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Peb802 capstone design project assesment 2

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This document summarizes the results of several soil tests conducted as part of a capstone design project. The tests included sieve analysis, moisture content determination, density tests using a core cutter method, liquid limit tests, and compaction tests. For each test, the materials and methods are described and test results including weights, densities, moisture contents and other measured values are reported. The overall goal of the project was to minimize soil stabilization costs using various additives like coir fiber, KOBM, and geotextiles.

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1 PEB 802 Capstone Design Project Assignment 2 Sustainable Soil Stabilization of Red Clay Using Coir Fiber, KOBM and Geotextile Material Submitted By Vishwaleen Vishaal Ram - 2016133741 Under Supervision of Supervisor(s) Mr. Sateesh Kumar Pisini Submitted in Partial Fulfillment of the Requirement for the Degree of Bachelor of Engineering (Honours) (Bachelor of Civil engineering), to SCHOOL OF BUILDING AND CIVIL ENGINEERING, FIJI NATIONAL UNIVERSITY, FIJI ISLAND 13th September
2 1. Detailed Interpretation of the outcomes of the PEB 802 Capstone Design Project, Data Presentation & Error Analysis, Evaluation of Experiment and Courtesy &Safety The outcome of this project is to minimizing the cost of stabilizing soil of foundations of structures like building, roads, and etc. It will be achieved by doing soil experimentation on fiber-soil mixture with the addition of geotextile and KOBM. There are different types of soil test that will be performed on the soil-fiber mixture such as CBR test, compaction test, Atterberg’s limit test and many more. The outcome of the project will achieve before the final submission since the convectional design and optimum methods.
3 Sieve Analysis Description of soil: Red Clay Soil Sample No. Mass of oven dry specimen, W: 500 g Location: FNU Civil Lab Date: Description of soil: Sample No. Mass of oven dry specimen, W: 1000 g Location: Date: Tested by: 2.360 0.424 424 1.180 0.397 0.3979 0.001 397 0.600 0.401 0.4028 0.002 401 0.425 0.382 0.3833 0.001 382 0.300 0.376 0.3793 0.003 376 0.150 0.363 0.3709 0.008 363 0.075 0.3615 0.3712 0.010 361.5 PAN 0.3425 0.3425 0.000 342.5 2.6 MASS OF SIEVE 339.5 Sampling pan mass of retained on each sieve, Rn Cumulative percent retained Percent Finer Sieve Size. Sieve Weight (kg) mass of soil + mass of sieve, Wn (kg) Mass loss during sieve analysis 99.47042 % (OK, if less than 2%)
4 W1= Wet wt of soil W2= Dry wt of soil WaterContent Water content, w = Description of soil: Clay Sample No. Mass of oven dry specimen, W: 0 g Location: Near MB hall Date: 11/08/2020 sample 1 sample 2 Average 200 0.075 678 785 107.0 53.5 10.7 10.7 89.3 Pan - 893.0 Cumulative percent retained Percent Finer mass ofsoilretained oneachsieve, Wn (g)Sieve No. Sieve Opening (mm) mass ofSieve, W (g) mass ofSieve + drysoilretained, W (g) Percent of mass retained oneachsieve, Rn 2.360 0.4240 0.4241 0.0001 1.180 0.3971 0.3976 0.0005 . 0.600 0.4014 0.4027 0.0003 0.425 0.3822 0.3829 0.0007 0.300 0.3765 0.3779 0.0014 0.150 0.3630 0.3669 0.0039 0.075 0.3614 0.3657 0.0043 PAN 0.3425 0.3426 0.0001 0.0113 Percent Cumulative mass retained Sieve Size. Sieve Weight (kg) mass of soil + mass of sieve, Wn (kg) mass of soil retained on each sieve, Rn weight of soil passing (kg)
