Stochastic Model for Damage Accumulation in Rubble-Mound Breakwaters Based on Compatibility Conditions and the Central Limit Theorem

Castillo, Carmen; Castillo, Enrique; Fernández‐Canteli, Alfonso; Molina, Rafael; Gómez, Rebeca

doi:10.1061/(asce)ww.1943-5460.0000146

Cited by 17 publications

(14 citation statements)

References 23 publications

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“… The stochastic nature of damage has been traditionally linked to a normal distribution. However, according to the suggestions from Castillo et al (2012), damage has been proven not to follow a normal distribution, but transformed damage D trans =(D-) 1/b does instead. Based on assumptions of general validity and with a comprehensive probabilistic approach, they proposed the DPPM of Eq.3 which permits, not only to predict the mean trend of damage progression, but also the whole PDF.…”

Section: Discussionmentioning

confidence: 99%

“…they did not provide the distribution of damage around a predicted mean value of the damage progression model. This fact, as well as some modeling difficulties reported by M&K (1999), motivated Castillo et al (2012) to make some suggestions on how to build consistent stochastic models avoiding the selection of easy-to-use mathematical functions, which were replaced by those resulting from a set of properties to be satisfied by the model. Contrary to other existing models that are built under a deterministic approach, the Cumulative Density Function (CDF) of Eq.3 was proposed after applying dimensional analysis (Buckingham  theorem), compatibility conditions and the central limit theorem.…”

Section: Introductionmentioning

confidence: 99%

“…Contrary to other existing models that are built under a deterministic approach, the Cumulative Density Function (CDF) of Eq.3 was proposed after applying dimensional analysis (Buckingham  theorem), compatibility conditions and the central limit theorem. The Damage Progression Probability Model of Castillo et al (2012), referred as DPPM herein, was developed under assumptions of general validity but their variables need to be calibrated for each specific case.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of the Influence of the Different Variables Involved in a Damage Progression Probability Model

Campos

Castillo

Molina

2014

Int. Conf. Coastal. Eng.

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Nowadays risk based designs as well as reliable maintenance strategies are essential when dealing with coastal structures. In that sense, the probability of failure due to hydraulic instability of the armor layer is one of the main issues in rubble mound breakwaters, and so is improving the knowledge on the deterioration rate of the armor layer. In 2012 Castillo et al. made some suggestions on how to build consistent stochastic damage models and proposed a comprehensive Damage Progression Probability Model (DPPM) with general validity, depending on a pair of parameters for each of the three major entities involved in the problem: structure, wave action and initial damage. Based on experimental data, two different calibrations of these parameters are accomplished in the present paper, allowing an initial evaluation of the specific influence of each entity in the model.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Analysis of the Influence of the Different Variables Involved in a Damage Progression Probability Model

Campos

Castillo

Molina

2014

Int. Conf. Coastal. Eng.

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“…Reference [12] even questions the reliability of tests conducted on prototypes of structures with the aim to simulate or predict the damage progression patterns. This criticism is based upon the multitude of factors making such prediction highly uncertain, and is further ascertained in [13] and [14].…”

Section: Estimating Future Deteriorationmentioning

confidence: 99%

“…Furthermore, a statistical approach for modelling damage progression on rubble-mound breakwaters is followed in [15] and [16], and was further extended in [14]; but again, this statistical approach is built upon the Damage Parameter "S" established in [9] and used since then in all literature featuring armor stability empirical formulae [17].…”

Section: Estimating Future Deteriorationmentioning

confidence: 99%

Integrated Simulation Model for Maintenance and Repair Optimisation for Rubble Mound Coastal Structures Using Markov Chains, Regression and Genetic Algorithms

Hakea

Abu-Samra

Hosny

et al. 2015

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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The significant increase in the world population living within close proximity to coastlines has assigned further importance to coastal protection structures. This importance has been even ascertained given the increasing risks posed by climate change. From this standpoint comes the importance of maintenance and repair strategies for coastal protection structures especially in low-lying coastal areas. This research provides an integrated model for the optimisation of maintenance and repair for rubble-mound breakwaters, revetments and groins under simulated climatic conditions. The model starts by establishing an Asset Inventory Database (AID), a Markov-Chain (MC) Deterioration Engine, and a Genetic Algorithm (GA) repair and maintenance Optimisation Engine. The AID includes the coastal structures within any particular study area, along with their design attributes and hydrodynamic data. The database divides coastal structures into structural reaches for ease of management. The MC deterioration engine predicts future condition of the structure based upon actual visual inspection results, while taking into account the single-time condition drop caused by seasonal storms. The GA Optimisation Engine includes a set of decisions that are triggered when the structure's Priority Index (PI) -a factor of the condition and the magnitude of failure impactattains the defined threshold. MC deterioration patterns are expressed using best-fit regression to enable the integration between MC's and the GA Optimisation Engine. The case study consists of a group of rubble-mound structures in Alexandria, Egypt. The Optimisation Engine simulates repair and maintenance scenarios for various climatic conditions at a preset PI threshold, and results are compared and discussed.

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Ripple and sandbar dynamics under mid-reflecting conditions with a porous vertical breakwater

Cobos

Chiapponi

Longo

et al. 2017

Coastal Engineering

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Stochastic Model for Damage Accumulation in Rubble-Mound Breakwaters Based on Compatibility Conditions and the Central Limit Theorem

Cited by 17 publications

References 23 publications

Analysis of the Influence of the Different Variables Involved in a Damage Progression Probability Model

Analysis of the Influence of the Different Variables Involved in a Damage Progression Probability Model

Integrated Simulation Model for Maintenance and Repair Optimisation for Rubble Mound Coastal Structures Using Markov Chains, Regression and Genetic Algorithms

Ripple and sandbar dynamics under mid-reflecting conditions with a porous vertical breakwater

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