A critical problem encountered in structural health monitoring of civil engineering structures, and other structures such as mechanical or aircraft structures, is how to convincingly analyze the nonstationary data that is coming online, how to reduce the high-dimensional features, and how to extract informative features associated with damage to infer structural conditions. Wavelet transform among other techniques has proven to be an effective technique for processing and analyzing nonstationary data due to its unique characteristics. However, the biggest challenge frequently encountered in assuring the effectiveness of wavelet transform in analyzing massive nonstationary data from civil engineering structures, and in structural health diagnosis, is how to select the right wavelet. The question of which wavelet function is appropriate for processing and analyzing the nonstationary data in civil engineering structures has not been clearly addressed, and no clear guidelines or rules have been reported in the literature to show how the right wavelet is chosen. Therefore, this study aims to address an important question in this regard by proposing a new framework for choosing a proper wavelet that can be customized for massive nonstationary data analysis, disturbances separation, and extraction of informative features associated with damage. The proposed method takes into account data type, data and wavelet characteristics, similarity, sharing information, and data recovery accuracy. The novelty of this study lies in integrating multi-criteria which are associated directly with features that correlated well with change in structures due to damage, including common criteria such as energy, entropy, linear correlation index, and variance. Also, it introduces and considers new proposed measures, such as wavelet-based nonlinear correlation such as cosh spectral distance and mutual information, wavelet-based energy fluctuation, measures-based recovery accuracy, such as sensitive feature extraction, noise reduction, and others to evaluate various base wavelets’ function capabilities for appropriate decomposition and reconstruction of structural dynamic responses. The proposed method is verified by experimental and simulated data. The results revealed that the proposed method has a satisfactory performance for base wavelet selection and the small order of Daubechies and Symlet provide the best results, especially order 3. The idea behind our proposed framework can be applied to other structural applications.
This chapter discusses the fundamental principles of bearing selection, lubrication, design computations, advanced bearing materials, arrangement, housing, and seals. Also, this chapter discusses fatigue failure mechanisms, fatigue lifetimes, and the reliability of rolling bearings and lubricating greases. Furthermore, readers are provided with hands-on essential formulas, along with examples and solved/unsolved problems for computational design of rolling bearings. This chapter can be used as teaching material for courses in machine design for mechanical, industrial, and materials 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.
Most organizations today strive to achieve sustainability. Although there are many definitions given to sustainability, there is no agreed definition. The idea
Implementation of efficient vibration control schemes for seismically excited structures is becoming more and more important in recent years. In this study
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This paper introduces a stiffness reduction based model developed by the authors to characterize accumulative fatigue damage in unidirectional plies and (0/θ/0) composite laminates in fiber reinforced polymer (FRP) composite laminates. The proposed damage detection model is developed based on a damage evolution mechanism, including crack initiation and crack damage progress in matrix, matrix-fiber interface and fibers. Research result demonstrates that the corresponding stiffness of unidirectional composite laminates is reduced as the number of loading cycles progresses. First, three common models in literatures are presented and compared. Tensile viscosity, Young’s modulus and ultimate tensile stress of composites are incorporated as key factors in this model and are modified in accordance with temperature. Four types of FRP composite property parameters, including Carbon Fiber Reinforced Polymer (CFRP), Aramid Fiber Reinforced Polymer (AFRP), Glass Fiber Reinforced Polymer (GFRP), and Basalt Fiber Reinforced Polymer (BFRP), are considered in this research, and a comparative parameter study of FRP unidirectional composite laminates with different off-angle plies using control variate method are discussed. It is concluded that the relationship between the drop in stiffness and the number of cycles also shows three different regions, following the mechanism of damage of FRP composites and the matrix is the dominant factor determined by temperature, while fiber strength is the dominant factor that determine the reliability of composite.
This chapter provides readers with an inclusive study of all stress types applied on structures and presents a comprehensive introduction to load and stress analysis. The chapter starts with the basic principles of load and stress analysis, and then covers the different types of stress, such as simple stress, combined stress, tensile stress, compressive stress, bending stress, direct shear, torsion stress, and thermal stresses. This chapter also presents how to evaluate the various types of stress and apply them in design equations, along with examples and solved/unsolved problems. The chapter can be used as teaching material for courses in machine design for mechanical, industrial, and materials 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.
The Micro circular diaphragm (MCD) is the mechanical actuator part used in the micro electro-mechanical sensors (MEMS) that combine electrical and mechanical components. These actuators are working under harsh mechanical and thermal conditions, so it is very important to study the mechanical and thermal behaviors of these actuators, in order to do with its function successfully. The objective of this paper is to determine the thermo-mechanical behavior of MCD by developing the traditional bulge test technique to achieve the aims of this work. The specimen is first pre-stressed to ensure that is no initial deflection before applied the loads on diaphragm and then clamped between two plates, a differential pressure (P) and temperature (<TEX>$T_b$</TEX>) is leading to a deformation of the MCD. Analytical formulation of developed bulge test technique for MCD thermo-mechanical characterization was established with taking in-to account effect of the residual strength from pre-stressed loading. These makes the plane-strain bulge test ideal for studying the mechanical and thermal behavior of diaphragm in both the elastic and plastic regimes. The differential specimen thickness due to bulge effect to describe the mechanical behavior, and the temperature effect on the MCD material properties to study the thermal behavior under deformation were discussed. A finite element model (FEM) can be extended to apply for investigating the reliability of the proposed bulge test of MCD and compare between the FEM results and another one from analytical calculus. The results show that, the good convergence between the finite element model and analytical model.
