Xls Uscs Soil Classification Homework

We created the USCS Calculator for those of you that classify soil according to the ASTM Visual-Manual Procedure (ASTM-D2488) and record only the percentage of gravel, sand, and fines in the field, without the soil group name and symbol. The USCS Calculator allows you to determine the soil group name and symbol from your field data, for use in soil descriptions when preparing boring and test pit logs. Students and young professionals are welcome to use the USCS Calculator for learning the first part of this soil classification procedure online. The USCS Calculator is the core of our Pro Soil Logging Functionality.

USCS Calculator - Quick Start Instructions:

  1. Tap on, or move the slider to, the percentage for each Gravel, Sand, and Fines (Sum=100%).
  2. In the fourth row, select the Grading, Grading+Fines Type, or Fines Type button(s).
  3. The soil group name and symbol will appear in the window at the top.
  4. Press the Clear button to reset the calculator and enter another soil sample.


USCS Calculator - Learn the ASTM Visual-Manual Procedure:

  1. Of the fraction of the soil smaller than 3 in. (75 mm), estimate and note the percentage, by dry weight, of the gravel, sand, and fines (Section 12.3). Enter the percentage of each fraction using the slider bars.
  2. The percentages shall be estimated to the closest 5 %. The percentages of gravel, sand, and fines must add up to 100 % (Section 12.3.1).
  3. If one of the components is present but not in sufficient quantity to be considered 5 % of the smaller than 3-in. (75-mm) portion, indicate its presence by the term trace, for example, trace of fines. A trace is not to be considered in the total of 100 % for the components (Section 12.3.2).

The soil is fine grained if it contains 50 % or more fines (Section 13.1). Perform the field tests described in Section 14 and, based on Table 12 (Identification of Inorganic Fine-Grained Soils from Manual Tests), select the appropriate Fines Type button.

The soil is coarse grained if it contains less than 50 % fines (Section 13.2). Based on the percentage of fines, select the appropriate Grading (Fines ≤ 5%), Grading and Fines Type (Fines = 10%), or Fines Type (Fines = 15-45%) button(s).

To use the calculator for another soil sample, press the Clear button.

If you have any comments about the usefulness of this tool or suggestions for improving it, please feel to contact us.

To try out our full logging software with this functionality, click on  TRY DEMO , otherwise Sign Up and start using this functionality regularly when logging and creating boring logs.


