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Structure and Infrastructure Engineering
Maintenance, Management, Life-Cycle Design and Performance
Volume 14, 2018 - Issue 2
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Original Articles

Evaluation of uncertainties in sewer condition assessment

Nicolas CaradotKompetenzzentrum Wasser Berlin, Berlin, GermanyCorrespondence[email protected]
,
Pascale RouaultKompetenzzentrum Wasser Berlin, Berlin, Germany
,
Francois ClemensSection Sanitary Engineering, Faculty of Civil Engineering and Geosciences, University of Technology, Delft, The Netherlands
&
Frederic CherquiINSA-LYON, University of Lyon, Université Claude Bernard Lyon 1, Villeurbanne, France
Pages 264-273 | Received 04 Jan 2017, Accepted 05 Jun 2017, Published online: 02 Aug 2017

Citations (17)

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Read on this site (3)

Thomas Fugledalen, Marius Møller Rokstad & Franz Tscheikner-Gratl. (2023) On the influence of input data uncertainty on sewer deterioration models – a case study in Norway. Structure and Infrastructure Engineering 19:8, pages 1064-1075.
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Nicolas Caradot, Mathias Riechel, Pascale Rouault, Antoine Caradot, Nic Lengemann, Elke Eckert, Alexander Ringe, François Clemens & Frédéric Cherqui. (2020) The influence of condition assessment uncertainties on sewer deterioration modelling. Structure and Infrastructure Engineering 16:2, pages 287-296.
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Vitor Sousa, José P. Matos, Natércia Matias & Inês Meireles. (2019) Statistical comparison of the performance of data-based models for sewer condition modeling. Structure and Infrastructure Engineering 15:12, pages 1680-1693.
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Articles from other publishers (14)

Bardia Roghani, Massoud Tabesh & Frédéric Cherqui. (2023) A Fuzzy Multidimensional Risk Assessment Method for Sewer Asset Management. International Journal of Civil Engineering.
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Hossein Khaleghian & Yongwei Shan. (2023) Developing a Data Quality Evaluation Framework for Sewer Inspection Data. Water 15:11, pages 2043.
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Mingzhu Wang & Xianfei Yin. (2022) Construction and maintenance of urban underground infrastructure with digital technologies. Automation in Construction 141, pages 104464.
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Bartosz Szeląg, Grzegorz Łagód, Anna Musz-Pomorska, Marcin K. Widomski, David Stránský, Marek Sokáč, Jozefína Pokrývková & Roman Babko. (2022) Development of Rainfall-Runoff Models for Sustainable Stormwater Management in Urbanized Catchments. Water 14:13, pages 1997.
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Jingjing Guo & Qian Wang. (2022) Human-Related Uncertainty Analysis for Automation-Enabled Façade Visual Inspection: A Delphi Study. Journal of Management in Engineering 38:2.
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S. Ulutaş, M. Wichern & B. Bosseler. (2022) Laboratory investigations on the quality of leak tests and visual inspections of wastewater connection pipes carried out by specialist contractors. Water Practice and Technology 17:1, pages 91-101.
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Małgorzata Kutyłowska & Dariusz Kowalski. (2021) Application of regression methods for classification of sewers’ damages. Applied Water Science 11:9.
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S. Ulutaş, M. Wichern & B. Bosseler. (2021) Evaluation of testing procedures for real-scale sewage pipes. Water Science and Technology 84:4, pages 810-819.
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N. Caradot, Ph. R. Sampaio, A. S. Guilbert, H. Sonnenberg, V. Parez & V. Dimova. (2021) Using deterioration modelling to simulate sewer rehabilitation strategy with low data availability. Water Science and Technology 83:3, pages 631-640.
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Xin Zuo, Bin Dai, Yongwei Shan, Jifeng Shen, Chunlong Hu & Shucheng Huang. (2020) Classifying cracks at sub-class level in closed circuit television sewer inspection videos. Automation in Construction 118, pages 103289.
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Srinath Shiv Kumar, Mingzhu WangDulcy M. AbrahamMohammad R. Jahanshahi, Tom IseleyJack C. P. Cheng. (2020) Deep Learning–Based Automated Detection of Sewer Defects in CCTV Videos. Journal of Computing in Civil Engineering 34:1.
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Bardia Roghani, Frédéric Cherqui, Mehdi Ahmadi, Pascal Le Gauffre & Massoud Tabesh. (2019) Dealing with uncertainty in sewer condition assessment: Impact on inspection programs. Automation in Construction 103, pages 117-126.
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Nathalie Hernández, Nicolas Caradot, Hauke Sonnenberg, Pascale Rouault & Andrés Torres. (2018) Support tools to predict the critical structural condition of uninspected pipes for case studies of Germany and Colombia. Water Practice and Technology 13:4, pages 794-802.
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N. Caradot, M. Riechel, M. Fesneau, N. Hernandez, A. Torres, H. Sonnenberg, E. Eckert, N. Lengemann, J. Waschnewski & P. Rouault. (2018) Practical benchmarking of statistical and machine learning models for predicting the condition of sewer pipes in Berlin, Germany. Journal of Hydroinformatics 20:5, pages 1131-1147.
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