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Experimental Investigation and Numerical Modeling of Corrosion Induced Expansive Pressure on Concrete Cover in Reinforced Concrete
No full textThis thesis is submitted to the Department of Civil Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Civil Engineering, November 2018.Cataloged from PDF Version of Thesis.Includes bibliographical references (pages 90-93).Corrosion of reinforcement is an important durability concern for the structures exposed to adverse weather conditions especially in coastal regions. The volume of corrosion products are much higher than the original volume of the corroding reinforcement, which exerts an expansive pressure on the surrounding concrete and results in cracking of the concrete cover. In this research an investigation was carried out through numerical modeling and experimentation to explore the mechanism of concrete cover cracking due to that expansive pressure. It was aimed that structural health monitoring in terms of level of corrosion might be possible through monitoring the crack width and crack propagation in the cover concrete. In addition a convenient means of corrosion protection was investigated by using zinc as sacrificial anode. A numerical model was developed using a commercial finite element modeling software ABAQUS 6.14 to evaluate the cracking pressure, crack initiation, crack propagation and radial deformation for different cover thicknesses and bar locations. The model was also used to determine the effect of bar diameter on cracking pressure and the patterns of crack for different number of bars. Numerical results were validated by experimental investigation.
The cracking pressure was simulated experimentally by applying hydraulic pressure through a hole in the specimens having similar diameter as of the reinforcement. 150 mm cube specimens for three different grades of concrete with various clear cover and location of bar were used for the simulation. Impressed current technique was used to accelerate the corrosion of reinforcement. Characterization of impressed current technique involved determination of optimum chloride content and minimum immersion time of specimens for which the application of Faraday’s law could be efficient. To obtain optimum chloride content, the electrolytes in the corrosion cell were prepared similar to that of concrete pore solutions. Concrete cubes of 50 mm were used to determine the optimum immersion time for saturation. It was found that the optimum chloride content was 3.5% by mass of water and the minimum immersion time for saturation was 24 hours. Concrete prisms of 250 mm x 250 mm x 300 mm with 12 mm-Ø grade 60 plain mild steel bars were used to simulate RCC beams with various cover thicknesses of 20 mm, 37.5 mm, 50 mm and 75 mm, respectively, to observe the mechanism of crack initiation, propagation and level of corrosion with respect to the width of surface crack. Level of corrosion was measured in mg/cm2 following Faraday’s law and by gravimetric loss method, and width of crack was measured by image analysis.
From numerical modeling it was found that, with the increase of cover thickness the pressure as well as the radial expansion needed to initiate crack was increased. The same pattern was found for both corner bar and side bar. A lower cracking pressure was required for corner bar with respect to side bar. On the other hand, with the increase in bar diameter, a decrease in cracking pressure was observed. It was also found that the crack was initiated from outer surface and propagated towards the steel concrete interface for a cover thickness of 20 mm as well as 37.5 mm. This result was accomplished due to heaving of cover concrete and crack initiated when bending stress exceeded the tensile strength of concrete. Whereas for a cover thickness of 50 mm as well as 75 mm, crack was initiated at the steel-concrete interface and propagated towards the cover surface. These observations were further confirmed through experimental investigation. From the experimental simulation of cracking pressure, it was found that the cracking pressure varied linearly with the increase in concrete cover-to-diameter ratio (c/d). The pressure requirement to initiate crack was also higher with higher grades of concrete. For corner bars with cover thickness 37.5 mm, the critical pressure was 6-10 MPa and it increased up to 17 MPa for cover thickness of 64 mm for different grades of concrete. On the other hand, for other bar location with cover thickness of 37.5 mm and 64 mm, the pressure required to initiate crack was about 7.6 MPa and 14.8 MPa, respectively, for C20 grade concrete. A linear relationship was found between crack width and level of corrosion. For cover thicknesses of 20 mm and 37.5 mm, the critical corrosion amount (CCA) needed to initiate crack was about 22 mg/cm2. However, a sudden increase in CCA was noticed when the cover thickness was over 44 mm. For cover thicknesses of 50 mm and 75 mm the CCA values were 129 and 211 mg/cm2, respectively. Cathodic protection of reinforcement corrosion was investigated by using zinc as sacrificial anode in the accelerated corrosion cell with two environments- (i) synthesized solutions similar to concrete pore solution and, (ii) concrete. It was found that up to 65% of the corrosion current could be diverted through the sacrificial anode.
It is concluded that level of corrosion could be predicted by monitoring the surface crack width with reasonable accuracy, a minimum of 50 mm concrete cover should be provided in the corrosion prone environment and zinc as sacrificial anode could reduce as much as two-thirds of corrosion hazard to prolong the service life of reinforced concrete structures.Sheikh ShakibMaster of Science in Civil Engineerin
Brain Tumor Classification and Watermarking of MRI Using Nonsubsampled Contourlet Transform
No full textThis thesis is submitted to the Department of Electronics and Communication Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of M.Sc. Engineering in Electronics and Communication Engineering, November 2018.Cataloged from PDF Version of Thesis.Includes bibliographical references in each chapter.Automatic or semi-automatic brain tumor classification scheme is demanded in today’s
medical system to get rid of human involvement of classification of brain tumor images. So,
here we propose nonsubsampled contourlet transform (NSCT) based MRI brain tumor
classification using support vector machine (SVM) and artificial neural network (ANN)
classifier. In this scheme, K-means clustering is used for segmentation of region of interest.
NSCT is applied to the region of interest of brain image in order to obtain its low and high
subband coefficients. Then from the coefficients of NSCT, twelve features are extracted from
the region of interest. SVM which incorporates two stages is trained with these twelve features.