5 Soil Density (Core Cutter Mtd) Description of soil: Red Clay Soil Sample No. 1 Mass of oven dry specimen, W: 0 g Location: Near MB hall Date: 31/072020 Tested by: Group members time length = Friday(3:30pm to Monday (9.25am) 1 2 3 I10 M1 E9 17.57 17.42 17.44 69.01 67.56 65.69 50.19 49.12 48.04 18.82 18.44 17.65 32.62 31.7 30.6 Mass of can + wet soil, W2 (g) Item Can No. Mass of can, W1 (g) Test No. 1 Average moisture content, w(%) = 57.84825047 Mass of can + dry soil, W3 (g) Mass of moisture, W2 -W3 (g) Mass of dry soil, W3-W1 (g) Moisture content 57.6946658 58.170347 57.6797386 1 2 3 D8 C4 K8 17.51 17.31 17.36 65.67 62.61 64.34 48.9 46.88 47.95 16.77 15.73 16.39 31.39 29.57 30.59 Item Test No. 1 Can No. Mass of can, W1 (g) Mass of can + wet soil, W2 (g) 53.1958066 53.5796012 Average moisture content, w(%) = 53.40002176 Mass of can + dry soil, W3 (g) Mass of moisture, W2 -W3 (g) Mass of dry soil, W3-W1 (g) Moisture content 53.4246575
6 Soil sample volume 93.4366 cm^3 Wet density 1.595 g/cm^3 Description of soil: Red Clay Soil Sample No. 2 Mass of oven dry specimen, W: 0 g Location: Near MB hall Date: 31/072020 Tested by: Group members mm mm cm g g g cm 1 2 3 K8 C5 C4 17.4 18.5 17.7 34.83 32.2 36.14 27.43 26.38 28.26 7.4 5.82 7.88 10.03 7.88 10.56 ValueItem Ht of Cylinder Ht of Empty space in Cylinder Ht of soil sample wt of cylinder + soil sample wt of empty cylinder 74.621 Average moisture content, w(%) = 74.086 Mass of can + dry soil, W3 (g) Mass of moisture, W2 -W3 (g) Mass of dry soil, W3-W1 (g) Moisture content 73.779 73.858 Item 84.06 8.406 310 161 149wt of soil sample Test No. 2 Can No. Mass of can, W1 (g) Mass of can + wet soil, W2 (g) Soil sample radius, r 1.881 V 𝜋𝑟 𝐻𝑠 V 𝛾 𝑚 𝑣 𝛾
7 Soil sample volume 95.6121 cm^3 Wet density 1.569 g/cm^3 Description of soil: Red Clay Soil Sample No. 3 Mass of oven dry specimen, W: 0 g Location: Near MB hall Date: 31/072020 Tested by: Group members mm mm mm g g g cm 1 2 3 F4 5E D5 18.1 17.12 17.6 33.67 34.51 33.92 27.11 27.11 26.95 6.56 7.4 6.97 9.01 9.99 9.35 Ht of Empty space in Cylinder Ht of soil sample 8.36 wt of cylinder + soil sample 308 Item Value Ht of Cylinder 83.6 Item Test No. 2 Can No. Mass of can, W1 (g) Mass of can + wet soil, W2 (g) Mass of can + dry soil, W3 (g) wt of empty cylinder 158 wt of soil sample 150 Soil sample radius, r 1.908 Average moisture content, w(%) = 73.809 Mass of moisture, W2 -W3 (g) Mass of dry soil, W3-W1 (g) Moisture content 72.808 74.074 74.545 V 𝜋𝑟 𝐻𝑠 V 𝛾 𝑚 𝑣 𝛾
8 Soil sample volume 93.437 cm^3 Wet density 1.744 g/cm^3 Average moisture content of the three samples, w(%) = 72.468 % w(%) = 0.725 Average wet density of the three samples, 1.636 g/cm^3 Experimental 0.95 g/cm^3 Actual 2.65 g/cm^3 Error (%) = 64.2045 mm mm cm g g g cm 1 2 3 B8 D8 H7 17.54 17.52 17.6 36.84 30.38 33.53 28.93 25.07 27.04 7.91 5.31 6.49 11.39 7.55 9.44 Ht of Empty space in Cylinder Ht of soil sample 8.406 wt of cylinder + soil sample 324 Item Value Ht of Cylinder 84.06 Item Test No. 2 Can No. Mass of can, W1 (g) Mass of can + wet soil, W2 (g) Mass of can + dry soil, W3 (g) wt of empty cylinder 161 wt of soil sample 163 Soil sample radius, r 1.881 Average moisture content, w(%) = 69.509 Mass of moisture, W2 -W3 (g) Mass of dry soil, W3-W1 (g) Moisture content 69.447 70.331 68.750 V 𝜋𝑟 𝐻𝑠 V 𝛾 𝑚 𝑣 𝛾 (𝛾 𝑎𝑣𝑔) (𝛾 𝑑) (𝛾 𝑑)
9 COMPACTION TEST TRIAL Aggregate = 2.5 Kg Weight of hammer = 2.4 Kg Diameter of mould = 101.16mm Height of mould = 116.05 Volume of mould = 932722.9599 mmˆ2 0.93272296 Trial 1 Trial 2 Trial 3 Trial 4 Trial 5 Trial 6 Trial 7 Weightof Mould (Kg) 3.633 3.633 3.633 3.633 3.633 3.633 3.633 Weight of Mould + base plate + wet soil sample 5.013 5.0395 5.0838 5.128 5.139 5.142 5.155 Amountof Water 50 100 150 200 250 300 350 Can labelling D9 B3 B9 G10 D6 G9 A4 Weightof Can (g) W1 22.36 22.63 22.54 22.95 23.06 23.1 22.83 Weightof Can + wetsoil sample (g) W2 92.83 93.45 87.63 89.59 108.96 101.46 100.74 Weight of Can + dry soil sample (g) W3 70.47 70.82 65.09 66.64 85.9 78.36 77.91 Mass of Moisture (g) W2 - W3 22.36 22.63 22.54 22.95 23.06 23.1 22.83 Mass of Dry soil (g) W3 - W1 48.11 48.19 42.55 43.69 62.84 55.26 55.08 Moisture content 46.47682395 46.9599502 52.972973 52.52918288 36.6963717 41.8023887 41.44880174 Wet density 1.479539005 1.507950442 1.55544579 1.602833922 1.61462735 1.61784374 1.631781424 Dry density 1.010084029 1.026096185 1.01681085 1.050837546 1.18117791 1.14091431 1.153619829 ( )
