Predicting a Steel-Reinforced Concrete Beam Failure … concrete is a widely used ... The concrete used to build the beam was Home Depot’s ... breaking of the concrete and hydraulic

WJP, PHY381 (F2011) Wabash Journal of Physics v1.3, p.1

Predicting a Steel-Reinforced Concrete Beam Failure Using

Acoustic Emissions Monitoring

William J. Costakis, Evan S Groninger, and M. J. Madsen

Department of Physics, Wabash College, Crawfordsville, IN 47933

(Dated: October 21, 2011)

The maximum load strength of a concrete beam is determined by its geometrical

make up and ability to withstand compressive and tensile forces. Concrete alone

cannot withstand a large load because of its brittle nature and poor tensile strength.

Therefore, it is interesting to test the load strength of concrete beams reinforced

by embedded steel rebar. In order to test the load strength, acoustical analysis

will be employed for identification of molecular bond separation. The goal of this

experiment is to be able to accurately predict the behavior before a load forces a

beam to fracture.


Steel-reinforced concrete is a widely used material throughout the realm construction

and civil engineering. Prior research has determined the nature of steel-reinforced concrete

to be brittle yet able to withstand large compression forces [6] [9]. Acoustical emissions

monitoring (AEM) is a standard way to analyze the structural properties for concrete under

a load because AEM provides a real time non-destructive record of what is happening inside

the material. Waveforms produced by cracking of the material propagate throughout the

material and are received by the piezoelectric detectors. The sensors then transfered the

wave information to a computer where information about crack location, crack density,

and material severity is recorded [1]. According to Dimitrios Aggelis’s research, cracking

modes carry different signatures [1]. For example, a tensile crack results in a high frequency,

short rise time wave while shear are characterized by low frequency, long wavelength, and

longer rise time [1]. Also, the AEM can differentiate between the three stages of cracking:

micro-cracking, macro-cracking, and macro-crack expansion [3]. Using AEM to understand

properties of steel-reinforced concrete is significant because if we can understand when a

material is going to fail, our understanding will provide a safer environment. One such

instance that cried out for a better understanding was the infamous 2007 Minnesota I-35

bridge collapse. I-35 was one of Minnesota’s busiest highways and when a structural failure

occurred, 13 people lost their lives and 145 were injured [7]. If the structural condition

could have been properly assessed, millions of dollars and several lives could possibly have

been saved. In order to understand what happened and also to possibly predict a failure

within concrete, we used AEM to test load strength of steel-reinforced concrete beams. We

attempted to analyze the data collected from two failures within a steel-reinforced concrete

beam and develop a method for predicting a failure.

We fabricated a steel-reinforced concrete beam to achieve our goal. The maximum load

of a steel-reinforced concrete beam is a based on the longitudinal length of the concrete

beam, the beam’s depth, as well as the beam’s width. Using the modulus of rupture Eq. (1)

we estimated that a steel-reinforced concrete beam with dimensions b=19 cm, d=19 cm and

L=53 cm would have a maximum load of roughly 2700 kg or about 3 tons[2]. Our actual

beam measured b = (14.5 ± .3)cm, d = (15 ± .3)cm, and L = (51.5 ± .3)cm.

R =3Pl

2bd2(1)

The concrete used to build the beam was Home Depot’s Ready-To-Use Quikrete 80 lb


Concrete Mix Part No. (1101) We mixed the concrete with a water to mixt ratio of .077

liters of water per kilogram of mix. Then we poured the concrete mixture into molds of the

above dimensions and let it set for five days to allow the concrete to cure to a firm state.

We used a Images SI Inc. Piezoelectric film sensor part number PZ-03 to pick up waves

propagating through the concrete beam.

P(load)

L

Aluminum Supports

b

d

Sensor

hl

D

FIG. 1. The beam has dimensions of b = (14.5 ± .3)cm, d = (15 ± .3)cm, h = (3.81 ± .3)cm,l =

(35.5 ± .3) cm D = (.95 ± .3)cm, and L = (51.5 ± .3)cm.