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Soil Classification Through Sieve and Hydrometer Analysis, and the Atterberg Limits Test Prepared for: Dr. Andre Unger, P.Eng University of Waterloo Waterloo, ON. Prepared by: Kyle Pellerin ######## ######## ### ######## March 25, 2013 March 25, 2013 Andre Unger, P.Eng Department of Earth and Environmental Sciences University of Waterloo Waterloo ON. N2L 3G1 Dear Dr. Unger, Enclosed is our report titled “Soil Classification Through Sieve and Hydrometer Analysis, and the Atterberg Limits Test”. This report was written in collaboration by Kyle Pellerin and ####### ###. The purpose of this report is to classify the soil samples provided by the Earth Engineering laboratory sessions. The samples were tested through Sieve, Hydrometer Analysis and the Atterberg Limit Test. References can be found for classification and other purposes. Anne Allen and Atena Pirayeh are acknowledged for assistance in performing the tests on the soil samples. Sincerely, Kyle Pellerin ######## ### ######## ######## 2 Table of Contents 1.0 Introduction ........................................................................................................................................ 4 2.0 Procedure ............................................................................................................................................. 4 3.0 Discussion ............................................................................................................................................... 5 3.1 Sieve Analysis ..................................................................................................................................... 5 3.2 Hydrometer Analysis .......................................................................................................................... 7 3.3 Atterberg Limits Test .......................................................................................................................... 9 4.0 Conclusion ............................................................................................................................................ 11 5.0 References ............................................................................................................................................ 12 Appendix A ................................................................................................................................................. 13 Appendix B.................................................................................................................................................. 20 Appendix C.................................................................................................................................................. 21 List of Tables Table 1: Determination of D Values & Coefficients for Coarse and Fine Gradation ....................... 6 Table 2: Determination of D Values & Coefficients for Hydrometer Analysis ......................................... 8 List of Figures Figure 1: Grain Size Distribution .................................................................................................... 6 Figure 2: Hydrometer Analysis Particle Distribution ..................................................................... 8 Figure 3: Liquid Limit of Sample ................................................................................................. 10 3 1.0 Introduction Soil sampling and soil classification are the first steps to most civil engineering design. Technical information such as particle distribution and plasticity index are critical for understanding the properties of soil. These properties are crucial for civil engineering design all over the world. The purpose of this report is to classify the soils in question under the Unified Soil Classification System (USCS). The scope of the analyses performed is limited to the data retrieved from each analysis and within the USCS. The classification of unconsolidated soil must be done through two standard testing procedures. These are Sieve and Hydrometer Analysis. This report utilizes both of these analyses. The results were then compared to the USCS. Another soil property that cause great problem to engineering design is the soil‟s ability to consolidate or expand. To determine this behaviour, the Atterberg Limits Test was used to determine the soil sample‟s plastic and liquid limits. 2.0 Procedure The procedures for the Atterberg Limits, Sieve and Hydrometer analysis that were conducted in the labs were prepared by Anne Allen. Refer to “Grain Size analysis”, “Hydrometer Analysis”, and “Atterberg Limits” (Anne Allen, 2013). The lab manuals were strictly followed, and no changes were made to the procedures throughout. 