Prognosis 2030 – A Vision
February 19 2008
T.A. Cruse, DARPA/DSO Consultant
Dayton, Ohio 45459
1
The Perfect World for Prognosis
Damage progression is deterministic


Perfect knowledge of microstructural features,
chemistry, initial strains, etc.
Perfect physics-based damage models appropriate
to microstructures
Ignorance of any = uncertainty



Usually seen as scatter in actual/predicted
Processing deviation = new population
Design error = major shift in new population
Prognosis is more than physics/chemistry
19 February 2008
DCT Workshop
Slide 2
Prognosis is a 3-Legged Stool
Leg 1: Physics-based system state models



Response to defined/controlled processing
Response to defined/recorded environments
Prediction of future states, given initial state
Leg 2: System state “fingerprint”

Initial state definition and recording
Leg 3: State validation – “virtual sensor”

Linking Leg 1 with new NDE characterizations
to provide updated system state “fingerprint”
19 February 2008
DCT Workshop
Slide 3
What is New NDE?
What it is not



Finding cracks
Finding delaminations
Stiffness change
What it will include





Change detection
New signal processing
Witness mapping
Ping-ring response mode
Focus on state awareness
What it will be

Integral part of 3-legs
19 February 2008
DCT Workshop
Slide 4
State Awareness Attributes
Real-time environmental loads & history

E.g., loads, thermal loads, humidity, chemistry,
etc.
Real-time microstructural response

E.g., strain, temperature, diffusion, oxidation, etc.
Initial state “fingerprint”


Micro/macro state definition at service intro
Critical processing history state contributions
Current state “fingerprint”
19 February 2008
DCT Workshop
Slide 5
Prognosis 2030 – the vision
Vast computational power in the system





Real-time state assessment updating
Real-time integration of initial state and environmental
history
Real-time forensics (space systems/avionics)
Real-time communications to user for prognosing future
state capabilities
“Columbia safe-return” scenario capability
System operates as integrated, virtual sensor


All three legs are fully integrated
State awareness through “new NDE”
Analytical system certification revolution


Fully risk based design/deployment with processing histories
Fully adaptive to individual part tracking up to the “tail
number”
19 February 2008
DCT Workshop
Slide 6
Prognosis 2030 - Challenges
Close the “scatter band”


High fidelity modeling – system response
High fidelity damage models
 Complex 3D material systems
 High heat flux loading environments/responses
Revolutionize material state awareness




Neural materials and systems
Ping-ring state updating
Global-local communications within system
Remote diagnostics/forensics
Future material system complexities


Hybrids, 3D and tailored systems,
Complete material processing
All things to be probabilistically integrated
19 February 2008
DCT Workshop
Slide 7
Recommendations to Workshop
Assess balance between the three legs


High fidelity, probabilistic system modeling
Complex materials – damage state modeling
 Microstructurally physics-based state processes
 Cumulative history, fully-integrated mechanisms

Integrated, new NDE concepts
 Self-assessing materials; automated reporting
 Characterize the material state; integrate with models
Define the most important basic research
enablers for each


Where are the greatest discovery potentials?
What are the most critical challenge problems?
19 February 2008
DCT Workshop
Slide 8