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dc.contributor.authorXie, Lejuan
dc.contributor.authorZhang, Shuzeng
dc.date.accessioned2025-04-21T10:06:27Z
dc.date.available2025-04-21T10:06:27Z
dc.date.copyright2/5/2025 12:00:00 AM
dc.date.issued2025
dc.identifier.issn2572-3901
dc.identifier.othernde_8_3_031006.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4305509
dc.description.abstractAn understanding of the influence of surface roughness on wave scattering and accurate predictions of wave amplitudes are crucial for quantitative ultrasonic nondestructive testing and evaluation. In this work, the effects of surface roughness on the reflection coefficient are investigated using a quasi-Monte Carlo (QMC) method. The wave fields reflected from smooth and rough interfaces with an immersion transducer are modeled using the Rayleigh integral method, and the solutions are efficiently calculated using the QMC method for interfaces constructed using pseudo-random samples. The reflected wave fields are simulated and presented, and the properties of coherent and incoherent waves affected by interface roughness are discussed. The surface roughness–induced attenuation of reflected waves is calculated using the ratio of received pressures for waves reflected from rough and smooth interfaces, and the predicted results are compared with those obtained using other recognized methods. It is shown that at low levels of roughness, excellent agreement is obtained between the results from the QMC method and the well-known Kirchhoff approximation, while for high levels of roughness, where the Kirchhoff theory gives pessimistic results, the predicted values agree well with those simulated using a finite element modeling approach, thus verifying the effectiveness of the proposed method.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleInvestigation of Surface Roughness–Induced Attenuation of Reflected Waves Using a Quasi-Monte Carlo Method
dc.typeJournal Paper
dc.journal.volume8
dc.journal.issue3
dc.journal.titleJournal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems
dc.identifier.doi10.1115/1.4067542
dc.journal.fristpage31006-1
dc.journal.lastpage31006-7
dc.page7
dc.treeJournal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems:;2025:;volume( 008 ):;issue: 003
dc.contenttypeFulltext


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