Aggregate Properties_lab5
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1 Laboratory 3: Aggregate Properties CEE 3020 Civil Engineering Materials Submitted to: Alex Wu Savannah Lynn Howard by: Fukhraj Khairy
Section B4 Group Braxton Brown Fukhraj Khairy Jimmy Rivas Nicklaus Foster Oscar Cleveland 3/5/23 Quiz _____ / 4 Abstract _____ / 8 Introduction _____ / 8 Experiment _____ / 5 Results _____ / 25 Discussion _____ / 25 Conclusion _____ / 10 Technical Writing _____ / 10 Graphics and Design _____ / 5 Total _____ / 100
2 Abstract The objective of this experiment is to determine the specific gravity, water absorption capacity, and fineness modulus of a laboratory-provided aggregate sample. The specific gravity is obtained by measuring the weight of the aggregate four times, before and after adding water, after vacuum pump removal of air, and after baking. The specific gravity and water absorption capacity are then calculated from these measurements. To determine the sample aggregate's gradation, it is passed through a stack of six sieves to separate it into six different sizes, and the weight of each particle on each sieve is divided by the total weight of aggregate on the sieve. The resulting values are 2.4972 for the apparent specific gravity (dry), 2.4858 for the bulk specific gravity (dry), 2.4903 for the bulk specific gravity (SSD), and 0.1828% for the water absorption capacity. The bulk specific gravity (dry) has the lowest value, the apparent specific gravity (dry) has the highest value, and the bulk specific gravity (SSD) is in the middle when specific gravity is listed in incremental order. The density of the aggregate is 143.8 pound-force per cubic foot, obtained by multiplying the density of water with the bulk specific gravity. Heavyweight aggregates have a density greater than 150, and lightweight aggregates have a density less than 70, indicating that the sample aggregate is classified as normal weight. The fineness modulus is determined by dividing the cumulative percent retained by 100, yielding a value of 2.599, which suggests that the sample aggregate has a fine gradation with a range of 2.3 to 3.1. A higher value indicates coarser aggregate, and a lower value indicates finer aggregate.
3 Table of Contents
Abstract
2 Table of Contents
3 Introduction
4 Experiment
4 Results
4 Discussion
7 Conclusion
9
References
10
Appendix
1
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4 Introduction Aggregates are available in various shapes and sizes, and each type possesses unique qualities such as stability and water absorption rate, which contribute to the functionality of concrete. Therefore, it is essential to consider these characteristics before mixing the aggregate with the mortar paste to create a concrete mix that maximizes strength, durability, workability, and reduces cost. To determine the most suitable aggregate for a particular project, several tests need to be performed, including specific gravity and water absorption tests. According to Gopal Mishra from The Constructor, the main objective of these tests is to evaluate the strength and quality of the material and determine the water absorption capacity of the aggregate. The first part of the lab aims to determine the specific gravity and absorption of the sample aggregate in a saturated, surface-dry condition. Construction aggregates are made up of various pebble particles of different sizes, and a sieve can be used to analyze their size distribution or gradation, which is crucial in determining their suitability for the concrete mix. As Haseeb Jamal from the Uniform points out, grading limits and maximum aggregate size are specified because these properties affect the amount of aggregate used, as well as cement and water requirements, workability, and durability of concrete. Additionally, the fineness modulus can be calculated using the cumulative percent weight of aggregates separated by each sieve, which provides insight into the aggregate's coarseness or fineness. The second part of the lab involves checking the grain size distribution using multiple layers of sieves and determining the fineness modulus of the sample aggregate.
5 Experiment Materials The materials for this experiment are the same as those described in the Laboratory 5:
Aggregate Properties (Stewart, 2023).
Equipment The materials for this experiment are the same as those described in the Laboratory 5:
Aggregate Properties (Stewart, 2023).
Procedure The materials for this experiment are the same as those described in the Laboratory 5:
Aggregate Properties (Stewart, 2023). Results Part A: Table 1: Represents the weight of aggregate and experiment tools used throughout the experiment.
Fine Aggregate Test Data
SSD Weight in the air (D) 400.00g Weight of flask + water (B) 576.20 g Weight of flask + water + Sample (C) 815.58 g Oven dry weight with pan 415.91g Tall metal pan weight 16.64 g Oven dry weight without pan (A) 399.27 g Table 2: Represents the specific gravity of aggregate in different water levels and absorption capacity.
Summary of Test Results
Fine Aggregate Apparent Specific Gravity (dry) A/(B+A-C) 2.4972 Bulk Specific Gravity (dry) A/(B+D-C) 2.4858 Bulk Specific Gravity (SSD) D/(B+A-C) 2.4903 Absorption (D-A)/(A)*100% 0.1828% Table 3: Represents the formula and process of calculating the specific gravity and absorption capacity.
