Erodibility Factor Research Articles

Time-series prediction of steel corrosion in concrete using recurrent neural networks

ABSTRACT Steel corrosion is a time-series problem where the current corrosion state is influenced by past corrosion and environmental factors. Most models incorporate time as a variable but fail to comprehensively consider past states and spatial-temporal factors. This study collects continuously monitored corrosion data from the literature and develops time-variant corrosion rate prediction models using traditional machine learning (TML) and recurrent neural networks (RNN). The TML model captures temporal variations, while the RNN model incorporates past and current corrosion factors, focusing on different lookback lengths. Empirical and electrochemical models are also compared to evaluate efficacy. The results indicate superior predictive capabilities for bothTML and RNN models. The TML model yields an RMSE of 0.26 μA/cm2 and a MAPE of 11.27%, while the RNN model achieves 0.22 μA/cm2 and 8.15%. In contrast, empirical and electrochemical models yield suboptimal RMSE (1.48 μA/cm2, 0.53 μA/cm2) and MAPE (77.31%, 35.05%). Analysis of Simple-RNN and LSTM models, reveals optimal performance when considering corrosion factors from the preceding two-time intervals. These results underscore the importance of incorporating past corrosion factors and demonstrate the enhanced efficacy of data-driven approaches, particularly LSTM, over traditional models.

Soil Erosion Assessment Using the RUSLE Model and Geospatial Techniques (Remote Sensing and GIS) in Kalyani River Watershed of Uttar Pradesh, India

Soil erosion significantly impacts environmental sustainability, agriculture, and water quality. This study examines soil erosion in the Kalyani River within the Nindoora and Fatehpur blocks of Barabanki District, Uttar Pradesh, India, where seasonal fluctuations and steep banks exacerbate the issue. The region experiences severe soil degradation due to uncontrolled land use, deforestation, over-cultivation, overgrazing, and biomass exploitation driven by population growth. To address this, GIS and Remote Sensing technologies were utilized, employing the Revised Universal Soil Loss Equation (RUSLE) model to identify erosion-prone areas. The RUSLE model involves calculating parameters such as the runoff-rainfall erosivity factor (R), soil erodibility factor (K), topographic factor (LS), cropping management factor (C), and support practice factor (P). Layer-wise thematic maps of each factor were generated using a GIS platform, incorporating various data sources and preparation methods. The study's results indicate that value of K factor is found to be 0.025 indicates that the soil is relatively resistant to erosion. Higher LS factor values are scattered across the area, especially near the Kalyani River. The southeastern regions show higher C factor values, indicating less effective soil cover and management against erosion. It has also been estimated that 90% of the Kalyani River watershed faces low soil erosion risk (0–10 ton/ha/yr), while 0.20% primarily near riverbanks experiences high to very high erosion risk (10–40 ton/ha/yr). Sandy and sandy loam soils near riverbanks, exacerbated by seasonal water level fluctuations and steep slopes, are highly prone to erosion. The RUSLE-based GIS approach allowed for the precise identification of erosion hotspots, facilitating the development of targeted soil conservation strategies to mitigate soil degradation and promote sustainable land management.

Relationship Between Laryngopharyngeal Reflux, Gastroesophageal Reflux Disease, and Dental Erosion in Adult Populations: A Systematic Review.

As one of the most common complications of laryngopharyngeal reflux or gastroesophageal reflux disease, dental erosion presents a significant association with laryngopharyngeal reflux. This study aimed to elucidate the role of laryngopharyngeal reflux and gastroesophageal reflux disease on the severity and occurrence of dental erosion in adult populations. A comprehensive search was performed in the databases of PubMed/MEDLINE, Web of Science, Cochrane Library, and Scopus for English literature published from July 1999 to June 2024. Peer-reviewed publications evaluating the relationship between gastroesophageal reflux disease, laryngopharyngeal reflux, and dental erosion in adult populations were retrieved. Opensigle and the International Clinical Trials Registry Platform database were used to search the potential gray literature. A manual search was also performed to uncover further relevant studies from the reference lists. The electronic literature search yielded 1382 studies, with 22 researches in line with the inclusion criteria. Results of included publications indicated a significantly higher prevalence of dental erosion in adult populations with gastroesophageal reflux disease or laryngopharyngeal reflux compared to healthy populations. Subjects with dental erosion demonstrate a greater prevalence of laryngopharyngeal reflux or gastroesophageal reflux disease as well. The heterogeneity of the evaluation of clinical outcomes, diagnostic methods, and the definition of diseases need to be considered. Future studies should define reflux disease according to a universal guideline to better enhance treatment in adult populations. Gastroesophageal reflux disease or laryngopharyngeal reflux presents a significant association with dental erosion in adult populations. Clinicians should emphasize timely detection and management of the underlying factors of dental erosion in patients with laryngopharyngeal reflux or gastroesophageal reflux disease.

