters, the face stabilizing pressures and soil conditioning additives are not used in hard rock tunneling. Moreover, the laboratory simulation of soil in-situ conditions, especially in granular soil, is very difficult. Consequently, the study of soil abrasivity and predicting the wear of soil cutting tools are more complicated than the same issues in hard rocks.
Corresponding author. E-mail address: [email protected] (M.-T. Hamzaban).
https://doi.org/10.1016/j.tust.2019.103054 Received 28 March 2019; Received in revised form 23 June 2019; Accepted 20 July 2019 0886-7798/ © 2019 Elsevier Ltd. All rights reserved.
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Table 1 . Summary of previous studies on soil abrasivity for mechanized tunneling applications. Parameter
Testing model
References
The hardness of soil grains
LCPC
Thuro et al., 2006; Köhler et al., 2011; Hashemnejad et al., 2012, 2016; Barzegari et al., 2013, 2015; Düllmann et al., 2014; Kahraman et al., 2016, 2018 Rostami et al., 2012; Mosleh et al., 2013 Jakobsen et al., 2013a Barzegari et al., 2015 Thuro et al., 2006; Drucker 2011; Barzegari et al., 2015; Hashemnejad et al., 2012, 2016; Kahraman et al., 2016 Rostami et al., 2012 Jakobsen et al., 2013a Barzegari et al., 2015 Küpferle et al., 2016 Thuro et al., 2006; Hashemnejad et al., 2012, 2016; Düllmann et al., 2014; Kahraman et al., 2016 Alavi Gharahbagh et al., 2013 Jakobsen et al., 2013a Klemetsrud, 1985 Drucker, 2011; Hashemnejad et al., 2012 Rostami et al., 2012; Alavi Gharahbagh et al., 2013, 2014a Jakobsen et al., 2013b Rostami et al., 2012 Jakobsen et al., 2013b Barzegari et al., 2015 Hamzaban et al., 2019 Rostami et al., 2012 Jakobsen et al., 2013b Hamzaban et al., 2019 Barzegari et al., 2015 Barzegari et al., 2015 Drucker, 2011; Küpferle et al., 2015a, 2015b Rostami et al., 2012; Mosleh et al., 2013; Alavi Gharahbagh et al., 2013 Klemetsrud 1985 Alavi Gharahbagh et al., 2014b Jakobsen et al., 2012, 2013b. Küpferle et al., 2016 Bakar et al., 2014; Hamzaban et al., 2019 Jakobsen et al., 2013b Küpferle et al., 2016 Rostami et al., 2012
The diameter of soil grains
The Shape and angularity of soil grains Water content
Ambient pressure level Pore Pressure Compaction Effective stress level Shear strength parameters The hardness of wear parts Conditioning additives Penetration rate Rotation speed Mechanism of engagement
PSU NTNU SAT SATC LCPC PSU NTNU SAT SATC RUB LCPC PSU NTNU SAT Ball Mill LCPC PSU SGAT PSU SGAT SATC LCPC PSU SGAT LCPC SATC SATC LCPC PSU Ball Mill PSU SGAT RUB LCPC SGAT RUB PSU
The investigations on the effect of different geological and technical factors have been the main topic of many experimental and empirical studies on the soil abrasive properties. Table 1 summarizes a list of previous investigations performed to study the effect of different factors. In the investigations presented in this research paper, the effect of plastic behavior of fine particles on the abrasivity of soil materials is studied with the LCPC test. Natural soil deposits often have a considerable amount of clay particles with different mineralogy, which is expected to influence both the abrasivity and the consistency of the soil. Moreover, slurry shields, and sometimes EPB TBMs, use bentonite for soil conditioning purposes. The rheological behavior of clay containing soils changes considerably with the change of dominant water content. It appears that the rheological changes have a significant effect on the abrasive properties of soft grounds. In addition, the effect of the plastic behavior of the clay part in the soil mixture was investigated in this study. The findings of this research paper can be used to theoretically assess how the existing clay mineralogy and amount influences the abrasivity of soil.
