Yu et al 2023d - Revision history

Rimni: /* References */

2023-11-14T09:24:53Z

‎References

Pp00 at 02:48, 14 November 2023

2023-11-14T02:48:23Z

Pp00 at 01:24, 14 November 2023

2023-11-14T01:24:17Z

Rimni at 14:59, 13 November 2023

2023-11-13T14:59:21Z

Rimni at 13:31, 13 November 2023

2023-11-13T13:31:29Z

Rimni: /* 5. Conclusions */

2023-11-13T13:14:55Z

‎5. Conclusions

Rimni at 13:14, 13 November 2023

2023-11-13T13:14:30Z

Rimni at 13:12, 13 November 2023

2023-11-13T13:12:53Z

Rimni at 13:12, 13 November 2023

2023-11-13T13:12:09Z

Rimni: /* 4.2.2 Influence of feed particle size on morphological characteristics of crushed rock */

2023-11-13T13:11:00Z

‎4.2.2 Influence of feed particle size on morphological characteristics of crushed rock

@@ Line 657: / Line 657: @@
 [14] Höving S., Neuendorf L., Betting T., Kockmann N. Determination of particle size distributions of bulk samples using micro-computed tomography and artificial intelligence. Materials, 16(3):1002, 2023.
-[15]  Lin yuke,Wu mengyao,Wang ping. Field test and analysis of multiple vibration-damped track structures for 120 km/h subway[J]. Railway Standard Design,2018,62(02):67-71.
+[15]  Lin Y., Wu M., Wang P. Field test and analysis of multiple vibration-damped track structures for 120 km/h subway. Railway Standard Design, 62(02):67-71, 2018.
 [16] Guan Z.,  He Y., Gao X., Den T. 2D shape characteristic and the clump reconstruction of gravel particle in granite residual soil. Journal of Water Resources and Architectural Engineering, (04):4-10, 2021.
-[17] Ye Jia-bing, Zhang Jia-fa, Zou Wei-lie. Influences of grain shape on pore characteristics of filled breakstone aggregate[J]. Rock and Soil Mechanics, 2018, 39(12): 4457-4467.
+[17] Ye J., Zhang J., Zou W. Influences of grain shape on pore characteristics of filled breakstone aggregate. Rock and Soil Mechanics, 39(12):4457-4467, 2018.

@@ Line 624: / Line 624: @@
 ==Acknowledgments==
-This project is funded by Fujian University of Technology and is a scientific and technological project of Fujian University of Technology,Project No. GY-Z220201. University-Industry Collaboration Program, Project No. 2020N5015. Key Research and Industrial Projects of Technological Innovation in Fujian Province (School-Enterprise Joint Category), Project No. 2023XQ002.
+This project is funded by Fujian University of Technology for the Fujian University of Technology Science and Technology Project, Project No. GY-Z220201. Agricultural University Industry-University Cooperation Project, Project No. 2020N5015.  Key Research and Industrialization Project of Technological Innovation in Fujian Province (University-Enterprise Joint Category), Project No. 2023XQ002.
 ==References==

