Modeling the Regression Rates of Protrusion-and-Lattice Hybrid Rocket Fuel Grains

Hybrid rockets based on neat paraffin fuel grains often suffer from poor combustion efficiency due to fuel sloughing and propellant stratification. Fuel sloughing occurs when unburned fuel fragments detach because of the weak mechanical properties of paraffin, reducing thrust and risking motor failure. Embedding lattice structures within the fuel grain enhances structural integrity and mitigates sloughing. Stratification refers to the layering of fuel-rich and oxidizer-rich zones, resulting from the diffusion flame formed at the interface between the solid fuel and gaseous oxidizer that leads to incomplete combustion. To address this, prior studies have introduced passive mixing devices, such as protrusions, to enhance turbulent mixing and combustion efficiency. The first objective of this study is to develop a one-dimensional analytical model that predicts the regression rates of protrusion-and-lattice-augmented fuel grains, accounting for enhanced convective heat transfer induced by protrusions. The second objective is to evaluate the effect of lattice volume fraction on regression rates for values ranging from 5% to 25% and compare predictions with experimental data. Results indicate that increasing lattice volume fraction reduces regression rates, and the model accurately captures this trend, matching experimental data within the error margin for lattice volume fractions up to 10%.

Authors

Institutions

Publication Details

Journal
Journal of Propulsion and Power
Published
2025-11-26
DOI
https://doi.org/10.2514/1.b40192
Primary Topic
Rocket and propulsion systems research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modeling the Regression Rates of Protrusion-and-Lattice Hybrid Rocket Fuel Grains

Craig T. Johansen, J. Wong, Annapurna Basavaraju
Journal of Propulsion and Power
Rocket and propulsion systems research
article

Modeling the Regression Rates of Protrusion-and-Lattice Hybrid Rocket Fuel Grains

Craig T. Johansen, J. Wong, Annapurna Basavaraju
article en

Abstract

Hybrid rockets based on neat paraffin fuel grains often suffer from poor combustion efficiency due to fuel sloughing and propellant stratification. Fuel sloughing occurs when unburned fuel fragments detach because of the weak mechanical properties of paraffin, reducing thrust and risking motor failure. Embedding lattice structures within the fuel grain enhances structural integrity and mitigates sloughing. Stratification refers to the layering of fuel-rich and oxidizer-rich zones, resulting from the diffusion flame formed at the interface between the solid fuel and gaseous oxidizer that leads to incomplete combustion. To address this, prior studies have introduced passive mixing devices, such as protrusions, to enhance turbulent mixing and combustion efficiency. The first objective of this study is to develop a one-dimensional analytical model that predicts the regression rates of protrusion-and-lattice-augmented fuel grains, accounting for enhanced convective heat transfer induced by protrusions. The second objective is to evaluate the effect of lattice volume fraction on regression rates for values ranging from 5% to 25% and compare predictions with experimental data. Results indicate that increasing lattice volume fraction reduces regression rates, and the model accurately captures this trend, matching experimental data within the error margin for lattice volume fractions up to 10%.

Journal of Propulsion and Power
University of Calgary (CA)
Openalex Percentile: Top 53%
Rocket and propulsion systems research
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.