Formula Calculation
6 Apparent Specific Gravity (DRY) A / (B+A-C) 399.27 / (576.20 + 399.27 –
815.58) = 2.4972 Bulk Specific Gravity (DRY) A / (B+D-C) 399.27 / (576.20+ 400.00 –
815.58) = 2.4858 Bulk Specific Gravity (SSD) D / (B+D-C) 400.00 / (576.20+ 400.00 –
815.58) = 2.4903 Absorption capacity (D-A) / (A) x 100 (400.00- 399.27)/399.27 * 100% = 0.1828% Part B: Table 4: Represents separated aggregate weight by each sieve and fineness modulus value of aggregate based on the measured weight values.
Sieve Analysis Test Data
Initial Weight of Aggregate 411.38 g Sieve # Sieve Weight (g) Sieve + material (g) Weight Retained (g) Cumulative Weight Retained (g) Cumulative % Retained % Passing 4 584.05 587.22 3.67 3.67 0.87 99.13 8 678.11 700.90 22.79 26.46 6.43 93.57 16 654.11 713.80 59.69 86.15 20.94 79.06 30 584.18 710.47 116.29 202.44 49.23 50.77 50 542.23 693.47 150.94 353.38 85.93 14.07 100 362.10 405.60 43.5 396.88 96.51 3.49 200 350.17 362.60 12.43 409.31 99.54 0.46 Base 472.82 474.73 1.91 411.22 100.0 0.00
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7 Fineness Modulus Calculation Sample Calculation (Fineness modulus) | (
Culminative % retained / 100) (0.89+ 6.435+ 20.95 + 49.23 + 85.93 + 96.51)/100 = 2.599 Fineness Modulus (FM) 2.599g Figure 1
: Shows the relationship between the particle size of aggregate in millimeters and the amount of aggregate passing through the sieves in percentage.
Discussion Part A: 1.
Discuss possible sources of error in test procedure or calculations which may have affected the test results. There are possible sources of error that could have affected the test results. The calculation error happens when solving a calculation incorrectly to find results. Simple calculations are required when finding specific gravity and water absorption capacity, but little mathematical errors, such as using the wrong mathematic symbol or following the incorrect mathematic order, could lead to an inaccurate result. The observation error happens when values are inaccurately surveyed during the lab. A digital scale was used to measure the weight of aggregate and tick marks on the volumetric cylinder were used to measure the height of water. Not resetting the scale to zero before measuring the weight and reading a wrong tick mark on the cylinder could lead to collecting inaccurate data. The instrumental error happens when the test equipment is not properly used according to the lab manual or handled incorrectly. During the lab, SSD aggregate and tab water was mixed in a volumetric flask and connected to a vacuum pump to remove any air bubbles. While applying the rolling motion to fasten the air removal process, a tube that connects the vacuum pump to a volumetric flask was disconnected for a brief second due to a faulty connection. Accidental disconnection could have introduced air to the mixture and reduced the density of the sample aggregate.
8 2.
Compare values of apparent specific gravity, bulk specific gravity (SSD), and bulk specific gravity (oven dry). Does the relationship, G
b
<G
bSSD
<G
a
, hold true? Explain why or why not. The apparent specific gravity of dry aggregate is 2.4972, the bulk specific gravity of dry aggregate is 2.4858, and the bulk specific gravity of SSD aggregate is 2.4903. Laying those numbers in increment order shows that the bulk specific gravity (oven dry) has the lowest value, the bulk specific gravity (SSD) has the second largest value, and the apparent specific gravity is the largest among other values. So, the relationship, G
b
<G
bSSD
<G
a
, does hold true. This is because the weight of the oven dry sample has the smallest measurement. When calculating the apparent specific gravity and the dry bulk specific gravity, they both contain the same numerator. However, the apparent specific gravity is divided by a smaller value which results in a larger final apparent specific gravity value. On the other hand, calculating the bulk specific gravity requires division with a larger denominator, which yields a smaller result. Finally, the dry and SSD bulk specific gravity calculation shares the same denominator as its dry counterpart, but SSD bulk specific gravity has a larger numerator, which yields a larger result than the dry bulk specific gravity. 3.