The piezo sensors measured small displacements and produced a voltage drop of a few

millivolts. We amplified this signal with a Vernier software instrumentation amplifier part

No. (INA-DIN) set to ±20 mV. We set the data acquisition system to measure the voltage

signal from four Piezo sensors at 250 samples per second for a period of 600 seconds. We

set up a camera to take a video of the entire experiment. So significant occurrences such as

breaking of the concrete and hydraulic pumps that appeared in the data could be matched

and visualized in the video. We used a Kodak Zi8 digital camera that was set to take data at

720p with 30 frames per second. In order to match up incidents, we synchronized the camera

with the Piezo voltage data by taping the top of a sensor three times. We found that the

internal clocks from the computer data acquisition system and the camera were consistent

over a 600 second period.We used a OTC 10-Ton Capacity Bench Press part No. (1884)

with a working area of roughly 56 × 39 and a two-speed OTC hydraulic hand pump part

No. (4004) to apply a load to the beam. We placed aluminum spacers under the concrete

beam with a distance of roughly 35 cm to provide space for the beam to bend. We clamped


the spacers to the press to stop them from moving or tilting under stress. We recorded

the hydraulic ram pressure, measured in pounds per square inch (PSI), which we believe

is a scale factor of the total load applied to the beam and pump number after each pump

was completed. We increased the hydraulic pressure approximately 100 psi by engaging the

pump for a full stroke. As the total PSI became larger the PSI increment increase per stroke

also became larger. We obtained a value of approximately 300 PSI per stroke just before

the fracture of the beam.

w

Sensor

Clamp

Hydraulic Press

Concrete Beam

Line to Hydraulic pump

H

l

FIG. 2. The experimental set-up used with measurements of the bench length w = (55.8 ± .3)cm,

height H = (39.1 ± .03)cm, and the distance between aluminum spacers l = (35.5 ± .3)cm

In order to test the failure load of a steel reinforced concrete beam, we had to first build

the wooden forms for the concrete beams. We fabricated our molds to form 21in.X6in.X6in.

beams and filled the molds with concrete mix. Once the beams were formed, they were

tested on a 10-Ton single-acting hydraulic ram (See FIG. (3)). Piezoelectric sensors were

applied to each side of the concrete beam and connected to Logger Pro. The computer was

then used for data analysis.

The 21.3±.1kg concrete beam we used for data collection was stressed to roughly 2700 PSI

over 6 minutes and 27 seconds. A fracture occurred at data collection time 387.86 ± .07sec.

The macro-crack expanded from the load point through the body of the beam to a point

flush with the edge of an aluminum support beam. The data collected from the run allotted

for an analysis between “pumps” or human induced activity, and cracking, which actually

occurred in the material from the stress caused by the hydraulic press. FIG. (4) displays the


a)

b)

FIG. 3. Above are the comparisons of the beam a) before and b) after a load of about 2700 PSI.

data collected throughout the entire load increasing process. FIG. (5) is a comparison chart

of data extracted from three different points in the collection period, each displaying the

“dead zone” before a pump as well as the pump. We located each feature within the data

by matching video footage with known data characteristics. For example, we tapped on a

sensor using a metal rod and coordinated the software to the remaining video footage using

the wave caused by the tap. With video time linked to data recording time, we matched all

pumps on the video footage to pumps in the data.

The period before a pump is significant because the signal picked up is strictly the behav-

ior of the concrete. We cross examined three dead zones from significantly different periods

in the experimentation because each period represented a different applied load. Each data

segment had a qualitative average amplitude of about 1 mV, however with the earliest seg-

ment being consistently slightly less that 1 mV, the middle segment average right at 1 mV,

and the final segment average above 1 mV. We also noticed that as time progressed, the

dead zones became more noisy. In other words, there was a noticeable difference between

the amount of wave propagation picked up in each section with the latter section containing


the most propagation and the earlier section containing the least. We also discovered with

respect to the cracks, the peak amplitudes were irrelevant.

