Classification and spatial mapping of atmospheric corrosion of China

Hao, Wenkui; Xu, Lingling; Chen, Xin; Jin, Yan; Han, Yu; Zhang, Xinghui; Chen, Yun; Huang, Luyao; Yang, Bingkun; Zhu, Zhixiang; Wang, Xiaofang

doi:10.1038/s41529-022-00315-4

Cited by 8 publications

(3 citation statements)

References 39 publications

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“…As shown in Figure 13 , we employ three typical interpolation algorithms for calculating test pit data across the full-section: Inverse Distance Weighting (IDW) [ 67 ], Spline function interpolation (Spline) [ 68 ], and Kriging interpolation [ 69 ]. In the process of developing the interpolation model, cross-validation [ 70 ] is used to assess the interpolation accuracy and determine the optimal interpolation algorithm. Moreover, the optimal interpolation algorithm provides data support for subsequent calculation of the full-section distribution interval for ρ d max and assessments of full-section compaction quality.…”

Section: Methodsmentioning

confidence: 99%

A Novel Method for Full-Section Assessment of High-Speed Railway Subgrade Compaction Quality Based on ML-Interval Prediction Theory

Deng,

Wang,

et al. 2024

Sensors

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The high-speed railway subgrade compaction quality is controlled by the compaction degree (K), with the maximum dry density (ρdmax) serving as a crucial indicator for its calculation. The current mechanisms and methods for determining the ρdmax still suffer from uncertainties, inefficiencies, and lack of intelligence. These deficiencies can lead to insufficient assessments for the high-speed railway subgrade compaction quality, further impacting the operational safety of high-speed railways. In this paper, a novel method for full-section assessment of high-speed railway subgrade compaction quality based on ML-interval prediction theory is proposed. Firstly, based on indoor vibration compaction tests, a method for determining the ρdmax based on the dynamic stiffness Krb turning point is proposed. Secondly, the Pso-OptimalML-Adaboost (POA) model for predicting ρdmax is determined based on three typical machine learning (ML) algorithms, which are back propagation neural network (BPNN), support vector regression (SVR), and random forest (RF). Thirdly, the interval prediction theory is introduced to quantify the uncertainty in ρdmax prediction. Finally, based on the Bootstrap-POA-ANN interval prediction model and spatial interpolation algorithms, the interval distribution of ρdmax across the full-section can be determined, and a model for full-section assessment of compaction quality is developed based on the compaction standard (95%). Moreover, the proposed method is applied to determine the optimal compaction thicknesses (H0), within the station subgrade test section in the southwest region. The results indicate that: (1) The PSO-BPNN-AdaBoost model performs better in the accuracy and error metrics, which is selected as the POA model for predicting ρdmax. (2) The Bootstrap-POA-ANN interval prediction model for ρdmax can construct clear and reliable prediction intervals. (3) The model for full-section assessment of compaction quality can provide the full-section distribution interval for K. Comparing the H0 of 50~60 cm and 60~70 cm, the compaction quality is better with the H0 of 40~50 cm. The research findings can provide effective techniques for assessing the compaction quality of high-speed railway subgrades.

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Section: Methodsmentioning

confidence: 99%

A Novel Method for Full-Section Assessment of High-Speed Railway Subgrade Compaction Quality Based on ML-Interval Prediction Theory

Deng,

Wang,

et al. 2024

Sensors

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“…For practical purposes, the correct assessment of the atmosphere corrosivity category [31] is of greater importance than the accuracy of corrosion rate prediction, since for each category, designers provide for the thickness of the metal of products, methods, and means of protection and preservation, estimate their durability, etc. Without corrosion testing, K 1 can be calculated using dose-response functions (DRFs).…”

Section: Accessing the Atmosphere Corrosivity Categoriesmentioning

confidence: 99%

Corrosion Resistance of Zinc and Zinc-Aluminum-Magnesium Coatings in Atmosphere on the Territory of Russia

et al. 2023

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Zinc-coated carbon steel is commonly used in the construction of buildings, infrastructure objects such as roads and bridges, automotive production, etc. Coatings based on zinc-aluminum-magnesium alloys that may have better corrosion resistance than zinc have been developed. The coatings made of the new alloys have been available on the market for a shorter period of time than conventional zinc coatings. This paper presents data on the corrosion resistance of zinc and zinc-aluminum-magnesium coatings on carbon steel obtained by tests in four locations in Russia with marine and non-marine atmospheres. Four one-year exposures at the beginning of each season and two-year tests were performed. It is shown that the corrosion resistance of the coatings depends significantly on the beginning of the exposure. The categories of atmosphere corrosivity in relation to the coatings were determined at each location. Based on the dose–response function (DRF) for zinc developed for the territory of Russia, DRFs for the coatings were obtained. A match between the categories of atmosphere corrosivity determined by the first-year corrosion losses and estimated from the values of corrosion losses calculated using the DRF is shown. Based on the data of two-year tests, the variation in the corrosion rate over time is obtained. The corrosion rates of the coatings in the territory of Russia are compared to the corrosion rates of coatings observed in various locations around the world. An approximate estimate of the service life of the coatings at the test sites is given.

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“…Consequently, redox (i.e., reduction and oxidation) reactions are triggered and solid mineral precipitations occur. To date, various investigations have looked into the parameters that influence the electrochemical mineral precipitation in seawater, including current density, [13,19] applied potential, [20][21][22][23][24][25] seawater chemistry, [26] salinity, [20] temperature, [20,21,27,28] depth, [20] and mass transport. [20,21,25] Studies have shown that the applied electrochemical potential strongly influences the composition and morphology of calcareous deposits in seawater.…”

Section: Introductionmentioning

confidence: 99%

Mechanistic Insights into Electrodeposition in Seawater at Variable Electrochemical Potentials

Devi,

Wagner,

Lopez

et al. 2023

Advanced Sustainable Systems

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The classical approach to manufacturing cement and concrete involves considerable and energy‐intensive exploitation of minerals from the environment, calling for alternative and sustainable methods to obtain such resources. Electrodeposition resulting from local pH changes near an oxygen or water reduction electrode can be used to grow valuable minerals in seawater for use in the cement and concrete industries, with the potential to use clean electricity without relying on the mining of resources. Limited knowledge is available about the electrochemical reaction networks that yield mineral precipitates via electrodeposition in seawater, hindering a complete assessment of the promise of such an approach to serving the construction industry. This work presents an investigation of the electrodeposition in seawater as a function of the applied potential. The work identifies multiple electrochemical potential regimes that yield distinct polymorphs, quantities, and production rates of calcium and magnesium‐based minerals due to the varying rates of oxygen reduction and water‐splitting reactions. The quality of the produced minerals is comparable to that of traditionally mined aggregates in terms of morphology and composition, supporting that seawater represents a vast source of raw materials for use in the construction industry upon an enhancement in the efficiency of hydroxide‐producing reactions and the reactor design.

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Classification and spatial mapping of atmospheric corrosion of China

Cited by 8 publications

References 39 publications

A Novel Method for Full-Section Assessment of High-Speed Railway Subgrade Compaction Quality Based on ML-Interval Prediction Theory

A Novel Method for Full-Section Assessment of High-Speed Railway Subgrade Compaction Quality Based on ML-Interval Prediction Theory

Corrosion Resistance of Zinc and Zinc-Aluminum-Magnesium Coatings in Atmosphere on the Territory of Russia

Mechanistic Insights into Electrodeposition in Seawater at Variable Electrochemical Potentials

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