This document outlines a procedure to determine the particle size distribution of fine aggregates through sieving. The test aims to classify fine aggregates according to grading zones based on percentages retained on various sieve sizes. Fine aggregates are sieved through a series of sieves ranging from 4.75mm to 75μm. The weights retained on each sieve are recorded to calculate the cumulative percentage retained and fineness modulus. The results of this test can be used to inform concrete mix design based on the gradation characteristics of the fine aggregates.
MEANING OF MIX DESIGN
GRADE OF CONCRETE.
FACTORS INFLUCING THE CHOICE OF MIX DESIGN.
MATHODS OF CONCRETE MIX DESIGN
MIX DESIGN BY INDIAN STANDARD METHOD.
MEANING OF MIX DESIGN
GRADE OF CONCRETE.
FACTORS INFLUCING THE CHOICE OF MIX DESIGN.
MATHODS OF CONCRETE MIX DESIGN
MIX DESIGN BY INDIAN STANDARD METHOD.
Design of Reinforced Concrete Structure (IS 456:2000)MachenLink
This is the 1st Lecture Series on Design Reinforced Cement Concrete (IS 456 -2000).
In this video, you will learn about the objective of structural designing and then basic properties of concrete and steel.
Concrete properties like...
1. Grade of Concrete
2. Modulus of Elasticity
3. Characteristic Strength
4. Tensile Strength
5. Creep and Shrinkage
6. Durability
Reinforced Steel Properties....
1. Grade and types of steel
2. Yield Strength of Mild Steel and HYSD Bars
Lesson: Concrete Technology - Building Materials
The quality of aggregate affect the durability and strength of concrete. Since about 3/4 of the volume of concrete is occupied by aggregate.
In the following pages to follow an attempt is being made to bring forward a brief analysis about the concrete mix designs of M30 and M40 concrete. Here an effort has been made to find out the compressive strengths developed by both M30 and M40 concrete not only by its normal mix design but also through addition of admixtures and fibres.
The theories presented here have been adopted from the study of various standard codes available for the conduct of civil engineers. Any suggestions and queries regarding correction of the theories as well as the numerical presentations are welcome.
Close care has been taken to present the design solution calculation to the nearest possible decimal values and any error or misprint in the calculations may suitably be considered.
Design of Reinforced Concrete Structure (IS 456:2000)MachenLink
This is the 1st Lecture Series on Design Reinforced Cement Concrete (IS 456 -2000).
In this video, you will learn about the objective of structural designing and then basic properties of concrete and steel.
Concrete properties like...
1. Grade of Concrete
2. Modulus of Elasticity
3. Characteristic Strength
4. Tensile Strength
5. Creep and Shrinkage
6. Durability
Reinforced Steel Properties....
1. Grade and types of steel
2. Yield Strength of Mild Steel and HYSD Bars
Lesson: Concrete Technology - Building Materials
The quality of aggregate affect the durability and strength of concrete. Since about 3/4 of the volume of concrete is occupied by aggregate.
In the following pages to follow an attempt is being made to bring forward a brief analysis about the concrete mix designs of M30 and M40 concrete. Here an effort has been made to find out the compressive strengths developed by both M30 and M40 concrete not only by its normal mix design but also through addition of admixtures and fibres.
The theories presented here have been adopted from the study of various standard codes available for the conduct of civil engineers. Any suggestions and queries regarding correction of the theories as well as the numerical presentations are welcome.
Close care has been taken to present the design solution calculation to the nearest possible decimal values and any error or misprint in the calculations may suitably be considered.
