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Nonlinear Regression Modeling for Engineering Applications: Modeling, Model Validation, and Enabling Design of ExperimentsAvailable to Purchase
ISBN:
9781118597965
No. of Pages:
400
Publisher:
ASME-Wiley
Publication date:
2016
eBook Chapter
18 Design of Experiments for Model Development and Validation Available to Purchase
Page Count:
16
-
Published:2016
Citation
"Design of Experiments for Model Development and Validation." Nonlinear Regression Modeling for Engineering Applications: Modeling, Model Validation, and Enabling Design of Experiments. Ed. Rhinehart, RR. ASME-Wiley, 2016.
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To run an experiment, you need to choose values for influence variables. You will implement a specific set of input conditions and then wait until conditions are right to collect response data. This might be to wait until the process settles to a new steady state (SS). Then collect data. Then move to the next set of input values. However, for dynamic models, data from the transient period is of interest. There, you will collect data at time intervals chosen to reveal the time-response.
18.1
Concept – Plan and Data
18.2Sufficiently Small Experimental Uncertainty – Methodology
18.3Screening Designs – A Good Plan for an Alternate Purpose
18.4Experimental Design – A Plan for Validation and Discrimination
18.5EHS&LP
18.6Visual Examples of Undesired Designs
18.7Example for an Experimental Plan
18.8Takeaway
Exercises
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