This document provides information on mechanical analysis of soil, which involves determining the particle size distribution of soil through sieve analysis and hydrometer analysis. Sieve analysis involves shaking a soil sample through a nested set of sieves with progressively smaller openings to separate particles. Hydrometer analysis is used to determine the portion of soils smaller than 0.075mm. The document defines various soil particle sizes and provides an example of calculating particle size distribution, effective size, uniformity coefficient, and coefficient of gradation from sieve analysis results.
Subject: soil mechanic
Grain Size Analysis Test
Experiment No: 2
*Prepared by;
Rezhwan Hama Karim
*University Of Halabja
*Civil Engineering Department
Contents:
Introduction
References
Purpose of this experiment
Materials and equipment
Procedure
Data analysis
Calculation
Discussion
Conclusion
Introduction
Grain size analysis is a typical laboratory test conducted in the soil mechanics field. The purpose of the analysis is to derive the particle size distribution of soils. A sieve analysis (or gradation test) is a practice or procedure used (commonly used in civil engineering) to assess the particle size distribution (also called gradation) of a granular material by allowing the material to pass through a series of sieves of progressively smaller mesh size and weighing the amount of material that is stopped by each sieve as a fraction of the whole mass.
Standard References:-
ASTM D 422-standard test method for particle-size analysis of soils.
Purpose of this experiment
This test is performed to determine the percentage of different grain sizes contained within a soil. The mechanical or sieve analysis performed to determine the distribution of the coarser, larger-sized particles, and the hydrometer method is used the distribution of the finer particles.
Procedure:
First of all we found weight of each sieve as well as the bottom pan and we wrote it to use it in the analysis.
And we found the weight of the given dry soil sample and recorded it.
Then we checked all the sieves to make sure that all of sieves are clean, and assembled them in the ascending order of sieve numbers (#4 sieve at top and #200 sieve at bottom). And we placed the pan below #200 sieve. Carefully we poured the soil sample into the top sieve and place the cap over it.
After that we placed the sieve stack in the mechanical shaker and shack it for 10 minutes.
Finally we removed the stack from the shaker and carefully weighted and recorded the weight of each sieve with its retained soil. Weighted and recorded the weight of the bottom pan with its retained fine soil.
Discussion:
In this test we learn how to find grain size of the soil and how to classify it with comparing to ASTMD standards.
By using gradation curve and our table since F200 (1.55%) <50%, this mean our soil type should be Gravel or Sand.
R4 (22.2%)<12 R200(98.45%)=49.25 and this should be sand.
F200 (1.55%) <%5 so this should be SW or SP.
Our Cu>=6 but our Cg is not between 1 and 3 so our soil is SP.
%gravel (22.2%)>=15%so our soil is SP with gravel.
Conclusion:
In this test we are learn how to fined particle size distribution and classified our soil sample with ASTM D standard which we notice that our soil is poorly grained sand with gravel due to our comparing with ASTMD standard and we drew a particle-size distribution for our sample which is our curve well graded because it take a lot of particle sizes of our soil sample. This test we didn’t have many of sieve numbers this result to this 4.3
Class notes of Geotechnical Engineering course I used to teach at UET Lahore. Feel free to download the slide show.
Anyone looking to modify these files and use them for their own teaching purposes can contact me directly to get hold of editable version.
Astm designation c 136 for fine aggregatesMuhammad Ahmad
Sieve Analysis for Fine Aggregate as per ASTM. Slides contain all the relevant data and steps that would be required for the performance of sieve analysis of fine aggregates.
Site investigation for multistorey buildingKiran Birdi
Preliminary and Detailed Investigation of Site.
It is done to check whether the site is feasible for Multistorey Building or not.
In this, I have calculated the Bearing Capacity of Soil by performing SPT.
Subject: soil mechanic
Grain Size Analysis Test
Experiment No: 2
*Prepared by;
Rezhwan Hama Karim
*University Of Halabja
*Civil Engineering Department
Contents:
Introduction
References
Purpose of this experiment
Materials and equipment
Procedure
Data analysis
Calculation
Discussion
Conclusion
Introduction
Grain size analysis is a typical laboratory test conducted in the soil mechanics field. The purpose of the analysis is to derive the particle size distribution of soils. A sieve analysis (or gradation test) is a practice or procedure used (commonly used in civil engineering) to assess the particle size distribution (also called gradation) of a granular material by allowing the material to pass through a series of sieves of progressively smaller mesh size and weighing the amount of material that is stopped by each sieve as a fraction of the whole mass.
