A Review of Candu Feeder Wall Thinning

Chung, Han Sub

doi:10.5516/net.2010.42.5.568

“…FAC is a type of steel corrosion exacerbated by coolant flow in feeder pipes at high velocities and temperatures. Factors known to affect the rate of FAC include mass transfer, coolant flow velocity, pipe material composition in terms of chromium content, stress levels such as temperature and pressure, bend angle, coolant pH and oxidizing species (Duan et al 2009;Chung 2010;Lee et. al.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Modelling of Spatio-Temporal Uncertainties in Degradation

Adegbola¹,

Yuan²

2022

Preprint

0

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Deterioration is a major problem facing engineering structures, systems and components (SSCs). To maintain the structural integrity and safe operation of such SSCs all through their service life, it is important to understand how degradation phenomena progress over time and space. Hence degradation modelling has been increasingly used to model existing deterioration, predict future deterioration as well as provide input for infrastructure management in terms of inspection and maintenance decision making. As deterioration is known to be random, modelling of spatial and temporal uncertainty remains a crucial challenge for infrastructure asset professionals. The main objective of the thesis is to develop sophisticated models for characterizing spatial and temporal uncertainties in deterioration modelling with a view to enhancing decision making under uncertainty. The thesis proposes a two-dimensional copula-based gamma distributed random field for the spatial uncertainties, and a copula-based multivariate gamma process model to characterize stochastic dependence of multiple degradation phenomena. Techniques for estimating the model parameters and simulating the field or process, prediction of the remaining lifetime distribution as well as condition-based maintenance optimization are also presented. To study the extreme value distribution of the random field, the thesis also presents a numerical method based on the Karhunen-Loève expansion for evaluating extrema of both one- and two-dimensional homogeneous random fields. The simulation results are benchmarked against existing analytical models for special cases. In addition, the study also investigates the effect of parameter (epistemic) uncertainty on the extreme value distribution of the field. Finally, the thesis presents a practical application of the proposed copula-based gamma field by treating the wall profile of a feeder pipe as one- and twodimensional gamma fields. The thesis demonstrates a practical application of the multivariate gamma process model to rutting, cracking, and surface roughness of highway pavements. In summary, the proposed models have advanced the knowledge and techniques of stochastic deterioration modelling in the engineering field.

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“…FAC is a type of steel corrosion exacerbated by coolant flow in feeder pipes at high velocities and temperatures. Factors known to affect the rate of FAC include mass transfer, coolant flow velocity, pipe material composition in terms of chromium content, stress levels such as temperature and pressure, bend angle, coolant pH and oxidizing species (Duan et al 2009;Chung 2010;Lee et. al.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Modelling of Spatio-Temporal Uncertainties in Degradation

Adegbola¹,

Yuan²

2022

Preprint

0

View full text Add to dashboard Cite

Deterioration is a major problem facing engineering structures, systems and components (SSCs). To maintain the structural integrity and safe operation of such SSCs all through their service life, it is important to understand how degradation phenomena progress over time and space. Hence degradation modelling has been increasingly used to model existing deterioration, predict future deterioration as well as provide input for infrastructure management in terms of inspection and maintenance decision making. As deterioration is known to be random, modelling of spatial and temporal uncertainty remains a crucial challenge for infrastructure asset professionals. The main objective of the thesis is to develop sophisticated models for characterizing spatial and temporal uncertainties in deterioration modelling with a view to enhancing decision making under uncertainty. The thesis proposes a two-dimensional copula-based gamma distributed random field for the spatial uncertainties, and a copula-based multivariate gamma process model to characterize stochastic dependence of multiple degradation phenomena. Techniques for estimating the model parameters and simulating the field or process, prediction of the remaining lifetime distribution as well as condition-based maintenance optimization are also presented. To study the extreme value distribution of the random field, the thesis also presents a numerical method based on the Karhunen-Loève expansion for evaluating extrema of both one- and two-dimensional homogeneous random fields. The simulation results are benchmarked against existing analytical models for special cases. In addition, the study also investigates the effect of parameter (epistemic) uncertainty on the extreme value distribution of the field. Finally, the thesis presents a practical application of the proposed copula-based gamma field by treating the wall profile of a feeder pipe as one- and twodimensional gamma fields. The thesis demonstrates a practical application of the multivariate gamma process model to rutting, cracking, and surface roughness of highway pavements. In summary, the proposed models have advanced the knowledge and techniques of stochastic deterioration modelling in the engineering field.

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“…Because pipe wall thinning due to FAC is very slow (a few tens of μm per one year), it is necessary to monitor the piping walls for delamination, cracks and leaks as well as the piping thickness with very high accuracy. This is one of the important issues in the structural stability of a system, which requires continuous monitoring [1,2,3,4,5]. Presently, an ultrasonic method is used, which is one of the nondestructive inspection techniques for measuring the piping wall thickness.…”

Section: Introductionmentioning

confidence: 99%

On-Line Monitoring of Pipe Wall Thinning by a High Temperature Ultrasonic Waveguide System at the Flow Accelerated Corrosion Proof Facility

Oh

¹

,

Cheong

²

,

Kim

³

et al. 2019

Sensors

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Pipe wall thinning and leakage due to flow accelerated corrosion (FAC) are important safety concerns for nuclear power plants. A shear horizontal ultrasonic pitch/catch technique was developed for the accurate monitoring of the pipe wall-thickness. A solid couplant should be used to ensure high quality ultrasonic signals for a long operation time at an elevated temperature. We developed a high temperature ultrasonic thickness monitoring method using a pair of shear horizontal transducers and waveguide strips. A computer program for on-line monitoring of the pipe thickness at high temperature was also developed. Both a conventional buffer rod pulse-echo type and a developed shear horizontal ultrasonic waveguide type for a high temperature thickness monitoring system were successfully installed to test a section of the FAC proof test facility. The overall measurement error was estimated as ±15 μm during a cycle ranging from room temperature to 150 °C. The developed waveguide system was stable for about 3300 h and sensitive to changes in the internal flow velocity. This system can be used for high temperature thickness monitoring in all industries as well as nuclear power plants.

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A Review of Candu Feeder Wall Thinning

Cited by 10 publications

References 6 publications

Probabilistic Modelling of Spatio-Temporal Uncertainties in Degradation

Probabilistic Modelling of Spatio-Temporal Uncertainties in Degradation

Probabilistic Modelling of Spatio-Temporal Uncertainties in Degradation

On-Line Monitoring of Pipe Wall Thinning by a High Temperature Ultrasonic Waveguide System at the Flow Accelerated Corrosion Proof Facility

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