@@ Line 198: / Line 198: @@
 A series of indexes for evaluating the two-dimensional shape parameters of particles have been used in previous research [15-16].
-Ye [17] selected three representative particle shape evaluation parameters for research. The length-width ratio, flatness, and sphericity can sensitively reflect the degree of deviation from spherical particles and can be preferentially used as particle shape evaluation parameters.
+Ye Jiabing et al.[17] selected three representative particle shape evaluation parameters for research. The length-width ratio, flatness, and sphericity can sensitively reflect the degree of deviation from spherical particles and can be preferentially used as particle shape evaluation parameters.
 ===3.4 Angularity===
@@ Line 624: / Line 624: @@
 ==Acknowledgments==
-This study was jointly funded by the Department of Finance of Fujian Province and the Department of Science and Technology of Fujian Province under Grant No. 2022L3014. and the Science and Technology Program of Fujian Province under Grant No. 2020N5015.
+This project is funded by Fujian University of Technology and is a scientific and technological project of Fujian University of Technology,Project No. GY-Z220201. University-Industry Collaboration Program, Project No. 2020N5015. Key Research and Industrial Projects of Technological Innovation in Fujian Province (School-Enterprise Joint Category), Project No. 2023XQ002.
 ==References==
@@ Line 657: / Line 657: @@
 [14] Höving S., Neuendorf L., Betting T., Kockmann N. Determination of particle size distributions of bulk samples using micro-computed tomography and artificial intelligence. Materials, 16(3):1002, 2023.
-[15]  Lin Y.-k. Two-dimensional information identification and reconstruction of track ballast. Southwest Jiaotong University Master Degree Thesis, 2018. https://kns.cnki.net/kcms2/article/abstract?v=nmPmjihQfLtNDltkS9F0EWjKaC5Ttkamc4Sh8hOtA9qi9PQ9KSAAn6Z1FOI18vJxaPQ7V8HdE9eCw3Am8UuxpQ-e4ORzKn43u5CDYC3O8Iog17nktqyykysylYfQyn2q7lK19_qxZvM=&uniplatform=NZKPT&language=CHS
+[15]  Lin yuke,Wu mengyao,Wang ping. Field test and analysis of multiple vibration-damped track structures for 120 km/h subway[J]. Railway Standard Design,2018,62(02):67-71.
 [16] Guan Z.,  He Y., Gao X., Den T. 2D shape characteristic and the clump reconstruction of gravel particle in granite residual soil. Journal of Water Resources and Architectural Engineering, (04):4-10, 2021.
-[17] Ye J. Evaluation of breakstone grain shape and preliminary studies of its influence on the permeability.  Changjiang River Scientific Research Institute Master Degree Thesis, 2015. https://kns.cnki.net/kcms2/article/abstract?v=nmPmjihQfLt8ibB--kNGSETEEE2-dIegHTocR4qz8YJ7NcdXZk8ge5YwuVmCJErG2UNOsGMMkYXNltUUYM_PK5gLtYCW7-sT7B3fGKqEu4DBc9GDd3P_ZczgO76wSNo1HZOeLDpNFzs=&uniplatform=NZKPT&language=CHS
+[17] Ye Jia-bing, Zhang Jia-fa, Zou Wei-lie. Influences of grain shape on pore characteristics of filled breakstone aggregate[J]. Rock and Soil Mechanics, 2018, 39(12): 4457-4467.