10
11 LIQUID LIMIT TEST 1 1 2 3 4 C1 E7 E3 A7 17.4 17.35 17.37 17.85 Mass of can + wet soil, W2 (g) 39.64 42.88 43.99 47.98 Mass of can + dry soil, W3 (g) 28.29 29.58 30.25 32.13 Mass of moisture, W2 -W3 (g) 11.35 13.3 13.74 15.85 Mass of dry soil, W3-W1 (g) 10.89 12.23 12.88 14.28 Can No. Test No. 1 110.9943978 ITEM Trial 107.66 104.22 Mass of can, W1 (g) Average moisture content, w(%) = 106.6770186108.7489779 Moisture content 14 A7 110.9943978 19 E3 106.6770186 22 E7 108.7489779 26 C1 104.2240588 Actual no of blows Can # no. Moisture Content
12 LIQUID LIMIT TEST 2 BLOWS NO# OF ACTUAL BLOWS 10 to 15 13 H7 15 to 20 18 B8 20 to 25 22 C5 25 to 30 26 K10 1 2 3 4 C5 H7 B8 K10 Mass of can, W1 (g) 18.46 17.61 17.53 17.37 Mass of can + wet soil, W2 (g) 50.15 57.1 46.54 54.28 Mass of can + dry soil, W3 (g) 33.89 36.34 31.8 35.67 Mass of moisture, W2 -W3 (g) 16.26 20.76 14.74 18.61 Mass of dry soil, W3-W1 (g) 15.43 18.73 14.27 18.3 Average moisture content, w(%) = ITEM Test No. 1 Trial Can No. 105.37913 110.8382274 103.29362 101.69399 Moisture content 105.3012428 13 H7 110.8382274 18 B8 103.293623 22 C5 105.3791316 26 K10 101.6939891 Actual no of blows Can # no. Moisture Content
13 (26 BLOWS) 97.54 150.4 123.83 31 150 20.66666667PERCENTAGE SHRINKAGE LENGTH OF SHRINKAGE MOULD (mm) SHRINKAGE LIMIT TEST SRINKAGE MOULD +WET SOIL, W2 (g) SRINKAGE MOULD +DRY SOIL, W3 (g) LENGTH OF SHRINKAGE (mm) SRINKAGE MOULD, W1 (g)
14 PLASTIC LIMIT 1 2 3 4 C10 J1 J8 K5 Mass of can, W1 (g) 17.17 17.94 17.5 17.53 Mass of can + wet soil, W2 (g) 19.15 19.69 20.1 19.68 Mass of can + dry soil, W3 (g) 18.38 18.98 19.1 18.82 Mass of moisture, W2 -W3 (g) 0.77 0.71 1 0.86 Mass of dry soil, W3-W1 (g) 1.21 1.04 1.6 1.29 65.27 66.67 ITEM Test No. 1 Trial 63.64 68.27 Average moisture content, w(%) = 62.5 Can No. Moisture content 97.65 150.4 123.45 31 150 20.66666667 26.95 25.8 104.4573643 MOISTURE CONTENT PERCENTAGE SHRINKAGE (%) MASS OF MOISTURE, W2-W3 (g) MASS OF DRY SOIL, W3-W1 (g) SRINKAGE MOULD ,W1(g) LENGTH OF MOULD (mm) MASS OF SRINKAGE MOULD +WET SOIL , W2(g) MASS OF SRINKAGE MOULD + DRY SOIL, W3(g) LENGTH OF SHRINKAGE (mm) SHRINKAGE LIMIT TEST(26 blows)
15 2. Detailed Investigations of the Complex Engineering Problems Using Research-Based Knowledge in Implementation of PEB 802 Capstone Design Project Software MS Excel In mathematics, using MS Excel solver to calculate the required variables from the experiment to get to the results and create graphs. The problem of getting to results and creating graphs. FLAC-3D FLAC 3D, Fast Lagrangian Analysis of Continua in 3D, is numerical modeling software for advanced geotechnical analysis of soil, rock, groundwater, and ground support. C++ Simple and complex mathematical equation will be defined in the C++ programming which will output the optimization of percentage fiber to be used in relation to the weight of soil. Constraints getting to the expected experimentation results are difficult due to the errors created during the experiment and other conditions such as humidity difference in each day. Other constraints are using new software’s, adding data in the FLAC 3D and trying to solve it for the first time may give unexpected results. Objective function An objective function articulates the key goal of the model which is what's more to be minimalized or exploited. In naivest designation it is a set of variables which governor the importance of the objective function. Designvariables The design variables are recorded at the appendences this is formed from the convectional technique which will be enhanced to yield the finest ideal design.
