Seyyed Ali Mousavi Gavgani

Dr. Seyyed Ali Mousavi Gavgani

Department of Civil Engineering, Kharazmi University, Tehran, Tehrān, Iran
orcid

Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
23 January 2023 in Journal of Building Engineering
Verified
Journal Article
Closed access
Himan Hojat JalaliHiman Hojat Jalali
Himan Hojat Jalali
MFMaziar Fahimi Farzam
Maziar Fahimi Farzam
Seyyed Ali Mousavi GavganiSeyyed Ali Mousavi Gavgani
Seyyed Ali Mousavi Gavgani
GBGebrail Bekdaş
Gebrail Bekdaş

5 December 2020
Verified
Book Chapter
Closed access
PDF file
MFMaziar Fahimi Farzam
Maziar Fahimi Farzam
Himan Hojat JalaliHiman Hojat Jalali
Himan Hojat Jalali
Seyyed Ali Mousavi GavganiSeyyed Ali Mousavi Gavgani
Seyyed Ali Mousavi Gavgani
AKAylin Ece Kayabekir
Aylin Ece Kayabekir
Gebrail BekdaşGebrail Bekdaş
Gebrail Bekdaş

26 April 2023 in Ocean Engineering
Verified
Journal Article
Closed access
SLSeyed Hossein Hosseini Lavassani
Seyed Hossein Hosseini Lavassani
Seyyed Ali Mousavi GavganiSeyyed Ali Mousavi Gavgani
Seyyed Ali Mousavi Gavgani
RDRouzbeh Doroudi
Rouzbeh Doroudi


14 March 2023 in Journal of Vibration Engineering & Technologies
Verified
Journal Article
Closed access
PDF file
RDReza Darbanian
Reza Darbanian
Seyyed Ali Mousavi GavganiSeyyed Ali Mousavi Gavgani
Seyyed Ali Mousavi Gavgani
VKVahid Reza Kalatjari
Vahid Reza Kalatjari

1 July 2022 in Advances in Bridge Engineering
Verified
Journal Article
Open access
PDF file
Seyyed Ali Mousavi GavganiSeyyed Ali Mousavi Gavgani
Seyyed Ali Mousavi Gavgani
AZAmir Ahmadnejad Zarnaghi
Amir Ahmadnejad Zarnaghi
SHSajad Heydari
Sajad Heydari
Early detection of structural damages and making necessary interventions to repair them are one of the main challenges in structural health monitoring. The wavelet transform is one of the common methods for this purpose, and its efficiency is proven by many researchers. In the present study, this approach is used to assess the performance of Sani-khani bridge with single and multiple-damage scenarios. For this purpose, the displacement response difference between the intact and damaged bridge decks under a moving load is analyzed by discrete wavelet transform (DWT). In the present study, 10 sensors and one-time sampling are used, In fact, the proposition of a method that uses the minimum number of required sensors for practical damage detection. To verify the reliability of the suggested method, not only different damage locations were considered, but also 5% noise is considered for the input signals. The attained results proved that even in the presence of the noise, the proposed approach can detect the damage locations with acceptable accuracy. The accuracy of the method for middle and side damages is higher than corner damages.