An innovative & easy way of establishing a relationship ship between Schmidt's Hammer Rebound value & Uniaxial Compressive Strength, Point Load Index & Density of rocks to obtain the value of UCS on site. This method helps in eliminating the need of laboratory analysis of rock for UCS, Point Load Index & density determination.

1. Minor Project Presentation

2. Introduction
 Hardness is known to be one of the physical properties of materials. Various
methods to determine the hardness have been proposed (Brinell, Vickers,
Rockwell, Knoop, Schmidt, Shore, Mohr’s) depending on the properties' of the
material to be tested.
 However, traditional approach of obtaining hardness of rock involve complex
process & a number of allied instruments. The test carried with these
instruments require careful operation & a number of precautionary measures
to be followed.
 The Schmidt hardness test is a quick, cheap and non-destructive. It is widely
used for its simplicity, portability and the capability of instant data
production
 The Schmidt hammer, which was originally developed for measuring the
strength of hardened concrete (Schmidt, 1951) has later been improved to
predict the strength of rocks. Today, even though variety of Schmidt hammers
are available for use, the models of L-type and N-type are extensively
employed.

3. Significance of Project
Schmidt Hammer is used for prediction of unconfined
compressive strength of rock samples by performing
Schmidt’s hammer test & UCT on prepared rock samples.
A new correlation with a great degree of accuracy &
reliability can be developed. Also the correlation developed
has an advantage of being a function of only one independent
variable i.e. rebound number.

4. Schmidt’s Hammer
The SH consists of a spring-loaded
piston which is released when the
plunger is pressed against a surface.
The impact of the piston onto the
plunger transfers the energy to
the material. The extent to which
this energy is recovered depends
on the hardness (or impact
penetration/damage resistance) of the
material, which is expressed as a
percentage of the maximum stretched
length of the key spring before the
release of the piston to its length after
the rebound.

5.  A Schmidt hammer, also known as a rebound hammer, is a device to measure
the strength of concrete or rock, mainly surface hardness and penetration
resistance.
 It was invented by Ernst Schmidt, a Swiss engineer
 The hammer measures the rebound of a spring-loaded plunger impacting
against the surface of the sample. The test hammer will hit the rock at a defined
energy. Its rebound is dependent on the hardness of the rock and is measured
by the test equipment. The rebound value can be used to determine
the compressive strength. When conducting the test the hammer should be
held at right angles to the surface which in turn should be flat and smooth. The
rebound reading will be affected by the orientation of the hammer, when used
in a vertical position (on the underside of a suspended slab for example)
gravity will increase the rebound distance of the mass and vice versa for a test
conducted on a floor slab. The Schmidt hammer is an arbitrary scale ranging
from 10 to 100
More About Schmidt Hammer

6. Construction of Hammer

7. Performance Check
Performance check shall be carried out
after every 1000 impacts or every 3
months (as suggested by manufacturer)
Steps followed to check calibration :
 Place the testing anvil on a hard
smooth surface
 Clean the contact surface of the anvil &
the impact plunger
 Perform about 10 impacts with the test
hammer & check the results aginst
calibration value specified on the testing
anvil.
Testing Anvil &
Schmidt’s Hammer
Conducting Test

8. Sample Holder
We have prepared a sample
holder such that the Schmidt
Hammer remain vertical to the
sample during the experiment.
A nut-bolt system is provided to
the sample holder to prevent any
kind of movement during the
hammering and to keep axis of
sample and hammer perpendicular
during all time.

9. L-Type N-Type
• Handling equals type N, but the type L offers
an impact energy three times smaller.
• The type L/LR Original Schmidt operates with
significant lower impact energy, making this
test
hammer the ideal option for testing thin walled
items with a thickness between 50 to 100 mm
• L-type hammer has greater
sensitivity in the lower range and gives better
results when testing weak, porous and
weathered rocks.
• The standard L-type hammers, produces
impact energy of 0.735 N m,
• Rebound values are read from a scale for
subsequent calculation of the mean.
• Compressive strength values can be read
from a conversion diagram.
• The N-type hammer is less sensitive to
surface irregularities, and should be
preferred in field applications.
• The standard N-type hammers, produces
impact energy of 2.207N m
Common Types of Schmidt’s Hammer

10. TEST PERFORMED UNDER THIS PROJECT
 SLAKE DURABILITY INDEX
 DENSITY
 POINT LOAD STRENGTH

11. Slake Durability Test
 The slake durability index is calculated
as the percentage ratio of the final to
initial dry sample masses as follows.
ID2 =
𝑪−𝑬
𝑨−𝑬
× 100
Where,
A = Initial weight of sample + drum (gm)
C = Weight of sample retained + drum after
second cycle of rotation (gm)
E = Weight of empty drum (gm)
ID = 2nd cycle Slake durability index (%)