16 3. An Overview of Modern IT Tools, And Why You Decided to Use in Your Capstone Design Project Experimentation Optimization In producing the optimal percent of fiber to be used with clay soil we need to do lab test and find the best matching of fiber soil combination, such lab test includes Atterberg’s limit test Consistency limits, Specific gravity. The Compaction tests. The Unconfined compression tests, The California bearing ratio test. Also the addition of KOBM and geotextile in the soil fiber mixture to enhance the stability. Using the manual calculated results from the soil test to get a finest value of soil fiber and KOBM mixture. Software Optimization The use of software’s to get an optimal percentage of fiber and KOBM by analysis of required data input into the software such as using FLAC 3D to analyze progressive geotechnical exploration of soil, rock, groundwater, and ground provision. The use of MS Excel to compile data and generate graphs from results to get an optimal value of fiber and soil and KOBM. Use of C++ program to get an instant shortcut to get the amount of percentage fiber KOMB in the required amount of soil.
17 4. Recommendations The study deals the design of minimum cost for stabilizing soil for the use in the foundations of structures. A mathematical approach of the problem based on a criterion of minimum cost design and a set of constraints in accordance to the building code requirements for the structure and commentary are formulated.
18 5. Recommendations for The Future Research The trials and error are still in progress and the final design will be produced in the final submission of this project, once the constraints are satisfied and is accepted in the software (FLAC 3D & C++ Programming).
19 6. References Amu,O. O.,Owokade,O.S.,& Shitan,O.I. (2011). Potentialsof coconutshell andhuskashonthe geotechnical propertiesof lateriticsoil forroadworks. InternationalJournalof Engineering and Technology,3(2),87–94. Danso,H., & Manu, D. (2020). Influence of coconutfibresandlime onthe propertiesof soil-cement mortar. CaseStudiesin Construction Materials,12, e00316. https://doi.org/10.1016/j.cscm.2019.e00316 Devdatt,S.,K, R. S.S. A.,& Jha,A.K. (2015). 3 IXSeptember2015. September. Fattah,M. Y., Al-Saidi,À.A.,&Jaber,M. M. (2015). Characteristicsof claysstabilizedwithlime-silica fume mix. Italian Journalof Geosciences, 134(1), 104–113. https://doi.org/10.3301/IJG.2014.36 Ikeagwuani,C.C.,& Nwonu,D.C. (2019). Emergingtrendsinexpansivesoil stabilisation:A review. Journalof RockMechanicsand Geotechnical Engineering,11(2), 423–440. https://doi.org/10.1016/j.jrmge.2018.08.013 Manikandan,A.T., Ibrahim,Y.,Thiyaneswaran,M.P.,Dheebikhaa,B.,&Raja,K. (2017). a Studyon Effect of BottomAshand CoconutShell Powderonthe Propertiesof ClaySoil aStudyon Effectof Bottom Ashand CoconutShell Powder. InternationalResearch Journalof Engineering and Technology(IRJET),4(2),550–553. https://irjet.net/archives/V4/i2/IRJET-V4I2104.pdf Mir, I. A.,& Bawa, A.(2018). Utilizationof waste coconutcoirfiberinsoil reinforcement. International Journalof Civil Engineering and Technology,9(9),774–781.