4 3.0 Discussion The client requested that three soil samples be tested. One sample was tested using a sieve analysis, the second through a hydrometer analysis, and the final sample was tested using the Atterberg Limits Test. The tests were used in order to classify the soil types under the USCS. The sieve and hydrometer analyses rely on the analysis of the grain size and particle distribution while the Atterberg Limits Test analyzed the behaviour of the soil based on different moisture contents. All values found in this report can be proven by the data sheets and hand calculations in Appendix B, and the classification can be supported by the USCS tables found in appendix D. 3.1 Sieve Analysis Using sieves among other tools outlined in the “Grain Size Analysis” lab, a sieve analysis technique was utilized. Using this analysis, it was determined that the initial total weight of the soil sample was 1501.0g. The total retained weight of both coarse grain and fine grain were 558.5g and 942.2g respectively. The total soil sample weight was 1501.4g, therefore there was a gain of 0.4g. An explanation of this error is human error, such as forgetting to zero the scale before weighing, inexperience of the lab technicians or several rounding errors adding up to one large error. The fine grains were split until 114 g were remaining. The final fine weight was 99.5g, therefore 5.75% of the total fine grains were lost. The percent lost is above the acceptable limit of 2%. This can also be explained by human error. The percent retained on the coarse grain sieve was calculated by dividing the cumulative weight in grams by the total weight. Multiplying this value by 100 resulted in a percentage. For the fine grain sieve (size less than 4.75 mm), the percent retained was calculated by obtaining a Factor Number. The Factor Number was computed by dividing the percent passing the 4.75 mm by the total weight of the fine-grain material (942.9 g). The percent passing was calculated by multiplying the Factor Number into each cumulative weight. Then subtracting this value from the percent passing the 4.75 mm retrieves the percent passing of the respective sieve size. The percent retained is obtained by subtracting 100 to the percent passing respectively. A percent 5 passing vs. particle size graph with a logarithmic scale was produced as seen in Figure 1 below. This figure clearly illustrates that the soil is gap graded. 100 90 80 Percent Passing 70 60 50 40 30 20 10 0 100 10 1 0.1 0.01 Grain Size (mm) Figure 1: Grain Size Distribution Utilizing Microsoft Excel‟s interpolation technique, the grain diameters (mm) that correspond to 60 (D60), 30 (D30), 10 (D10) percent passing were calculated. The interpolation from Microsoft Excel was based on a Point-Slope formula. Table 1 provides the grain size percent passing at these points described above, along with coefficients of uniformity (Cu) and gradation (Cc). Table 1: Determination of D Values & Coefficients for Coarse and Fine Gradation D60 D30 D10 Cu Cc 3.88 0.271 0.091 42.637 0.208 Additional information based on the Sieve Analysis was calculated and is supplied in Appendix A. 6 Based on the USCS, the sample of soil is poorly graded sand with gravel (SP in the USCS). This was based on the results that the gravel percentage was 37.21, the sand percentage was 54.81, and the fines percentage was 7.98. It was also based on the coefficient of gradation (0.208) and the uniformity coefficient (42.637) determined through analysis. (University of Virginia, 2013) 3.2 Hydrometer Analysis According to the lab manual “Hydrometer Analysis” by Anne Allen, the hydrometer analysis is used to determine the grain size distribution of the sample soils passing through the No.200 sieve. The Analysis is based on Strokes law which relates the terminal velocity in liquid to its diameter. To simplify the theory, the hydrometer and stroke‟s law, the diameter of a particle can be calculated using equation ( ) √ ( ) ( ) (1) where D is the diameter of the particle in mm, K is the hydrometer constant, L is the hydrometer length in cm and t is the time lapse in minutes. Equipment used were sieves, brushes, balance, oven, a mechanical stirring apparatus, hydrometer, thermometer, a cylinder, stop watch, dispersing agent, and a rubber stopper. The methodology of the test analysis was followed strictly with the lab manual created by Anne Allen. To prepare the specimen, a 250 g sample was used over a No.10 sieve. The process was repeated until only aggregate particles remain on sieve. The sample that passed the No. 10 sieve was split until there was an approximately 50g sample. The sample was mixed with 125 mL of sodium hexametaphosphate (dispersing agent) and was soaked for 16hrs. Figure 2 shows a semi logarithmic graph relating the percent fines with the diameter of the particles. 