Microtopography-induced hydrological heterogeneity promotes the co-assembly of vascular plant and biocrust communities, providing synergistic protective functions for the Great Wall.

The Great Wall in China, constructed from rammed earth, faces threats from natural erosion. Vascular plants and biocrusts have enhanced the stability of the Great Wall through various mechanisms; however, understanding of the colonization processes of vascular plants and biocrusts on the wall, as well as their protective mechanisms, remains limited. This study investigated the vascular plant communities, biocrusts, soil moisture content, soil properties, aggregate mechanical stability, aggregate water stability, and soil erodibility factors across seven fine-scale microtopographies of the Great Wall (lower, middle, and upper zones on the east and west faces, as well as the wall crest). After rainfall events and under no-rainfall conditions, soil moisture content was higher at the crest compared to the lower zones on both sides; this demonstrates that microtopography significantly influences soil moisture distribution through rainfall distribution. Soil moisture content was positively correlated with variables associated with vascular plant communities (except evenness) and moss crust (p<0.05). This suggests that the microtopography of the wall and its induced water heterogeneity drive the distribution pattern of vascular plant communities and moss crusts. Vascular plant communities and moss crusts significantly enhanced the mechanical and water stability of soil aggregates, reducing soil erosion susceptibility by providing physical protective cover, increasing the content of mechanically stable and water-stable macroaggregates, and enhancing soil silt and clay content, soil porosity, and water-holding capacity. Based on the regulation of vascular plant communities and biocrusts by microtopography, a restoration framework was proposed, offering a theoretical foundation and practical methods for the protection of the wall and similar earthen heritage sites.

A New Innovative Approach with Revised Pythagorean Fuzzy SWARA in Assessing of Soil Erodibility Factor

Soil erosion is a significant issue that threatens to soil in land degradation processes. The soil erodibility factor is a crucial tool for assessing the susceptibility of soils to erosion. The main aim of this study was to compare the results obtained using the Pythagorean Fuzzy-SWARA method which evaluates the impact weights of the criteria considered for the soil erodibility factor of the soils in the micro-basins located in the district of Çarşamba district of Samsun province, with the results obtained using the formula developed by Wischmeier and Smith. To achieve this case, 78 surface soil samples were collected from micro basins and analyzed for organic matter, clay, sand, silt, very fine sand, degree of structure, and hydraulic conductivity parameters. The erodibility factor was then calculated using these data, and spatial distribution maps were created for both methods. In this study, a revised of the Pythagorean Fuzzy-SWARA approach is proposed to calculate the weight values of the criteria. The values were 0.418 for organic matter, 0.227 for clay, 0.120 for degree of structure, 0.100 for hydraulic conductivity, 0.058 for sand, 0.053 for silt, and 0.039 for very fine sand. Soil erodibility values were determined using a linear combination approach, which normalized all parameter values by a standard scoring function. In estimating soil erodibility, our revised Pythagorean Fuzzy-SWARA approach was found to have a significant relationship with the soil erodibility factor method (R2 = 0.691 at the 1% level) compared to the soil erodibility factor method in estimating soil erodibility. Consequently, the method developed here suggests that fuzzy multi-criteria decision-making methods can be an alternative approach for determining the soil erodibility factor.