@@ Line 627: / Line 627: @@
 ==References==
 [1] Hamzeloo E., Massinaei M., Mehrshad N. Estimation of particle size distribution on an industrial conveyor belt using image analysis and neural networks. Powder technology, 261:185-190, 2014. https://doi.org/10.1016/j.powtec.2014.04.038
@@ Line 644: / Line 645: @@
 [8] Chen H., Tang L., Chen J., Xu X.-R. Study on measurement technique of sediment particle size base on RGB image. Journal of Sediment Research, 01:25-29, 2015.
-[9] Yonghao Y, Zuoan W, Yulong C, et al. Study on the shapes of tailings particles based on microscopy and image processing technologies[J]. Chin. J. Rock Mechan. Engin, 2017, 36: 3689-3695.
+[9] Yang Y., Wei Z., Chen Y., Ren B. Study on the shapes of tailings particles based on microscopy and image processing technologies. Chin. J. Rock Mechan. Engin, S1:3689-3695, 2017.
-[10] Li Z, Ye Y, Tong X, et al. Study on the Mechanism of Particle Breakage under New Composite Loads[J]. Journal of Engineering and Technological Sciences, 2019, 51(2).
+[10] Li Z., Ye Y., Tong X., Li K. Study on the mechanism of particle breakage under new composite loads. Journal of Engineering and Technological Sciences, 51(2):231-250, 2019.
-[11] CHEN J, ZHANG Z, XU W, et al. Quantitative method of shape parameters of mineral particles based on image processing[J]. Journal of Engineering Geology, 2021, 29(1): 59-68.
+[11] Chen J., Zhang Z., Xu W., Li L. Quantitative method of shape parameters of mineral particles based on image processing. Journal of Engineering Geology, 29(1):59-68, 2021.
-[12] Li Zhang, Maoxiang Chu, Xin Deng,et al. Graph-based detection technology for mineral grains image. Journal of Hefei University of Technology(Natural Science) ,2021,44 (09),1193-1197+1209.
+[12] Zhang L., Chu M., Deng X., Chen Z. Graph-based detection technology for mineral grains image. Journal of Hefei University of Technology (Natural Science), 44(09):1193-1197+1209, 2021.
-[13] Wu M, Wang J. Constitutive modeling of natural sands using a deep learning approach accounting for particle shape effects[J]. Powder Technology, 2022, 404: 117439.
+[13] Wu M., Wang J. Constitutive modeling of natural sands using a deep learning approach accounting for particle shape effects. Powder Technology, 404:117439, 2022.
-[14] Höving S, Neuendorf L, Betting T, et al. Determination of Particle Size Distributions of Bulk Samples Using Micro-Computed Tomography and Artificial Intelligence[J]. Materials, 2023, 16(3): 1002.
+[14] Höving S., Neuendorf L., Betting T., Kockmann N. Determination of particle size distributions of bulk samples using micro-computed tomography and artificial intelligence. Materials, 16(3):1002, 2023.
-[15] Yu-ke Lin.(2018).Two-dimensional information identification and reconstruction of track ballast(Southwest Jiaotong University Master Degree Thesis).https://kns.cnki.net/kcms2/article/abstract?v=nmPmjihQfLtNDltkS9F0EWjKaC5Ttkamc4Sh8hOtA9qi9PQ9KSAAn6Z1FOI18vJxaPQ7V8HdE9eCw3Am8UuxpQ-e4ORzKn43u5CDYC3O8Iog17nktqyykysylYfQyn2q7lK19_qxZvM=&uniplatform=NZKPT&language=CHS
+[15]  Lin Y.-k. Two-dimensional information identification and reconstruction of track ballast. Southwest Jiaotong University Master Degree Thesis, 2018. https://kns.cnki.net/kcms2/article/abstract?v=nmPmjihQfLtNDltkS9F0EWjKaC5Ttkamc4Sh8hOtA9qi9PQ9KSAAn6Z1FOI18vJxaPQ7V8HdE9eCw3Am8UuxpQ-e4ORzKn43u5CDYC3O8Iog17nktqyykysylYfQyn2q7lK19_qxZvM=&uniplatform=NZKPT&language=CHS
-[16] Zhenchang Guan, Yajun He, Xiang Gao,et al.(2021). 2D Shape Characteristic and the Clump Reconstruction of Gravel Particle in Granite Residual Soil. Journal of Water Resources and Architectural Engineering (04),1-7.
+[16] Guan Z.,  He Y., Gao X., Den T. 2D shape characteristic and the clump reconstruction of gravel particle in granite residual soil. Journal of Water Resources and Architectural Engineering, (04):4-10, 2021.
-[17] Jiabing Ye.(2015). Evaluation of Breakstone Grain Shape and Preliminary Studies of its Influence on the Permeability (Changjiang River Scientific Research Institute Master Degree Thesis ).https://kns.cnki.net/kcms2/article/abstract?v=nmPmjihQfLt8ibB--kNGSETEEE2-dIegHTocR4qz8YJ7NcdXZk8ge5YwuVmCJErG2UNOsGMMkYXNltUUYM_PK5gLtYCW7-sT7B3fGKqEu4DBc9GDd3P_ZczgO76wSNo1HZOeLDpNFzs=&uniplatform=NZKPT&language=CHS
+[17] Ye J. Evaluation of breakstone grain shape and preliminary studies of its influence on the permeability.  Changjiang River Scientific Research Institute Master Degree Thesis, 2015. https://kns.cnki.net/kcms2/article/abstract?v=nmPmjihQfLt8ibB--kNGSETEEE2-dIegHTocR4qz8YJ7NcdXZk8ge5YwuVmCJErG2UNOsGMMkYXNltUUYM_PK5gLtYCW7-sT7B3fGKqEu4DBc9GDd3P_ZczgO76wSNo1HZOeLDpNFzs=&uniplatform=NZKPT&language=CHS