7 80 70 Percent Fines 60 50 40 30 20 10 0 0.1 0.01 0.001 Grain Size (mm) Figure 2: Hydrometer Analysis Particle Distribution This figure displays that the tested soil is poorly graded. D60, D30 and D10 were calculated by using MatLab‟s interpolation. More specifically the „pchip‟ interpolation. Table 2 below provides the data for D60, D30 and D10 along with the coefficient of gradation and uniformity, while the MatLab code in Appendix A entitled “Code for Hydrometer D60, D30, D10, Cu, Cc” references how these values were found. Table 2: Determination of D Values & Coefficients for Hydrometer Analysis D60 D30 D10 Cu Cc 0.0041 0.00049 0.000060 67.935 0.9855 Based on the results concluded from the Hydrometer Analysis, this sample cannot be classified under the USCS. Although this sample cannot be classified, it should be noted that the UCSC can classify it as fine grained based on the fact that more than 50% of the material passed through the number 200 sieve. Further classification of this sample would require the Atterberg Limits Test. 8 3.3 Atterberg Limits Test The Atterberg Limits Tests applies the theory that a clay or soil‟s condition can be altered by changing its moisture content. This test was applied to find the Atterberg limits of the soil in question. These limits include the liquid limit, shrinkage limit, and plastic limit. It should be noted that the ASTM D 4318-10 test was used. This test defines the liquid limit of a soil sample as the moisture content in the sample (%) that is required to close a 13 mm groove made by a grooving tool in the soil. A soil sample at its liquid limit will be closed by 25 blows struck at a constant rate of two strikes per second. The procedure follows that some of the sample is placed into the Casagrande cup of the liquid limit device, and the amount of blows needed to close the groove is recorded. After the cup is cleaned and the sample from the cup has been weighed and set aside to be dried in an oven, water is added to the rest of sample to increase its moisture content. After it is thoroughly mixed, more of the sample is added to the Casagrande cup and the process is repeated. It is ideal that there is between 10 and 60 blows struck in a trial. Figure 3 on the following page illustrates the five trials of the test for this particular example. It can be noted that the moisture content (%) portrayed in the figure is the ratio between the mass of water to the mass of dry soil. This value is then multiplied by 100 to become a percentage. As defined by this test, the plastic limit of a sample is its moisture content in (%) that a soil will crumble when rolled into thin tubes of about 3.2 mm in diameter. This represents the boundary between the plastic and semi-solid states of a soil. It has been found using the Atterberg Limits Test that this particular specimen has a liquid limit of 23% and a plastic limit of 7%. The plasticity index is defined by the test to be the liquid limit minus the plastic limit. For this sample, the plasticity index is 16%. According to the Plasticity Chart for USCS in the “Atterberg Limits Analysis” reference, the material is CL. This specific type of clay is mostly made up of inorganic clay with low plasticity. Based on a plasticity index of 21% as given by the client and the percentage of clay-sized particles less than 2μm denoted (%D<2μm) being 55%, an activity for the clay was found to be 0.38. According to table 3.4 from (Kehew, 2006), an activity for clay of 0.38 suggests that the dominant clay mineral in this sample is Kaolinite. 9 Number of Blows 100 10 20 21 22 23 24 25 26 27 28 Moisture Content (%) Figure 3: Liquid Limit of Sample Human error is a factor in the results of this test. It is likely that a constant revolution rate for the Casagrande cup was not consistently 2 revolutions per second which could affect the results. Dried clay on the edge of the bowl could have been mixed into the sample. This would make the moisture content inconsistent throughout the sample and affect the number of blows taken to close the groove in the liquid limit device. Finally, small human error from misreading the scale when weighing sample to forgetting to reset the counter which counts the number of blows, or even not setting the height of the Casagrande cup to the correct height when starting the test could set the results of this test astray. 10 4.0 Conclusion The three soil samples have been classified accordingly to the USCS and have calculated additionally engineering soil properties. Such properties have been calculated for further understanding of the soil sample properties. The sample used in the sieve analysis was categorized to be poorly graded (SP) based on the USCS, however based on Figure 1 displaying the percent passing of the sample presented a soil which was gap graded. The sample used in hydrometer analysis was determined to be poorly graded yet fine grained. It should be noted that due to insufficient data, this sample could not be classified based on the USCS. Finally the sample used in the Atterberg Limits Test is classified under the group CL. Kaolinite was the dominant material in this sample. It is strongly recommended that the Atterberg Limits Test be redone on the sample. This is because the experimental data did not display a linear trend, yet a scattered trend. Thus the results obtained were likely to be unreliable. It is also recommended that the sample from the hydrometer analysis be tested by the Atterberg Limits Test. The reason being that the hydrometer analysis provided insufficient information to classify the soil. The Atterberg Limits Test would solve this issue. 