Study on improving tribological properties of brush/ring current carrying based on anodic oxidation

Abstract Surface corrosion of the collector ring is an important factor that affects the current-carrying characteristics of the brush/ring system. A suitable surface film can effectively enhance the corrosion resistance of the surface and improve the tribological characteristics of the current-carrying ring. This paper focuses on the collector ring in the brush/ring current-carrying system of a hydrogenerator as the research object. Under the conditions of an anodic oxidation test with a current density of 0.004A/cm², optimized as the anodic oxidation technology, a surface film was formed by selecting oxidation times of 3, 5, 10, and 15 minutes (short duration, low current). The characteristics of the film were measured and analyzed using XPS, AFM, and SEM. Current-carrying tribological tests were conducted on a brush/ring current-carrying wear tester, and the relationship between surface film characteristics, polarization curves, and impedance spectra under different oxidation conditions was analyzed using an electrochemical device. The results show that, as oxidation time increases, the oxide film transitions from a dense barrier layer to a porous oxide film, with both the thickness of the oxide layer and the oxygen content in the film increasing. The wear mechanism evolves from "three-body" wear to "two-body" wear, and eventually to arc wear. An oxidation time of 10 minutes provides the best current-carrying performance, with a contact resistance of 1.118Ω and a friction coefficient of 0.2643. An oxidation time of 3 minutes offers the best corrosion resistance, with a maximum self-corrosion potential of -0.8784V and a minimum corrosion current density of 3.872×10⁻⁶A/cm². The anodic oxide film effectively protects the collector ring from external corrosive factors, extending its service life. Additionally, it reduces friction and contact resistance to some extent, ensuring the long-term stable operation of the equipment in harsh environments.&amp;#xD;

Quantification of soil losses using RUSLE model in the Boumlal watershed (Central Rif, Morocco)

This contribution estimates soil losses in the Boumlal watershed by applying the Revised Universal Soil Loss Equation (RUSLE) and using GIS and remote sensing. This model incorporates five essential factors in water erosion: rainfall erosivity (R), soil erodibility (K), slope length (LS), cover management (C), and erosion control practice (P). The overlay of these parameters makes it possible to produce the synthetic map of annual soil losses (t/ha/year) and identify the most vulnerable areas to water erosion. The results indicate that Boumlal watershed is characterized by high sediment production. Indeed, more than 40% of the watershed produces a considerable amount of sediment exceeding 50 t/ha/year, with soil losses reaching over 200 t/ha/year in some parts of the study area. However, areas with low erosion rates represent approximately 33% of the total watershed area. The extent of water erosion and the high soil loss values are linked to the study area's vulnerability and inadequate anthropogenic interventions. Water erosion in this watershed directly affects soil quality, agricultural land productivity, arable land area, and the siltation of downstream reservoirs.

Corrosion prediction and factors analysis of 2A12 aluminum alloy in marine environment based on data mining

Corrosion prediction and factors analysis of 2A12 aluminum alloy in marine environment based on data mining

Income inequality and the erosion of democracy in the twenty-first century

Among the most pressing problems societies face today are economic inequality and the erosion of democratic norms and institutions. In fact the two problems-inequality and democratic erosion-are linked. In a large cross-national statistical study of risk factors for democratic erosion, we establish that economic inequality is one of the strongest predictors of where and when democracy erodes. Even wealthy and longstanding democracies are vulnerable if they are highly unequal (though national wealth might provide some resiliency). The association between inequality and risk of democratic backsliding is robust, and holds under different measures and structures of both income inequality and wealth inequality. The association is unlikely to be a case of reverse causation. For concerned citizens seeking to understand why so many democracies are eroding and how to stop this process, our study indicates that policies for ameliorating inequality are a promising path forward.

