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Experimental Study and Machine Learning Modeling of Wear Properties in Al Metal Matrix Composites

Year: 2025

Type: article

Abstract: This repository contains Python code and supporting dataset for the research paper: "Experimental Study and Machine Learning Modeling of Wear Properties in Al Metal Matrix Composites" The code implements and compares multiple machine learning models to predict the COF and wear rate of Al-based Metal Matrix Composites (MMCs) reinforced with varying percentages of Carbon Nanotubes (CNT). The dataset includes experimental parameters such as applied load, sliding velocity, and sliding distance.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.15520699

Authors: Birada, Lakshmi Manasa, mulpur, sarat babu, Mondi, Rama Karthik

Institutions: Jawaharlal Nehru Technological University, Kakinada, National Institute of Technology Andhra Pradesh

Language: English

Topic: Aluminum Alloys Composites Properties

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W6911945835

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