@@ Line 627: / Line 627: @@
 ==References==
-# Hamzeloo E, Massinaei M, Mehrshad N. Estimation of particle size distribution on an industrial conveyor belt using image analysis and neural networks[J]. Powder technology, 2014, 261: 185-190. https://doi.org/10.1016/j.powtec.2014.04.038
-# Chen A L, Chen B Z, Feng C A. Image analysis algorithm and verification for on-line molecular sieve size and shape inspection[J]. Advanced Powder Technology, 2014, 25(2): 508-513. https://doi.org/10.1016/j.apt.2013.08.004
+[1] Hamzeloo E., Massinaei M., Mehrshad N. Estimation of particle size distribution on an industrial conveyor belt using image analysis and neural networks. Powder technology, 261:185-190, 2014. https://doi.org/10.1016/j.powtec.2014.04.038
-# Jug J, Strelec S, Gazdek M, et al. Fragment size distribution of blasted rock mass[C]//IOP Conference series: earth and environmental science. IOP Publishing, 2017, 95(4): 042013.
-# Yang J, Chen S. An online detection system for aggregate sizes and shapes based on digital image processing[J]. Mineralogy and Petrology, 2017, 111(1): 135-144.https://doi.org/10.1007/s00710-016-0458-y
+[2] Chen A.L., Chen B.Z., Feng C.A. Image analysis algorithm and verification for on-line molecular sieve size and shape inspection. Advanced Powder Technology, 25(2):508-513, 2014. https://doi.org/10.1016/j.apt.2013.08.004
-# Zheng J, Hryciw R D. Soil particle size and shape distributions by stereophotography and image analysis[J]. Geotech. Test. J, 2017, 40(2): 317-328.
-# Shehu S A, Yusuf K O, Hashim M H M. Comparative study of WipFrag image analysis and Kuz-Ram empirical model in granite aggregate quarry and their application for blast fragmentation rating[J]. Geomechanics and Geoengineering, 2022, 17(1): 197-205.
+[3] Jug J., Strelec S., Gazdek M., Kavur B. Fragment size distribution of blasted rock mass. IOP Conference Series: Earth and Environmental Science. IOP Publishing, 95(4):042013, 2017.
-# Huang-Yi,W. & Luo-Jian,Y.(2022).Study on the crushing mechanism and parameters of the two-flow crusher. Applied Mathematics and Nonlinear Sciences,7(2) 875-890. https://doi.org/10.2478/amns.2021.2.00172
-# Chen Hong, Tang Limo, Chen Jun, etc.;State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering,Hohai University;Study on measurement technique of sediment particle size base on RGB image[J].Journal of Sediment Research,2015,01:25-29
+[4] Yang J., Chen S. An online detection system for aggregate sizes and shapes based on digital image processing. Mineralogy and Petrology, 111(1):135-144, 2017. https://doi.org/10.1007/s00710-016-0458-y
-# Yonghao Y, Zuoan W, Yulong C, et al. Study on the shapes of tailings particles based on microscopy and image processing technologies[J]. Chin. J. Rock Mechan. Engin, 2017, 36: 3689-3695.
-# Li Z, Ye Y, Tong X, et al. Study on the Mechanism of Particle Breakage under New Composite Loads[J]. Journal of Engineering and Technological Sciences, 2019, 51(2).
+[5] Zheng J., Hryciw R.D. Soil particle size and shape distributions by stereophotography and image analysis. Geotech. Test. J, 40(2):317-328, 2017.
-# CHEN J, ZHANG Z, XU W, et al. Quantitative method of shape parameters of mineral particles based on image processing[J]. Journal of Engineering Geology, 2021, 29(1): 59-68.
-# Li Zhang, Maoxiang Chu, Xin Deng,et al. Graph-based detection technology for mineral grains image. Journal of Hefei University of Technology(Natural Science) ,2021,44 (09),1193-1197+1209.
+[6]  Shehu S.A., Yusuf K.O., Hashim M.H.M. Comparative study of WipFrag image analysis and Kuz-Ram empirical model in granite aggregate quarry and their application for blast fragmentation rating. Geomechanics and Geoengineering, 17(1):197-205, 2022.
-# Wu M, Wang J. Constitutive modeling of natural sands using a deep learning approach accounting for particle shape effects[J]. Powder Technology, 2022, 404: 117439.
-# Höving S, Neuendorf L, Betting T, et al. Determination of Particle Size Distributions of Bulk Samples Using Micro-Computed Tomography and Artificial Intelligence[J]. Materials, 2023, 16(3): 1002.
+[7] Huang-Yi W., Luo-Jian Y .Study on the crushing mechanism and parameters of the two-flow crusher. Applied Mathematics and Nonlinear Sciences, 7(2):875-890, 2022. https://doi.org/10.2478/amns.2021.2.00172
-# Yu-ke Lin.(2018).Two-dimensional information identification and reconstruction of track ballast(Southwest Jiaotong University Master Degree Thesis).https://kns.cnki.net/kcms2/article/abstract?v=nmPmjihQfLtNDltkS9F0EWjKaC5Ttkamc4Sh8hOtA9qi9PQ9KSAAn6Z1FOI18vJxaPQ7V8HdE9eCw3Am8UuxpQ-e4ORzKn43u5CDYC3O8Iog17nktqyykysylYfQyn2q7lK19_qxZvM=&uniplatform=NZKPT&language=CHS
-# Zhenchang Guan, Yajun He, Xiang Gao,et al.(2021). 2D Shape Characteristic and the Clump Reconstruction of Gravel Particle in Granite Residual Soil. Journal of Water Resources and Architectural Engineering (04),1-7.
+[8] Chen H., Tang L., Chen J., Xu X.-R. Study on measurement technique of sediment particle size base on RGB image. Journal of Sediment Research, 01:25-29, 2015.
-# Jiabing Ye.(2015). Evaluation of Breakstone Grain Shape and Preliminary Studies of its Influence on the Permeability (Changjiang River Scientific Research Institute Master Degree Thesis ).https://kns.cnki.net/kcms2/article/abstract?v=nmPmjihQfLt8ibB--kNGSETEEE2-dIegHTocR4qz8YJ7NcdXZk8ge5YwuVmCJErG2UNOsGMMkYXNltUUYM_PK5gLtYCW7-sT7B3fGKqEu4DBc9GDd3P_ZczgO76wSNo1HZOeLDpNFzs=&uniplatform=NZKPT&language=CHS