Standard References:-
ASTM D 422-standard test method for particle-size analysis of soils.
Purpose of this experiment
This test is performed to determine the percentage of different grain sizes contained within a soil. The mechanical or sieve analysis performed to determine the distribution of the coarser, larger-sized particles, and the hydrometer method is used the distribution of the finer particles.
Procedure:
First of all we found weight of each sieve as well as the bottom pan and we wrote it to use it in the analysis.
And we found the weight of the given dry soil sample and recorded it.
Then we checked all the sieves to make sure that all of sieves are clean, and assembled them in the ascending order of sieve numbers (#4 sieve at top and #200 sieve at bottom). And we placed the pan below #200 sieve. Carefully we poured the soil sample into the top sieve and place the cap over it.
After that we placed the sieve stack in the mechanical shaker and shack it for 10 minutes.
Finally we removed the stack from the shaker and carefully weighted and recorded the weight of each sieve with its retained soil. Weighted and recorded the weight of the bottom pan with its retained fine soil.
Discussion:
In this test we learn how to find grain size of the soil and how to classify it with comparing to ASTMD standards.
By using gradation curve and our table since F200 (1.55%) <50%, this mean our soil type should be Gravel or Sand.
R4 (22.2%)<12 R200(98.45%)=49.25 and this should be sand.
F200 (1.55%) <%5 so this should be SW or SP.
Our Cu>=6 but our Cg is not between 1 and 3 so our soil is SP.
%gravel (22.2%)>=15%so our soil is SP with gravel.
Conclusion:
In this test we are learn how to fined particle size distribution and classified our soil sample with ASTM D standard which we notice that our soil is poorly grained sand with gravel due to our comparing with ASTMD standard and we drew a particle-size distribution for our sample which is our curve well graded because it take a lot of particle sizes of our soil sample. This test we didn’t have many of sieve numbers this result to this 4.3
Class notes of Geotechnical Engineering course I used to teach at UET Lahore. Feel free to download the slide show.
Anyone looking to modify these files and use them for their own teaching purposes can contact me directly to get hold of editable version.
Astm designation c 136 for fine aggregatesMuhammad Ahmad
Sieve Analysis for Fine Aggregate as per ASTM. Slides contain all the relevant data and steps that would be required for the performance of sieve analysis of fine aggregates.
Site investigation for multistorey buildingKiran Birdi
Preliminary and Detailed Investigation of Site.
It is done to check whether the site is feasible for Multistorey Building or not.
In this, I have calculated the Bearing Capacity of Soil by performing SPT.
Class notes of Geotechnical Engineering course I used to teach at UET Lahore. Feel free to download the slide show.
Anyone looking to modify these files and use them for their own teaching purposes can contact me directly to get hold of editable version.
Particle Size Distribution & Classification of Soilwasim shaikh
According to the US classification standards, soil particles are divided into seven grades: clay particles <0.002 mm, silt particles 0.002–0.05 mm, very fine sand 0.05–0.1 mm, fine sand 0.1–0.25 mm, medium sand 0.25–0.5 mm, coarse sand 0.5–1.0 mm, and very coarse sand 1–2 mm.
Determination of strength and stress-strain relationships of a cylindrical specimen of reconstituted specimen using Consolidated Drained (CD) Triaxial Test.
1. A series of drained triaxial tests under four different initial states were conducted on Yamuna River sand. The results consist of simple stress-strain relation, change in volume behaviour were plotted.
2. Basic stress-strain relation with volume behaviour was presented in plot. The results for densely prepared sand samples show an expected behaviour. There is a significant difference in peak and residual deviatoric stress (q) as can be depicted form the plot.
3. With increase in confining stress, load carrying capacity of specimen increases.
4. Saturation value ‘B’ must be acquired to be more than 0.95 before starting the isotropic consolidation phase in CD test.
5. CD tests are performed at much slower strain rate as compared to CU tests for the same soil. The strain rate for CD test can be chosen approx. 8-10 times lower than the CU test.
6. It is important to have no pore water pressure generation throughout the shearing phase of CD test or in other words strain rate must be so small that pore water pressure must get dissipated quickly when specimen is subjected to compression loading in CD test.
