2006-04-03
Probabilistic Assessment of CAE Models 2006-01-0456
This paper investigates a wide range of statistical methods for application in model validation under uncertainty. Hypothesis testing methods are explored first and an interval-based testing is found to be more practically useful for model validation than the commonly used point null hypothesis testing. Also, a more direct approach is proposed by formulating model validation as a reliability estimation problem. The proposed methods are illustrated and compared using numerical examples.
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JOURNAL ARTICLE
Approaches to Achieving High Reliability and Confidence Levels with Small Test Sample Sizes
2015-01-2758
BOOK
Engine Development for Performance and Efficiency (DVD)
TECHNICAL PAPER
Development of a Specific Durability Test Cycle for a Commercial Vehicle Based on Real Customer Usage
2013-26-0137
