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615 results on '"Ravin N"'

1. Inferring highly corroded buried pipeline locations through saturated soil resistivity information

Author

Ravin N Deo, Rukshan Azoor, Guoyang Fu, Benjamin Shannon, and Jayantha Kodikara

Subjects
Underground corrosion, Soil resistivity, Condition assessment, Pipe inspection, Engineering (General). Civil engineering (General), TA1-2040
Abstract

Inspection and assessment of ageing buried metallic infrastructure such as pipelines can be costly, especially when soil sampling programs are involved to evaluate large networks and pipe health conditions. In order to reduce these costs through assessment prioritisation at infrastructure locations that are scientifically inferred to be under highly corroded state, advancements in current approaches are necessary. In this study we have investigated the utility of soil resistivity as an index for buried and ageing pipe health status through numerical and field case studies. Numerical study showed that the monotonous relationship between soil resistivity and maximum pit depth that is often considered in literature as linear is actually non-linear. Field study involving in-situ wall thickness measurements of 3 separate water distribution mains (each > 1.5 km in length) at selected excavated locations were compared with the saturated soil resistivity (ρsat) acquired a-prior. The ρsat was found to be highly correlated to the maximum corrosion pit depths observed in-situ. This correspondence is argued to exist provided the saturated soil resistivity displays statistical uniformity along the pipe and the pipes are not under submerged conditions. Locations on the pipe where ρsat < 15 Ω m were found to have corroded relatively more than other locations; in one instant a leaking pipe due to excessive corrosion was also observed. A practical indirect assessment framework was proposed that can be utilised immediately in professional practice.

Published
2022
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2. A Prototype of an Electromagnetic Induction Sensor for Non-Destructive Estimation of the Presence of Corrosive Chemicals Ensuing Concrete Corrosion

Author

Kabir A. Mamun, Ravin N. Deo, F. R. Islam, Hemanshu R. Pota, Aneesh A. Chand, Kushal A. Prasad, and Aisake Cakacaka

Subjects
EMI sensor, concrete corrosion, non-destructive evaluation, single-loop coil (SLC), multiple-loop coil (MLC), Chemical technology, TP1-1185
Abstract

The corrosion of steel reinforcement in concrete often leads to huge unbudgeted expenses for maintaining, monitoring and renovating an infrastructure. This is mainly due to the presence of salts or chemical chlorides that pose a danger to the concrete structures. The determination of the existence of these corrosive salts is vital for defining the service life of concrete. This research looked at developing an electromagnetic induction (EMI) sensor for the detection of corrosive salts. The first design adopted a single-loop coil (SLC) concept, and the second was based on a multiple-loop coil (MLC) one using copper wire. Tests were conducted on these two techniques, and with the results obtained, the latter seemed more promising; thus, a prototype sensor was developed using the MLC concept. As this new prototype sensor was able to detect the manifestation of chemical contents in a concrete structure, it could be used as a non-destructive evaluation (NDE) technique for the detection of corrosive chemicals in concrete and has the further possibility of detecting corrosion in concrete.

Published
2019
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44. Numerical Study on Urban Infrastructure Diagnosis in Laterally Heterogenous Soils Using Resistivity and Ground Penetrating Radar Techniques

Author

Ravin N Deo, Nikhil Singh, Kaushal Kishore, and Jayantha Kodikara

Subjects
Geophysics, Environmental Engineering, Geotechnical Engineering and Engineering Geology
Abstract

Urban environment can be considered a complex system consisting of the engineered pavement physical structure over the buried utilities (water, gas, sewer) network embedded in the background soil environment. Assessment of buried pipeline civil infrastructures using proximal geophysical methods in such instances has to consider possible interferences, difficulties, and incorrect inferences. In this study, we have conducted a numerical modelling investigation to understand and evaluate how electrical resistivity profiling (ERP) and ground penetrating radar (GPR) can be utilised to provide subsurface information that otherwise may not be possible if either one of the techniques is used. A model geometry consisting of a typical pavement structure (asphalt, base/subbase, and background soil) with a single 2 m pipe buried at a depth of 1 m was used. Strong lateral variations in soil type were incorporated over the short pipe section in order to understand the complexities that can arise, especially with ERP measurements. The 3D electrical resistivity measurements were simulated in Comsol using the 4-probe method, while the 2D GPR measurements were simulated in gprMax to obtain the subsurface information. The results from both ERP and GPR were used to develop a practical framework that can be utilised by relevant authorities for proximal condition assessment of their buried assets. It was suggested that ERP can be used as a first level screening tool over the whole pipeline length, followed by discretely selected GPR scans in order to further gain information on the pipe health. This is attractive practically since, following delineations of a large pipe section into shorter subsections, advanced condition assessment approaches that are generally intrusive in nature can then be economically deployed within the subsections suspected of experiencing significant corrosion damage.

Published
2022

45. Automated Segmentation Framework for Asphalt Layer Thickness from GPR Data Using a Cascaded k-Means - DBSCAN Algorithm

Author

Nikhil A Singh, Kaushal Kishore, Ravin N Deo, Ye Lu, and Jayantha Kodikara

Subjects
Geophysics, Environmental Engineering, Geotechnical Engineering and Engineering Geology
Abstract

Timely monitoring of pavement sub-surface layer thickness and condition evaluation is essential to ensure stable pavement performance and safety under heavy traffic loading. In addition, accurate estimation of pavement layer thicknesses is required for condition evaluation, overlay design/ quality control assurance, and structural capacity evaluation of existing pavements to predict its remaining service life. Traditionally this vital information is ascertained through coring/drilling and visual inspections. In contrast to these current techniques, ground-penetrating radar (GPR) is a non-destructive technique gaining popularity in pavement asphalt layer thickness estimation and structural condition monitoring. Its high-quality data contains vital pavement condition information, and survey costs are reasonably economic. In this work, GPR data were acquired along a toll road in Queensland, Australia, using the GSSI 4-channel SIR30 GPR unit. Asphalt layer thickness information is considered an important input parameter for condition assessment, pavement performance, and lifetime modelling. This work presents an automated segmentation framework to evaluate pavement conditions for a large pavement network. The developed algorithm uses GPR asphalt thickness data as input and generates segments with decision boundaries utilising a cascaded k-means and DBSCAN approach that works in two steps: 1) centroid initialisation using k-means algorithm, 2) clustering using DBSCAN algorithm. Presented in this paper is the workflow of the cascaded method that is applicable to automated analysis of GPR asphalt thickness data. The performance of the cascaded k-means and DBSCAN algorithm was evaluated in terms of entropy compared with traditional k-means and traditional DBSCAN algorithms. The results show that the proposed method outperforms its constituents. Based on the results of this study, the method presented in this paper is cost-effective, economical and robust for segmenting large pavement network with GPR data.

Published
2022

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