2026-10-15T06:41:49Z https://data.mendeley.com/oai

oai:data.mendeley.com/svdcbwt6j5.1 2026-07-08T20:20:06Z

Nakimuli, Constance Nakato Predicting Relaxed Density, Durability, and Compressive Strength of Blended Agricultural Waste Biomass Briquettes Mendeley Data This dataset contains 63 treatment-level observations from a full factorial experiment on blended agricultural biomass briquettes, comprising 7 blend compositions × 3 particle sizes × 3 compaction pressures. Eight agricultural residues were used across the blends: banana peel, banana bunch, maize cob, maize stalk, millet bran, coffee husk, groundnut shell, and bean husk. For each treatment combination, the dataset reports mean values and standard deviations for three mechanical quality indicators: compressive strength (MPa), impact resistance index (%), and relaxed density (g/cm³), along with process parameters (particle size, compaction pressure, moisture content) and blend composition (percentage by mass of each feedstock). This dataset supports the study "Interpretable Machine Learning for Predicting Relaxed Density, Durability, and Compressive Strength of Blended Agricultural Biomass Briquettes." Machine Learning Biomass Biomass Densification Kilama Okot, David KAWUMA, SIMON KAGGWA, FRED Asasira, Justus De Greef, Johan Vanierschot, Maarten Dataset doi:10.17632/svdcbwt6j5.1 oai:data.mendeley.com/svdcbwt6j5.1 Creative Commons Attribution 4.0 International http://creativecommons.org/licenses/by/4.0 https://data.mendeley.com/datasets/svdcbwt6j5 2026-07-08T20:20:06Z