7. In CD test, volumetric strain versus axial strain relationship shows contractive response for NC soils and dilative response for OC soils. (NC = Normally consolidated, OC = Over consolidated)
References:
1. IS: 2720 (Part 11):1993- Determination of the shear strength parameters of a specimen tested in unconsolidated undrained triaxial compression without the measurement of pore water pressure (first revision). Reaffirmed- Dec 2016.
2. IS: 2720 (Part 12):1981- Determination of Shear Strength parameters of Soil from consolidated undrained triaxial compression test with measurement of pore water pressure (first revision). Reaffirmed- Dec 2016.
3. ASTM D7181-11. Method for Consolidated Drained Triaxial Compression Test for Soils; ASTM: West Conshohocken, PA, USA, 2011.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
1. CIVL 1101 Sieve Analysis 1/7
Mechanical Analysis of Soil
Mechanical Analysis of Soil
As complex as it is, soil can be described simply.
It consists of four major components: air, water, organic
matter, and mineral matter.
Mechanical Analysis of Soil
The structure of soil determines its suitability for concrete,
road subsurface, building foundation, or filter media.
Soil has four constituent parts:
Sand is any soil particle larger than 0.06 millimeters (0.002
inches).
Silt is any soil particle from 0.002 - 0.06 millimeters.
Clay is any soil particle below 0.002 millimeters, including
colloidal clay so small it does not settle out of suspension in
water.
Mechanical Analysis of Soil
Mechanical Analysis of Soil
The percentage distribution of those parts determines soil
structure.
Mechanical analysis is the determination of the size range
of particles present in a soil, expressed as a percentage of
the total dry weight.
There are two methods generally used to find the particle-size
distribution of soil:
(1) sieve analysis - for particle sizes larger than 0.075 mm
in diameter, and
(2) hydrometer analysis - for particle sizes smaller
than 0.075 mm in diameter.
Mechanical Analysis of Soil
Sieve analysis Hydrometer analysis
2. CIVL 1101 Sieve Analysis 2/7
Sieve Analysis
Sieve analysis consists of shaking the soil sample through a
set of sieves that have progressively smaller openings.
Sieve Analysis
Sieve analysis consists of shaking the soil sample through a
set of sieves that have progressively smaller openings.
Sieve Analysis
Sieve Number Opening (mm)
4 4.750
6 3.350
8 2.360
10 2.000
16 1.180
20 0.850
30 0.600
40 0.425
50 0.300
60 0.250
80 0.180
100 0.150
140 0.106
170 0.088
200 0.075
270 0.053
Sieve Analysis
First the soil is oven dried and then all lumps are broken
into small particle before they are passed through the
sieves
After the completion of the
shaking period the mass of
soil retained on each sieve
is determined
Sieve Analysis
The results of sieve analysis are generally expressed in
terms of the percentage of the total weight of soil that
passed through different sieves
Mass of soil
Sieve # Diameter retained on Percent Cumlative Percent
(mm) each sieve (g) retained (%) retained (%) finer (%)
10 2.000 0.00 0.00% 0.00% 100.00%
16 1.180 9.90 2.20% 2.20% 97.80%
30 0.600 24.66 5.48% 7.68% 92.32%
40 0.425 17.60 3.91% 11.59% 88.41%
60 0.250 23.90 5.31% 16.90% 83.10%
100 0.150 35.10 7.80% 24.70% 75.30%
200 0.075 59.85 13.30% 38.00% 62.00%
Pan 278.99 62.00% 100.00% 0.00%
Sum = 450.0
Sieve Analysis
The results of sieve analysis are generally expressed in
terms of the percentage of the total weight of soil that
passed through different sieves
Mass of soil
Sieve # Diameter retained on Percent Cumlative Percent
(mm) each sieve (g) retained (%) retained (%) finer (%)
10 2.000 0.00 0.00% 0.00% 100.00%
16 1.180 9.90 2.20% 2.20% 97.80%
30 0.600 24.66 5.48% 7.68% 92.32%
40 0.425 17.60 3.91% 11.59% 88.41%
60 0.250 23.90 5.31% 16.90% 83.10%
100 0.150 35.10 7.80% 24.70% 75.30%
200 0.075 59.85 13.30% 38.00% 62.00%
Pan 278.99 62.00% 100.00% 0.00%
Sum = 450.0
3. CIVL 1101 Sieve Analysis 3/7
Sieve Analysis
The results of sieve analysis are generally expressed in
terms of the percentage of the total weight of soil that
passed through different sieves
Mass of soil
Sieve # Diameter retained on Percent Cumlative Percent
(mm) each sieve (g) retained (%) retained (%) finer (%)
10 2.000 0.00 0.00% 0.00% 100.00%
16 1.180 9.90 2.20% 2.20% 97.80%
30 0.600 24.66 5.48% 7.68% 92.32%
40 0.425 17.60 3.91% 11.59% 88.41%
60 0.250 23.90 5.31% 16.90% 83.10%
100 0.150 35.10 7.80% 24.70% 75.30%
200 0.075 59.85 13.30% 38.00% 62.00%
Pan 278.99 62.00% 100.00% 0.00%
Sum = 450.0
Particle-Size Distribution Curve
The results of mechanical analysis (sieve and hydrometer
analyses) are generally presented by semi-logarithmic plots
known as particle-size distribution curves.
