Supervision Ian F. C. Smith - documents.epfl.ch · Supervision Ian F. C. Smith EDCE 2011 Modelling...
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ENAC / How do structures really behave? Why does it matter?... to save money! Author James-A. Goulet Supervision Ian F. C. Smith EDCE 2011 / Modelling uncertainties p i j k L m n o x 0 y 0 z 0 PROBABILITY-BASED OBJECTIVE FUNCTION 0 = THE ‘’MOST-LIKELY‘’ MODEL IS OFTEN NOT THE RIGHT MODEL SEVERAL MODELS EXPLAIN MEASUREMENTS 1 STEP Objective function Measuring and Modelling 2 STEP Developping an objective function 3 STEP Interpreting measurements Measurement uncertainties + MODEL FILTERING MODEL FITTING Accelerometers Inclinometers Transducer Strain guages etc... (Model calibration does not work!) 0 Objective function Prediction-measure (Sensor location #i) Prediction-measure (Sensor location #j) Set of acceptable models Single ‘’most-likely’’ model Used to compare measured values to the predictions of several thousand models Prediction-measure (Sensor location #i) Prediction-measure (Sensor location #j) (One per sensor location) 0 0 0 Boundary conditions? What is the prestress level? What is the expansion joint condition? What is the saddle condition? Sensors
Transcript of Supervision Ian F. C. Smith - documents.epfl.ch · Supervision Ian F. C. Smith EDCE 2011 Modelling...
ENAC /
How do structures really behave?Why does it matter?... to save money!Author James-A. Goulet
Supervision Ian F. C. Smith EDCE 2011/
Modelling uncertainties
p i
j
kLm
no x0
y0z0
PROBABILITY-BASEDOBJECTIVE FUNCTION
0
=
THE ‘’MOST-LIKELY‘’ MODELIS OFTEN NOT THE RIGHT MODEL
SEVERAL MODELS EXPLAINMEASUREMENTS
1STEP
Objectivefunction
Measuring and Modelling
2STEP Developping an objective function
3STEP
Interpreting measurements
Measurement uncertainties
+
MODEL FILTERINGMODEL FITTING
AccelerometersInclinometersTransducerStrain guagesetc...
(Model calibration does not work!)
0
Objectivefunction
Prediction-measure
(Sensor location #i)
Prediction-measure
(Sensor location #j)
Set of acceptablemodels
Single ‘’most-likely’’model
Used to compare measured values to the predictions ofseveral thousand models
Prediction-measure
(Sensor location #i)
Prediction-measure
(Sensor location #j)
(One per sensor location) 0
0
0Boundary conditions?
What is the prestress level?
What is theexpansion joint condition?
What is the saddle condition?
Sensors
ENAC /
How do structures really behave?Why does it matter?... to save money!Author James-A. Goulet
Supervision Ian F. C. Smith EDCE 2011/
Modelling uncertainties
p i
j
kLm
no x0
y0z0
PROBABILITY-BASEDOBJECTIVE FUNCTION
0
=
THE ‘’MOST-LIKELY‘’ MODELIS OFTEN NOT THE RIGHT MODEL
SEVERAL MODELS EXPLAINMEASUREMENTS
1STEP
Objectivefunction
Measuring and Modelling
2STEP Developping an objective function
3STEP
Interpreting measurements
Measurement uncertainties
+
MODEL FILTERINGMODEL FITTING
AccelerometersInclinometersTransducerStrain guagesetc...
(Model calibration does not work!)
0
Objectivefunction
Prediction-measure
(Sensor location #i)
Prediction-measure
(Sensor location #j)
Set of acceptablemodels
Single ‘’most-likely’’model
Used to compare measured values to the predictions ofseveral thousand models
Prediction-measure
(Sensor location #i)
Prediction-measure
(Sensor location #j)
(One per sensor location) 0
0
0Boundary conditions?
What is the prestress level?
What is theexpansion joint condition?
What is the saddle condition?
Sensors
