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It presents the classification of testing methods for durability of alloys/intermetallics and reports examples of intrinsic and extrinsic tests that include cycling and aging for AB5/AB and other alloys and more recent results on extrinsic tests on lightweight complex hydrides (imide-amide) that were cycled between Li2NH/LiNH2 phases.
Although we have not yet done a full analysis using that tool, a preliminary investigation suggests that the same basic pattern of high performance on intrinsic evaluation of mutation extraction and low recall on the extrinsic tests we have performed in our experiments also holds.
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Comparison of the present test results with data obtained with a variety of test methods and test parameters clarified the role of intrinsic (material-dependent) and extrinsic (test-method-dependent) factors on the measured fatigue behavior.
This chapter focuses on the classical metal hydrides their thermal, cyclic hydrogen charge discharge behavior, and methodology of intrinsic and extrinsic testing to test long-term durability of the alloys, from a metallurgical engineer's perspective.
Models were generated until 20 models with 0% extrinsic omission were compiled (i.e., all of the extrinsic testing subset completely predicted), and remaining models were discarded.
The GARP program further divides training data into intrinsic training and extrinsic testing subsets (80% and 20% respectively herein) prior to each model building process [78].
Occurrence data are used by GARP as follows: 50% of occurrence data points are set aside for an independent test of model quality (extrinsic testing data); 25% are used for developing models (training data); and 25% are used for tests of model quality internal to GARP (intrinsic testing data).
Occurrence data are used by GARP as follows: 50% of occurrence data points are set aside for an independent filtering to assure predictive ability of models (extrinsic testing data), 25% are used for developing models (training data), and 25% are used for tests of model quality internal to GARP (intrinsic testing data).
Occurrence points were divided randomly into three parts: extrinsic testing data (50%), used for model evaluation; training data (25%), used for model development; intrinsic testing data (25%), used for intrinsic evaluation and tuning of model rules.
Occurrence data are used as follows: 50% of occurrence data points are set aside for an independent test of model quality (extrinsic testing data), 25% are used for developing models (training data), and 25% are used for tests of model quality internal to GARP (intrinsic testing data).
For species or subspecies for which fewer than 10 distribution points were available (which would have a weak extrinsic test of model quality) we developed 20 replicate models based on all points available and summed them as a "best" distribution hypothesis.
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