The Experts below are selected from a list of 18819 Experts worldwide ranked by ideXlab platform

Victor Giurgiutiu - One of the best experts on this subject based on the ideXlab platform.

  • Predictive model of fatigue crack detection in thick bridge steel structures with piezoelectric wafer active sensors
    Smart Structures and Systems, 2013
    Co-Authors: Matthieu Gresil, Lingyu Yu, Yanfeng Shen, Victor Giurgiutiu
    Abstract:

    This paper presents numerical and experimental results on the use of guided waves for structural health monitoring (SHM) of crack growth during a fatigue test in a thick steel plate used for Civil Engineering Application. Numerical simulation, analytical modeling, and experimental tests are used to prove that piezoelectric wafer active sensor (PWAS) can perform active SHM using guided wave pitch-catch method and passive SHM using acoustic emission (AE). AE simulation was performed with the multi-physic FEM (MP-FEM) approach. The MP-FEM approach permits that the output variables to be expressed directly in electric terms while the two-ways electromechanical conversion is done internally in the MP-FEM formulation. The AE event was simulated as a pulse of defined duration and amplitude. The electrical signal measured at a PWAS receiver was simulated. Experimental tests were performed with PWAS transducers acting as passive receivers of AE signals. An AE source was simulated using 0.5-mm pencil lead breaks. The PWAS transducers were able to pick up AE signal with good strength. Subsequently, PWAS transducers and traditional AE transducer were applied to a 12.7-mm CT specimen subjected to accelerated fatigue testing. Active sensing in pitch catch mode on the CT specimen was applied between the PWAS transducers pairs. Damage indexes were calculated and correlated with actual crack growth. The paper finishes with conclusions and suggestions for further work.

  • fatigue crack detection in thick steel structures with piezoelectric wafer active sensors
    Proceedings of SPIE, 2011
    Co-Authors: Matthieu Gresil, Victor Giurgiutiu
    Abstract:

    ABSTRACT This paper presents a set of numerical and experimental results on the use of guided waves for structural health monitoring (SHM) of crack growth during a fatigue test in a thick steel plate used for Civil Engineering Application. The capability of embedded piezoelectric wafer active sensors (PWAS) to perform in situ nondestructive evaluation (NDE) is explored. Numerical simulation and experimental tests are used to prove that PWAS can perform active SHM using guided wave pitch-catch method and passive SHM using acoustic emission (AE). Multi-physics finite element (MP-FEM) codes are used to simulate the transmission and reception of guided waves in a 1-mm plate and their diffraction by a through hole. The MP-FEM approach permitted that the input and output variables be expressed directly in electric terms while the two-ways electromechani cal conversion was done internally in the MP-FEM formulation. The analysis was repeated for several hole sizes and a damage index performances was tested. AE simulation was performed with the MP-FEM approach in a 13-mm plate in the shape of the compact tension (CT) fracture mechanics specimen. The AE event was simulated as a pulse of defi ned duration and amplitude. The electrical signal measured at a receiver PWAS was simulated. Daubechies wavelet transform was used to process the signal and identify its Lamb modes and FFT frequency contents. Experimental tests were performed with PWAS transducers acting as passive receivers of AE signals. The 8-mm thick flange of an I beam was instrumented on one side with PWAS transducers and on the other side with conventional AE transducers (PAC R15I) acting as comparison witnesses. An AE source was simulated using 0.5-mm pencil lead breaks; the PWAS transducers were able to pick up AE signal with good strength. Subsequently, PWAS transducers and R15I sensors were app lied to a 13-mm CT specimen subjected to accelerated fa tigue testing. The PWAS and R15I transducers signals were collected with PAC data acquisition system using the AE-win software. Comparative results of AE hits and source localization from the PWAS and R15I sensors are given. Active sensing in pitch catch mode was applied between the PWAS transducers installed on the CT specimen and damage indexes were calculated and correlated with physical crack growth as measured optically. The paper finishes with summary, conclusion, and suggestions for further work. Keywords : Acoustic emission, finite element modeling, fatigue test , crack, piezoelectric, stru ctural health monitoring.