Modal macro strain-based damage identification is a promising approach since it has the advantages of high sensitivity and effectiveness over other related methods. In this paper, a basalt fiber-reinforced polymer (BFRP) pipeline system is used for analysis by using long-gauge distributed fiber Bragg grating (FBG) sensors. Dynamic macro strain responses are extracted to form modal macro strain (MMS) vectors. Both longitudinal distribution and circumferential distribution plots of MMS are compared and analyzed. Results show these plots can reflect damage information of the pipeline based on the previous work carried out by the authors. However, these plots may not be good choices for accurate detection of damage information since the model is 3D and has different flexural and torsional effects. Therefore, by extracting MMS information in the circumferential distribution plots, a novel deep neural network is employed to train and test these images, which reflect the important and key information of modal variance in the pipe system. Results show that the proposed Deep Learning based approach is a promising way to inherently identify damage types, location of the excitation load and support locations, especially when the structural types are complicated and the ambient environment is changing.
In this paper, basic concepts of resilience, ecology and sustainability are introduced first. Then, associated performance metrics and interdependency of critical infrastructure systems are presented and discussed. Moreover, the importance of big data (BD) and data mining (DM), as emerging themes in this field, is discussed. Other relevant issues such as how to foster decision making and accountability to plan for any expansion in resilience services, resources, and the associated performance metrics and interdependency of critical infrastructure systems are presented. It is the recommendation of this study that due to the difficulty and complexity of resilience, and its definitional ambiguity, the ability to assess such a concept helps to bridge the gap between theory and application, and between the academic and the policy circles. A framework for creating resilient, ecological and sustainable infrastructure systems is also proposed, as a recommendation, in a more holistic and comprehensive way.
Undoubtedly, infrastructure is the backbone of the world’s economies. This include transportation networks, such as bridges, tunnels, subways, railways, ship yard cranes; water delivery, utilities, dams, various pipeline networks, power transmission, communication network, government centers, and large business centers. Resilience research for infrastructure networks covers multifaceted and multidisciplinary domains encompassing risk analysis, uncertainty quantification, reliability design, vulnerability mitigation, performance improvement, sustainable development. It is characterized of diversity, efficiency, adaptability, and cohesion. However, a holistic framework for creating resilient infrastructure systems regarding component, system and system-of-systems levels has not been established by incorporating technical, organizational, economic, social and environmental, and ecological dimensions. In this paper, basic concepts of resilience, ecology and sustainability are introduced first. Then given associated performance metrics and interdependency of critical infrastructure systems are presented and discussed the importance of big data and data mining to foster decision-making and accountability to plan for any expansion in resilience services, resources, and the associated performance metrics and interdependency of critical infrastructure systems are presented. We found after study, due to the difficulty and complexity of resilience, and its definitional ambiguity, the ability to assess such a concept helps to bridge the gap between theory and application, between academic and policy circles. A framework for creating resilient, ecological and sustainable infrastructure systems is proposed in a more holistic and comprehensive way. This framework is shown promising for its effectiveness and efficiency in modeling, designing and assessing system resilience. Finally, the review reveals that several opportunities are available for apply the resilience on infrastructure; however, there are still many issues and challenges to be addressed to achieve better utilization of this technology, and the new evaluation methodology for the resilience system used gave specific and satisfied results and completely methodology for resilience evaluation.
This paper presents a semi-analytical method to investigate the effect of intermediate elastic support on the natural frequencies of basalt fiber reinforced polymer (FRP) laminated, variable thickness plates based on the finite strip transition matrix (FSTM) method. The plate has a uniform thickness in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>x</mml:mi></mml:math> direction and varying thickness <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>h</mml:mi><mml:mfenced separators="|"><mml:mrow><mml:mi>y</mml:mi></mml:mrow></mml:mfenced></mml:math> in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>y</mml:mi></mml:math> direction. A singular value decomposition algorithm is employed at the intermediate support to eliminate the dependence of the solution of the first span on another span. By a new treatment of the intermediate line support, the dimension of the final matrix of the general solution will be the same as that of plates without intermediate support. Numerical results for different combinations of classical boundary conditions at the plate edges with different elastic restraint coefficients (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mrow><mml:mi>K</mml:mi></mml:mrow><mml:mrow><mml:mi>T</mml:mi></mml:mrow></mml:msub></mml:math>) for intermediate elastic support are presented to obtain the first six frequency parameters. The illustrated results are in excellent agreement with solutions available in the literature, thus validating the accuracy and reliability of the proposed technique.
The deflection of a section is the displacement of the centroid of the cross section of the beam along the direction perpendicular to the axis of the beam, which is one of the basic quantities to measure the deformation of a beam. There are many factors that cause structure displacement, such as load, temperature change, support displacement, and so on. On the premises that the material obeys Hooke's law, the structure has small deformation, and the connection has no friction, the methods of structural mechanics are used to derive the displacement formula of the structure under load. This chapter examines the methods to derive the displacement formula, such as double integration, superposition, area moment, singularity functions, strain energy (Castigliano), and the three-moment equation, and then discusses the deflection in columns (buckling), along with examples and solved/unsolved problems. This chapter can be used as teaching material for courses in machine design for mechanical, industrial engineering, and materials 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.