20 7. Appendices LIQUID LIMITTEST SHRINKAGE LIMIT TEST COMPACTION TEST PREPARATION

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Peb802 capstone design project assesment 2

  • 1. 1 PEB 802 Capstone Design Project Assignment 2 Sustainable Soil Stabilization of Red Clay Using Coir Fiber, KOBM and Geotextile Material Submitted By Vishwaleen Vishaal Ram - 2016133741 Under Supervision of Supervisor(s) Mr. Sateesh Kumar Pisini Submitted in Partial Fulfillment of the Requirement for the Degree of Bachelor of Engineering (Honours) (Bachelor of Civil engineering), to SCHOOL OF BUILDING AND CIVIL ENGINEERING, FIJI NATIONAL UNIVERSITY, FIJI ISLAND 13th September
  • 2. 2 1. Detailed Interpretation of the outcomes of the PEB 802 Capstone Design Project, Data Presentation & Error Analysis, Evaluation of Experiment and Courtesy &Safety The outcome of this project is to minimizing the cost of stabilizing soil of foundations of structures like building, roads, and etc. It will be achieved by doing soil experimentation on fiber-soil mixture with the addition of geotextile and KOBM. There are different types of soil test that will be performed on the soil-fiber mixture such as CBR test, compaction test, Atterberg’s limit test and many more. The outcome of the project will achieve before the final submission since the convectional design and optimum methods.
  • 3. 3 Sieve Analysis Description of soil: Red Clay Soil Sample No. Mass of oven dry specimen, W: 500 g Location: FNU Civil Lab Date: Description of soil: Sample No. Mass of oven dry specimen, W: 1000 g Location: Date: Tested by: 2.360 0.424 424 1.180 0.397 0.3979 0.001 397 0.600 0.401 0.4028 0.002 401 0.425 0.382 0.3833 0.001 382 0.300 0.376 0.3793 0.003 376 0.150 0.363 0.3709 0.008 363 0.075 0.3615 0.3712 0.010 361.5 PAN 0.3425 0.3425 0.000 342.5 2.6 MASS OF SIEVE 339.5 Sampling pan mass of retained on each sieve, Rn Cumulative percent retained Percent Finer Sieve Size. Sieve Weight (kg) mass of soil + mass of sieve, Wn (kg) Mass loss during sieve analysis 99.47042 % (OK, if less than 2%)
  • 4. 4 W1= Wet wt of soil W2= Dry wt of soil WaterContent Water content, w = Description of soil: Clay Sample No. Mass of oven dry specimen, W: 0 g Location: Near MB hall Date: 11/08/2020 sample 1 sample 2 Average 200 0.075 678 785 107.0 53.5 10.7 10.7 89.3 Pan - 893.0 Cumulative percent retained Percent Finer mass ofsoilretained oneachsieve, Wn (g)Sieve No. Sieve Opening (mm) mass ofSieve, W (g) mass ofSieve + drysoilretained, W (g) Percent of mass retained oneachsieve, Rn 2.360 0.4240 0.4241 0.0001 1.180 0.3971 0.3976 0.0005 . 0.600 0.4014 0.4027 0.0003 0.425 0.3822 0.3829 0.0007 0.300 0.3765 0.3779 0.0014 0.150 0.3630 0.3669 0.0039 0.075 0.3614 0.3657 0.0043 PAN 0.3425 0.3426 0.0001 0.0113 Percent Cumulative mass retained Sieve Size. Sieve Weight (kg) mass of soil + mass of sieve, Wn (kg) mass of soil retained on each sieve, Rn weight of soil passing (kg)
  • 5. 5 Soil Density (Core Cutter Mtd) Description of soil: Red Clay Soil Sample No. 1 Mass of oven dry specimen, W: 0 g Location: Near MB hall Date: 31/072020 Tested by: Group members time length = Friday(3:30pm to Monday (9.25am) 1 2 3 I10 M1 E9 17.57 17.42 17.44 69.01 67.56 65.69 50.19 49.12 48.04 18.82 18.44 17.65 32.62 31.7 30.6 Mass of can + wet soil, W2 (g) Item Can No. Mass of can, W1 (g) Test No. 1 Average moisture content, w(%) = 57.84825047 Mass of can + dry soil, W3 (g) Mass of moisture, W2 -W3 (g) Mass of dry soil, W3-W1 (g) Moisture content 57.6946658 58.170347 57.6797386 1 2 3 D8 C4 K8 17.51 17.31 17.36 65.67 62.61 64.34 48.9 46.88 47.95 16.77 15.73 16.39 31.39 29.57 30.59 Item Test No. 1 Can No. Mass of can, W1 (g) Mass of can + wet soil, W2 (g) 53.1958066 53.5796012 Average moisture content, w(%) = 53.40002176 Mass of can + dry soil, W3 (g) Mass of moisture, W2 -W3 (g) Mass of dry soil, W3-W1 (g) Moisture content 53.4246575
