Telemetry techniques for continuous monitoring of partially submerged large civil infrastructure

Alexander, Quincy G.; Thurmer, Clayton R.; Netchaev, Anton; Smith, Matthew D.; Klein, Jordan D.

doi:10.1117/12.2298413

Cited by 6 publications

(3 citation statements)

References 4 publications

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“…Navigation locks form a crucial part of inland waterways infrastructure network. Miter gates are the most common type of navigation locks in the United States (US) with other types of lock gates being sector, tainter, and vertical lift [1]. Miter gates are steel structures that allow passage of ships, boats, and watercrafts across stretches of different water levels in canals and rivers.…”

Section: Introductionmentioning

confidence: 99%

Efficient Bayesian Inference of Miter Gates Using High-Fidelity Models

Vega

Ramancha

Conte

et al. 2020

Model Validation and Uncertainty Quantification, Volume 3

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Continuous monitoring of miter gates used in navigation locks is desirable in order to prioritize maintenance and avoid unexpected failures. Substantial economic losses to the marine cargo and associated industries are caused by the closure of these inland waterway structures. Strain gauges are often installed in many of these miter gates for data collection, and various inverse finite element techniques are used to convert the strain gauges data to damage-sensitive features. One of the damage features is the development of a contact-loss "gap" between the components (i.e. quoin blocks) that support the gate laterally, which leads to load re-distribution that can induce overload in some components of the gate. Arguably, a refined finite element model of such structure can be very computationally expensive even when using linear models. An efficient way to solve an inverse problem with time-consuming model evaluations is making use of parallel model evaluations using a Sequential Monte Carlo (SMC) algorithm and parallel solution of the finite element (FE) equations using a commercial FE software. A significant advantage of SMC algorithms is that model evaluations are independent and are able to be run in parallel. In this paper, an expensive high fidelity model of a miter gate is used to infer the gap extend given a noisy set of strain measurements.

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Section: Introductionmentioning

confidence: 99%

Efficient Bayesian Inference of Miter Gates Using High-Fidelity Models

Vega

Ramancha

Conte

et al. 2020

Model Validation and Uncertainty Quantification, Volume 3

View full text Add to dashboard Cite

show abstract

“…Knowing the condition of a lock gate and its components can allow to take preventive measures to avoid or minimize the loss in unscheduled closures. Miter gates are the most common type in the United States with other types of lock gates being sector, tainter and vertical lift [4].…”

Section: Introductionmentioning

confidence: 99%

A Neural Network Surrogate Model for Structural Health Monitoring of Miter Gates in Navigation Locks

Vega

Madarshahian

Todd

2019

Model Validation and Uncertainty Quantification, Volume 3

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Structural health monitoring (SHM) of miter gates of navigation locks is crucial for facilitating cargo ship navigation. Closure of these inland waterway structures causes considerable economical loss to the marine cargo and associated industries. In practice, strain gauges are often mounted in many of these miter gates for data collection, and various inverse finite element techniques are used to convert the strain gauges data to damage-sensitive features. Arguably, these models are computationally expensive and sometimes they are not suitable for real-time health monitoring or for monitoring confounding environmental effects. In this work, a Muti-Layer Artificial Neural Network (MANN) is designed to serve as a "run time" surrogate model that links data (from the strain gages) to damage classification (gaps in the miter gate contact). Three cases of complexity, combining hydrostatic and thermal loading scenarios with varying gap scenarios, are considered to design the MANN. A confusion matrix is used to evaluate the performance of the networks and derive probabilities. Results show the potential of MANNs as a reliable surrogate model for computationally expensive inverse finite element modeling in damage classification for this application.

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“…According to Foltz [2], more than half of these assets have surpassed their economic design life, 50 years, and need frequent inspections to ensure their safe and reliable operation. Miter gates are the most common type in the United States among other designs including sector, tainter, and vertical lift [3]. Damage to critical components in miter gates may lead to closures of the lock chamber, which produce substantial economic losses on the marine cargo industry and their commercial clients.…”

Section: Introductionmentioning

confidence: 99%