Spatial-temporal reliability analysis of corroding cast iron water pipes

Aryai, Vahid; Mahmoodian, Mojtaba

doi:10.1016/j.engfailanal.2017.08.017

Cited by 16 publications

(7 citation statements)

References 21 publications

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“…Several discretization methods have been introduced in literature, 45 including the Karhunen–Loève (K–L) expansion method, 46 the orthogonal series expansion (OSE) method, 47 and the expansion optimal linear estimation (EOLE) method. 48 Both KL and EOLE can give good accuracy, and the EOLE method seems to be more efficient than the other discretization methods, 49 and it is then utilized in this paper. Let a stochastic process Y ( t ) possess a mean function μ Y ( t ), a standard deviation function σ Y ( t ), and autocorrelation functions ρ Y ( t i , t j ).…”

Section: Discretization Of Stochastic Processes and Random Fieldsmentioning

confidence: 99%

Temporal-spatial reliability analysis of RC bridges with corroded steel reinforcement bars

Chen

Wei

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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Corrosion of steel bars is one of the most significant causes of deterioration of reinforced concrete (RC) structures. The performance of RC structures is affected by many factors such as materials, environments, and load conditions, which usually possess uncertain features. Some of uncertainties may be time- and space-dependent, and the corresponding reliability problems become more challenging. To address these issues, this paper studies the temporal-spatial reliability analysis of RC bridges with corroded steel reinforcement bars. At first, a compound corrosion model is developed in which the combined effects of carbonation (general corrosion) and chloride penetration (pitting corrosion) are considered. In the reliability analysis, both the temporal and spatial variability are accounted through a stochastic process and a random field, respectively. An extended instantaneous response surface (t-IRS) method is then proposed to evaluate the temporal-spatial reliability. Unlike the original t-IRS method, in addition to the original variables, the random variables transformed from the random fields and the space variable are also used as the input variables of the extended surrogate model. When generating sample points, both the time variable and the space variable are treated as uniformly distributed random variables within given intervals. Finally, the proposed method is applied to a RC bridge example with corroded steel reinforcement bars and the results are compared with that of Monte Carlo simulation (MCS) method, demonstrating the effectiveness of the extended t-IRS method.

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Section: Discretization Of Stochastic Processes and Random Fieldsmentioning

confidence: 99%

Temporal-spatial reliability analysis of RC bridges with corroded steel reinforcement bars

Chen

Wei

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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“…For example, Shafei and Alipour (2015) The Karhunen-Loeve (KL) expansion is one of the most commonly used representation of stochastic fields. Recently, Zhao and Yun (2018) and Aryai and Mahmoodian (2017) used the KL expansion to model spatial random fields with regards to deterioration in a reinforced-concrete bridge slab and cast-iron pipes, respectively. Meanwhile, Na et.…”

Section: Random Field Modelling For Degradationmentioning

confidence: 99%

Probabilistic Modelling of Spatio-Temporal Uncertainties in Degradation

Adegbola¹,

Yuan²

2022

Preprint

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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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“…Many of the environmental parameters, such as soil characteristics would take different but correlated values at different locations of the farm. Existing reliability methods commonly model such uncertain spatially variable phenomena by using random fields ( Aryai and Mahmoodian, 2017 ; Stewart, 2012 ; Hajializadeh et al, 2016 ). In order to minimise the computational cost, the random fields are discretised first, and then the discretised fields are incorporated into the analysis.…”

Section: Reliability Analysis Of the Integrated Systemmentioning

confidence: 99%

“…Other methods such as LH, SS and IS can be incorporated to decrease the computational burden of MCS. ( Aryai and Mahmoodian, 2017 ; Fu et al, 2018 ; Graf et al, 2018 ; Leheta et al, 2017 ) Transformation/Approximation Methods Approximate the failure domain mainly using first or higher order Taylor expansion at the design point. FORM, SORM and Response Surface Method (RSM) Easy to implement and computationally efficient.…”

Section: Reliability Analysis Of the Integrated Systemmentioning

confidence: 99%

Reliability of multi-purpose offshore-facilities: Present status and future direction in Australia

Aryai

Abdussamie

Salehi

et al. 2021

Process Safety and Environmental Protection

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Sustainable use of the ocean for food and energy production is an emerging area of research in different countries around the world. This goal is pursued by the Australian aquaculture, offshore engineering and renewable energy industries, research organisations and the government through the “Blue Economy Cooperative Research Centre”. To address the challenges of offshore food and energy production, leveraging the benefits of co-location, vertical integration, infrastructure and shared services, will be enabled through the development of novel Multi-Purpose Offshore-Platforms (MPOP). The structural integrity of the designed systems when being deployed in the harsh offshore environment is one of the main challenges in developing the MPOPs. Employing structural reliability analysis methods for assessing the structural safety of the novel aquaculture-MPOPs comes with different limitations. This review aims at shedding light on these limitations and discusses the current status and future directions for structural reliability analysis of a novel aquaculture-MPOP considering Australia’s unique environment. To achieve this aim, challenges which exist at different stages of reliability assessment, from data collection and uncertainty quantification to load and structural modelling and reliability analysis implementation, are discussed. Furthermore, several solutions to these challenges are proposed based on the existing knowledge in other sectors, and particularly from the offshore oil and gas industry. Based on the identified gaps in the review process, potential areas for future research are introduced to enable a safer and more reliable operation of the MPOPs.

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Spatial-temporal reliability analysis of corroding cast iron water pipes

Cited by 16 publications

References 21 publications

Temporal-spatial reliability analysis of RC bridges with corroded steel reinforcement bars

Temporal-spatial reliability analysis of RC bridges with corroded steel reinforcement bars

Probabilistic Modelling of Spatio-Temporal Uncertainties in Degradation

Reliability of multi-purpose offshore-facilities: Present status and future direction in Australia

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