Development of mathematical models to predict the density and hardness of Fe-ZrO<sub>2</sub> composites

Jha, Pramod; Kumar, Devendra; Mishra, Vijay Kumar

doi:10.1080/2374068x.2021.1945298

Cited by 3 publications

(2 citation statements)

References 18 publications

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“…In this direction, researchers have reported the mechanical and wear properties of various ceramic-reinforced Fe-based metal matrix composites processed using P/M. 7–10 Gupta et al 11 observed that wear rate of Fe-Al 2 O 3 metal matrix composites was dependent on the sintering temperature and time. Adhesive wear was found to be dominant at lower load, while abrasive wear was instrumental at higher load.…”

Section: Introductionmentioning

confidence: 99%

Investigation on the dry sliding friction and wear properties of Fe-ZrO₂ composite

Jha,

Sinha,

Singh

et al. 2024

Tribology - Materials, Surfaces & Interfaces

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The present work investigated the wear behaviour of powder metallurgy-processed ZrO2 (10 wt.%) reinforced Fe-based metal matrix composite under dry sliding conditions. The friction and wear properties were evaluated under varying loads and sliding speeds ranging from 5 to 10 N, and 0.75 to 1.25 m/s, respectively. The wear tests were performed against a counter face of EN31 steel (HRC 60) employing pin-on-disc tribometer under room temperature. Microstructural examination of the composite by field-emission scanning electron microscopy (FE-SEM), equipped with energy dispersive spectroscopy (EDS), displayed the presence as well as a homogeneous dispersion of reinforcement phase into the matrix. At a particular load and sliding speed, transition behaviour was observed in the coefficient of friction, whereas wear rate increased with increasing load and sliding speed. The analysis of worn surface indicated that the adhesive wear was dominant at relatively high operating conditions, while abrasive wear remained operative at lower load and sliding speed.

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Section: Introductionmentioning

confidence: 99%

Investigation on the dry sliding friction and wear properties of Fe-ZrO₂ composite

Jha,

Sinha,

Singh

et al. 2024

Tribology - Materials, Surfaces & Interfaces

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“…Data interpretation has become an important task to be considered within research and development activities of new products. Tools such as the statistical data-driven model (SDDM) enable the prediction and discovery of the repercussions of certain processing variables involved in manufacturing and experimental processes for the validation of prototypes or new products on certain characteristics or properties of interest [21][22][23][24]. This allows a better approach to the design of experiments (DOE) and the search for process optimization based on prediction by statistical analysis.…”

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confidence: 99%

Statistical Data-Driven Model for Hardness Prediction in Austempered Ductile Irons

Rodríguez-Rosales

Montes-González

Gómez-Casas

et al. 2022

Metals

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This research evaluates the effect of temperature and time austempering on microstructural characteristics and hardness of ductile iron, validating the results by means of a statistical method for hardness prediction. Ductile iron was subjected to austenitization at 950 °C for 120 min and then to austempering heat treatment in a salt bath at temperatures of 290, 320, 350 and 380 °C for 30, 60, 90 and 120 min. By increasing austempering temperature, a higher content of carbon-rich austenite was obtained, and the morphology of the thin acicular ferrite needles produced at 290 °C turned completely feathery at 350 and 380 °C. A thickening of acicular ferrite needles was also observed as austempering time increased. An inversely proportional behavior of hardness values was thus obtained, which was validated through data analysis, statistical tools and a regression model taking temperature and time austempering as input variables and hardness as the output variable, which achieved a correlation among variables of about 97%. The proposal of a mathematical model for the prediction of hardness in austempered ductile iron represents a numerical approximation which validates the experimental results at 95.20%.

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A brief review of processing techniques for NiAl intermetallic composites

Aprajak

Jha

Mohapatra

et al. 2023

Materials Today: Proceedings

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Development of mathematical models to predict the density and hardness of Fe-ZrO₂ composites

Cited by 3 publications

References 18 publications

Investigation on the dry sliding friction and wear properties of Fe-ZrO₂ composite

Investigation on the dry sliding friction and wear properties of Fe-ZrO₂ composite

Statistical Data-Driven Model for Hardness Prediction in Austempered Ductile Irons

A brief review of processing techniques for NiAl intermetallic composites

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Development of mathematical models to predict the density and hardness of Fe-ZrO2 composites

Cited by 3 publications

References 18 publications

Investigation on the dry sliding friction and wear properties of Fe-ZrO2 composite

Investigation on the dry sliding friction and wear properties of Fe-ZrO2 composite

Statistical Data-Driven Model for Hardness Prediction in Austempered Ductile Irons

A brief review of processing techniques for NiAl intermetallic composites

Contact Info

Product

Resources

About

Development of mathematical models to predict the density and hardness of Fe-ZrO₂ composites

Investigation on the dry sliding friction and wear properties of Fe-ZrO₂ composite

Investigation on the dry sliding friction and wear properties of Fe-ZrO₂ composite