12. ID2 (%) Durability classification
0 – 25 Very low
25 – 50 Low
50 – 75 Medium
75 – 90 High
90 – 95 Very high
95 – 100 Extremely high
SLAKE DURABILITY INDEX TABLE

13. Ancillary Equipment
used for various Measurements
DRYING OVEN
WEIGHING MACHINE

14. Drying Oven
Drying oven temperature was kept at
105 Degree Celsius and the sample
was dried for 10 hours

15. Weighing Machine
Digital Weighing machine was
used to accurately measure
the weight of the samples.
Its least count was 1 gm

16. DENSITY
 For measuring density of the rock sample, we take dry weight of the sample.
 For drying the sample we use the dry oven, in which we keep the sample for
atleast 10 hours at a temperature of 105 degree celsius.
 For measuring the weight we use an electronic weighing machine which gives the
measurement electronically, because of which the chances of error is very less.
 Now for measuring the volume we use water displacement technique by putting
the sample in water and measuring the volume of water displaced using a
measuring cylinder.
 Weight density is calculated using the formula= weight/volume.
 All the specimens prepared were of Standard NX size i.e having height to dia ratio
2:1. and the samples were made free from any irregularities. finishing has been
done through grinding machine.

17. Point Load Test For UCS
 The Point Load Strength was calculated as;
Id=F/D2
e
Where,
Id =Point load strength index
F = Failure load (N)
D2
e = Distance2 between cones (usually diameter of the sample)

18. Calculation Of UCS using
Point Load Index Value
Broch and Franklin [5] reported
that for 50 mm diameter cores
the uniaxial compressive
strength is approximately equal
to 24 times the point load index.
UCS = 24 Id(50)
Bieniawski [6] suggested the
following approximate relation
between UCS, Is and the core
diameter (D).
UCS = (14 + 0.175 D) Id(50)

19. CONCLUSION AND
RESULTS
Five samples each of Siltstone, Fine Sandstone & Shale were
taken corresponding Hammer rebound values, density and
Point Load Index was determined.
The results of tests for density, Schmidt rebound hammer,
Density, Slake durability index, point load strength and
unconfined compressive strength are given in Table.

20. HAMMER REBOUND VALUE-
S.NO. R1 R2 R3 R4 R5
1 13 18 12 13 19
2 13 25 19 23 22
3 22 23 20 22 22
4 19 24 19 23 19
5 13 24 23 22 23
6 12 29 22 19 19
7 20 17 12 13 20
8 18 16 14 16 13
9 20 26 17 20 16
10 15 19 24 18 19
AVERAGE 16.5 22.1 18.2 18.9 19.2
SILTSTONE

21. Fine Sandstone
S.NO. R1 R2 R3 R4 R5
1 29 32 20 23 20
2 25 30 33 25 31
3 27 33 25 30 29
4 26 34 29 31 33
5 24 32 35 29 27
6 24 31 22 23 31
7 25 28 25 29 27
8 26 28 28 23 35
9 26 31 31 30 22
10 28 19 27 29 26
AVERAGE 26 29.8 27.5 27.9 28.1

22. Shale
S.NO. R1 R2 R3 R4 R5
1 20 16 15 19 17
2 14 24 23 23 20
3 25 16 13 20 21
4 25 12 17 20 13
5 20 15 22 21 14
6 22 24 25 15 20
7 24 12 19 17 19
8 20 21 14 21 21
9 28 21 20 19 23
10 22 12 21 24 24
AVERAGE 22 17.3 18.9 19.9 19.2

23. Density
SiltStone
S.NO DRY WEIGHT(gm) VOLUME(ml) DENSITY(gm/cc)
1 45 26 1.73
2 61 30 2.03
3 51 28 1.82
4 51 29 1.75
5 46 25 1.84
AVERAGE 1.834

24. Fine SandStone
S.NO DRY WEIGHT(gm) VOLUME(ml) DENSITY(gm/cc)
1 45 26 1.73
2 61 30 2.03
3 51 28 1.82
4 51 29 1.75
5 46 25 1.84
AVERAGE 1.834

25. Shale
S.NO DRY WEIGHT(gm) VOLUME(ml) DENSITY(gm/cc)
1 41 27 1.51
2 49 29 1.68
3 54 33 1.63
4 52 31 1.67
5 48 31 1.54
AVERAGE 1.60

26. POINT LOAD INDEX-
SiltStone
S.NO DIAMETER(cm) FAILURE LOAD(KN) POINT LOAD INDEX(MPa)
1 4.73 1.3 0.58
2 4.73 2.8 1.25
3 4.72 2.4 1.07
4 4.74 1.9 0.84
5 4.71 2.1 0.94
AVERAGE 0.94

27. Fine SandStone
S.NO DIAMETER(cm) FAILURE LOAD(KN) POINT LOAD INDEX(MPa)
1 4.74 2.8 1.24
2 4.73 2.7 1.20
3 4.74 1.8 0.80
4 4.72 1.5 0.67
5 4.71 2.4 1.08
AVERAGE 0.99