ANALISIS KELAS KEMAMPUAN PENGGUNAAN LAHAN DI AREAL SUB DAS RIAM KANAN KABUPATEN BANJAR PROVINSI KALIMANTAN SELATAN

Inappropriate land use can result in changes in environmental conditions that have negative impacts on humans. Land use that is not in accordance with its capabilities can cause various disasters, such as excessive erosion, landslides, floods, droughts, and an increase in the area of critical land. The Riam Kanan sub-watershed is one of the sub-watersheds in Banjar Regency, South Kalimantan whose condition requires conservation because this area has varying slopes, so if the land is not managed properly, it can cause flooding and other natural disasters. Based on this, it is necessary to carry out research related to the Land Use Capability Classification. The aim of this research is to analyze inhibiting or limiting factors and to formulate land use capability classes. The highest slope percentage of 15 - 25% is found in Land Unit 3 (three) Block A, Land Unit 4 (four) Block B and Land Unit 2 (two) in Block D. The lowest slope percentage of 3-8% is found in Unit Land 1 (one) Block A, Land Unit 1 (one) Block B and Land Unit 3 (three) in Block C. Other Land Units have a slope percentage of 8-15%. Land Use Capability Classes (KPL) obtained from the analysis results are 3 (three) Land Use Capability Classes (KPL), namely 1). KPL II with Soil Depth Limiting Factor "s". 2). KPL III with limiting factors for slope, soil depth and erosion. 3). KPL IV with Erosion Limiting Factor "e".

Evaluating the role of inherited structural discontinuities in badland erosional processes with landscape evolution modelling

AbstractCatchment‐wide erosion and sedimentation behaviour is influenced by variety of controls. One of these controls is erodibility, which may be determined by the lithological properties (e.g. texture, porosity) or the (density of) structural discontinuities (e.g. faults, fractures). In this study, the potential role of different erodibility of lithology and faults in spatio‐temporal erosion and sedimentation behaviour was evaluated using the landscape evolution model, Landscape Process Modelling at Multi‐dimensions and Scales (LAPSUS). The study area, Kula Badlands (western Turkey), is known for dense badland gully networks, incised into fine‐grained sediments in one of the tributaries of the Gediz River, the Geren catchment. An earlier field‐based study demonstrated the fault‐controlled net erosion and consequent sedimentation in these badlands. Here, we test the role of lithology and faults in landscape development with scenario‐based modelling. A reconstructed PalaeoDEM, representing a 30‐ka‐old landscape, was used as an input. Scenario simulations were conducted with lithology‐ and fault‐related erodibility and sedimentability factors. Simulation results demonstrate a significant difference in spatial erodibility and sedimentability and catchment erosion and sedimentation behaviour. Incorporating higher erodibility factors for fault zones caused not only a considerable amount of within‐catchment erosion in fault‐determined erosion zones, but also a decrease in overall catchment sediment export. In addition, high constant sedimentability lowers the sediment export considerably whilst slightly increasing total erosion rates. These outcomes indicate that fault zones with higher erodibility can increase accommodation spaces, producing temporary (re)sedimentation locations, which decrease overall sediment delivery from its catchment on the long run. The model simulations suggest that fault‐related higher erodibility and sedimentability can be important factors in controlling landscape dynamics at the local and catchment scale.

An Optimized GWO-BPNN Model for Predicting Corrosion Fatigue Performance of Stay Cables in Coastal Environments

Corrosion and fatigue damage of high-strength steel wires in cable-stayed bridges in coastal environments can seriously affect the reliability of bridges. Previous studies have focused on isolated factors such as corrosion rates or stress ratios, failing to capture the complex interactions between multiple variables. In response to the critical need for accurate fatigue life prediction of high-strength steel wires under corrosive conditions, this study proposes an innovative prediction model that combines Grey Wolf Optimization (GWO) with a Backpropagation Neural Network (BPNN). The optimized GWO-BPNN model significantly enhances prediction accuracy, stability, generalization, and convergence speed. By leveraging GWO for efficient hyperparameter optimization, the model effectively reduces overfitting and strengthens robustness under varying conditions. The test results demonstrate the model’s high performance, achieving an R2 value of 0.95 and an RMSE of 140.45 on the test set, underscoring its predictive reliability and practical applicability. The GWO-BPNN model excels in capturing complex, non-linear dependencies within fatigue data, outperforming conventional prediction methods. Sensitivity analysis identifies stress range, average stress, and mass loss as primary determinants of fatigue life, highlighting the dominant influence of corrosion and stress factors on structural degradation. These results confirm the model’s interpretability and practical utility in pinpointing key factors that impact fatigue life. Overall, this study establishes the GWO-BPNN model as a highly accurate and adaptable tool, offering substantial support for advancing predictive maintenance strategies and enhancing material resilience in corrosive environments.

