Guidelines for validation experiments Oberkampf and Roy provide guidelines for validation experiments This lecture deals with their applications to the –Paper helicopter –CCMT shock tube validation of Rocflu

CCMT | 2 Explosive solid particle dispersal  Target three dimensional dispersal phenomenon -Explosive processes influence dynamics of densely packed particles -Predicting particle dynamics with a simulation

CCMT | 3 Validation of Shock Tube Simulation  Validation of the models for shock-particle interactions Experimental Data Shock Tube Simulation Validation

I: Joint design Guideline 1: A validation experiment should be jointly designed by experimentalists, model developers, and code users working closely together throughout the program, from inception to documentation with complete candor about the strength and weaknesses of each approach.

History of processes Experiments always precede some of the modeling. Validation is intended to check whether the model only works as a curve fit or does it have predictive capability. For shock tube V&V team acts as bridge. How did you wear the different hats of analysts, code developers and experimentalists for helicopter project? What is the validation part of the paper helicopter project?

CCMT | 6 Prediction Metrics Prediction Metrics: The locations of the particle curtain edges at upstream and downstream  What are the alternatives? Curtain thickness after impact Before impact After impact

What should be measured? Guideline 2: A validation experiment should be designed to capture the essential physics of interest, and measure all relevant physical modeling data, initial and boundary conditions, and system excitation information required by the model. For the shock tube experiment the essential physics is the interaction of shock and particles. What is the essential physics for helicopter? What else would be worthwhile measuring?

Synergism Guideline 3: A validation experiment should try to emphasize the inherent synergism that is attainable between computational and experimental approaches. –Example: Use simple configuration to reveal test deficiencies (e.g. flow without particles) –Example: Use simulation to decide on sensor placement. –Examples from helicopter project?

Independence Guideline 4: Although the experimental design should be developed cooperatively, independence must be maintained in obtaining the computational and experimental system response results. –Blind test prediction is important! –Why?

Hierarchy of measurements Guideline 5: Experimental measurements should be made of a hierarchy of system response quantities, for example from globally integrated quantities to local quantities. –For shock tube experiment, local quantities include pressures and local volume fractions. –What are local and global quantities for helicopter measurements?

Uncertainty Guideline 6: The experimental design should be constructed to analyze and estimate the components of random (precision) and systematic (bias) experimental uncertainties. How do you determine the bias in the helicopter experiment?