@@ Line 619: / Line 619: @@
 The authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers' bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements) or nonfinancial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.
-''''Data Availability'''
+'''Data Availability'''
 The data will be provided upon request and can be used without any conflict of interest.

@@ Line 601: / Line 601: @@
 |}
-==5 Conclusion==
+==5. Conclusions==
-<big>An imaging approach was used to detect the crushing effect of rock particles. The influence of loading mode and feeding particle size on the degree of rock crushing and the influence of rock morphology after crushing are analyzed and the corresponding experimental study is carried out, the main conclusions are as follows:</big>
+An imaging approach was used to detect the crushing effect of rock particles. The influence of loading mode and feeding particle size on the degree of rock crushing and the influence of rock morphology after crushing are analyzed and the corresponding experimental study is carried out, the main conclusions are as follows:
-<big>(1) Under a shear load, the crushing ratio decreases from 1.881 to 1.772. Under extrusion, the crushing ratio increases from 5.55 to 6.96.</big>
+(1) Under a shear load, the crushing ratio decreases from 1.881 to 1.772. Under extrusion, the crushing ratio increases from 5.55 to 6.96.
-<big>(2) Under extrusion, the angularity shows an upward trend, with the highest value of 1.04301. Roundness first decreases and then increases with an inflection point of 2.23. The overall profile coefficient first increases and then decreases, and the inflection point is 0.675. Under shear loading, angularity first decreases and then rises with an inflection point of 1.0404. Roundness also decreases first and then increases with an inflection point of 2.03. In contrast, the overall profile coefficient rises first and then falls, showing an approximately symmetrical inflection point of 0.7028.</big>
+(2) Under extrusion, the angularity shows an upward trend, with the highest value of 1.04301. Roundness first decreases and then increases with an inflection point of 2.23. The overall profile coefficient first increases and then decreases, and the inflection point is 0.675. Under shear loading, angularity first decreases and then rises with an inflection point of 1.0404. Roundness also decreases first and then increases with an inflection point of 2.03. In contrast, the overall profile coefficient rises first and then falls, showing an approximately symmetrical inflection point of 0.7028.
-<big>(3)</big> <big>Under a shear load, when the inlet particle size is between 9.5mm and 16mm, rocks composed of different materials have obvious differences. Under these conditions, the crushing ratio of limestone is 1.915, and the sand formation rate is 2.89%. Under extrusion, when the inlet particle size is between 9.5mm and 16mm, there are obvious variations between rocks composed of different materials; in particular, when the inlet particle size of granite is between 16mm and 19mm, the crushing ratio is 7.21, and the sand formation rate is 11%.</big>
+(3) Under a shear load, when the inlet particle size is between 9.5mm and 16mm, rocks composed of different materials have obvious differences. Under these conditions, the crushing ratio of limestone is 1.915, and the sand formation rate is 2.89%. Under extrusion, when the inlet particle size is between 9.5mm and 16mm, there are obvious variations between rocks composed of different materials; in particular, when the inlet particle size of granite is between 16mm and 19mm, the crushing ratio is 7.21, and the sand formation rate is 11%.
-<big>(4) The analysis of the morphological characteristics of the broken rock shows that the parameters of granite with a grain size between 9.5mm and 16mm tend to increase: the angularity is 1.055, the roundness is 2.06, and the overall profile coefficient is 0.7001. Under extrusion, rock composed of different materials changes from 9.6mm to 16mm. The angularity, roundness and overall profile coefficient, which have a great influence on the morphological characteristics of broken rock, are 1.046, 2.33 and 1.9, respectively.</big>
+(4) The analysis of the morphological characteristics of the broken rock shows that the parameters of granite with a grain size between 9.5mm and 16mm tend to increase: the angularity is 1.055, the roundness is 2.06, and the overall profile coefficient is 0.7001. Under extrusion, rock composed of different materials changes from 9.6mm to 16mm. The angularity, roundness and overall profile coefficient, which have a great influence on the morphological characteristics of broken rock, are 1.046, 2.33 and 1.9, respectively.
-<big>It shows that the image-based detection system for detecting the effect of rock particle breakage has high applicability and credibility, and has the advantages of real-time and stability, which can provide a basis for the follow-up research on intelligent mine construction and equipment optimization, and is worthy of further popularization and application.</big>
+It shows that the image-based detection system for detecting the effect of rock particle breakage has high applicability and credibility, and has the advantages of real-time and stability, which can provide a basis for the follow-up research on intelligent mine construction and equipment optimization, and is worthy of further popularization and application.
-<big>Declaration of Competing Interest</big>
+'''Declaration of Competing Interest'''
-<big>The authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers' bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements) or nonfinancial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.</big>
+The authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers' bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements) or nonfinancial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.
-<big>Data Availability</big>
+''''Data Availability'''
-<big>The data will be provided upon request and can be used without any conflict of interest.</big>
+==Acknowledgments==
-−
-<big>Acknowledgments</big>
 This study was jointly funded by the Department of Finance of Fujian Province and the Department of Science and Technology of Fujian Province under Grant No. 2022L3014. and the Science and Technology Program of Fujian Province under Grant No. 2020N5015.

