Statistical Analysis of CFD Solutions from the Fifth AIAA Drag Prediction Workshop

Morrison, Joseph H.

doi:10.2514/6.2013-47

Cited by 8 publications

(4 citation statements)

References 29 publications

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“…The statistical approach identified which solutions differed from the collective and was useful in identifying sources of variation. 3,8,10,15,20 Individual solutions could differ from the collective for multiple reasons. Different turbulence model, different numerical scheme, and errors are some of the sources of variation that were identified.…”

Section: Observations From Dpwmentioning

confidence: 99%

Observations on CFD Verification and Validation from the AIAA Drag Prediction Workshops

Morrison

Kleb

Vassberg

2014

52nd Aerospace Sciences Meeting

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The authors provide observations from the AIAA Drag Prediction Workshops that have spanned over a decade and from a recent validation experiment at NASA Langley. These workshops provide an assessment of the predictive capability of forces and moments, focused on drag, for transonic transports. It is very difficult to manage the consistency of results in a workshop setting to perform verification and validation at the scientific level, but it may be sufficient to assess it at the level of practice. Observations thus far: 1) due to simplifications in the workshop test cases, wind tunnel data are not necessarily the "correct" results that CFD should match, 2) an average of core CFD data are not necessarily a better estimate of the true solution as it is merely an average of other solutions and has many coupled sources of variation, 3) outlier solutions should be investigated and understood, and 4) the DPW series does not have the systematic build up and definition on both the computational and experimental side that is required for detailed verification and validation. Several observations regarding the importance of the grid, effects of physical modeling, benefits of open forums, and guidance for validation experiments are discussed. The increased variation in results when predicting regions of flow separation and increased variation due to interaction effects, e.g., fuselage and horizontal tail, point out the need for validation data sets for these important flow phenomena. Experiences with a recent validation experiment at NASA Langley are included to provide guidance on validation experiments.

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Section: Observations From Dpwmentioning

confidence: 99%

Observations on CFD Verification and Validation from the AIAA Drag Prediction Workshops

Morrison

Kleb

Vassberg

2014

52nd Aerospace Sciences Meeting

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“…The approach is based on the principles of the AIAA Drag Prediction Workshop (DPW) statistical summary. 1,9 Two samples of the submissions are examined: a sample where the assumption of independence is violated by including uniformly refined grids from the same code and participant to increase the sample size, and a sample where the coarser uniformly refined grids are excluded. For each population, the scatter limits are established asμ ± Kσ.…”

Section: Statistical Approachmentioning

confidence: 99%

“…A coverage factor of K = √ 3 is calculated by assuming a uniform distribution of results because the actual distribution of the submissions is unknown. 9 The first two DPW statistical summaries assumed 99% coverage of a normal distribution, which resulted in a larger K. 1 A submission is significant and considered outlier if it is outside the limits established by Eq. (2).…”

Section: Statistical Approachmentioning

confidence: 99%

“…SBPW-1 benefits from the lessons learned at the 2008 NASA Sonic Boom Prediction Workshop and previous AIAA workshops. [8][9][10][11] The data and analysis methods of this summary are intended to contribute toward the discussion of replacing the prohibition of overland supersonic flight 13 with a certification standard. The existing ban on overland flight increases the cost and block time 14 of supersonic fights between city pairs and is an important driver of the economic viability of a supersonic transport.…”

Section: Introductionmentioning

confidence: 99%

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Summary and Statistical Analysis of the First AIAA Sonic Boom Prediction Workshop

Park

Morgenstern

2016

Journal of Aircraft

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A summary is provided for the First AIAA Sonic Boom Workshop held 11 January 2014 in conjunction with AIAA SciTech 2014. Near-field pressure signatures extracted from computational fluid dynamics solutions are gathered from nineteen participants representing three countries for the two required cases, an axisymmetric body and simple delta wing body. Structured multiblock, unstructured mixed-element, unstructured tetrahedral, overset, and Cartesian cut-cell methods are used by the participants. Participants provided signatures computed on participant generated and solution adapted grids. Signatures are also provided for a series of uniformly refined workshop provided grids. These submissions are propagated to the ground and loudness measures are computed. This allows the grid convergence of a loudness measure and a validation metric (difference norm between computed and wind tunnel measured near-field signatures) to be studied for the first time. Statistical analysis is also presented for these measures. An optional configuration includes fuselage, wing, tail, flow-through nacelles, and blade sting. This full configuration exhibits more variation in eleven submissions than the sixty submissions provided for each required case. Recommendations are provided for potential improvements to the analysis methods and a possible subsequent workshop.

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Sparno profilių aerodinaminių charakteristikų tyrimas

Naujokaitis¹

2013

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Statistical Analysis of CFD Solutions from the Fifth AIAA Drag Prediction Workshop

Cited by 8 publications

References 29 publications

Observations on CFD Verification and Validation from the AIAA Drag Prediction Workshops

Observations on CFD Verification and Validation from the AIAA Drag Prediction Workshops

Summary and Statistical Analysis of the First AIAA Sonic Boom Prediction Workshop

Sparno profilių aerodinaminių charakteristikų tyrimas

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