کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6711833 | 1428721 | 2018 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Evaluation of the performance of sensor-enabled geobelts after cyclic loading
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی عمران و سازه
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Evaluation of the performance of sensor-enabled geobelts after cyclic loading Evaluation of the performance of sensor-enabled geobelts after cyclic loading](/preview/png/6711833.png)
چکیده انگلیسی
Geosynthetics are an effective method to increase the seismic level of reinforcement soil structures. In this paper, sensor-enabled geobelts (SEGB) that performed self-measurement and reinforcement functions were developed on the strain-sensitive electrical conductivity (tensoresistivity) of the high-density polyethylene (HDPE) filled with super conductive carbon black (CB). To study the influence of seismic loads on SEGB, a series of cyclic loading tests were performed. Before cyclic loading, different prestrains were applied to simulate the deformation of SEGB in soil before earthquake. The results show that the tensile strength and elongation at break of SEGB after cyclic loading decrease with the number of loading cycles and strain amplitude of cyclic load, though the prestrains have a limited influence on the reduction of mechanical properties of SEGB. For the tensoresistivity response of SEGB after cyclic loading, the electrical conductivity of SEGB becomes more sensitive to strain by increasing number of loading cycles, amplitude of cyclic load and prestrains. Based on the test results, a preliminary model was proposed to evaluate the tensoresistivity performance of SEGB after cyclic loading.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Construction and Building Materials - Volume 185, 10 October 2018, Pages 414-422
Journal: Construction and Building Materials - Volume 185, 10 October 2018, Pages 414-422
نویسندگان
Xin-zhuang Cui, She-qiang Cui, Tu Lu, Lei Zhang, Yi-lin Wang, Jun Li,