  • 6. 6 Soil sample volume 93.4366 cm^3 Wet density 1.595 g/cm^3 Description of soil: Red Clay Soil Sample No. 2 Mass of oven dry specimen, W: 0 g Location: Near MB hall Date: 31/072020 Tested by: Group members mm mm cm g g g cm 1 2 3 K8 C5 C4 17.4 18.5 17.7 34.83 32.2 36.14 27.43 26.38 28.26 7.4 5.82 7.88 10.03 7.88 10.56 ValueItem Ht of Cylinder Ht of Empty space in Cylinder Ht of soil sample wt of cylinder + soil sample wt of empty cylinder 74.621 Average moisture content, w(%) = 74.086 Mass of can + dry soil, W3 (g) Mass of moisture, W2 -W3 (g) Mass of dry soil, W3-W1 (g) Moisture content 73.779 73.858 Item 84.06 8.406 310 161 149wt of soil sample Test No. 2 Can No. Mass of can, W1 (g) Mass of can + wet soil, W2 (g) Soil sample radius, r 1.881 V 𝜋𝑟 𝐻𝑠 V 𝛾 𝑚 𝑣 𝛾
  • 7. 7 Soil sample volume 95.6121 cm^3 Wet density 1.569 g/cm^3 Description of soil: Red Clay Soil Sample No. 3 Mass of oven dry specimen, W: 0 g Location: Near MB hall Date: 31/072020 Tested by: Group members mm mm mm g g g cm 1 2 3 F4 5E D5 18.1 17.12 17.6 33.67 34.51 33.92 27.11 27.11 26.95 6.56 7.4 6.97 9.01 9.99 9.35 Ht of Empty space in Cylinder Ht of soil sample 8.36 wt of cylinder + soil sample 308 Item Value Ht of Cylinder 83.6 Item Test No. 2 Can No. Mass of can, W1 (g) Mass of can + wet soil, W2 (g) Mass of can + dry soil, W3 (g) wt of empty cylinder 158 wt of soil sample 150 Soil sample radius, r 1.908 Average moisture content, w(%) = 73.809 Mass of moisture, W2 -W3 (g) Mass of dry soil, W3-W1 (g) Moisture content 72.808 74.074 74.545 V 𝜋𝑟 𝐻𝑠 V 𝛾 𝑚 𝑣 𝛾
  • 8. 8 Soil sample volume 93.437 cm^3 Wet density 1.744 g/cm^3 Average moisture content of the three samples, w(%) = 72.468 % w(%) = 0.725 Average wet density of the three samples, 1.636 g/cm^3 Experimental 0.95 g/cm^3 Actual 2.65 g/cm^3 Error (%) = 64.2045 mm mm cm g g g cm 1 2 3 B8 D8 H7 17.54 17.52 17.6 36.84 30.38 33.53 28.93 25.07 27.04 7.91 5.31 6.49 11.39 7.55 9.44 Ht of Empty space in Cylinder Ht of soil sample 8.406 wt of cylinder + soil sample 324 Item Value Ht of Cylinder 84.06 Item Test No. 2 Can No. Mass of can, W1 (g) Mass of can + wet soil, W2 (g) Mass of can + dry soil, W3 (g) wt of empty cylinder 161 wt of soil sample 163 Soil sample radius, r 1.881 Average moisture content, w(%) = 69.509 Mass of moisture, W2 -W3 (g) Mass of dry soil, W3-W1 (g) Moisture content 69.447 70.331 68.750 V 𝜋𝑟 𝐻𝑠 V 𝛾 𝑚 𝑣 𝛾 (𝛾 𝑎𝑣𝑔) (𝛾 𝑑) (𝛾 𝑑)
  • 9. 9 COMPACTION TEST TRIAL Aggregate = 2.5 Kg Weight of hammer = 2.4 Kg Diameter of mould = 101.16mm Height of mould = 116.05 Volume of mould = 932722.9599 mmˆ2 0.93272296 Trial 1 Trial 2 Trial 3 Trial 4 Trial 5 Trial 6 Trial 7 Weightof Mould (Kg) 3.633 3.633 3.633 3.633 3.633 3.633 3.633 Weight of Mould + base plate + wet soil sample 5.013 5.0395 5.0838 5.128 5.139 5.142 5.155 Amountof Water 50 100 150 200 250 300 350 Can labelling D9 B3 B9 G10 D6 G9 A4 Weightof Can (g) W1 22.36 22.63 22.54 22.95 23.06 23.1 22.83 Weightof Can + wetsoil sample (g) W2 92.83 93.45 87.63 89.59 108.96 101.46 100.74 Weight of Can + dry soil sample (g) W3 70.47 70.82 65.09 66.64 85.9 78.36 77.91 Mass of Moisture (g) W2 - W3 22.36 22.63 22.54 22.95 23.06 23.1 22.83 Mass of Dry soil (g) W3 - W1 48.11 48.19 42.55 43.69 62.84 55.26 55.08 Moisture content 46.47682395 46.9599502 52.972973 52.52918288 36.6963717 41.8023887 41.44880174 Wet density 1.479539005 1.507950442 1.55544579 1.602833922 1.61462735 1.61784374 1.631781424 Dry density 1.010084029 1.026096185 1.01681085 1.050837546 1.18117791 1.14091431 1.153619829 ( )
