An age- and state-dependent Markov model for degradation processes

Giorgio, Massimiliano; Guida, Maurizio; Pulcini, Gianpaolo

doi:10.1080/0740817x.2010.532855

Cited by 91 publications

(54 citation statements)

References 16 publications

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“…Conditional on those values of k and T 0 , the MLE for (c * 1 , c * 2 ) is given by (0.63 · 10 −4 , 1.2 · 10 −4 ). In the right panel, the corresponding 90% confidence band is shown, which is very similar to the one obtained in [8], but we use a more parsimonious model for the wearing process. computed using the upscaled models, but fitted using the ME, which acts directly in the microscopic base model (3.1).…”

Section: Numerical Resultssupporting

confidence: 60%

“…Let X(t) be the thickness process derived from the wear of the cylinder liners up to time t (see [7,8]), i.e., X(t) = T 0 − W (t), where W is the wear process and T 0 is the initial thickness. We model X(t) as a sum of two simple decay processes (see Example 2.1) with Δ = 0.05 (which is the resolution of the measurement instrument), since one simple decay process is not enough to explain the variance of the data.…”

Section: The Thickness Measurement Processmentioning

confidence: 99%

“…The stochastic modeling of the wear degradation of cylinder liners is extensively treated in [5,6,7,8] and the references therein. This wear process, at some point, will cause failure if no maintenance program is utilized.…”

Section: Introductionmentioning

confidence: 99%

“…The data set, w = {w i } n i=1 , taken from [8], consists of wear levels observed on 397 n = 32 cylinder liners of eight-cylinder SULZER engines as measured by a caliper with a precision of 0.05 mm. Warranty clauses specify that, to avoid failures, the liner should be changed before it accumulates a wear level of 4.0 mm.…”

Section: Introductionmentioning

confidence: 99%

“…The resulting fitting with this approach is poor and the authors do not proceed further in this direction. In [8], a state-dependent, inhomogeneous in time Markov chain is proposed. The authors use a similar inference strategy by discretizing time and space.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Multiscale Modeling of Wear Degradation in Cylinder Liners

Moraes

Ruggeri

Tempone

et al. 2014

Multiscale Model. Simul.

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Abstract. Every mechanical system is naturally subjected to some kind of wear process that, at some point, will cause failure in the system if no monitoring or treatment process is applied. Since failures often lead to high economical costs, it is essential both to predict and to avoid them. To achieve this, a monitoring system of the wear level should be implemented to decrease the risk of failure. In this work, we take a first step into the development of a multiscale indirect inference methodology for state-dependent Markovian pure jump processes. This allows us to model the evolution of the wear level and to identify when the system reaches some critical level that triggers a maintenance response. Since the likelihood function of a discretely observed pure jump process does not have an expression that is simple enough for standard nonsampling optimization methods, we approximate this likelihood by expressions from upscaled models of the data. We use the Master Equation (ME) to assess the goodness-of-fit and to compute the distribution of the hitting time to the critical level.

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Section: Numerical Resultssupporting

confidence: 60%

Section: The Thickness Measurement Processmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Multiscale Modeling of Wear Degradation in Cylinder Liners

Moraes

Ruggeri

Tempone

et al. 2014

Multiscale Model. Simul.

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Closed‐form aftershock reliability of damage‐cumulating elastic‐perfectly‐plastic systems

Iervolino

Giorgio²,

Chioccarelli

2013

Earthq Engng Struct Dyn

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Major earthquakes (i.e., mainshocks) typically trigger a sequence of lower magnitude events clustered both in time and space. Recent advances of seismic hazard analysis stochastically model aftershock occurrence (given the main event) as a nonhomogeneous Poisson process with rate that decays in time as a negative power law. Risk management in the post-event emergency phase has to deal with this short-term seismicity. In fact, because the structural systems of interest might have suffered some damage in the mainshock, possibly worsened by damaging aftershocks, the failure risk may be large until the intensity of the sequence reduces or the structure is repaired. At the state-of-the-art, the quantitative assessment of aftershock risk is aimed at building tagging, that is, to regulate occupancy. The study, on the basis of age-dependent stochastic processes, derived closed-form approximations for the aftershock reliability of simple nonevolutionary elastic-perfectly-plastic damage-cumulating systems, conditional on different information about the structure. Results show that, in the case hypotheses apply, the developed models may represent a basis for handy tools enabling risk-informed tagging by stakeholders and decision makers

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Markovian modeling of seismic damage accumulation

Iervolino

Giorgio²,

Chioccarelli

2015

Earthq Engng Struct Dyn

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SUMMARYAnalysis of civil structures at the scale of life-cycle requires stochastic modeling of degradation. Phenomena causing structures to degrade are typically categorized as aging and point-in-time overloads. Earthquake effects are the members of the latter category this study deals with in the framework of performance-based earthquake engineering (PBEE). The focus is structural seismic reliability, which requires modeling of the stochastic process describing damage progression, because of subsequent events, over time. The presented study explicitly addresses this issue via a Markov-chain-based approach, which is able to account for the change in seismic response of damaged structures (i.e. state-dependent seismic fragility) as well as uncertainty in occurrence and intensity of earthquakes (i.e. seismic hazard). The state-dependent vulnerability issue arises when the seismic hysteretic response is evolutionary and/or when the damage measure employed is such that the degradation increment probabilistically depends on the conditions of the structure at the time of the shock. The framework set up takes advantage also of the hypotheses of classical probabilistic seismic hazard analysis, allowing to separate the modeling of the process of occurrence of seismic shocks and the effect they produce on the structure. It is also discussed how the reliability assessment, which is in closed-form, may be virtually extended to describe a generic age-and state-dependent degradation process (e.g. including aging and/or when aftershock risk is of interest). Illustrative applications show the options to calibrate the model and its potential in the context of PBEE.

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An age- and state-dependent Markov model for degradation processes

Cited by 91 publications

References 16 publications

Multiscale Modeling of Wear Degradation in Cylinder Liners

Multiscale Modeling of Wear Degradation in Cylinder Liners

Closed‐form aftershock reliability of damage‐cumulating elastic‐perfectly‐plastic systems

Markovian modeling of seismic damage accumulation

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