Coupling Benefit of Land Use, Land Cover Change and Soil Erosion Under Algorithmic Optimization Model

Technology realizes the quantitative and positioning acquisition of soil erosion and land use information, grasps the relationship between the two from space, and provides theoretical reference and scientific basis for local ecological environment construction and soil and water conservation work. This paper uses remote sensing images in my country in 2020 and 2021 as the data source and obtains land use data in four periods respectively. The experimental results show that the land use structure in my country has undergone great changes in 2020, and the land use type has gradually changed from a structure dominated by cultivated land, grassland, and unused land to grassland, forest land, and cultivated land. The other four types of land use area have increased to varying degrees, the unused land has decreased significantly, and the grassland and forest land have increased significantly; there are differences in the changes in the degree of land use in each study period, and the overall level of land use has developed phase by phase toward higher levels. In addition, this paper also studies the clustering algorithm in machine learning and proposes an improved interpolation algorithm for the completion of the original rainfall data. This algorithm can also be applied to the calculation process of rainfall erosion factors, which realizes the automatic calculation system of soil erosion model factors, realizes the real-time calculation and monitoring of soil erosion in the form of calculation tasks, and solves the problem that manual calculation consumes manpower and material resources.

Partially precise instrument measurements-aided deep learning for industrial quality prediction

Material composition is a kind of important quality index in the process industry. Even though instruments for online measuring these compositions have been widely applied, the precision of material composition measurements is suspicious due to corrosion, scaling and other factors. Laboratory values are more convinced, while these instruments are largely idle in real applications. Nevertheless, despite suspicious precision, partially precise trends exist in these measurements, which are also useful for indicating the variation in quality. This means that a wealth of information directly related to quality variables can provide positive guidance for quality prediction. Enlightened by the requirement of information utilization, a long short-term memory network with embedded trend consistency criteria (TCC-LSTM) is proposed for industrial quality prediction through extremely efficient utilization of partially precise quality instrument data. Specifically, based on the property that the trends of the measured values for quality variable are similar to that of the corresponding laboratory values over time, six trend consistency criteria are designed to evaluate the reliability of instrument data, so as to determine the contribution weights of these data in deep learning-based quality prediction. Moreover, in the neural network structure, the space-wise and time-wise attention mechanisms are designed for capturing important variables and time information. Extensive experiments on an actual alumina digestion process demonstrate the efficiency of TCC-LSTM, whose correlation coefficient is averagely improved by 0.2247 and mean absolute error is as low as 0.008079.

Assessing the Global Sensitivity of RUSLE Factors: A Case Study of Southern Bahia, Brazil

Global sensitivity analysis (GSA) of the revised universal soil loss equation (RUSLE) factors is in its infancy but is crucial to rank the importance of each factor in terms of its non-linear impact on the soil erosion rate. Hence, the goal of this study was to perform a GSA of each factor of RUSLE for a soil erosion assessment in southern Bahia, Brazil. To meet this goal, three non-linear topographic factor (LS factor) equations alternately implemented in RUSLE, coupled with geographic information system (GIS) software and a variogram analysis of the response surfaces (VARSs), were used. The results showed that the average soil erosion rate in the Pardo River basin was 25.02 t/ha/yr. In addition, the GSA analysis showed that the slope angle which is associated with the LS factor was the most sensitive parameter, followed by the cover management factor (C factor) and the support practices factor (P factor) (CP factors), the specific catchment area (SCA), the sheet erosion (m), the erodibility factor (K factor), the rill (n), and the erosivity factor (R factor). The novelty of this work is that the values of parameters m and n of the LS factor can substantially affect this factor and, thus, the soil loss estimation.

Improving safety by fatigue life assessment of pressure hull considering corrosion factors: a review

Abstract Research on determining fatigue endurance of submarine pressure-resistant hulls is crucial for determining their remaining operational lifespan. These studies typically focus on the effects of hydrostatic pressure on fatigue under ideal conditions without taking into account other significant factors. However, the actual condition of pressure hulls is influenced by multiple elements, one of which is operational environmental factors such as corrosion. While current research has examined these factors individually, there is a notable absence of a comprehensive analysis that integrates all of them. Corrosion can reduce structural strength due to the resulting plate thinning effect caused by hydrostatic pressure and low cyclic fatigue. This oversight hampers the development of accurate models for predicting fatigue life and compromises the safety and reliability of underwater structures. This paper addresses the research gap by emphasizing corrosion factors in fatigue life assessments using the low-cyclic fatigue method. By incorporating these elements into the assessment methodology, a more comprehensive understanding of pressure hull fatigue can be achieved, leading to more accurate predictions of pressure hull remaining lifespan.