Matthieu Gresil - One of the best experts on this subject based on the ideXlab platform.

  • Predictive model of fatigue crack detection in thick bridge steel structures with piezoelectric wafer active sensors
    Smart Structures and Systems, 2013
    Co-Authors: Matthieu Gresil, Lingyu Yu, Yanfeng Shen, Victor Giurgiutiu
    Abstract:

    This paper presents numerical and experimental results on the use of guided waves for structural health monitoring (SHM) of crack growth during a fatigue test in a thick steel plate used for Civil Engineering Application. Numerical simulation, analytical modeling, and experimental tests are used to prove that piezoelectric wafer active sensor (PWAS) can perform active SHM using guided wave pitch-catch method and passive SHM using acoustic emission (AE). AE simulation was performed with the multi-physic FEM (MP-FEM) approach. The MP-FEM approach permits that the output variables to be expressed directly in electric terms while the two-ways electromechanical conversion is done internally in the MP-FEM formulation. The AE event was simulated as a pulse of defined duration and amplitude. The electrical signal measured at a PWAS receiver was simulated. Experimental tests were performed with PWAS transducers acting as passive receivers of AE signals. An AE source was simulated using 0.5-mm pencil lead breaks. The PWAS transducers were able to pick up AE signal with good strength. Subsequently, PWAS transducers and traditional AE transducer were applied to a 12.7-mm CT specimen subjected to accelerated fatigue testing. Active sensing in pitch catch mode on the CT specimen was applied between the PWAS transducers pairs. Damage indexes were calculated and correlated with actual crack growth. The paper finishes with conclusions and suggestions for further work.

  • fatigue crack detection in thick steel structures with piezoelectric wafer active sensors
    Proceedings of SPIE, 2011
    Co-Authors: Matthieu Gresil, Victor Giurgiutiu
    Abstract:

    ABSTRACT This paper presents a set of numerical and experimental results on the use of guided waves for structural health monitoring (SHM) of crack growth during a fatigue test in a thick steel plate used for Civil Engineering Application. The capability of embedded piezoelectric wafer active sensors (PWAS) to perform in situ nondestructive evaluation (NDE) is explored. Numerical simulation and experimental tests are used to prove that PWAS can perform active SHM using guided wave pitch-catch method and passive SHM using acoustic emission (AE). Multi-physics finite element (MP-FEM) codes are used to simulate the transmission and reception of guided waves in a 1-mm plate and their diffraction by a through hole. The MP-FEM approach permitted that the input and output variables be expressed directly in electric terms while the two-ways electromechani cal conversion was done internally in the MP-FEM formulation. The analysis was repeated for several hole sizes and a damage index performances was tested. AE simulation was performed with the MP-FEM approach in a 13-mm plate in the shape of the compact tension (CT) fracture mechanics specimen. The AE event was simulated as a pulse of defi ned duration and amplitude. The electrical signal measured at a receiver PWAS was simulated. Daubechies wavelet transform was used to process the signal and identify its Lamb modes and FFT frequency contents. Experimental tests were performed with PWAS transducers acting as passive receivers of AE signals. The 8-mm thick flange of an I beam was instrumented on one side with PWAS transducers and on the other side with conventional AE transducers (PAC R15I) acting as comparison witnesses. An AE source was simulated using 0.5-mm pencil lead breaks; the PWAS transducers were able to pick up AE signal with good strength. Subsequently, PWAS transducers and R15I sensors were app lied to a 13-mm CT specimen subjected to accelerated fa tigue testing. The PWAS and R15I transducers signals were collected with PAC data acquisition system using the AE-win software. Comparative results of AE hits and source localization from the PWAS and R15I sensors are given. Active sensing in pitch catch mode was applied between the PWAS transducers installed on the CT specimen and damage indexes were calculated and correlated with physical crack growth as measured optically. The paper finishes with summary, conclusion, and suggestions for further work. Keywords : Acoustic emission, finite element modeling, fatigue test , crack, piezoelectric, stru ctural health monitoring.