The signal recorded by the data acquisition software increased throughout the data col-

lection as a function of load is significant because this shows that, closer to failure, more

micro cracks occur. Therefore instead of the average amplitude of the Piezoelectric signal

carrying the most significance, the frequency of propagation in a given time zone is more

significant. With a small applied load, the experimental frequency was nearly zero; with a

moderate load, the frequency was roughly one peak per second, and just prior to the fracture

the frequency is roughly 3 peaks per second. The 3 peaks per second frequency may be the

signal frequency for a failure.

FIG. 4. Above is a graph of the propagation of stress waves in the concrete beam from 0 seconds

to the fracture point. Each pump number is labeled and located by its identified propagation and

time. The bottom and top sensor are featured and differentiated by color.

In conclusion, the data we collected from the AEM is just the start of an understanding

on how to predict occurrences in concrete beams. We did not predict when beam failure

was going to happen as expected. In the future, improvements will need to be made on


Bottom Sensor

-3

-2

-1

0

1

2

3

19 20 21 22 23 24

-3

-2

-1

0

1

2

3

179 180 181 182 183 184

-3

-2

-1

0

1

2

3

339 340 341 342 343 344

Time (s)

Pote

ntia

l (m

V)a)

b)

c)

Rear Sensor

FIG. 5. The comparison graph from above features three, five second periods throughout the data

collection time. Each graph not only represents a different time, but also a different load. The

featured sensors are the rear and bottom sensors respective to the camera angle. a) is a period

of data in which a low, near zero load was applied. The propagation in the final 2.5 seconds of

the graph is most likely due to the sensors picking up walking in the data collection area. b)

is a segment displaying a moderate load. Relative to graph a), this graph has a higher wave

propagation frequency showing greater stress. c) is a segment of the data collection period just

before the fracture moment. Notice the much greater propagation frequency as compared to the

first two graphs. This is because the beam is under a near maximum load, and micro fractures are

frequent.


this experiment. One improvement that can be made is in the mixing and pouring of the

concrete. In this experiment we observed that the mixture of the concrete when cured

had numerous air pockets in it. One way to improve this is to use a finer concrete mix, a

more sand-based concrete mix. Also, we found air pockets in the concrete developed in the

pouring process. We suggest that poking through the poured mixture in the molds would

help release the air. Another improvement that would advance this experiment would be to

finding a better placement of the Piezoelectric sensors and a better adhesive. This would

allow for a better data collection since in the middle of collecting data one of the sensors

failed.

[1] Aggelis, G. Dimitrios., “Classification of Cracking Mode in Concrete by Acoustic Emission

Parameters”. Mechanics Research Communications, 38,153-157 (2011).

[2] Iowa. Method of Test Flexural Strength Using Simple Beam with Center-Point Loading. Office

of Materials, 2000. Web.

[3] D. Soulioti, et. al., “Acoustic Emission Behavior of Steel Fiber Reinforced Concrete under

Bending.” Construction and Building Materials, 23, 3532-3536 (2009).

[4] ”Piezo Electric Film Products.” N.p., n.d. Web. 16 Mar 2011.

[5] K. Wu, B. Chen, W. Yao., “Study on the AE Characteristics of Fracture Process of Mortar,

Concrete and Steel-Fiber-Reinforced Concrete Beams”. Cement and Concrete Research,30,

1495-1500 (2000).

[6] R. Sagar, B. Prasad., “An Experimental Study on Acoustic Emission Energy as a Quantitative

Measure of Size Independent Specific Fracture Energy of Concrete Beams”. Construction and

Building Materials, 25, 2349-2357 (2011).

[7] ”NTSB: Design Flaw Led to Minnesota Bridege Collapse.” CNN News 14 Nov 2008. n. pag.

Web. 11 Oct. 2011. ¡http://articles.cnn.com/2008-11-14/us/bridge.collapse

[8] Gere, James ames M. Mechanics Of Materials. CL-Engineering, 2001. Print.

¡http://books.google.com/books/feeds/volumes?q=9780534371333¿.

[9] Wright, James, and James MacGregor. Reinforced Concrete. 5th ed. Upper Saddle River: Pear-

son Prentice Hall, 2009. 56-57. Print.

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Predicting a Steel-Reinforced Concrete Beam Failure … concrete is a widely used ... The concrete used to build the beam was Home Depot’s ... breaking of the concrete and hydraulic