کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
799515 1467439 2016 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Nonlinear viscoelastic constitutive model identification for a polyurethane adhesive in a bonded joint using structural dynamic model updating
ترجمه فارسی عنوان
شناسایی مدل سازنده ناپیوسته واسکولاسیون برای یک چسب پلی اورتان در یک پیوند باند با استفاده از مدلسازی پویای مدل ساختاری
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی مکانیک
چکیده انگلیسی


• A nonlinear viscoelastic model was considered for a polyurethane adhesive.
• An updating method based on FRFs was modified to identify the model's parameters.
• Using experimentally measured FRFs the model's parameters were identified.
• Identified model resulted in highly correlated FRFs in comparison with experiments.
• As the excitation level increases, the storage modulus of the adhesive decreases.

In this study, a nonlinear viscoelastic constitutive model was identified to characterize the mechanical properties of an industrial adhesive in a bonded joint. A model updating method based on Frequency Response Function (FRF), referred to as the Response Function Method (RFM), was modified for identification of the parameters of the constitutive model. A test setup was utilized which comprises of a steel beam that is bonded to a heavy rigid steel block by a layer of Sikaflex-252 polyurethane adhesive. The accelerance FRFs at different excitation levels were measured experimentally, using the concept of Optimum Equivalent Linear FRF (OELF) and the parameters of the nonlinear viscoelastic constitutive model were identified. Then applying the identified model, the correlations between the FRFs of the FE models and the experimental ones were tested and high level of correlation was observed. Also, it has been shown that, as the strain level increases, the storage modulus of the adhesive decreases.

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ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Mechanics of Materials - Volume 100, September 2016, Pages 72–85
نویسندگان
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