&lt;title&gt;Active composite materials as sensing elements for fiber-reinforced smart composite structures&lt;/title&gt;

Blanas, P.; Wenger, M. P.; Rigas, Elias J.; Das-Gupta, D.K.

doi:10.1117/12.316917

Cited by 8 publications

(5 citation statements)

References 2 publications

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“…Many researchers have demonstrated that new features may be induced by combining two or more materials in a controlled ratio which is known as the composite structures process, which has recently become an interesting topic of research [1][2][3][4]. Composites have been used in a variety of applications including sensors, electrodes, photocatalysts, fuel cells, non-volatile magnetic memories, and data storage device magnetic heads [5][6][7][8]. Zinc oxide (ZnO) nanoparticles have attracted a lot of attention because of their good performance in optics, electronics, and photonics fields [9].…”

Section: Introductionmentioning

confidence: 99%

Tuning the optical and magnetic properties of ZnO by Fe₃O₄

Solyman¹,

Ahmed²,

Azab³

2022

Phys. Scr.

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In this work, nanocomposites were prepared with different weight ratios based on the formula (1-x)ZnO + (x)Fe3O4, where x = 0.01, 0.03, 0.05, 0.07 and 0.09. The structure, morphology, optical, and magnetic properties were examined by X-ray diffraction, UV VIS-NIR diffuse reflectance spectroscopy, high-resolution transmission electron microscopy (HRTEM), and vibrating sample magnetometer (VSM). The X-ray diffraction (XRD) results confirm the phase purity formation of Fe3O4-ZnO nanocomposites. The transmission electron microscopy (TEM) exhibited the prepared powders are nanoparticles with the spherical shapes of Fe3O4 and nanorod for ZnO. UV VIS-NIR diffuse reflectance measurements showed that the Fe3O4 modified the optical properties of ZnO. Results of the vibrating sample magnetometer (VSM) display a superparamagnetic characteristic of Fe3O4 and ferromagnetic behavior for nanocomposites. The magnetization and remanence magnetization of nanocomposites increases with Fe3O4 content.

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Section: Introductionmentioning

confidence: 99%

Tuning the optical and magnetic properties of ZnO by Fe₃O₄

Solyman¹,

Ahmed²,

Azab³

2022

Phys. Scr.

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“…Moetakef, Joshi, and Lawrence (1996) performed finite-element modeling and experimental study of elastic waves generation through equally spaced piezoceramic wafers. Blanas et al (1997Blanas et al ( , 1998 studied the use of active composites sensors for acoustic-emission health monitoring. Liang et al (1996) developed an impedance method for dynamic analysis of active material systems.…”

Section: Introductionmentioning

confidence: 99%

<title>Active sensor wave propagation health monitoring of beam and plate structures</title>

2001

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Active sensor wave propagation technique is a relatively new method for in-situ nondestructive evaluation (NDE). Elastic waves propagating in material carry the information of defects. These information can be extracted by analyzing the signals picked up by active sensors. Due to the physical property of wave propagation, large area can be interrogated by a few transducers. This simplifies the process of detecting and characterizing defects. To apply this method, efficient numerical modeling is required to predict signal amplitude and time history of elastic wave scattering and diffraction. In order to construct the model, good understanding of these physical phenomena must be achieved. This paper presents results of an investigation of the applicability of active sensors for in-situ health monitoring of aging aircraft structures. The project set forth to develop non-intrusive active sensors that can be applied on existing aging aerospace structures for monitoring the onset and progress of structural damage such as fatigue cracks and corrosion. Wave propagation approach was used for large area detection. In order to get the theoretical solution of elastic wave propagating in the material, wave functions of axial wave, share wave, flexure wave, Raleigh wave, and Lamb waves were thoroughly investigated. The wave velocities and the motion of these different types of waves were calculated and simulated using mathematical analysis programs. Finite Element Method was used to simulate and predict the wave propagating through the structure for different excitation and boundary conditions. Aluminum beams and plates were used to get experiment results. Structures both pristine and with known defects are used in our investigation. The experimental results were then compared with the theoretical results.

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“…This approach seemed to offer better resolution to detect high-frequency shifts due to transverse-crack damage. Blanas et al (1998) studied the use of composites active sensors for acoustic-emission health monitoring. Kawiecki (1998) demonstrated experimentally the feasibility of nondestructive damage detection by an array of piezotransducers (25-mm square, 025 mm thick) bonded to the surface of four types of structures: aluminum beam; aluminum plate; concrete beam; concrete block.…”

Section: Wave Propagation Methodologiesmentioning

confidence: 99%

Active sensors for health monitoring of aging aerospace structures

Giurgiutiu

Redmond²,

Roach³

et al. 2000

SPIE Proceedings

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A project to develop non-intrusive active sensors that can be applied on existing aging aerospace structures for monitoring the onset and progress of structural damage (fatigue cracks and corrosion) is presented. The state of the art in active sensors structural health monitoring and damage detection is reviewed. Methods based on (a) elastic wave propagation and (b) electro-mechanical (E/M) impedance technique are cited and briefly discussed. The instrumentation of these specimens with piezoelectric active sensors is illustrated. The main detection strategies (E/M impedance for local area detection and wave propagation for wide area interrogation) are discussed. The signal processing and damage interpretation algorithms are tuned to the specific structural interrogation method used. In the high-frequency E/M impedance approach, pattern recognition methods are used to compare impedance signatures taken at various time intervals and to identify damage presence and progression from the change in these signatures. In the wave propagation approach, the acousto-ultrasonic methods identifying additional reflection generated from the damage site and changes in transmission velocity and phase are used. Both approaches benefit from the use of artificial intelligence neural networks algorithms that can extract damage features based on a learning process. Design and fabrication of a set of structural specimens representative of aging aerospace structures is presented. Three built-up specimens, (pristine, with cracks, and with corrosion damage) are used. The specimen instrumentation with active sensors fabricated at the University of South Carolina is illustrated. Preliminary results obtained with the E/M impedance method on pristine and cracked specimens are presented.

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<title>Active composite materials as sensing elements for fiber-reinforced smart composite structures</title>

Cited by 8 publications

References 2 publications

Tuning the optical and magnetic properties of ZnO by Fe₃O₄

Tuning the optical and magnetic properties of ZnO by Fe₃O₄

<title>Active sensor wave propagation health monitoring of beam and plate structures</title>

Active sensors for health monitoring of aging aerospace structures

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<title>Active composite materials as sensing elements for fiber-reinforced smart composite structures</title>

Cited by 8 publications

References 2 publications

Tuning the optical and magnetic properties of ZnO by Fe3O4

Tuning the optical and magnetic properties of ZnO by Fe3O4

<title>Active sensor wave propagation health monitoring of beam and plate structures</title>

Active sensors for health monitoring of aging aerospace structures

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Resources

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Tuning the optical and magnetic properties of ZnO by Fe₃O₄

Tuning the optical and magnetic properties of ZnO by Fe₃O₄