wear on steel due to abrasivity of rock aggregates and coarse soil grains, especially in central Europe. The abrasimeter has a 750 W electromotor to rotate a propeller. The propeller is a steel plate of 50 mm × 25 mm × 5 mm size and is made of a standard steel with a hardness of 60–75 Rockwell-B. The steel propeller is placed at a defined position in a sample container and is replaced after each test (Thuro et al., 2006). In the standard testing procedure, an air-dried soil sample with a mass of 500 ± 2 g and a particle size range of 4.0–6.3 mm is added in the sample container. The rectangular-shape propeller rotates for 5 min in the container, which is filled with testing sample. Here, the rotation speed is 4500 RPM. In order to determine the abrasivity of the soil sample, the propeller is weighted before and after the test. The LCPC abrasivity coefficient, that is LAC, is calculated as follows:
LAC = (m 0
(1)
where m0 is the mass of propeller before the test, m is the mass of propeller after the test, and M is the mass of the soil sample (=0.0005 t) (Thuro et al., 2006). In the conducted investigations, five weights were designed and made to study the impact of effective stress levels on the wear of steel propellers. The details of the design of loading weights have been published elsewhere (Hamzaban et al., 2019). The AFNOR standard recommends using XC12 steel grade with the hardness of 60–75 HRB in making propellers. However, regarding to inaccessibility to this grade of steel, the propellers were made of St-37 structural steel. The hardness of used steel parts was measured in the range of 63 ± 5 Rockwell B (HRB) that is in line with the recommended hardness in the standardized test. During a part of the experimental investigations, in addition to measure the weight loss of the steel propeller, the consumed power of
2. Testing materials and procedure LCPC abrasivity tests were applied in the studies. The central laboratory of bridges and roads1 in France has developed the test in the 1980s, and their standard of P18-579 describes the testing device (AFNOR, 1990). It was originally developed to measure rock aggregates resistance against crushing. However, it is also used to measure the 1
m)/ M
Laboratoire Central des Ponts et Chaussées. 2
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Fig. 1. . (a) 3-Phase power meter to measure the consumed power of the electromotor, (b) A recorded real-time power signal during a LCPC test on a dry crushed silica sample (size range = 4–6.3 mm with no surface load) (c) the general set up of the testing device and its accessories.
Fig. 2. . (a) The crushed silica grains, (b) The particle size distribution curve of crushed silica grains.
the electromotor was recorded. A 3-phase power meter was designed and manufactured (Fig. 1a), and it was installed parallel to the main power supply line of the testing device. Consequently, the power meter provided a real-time measurement of the consumed power of the electromotor. The output signal of the power meter was transmitted to a
data logger, and finally, the recorded power signal was saved in a PC. Fig. 1b shows an example of the recorded power signal obtained in an LCPC test performed on dry crushed silica grains (4–6.3 mm) without applying surface loads. The general set up of the testing device along with the added accessories to control testing duration time, propeller 3
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Fig. 3. . Different clay materials used in the testing program, (a) talc, (b) kaolinite, (c) bentonite.
conditions with no surface loading weights. The absence of water means that the clay parts do not show plastic behavior, and the graphs just reveal the effect of fine particles. All graphs start from the same point where the percentage of fine particles is zero. However, adding different fine particles changes the obtained LAC values at the same mixing ratios. The mixtures of crushed and fine silica grains show a quite different trends in Fig. 4. Due to the same hardness of components in these mixtures, the different abrasive samples have the same hardness. Therefore, in the graph relevant to the fine–coarse silica grains, we can just see the effect of particles size distribution. The average hardness of abrasive mixtures changes in addition to particles size distribution curves, when the different ratios of clay minerals are mixed with crushed silica grains. Consequently, different trend lines are obtained for silica – talc and silica – kaolinite mixtures. However, the trend lines for clay mixtures are more similar. As one can see from Fig. 4, pure fine particles show nearly zero LAC values. It is important that despite the significant hardness of fine silica particles, the relevant LAC values are quite small and very close to those of talc and kaolinite. This means that decreasing the size of soil particles decreases the importance of their hardness in soil abrasivity measured in the LCPC test. Figs. 5 and 6 shows the variations of LAC with the changes in water content for the different abrasive mixtures of silica–talc and silica–kaolinite, respectively. Fig. 5a and 6a are the same and show the results for pure silica samples. The authors have discussed these graphs previously (Hamzaban et al., 2019). Adding clay minerals to the abrasive samples and changing the share of clay minerals change the LAC – w curves drastically (Figs. 5b–f and 6b–f). It seems that in the presence of talc particles (Fig. 5b–f), the general trend is the decrease of LAC values with the increase of water content at the first stage. However, after passing a minimum value, LAC shows an ascending trend if the increase of water content is continued. The observed trend for silica–kaolinite abrasive mixtures is different, especially in the graphs of 6c, d, and e. LAC values show an ascending trend in the first part of these graphs. Consequently, comparing the same graphs of Figs. 5 and 6 reveals that the type of clay component affects the abrasive behavior of the tested mixtures at the same water contents. The principals of soil mechanics can describe the trends of Figs. 5 and 6. Based on the theory of consistency of fine-grained soils, at a very low moisture content, soil behaves more like a solid. When the moisture content is very high, the soil and water may flow like a liquid. Hence, on an arbitrary basis, depending on the moisture content, the behavior of soil can be divided into four basic states: solid, semisolid, plastic, and liquid, as shown in Fig. 7. The moisture content, in percent, at which the transition from solid to semisolid state takes place, is defined as the shrinkage limit (SL). The moisture content at the point of transition from semisolid to plastic state is the plastic limit (PL), and from plastic to liquid state is the liquid limit (LL) (Das and Sobhan, 2014). Considering the very low water absorption of silica particles in the abrasive samples, one can assume that the whole added water into the sample is absorbed with clay particles. Moreover, Fig. 7 shows ideally
Table 2 . Plastic limit, liquid limit, and plasticity index of different clay materials. Clay mineral type
Plastic limit (%)
Liquid limit (%)
Plasticity index (%)
bentonite kaolinite talc
40 31 22
328 45 29
288 14 7
Fig. 4. . The variations of LCPC abrasivity coefficient with the percentage of fine particles in different abrasive mixtures.
