Sharif Digital Repository

The purpose of this paper is to quantify the extent of damage of rectangular reinforced concrete shear walls after an earthquake using surface crack patterns. One of the most important tasks after an earthquake is to assess the safety and classify the performance level of buildings. This assessment is usually performed by visual inspection that is prone to significant errors. In this research, an extensive database on the images of damaged rectangular reinforced concrete shear walls is collected from the literature. This database includes more than 200 images from experimental quasi-static cyclic tests. Using the concept of Fractal geometry, several probabilistic models are developed by... 

Structural health monitoring (SHM) has been motivated in aircraft and civil industries over the two last decades. Ultrasonic guided wave propagation technique is one of the best damage detection methods in airplane thin wall structures because of their large distance traveling and low attenuation.
In fact by efficient design of sensors pattern one can effectively pick up the changes that happen in propagated signals due to presence of any kind of structural damage. This could be effectively achieved by numerical simulation techniques like finite element modeling. To obtain a damage detection algorithm based on instantaneous baseline data, here, finite element technique is employed for... 

structures during their service life continually accumulate damage as a result of the action of various environmental forces. Clearly the development of robust techniques for early damage detection is crucial to avoid the possible occurrence of catastrophic structural failure. In a big picture we can divide process into two subcategories: first – we need modal properties of structure. In this case we install several motion sensors on structure and collect their data. Then use a group of methods named as System Identification Process to discover dynamic properties of structure as natural frequencies and mode shapes. Three famous system identification method have been used in this thesis and... 

In this dissertation a new approach is introduced for damage detection in offshore jacket platforms. The procedure uses the measured ambient vibration responses and the corresponding readable natural frequencies and mode shapes of the structural systems. Since offshore platforms are composed of heavy topsides supported by jacket structures, participation of the first mode is dominant in each direction in the response of the structure under field excitations. Moreover, ambient vibrations such as wave loads and boat impacts only excite the first modes of the structure. Therefore, it is difficult to find higher modes and the pertinent frequencies by use of accelerometers data. The introduced... 

Nowadays a major part of energy, fresh water and sewer water in over the world are transmitted by buried pipe, and always these lines are under the loads and different stresses such as corrosion, earth quick and etc.
In many countries the age of these lines are more than 30 years which causes corrosion of the pipe wall and the necessity of health investigating of transmission lines has a special importance for the governments and leak detection can also keep the natural environment healthyand the costs will come down significantly, scientists and researchers have always tried different ways to check the health of the pipes.
In the field of leak detection and the problems of age... 

In this thesis selection criteria are present for types, numbers and locations of sensors for structural health monitoring of offshore jacket platform in the Persian Gulf. The selection criteria are chosen by studying structural health monitoring of various structures in civil and aerospace industries. Knowing the types of sensors that can be used, a new approach of inverse vibration problem is introduced for structural health monitoring of offshore jacket platforms. In the previous studies, significant numbers of frequencies and mode shapes are usually used to detect damages by updating components of stiffness matrix. Considering the fact that offshore platforms are composed of a heavy... 

Pipeline systems have a major role in civil infrastructure for transportation of energy sources including, petroleum, natural gas, and water. As most pipelines are located in hard-access location such as underground and sea as well as mountains, they are vulnerable to corrosion, cracks and thus, unpredictable failure. Failure of pipelines not only costs millions of dollars but also causes environmental damage, requiring continuous health monitoring systems to provide early detection and early warning of flaws such as corrosion and leaks. Structural health monitoring based on ultrasonic guided waves is used in structures as plates, composites, rods, piping and tubing. This research aims to... 

Structural Health Monitoring (SHM) of pipelines is an important task for economic/safety reasons which depends on the method of study of the integrity profile of the pipeline structure. Process pipes, particularly, pipelines in thermal power plants are susceptible to stress corrosion cracking (SCC). Failure of these pipes may result in catastrophic damages, thus, require systematic regular inspections. The damage assessment may demand embedding of appropriate sensors and specific data analysis techniques. According to what is reported from the respective experiments, data analysis of a single sensor may not be adequate to provide a reasonable damage assessment, and in turn to making a... 

Reliability evaluation is a key factor in serviceability and safety analysis of air vehicles. Structural health monitoring methods have grown to a degree of maturity in many industries. However, there is a challenging interest to tie in SHM with reliability assessment. In this respect, consideration of stochastic structural dynamics with SHM data and random loadings opens a new chapter in failure prevention. The current study focuses on the stochastic behavior of structures as a way to relate SHM data with reliability. In this respect, uncertain factors such as atmospheric turbulence, structural parameters, and sensor outputs are considered in the process of reliability assessment. Firstly,... 

