DATAWorks Sessions Archive

Two responses to an expensive, time consuming test on a final product will be referred to as “adhesion” and “strength”. A screening test was performed on compounds that comprise the final product. These screening tests are multivariate profile measurements. Previous models to predict the expensive, time consuming test lacked accuracy and precision. Data visualization was used to guide a statistical engineering model that makes use of multiple statistical techniques. The modeling approach raised some interesting statistical questions for partial least square models regarding over-fitting and cross validation. Ultimately, the model interpretation and the visualization both make engineering sense and led to interesting insights regarding the product development program and screening compounds.

There are many testing situations that historically involve a large number of runs. The use of experimental design methods can reduce the number of runs required to obtain the information desired. Example applications include wind tunnel test campaigns, computational experiments and live fire tests. In this work we present three case studies conducted under the auspices of the Science of Test Research Consortium comparing the information obtained via a historical experimental approach with the information obtained via an experimental design approach. The first case study involves a large scale wind tunnel experimental campaign. The second involves a computational fluid dynamics model of a missile through various speeds and angles of attack. The third case involves ongoing live fire testing involve hot surface testing. In each case, results suggest a tremendous opportunity to reduce experimental test efforts without losing test information.

Co-authors: Dr. Darryl Ahner, Director, STAT COE Dr. Lenny Truett, STAT COE Mr. Scott Wacker, 96 TG/OL-ACS. This presentation will present the benefits of sequential testing and demonstrate how sequential testing can be used to address complex test conditions by developing well controlled early experiments to explore basic questions before proceeding to full-scale testing. This approach can result in increased knowledge and decreased cost. As of FY13 the Air Force had spent an estimated $47M on dry bay fire testing making fire the largest cost contributor for Live Fire Test and Evaluation (LFT&E) programs. There is currently an estimated 60% uncertainty in total platform vulnerable area (Av) driven by probability of kill (PK) due to ballistically ignited fires. A large part of this uncertain comes from the fact that current spurt modeling does not predict fuel spurt delay with reasonable accuracy despite a large amount of test data. A low-cost sequential approach was developed to improve spurts models. Initial testing used a spherical projectile to test 10 different factors in a definitive screening design. Once the list of factors was refined, a second phase of testing determined if a suitable methodology could be developed to scaled results using water as a surrogate for JP-8 fuel. Finally testing was performed with cubical projectiles to evaluate the effect of fragment orientation. The entire cost for this effort was less than one or two typical full-scale live fire tests.