Sheng Shen - One of the best experts on this subject based on the ideXlab platform.

  • a new type of smart basalt fiber reinforced polymer bars as both reinforcements and sensors for Civil Engineering Application
    Smart Materials and Structures, 2010
    Co-Authors: Yongsheng Tang, Caiqian Yang, Sheng Shen
    Abstract:

    In this paper, a new type of smart basalt fiber-reinforced polymer (BFRP) bar is developed and their sensing performance is investigated by using the Brillouin scattering-based distributed fiber optic sensing technique. The industrial manufacturing process is first addressed, followed by an experimental study on the strain, temperature and fundamental mechanical properties of the BFRP bars. The results confirm the superior sensing properties, in particular the measuring accuracy, repeatability and linearity through comparing with bare optical fibers. Results on the mechanical properties show stable elastic modulus and high ultimate strength. Therefore, the smart BFRP bar has potential Applications for long-term structural health monitoring (SHM) as embedded sensors as well as strengthening and upgrading structures. Moreover the coefficient of thermal expansion for smart BFRP bars is similar to the value for concrete.

Francesco Benedetto - One of the best experts on this subject based on the ideXlab platform.

  • Application field specific synthesizing of sensing technology Civil Engineering Application of ground penetrating radar sensing technology
    Reference Module in Materials Science and Materials Engineering#R##N#Comprehensive Materials Processing, 2014
    Co-Authors: Andrea Benedetto, Francesco Benedetto
    Abstract:

    In many fields of Civil Engineering, the needs for innovative sensing technologies are growing. Ground-penetrating radar (GPR) is actually one of the most advanced sensing technologies available, allowing a nonintrusive inspection of the materials under investigation. GPR uses radar pulses to image the subsurface, exploiting electromagnetic (EM) radiation and then detecting the reflected signals from subsurface structures. This chapter provides an overview of GPR sensing technologies for Civil Engineering Applications and related research topics. In particular, a number of promising concepts for GPR are introduced and discussed in this chapter, starting from the theoretical EM background of GPR signal propagation in soils and construction materials. Then, we illustrate the Applications of GPR to Civil Engineering fields, from the construction and inspection of transportation infrastructures and hydraulic works, to geotechnical surveys, environmental monitoring, as well as building and bridge structural assessments. We will demonstrate why GPR is currently considered as one of the most effective and efficient sensing technologies and is a potential candidate to become the best available remote-sensing technology for Civil Engineering Applications. Finally, a wide literature review will be presented in order to give the reader all of the sources of information useful for any in-depth study.

Yongsheng Tang - One of the best experts on this subject based on the ideXlab platform.

  • a new type of smart basalt fiber reinforced polymer bars as both reinforcements and sensors for Civil Engineering Application
    Smart Materials and Structures, 2010
    Co-Authors: Yongsheng Tang, Caiqian Yang, Sheng Shen
    Abstract:

    In this paper, a new type of smart basalt fiber-reinforced polymer (BFRP) bar is developed and their sensing performance is investigated by using the Brillouin scattering-based distributed fiber optic sensing technique. The industrial manufacturing process is first addressed, followed by an experimental study on the strain, temperature and fundamental mechanical properties of the BFRP bars. The results confirm the superior sensing properties, in particular the measuring accuracy, repeatability and linearity through comparing with bare optical fibers. Results on the mechanical properties show stable elastic modulus and high ultimate strength. Therefore, the smart BFRP bar has potential Applications for long-term structural health monitoring (SHM) as embedded sensors as well as strengthening and upgrading structures. Moreover the coefficient of thermal expansion for smart BFRP bars is similar to the value for concrete.