The particle diameters are plotted in log scale, and the
corresponding percent finer in arithmetic scale.
Particle-Size Distribution Curve
Silt and clay
Sand
Particle diameter (mm)
Percent finer (%)
Recommended Procedure
1. Weigh to 0.1 g each sieve which is to be used
2. Select with care a test sample which is representative
of the soil to be tested
3. Weigh to 0.1 a specimen of approximately 500 g
of oven-dried soil
4. Sieve the soil through a nest of sieves by hand
shaking. At least 10 minutes of hand sieving is
desirable for soils with small particles.
5. Weigh to 0.1 g each sieve and the pan with the soil retained on them.
6. Subtract the weights obtained in step 1 from those of step 5 to give
the weight of soil retained on each sieve.
The sum of these retained weights should be checked against the
original soil weight.
Calculations
Percentage retained on any sieve:
weight of soil retained 100%
total soil weight
Cumulative percentage retained on any sieve:
Percentage retained
Percentage finer than an sieve size:
100% Percentage retained
Effective Size, Uniformity Coefficient, and
Coefficient of Gradation
Three basic soil parameters can be determined from
these grain-size distribution curves:
Effective size
Uniformity coefficient
Coefficient of gradation
The diameter in the particle-size distribution curve
corresponding to 10% finer is defined as the effective
size, or D10.
4. CIVL 1101 Sieve Analysis 4/7
Particle diameter (mm)
Percent finer (%)
Effective Size, Uniformity Coefficient, and
Coefficient of Gradation
Find D10:
Reading Semi-Logarithmic Scales
In science and engineering, a semi-log graph or semi-log
plot is a way of visualizing data that are changing with
an exponential relationship.
One axis is plotted on a logarithmic scale.
This kind of plot is useful when one of the variables being
plotted covers a large range of values and the other has
only a restricted range
The advantage being that it can bring out features in the
data that would not easily be seen if both variables had
been plotted linearly.
Reading Semi-Logarithmic Scales
To facilitate use with logarithmic tables, one usually takes
logs to base 10 or e
Let’s look at the log scale:
8 9
0.8 0.9
0.1 1.0 10
2 3 4 5 6 7
0.2 0.3 0.4 0.5 0.6 0.7
Reading Semi-Logarithmic Scales
To facilitate use with logarithmic tables, one usually takes
logs to base 10 or e
Let’s look at some values on a log scale and practice
interpolation values:
0.24
0.1 1.0 10
0.2 0.3
0.82
0.8 0.9
4.9
4 5
Particle diameter (mm)
Percent finer (%)
Effective Size, Uniformity Coefficient, and
Coefficient of Gradation
Find D10:
Particle diameter (mm)
Percent finer (%)
Effective Size, Uniformity Coefficient, and
Coefficient of Gradation
0.09 0.1
D10 = 0.093 mm
5. CIVL 1101 Sieve Analysis 5/7
Effective Size, Uniformity Coefficient, and
Coefficient of Gradation
The uniformity coefficient is given by the relation:
C D
60
10
u
D
Where D60 is the diameter corresponding to 60% finer in
the particle-size distribution
Effective Size, Uniformity Coefficient, and
Coefficient of Gradation
Particle diameter (mm)
Percent finer (%)
D60 = 0.51 mm
Find D60:
Effective Size, Uniformity Coefficient, and
Coefficient of Gradation
The coefficient of gradation may he expressed as:
2
30
C D
10 60
c
D D
Where D30 is the diameter corresponding to 30% finer in
the particle-size distribution
Effective Size, Uniformity Coefficient, and
Coefficient of Gradation
(%)
finer D30 = 0.25 mm
Percent Particle diameter (mm) Find D30:
Effective Size, Uniformity Coefficient, and
Coefficient of Gradation
For the particle-size distribution curve we just used, the
values of D10, D30, and D60 are:
D10 = 0.093 mm D30 = 0.25 mm D60 = 0.51 mm
C D
0.51 5.5
60
10
u
D
mm
mm
0.093
2
30
C D
10 60
c
D D
(0.25 mm
)2 1.3
0.51
0.093
mm mm
Effective Size, Uniformity Coefficient, and
The particle-size distribution curve shows not only the
range of particle sizes present in a soil but also the type
of distribution of various size particles.