  • 10. 10
  • 11. 11 LIQUID LIMIT TEST 1 1 2 3 4 C1 E7 E3 A7 17.4 17.35 17.37 17.85 Mass of can + wet soil, W2 (g) 39.64 42.88 43.99 47.98 Mass of can + dry soil, W3 (g) 28.29 29.58 30.25 32.13 Mass of moisture, W2 -W3 (g) 11.35 13.3 13.74 15.85 Mass of dry soil, W3-W1 (g) 10.89 12.23 12.88 14.28 Can No. Test No. 1 110.9943978 ITEM Trial 107.66 104.22 Mass of can, W1 (g) Average moisture content, w(%) = 106.6770186108.7489779 Moisture content 14 A7 110.9943978 19 E3 106.6770186 22 E7 108.7489779 26 C1 104.2240588 Actual no of blows Can # no. Moisture Content
  • 12. 12 LIQUID LIMIT TEST 2 BLOWS NO# OF ACTUAL BLOWS 10 to 15 13 H7 15 to 20 18 B8 20 to 25 22 C5 25 to 30 26 K10 1 2 3 4 C5 H7 B8 K10 Mass of can, W1 (g) 18.46 17.61 17.53 17.37 Mass of can + wet soil, W2 (g) 50.15 57.1 46.54 54.28 Mass of can + dry soil, W3 (g) 33.89 36.34 31.8 35.67 Mass of moisture, W2 -W3 (g) 16.26 20.76 14.74 18.61 Mass of dry soil, W3-W1 (g) 15.43 18.73 14.27 18.3 Average moisture content, w(%) = ITEM Test No. 1 Trial Can No. 105.37913 110.8382274 103.29362 101.69399 Moisture content 105.3012428 13 H7 110.8382274 18 B8 103.293623 22 C5 105.3791316 26 K10 101.6939891 Actual no of blows Can # no. Moisture Content
  • 13. 13 (26 BLOWS) 97.54 150.4 123.83 31 150 20.66666667PERCENTAGE SHRINKAGE LENGTH OF SHRINKAGE MOULD (mm) SHRINKAGE LIMIT TEST SRINKAGE MOULD +WET SOIL, W2 (g) SRINKAGE MOULD +DRY SOIL, W3 (g) LENGTH OF SHRINKAGE (mm) SRINKAGE MOULD, W1 (g)
  • 14. 14 PLASTIC LIMIT 1 2 3 4 C10 J1 J8 K5 Mass of can, W1 (g) 17.17 17.94 17.5 17.53 Mass of can + wet soil, W2 (g) 19.15 19.69 20.1 19.68 Mass of can + dry soil, W3 (g) 18.38 18.98 19.1 18.82 Mass of moisture, W2 -W3 (g) 0.77 0.71 1 0.86 Mass of dry soil, W3-W1 (g) 1.21 1.04 1.6 1.29 65.27 66.67 ITEM Test No. 1 Trial 63.64 68.27 Average moisture content, w(%) = 62.5 Can No. Moisture content 97.65 150.4 123.45 31 150 20.66666667 26.95 25.8 104.4573643 MOISTURE CONTENT PERCENTAGE SHRINKAGE (%) MASS OF MOISTURE, W2-W3 (g) MASS OF DRY SOIL, W3-W1 (g) SRINKAGE MOULD ,W1(g) LENGTH OF MOULD (mm) MASS OF SRINKAGE MOULD +WET SOIL , W2(g) MASS OF SRINKAGE MOULD + DRY SOIL, W3(g) LENGTH OF SHRINKAGE (mm) SHRINKAGE LIMIT TEST(26 blows)
  • 15. 15 2. Detailed Investigations of the Complex Engineering Problems Using Research-Based Knowledge in Implementation of PEB 802 Capstone Design Project Software MS Excel In mathematics, using MS Excel solver to calculate the required variables from the experiment to get to the results and create graphs. The problem of getting to results and creating graphs. FLAC-3D FLAC 3D, Fast Lagrangian Analysis of Continua in 3D, is numerical modeling software for advanced geotechnical analysis of soil, rock, groundwater, and ground support. C++ Simple and complex mathematical equation will be defined in the C++ programming which will output the optimization of percentage fiber to be used in relation to the weight of soil. Constraints getting to the expected experimentation results are difficult due to the errors created during the experiment and other conditions such as humidity difference in each day. Other constraints are using new software’s, adding data in the FLAC 3D and trying to solve it for the first time may give unexpected results. Objective function An objective function articulates the key goal of the model which is what's more to be minimalized or exploited. In naivest designation it is a set of variables which governor the importance of the objective function. Designvariables The design variables are recorded at the appendences this is formed from the convectional technique which will be enhanced to yield the finest ideal design.