11 5.0 References Allen, Anne. (2013). Atterberg Limits Analysis. Waterloo, ON: University of Waterloo Department of Environmental and Civil Engineering. Allen, Anne. (2013). Grain Size Analysis. Waterloo, ON: University of Waterloo Department of Environmental and Civil Engineering. Allen, Anne. (2013). Hydrometer Analysis. Waterloo, ON: University of Waterloo Department of Environmental and Civil Engineering. Kehew, Alan. (2006). Geology for Engineers and Environmental Scientists. 3rd Edition. University of Virginia. (2013). Unified Soil Classification System. Retrieved from: http://matrix.vtrc.virginia.edu/DATA/GINT/vdotusc.PDF 12 Appendix A Reduced Data 13 Sieve Analysis Sieve Size 37.5 mm 26.5 mm 22.4 mm 19.0 mm 16.0 mm 9.50 mm 6.70 mm 4.75 mm Non-Cumulative Weight (g) 0.0 0.0 16.7 31.9 55.6 217.3 151.1 85.9 Cumulative Weight (g) 0.0 0.0 16.7 48.6 104.2 321.5 472.6 558.5 Initial Total Wt. Initial Fines Wt. 1501.0 g 942.9 g Total Fines Wt. Coarse Retained Wt. Final Coarse Wt. 2.36 mm 1.18 mm 600 μm 300 μm 150 μm 75 μm 14.0 8.6 10.4 21.2 28.0 17.3 14.0 22.6 33.0 54.2 82.2 99.5 Total Fines Wt. (before wash) Pan Wt. (after sieving) 114.0 g Fines Retained Wt. 99.5 g Fines Passing Wt. 7.94 g Total Fines Wt. 107.44 g Gravel Sand Fines 37.21 % 54.81 % 7.98 % 0.5 g Initial Total Weight Initial Fine Weight Percent Gain of Coarse Sample Percent Loss of Fine Sample 1501.0 g 942.9 g 0.026 % 5.75 % Factor Number 0.5508 14 % Retained % Passing 0 0 1.11 3.24 6.94 21.42 31.49 37.21 100 100 98.89 96.76 93.06 78.58 68.51 62.79 942.9 g 558.5 g 1501.4 g 44.92 49.66 55.39 67.06 82.48 92.02 55.08 50.34 44.61 32.94 17.52 7.98 Material Data Bulk Density Total Volume Specific Gravity Total mass of sample Mass of Water in sample Mass of solids in sample Density of water (Pb) (Vt) (Gs) (Mt) (Mw) (Ms) (Pw) 1958.3 kg/m3 1.2 m3 2.71 2350 kg 192 kg 2158 kg 1000 kg/m3 Calculated Properties Water content (θw) Unit density (ϒb) Void ratio (e) Porosity (n) Volume of voids (Vv) Volume of water in voids (Vw) Water saturation (Sw) 8.9 % 195833.33 N/m3 0.506 0.3364 0.403 m3 0.192 m3 0.4756 15 Hydrometer Hydrometer Test Sample Mass of total hydrometer sample (g) (hs) Specific Gravity of Solids (GS) Dispersing Agent Hydrometer No. Temperature °C Composite Correction Mass of Hydrometer sample tests (M) 55.0 2.65 125 105.861 21.8 +6 54.208 Hydrometer Test Data: Elapsed Time (min) Actual Hydro Reading CT a 47 Composite L Corrected Hydro Reading (R) 41 8.6 2 K D (mm) 1 Corrected % Hydro Finer Reading P RC 41.4 76.37 0.01332 0.02762 +0.4 5 46 40 8.8 8 45 39 15 44 30 75.97 0.01332 0.01767 +0.4 1 40.4 74.53 74.13 8.9 0.01332 0.01405 +0.4 1 39.4 72.68 72.29 38 9.1 0.01332 0.01037 +0.4 1 38.4 70.84 70.46 43 37 9.2 0.01332 0.00738 +0.4 1 37.4 68.99 68.62 60 41 35 10.6 0.01332 0.00560 +0.4 1 35.4 65.30 64.95 250 3505 29.5 11.4 0.01332 0.00284 +0.4 1 29.9 55.18 54.89 24 hours 31 25 12.2 0.01332 0.00123 +0.4 1 25.4 46.86 46.61 16 % Finer PA Hygroscopic Moisture Content Data Weight (g) 59.57 109.57 108.85 50 49.28 0.72 1.46% 0.9856 Mass of Pan A Air dried weight + Pan A Oven dried Weight + Pan A Mass of Air dried soil Mass of Oven dried soil Mass of Water Hygroscopic water content (%)(θhw) Hygroscopic Correction Factor (Hcf) Sieve Analysis – Coarse and Fine material Sieve Size Non-Cumulative Cumulative Weight (g) Weight (g) 4.75 mm 0.0 0 2.00 mm 0.0 0. 850 μm 0.03 0.03 425 μm 0.03 0.06 250 μm 0.01 0.07 150 μm 0.05 0.12 75 μm 0.14 0.26 17 % retained 0 0 0.061 0.12 0.14 0.24 0.53 % passing 100% 100% 99.939 99.88 99.86 99.76 99.4 Atterberg Limits Liquid Limit Trial Number No. of Blows Tin Number Tin + Wet Soil (g) Tin + Dry Soil (g) Wt. of Water (g) Tin Wt. (g) Dry Soil Wt. (g) % Moisture 1 45 120 26.89 24.91 1.98 16.33 8.56 23.13 2 30 339 34.04 32.00 2.04 23.33 8.07 23.53 Plastic Limit Trial Number Tine Number Tin + Wet Soil (g) Tin + Dry Soil (g) Wt. of Water (g) Tin Wt. (g) Dry Soil Wt. (g) % Moisture 1 408 7.56 7.34 0.22 5.43 1.91 11.52 Data Liquid Limit (%) Plastic Limit (%) Plasticity Index Sample ID 23 7 16 CL 3 20 396 31.51 29.85 1.66 22.52 7.33 22.65 2 509 11.14 11.06 0.08 9.31 1.75 4.57 18 4 17 20.12 28.03 26.44 1.59 19.65 6.74 23.42 5 15 57 28.27 26.70 1.57 20.15 6.55 23.97 3 471 13.19 13.04 0.15 10.52 2.52 5.95 Hydrometer D60,D30,D10,Cu,and Cc values clc, clear, format short, format compact % ----- input data vectors D = [0.02762, 0.01767, 0.01405, 0.01037, 0.00738, 0.0056, 0.00284, 0.00123]; Pa = [75.97, 74.13, 72.29, 70.46, 68.62, 64.95, 54.89, 46.61]; % ----- graph to confirm correct semilogx(D,Pa,'o','markerfacecolor','r') set(gca,'xdir','reverse') xlim([0.001,0.1]) ylim([0,100]) grid on % ----- interpolate D60 = interp1(Pa,D,60,'pchip') % ----- to extrapolate, must concatenate a point on the trendline for added % correctness D = [D,10^(-5)]; Pa = [Pa,0]; D30 = interp1(Pa,D,30,'pchip') D10 = interp1(Pa,D,10,'pchip') % ----- solve for Cu and Cc Cu = D60/D10 Cc = (D30^2)/(D60*D10) % ----- Coded By Kyle Pellerin 19 Appendix B Original Lab Data 20 Appendix C Hand Calculations 21 Appendix D References 22

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