Pipelines are major part of any oil and petrochemical industry. It is common to burry transportation pipelines under soil for mechanical protection. However, corrosion in soil can reach high rates and becomes a major loss especially in costal environments and wet soils. In this paper, a numerical simulation analysis of pipeline corrosion is developed by using a new technique for corrosion evaluation. This technique is electrical capacitance tomography (ECT). The electrical capacitance system consists of number of electrodes mounted on the outer surface of pipeline, radius-electrode ratio is defined as the ratio of inner and outer radius of pipeline. The electrodes will act as a capacitance detector and the resulting capacitance can be measured between the electrodes. This capacitance will therefore vary when the pipeline thickness changes with time (that is, when the corrosion occurs). The finite element simulation technology can be used to calculate capacitance value to obtain the capacitance-sensitive field distribution electrode sensors. The effect of pipe wall corrosion on sensor capacitance measurements is presented in this work. It is based on the finite element model. The simulation results are obtained using ANSYS and MATLAB software.
In this paper, the structural mode shapes extracted from the finite element model of a simply supported reinforced concrete beam are employed for damage identification using different types of wavelets. To start with, the parity of signals, wavelets, and their convolution, that is, wavelet transform properties, are verified. In light of the mathematical modeling complexity of modal frequency, which relates to the localization and quantification of damage in the reinforced concrete beam, the maximum curves based on multiresolution wavelet transform coefficient differences and the corresponding theoretical assumptions are described and analyzed. It is concluded that the maximum curve reaches a peak value at a specific scale for a specific case, based upon which, a new mode shape based algorithm and damage index are proposed for damage identification. The accuracy of localization as well as the sensitivity of quantification is further discussed.
Over the past two decades extensive research has been carried out in the field of structural health monitoring for damage detection in structural systems. Most
Delamination is the most common failure mode in layered composite materials. The author have found that the electrical potential change (EPC) technique using response surfaces method is very effective in assessment delamination in basalt fiber reinforced polymer (FRP) laminate composite pipe by using electrical capacitance sensor (ECS). In the present study, the effect of the electrodes number on the method is investigated using FEM analyses for delamination location/size detection by ANSYS and MATLAB, which are combined to simulate sensor characteristic. Three cases of electrodes number are analyzed here are eight, twelve and sixteen electrodes, afterwards, the delamination is introduced into between the three layers [<TEX>$0^{\circ}/90^{\circ}/0^{\circ}$</TEX>]s laminates pipe, split into eight, twelve and sixteen scenarios for cases of eight, twelve and sixteen electrodes respectively. Response surfaces are adopted as a tool for solving inverse problems to estimate delamination location/size from the measured EPC of all segments between electrodes. As a result, it was revealed that the estimation performances of delamination location/size depends on the electrodes number. For ECS, the high number of electrodes is required to obtain high estimation performances of delamination location/size. The illustrated results are in excellent agreement with solutions available in the literature, thus validating the accuracy and reliability of the proposed technique.
A novel structural damage identification method based on the noncontact measurement technique and Jaya algorithm is presented. The “Features from Accelerated Segment Test” (FAST) algorithm and Kanade–Lucas–Tomasi algorithm are used to identify the displacements from the video clips synergistically. Since the fixed threshold value for the FAST algorithm may not meet the pixel requirements for different images, an adaptive threshold value strategy is applied in this study. The natural frequencies extracted from the acquired displacements are used to formulate a multisample objective function, which is defined on the basis of the Bayesian inference. The K-means clustering strategy, the Hooke–Jeeves pattern search mode, and the colony reduction mechanism are integrated into the Jaya algorithm to improve the convergence of the Jaya technique. Structural damage location and severity can be identified through minimizing the multisample objective function using this enhanced Jaya algorithm. The proposed method is then applied to a laboratory space frame. The damaged elements of the five verification cases (cases 1–5) are detected correctly. Finally, the damaged elements in cases 6–10 are identified and reported.
In this work, a damage identification framework is presented for Basalt Fiber Reinforced Polymer (BFRP) composite plate systems using the wavelet packet energy curvature difference (WPECD) method. A finite element model (FEM) of the plate is established and an accumulative damage model is introduced to model the plate damage subjected to fatigue, and five damage cases are considered. In the WPECD method for damage identification, dynamic features such as shape models, natural frequencies, and frequency responses is used. To simulate the composite plate damage, four stiffness reduction levels (5%, 10%, 15%, 20%) are employed. The damage can be identified by the WPECD index curve plot, and the influence of the wavelet function and the number of decomposition layers on the damage nodes identification was investigated. The results show that the proposed WPECD index can be identified the low damage levels (i.e. a 5% stiffness reduction). The proposed WPECD index can be employed to effectively identify structural damage.
This research studies a novel damage detection framework for beam structure systems using displacement sensors.First, a finite element model is established under the impact load.Based on this model, an accumulative damage model is introduced to model the beam damage, and the damage case is considered.Both static and transient displacement are collected from the beam sensors installing a long beam structure.A system transfer function (TF) is proposed and applied to the "open loop" beam system.Results show these approaches perform great promises when damage evolves in beam structure.
