Study the Effect of the Diameter of Annular Parachute on Drag Using CFD
Bibliographic record
Abstract
Parachutes are made of highly deformable fabrics.These fabrics can deploy under many different conditions where the payload must decelerate to a velocity that allows it to survive once it reaches the ground.Understanding the dynamic behavior of parachutes is complex.The problem with modeling parachutes in descent is the challenge of coupling equations involving the unsteady airflow acting around the parachute and the structure of the parachute itself.Because the airflow acting around the parachute is dependent on the parachute's geometry which changes at any given moment of flight, fluid-structure interaction modeling is most appropriate approach to analyzing the parachute behavior.The objective of this project is to investigate the effects of air resistance on annular parachutes of varying diameters.The data and accompanying CFD is analyzed to compare experimental drag force and simulation drag force results.The testing of these parachutes takes place in a wind tunnel, where conditions are controlled and can be matched up with CFD simulations.This will allow us to understand the characteristics of the parachute under steady state conditions.This data was within 10% at the 25% speed.From the error percentages observed for the given diameters the 4.0 inch has the best results between the experimental and CFD values.While every other model's error percentage goes up along with the speed, the 4.0 inch decreases its error percentage.Although the error percentages could be due to improper test equipment's, the 4.0 diameter has the best data from the given models, leading us to conclude that it is the best diameter for the annular parachute designed.The experimental drag force for the 4.75-inch diameter parachute model at 25% speed was 0.26 Newtons, at 50% speed was 1.53 Newtons and at 75% speed was 3.69 Newtons.The CFD results for drag force at 25% was 0.245 Newtons, at 50% speed was 1.005 Newtons and at 75% speed was 2.218 Newtons.This yielded an error of 5.708% at 25% speed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".