Classify the aggregate as light, normal, or heavy weight based on the classification of aggregate by specific gravity (or density) described in class. Aggregates can be classified into three types based on density: light, normal, and heavy. According to the lecture 3 slide (Dai), Lightweight is typically less than 70 pound-force per cubic foot. Normal weight is when the density of aggregates is between 70 to 110 pound-force per cubic foot. Heavyweight is any density that is larger than 150 pound-force per cubic foot. The density of water is 62.4 pounds per cubic foot multiplying the bulk specific gravity of aggregate
9 gives 143.8 pound-force per cubic foot. Since the pound-force per cubic foot of sample aggregate is less than the starting force value for the heavyweight, the density of the sample aggregate could be classified as normal weight. 4.
Suppose you had a 10 kg (10,000g) sample of this aggregate at an air-dry condition (MC = 0.07%). How much water (in grams) would be needed to bring the sample to SSD conditions? Show your calculations. W
moist = (MC * W
dry
) / 100 + W
dry = (0.07 * 10,000) / 100 + 10,000 = 10,007 g W
water - W
moist = 10,007 - 10,000 = 7g W
dry - W
water = 10,000 - 7 = 9,993 g W
moist = (MC * W
oven dry
) / 100 + W
oven dry = (1.54 * 9,993) / 100 + 9,993 = 10,146.89 g W
SSD = W
moist - W
dry = 10,146.89 - 9,993g = 153.89 g W = W
SSD - W
dry = 153.89 - 7 = 146.89 Ten kilograms of aggregate sample in air dry condition with the moisture content of 0.07% require 146.89 grams of water to bring the sample to SSD condition. 5.
Suppose you take the 10 kg air-dry aggregate sample from problem 4 and add 2 kg of oven-
dry glass microbeads (G = 2.4). How will that affect your sample’s moisture content and specific gravity?
Show all calculations. W
total = 10,000 + 2,000 = 12,000 Moisture content percent = 0.0583 % (SSD
MC
/ total weight )(100) = 7/12,000 x 100 =0.0583 % G
total = (G
agg * W
agg + G
beads * W
agg
) / W
total = (2.47 * 10,000 + 2.4 * 2,000) / 12,000 = 2.45 6.
Would you expect this new hybrid material to result in stronger and more durable concrete than if you used the original aggregate? Explain. Assume the beads are smooth impermeable spheres. Adding two kilograms of oven-dry glass microbeads with a specific gravity of 2.4 to the ten kilograms of air dry aggregates will decrease the specific gravity from 2.47 to 2.45 and the moist content from 0.7% to 0.058%. Glass microbeads might act as a filling for the air-dry aggregate and make the concrete mix more durable and less permeability than the concrete mix with the original aggregate, but the fact that glass is made out of silica, it could lead to the reaction with alkalis and fasten the corrosion.
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10 Part B: 1.
Discuss possible sources of error in test procedure or calculations that may have affected the test results. There are possible sources of error that could have affected the test results. The calculation error happens when solving a calculation incorrectly to find results. Calculating retained weight and percentage of retained aggregate requires multiple mathematic steps. Performing the wrong steps to find the retained weight can lead to incorrect results. The observation error happens when values are inaccurately surveyed during the experiment. A digital scale was used to measure the weight of the aggregate and each layer of sieves. Not resetting the scale to zero before measuring weight can result in collecting faulty weight values and calculating an inaccurate fineness modulus value. The instrumental error happens when the test equipment is not properly used according to the lab manual or handled incorrectly. Before pouring aggregates into the sieve tower, sieves have to be cleaned with a brush to remove as many aggregate particles that are stuck in a sieve crossing. There were some fine particles that were stuck on the sieve crossing. Failing to remove particles could lead to faulty data which can lead to inaccurate results. 2.
Compare the FM of the lab sample to the FM for the aggregate sample in Table 5.7 of the textbook. Which aggregate is “more fine”?
The fineness modulus of the lab sample is 2.599 and the fineness modulus for the aggregate sample in Table 5.7 of the textbook (Mamlouk, 2018) is 2.86. According to the textbook definition of fineness modulus, a higher number represents the coarser aggregate and a smaller number means a finer aggregate. So, the lab sample, which has a smaller fineness modulus value than the textbook example, is more fine. 3.
Do aggregates with the same FM necessarily have the same gradation? Explain. The fineness modulus is a good way to determine the fineness characteristics and gradation of aggregate, but this is not appropriate in every situation. For example, two aggregate samples that have the same value of fineness modulus could have different gradations. Calculating the fineness modulus requires dividing the sum of cumulative percent retained by one hundred. The Sum of cumulative percent retained does not consider which sieves have higher aggregate retainment, which is important to determine if the aggregate is coarse or fine. No matter how large the retainment is for the large sieve size or small sieve size, if the sum of the cumulative percent retain is the same, then the fineness modulus will be equal. 4.
