NASA Langley Research Center - 1Workshop on UQEE Prediction of Computational Quality for Aerospace Applications Michael J. Hemsch, James M. Luckring, Joseph H. Morrison NASA Langley Research Center Elements of Predictability Workshop November 13-14, 2003 Johns Hopkins University

NASA Langley Research Center - 2Workshop on UQEE Outline Breakdown of the problem (again) with a slight twist. The issue for most of aerospace is that non-computationalists are doing the applications computations. What are they doing now? What can we do to help?

NASA Langley Research Center - 3Workshop on UQEE Breakdown of tasks Measuring the measurement system Measuring the measurement system Random error characterization using standard artifacts Discrimination testing of the measurement system Discrimination testing of the measurement system Systematic error characterization QA checks against above measurements during customer testing QA checks against above measurements during customer testing Process output of interest Calibration of instruments Calibration of instruments Traceability to standards Off-line Measuring the computational process Measuring the computational process Model-to-model and model-to-reality discrimination Model-to-model and model-to-reality discrimination QA checks against above measurements during computation for customer QA checks against above measurements during computation for customer Verifying that the coding is correct Verifying that the coding is correct Off-line Characterization of process variation using standard problems Systematic error characterization Solution verification Traceable operational definition of the process Experimentation Computation

NASA Langley Research Center - 4Workshop on UQEE The key question for applications: “How is the applications person going to convince the decision maker that the computational process is good enough?”

NASA Langley Research Center - 5Workshop on UQEE Our tentative answer based on observation of aero engineers trying to use CFD on real-life design problems is that it is the quantitative explanatory force of any approach that creates acceptance.

NASA Langley Research Center - 6Workshop on UQEE How can quantitative "explanatory force“ be provided? Breakdown to two questions: –How do I know that I am predicting the right physics at the right place in the inference space? –How accurate are my results if I do have the right physics at the right place in the inference space?

NASA Langley Research Center - 7Workshop on UQEE Airfoil Stall Classification

NASA Langley Research Center - 8Workshop on UQEE Boundaries Among Stall Types

NASA Langley Research Center - 9Workshop on UQEE The applications person needs a process that can be  Controlled  Evaluated  Improved (i.e. a predictable process)

NASA Langley Research Center - 10Workshop on UQEE Process Predicted coefficients, flow features, etc. Geometry, flight conditions, etc. Controllable input (assignable cause variation) Uncontrolled input from the environment (variation that we have to live with, e.g. numerics, parameter uncertainty, model form uncertainty, users) Creating a predictable process …

NASA Langley Research Center - 11Workshop on UQEE Critical levels of attainment for a predictable process A defined set of steps Stable and replicable Measurable Improvable

NASA Langley Research Center - 12Workshop on UQEE What it takes to have an impact... Historically, practitioners have created their designs (and the disciplines they work in) with very little reference to researchers. Practitioners who are successfully using aero computations already know what it takes to convince a risk taker. If we want to have an impact on practitioners, we will have to build on what they are already doing.

NASA Langley Research Center - 13Workshop on UQEE What is takes to have an impact... Good questions: –Are researchers going to be an integral part of the applications uncertainty quantification process or are we going to be irrelevant? –What specific impact on practitioners do I want to have with a particular project? –What process/product improvement am I expecting from that project?

NASA Langley Research Center - 14Workshop on UQEE What is takes to have an impact... We can greatly improve, systematize and generalize the process that practitioners are successfully using right now. The key watchwords for applications are: –practicality, as in mission analysis and design –alacrity, as in "I want to use it right now." –impact, as in "Will my customer buy in?" and "Am I willing to bet my career (and my life) on my prediction?"

NASA Langley Research Center - 15Workshop on UQEE Actions Establish working groups like the AIAA Drag Prediction Workshop (DPW) –Select a small number of focus problems –Use those problems »to demonstrate the prediction uncertainty strategies »to find out just how tough this problem really is For right now … –Run multiple codes, different grid types, multiple models, etc. –Work data sets that fully capture the physics of the application problem of interest. –Develop process best practices and find ways to control and evaluate them. –Develop experiments to determine our ability to predict uncertainty and to predict the domain boundaries where the physics changes.

NASA Langley Research Center - 16Workshop on UQEE Breakout Questions/Issues 1.Defining predictability in the context of the application 2.The logical or physical reasons for lack of predictability 3.Possibility of isolating the reducible uncertainties in view of dealing with them (either propagating them or reducing them) 4.The role of experimental evidence in understanding and controlling predictability 5.The possibility of gathering experimental evidence 6.The role that modeling plays in limiting predictability 7.Minimum requisite attributes of predictive models 8.The role played by temporal and spatial scales and possibilities mitigating actions and models