rotation speed, and record power signal are shown in Fig. 1c. In order to investigate the effect of the plasticity of fine particles on the wear capacity of soil deposits, synthetic soil samples were made with mixing the crushed angular Silica grains and clay particles. The size range of the used silica grains (Fig. 2a) was between 4.0 and 6.3 mm. Fig. 2b shows the particle size distribution curve of the silica grains. These coarse grains were mixed with three different types of clay materials: talc, kaolinite, and bentonite particles, which are shown in Fig. 3a–c respectively. The percentage of clay part in the abrasive mixture was zero, 20, 40, 60, 80, and 100. Adding different amounts of water to the different abrasive mixtures creates different plastic behaviors in the clay part. In order to study the appeared plastic behaviors accurately, Plastic and Liquid limits of clay materials were determined with Atterberg limits tests (ASTM D4318, 2005). Table 2 shows the results of these tests. LCPC tests were performed with the water contents of zero, 5, 10, 15, 20, 25, and 30 percent under the surface stress levels of zero, 1.0, 1.7, 2.3, 2.9, and 3.5 kPa. Consequently, the testing program included performing more than 470 LCPC tests. 3. Results and discussion In the first step, in order to see the effect of fine particles on the abrasive behavior of soil mixtures, the variations of LAC against the percentage of fine particles were plotted in Fig. 4. The abrasive mixtures are the combinations of crushed angular silica grains with fine silica, talc, and kaolinite. The data are the results of LCPC tests in dry 4
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Fig. 5. . The changes of LAC values with water contents under the different normal stress levels and talc shares of, (a) zero, (b) 20%, (c) 40%, (d) 60%, (e) 80%, (f) 100% (White, light grey, and dark grey backgrounds show the ranges of liquid, plastic, and semi-solid/solid behavior of clay part respectively).
how moisture content influence the stress-strain relationships of soils, which is influencing the rheology. Therefore, it seems that there is a correlation between the plastic behavior of the clay part and the results of LCPC tests, and using the water contents relevant to plastic and liquid limits, the fitted trend lines of Figs. 5 and 6 can be described. Table 2 represents the values of PL and LL for talc and kaolinite. As mentioned before, it is assumed that the clay part (talc or kaolinite) absorbs completely the added water to the sample. The horizontal axes in the graphs of Figs. 5 and 6 show the moisture content calculated based on the dry mass of whole sample (=500 g). Considering the mentioned assumption, the moisture contents can be calculated only based on the dry mass of the clay with using simple weight – volume relationships. This will be in line with the assumption that the clay part absorbs completely the added water to the testing mixture. Using this way one can calculate the water contents, which are relevant to the plastic and liquid limits of the clay part, on the horizontal axes of the graphs in Figs. 5 and 6. These values for the different talc and kaolinite shares are calculated and summarized in Table 3. The vertical lines in
Figs. 5 and 6 show the plastic and liquid limits in the abrasive mixtures. It is evident that if w < PL, the clay part behaves as a semisolid/solid material. For the range of PL < w < LL, the behavior is plastic, and finally in the range of w > LL the clay part show a liquid behavior. In Figs. 5 and 6, the mentioned behavior ranges are shown with dark grey, light grey, and white backgrounds respectively. Using the specified ranges for the behavior of the clay part in the graphs of Figs. 5 and 6, the obtained trends can easily be described. In silica–talc samples, in the range of semisolid/solid behavior (w < PL), increasing water content decreases the resulting LAC values. At the completely dry condition, silica and clay parts behave independently. The impaction of the hard silica grains to the rotating propeller creates considerable wear amounts. Adding water to the abrasive mixture, the clay particles start to cohere themselves and Silica particles. Nevertheless, due to low moisture content, a continuous matrix of clay does not create. However, a thin clay layer covers abrasive silica grains and reduces their mobility and apparent surface hardness. Consequently, LAC values decrease and the more the added water the higher the 5
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Fig. 6. . The changes of LAC values with water contents under the different normal stress levels and kaolinite shares of, (a) zero, (b) 20%, (c) 40%, (d) 60%, (e) 80%, (f) 100% (White, light grey, and dark grey backgrounds show the ranges of liquid, plastic, and semi-solid/solid behavior of clay part respectively).