Use the gradation plot generated from the lab data to classify the aggregate as open, gap, uniform, well, or dense graded, as defined in the lecture. There are five types of gradation that aggregates are formed: well-graded, uniform, open, gap, and dense. Figure 5.15 of the textbook (Mamlouk, 2018) shows those five types of gradations plotted on the particle size versus the percent passing graph. A graph drawn with the lab data as shown in Figure 1 has a sudden horizontal spike in the middle of the graph, which has a similarity to the graph of the gap graded aggregate graph shown in the textbook. This led to the conclusion that the sample used in a lab is a gap graded aggregate. The graph that shows the particle size distribution for gap graded aggregate has a sudden horizontal increment because the aggregate has missing one or more aggregate sizes that are large or small.
11 5.
The gradations and the specific gravity of two aggregates (Aggregate A and Aggregate B) are given below. Graph the gradation and determine the specific gravity of the aggregate which combines 20% Aggregate A, 40% Aggregate B, and 40% of the sand used in the laboratory. Figure 2
: Shows the relationship between the aggregate particle size and the amount of aggregate passing through the sieves for a combined mixture of aggregate A, aggregate B, and sample aggregate.
GT = (WAgg A * GAgg A + WAgg B * GAgg B + W Agg Lab * G Agg Lab) / 100 = (20 * 2.65 + 40 * 2.75 + 40 * 2.33) /100 = 2.56 The aggregate that combines 20% Aggregate A, 40% Aggregate B, and 40% of the sample used in the laboratory have a specific gravity of 2.56. Conclusions In the first part of the laboratory experiment, the main objective was to observe the change in specific gravity of aggregate as the water and air level changes. The specific gravity and water absorption test were conducted successfully, and the obtained data indicated a relationship between specific gravity and different stages. The initial weight of the aggregate was measured using B1-YEM data, which was 400.00 grams. The specific gravity was determined using a formula, which resulted in three values: the apparent specific gravity of dry aggregate was 2.4972, the bulk specific gravity of SSD aggregate was 2.4903, and the bulk specific gravity of dry aggregate was 2.4858. It was observed that the apparent specific gravity had the highest value, followed by the bulk specific gravity of SSD, and the bulk specific gravity of dry aggregate had the lowest specific gravity value. Moreover, the sample aggregate density was calculated to be 143.8-pound force per cubic foot, indicating that it could be classified as normal weight. Additionally, the absorption capacity of aggregate was found to be 0.1828 %. The second part of the laboratory experiment aimed to determine the gradation of the sample aggregate by using multiple sieves and finding the fineness modulus. The sample aggregate was separated by the size of particles using sieves, and the cumulative percent retained for each sized sieve was calculated. The fineness modulus of the sample aggregate was found to be 2.599, which falls under the range of fine aggregate in the textbook (Mamlouk, 2018). This indicates that the sample aggregate has a fine gradation.
12 However, finding the fineness modulus alone cannot entirely explain the fineness of the sample aggregate. The issue with finding the fineness modulus is that it does not specify which sized sieve separated more particles from the sample aggregate. This can be mitigated by creating a grain size distribution graph, which shows which sized sieve separated more particles. Based on the graph's shape, the type of aggregate can be determined. The sample aggregate used in part B of the experiment had a sudden horizontal increment in the middle of the graph, indicating that it is similar to gap-graded aggregate. In conclusion, the laboratory experiment was successful in determining the specific gravity, water absorption, gradation, and fineness modulus of the sample aggregate. The specific gravity values showed that the sample aggregate could be classified as normal weight, while the fineness modulus and grain size distribution graph indicated that it had a fine gradation and was similar to gap-graded aggregate. The obtained data could be useful in designing concrete mixtures and determining the strength and durability of concrete structures.
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13 References Lauren K. Stewart (2023).
Laboratory 3 Handout “Aggregate Properties
” Georgia Institute of Technology Lauren K. Stewart (2023).
Lecture Slides. Georgia Institute of Technology. Jamal, H. (2019, October 5). Haseeb Jamal
. Uniform. Retrieved March 4, 2023, from https://www.aboutcivil.org/gradation-of-aggregates Mamlouk, M. S. and Zaniewski, J. P. (2018). Materials for civil and Construction Engineers, 4th Edition
., Pearson, New Jersey. Mishra, G. (2018, September 11). Specific gravity and water absorption tests on aggregates
. The Constructor. Retrieved March 4, 2023, from https://theconstructor.org/building/aggregates-specific-gravit y-water-absorption-test/1358/
14 Appendix