  • 16. 16 3. An Overview of Modern IT Tools, And Why You Decided to Use in Your Capstone Design Project Experimentation Optimization In producing the optimal percent of fiber to be used with clay soil we need to do lab test and find the best matching of fiber soil combination, such lab test includes Atterberg’s limit test Consistency limits, Specific gravity. The Compaction tests. The Unconfined compression tests, The California bearing ratio test. Also the addition of KOBM and geotextile in the soil fiber mixture to enhance the stability. Using the manual calculated results from the soil test to get a finest value of soil fiber and KOBM mixture. Software Optimization The use of software’s to get an optimal percentage of fiber and KOBM by analysis of required data input into the software such as using FLAC 3D to analyze progressive geotechnical exploration of soil, rock, groundwater, and ground provision. The use of MS Excel to compile data and generate graphs from results to get an optimal value of fiber and soil and KOBM. Use of C++ program to get an instant shortcut to get the amount of percentage fiber KOMB in the required amount of soil.
  • 17. 17 4. Recommendations The study deals the design of minimum cost for stabilizing soil for the use in the foundations of structures. A mathematical approach of the problem based on a criterion of minimum cost design and a set of constraints in accordance to the building code requirements for the structure and commentary are formulated.
  • 18. 18 5. Recommendations for The Future Research The trials and error are still in progress and the final design will be produced in the final submission of this project, once the constraints are satisfied and is accepted in the software (FLAC 3D & C++ Programming).
  • 19. 19 6. References Amu,O. O.,Owokade,O.S.,& Shitan,O.I. (2011). Potentialsof coconutshell andhuskashonthe geotechnical propertiesof lateriticsoil forroadworks. InternationalJournalof Engineering and Technology,3(2),87–94. Danso,H., & Manu, D. (2020). Influence of coconutfibresandlime onthe propertiesof soil-cement mortar. CaseStudiesin Construction Materials,12, e00316. https://doi.org/10.1016/j.cscm.2019.e00316 Devdatt,S.,K, R. S.S. A.,& Jha,A.K. (2015). 3 IXSeptember2015. September. Fattah,M. Y., Al-Saidi,À.A.,&Jaber,M. M. (2015). Characteristicsof claysstabilizedwithlime-silica fume mix. Italian Journalof Geosciences, 134(1), 104–113. https://doi.org/10.3301/IJG.2014.36 Ikeagwuani,C.C.,& Nwonu,D.C. (2019). Emergingtrendsinexpansivesoil stabilisation:A review. Journalof RockMechanicsand Geotechnical Engineering,11(2), 423–440. https://doi.org/10.1016/j.jrmge.2018.08.013 Manikandan,A.T., Ibrahim,Y.,Thiyaneswaran,M.P.,Dheebikhaa,B.,&Raja,K. (2017). a Studyon Effect of BottomAshand CoconutShell Powderonthe Propertiesof ClaySoil aStudyon Effectof Bottom Ashand CoconutShell Powder. InternationalResearch Journalof Engineering and Technology(IRJET),4(2),550–553. https://irjet.net/archives/V4/i2/IRJET-V4I2104.pdf Mir, I. A.,& Bawa, A.(2018). Utilizationof waste coconutcoirfiberinsoil reinforcement. International Journalof Civil Engineering and Technology,9(9),774–781.
  • 20. 20 7. Appendices LIQUID LIMITTEST SHRINKAGE LIMIT TEST COMPACTION TEST PREPARATION