28. Shale
S.NO DIAMETER(cm) FAILURE LOAD(KN) POINT LOAD INDEX(MPa)
1 4.72 2.5 1.12
2 4.74 1.9 0.84
3 4.73 2.9 1.29
4 4.71 1.5 0.67
5 4.72 1.4 0.62
AVERAGE 0.91

29. SLAKE DURABILITY
INDEX-
S.NO ROCK TYPE DRY WEIGHT
(gm)
DRY WEIGHT
AFTER 1ST CYCLE
DRY WEIGHT
AFTER 2ND CYCLE
SLAKE
DURABILITY
INDEX(%)
1 SILTSTONE 509 505 501 98.42
2 FINE SANDSTONE 510 503 495 97.05
3 SHALE 502 495 482 96.01

30. ESTABLISHMENT OF RELATION USING
IBM-SPSS SOFTWARE
 IBM SPSS Statistics is one of the best solutions to formulate hypotheses and thus clarify
the relation between variables. Use its analysis tools to identify trends and complete
predictions. Furthermore, IBM SPSS Statistics allows you to see in depth customized
tables and dynamics which will make it easier to understand data.
We have used this software to establish relation between various
properties and rebound hammer values using regression analysis. The
analysis is carried out using curve-linear model with hammer value as
independent variable & other properties as dependent variable. The best
fit curve gives the relation between those variables.

31. SiltStone
 The plot of the
Schmidt rebound
hammer number as
a function of Density
is shown in Fig.
 The best fit trend line
can be explained by
following equation:
R2 = 0.844
D=0.815+0.054R
FIG-SCHIMDTREBOUNDVALUEVSDENSITY
REBOUND VALUE VS DENSITY

32. REBOUND VALUE VS POINT LOAD INDEX
 Figure shows the
relationship between
Schimdt Hammer
rebound Value and
Point Load Index
 The figure shows a
fairly good relation
having a coefficient
of relation(R2=0.762)
Id= -1.158+0.111R
FIG-SCHIMDTREBOUNDVALUEVSPOINTLOAD
INDEX

33. Fine Standstone
 The plot of the Schmidt
rebound hammer
number as a function of
Density is shown in Fig.
 The best fit trend line
can be explained by
following equation:
R2 = 0.798
D=0.971+0.028R
FIG-SCHIMDTREBOUNDVALUEVSDENSITY,
REBOUND VALUE VS DENSITY

34. REBOUND VALUE VS POINT LOAD
INDEX
 Figure shows the
relationship between
Schimdt Hammer
rebound Value and Point
Load Index fine
sandstone.
 The figure shows a fairly
good relation having a
coefficient of
relation(R2=0.772)
Id= -3.522 + 0.162R
FIG-SCHIMDTREBOUNDVALUEVSPOINTLOADINDEX,

35. Shale
 The plot of the Schmidt
rebound hammer
number as a function of
Density is shown in Fig.
 The best fit trend line can
be explained by following
equation:
R2 = 0.744
D= 0.85 + 0.039R
FIG-SCHIMDTREBOUNDVALUEVSDENSITY
REBOUND VALUE VS DENSITY

36. REBOUND VALUE VS POINT LOAD INDEX
 Figure shows the
relationship between
Schimdt Hammer rebound
Value and Point Load
Index for shale.
 The figure shows a fairly
good relation having a
coefficient of
relation(R2=0.861).
Id= -2.149 + 0.157R
FIG-SCHIMDTREBOUNDVALUEVSPOINTLOAD
INDEX

37. CONCLUSIONS AND RECOMMENDATIONS
 DENSITY :
For Siltstone, D = 0.815 + 0.054*r (R2 = 0.844)
For Fine Sandstone, D = 0.971 + 0.028*r (R2 = 0.798)
For Shale, D = 0.850 + 0.039*r (R2 = 0.744)
 POINT LOAD INDEX :
For Siltstone, Id = -1.158 + 0.111*r (R2 = 0.762)
For Fine Sandstone, Id = -3.522 + 0.162*r (R2 = 0.772)
For Shale, Id = -2.149 + 0.157*r (R2 = 0.861)
Where,
D-Density
Id-point load index
R2 - coffiecient of regression
r-hammer rebound number

38. Shortcomings
 The use of developed correlation for UCS prediction in highly weathered
rocks is not recommended due to improper UCS prediction.
 SRH provides only a crude estimate for the UCS of rocks
 SRH is not sensitive to intrinsic properties of rocks such as texture,
saturation, porosity & micro-fractures controlling the mechanical behavior
of rocks
 There is no unique relationship between the SRH & UCS for all rock types.

39. Factors affecting the analysis are:
 i. Calibration
 ii. Surface irregularities
 iii. Surface moisture content
 iv. Spacing between impacts
 v. Orientation of the hammer