Real-time prediction and classification of erosion crater characteristics in pulsating water jet machining of different materials with machine learning models

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27230%2F24%3A10255780" target="_blank" >RIV/61989100:27230/24:10255780 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68145535:_____/24:00585085

Výsledek na webu

<a href="https://link.springer.com/article/10.1007/s43452-024-00908-7" target="_blank" >https://link.springer.com/article/10.1007/s43452-024-00908-7</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s43452-024-00908-7" target="_blank" >10.1007/s43452-024-00908-7</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Real-time prediction and classification of erosion crater characteristics in pulsating water jet machining of different materials with machine learning models

Popis výsledku v původním jazyce

Erosion caused by water droplets is constantly in flux for practical and fundamental reasons. Due to the high accumulation of knowledge in this area, it is already possible to predict erosion development in practical scenarios. Therefore, the purpose of this study is to use machine learning models to predict the erosion action caused by the multiple impacts of water droplets on ductile materials. The droplets were generated by using an ultrasonically excited pulsating water jet at pressures of 20 and 30 MPa for individual erosion time intervals from 1 to 20 s. The study was performed on two materials, i.e. AW-6060 aluminium alloy and AISI 304 stainless steel, to understand the role of different materials in droplet erosion. Erosion depth, width and volume removal were considered as responses with which to characterise the erosion evolution. The actual experimental response data were measured using a non-contact optical method, which was then used to train the prediction models. A high prediction accuracy between the predicted and observed data was obtained. With this approach, the erosion resistance of the material can be predicted, and, furthermore, the prediction of the progress from the incubation erosion stage to the terminal erosion stage can also be obtained.

Název v anglickém jazyce

Real-time prediction and classification of erosion crater characteristics in pulsating water jet machining of different materials with machine learning models

Popis výsledku anglicky

Erosion caused by water droplets is constantly in flux for practical and fundamental reasons. Due to the high accumulation of knowledge in this area, it is already possible to predict erosion development in practical scenarios. Therefore, the purpose of this study is to use machine learning models to predict the erosion action caused by the multiple impacts of water droplets on ductile materials. The droplets were generated by using an ultrasonically excited pulsating water jet at pressures of 20 and 30 MPa for individual erosion time intervals from 1 to 20 s. The study was performed on two materials, i.e. AW-6060 aluminium alloy and AISI 304 stainless steel, to understand the role of different materials in droplet erosion. Erosion depth, width and volume removal were considered as responses with which to characterise the erosion evolution. The actual experimental response data were measured using a non-contact optical method, which was then used to train the prediction models. A high prediction accuracy between the predicted and observed data was obtained. With this approach, the erosion resistance of the material can be predicted, and, furthermore, the prediction of the progress from the incubation erosion stage to the terminal erosion stage can also be obtained.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

20301 - Mechanical engineering

Projekt

<a href="/cs/project/GA23-05372S" target="_blank" >GA23-05372S: Povrchová a podpovrchová eroze způsobená vícenásobným dopadem kapek</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Archives of Civil and Mechanical Engineering

ISSN

1644-9665

e-ISSN

2083-3318

Svazek periodika

24

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

19

Strana od-do

nestránkováno

Kód UT WoS článku

001195112100002

EID výsledku v databázi Scopus

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