← Older revision		Revision as of 13:12, 13 November 2023
Line 564:		Line 564:
	\| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"\| '''Figure 20'''. Gray‒greenstone extrusion		\| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"\| '''Figure 20'''. Gray‒greenstone extrusion
	\|}		\|}
−
−	~~{\| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"~~
−	~~\|-style="background:white;"~~
−	~~\|align="center" \|~~
−	{\|
−	\|+
−	~~{\| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"~~
−	~~\|-style="background:white;"~~
−	~~\|style="text-align: center;padding:10px;"\| [[File:Image24.png\|276x276px]]~~
−	\|-
−	~~\| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"\| '''Figure 19'''. Gray‒green rock shear~~
−	\|}
−	\|
−	~~{\| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"~~
−	~~\|-style="background:white;"~~
−	~~\|style="text-align: center;padding:10px;"\| [[File:Image25.png\|258x258px]]~~
−	\|-
−	~~\| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"\| '''Figure 20'''. Gray‒greenstone extrusion~~
−	\|}
−	\|}
−	\|}
−
−

@@ Line 576: / Line 576: @@
 | style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"| '''Figure 19'''. Gray‒green rock shear
 |}
-|+
-<div id='img-20'></div>
 {| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"
 |-style="background:white;"
@@ Line 583: / Line 582: @@
 |-
 | style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"| '''Figure 20'''. Gray‒greenstone extrusion
 |}
 |}

← Older revision		Revision as of 13:11, 13 November 2023
Line 564:		Line 564:
	\| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"\| '''Figure 20'''. Gray‒greenstone extrusion		\| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"\| '''Figure 20'''. Gray‒greenstone extrusion
	\|}		\|}
		+
		+	{\| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"
		+	\|-style="background:white;"
		+	\|align="center" \|
		+	{\|
		+	\|+
		+	{\| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"
		+	\|-style="background:white;"
		+	\|style="text-align: center;padding:10px;"\| [[File:Image24.png\|276x276px]]
		+	\|-
		+	\| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"\| '''Figure 19'''. Gray‒green rock shear
		+	\|}
		+	\|+
		+	<div id='img-20'></div>
		+	{\| class="wikitable" style="margin: 0em auto 0.1em auto;border-collapse: collapse;width:auto;"
		+	\|-style="background:white;"
		+	\|style="text-align: center;padding:10px;"\| [[File:Image25.png\|258x258px]]
		+	\|-
		+	\| style="background:#efefef;text-align:left;padding:10px;font-size: 85%;"\| '''Figure 20'''. Gray‒greenstone extrusion
		+	\|}
		+	\|}
		+
		+