STUDY ON THE EFFECT OF REPLACEMENT OF FINE AGGREGATE WITH PLASTIC GRANULES AL...AM Publications
Concrete is an ancient material of construction, first used during Roman Empire. Concrete is the second most consumed substance in the world after water. Plastic is a common material which finds its application in day today life. Lack of proper disposal methods for plastic waste is one of the main hazards faced by present the world. Plastic is of manmade material and is a stable polymer which is light in weight. The reduction of waste plastic is essential as it creates various environmental problems. This paper deals with the partial replacement of fine aggregate with plastic granules and using a fixed proportion of steel and polypropylene fibers. Experimental program includes two stages. In the first stage fine aggregate is replaced with 4%,8%,12% plastic granules in an M30 grade of concrete and its percentage was optimized and in the second stage, the residual strength of the above mixes were found out by heating the specimens to2000c,3000c and 4000c for one hour duration. Strength parameters studied includes compressive strength, flexural strength, split tensile strength, residual strength.
Effect of Copper Slag as a Fine Aggregate on Properties of ConcreteAM Publications
In this work, an extensive study using copper slag has been carried out to investigate strength, workability and durability. Copper slag is an industrial by-product material produced from the process of manufacturing copper. For, 2.2 tonnes of copper slag is generated at every ton of copper production in the world of copper industry, it has approximately 26.6 million tons of copper slag are generated. Copper slag as a substitute for conventional fine aggregate with partial or full replacement using M25 grade concrete The main objective is to encourage the use of these seemingly waste products as a construction material. In this paper , the effect of using copper slag as a fine aggregate on properties of cement mortars and concrete various mortars & concrete mixtures were prepared with different proportions of copper slag ranging from (0CS+100S)%, (10CS+90S)%, (20CS+80S)%,(30CS+70S)%, (40CS+60S)%, (50CS+50S)%, (60CS+40S)%, (70CS+30S)%, (80CS+20S)%, (90CS+10S)%, (100+0S)%. Form the above test result we concluded that the 50% CS+50% S gives optimum proportional of CS that can be used as a replacement substitute material for fine aggregate in concrete. The design M25 grade concrete for 50% replacement of CS shows the HPC characteristics. The design M25 grade concrete for 30% replacement of CS shows the HPC characteristics. We can fully replace (100%CS) by fine aggregate in concrete, because of above all test result more than control mix. We can use any proportion of CS replacement as pre our requirement for creating concrete, because we concluded that the all result of replacement of CS is more than control mix.
SAMPLE DATA TO SHOW THE SIZE OF COARSE AND FINE AGGREGATES. THIS REPORT IS FROM CONCRETE LAB OF UCE&T BZU MULTAN PAKISTAN. THE SAND USED HAS A FINENESS MODULUS OF .95.
Investigation of behaviour of concrete on adding crumbAbhimanyu Saraswat
Concrete is the basic ingredient for all types of construction. The current scenario of rapid urbanization and modernization, has resulted in escalated demand for aggregates, sand, water and cement. This demand has been met by causing extra burden on the environment. This thesis was an noble attempt to reduce that burden by replacing sand by "Crumb Rubber".
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/
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
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
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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.
1. Tests for sand and fine aggregate
AIM: To determine the particle size distribution of fine aggregates by sieving.
REFERENCE: IS 2386-1 (1963) - Methods of test for aggregates for concrete and IS
383 (1970): Specifications for coarse and fine aggregate from natural sources for
concrete.
SIGNIFICANCE:
Aggregate most of which passes 4.75 mm IS Sieve and contains only so much
coarser material such as natural sand, crushed stone sand and crushed
gravel sand.
As far as possible, flaky, scoriaceous and clongated pieces should be
avoided
The concrete mix design depends on the gradation of aggregates in a given
sample.
The sieve analysis of aggregate determines the % of sizes of aggregates in
the sample and hence packing as well as mix design ratios for a concrete
mix can be derived.