Fig. 7. . Shrinkage limit, Plastic limit, and Liquid limit (Das and Sobhan, 2014). 6
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silica grains in lower viscosities leads to the appearance of an ascending trend in LAC – w data. However, the ascending trend stops at high water contents in Figs. 5b, c and 6b, c. When the percentage of clay is 20 in Figs. 5b and 6b (40% of clay particles in Figs. 5c and 6c), increasing water content beyond 15% (beyond 20% in Figs. 5c and 6c) results in a very low viscosity mixture which easily drains under the applied loading weights (Fig. 10). A careful look at the relevant photos of Figs. 8 and 9 reveals the signs of the drainage. Hence, despite the different amounts of added water, due to drainage under the same applied normal load, the moisture content of the testing sample is indeed constant, and therefore the obtained LAC values are more or less similar. However, as Figs. 8 and 9 show, increasing clay percentage beyond 40 creates such a heavy mixture, which cannot drain. Therefore, the horizontal fitted segment of LAC – w trend lines is disappeared from these samples. As mentioned in Section 2, the consumed power of the electromotor of the testing device was measured during LCPC tests. The measured data provide more information about soil – steel interaction. Using the power data recorded during the performed tests (Fig. 1b), the total consumed energy during performing a LCPC test can be calculated as follows (Petrica et al., 2013):
Table 3 . The required water contents to reach liquid and plastic limits in the different silica–talc and silica–kaolinite mixtures. Clay part content (%)
MS(C) wPL (%)
20 40 60 80 100
4.4 8.8 13.2 17.6 22
100 200 300 400 500
wLL (%)
Talc (LL = 29, PL = 22) wPL (%)
Kaolinite (LL = 45, PL = 31) wLL (%)
5.8 11.6 17.4 23.2 29
6.2 12.4 18.6 24.8 31
9 18 27 36 45
cohesion of clay particles and the lower the LAC values. When the water content is within the range between PL and LL (PL < w < LL) the clay part exhibits a plastic behavior. In this condition, a plastic matrix of clay is formed, and it traps the abrasive silica grains. Consequently, the interaction between abrasive particles and steel part is removed, and as Figs. 5 and 6 show, the lowest LAC values are obtained in this range of moisture content (the areas marked with light grey background). Passing the moisture content relevant to liquid limit (w > LL), the behavior of the clay part becomes similar to a viscous liquid in which silica particles float in a clay–water suspension. Therefore, the silica grains regain mobility and create wear on the steel propeller. The more the water content in this range the lower the viscosity of the suspension and the greater the mobility of the abrasive grains. Consequently, unlike the previous moisture ranges, there is a direct correlation between water contents and LAC values. However, when the percentage of clay part is 20 or 40, it seems that the higher water contents have no effect on the abrasivity of the testing mixtures, and LAC – w trends become horizontal. Figs. 5f and 6f reveal that pure talc and kaolinite samples, regardless of their water contents, are non-abrasive, and the LAC values are very close to zero. However, as the other graphs of Figs. 5 and 6 show, the presence of these clay particles along with abrasive grains, like silica, in wet conditions has a drastic effect on the abrasivity of the mixture and cause huge changes in the resulting LAC values. In Figs. 8 and 9, the photos of abrasive mixtures at the end of LCPC tests are shown along with the LAC – w trends, respectively for silica–talc and silica–kaolinite samples. The figures do not include the photos of dry mixtures, and the relevant applied normal stress level is 1.7 kPa. The bolded rectangles specify the samples which their water contents are in the range between PL and LL (PL < w < LL). As it mentioned before, the clay part in these samples shows a plastic behavior and results in the lowest LAC values. In the photos in the left hand of the bolded rectangles w < PL, and in the right-hand photos w > LL. Comparing the photos of these two groups clearly shows the difference between their rheological behavior. When w < PL, completely separate pieces can be recognized in the abrasive sample. In the higher water contents, due to the higher cohesion in clay phase, the pieces become greater. In these conditions, a greater volume of clay particles surrounds the silica grains and reduces the probability of direct impacts between the steel part and hard silica grains. Therefore, lower wear amounts are created and the descending trend continues until the clay part converts to an entirely plastic paste, which fully traps the silica grains. However, in this range of w, silica–kaolinite mixtures show a different behavior which will be discussed later. When w > LL, the abrasive mixture exhibits a liquid rheological behavior. In this moisture range, the more the water content the lower the viscosity of the abrasive suspension. Increasing the mobility of hard
E=
T 0
P (t ) dt
(2)
where P(t) is the power signal recorded during LCPC test, T is the time interval of the performed test (=300 s), and E is the total consumed energy during the test. Figs. 11 and 12 show the variations of energy (E) with the water content of testing samples in a group of tests, respectively for silica–talc and silica–kaolinite abrasive mixtures. The LAC – w graphs are plotted in the figures as well. Comparing the E – w graphs (dashed lines in Figs. 11 and 12) with the LAC – w graphs (bold lines in Figs. 11 and 12) reveals very good conformity between the obtained trends. This means that the higher the LAC value of the sample the greater the resistance against the motion of the steel propeller and therefore the higher the required energy (E) to rotate the propeller. Moreover, the trends of the consumed energy graphs show correlations with the different moisture content ranges that are similar to those described for LAC – w changes previously. The E – w trends reveal that rotating the steel propeller inside a dry abrasive sample needs to consume a high level of energy. This is equivalent to a high resistance against the motion of the propeller