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Application of artificial neural networks for the prediction of the service conditions of an elastohydrodynamic EHL contact in the presence of solid pollutant

Mattallah Sabrina, Kelaiaia Ridha, Louahem M’Sabah Hanane, Kerboua Adlen

Diagnostyka

2024

Vol. 25, No. 1

art. no. 2024107

Lubricated mechanical mechanisms operate under service conditions influenced by several environmental parameters, and their life times may be threatened due to inappropriate use or by the presence of solid contaminants. The objective of this work is to study the effect of three operating parameters, namely: rotational speed 𝑉, load 𝑄 and kinematic viscosity 𝜈 in the presence of three sizes of solid contaminants 𝑇, on the degradation of an EHL contact, to predict the ranges of effects that may lead to the damage of the contacting surfaces. In our investigation, anexperimental design of nine trials is used to combine four factors with three levels each to accomplish the experimental investigation. Artificial neural network regression and the desirability function were used for the interpretation and modelling of the responses, whichare: wear 𝑊, arithmetic mean height 𝑅𝑎, total profile height 𝑅𝑡 and maximum profile height 𝑅𝑧. From these methods we observed that the sand grain sizes have a significant impact on the wear 𝑊 and the roughness 𝑅𝑎, but that viscosity has the primary influence on the variation of the roughnesses 𝑅𝑡 and 𝑅𝑧. We also found that the quality of the predicted models is very good, with overall determination coefficients of 𝑅2 learning = 0.9985 and 𝑅2 validation = 0.9996. Several levels of degradation depending on the operating conditions are predicted using the desirability function.

Estimating solid contaminant levels in beach sands through petrographic analysis, screening evaluation, and optical imaging

Kuś Sebastian, Jelonek Zbigniew, Jelonek Iwona, Sierka Edyta

Archives of Environmental Protection

2023

Vol. 49, no 3

50--63

Determining the level of solid pollution in beach sands located near artificial inland water bodies in order to maintain high safety standards is a difficult and expensive task. The tests aimed at determining beach pollution caused by solid wastes through analysis of toxic and chemical concentrations, are time-consuming and usually require several days before the results are available. In addition, the maintenance of the beach area involving beach raking or grooming, and the seasonal replenishment of sand makes it difficult to realistically determine the chemical or bacterial contamination of the tested material. Solid pollutants, such as glass, caps, cans, thick foil, metal, and plastic fragments, pose a greater health risk to beachgoers. The above-mentioned pollutants, especially small ones, are hardly visible on the surface or they are buried at shallow depths. Beach garbage poses a serious threat that can lead to infections from cuts and scratches. These injuries can become infected, further jeopardizing the health and lives of beachgoers due to risks like tetanus, staphylococcus, etc. The authors presented a new petrographic method aimed at assessing the quality of sand by examining the content of solid pollutants. The obtained results allowed us to conclude that the mentioned procedure can be used for a quick quantitative estimation of the content of potentially dangerous and undesirable pollutants in beach sands. Consequently, the method implemented to determent the amount of solid pollutants in beach sands has proven to be a valuable tool for recreational facility administrators, helping them in taking necessary measures to ensure the safety of beach users. Petrographic analysis of beach sands revealed the presence of pollutants of plant origin (0.4–1.8%), plastic (0.1–0.4%), paper (0.1–0.6%), charcoal (0.1–0.5%), glass (0.1–0.4%), metals (0.1–0.4%), rust (0.1–0.3%), ash and slag (0.1–0.3%), and fossil coals (0.1–0.2%).