The sieve analysis of aggregates shows the gradation curve of various sizes of
aggregates in the given sample
IS Sieve
designation
Grading Zone
1
(in %)
Grading Zone 2
(in%)
Grading Zone 3
(in %)
Grading ZONE
4
(in %)
10 mm 100 100 100 100
4.75 mm 90-100 90-100 90-100 95-100
2.36 mm 60-95 75-100 85-100 95-100
1.18 mm 30-70 55-90 75-100 90-100
2. 600 mu 15-34 35-59 60-79 80-100
300 mu 5-20 8-30 12-40 15-50
150 mu 0-10 0-10 0-10 0-15
NOTE:
• For crushed stone sands, the dermissible limit on 150-micron IS Sieve is
increased to 20 percent. This does not affect the 5 percent allowance
permitted in order to sieve size
• Fine aggregate complying with the requirements of any grading zone in
• This table is for concrete but the quality of concrete produced will
depend upon a number of factors including proportions.
• Where concrete of high strength and good durability is required, line
aggregate conforming to any one of the four grading zones may be
used, but the concrete mix should be properly designed. As the
progressively finer, that is, from Grading Zones I to 4, the ratio of
aggregate grading & coarse aggregate should be progressively reduced.
• The most suitable fine to coarse ratio to be used for any particular mix will,
however, depend upon the actual grading, particle shape and surface
texture of both fine and coarse aggregates.
• It is recommended that fine aggregate conforming to Grading Zone IV
should not be used in reinforced concrete unless tests have been made
to ascertain the suitability of proposed mix proportions.
3. APPARATUS:
SR. NO. APPARATUS SPECIFICATION
1 Sieves Conforming to IS: 460- 1962
2.36 mm
1.18 mm
600 mu
300 mu
150 mu
75 mu
2 Balance Maximum capacity: 20 Kg; Minimum
capacity: 0.002kg
3 Brush Fine camel hair brush
MATRIALS :
Fine aggregrate ( particle size =< 4.75 mm)
SAMPLING AND SELECTION OF TEST SPECIMEN :
The sample shall be brought to an oven dry condition before weighing and
sieving.This may be achieved by heating at a temperature of 100 to 110
°C in the oven for 24 hrs.
The air-dry sample shall be weighed and sieved successively on the
appropriate sieves starting with the largest
Care shall be taken to ensure that the sieves are clean before use
4. PROCEDURE :
Sieve the aggregate using the appropriate sieves (80 mm, 40 mm, 20 mm, 10
mm, 4.75 mm, 2.36 mm, 1.18 mm, 600 micron, 300 micron & 150 micron)
The shaking shall be done with a varied motion, backwards and forwards, left
to right, circular clockwise and anti-clockwise. Material shall not be forced
through the sieve by hand pressure. Lumps of fine material, if present, may
be broken by gentle pressure
Light brushing with a brush may be used on the 150-micron and 75-micron IS
Sieves to prevent aggregation of powder and blinding of apertures.
On completion of sieving, the material retained on each sieve, shall be
weighed.
Record the weight of aggregate retained on each sieve.
Calculate the cumulative weight of aggregate retained on each sieve.
Calculate the cumulative percentage of aggregate retained.
Add the cumulative weight of aggregate retained and divide the sum by
100. This value is termed as fineness modulus
OBSERVATION TABLE
SIEVE
NO.
SIEVE
SIZE
(mm)
RETAINED
ON EACH
SIEVE (%Wt)
CUMULATIV
E
PERCENTAG
E RETAINED
PASSING
THROUGH
(%Wt)
GRADING
LIMITS/
REMARKS
1 4.75
mm
5.76 5.76 94.24
2 2.36
mm
9.135 14.89 85.11
3 1.18
mm
7.81 22.70 77.3
4 600 mu 11.61 34.305 65.65
5 300 mu 49.515 83.865 16.14
6 150 mu 11.54 95.405 4.595
5. 7 75 mu 4.155 99.56 0.44
FINENESS MODULUS = (5.76+4.89+22.7+34.305+83.865+95.405 + 99.56)/100 =
346.485/100
=3.46
RESULT
Fineness modulus of fine aggregate is 3.46.
6. 7 75 mu 4.155 99.56 0.44
FINENESS MODULUS = (5.76+4.89+22.7+34.305+83.865+95.405 + 99.56)/100 =
346.485/100
=3.46
RESULT
Fineness modulus of fine aggregate is 3.46.