inside the sample and therefore a high degree of engagement between the steel and sample particles. The consequence of this engagement is reflected in the high levels of measured wear amounts in the relevant LAC graphs. Adding water to the abrasive samples and increasing it in the range of w < PL, leads to the coherence of clay particles and reduces the steel – soil engagement in the formed mixture. The relevant LAC values are reduced similarly. The lowest calculated E values are recorded in the range of PL < w < LL. This is entirely in line with the LAC – w trends. When the water content passes the liquid limit of the clay part, the calculated E values exhibit an ascending trend. This increase can be considered as the result of the greater degree of steel – soil engagement that again shows conformity with the increase of relevant LAC values. However, it seems that the increase of E values are smaller than LAC values. The greater increase of the recorded wear amounts is likely due to the higher mobility of silica particles when they float in a clay – water suspension. The high degree of conformity between the trends of E – w and LAC – w graphs confirms the effect of rheological behavior of testing samples on the recorded wear amounts. However, in the graphs of Fig. 12b, c, and d, a discrepancy between the trends of E – w and LAC – w is observed in the first part of the graphs, and it seems that a different
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Fig. 8. . The photos of abrasive samples at the end of the tests along with LAC – w graphs in silica–talc mixtures (the applied normal stress is 1.7 kPa).
mechanism governs in these samples. Figs. 13–15 reveal the steel – soil interaction in LCPC tests from another point of view. The figures plot the real-time consumed power signal (P(t)) during some of the LCPC tests on silica–talc and silica–kaolinite samples. Fig. 13a and b show the recorded signal in the dry silica–talc and silica–kaolinite samples respectively. The amplitude of consumed power signals changes between 400 and 500 W in silica–talc
samples and 350–400 W in silica–kaolinite mixtures. Some fluctuations are recognizable on the signals which likely reflect the effect of impacts between the steel propeller and sample grains. Fig. 14a and b shows the recorded P(t) signals when the water content of the testing samples is in the range between PL and LL. Comparing Figs. 13 and 14 reveals that when PL < w < LL, the average consumed power for rotating the steel propeller reduces to about 250 W. Moreover, the range of recorded 8
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Fig. 9. . The photos of abrasive samples at the end of the tests along with LAC – w graphs in silica–kaolinite mixtures (the applied normal stress is 1.7 kPa).
fluctuations on the P(t) signals becomes very small when the sample water content is in the range between plastic and liquid limits. This means that when the clay part of the sample behaves as a plastic medium, the steel propeller rotates in the sample much more easily with no impacts between the propeller and sample grains. Fig. 15a and b show an entirely different steel – soil interaction when w > LL. The amplitude of P(t) signals shows great sudden increases which reflect the effect of severe impacts between coarse silica grains and the steel propeller.
The P(t) signals shown in Figs. 13–15 confirm the described steel – soil interaction mechanisms and their changes in different water content ranges of w < PL, PL < w < LL, and w > LL discussed in the previous paragraphs. The silica–kaolinite mixtures in the moisture range of w < PL shows a different behavior compared to the silica–talc mixtures. As Fig. 6c, d, and e (and Fig. 12b, c, and d) show, in this range, the LAC results show an increase when the water content increases. The trend does not match with the expected descending trends based on the 9
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abrasive Silica grains segregates from the sticking clay phase and concentrates at the bottom of the testing container. Therefore, the steel propeller rotates in a part of the sample, which has more abrasive silica grains than the average of whole sample. It is evident that this leads to the development of more intense wears. Another important point in the figures of 6c, d, and e is that when w < PL, the obtained LAC values decrease with the increase of the applied normal stress levels. This is thoroughly inconsistent with the expected direct correlation between the prevailing stress levels and the intensity of the developed wears (Hamzaban et al., 2019). It seems that placing the loading weights on the surface of the abrasive sample reduces the amount of sticking clay on the container’s wall. Therefore, the percentage of clay in the part of the sample concentrated at the bottom of the container increases in the presence of loading weights, and this lead to decrease the wear amounts. The greater the applied normal load, the smaller the volume of sticking clay on the container’s wall. Hence, a descending trend appears between the applied stress levels and LAC values. The graphs of Fig. 5 do not show the increase of LAC values in the range of w < PL. Moreover, comparing Figs. 8 and 9 reveals that despite silica–kaolinite samples the sticking of the clay part does not occur in silica–talc mixtures. This implies that the provided interpretation for the abrasive behavior of silica–kaolinite mixture in the range of w < PL is correct. Clay particles and moist, are both normally present in the natural soil deposits. Based on the results, the plastic behavior of clay has a considerable effect on the abrasivity of soil mixture. The results also show that the plastic and liquid limit of the clay part can be used to predict the abrasive behavior of soil mixture, at least in the results of LCPC tests. It seems that in dry conditions, the hard and coarse grains play a major role in the abrasive capacity. However, in the presence of water, the kind, and percentage of clay particles, and in the other word,
Fig. 10. . The drainage of clay – water suspension during testing on an abrasive mixture containing 40% talc, 20% water, and under normal stress level of 1.7 kPa.