Structural system identification from vibration data is one of the most interesting research topics in the structural health monitoring area. Recently, realization and detection of the effects of damage when a structure is subjected to strong ground motion has become a great concern in earthquake and structural engineering communities. Seismic signal processing is one of the most reliable methods of detecting the structural damage during earthquakes. The structural responses during earthquakes are nonstationary with respect to both amplitude and frequency. The state-of-the-art time-frequency distributions when applied to vibration records were studied. Different methods of analysis for... 

Extracting modal parameters is necessary for future vibration-based health monitoring studies of the structures. Due to the reason that it is difficult to measure the input excitation forces acting on a real large structure in its operational condition, it is preferable to use the output-only methods which estimate the modal model by using responses data only. Also, the output-only dynamic testing has advantages of being inexpensive since no equipment is needed to excite the structure and the service condition does not have to be interrupted.This paper presents the results of modal identification of an offshore jacket platform using output-only methods with the assumption of ambient... 

This study aimed to develop a method for locating damages in the early stages of damage expansion in plate components of the structure using a one-dimensional discrete wavelet function. Continuous monitoring of the health of structures to preserve and repair them to protect the lives and property of individuals and national capitals and to lower the direct and indirect economic costs imposed on society is vital and inevitable for society's decision-makers. Because the damage to the structure caused by earthquakes occurring during the lifetime of the structure, exhaustion of structural components, improper implementation of the structure at the time of construction, and other events that... 

The behavior of construction materials at high temperatures has been an important aspect of researches in recent years. The first part of the current research aims to non-destructively monitor the formation and growth of damage at geopolymer concrete (GPC) after being exposed to high temperatures using linear and nonlinear ultrasonic techniques. Ultrasonic waveform and pulse velocity (UPV) tests were conducted on the specimens before and after exposure to the temperatures. Nonlinear wave signals were processed in phase-space domain for qualitative health monitoring of GPC. Furthermore, feature extraction was applied to phase-plane attractors using fractal dimension for quantitative... 

This research proposes a damage assessment framework based on the visual features of a damaged reinforced concrete shear wall, such as crack pattern distribution, crushing areal density, aspect ratio, and the presence of the boundary condition. The study contains two parts: identifying the performance level of the damaged walls (i.e., Immediate Occupancy, Life Safety, and Collapse Prevention) and estimating the residual strength and drift ratio of the walls. The research database contains 236 images of 72 reinforced concrete shear walls tested in the laboratory under the quasi-static cyclic loadings at various drift ratios between 0.0 to 4.0. To identify the performance level of a damaged... 

Structural Health Monitoring (SHM) is an effective method for the early detection of structural damage, and this method can reduce the maintenance costs of structures. In this thesis, the use of artificial one-way and multi-layer artificial neural network is evaluated to determine the damage to the structure. The neural network method used in this thesis is a post-propagation method. Finally, the numerically damage determine will be evaluated using a two-dimensional frame structure and a three-dimensional frame structure by finite element method. In this method, the dynamic properties of the structure are used only in the form of the modules. For this purpose, the finite element model is... 

Interpreting data of infrastructures monitored to detect damage of a structural is one of the most challenging issues of structural health monitoring (SHM). Especially, when environmental factors such as temperature, wind and humidity affect the data and the situation become more complicated. In this study, two methods of analysis free model of moving principal components analysis (MPCA) and robust regression analysis (RRA) have recently been considered for monitoring infrastructures compared with a variety of methods of data interpretation and results are presented. In this study, the performance of different ways in different loading conditions and arrangement of sensors have been... 

The goal of this research is to study the effect of local microcracking due to step by step pressure loading on the durability properties of geopolymer concrete. To better understand the behavior of GGBS-based GPC under different pressure stress levels, some experiments such as water permeability and water absorption conducted on the samples at each state of damage. Also, non-destructive tests such as ultrasonic waveform and pulse velocity (UPV) was used to quantify the extent of damage at each step. GGBFS and a blend of sodium silicate solution and 10 molar sodium hydroxide solution with SSSH⁄ ratio of 2 were used for production of GPC samples. GPC, OGPC and OPC samples with water to binder... 

Crack detection is a critical task in monitoring and inspection of civil engineering structures. This study proposes a deep-learning-based model for automatic crack detection on the concrete surface. The proposed model is an encoder-decoder model which uses EfficientNetB7, the state-of-the-art convolutional neural network, as encoder and the U Net’s expansion path as decoder. To minimize the training time and maximizing the accuracy, we use transfer learning in our approach. We train our model with a novel training strategy on images from an open-source dataset and achieve 96.44% F1-score for unseen test data. To compare the performance of the proposed method, we evaluate our model on CFD...