Log InRegister
Quick Links : The Mindat ManualThe Rock H. Currier Digital LibraryMindat Newsletter [Free Download]
Home PageAbout MindatThe Mindat ManualHistory of MindatCopyright StatusWho We AreContact UsAdvertise on Mindat
Donate to MindatCorporate SponsorshipSponsor a PageSponsored PagesMindat AdvertisersAdvertise on Mindat
Learning CenterWhat is a mineral?The most common minerals on earthInformation for EducatorsMindat ArticlesThe ElementsThe Rock H. Currier Digital LibraryGeologic Time
Minerals by PropertiesMinerals by ChemistryAdvanced Locality SearchRandom MineralRandom LocalitySearch by minIDLocalities Near MeSearch ArticlesSearch GlossaryMore Search Options
Search For:
Mineral Name:
Locality Name:
Keyword(s):
 
The Mindat ManualAdd a New PhotoRate PhotosLocality Edit ReportCoordinate Completion ReportAdd Glossary Item
Mining CompaniesStatisticsUsersMineral MuseumsClubs & OrganizationsMineral Shows & EventsThe Mindat DirectoryDevice SettingsThe Mineral Quiz
Photo SearchPhoto GalleriesSearch by ColorNew Photos TodayNew Photos YesterdayMembers' Photo GalleriesPast Photo of the Day GalleryPhotography

Goodarzi, Saeed, Kashani, Hamed F., Saeedi, Anahita, Oke, Jimi, Ho, Carlton L. (2023) Stochastic analysis for estimating track geometry degradation rates based on GPR and LiDAR data. Construction and Building Materials, 369. 130591 doi:10.1016/j.conbuildmat.2023.130591

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleStochastic analysis for estimating track geometry degradation rates based on GPR and LiDAR data
JournalConstruction and Building Materials
AuthorsGoodarzi, SaeedAuthor
Kashani, Hamed F.Author
Saeedi, AnahitaAuthor
Oke, JimiAuthor
Ho, Carlton L.Author
Year2023 (March)Volume369
PublisherElsevier BV
DOIdoi:10.1016/j.conbuildmat.2023.130591Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID15693540Long-form Identifiermindat:1:5:15693540:3
GUID0
Full ReferenceGoodarzi, Saeed, Kashani, Hamed F., Saeedi, Anahita, Oke, Jimi, Ho, Carlton L. (2023) Stochastic analysis for estimating track geometry degradation rates based on GPR and LiDAR data. Construction and Building Materials, 369. 130591 doi:10.1016/j.conbuildmat.2023.130591
Plain TextGoodarzi, Saeed, Kashani, Hamed F., Saeedi, Anahita, Oke, Jimi, Ho, Carlton L. (2023) Stochastic analysis for estimating track geometry degradation rates based on GPR and LiDAR data. Construction and Building Materials, 369. 130591 doi:10.1016/j.conbuildmat.2023.130591
In(2023) Construction and Building Materials Vol. 369. Elsevier BV

See Also

These are possibly similar items as determined by title/reference text matching only.

Rohrman, Andrew K., Kashani, Hamed F., Ho, Carlton L. (2020) Effects of natural abrasion on railroad ballast strength and deformation properties. Construction and Building Materials, 247. 118315pp. doi:10.1016/j.conbuildmat.2020.118315
Faghihi Kashani, Hamed, Ho, Carlton L., Hyslip, James P. (2018) Fouling and water content influence on the ballast deformation properties. Construction and Building Materials, 190. 881-895 doi:10.1016/j.conbuildmat.2018.09.058
Popov, K., De Bold, R., Chai, H.-K., Forde, M.C., Ho, C.L., Hyslip, J.P., Kashani, H.F., Kelly, R., Hsu, S.S., Rippin, M. (2023) Data-driven track geometry fault localisation using unsupervised machine learning. Construction and Building Materials, 377. 131141 doi:10.1016/j.conbuildmat.2023.131141
Han, Lei, Liao, Yingying, Wang, Haoyu, Zhang, Hougui (2023) Long-term prediction for railway track geometry based on an optimised DNN method. Construction and Building Materials, 401. 132687 doi:10.1016/j.conbuildmat.2023.132687
Charoenwong, C., Connolly, D.P., Colaço, A., Alves Costa, P., Woodward, P.K., Romero, A., Galvín, P. (2023) Railway slab vs ballasted track: A comparison of track geometry degradation. Construction and Building Materials, 378. 131121 doi:10.1016/j.conbuildmat.2023.131121
Popov, K., De Bold, R., Chai, H.-K., Forde, M.C., Ho, C.L., Hyslip, J.P., Kashani, H.F., Long, P., Hsu, S.S. (2022) Big-data driven assessment of railway track and maintenance efficiency using Artificial Neural Networks. Construction and Building Materials, 349. 128786 doi:10.1016/j.conbuildmat.2022.128786
Poncetti, Bernardo Lopes, Ruiz, Dianelys Vega, Futai, Marcos Massao (2025) GPR time-energy density analysis with complex wavelets for concrete data analysis. Construction and Building Materials, 458. doi:10.1016/j.conbuildmat.2024.139694
Uranjek, Mojmir, Štrukelj, Andrej, Lenart, Stanislav, Peruš, Iztok (2020) Analysis of influential parameters for accelerated degradation of ballast railway track. Construction and Building Materials, 261. 119938pp. doi:10.1016/j.conbuildmat.2020.119938
Kaplanvural, Ä°smail (2023) Volumetric water content estimation of concrete by particle swarm optimization of GPR data. Construction and Building Materials, 375. 130995 doi:10.1016/j.conbuildmat.2023.130995
Wang, Xin, Liu, Xiang, Euston, Todd L. (2023) Relationship between track geometry defect occurrence and substructure condition: A case study on one passenger railroad in the United States. Construction and Building Materials, 365. 130066 doi:10.1016/j.conbuildmat.2022.130066
Mohit, Mehdi, Haftbaradaran, Hamed, Riahi, Hossein Tajmir (2023) Investigating the ternary cement containing Portland cement, ceramic waste powder, and limestone. Construction and Building Materials, 369. 130596 doi:10.1016/j.conbuildmat.2023.130596
 
and/or  
Mindat.org is an outreach project of the Hudson Institute of Mineralogy, a 501(c)(3) not-for-profit organization.
Copyright © mindat.org and the Hudson Institute of Mineralogy 1993-2025, except where stated. Most political location boundaries are © OpenStreetMap contributors. Mindat.org relies on the contributions of thousands of members and supporters. Founded in 2000 by Jolyon Ralph.
To cite: Ralph, J., Von Bargen, D., Martynov, P., Zhang, J., Que, X., Prabhu, A., Morrison, S. M., Li, W., Chen, W., & Ma, X. (2025). Mindat.org: The open access mineralogy database to accelerate data-intensive geoscience research. American Mineralogist, 110(6), 833–844. doi:10.2138/am-2024-9486.
Privacy Policy - Terms & Conditions - Contact Us / DMCA issues - Report a bug/vulnerability Current server date and time: August 27, 2025 07:09:42
Go to top of page