described rheological behavior of abrasive mixtures. In order to clarify the reason, Fig. 16 shows the photos of all silica–kaolinite mixtures at the end of LCPC tests, which show an increase of LAC in the range of w < PL. Some of the photos appeared in Fig. 9 as well. The common point in all photos of Fig. 16 is the sticking of the major part of the sample to the container’s wall. A more accurate look reveals that the sticking part is composed of the clay phase. However, due to the lower amount of water content, and therefore lower cohesion, the clay phase cannot sustain the whole silica grains inside. Hence, a major part of
Fig. 11. . The graphs of the consumed energy of the electromotor (E) along with LAC – w graphs in different silica–talc shares of (a) 20%, (b) 40%, (c) 60%, (d) 80% (the applied normal stress is 2.3 kPa).
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Fig. 12. . The graphs of the consumed energy of the electromotor (E) along with LAC – w graphs in different silica–kaolinite shares of (a) 20%, (b) 40%, (c) 60%, (d) 80% (the applied normal stress is 2.3 kPa).
Fig. 13. . Consumed power signals (P(t)) during the LCPC test on the dry abrasive samples of (a) silica–talc, (b) silica–kaolinite (the applied normal stress is 2.3 kPa).
the rheological behavior of the clay part is determinant. The most important moisture range is the water contents between plastic limit and liquid limit, which results in nearly zero LAC values. In geotechnical engineering, the difference between liquid and plastic limit is known as the plasticity index (PI):
PI = LL
PL
will be correct. In order to approve the correctness of the presented prediction, a new set of LCPC tests were performed using a completely different kind of clay particles. Silica–bentonite mixtures with a ratio of 80:20 were tested under different moisture contents. As Table 2 shows, the plastic and liquid limits of bentonite are respectively 40 and 328 percent, which result in a plasticity index of 288 percent. Based on weight – volume relationships, the total water content of the samples, which are relevant to plastic and liquid limits of bentonite part, are respectively 8 and 65.6 percent. Therefore, it is expected that the testing samples give very small LAC values within the water content percentages of 8–65.6. Fig. 17 shows the obtained LAC – w graph. As one can see, the dry sample results in a LAC value of 1622 g/t. However, the LCPC coefficients decrease in higher moistures and become nearly zero when the water content is greater than 10 percent.
(3)
Therefore, the bigger the plasticity index, the greater the range of water contents in which the clay part shows plastic behavior. The PI values of talc and kaolinite are 7 and 14 respectively (Table 2). Therefore, kaolinite-containing mixtures will show non-abrasive behavior in a wider range of moisture content. The graphs of Figs. 5 and 6 do not exhibit such behavior at the first look. Nevertheless, if one ignores the effect of sticking kaolinite on the container’s wall, the prediction 11
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Fig. 14. . Consumed power signals (P(t)) during the LCPC test on the abrasive samples of (a) silica–talc, (b) silica–kaolinite when PL < w < LL (the applied normal stress is 2.3 kPa).
Fig. 15. . Consumed power signals (P(t)) during the LCPC test on the abrasive samples of (a) silica–talc, (b) silica–kaolinite when w > LL (the applied normal stress is 2.3 kPa).