1st stage of SVM is able to classify brain image as normal or abnormal and then 2nd stage of
SVM classifies grade of tumor as low grade, where tumor is slowly growing or high grade,
where tumor is rapidly growing. The grade of tumor is also classified using the ANN classifier
based on feed forward back propagation. Furthermore, when the multimedia contents like
MRIs or other images are transferred through a communication channel, sometimes the whole
content or its part may be modified or deteriorated by hackers. In order to protect this content
from unauthorized user, digital watermarking is considered to be a promising tool. So another
purpose of this research is to develop image watermarking scheme which ensures higher
security, imperceptibility and robustness against different distortion attacks. In first proposed
scheme of image watermarking, NSCT is also used because most of the perceptual content of
an image focuses on low frequency subband of NSCT. Singular value decomposition (SVD) is
also applied on low frequency subband of NSCT, because the singular values taken from low
frequency subband have certain stability. Besides, game of life (GOL) cellular automata is
used to scramble binary watermark so that no one can recover the watermark without secret
scrambling keys. So in this scheme, NSCT and SVD ensure the imperceptibility and
robustness as well as cellular automata improves the security. In second proposed scheme of
watermarking, multiple chaotic maps, NSCT and discrete cosine transform (DCT) are used.
Here, an arranged chaotic sequence which is created by logistic map is used to shuffle the
pixel positions of MRI. Patient information, watermark is encrypted by two chaotic maps, like
Arnold’s Cat map and tent map. Then, DCT coefficients of encrypted watermark are
embedded into the DCT coefficients of NSCT’s approximation band of shuffled MRI. Both
proposed watermarking schemes are tested on varieties of MRIs and their associated results
reveal that the two schemes have promising improvements in imperceptibility and robustness
against noise and geometric attacks. Overall, NSCT is used in both brain tumor classification
and watermarking in this research.Chandan SahaMaster of Science in Electronics and Communication Engineerin
Design a Multistage Multirate System for Atrial Fibrillation Detection using ECG Signal
No full textThis thesis is submitted to the Department of Electronics and Communication Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of
Master of Engineering (M.Sc. Eng.) in Electronics and Communication Engineering, November 2018.Cataloged from PDF Version of Thesis.Includes bibliographical references in each chapter.Atrial Fibrillation (AF) is one of the most common cardiac arrhythmias. The number of patients related to heart failure due to AF is increasing day by day. Early detection of AF may reduce the risk of death due to heart failure. So, it has become more important to detect AF. There are various method to detect AF. In this thesis, we use ECG signal for AF detection. The MIT-BIH Atrial Fibrillation database is used to import ECG data for analysis. Filtered ECG signal using multistage multirate system for removing noise. RR interval of the ECG signal is calculated. Here we use the algorithm that mainly follows statistical method for detection of AF. Parametric statistic RMSSD and SE, and non-parametric statistic, TPR are used for this purpose. MATLAB R2016a is used to measure the values of those parameters for estimation of AF. The threshold values of RMSSD/ (Mean RR) taken from the literature is 0.1, SE is 0.7 and TPR is greater than 0.54 and lesser than 0.77. The resultant values of RMSSD, SE and TPR of every beat are checked weather it crosses the threshold level or not. If all the three parameters cross the threshold level then the beat flagged as AF. It shows excellent result when compared with the annotations of the database, and then the sensitivity, specificity and accuracy are determined. The algorithm has the sensitivity of 98.03%, specificity of 98.80% and accuracy of 99.45%. Thus, the result obtained in this study is appreciable compared to the other study found in literature.Fatema Tuj JohuraMaster of Engineering (M.Sc. Eng.) in Electronics and Communication Engineerin
A Study on Big Data Management Strategy Using Fog Computing
No full textThis thesis is submitted to the Department of Computer Science and Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Engineering in Computer Science and Engineering, November 2018.Cataloged from PDF Version of Thesis.Includes bibliographical references (pages 31-34).In modern ages, data is increasing day by day using internet of things for various purposes.
Data intensive analysis is the major challenge because of the ubiquitous deployment of
various kinds of sensors. Traditional cloud computing infrastructure is not enough for
processing these large amount, variety or velocity of data that means big data. Traditional
cloud computing structure is geographically centralized. Balancing load for big data is a
crucial issue. A preprocessing stage is necessary to handle these big data for real time
service oriented application. In this thesis, a big data management strategy is proposed
using a preprocessing stage that is fog computing. Providing real time services from cloud
is too many time consuming for big data. Here, Fog Computing plays a vital role. The
maximum functions of processing data are implemented outside of cloud in the case of Fog
Computing and one thing considered in Fog Computing is that here memory of fog devices
is very little. So, a well-organized communication system is needed for data processing.
Here, in this work an affordable, robust and secure power supply or third party memory
management has been suggested which is Smart Grid and Smart Local Grid. The smart
grid and smart local grid or third party memory management support the customer's real
time services using fog infrastructure. In this work a hierarchical architecture has been
proposed for creating well-organized communication system for data processing in the case
of smart grid and smart local grid or third party memory management using fog
infrastructure or nodes. For task scheduling of nodes in case of fog infrastructure queue
based scheduling technique is used. In this work, an effective result for big data
management and providing real time services has been found. Here, different parameters
such as network latency, throughput have been used for measuring performance in real
time services. The overall network latency is minimized and throughput is increased in
case of fog computing.Tajul IslamMaster of Science in Engineering in Computer Science and Engineerin