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Record W2132485013 · doi:10.2514/6.2013-105

Reduction of Aft Fuselage Drag on the C-130 Using Microvanes

2013· article· en· W2132485013 on OpenAlexaff
Brian Smith, Patrick Yagle, John Hooker

Bibliographic record

Venue51st AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition · 2013
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsLockheed Martin (Canada)
FundersAir Force Research Laboratory
KeywordsFuselageDragMarine engineeringSoftware deploymentAerospace engineeringEngineeringDrop testCruiseComputational fluid dynamicsAirplaneDrop (telecommunication)AeronauticsAutomotive engineeringReduction (mathematics)PropulsionMechanical engineering

Abstract

fetched live from OpenAlex

‡The aft fuselage of the C-130 is upswept to accommodate the aft cargo ramp. The upswept aft fuselage accounts for as much as 11% of the total vehicle drag at cruise. While concepts to reduce this contribution to the C-130 drag were developed in the past, they interfered with air drop operations and were never integrated into the fleet. Using flow control technology, a relatively simple, structurally benign, microvane concept with minimal air drop impact has been developed. In a collaborative Lockheed Martin, Air Force Research Laboratory program, the microvane concept was matured. Using CFD, the microvane configuration was optimized. Integration and air drop constraints were evaluated and an air drop compliant, retrofittable microvane configuration was identified. Flight testing verified the accuracy of the CFD based drag reduction predictions and confirmed the viability of the design. The flight test configuration saves between 14 and 30 gallons of fuel per hour, resulting in a potential fleet wide savings to the USAF of 2.4 million gallons of fuel per year. With no impact on operational capability and a proven flight test technology readiness level (TRL), this low-risk solution offers benefits of low-cost and rapid deployment to the fleet. The Lockheed Martin (LM) C-130 Hercules tactical military transport incorporates a dual use aft cargo ramp which acts as both a loading ramp and a fairing which closes out the aft fuselage shape. This integrated cargo ramp design is responsible for as much as 11% of the total aircraft drag due to the resulting large aft fuselage upsweep angle. Numerous studies have been performed over the last 40 years to reduce this large drag contribution through the incorporation of relatively large aft fuselage mounted strakes. These strake concepts were developed in the 1970’s – 1980’s through wind tunnel and extensive flight testing. While strakes are effective at reducing aircraft drag, they create integration problems. Results from USAF operational test and evaluations of C-130 aft fuselage strakes in 1981 indicated that “C-130 airdrop capabilities are severely limited with the strakes installed” and that “large container-like loads may require strake removal prior to on or off loading.” 1 They were not incorporated primarily for these reasons. However, current research has indicated that microvanes, devices approximately 10 inches long and 0.5 to 1.2 inches tall arrayed along the breakline of the aft fuselage as shown in Figure 1, can significantly reduce the aft fuselage drag penalty while maintaining compatibility with air drop and loading operations. These devices have been developed using advanced computational fluid dynamics (CFD) methods and their drag reduction performance has been successfully verified with recent flight testing. These tests verified a

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.017
GPT teacher head0.233
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations21
Published2013
Admission routes1
Has abstractyes

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