Risk Factors Favoring Plaque Erosion.

Plaque erosion is the second leading cause of coronary thrombosis following plaque rupture and represents a key pathophysiological process underlying acute coronary syndromes that can culminate in sudden coronary death. While the precise mechanisms and risk factors driving plaque rupture are well-established, those for erosion have only recently been explored. This review summarizes current literature on the characteristics and risk factors favoring plaque erosion. Plaque erosion is characterized by a defective endothelial layer in the intima, promoting thrombus formation in the presence of an intact fibrous cap. It is more common in younger women (< 50 years) and smokers. Pathologic intimal thickening or fibroatheroma are common underlying lesions. Risk factors include gender, age, smoking, and disturbances in shear flow. Advances in pathogenic and molecular mechanisms, such as endothelial shear stress, neutrophil activation, and toll-like receptor-2 pathways, are discussed. Understanding the major risk factors for plaque erosion can inform diagnostics and therapeutics to prevent the progression of arterial thrombosis.

An integrated approach for gully erosion susceptibility mapping and factor effect analysis

An integrated approach for gully erosion susceptibility mapping and factor effect analysis

Footprint of soil erosion effects on pedodiversity at different hierarchical levels: A study across China's water erosion-prone areas.

Pedodiversity conservation is critical for the sustainable use of soil resources and the regulation of ecological security. To explore the relationship between pedodiversity and soil erosion over a prolonged history. In this paper, the response of the regional measurement factor for erosion (RMFE) to pedodiversity at different hierarchical levels was investigated using the optimal window method and structural equation modeling on the basis of water erosion-prone zones. The results suggest that variations in the factors used for soil classification at different hierarchical levels was the main cause of spatial heterogeneity in pedodiversity. Significant impacts of the RMFE on pedodiversity occurred mainly in the Middle reaches of Yangtze River low mountains, hills, plains and basins sub-region (IIC), the Southern China low mountains, hills and plains sub-region (IID) and the Southwestern Yunnan middle and high mountains sub-region (VE) at the Group, Subgroup and Genus levels. Notably, at the Subgroup and Genus levels, the impacts of soil erosion begin to be significant in the Wanda Mt and Sanjiang Plain low mountains and hills sub-region (IA), the Zhejiang and Fujian middle and low mountains, hills and valleys sub-region (IIA), and Taiwan plains and mountains of sub-region (IIE). The regional distribution revealed that pedodiversity in the southeast was more sensitive and positively correlated with the RMFE, with parent material, temperature and anthropogenic activities being the main influences. However, the negatively correlated effects of RMFE on pedodiversity were concentrated in the northeast, where the roles of parent material and vegetation were more critical. The findings of this study are of great practical value and scientific importance for the protection of soil ecological functions and the improvement of regional ecosystem quality and stability.

Carbon steel pipeline CO2 erosion-corrosion damage prediction model and numerical simulation research

CO2 erosion-corrosion (E-C) represents a significant and pervasive threat to the integrity of carbon steel pipeline in the oil and gas industry, which has attracted more and more attention. On this basis, a CO2 E-C damage prediction model considering the synergistic effect is established combining with multiphase flow model, corrosion model and CO2 corrosion model, in which the Eulerian-Lagrangian discrete particle method is employed in the multiphase flow model and the CO2 corrosion model is modified and verified by the erosion-corrosion test method. By using the CFD-DPM technology, the three-dimensional numerical simulation of the elbow is carried out to demonstrate the characteristics of the prediction model, and the dominant factors and extent of CO2 E-C damage can be determined based on the numerical simulation results. Both erosion and corrosion are non-negligible parts that lead to CO2 E-C damage, with corrosion factors being the more important factor to be considered. The prediction results can not only provide suggestions for improving the design of carbon steel pipelines in the oil and gas industry, but also provide protective measures for the operation of existing pipelines to extend their service life, which is helpful for the development and implementation of plans in the oil and gas industry.