Probabilistic models for the erosion rate in embankments and reliability analysis of earth dams

Andreini, Marco; Gardoni, Paolo; Pagliara, Stefano; Sassu, Mauro

doi:10.1016/j.ress.2018.09.023

Cited by 30 publications

(10 citation statements)

References 23 publications

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“…Focusing the attention in dam engineering field, the most interesting examples aim to determine the model parameters for the risk assessment of earth fill dams [31,32,33,34].…”

Section: Interpretation Of the Dam Structural Behaviour From Monitorimentioning

confidence: 99%

Concrete gravity dams model parameters updating using static measurements

Sevieri

Andreini

Falco

et al. 2019

Engineering Structures

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The structural control of concrete gravity dams is of primary importance. In this context, numerical models play a fundamental role both to assess the vulnerability of gravity dams and to control their behaviour during normal operativity and after extreme events. In this regard, data monitoring represents an important source of information for numerical model calibrations. This study proposes a novel probabilistic procedure, defined in the Bayesian framework, to calibrate the parameters of finite elements models of dams. To this aim, monitoring data and the results of material tests are used as reference information. The computational burden is reduced by using a new hybridpredictive model of the dam displacements. An application on an Italian dam shows the feasibility of the proposed procedure.

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“…Focusing the attention in dam engineering field, the most interesting examples aim to determine the model parameters for the risk assessment of earth fill dams [31,32,33,34].…”

Section: Interpretation Of the Dam Structural Behaviour From Monitorimentioning

confidence: 99%

Concrete gravity dams model parameters updating using static measurements

Sevieri

Andreini

Falco

et al. 2019

Engineering Structures

Self Cite

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“…Jin et al (2019) also reported that the GLCP raised the groundwater in their monitoring region, where more than 50% of the shallow soil samples (20 cm depth) suffered from light soil salinization. Equally, if the water in the GLCP does not drain for a long time the land may form a water outlet resulting in an unwanted piping effect, which poses a major threat to the safety of check‐dams (Andreini et al, 2019). In summary, we suggest that the GLCP construction can be strengthened in the arid gully regions to increase the farmland while enhancing soil moisture and relieving water supply pressure.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the impact of the Gully Land Consolidation Project on runoff under extreme rainfall

et al. 2022

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Extreme rainfall is an important driver of soil erosion and land damage. The Gully Land Consolidation program (GLCP) was first launched in 2011 as a major land reclamation practice to increase farmland in the Loess Plateau of China. Studying the impact of artificial projects on hydrology can help humans to respond to the various water issues, but the assessment of the effects of the GLCP on extreme rainfallinduced water runoff at watershed scale is currently lacking. Our study used the soil and water assessment tool (SWAT) to evaluate the influence of the GLCP at different locations and areas on water runoff under extreme rainfall events in the Yanhe watershed. Results showed that: (1) the GLCP can improve the interception of surface runoff, with interception efficiency in downstream of the watershed approximately twice that at midstream and entire watershed as well as seven-times that at the upstream; (2) when GLCP measures are evenly distributed in a watershed, as the area of GLCP increases from 76.40 km 2 (1% of watershed area) to 382.01 km 2 (5%), the interception of surface runoff increases by 0.77 mm; (3) and the GLCP can increase soil infiltration and groundwater recharge. This research is expected to provide insights into the optimized layout of the GLCP at watershed scale. Correspondingly, policymakers can refer to this information in developing policies on the sustainable use of land.

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“…L(θ|y) is the likelihood function that includes the information from the data vector y. f(θ|y) is the posterior probability distribution that reflects the updated state of information about the model parameter vector θ. κ is a normalizing factor as κ = ( L(θ|y) f (θ)dθ)) −1 . The detailed procedures for Bayesian updates are detailed in other literature [25,32]. Figure 3 shows the main procedure of the proposed method.…”

Section: Proposed Methodsmentioning

confidence: 99%

Efficient Seismic Fragility Analysis for Large-Scale Piping System Utilizing Bayesian Approach

Kwag

Ryu

2020

Applied Sciences

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In the event of an earthquake, it is essential to accurately assess the seismic fragility of piping systems to ensure the continued safety of society. When evaluating the seismic fragility of a piping system, which is generally a secondary structural system, this should mainly be an integrated model that includes both the primary structural frames and the secondary ones, unlike the primary structural system of a building. Hence, the piping seismic fragility evaluation has an issue in that it takes considerable computational time because numerical analyses must be performed on a relatively complex model. Given this background, the purpose of this study is to propose an efficient piping seismic fragility analysis method by utilizing the existing seismic fragility analysis method and the Bayesian updating concept. In order to verify the validity of the proposed method, it was applied to a building–piping coupled structural system example, and its results were analyzed and compared with the results of the existing method in terms of accuracy and efficiency. As a result, the proposed method showed a similar accuracy compared with the existing method while significantly reducing the numerical cost of nonlinear seismic response analyses necessary for these results.

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Probabilistic models for the erosion rate in embankments and reliability analysis of earth dams

Cited by 30 publications

References 23 publications

Concrete gravity dams model parameters updating using static measurements

Concrete gravity dams model parameters updating using static measurements

Evaluation of the impact of the Gully Land Consolidation Project on runoff under extreme rainfall

Efficient Seismic Fragility Analysis for Large-Scale Piping System Utilizing Bayesian Approach

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