A pressure vessel is a pressurized container, often cylindrical or spherical. The pressure acting on the inner surface is resisted by tensile stresses in the walls of the vessel. Pressure vessels are commonly used in industrial applications such as gas, oil, water, and chemical industries. Pressure vessels can be dangerous, and fatal accidents have occurred in the history of their development and operation. Consequently, pressure vessel design, manufacture, and operation are regulated by engineering authorities backed by legislation. For these reasons, the definition of a pressure vessel varies from country to country. This chapter examines the types of pressure vessels in mechanical applications, and covers the full design of different pressure vessel types, along with examples and solved/unsolved problems. The chapter explains the stress–strain analysis of pressure vessel types such as thin cylindrical shell, thick cylindrical shell, thin spherical shell, and multi-layer composite pipe. This chapter can be used as teaching material for courses in machine design for mechanical and industrial engineering majors in colleges and universities, and can also be used as a reference for scientific and technical personnel engaged in scientific and engineering calculations.
Comprising a total of seven articles divided into five research articles, one review article, and one editorial article, this Special Issue is dedicated to new techniques for piezoelectric energy harvesting and its design, optimization, applications, and analysis [...]
As a composite material, the magnetic flow in the Magnetorheological elastomer (MRE) becomes elastable particles suspended in the non-magnetic elastomer body. The magnetic field effect can make the material have variable stiffness and damping characteristics, so that it is adaptive and controllable. The biggest disadvantage of traditional MRE is that the width of the operating band is limited and narrow. The present work proposes a new model of seismic isolator based on MRE mixed with carbon Nano-tubes. During the curing process, a multi-wall carbon Nano-tubes (MWCNTs), which provides the adaptive frequency for real-time vibration control under transient disturbance. The adaptability has greatly improved the sustainability of the structures, especially for the high-risk structures of earthquakes. We found that the magnetic flow into the elastic body has more effective functions when mixed with MWCNTs. Compared with the traditional isolators, the magnetic and mechanical properties of the material are improved well, and it is expected to achieve structure optimization and adaptive performance.
A brake is a device used for slowing or controlling speed to a certain value under varying conditions, or for stopping a vehicle or other moving mechanism by the absorption or transfer of the energy of momentum, usually by means of friction. Brakes are used in cars or other vehicles where safe, fast, and smooth stopping is needed, or in elevators, escalators, hoists, and winches that must stop and hold a load after lifting it. Also, machine tools, conveyors, and other manufacturing equipment that must often be brought to a safe, quick stop employ brakes. This chapter examines the types of brakes in mechanical applications, covering the full design of several types of brake, along with examples and solved/unsolved problems. The chapter describes the force and stress analysis of brakes such as band brakes, external shoe drum brakes, and internal shoe drum brakes. This chapter can be used as teaching material for courses in machine design for mechanical and industrial engineering majors in colleges and universities, and can also be used as a reference for scientific and technical personnel engaged in scientific and engineering calculations.
Open access peer-reviewed chapter
The aiming of this work is to enhancement the structural health monitoring (SHM) framework of beams structure for damage detection to treatment the drawbacks of poor detection efficiency in traditional of beams monitoring algorithms, the improvement framework on beams SHM is based on novel data classification technique through designing the k-Nearest Neighbor (k-NN) algorithm. First, the beam finite element model under impact load is analysis, and the cumulative damages are considered and introduced to beam model. The datasets of beam SHM are compiled from the sensors installed in beam structure, and then processed using kernel principal component analysis to remove the unnecessary features and reduce the scale of classification features. The k-NN algorithm parameters of beam SHM are determined by the genetic optimization algorithm (GOA) to establish the optimal SHM classification model of beam. Finally, a comparison between the present damage detection results via k-NN and traditional models via convolutional neural network (CNN) and supper vector machine (SVM) results available in literatures is established through the most significant indexes of testing to check the effectiveness and superiority of suggested method. The results show that the presented SHM model are gave higher precision, reduced the time of modeling, and improvement the total performance of damage detection model in beams. The current performance are recorded 95.3%, 91.8%, and 89.7%, for accuracy rate, recall rate, and F-score respectively.
This book has been designed and written to support the learning process in the Fundamentals of Machine Design course. It is therefore limited and dedicated to topics included in the contents of the book only. The arrangement of chapters is also governed by solve examples, assignments offered and problems. Each chapter comprises the body of a chapter together with illustration material. Some of the drawings shall be completed concurrently with my explanations during the chapters. The content of this book is 14 chapters and references and the objectives of this book are: 1) To incorporate knowledge learned in the mechanics, structures, materials, and manufacturing courses. 2) To reinforce competence in multi-axis stress analysis and understand the importance of using them to determine principal stresses and maximum shear stresses. 3) To obtain a working knowledge in the use of the proper failure theories under steady and variable loadings. 4) To master the design of mechanical elements, such as shafts, power screws, bolts and welded connections, spring, pressure vessels and transmitted power elements such as belts, chain, gears and wire ropes.
