A Dynamic Bayesian Network framework for spatial deterioration modelling and reliability updating of timber structures subjected to decay

Tran, Thanh; Bastidas‐Arteaga, Emilio; Aoues, Younès

doi:10.1016/j.engstruct.2020.110301

Cited by 21 publications

(8 citation statements)

References 30 publications

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“…The proposed methodology is based on the Bayesian network (BN) approach, which is a probabilistic tool that could be used to identify parameters by integrating experimental data. The Bayesian approach has already been used to update/identify the parameters of chlorination models, and to assess/update the reliability of concrete [27,28] or timber [29,30] structures. However, it has not been used to estimate the effects of mechanical loading on the chloride ingress mechanism by using experimental data.…”

Section: Introductionmentioning

confidence: 99%

Bayesian Assessment of the Effects of Cyclic Loads on the Chloride Ingress Process into Reinforced Concrete

et al. 2020

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Chloride-induced corrosion and load induced concrete cracking affect the serviceability and safety of reinforced concrete (RC) structures. Once these phenomena occur simultaneously, the prediction of RC structures’ lifetimes becomes a major challenge. The objective of this paper is to propose a methodology to evaluate the effect of loading and cracking on the mechanism of chloride ion penetration in concrete. The proposed methodology will be based on Bayesian networks. Bayesian networks are useful to update the lifetime assessment based on experimental data as well as to characterize the uncertainties of the input parameters of a chlorination model including a chloride diffusion acceleration factor. The proposed methodology is illustrated with experimental data coming from tests on RC beams subjected to static and cyclic loading before being in contact with a solution containing chloride ions. The characterized parameters are then used to evaluate the effect of these two loading conditions (static and cyclic) on the corrosion initiation time and the corrosion initiation probability. The results obtained indicate that the proposed methodology is capable of integrating loading and chlorination test data for the determination of the probabilistic parameters of a model in a comprehensive way.

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Section: Introductionmentioning

confidence: 99%

Bayesian Assessment of the Effects of Cyclic Loads on the Chloride Ingress Process into Reinforced Concrete

et al. 2020

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“…In addition, the proposed methodology will be applied to other tropical and tempered species. These data and models will ultimately be used for the evaluation and updating of reliability of timber structures by considering spatial variability [27].…”

Section: Discussionmentioning

confidence: 99%

“…A specific procedure to correct these scale effects was proposed by the authors; this fact should be accounted for when the size of the specimen is very small in comparison to the correlation length. Tran et al [27] proposed a framework based on Bayesian networks to study the effect of the spatial variability of decay on the durability of timber beams. This framework could be used to evaluate the durability condition of the beam using partial observations; however, the spatial variability of mechanical properties was not considered in this work.…”

Section: Introductionmentioning

confidence: 99%

Spatial Variability of Ozigo Wood Beams under Long-Term Loadings in Various Environmental Exposures

et al. 2021

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Timber is a renewable material that should be more used for sustainable construction. While the mechanical behavior and durability of some species have been widely studied in the past, few studies are available for the Ozigo (Dacryodes buettneri) specie. This paper deals with the spatial variability of Ozigo beams subjected to long-term loadings and different environmental conditions. These beams were previously subjected to long-term creep in three environments (air-conditioned, unsheltered, and sheltered) at Masuku in the south-east of Gabon. Various specimens were extracted from these beams to determine its moisture content and subjected to three-point bending tests to obtain the modulus of elasticity and failure stress at various points in the space. The results obtained showed that, after long-term loadings, environmental exposure combined with mechanical loading, play a key role in the mechanical properties of the timber beams. A reduction of strength was found for the specimens extracted from the unsheltered and sheltered outdoor exposures in comparison with those extracted from the air-conditioned exposure. Concerning the spatial variability, statistical tests confirm that there is significant spatial correlation. It was also found that the spatial variation of properties in the beam is not stationary because it was affected by loading and support conditions.

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“…Zheng et al [40] presented an improved compression inference algorithm in multilevel BN to analyze the reliability of complex multistate satellite systems. A dynamic BN was also proposed to assess and update the reliability of timber structures exposed to deterioration processes based on inspection data [41]. Therefore, system level lifetime prediction based on a BN is very important to achieve a reasonable integration of performance data from constituting components for a complex system/product.…”

Section: Introductionmentioning

confidence: 99%

System level reliability assessment for high power light-emitting diode lamp based on a Bayesian network method

et al. 2021

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The increased system complexity in electronic products brings challenges in a system level reliability assessment and lifetime estimation. Traditionally, the graph model-based reliability block diagrams (RBD) and fault tree analysis (FTA) have been used to assess the reliability of products and systems. However, these methods are based on deterministic relationships between components that introduce prediction inaccuracy. To fill the gap, a Bayesian Network (BN) method is introduced that considers the intricacies of the high-power light-emitting diode (LED) lamp system and the functional interaction among components for reliability assessment and lifetime prediction. An accelerated degradation test was conducted to analyze the evolution of the degradation and failure of components that influence the system level lifetime and performance of LED lamps. The Gamma process and Weibull distribution are used for component level lifetime prediction. The junction tree algorithm was deployed in the BN structure to estimate the joint probability distributions of the lifetime states. The degradation and prediction results showed that LED modules contribute a major part for lumen degradation of LED lamps followed by drivers and the least effect is from diffuser and reflector. The BN based lifetime estimation results also exhibited an accurate prediction as validated with the Gamma process and such improved reliability assessment outcomes are beneficial to LED manufacturers and customers. Thus, the proposed approach is effective to evaluate and address the long-term reliability assessment concerns of high-reliability LED lamps and fulfill the guarantee of high prediction accuracy in less time and cost-effective manner.

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A Dynamic Bayesian Network framework for spatial deterioration modelling and reliability updating of timber structures subjected to decay

Cited by 21 publications

References 30 publications

Bayesian Assessment of the Effects of Cyclic Loads on the Chloride Ingress Process into Reinforced Concrete

Bayesian Assessment of the Effects of Cyclic Loads on the Chloride Ingress Process into Reinforced Concrete

Spatial Variability of Ozigo Wood Beams under Long-Term Loadings in Various Environmental Exposures

System level reliability assessment for high power light-emitting diode lamp based on a Bayesian network method

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