EVALUATING MECHANICAL PROPERTIES OF IRON ORE PELLETS FROM ITAKPE AND AGBAJA BLENDS

The determination of the mechanical properties of resultant pellets of Itakpe and Agbaja iron ore blends were carried out. The drop number determined gave a value of 3.89cm, at 70/30 Itakpe / Agbaja blend proportion ratio. The best drop resistance for Itakpe /Agbaja iron ore blend ratio at 60/40 with the corresponding value at 4.78cm. The best green compressive strength value at 11.98 N/P with corresponding blend ratio at 80/20 of Itakpe/Agbaja iron ore. The dry compression strength has a value of 34.7N/P with a corresponding blend ratio of 70/30 for Itakpe / Agbaja. The Itakpe / Agbaja blend ratio of 70/30 gave optimum indurating compressive strength of 2592.40N/P which indicates that this ratio is the best suitable for the reduction and production of liquid pig iron in the Blast Furnace and Direct Reduced Iron processes. These results further connotes that the sufficient mechanical strength for pellets for 70/30 Itakpe / Agbaja blend ratio gave better value. The best moisture content for Itakpe / Agbaja iron ore at 50/50, while the corresponding value was 6.76ml. The tumbler index value for Itakpe / Agbaja iron ore at 93.83% while the corresponding blend ratio value at 60/ 40. The best abrasion index value was obtained at a blend ratio of 60/40 for Itakpe / Agbaja iron ore, while the corresponding value was 4.59%. The microporosity value was achieved at a blend ratio of 10/90 Itakpe/ Agbaja iron ore, while the corresponding value was 9.98%.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-16
DOI
https://doi.org/10.5281/zenodo.17131442
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

EVALUATING MECHANICAL PROPERTIES OF IRON ORE PELLETS FROM ITAKPE AND AGBAJA BLENDS

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

EVALUATING MECHANICAL PROPERTIES OF IRON ORE PELLETS FROM ITAKPE AND AGBAJA BLENDS

article en

Abstract

The determination of the mechanical properties of resultant pellets of Itakpe and Agbaja iron ore blends were carried out. The drop number determined gave a value of 3.89cm, at 70/30 Itakpe / Agbaja blend proportion ratio. The best drop resistance for Itakpe /Agbaja iron ore blend ratio at 60/40 with the corresponding value at 4.78cm. The best green compressive strength value at 11.98 N/P with corresponding blend ratio at 80/20 of Itakpe/Agbaja iron ore. The dry compression strength has a value of 34.7N/P with a corresponding blend ratio of 70/30 for Itakpe / Agbaja. The Itakpe / Agbaja blend ratio of 70/30 gave optimum indurating compressive strength of 2592.40N/P which indicates that this ratio is the best suitable for the reduction and production of liquid pig iron in the Blast Furnace and Direct Reduced Iron processes. These results further connotes that the sufficient mechanical strength for pellets for 70/30 Itakpe / Agbaja blend ratio gave better value. The best moisture content for Itakpe / Agbaja iron ore at 50/50, while the corresponding value was 6.76ml. The tumbler index value for Itakpe / Agbaja iron ore at 93.83% while the corresponding blend ratio value at 60/ 40. The best abrasion index value was obtained at a blend ratio of 60/40 for Itakpe / Agbaja iron ore, while the corresponding value was 4.59%. The microporosity value was achieved at a blend ratio of 10/90 Itakpe/ Agbaja iron ore, while the corresponding value was 9.98%.

Zenodo (CERN European Organization for Nuclear Research)
University of Nigeria (NG)
Openalex Percentile: Top 36%
Geochemistry and Geologic Mapping
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.