Increasing moisture contents up to 30 percent have no sensible effect on the LAC values, and this is completely in line with the addressed prediction. The ascending trend of LAC – w data will start in the moisture contents greater than 65.6 percent. However, adding such volume of water into the abrasive sample is not possible because of the limited volume of the sample container. Fig. 18 shows the photos of some silica–kaolinite and silica–bentonite samples at the end of LCPC tests. The relevant water contents are within the range of plastic and liquid limits and the obtained LAC values are very small. In the presented photos, the creation of a hollow space due to the rotation of the steel propeller is obvious clearly. Because of the high cohesion of the samples, the space is completely stable during the test and silica grains have not enough mobility to move toward the steel propeller and to create wear on it. The photos confirm the described rheological behavior of abrasive mixtures in the water content range of PL < w < LL. The photos of Fig. 18 reveals a great difference between the prevailing mechanism in LCPC tests and real cutting tools. Regardless of the difference between the velocity of rotating propellers and cutting tools, another important difference is due to the conditions of relative motions. In LCPC tests, the steel propeller rotates at a fixed position and abrasive particles move toward it and create wear. However, in real cutting tools, the abrasive (soil) particles have a fixed position and the cutting tool itself moves toward the ground and removes it. During performing LCPC tests, any factor which affects the mobility of particles
(i.e. the type and percentage of clay particles along with water content), can change the resulting LAC values. However, the observed trends in real cutting tools will likely be different. Therefore, when PI increases, LAC values become nearly zero in a greater range of water contents. There is no doubt that the wear on soil cutting tools and other parts of shield TBMs depends on the rheological behavior of ground. However, considering the different mechanisms of relative motions, the impact between soil particles and real cutting tools always happen, unlike LCPC tests. Hence, the general conclusion is that the wear of soil cutting tools in addition to grain size, grain shape and grain mineralogy, is highly affected by the existing water content, clay minerals type, and the percentage of clay particles. However, it seems that the LCPC test is not an appropriate testing model to investigate the correlations. In the testing models like SGAT and RUB simulator, wear parts move toward soil grains. Therefore, they will likely produce different results from those of LCPC tests. The authors believe that the results of SGAT and RUB tests will likely show more conformity with the wear of real cutting tools. However, the only way to verify these predictions is to compare the results of laboratory tests with the real wear amounts recorded on cutting tools. 4. Conclusions In this paper, the effect of plastic behavior of fine particles on the abrasivity of soil materials has been studied. Natural soil deposits
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Fig. 16. . The photos of silica–kaolinite mixture at the end of LCPC tests in the moisture range of w < PL (the obtained LAC values have shown an increase in the tested samples).
normally contains clay particles with different mineralogy. Moreover, slurry TBMs and sometimes EPB TBMs use bentonite for soil conditioning purposes. The rheological behavior of clay materials changes considerably with the change of dominant water content. LCPC tests were performed on the synthetic soil samples, which include different percentages and types of clay particles. Water contents and surface stress levels were changed in the testing program. The results showed that:
• •
• Adding fine particles to the abrasive mixture has considerable effect on the obtained LAC values. Moreover, the type of fine particles
13
results in different LAC values in the same mixing ratios. In the dry conditions, decreasing the size of abrasive grains decreases the importance of their hardness on the resulting wear amounts. When clay particles are added to hard and coarser silica grains, the average hardness of the testing sample decreases and therefore lower LAC values are measured in general. However, the presence of moisture in the abrasive mixtures totally changes the consequent trends. When the water content is below the soils plastic limit (w < PL), increasing water content results in lower LAC values. Increasing the moisture, clay particles not only stick together but also stick to silica
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•
• Fig. 17. . The variations of LAC against water contents for silica–bentonite (80.20) mixtures.
•
grains. Therefore, in one hand, the movement possibilities of abrasive silica particles within the soil sample decreases. On the other hand, the impact of silica particles, which are covered with a clay layer, leads to lower wear amounts. A continuous plastic matrix of clay forms when the water content is
•
between the plastic limit and liquid limit (PL < w < LL). The matrix traps the abrasive silica particles and therefore the lowest LAC values are observed in this range of moisture content. When the prevailing water content is greater than the liquid limit (w > LL), the coarse silica grains float in a viscos suspension of clay – water. Therefore, the silica grains again retrieve mobility, and they can hit to the steel propeller and cause wear. This leads to higher LAC values in this range of moisture content. Moreover, there is a direct correlation between LAC and water content in this range. Recording the power consumption of the electromotor of the testing device reveals the interaction between the abrasive mixture and the steel propeller. Adding water to the dry samples decreases the level of consumed energy. The lowest level of consumed energy is always relevant to the water contents within the range of plastic and liquid limits. Entering into the range of liquid behavior of clay part not only increases the consumed power level but also severe fluctuations appear on the real-time power signals. These changes are thoroughly in line with the recorded trends of LAC values, and they reveal the correlation between the steel – soil interaction and the rheological behavior of the abrasive sample. The cohesion of the clay particles to the sample container wall can cause inconsistent trends in the obtained LAC values. The effect is due to the change of the composition of the sample, which engages
Fig. 18. . The photos of some abrasive mixtures at the end of LCPC tests. 14
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with the steel propeller.