Particle diameter (mm)
Percent finer (%)
Coefficient of Gradation
6. CIVL 1101 Sieve Analysis 6/7
Effective Size, Uniformity Coefficient, and
This particle-size distribution represents a soil in which
the particles are distributed over a wide range, termed
well graded
Particle diameter (mm)
Percent finer (%)
Coefficient of Gradation
Effective Size, Uniformity Coefficient, and
This particle-size distribution represents a type of soil in
which most of the soil grains are the same size. This is
called a uniformly graded soil.
Particle diameter (mm)
Percent finer (%)
Coefficient of Gradation
Effective Size, Uniformity Coefficient, and
This particle-size distribution represents such a soil. This
type of soil is termed gap graded.
Particle diameter (mm)
Percent finer (%)
Coefficient of Gradation
Example Sieve Analysis
From the results of a sieve analysis, shown below,
determine:
(a) the percent finer than each sieve and plot a grain-size
distribution curve,
(b) D10, D30, D60 from the grain-size distribution curve,
(c) the uniformity coefficient, Cu, and
Sieve
Number
(d) the coefficient of gradation, Cc.
Diameter
(mm)
Mass of soil retained
on each sieve (g)
4 4.750 28
10 2.000 42
20 0.850 48
40 0.425 128
60 0.250 221
100 0.150 86
200 0.075 40
Pan –– 24
Example Sieve Analysis
Sieve
Number
Diameter
(mm)
Mass of soil retained
on each sieve (g)
4 4.750 28
10 2.000 42
20 0.850 48
40 0.425 128
60 0.250 221
100 0.150 86
200 0.075 40
Pan –– 24
Example Sieve Analysis
Sieve
Number
Mass of soil
retained
on each sieve
(g)
Percent
retained
on each
sieve (%)
Cumulative
percent
retained on each
sieve (%)
Percent
finer (%)
4 28 4.54 4.54 95.46
10 42 6.81 11.35 88.65
20 48 7.78 19.13 80.87
40 128 20.75 39.88 60.12
60 221 35.82 75.70 24.30
100 86 19.93 89.63 10.37
200 40 6.48 96.11 3.89
Pan 24 3.89 100.00 0
617
7. CIVL 1101 Sieve Analysis 7/7
Example Sieve Analysis
Sieve
Number
Mass of soil
retained
on each sieve
(g)
Percent
retained
on each
sieve (%)
Cumulative
percent
retained on each
sieve (%)
Percent
finer (%)
4 28 4.54 4.54 95.46
10 42 6.81 11.35 88.65
20 48 7.78 19.13 80.87
40 128 20.75 39.88 60.12
60 221 35.82 75.70 24.30
100 86 19.93 89.63 10.37
200 40 6.48 96.11 3.89
Pan 24 3.89 100.00 0
617
Particle diameter (mm)
Percent finer (%)
Example Sieve Analysis
D10 = 0.14 mm
D30 = 0.27 mm
D60 = 0.42 mm
Example Sieve Analysis
For the particle-size distribution curve we just used, the
values of D10, D30, and D60 are:
D10 = 0.14 mm D30 = 0.27 mm D60 = 0.42 mm
C D
0.42 3.0
60
10
u
D
0.14
mm
mm
2
30
C D
10 60
c
D D
(0.27 mm
)2 1.2
0.42
0.14
mm mm
Mechanical Analysis of Soil
Any Questions?
Particle diameter (mm)
Percent finer (%)