stress, and rotation speed impact on the abrasivity of granular soils in mechanized excavation applications. Tunn. Undergr. Space Technol. 87, 41–55. https://doi.org/ 10.1016/j.tust.2019.02.003. Hashemnejad, H., Ghafoori, M., Lashkaripour, G.R., Tariq Azali, S., 2012. Effect of geological parameters on soil abrasivity using LCPC machine for predicting LAC. Int. J. Emerg. Technol. Adv. Eng. 2, 71–75. Hashemnejad, A., Ghafoori, M., Tarigh, Azali S., 2016. Utilizing water, mineralogy and sedimentary properties to predict LCPC abrasivity coefficient. Bull. Eng. Geol. Environ. 75, 841–851. https://doi.org/10.1007/s10064-015-0779-9. Jakobsen, P.D., Bruland, A., Dahl, F., 2013a. Review and assessment of the NTNU/SINTEF soil abrasion test (SAT) for determination of abrasiveness of soil and sot ground. Tunn. Undergr. Space Technol. 37, 107–114. https://doi.org/10.1016/j.tust.2013. 04.003. Jakobsen, P.D., Langmaack, L., Dahl, F., Breivik, T., 2013b. Development of the soft ground abrasion tester (SGAT) to predict TBM tool wear, torque and thrust. Tunn. Undergr. Space Technol. 38, 398–408. https://doi.org/10.1016/j.tust.2013.07.021. Jakobsen, P.D., Lohne, J., 2013. Challenges of methods and approaches for estimating soil abrasivity in soft ground TBM tunneling. Wear 308, 166–173. https://doi.org/10. 1016/j.wear.2013.06.022. Jakobsen, P.D., Langmaack, L., Dahl, F., Breivik, T., 2012. Predicting the abrasivity of insitu like soils. Tunn. Tunn. Int. 41–44 (June). Kahraman, S., Fener, M., Käsling, H., Thuro, K., 2016. The influences of textural parameters of grains on the LCPC abrasivity of coarse-grained igneous rocks. Tunn. Undergr. Space Technol. 58, 216–223. https://doi.org/10.1016/j.tust.2016.05.011. Kahraman, S., Fener, M., Käsling, H., Thuro, K., 2018. Investigating the effect of strength on the LCPC abrasivity of igneous rocks. Geomech. Eng. 15, 805–810. https://doi. org/10.12989/gae.2018.15.2.805. Klemetsrud, K., 1985. Soil Abrasion in Shield Tunneling. Civil and Transport Engineering. NTNU, Trondheim. Köhler, M., Maidl, U., Martak, L., 2011. Abrasiveness and tool wear in shield tunneling in soil. Geomech. Tunnel. 4, 36–53. https://doi.org/10.1002/geot.201100002. Küpferle, J., Röttger, A., Alber, M., Theisen, W., 2015a. Assessment of the LCPC abrasiveness test from the view of material science. Geomech. Tunnel. 8, 211–220. https://doi.org/10.1002/geot.201500002. Küpferle, J., Röttger, A., Theisen, W., Alber, M., 2015b. Abrasivity of rock and soil. In: International Conference on Stone and Concrete Machining (3rd ICSCM). Ruhr University, Bochum, pp. 262–271. Küpferle, J., Röttger, A., Theisen, W., Alber, M., 2016. The RUB tunneling device – a newly developed test method to analyze and determine the wear of excavation tools in soils. Tunn. Undergr. Space Technol. 59, 1–6. https://doi.org/10.1016/j.tust.2016. 06.006. Mosleh, M., Alavi Gharahbagh, E., Rostami, J., 2013. Effect of relative hardness and moisture on tool wear in soil excavation operation. Wear 302, 1555–1559. https:// doi.org/10.1016/j.wear.2012.11.041. Nilsen, B., Dahl, F., Holzhäuser, J., Raleigh, P., 2007. New test methodology for estimating the abrasiveness of soils for TBM tunneling. In: Rapid Excavation and Tunneling Conference, pp. 104–116. Peila, D., Picchio, A., Chieregato, A., Barbero, M., Dal N.E., Boscaro, A., 2012. Test procedure for assessing the influence of soil conditioning for EPB tunneling on the tool wear. In: World Tunneling Congress, Bangkok, pp. 1–9. Petrica, M., Badisch, E., Peinsitt, T., 2013. Abrasive wear mechanisms and their relation to rock properties. Wear 308, 86–94. https://doi.org/10.1016/j.wear.2013.10.005. Rostami, J., Alavi Gharahbagh, E., Palomino, A.M., Mosleh, M., 2012. Development of soil abrasivity testing for soft ground tunneling using shield machines. Tunn. Undergr. Space Technol. 28, 245–256. https://doi.org/10.1016/j.tust.2011.11.007. Thuro, K., Singer, J., Kasling, H., Bauer, M., 2006. Soil abrasivity assessment using the LCPC testing device. Felsbau 24, 37–45.
• An overall review of the results shows that there are considerable
differences between the interactional mechanisms prevailing in LCPC tests and real cutting tools. Moreover, it seems that the discrepancy increases when the rheological behavior of the testing sample changes due to the presence of clay and moisture. Based on this, it can be indicated that the LCPC test is not a proper experimental setup for studying prevailing trends and correlations in the wear of soil cutting tools.
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