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uncertainty

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Series: ASM Handbook
Volume: 22B
Publisher: ASM International
Published: 01 November 2010
DOI: 10.31399/asm.hb.v22b.a0005534
EISBN: 978-1-62708-197-9
... Abstract This article presents an approach to manage the uncertainty present in materials design. It describes inductive and deductive approaches to deal with uncertainty. The article focuses on providing an understanding of the opportunities for managing uncertainty and the decisions...
Series: ASM Handbook
Volume: 10
Publisher: ASM International
Published: 15 December 2019
DOI: 10.31399/asm.hb.v10.a0006634
EISBN: 978-1-62708-213-6
... and subsequently analyzing the uncertainty from both the calibration process and the measurement process. This article briefly summarizes the most common calibration and uncertainty analysis methods, namely external standard methods, abbreviated external standard methods, internal normalization, internal standard...
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Published: 01 November 1995
Fig. 10 Sources of uncertainty in impact testing More
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Published: 01 January 2000
Fig. 56 Allowable uncertainty More
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Published: 01 December 2009
Fig. 5 Types of error. (a) Noise. (b) Uncertainty More
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Published: 01 December 2009
Fig. 6 Illustration of the uncertainty in defining a fitting function in regions where data are sparse (B) or where they are noisy (A). Three possible functions are shown. More
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Published: 01 December 2009
Fig. 8 Predictions represented by the uncertainty range, and experimental data presented as points. The model responsible for the predictions was trained only on steel data. (a) A bearing steel not included in the data used for training the model. (b) A nickel based alloy Udimet 700. (b More
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Published: 01 August 2018
Fig. 47 Crack indication and edge indication uncertainty in a connecting rod. Courtesy of Y.F. Cheu, General Motors Technical Center More
Series: ASM Handbook
Volume: 19
Publisher: ASM International
Published: 01 January 1996
DOI: 10.31399/asm.hb.v19.a0002369
EISBN: 978-1-62708-193-1
... Abstract There are two parts to deal with uncertainty in fatigue design: determining the distributions of possible values for all uncertain inputs and calculating the probability of failure due to all the uncertain inputs. This article discusses the sources of uncertainty in a fatigue analysis...
Series: ASM Handbook
Volume: 11A
Publisher: ASM International
Published: 30 August 2021
DOI: 10.31399/asm.hb.v11A.a0006803
EISBN: 978-1-62708-329-4
... definitions, how uncertainty is quantified, and input for the associated random variables, as well as the characterization of the response uncertainty. Next, it focuses on specific and generic uncertainty propagation techniques: first- and second-order reliability methods, the response surface method...
Series: ASM Handbook
Volume: 1
Publisher: ASM International
Published: 01 January 1990
DOI: 10.31399/asm.hb.v01.a0001038
EISBN: 978-1-62708-161-0
... conditions of actual parts; variations in manufacturing processes such as bending, forming, and welding; and the uncertainty of environmental and loading conditions in service. carbon steels fatigue behavior fatigue data fatigue failure fatigue resistance low-alloy steels metallurgical variables...
Series: ASM Handbook
Volume: 6A
Publisher: ASM International
Published: 31 October 2011
DOI: 10.31399/asm.hb.v06a.a0005636
EISBN: 978-1-62708-174-0
... welding. The article presents the mathematical equations of mass, momentum, energy, and species conservation. It reviews the applications of heat transfer and fluid flow models for different welding processes. Finally, the article discusses the approaches to improve reliability of, and reduce uncertainty...
Series: ASM Handbook Archive
Volume: 11
Publisher: ASM International
Published: 01 January 2002
DOI: 10.31399/asm.hb.v11.a0003514
EISBN: 978-1-62708-180-1
... Abstract This article describes the historical background, uncertainties in structural parameters, classifications, and application areas of probabilistic analysis. It provides a discussion on the basic definition of random variables, some common distribution functions used in engineering...
Series: ASM Handbook
Volume: 22A
Publisher: ASM International
Published: 01 December 2009
DOI: 10.31399/asm.hb.v22a.a0005416
EISBN: 978-1-62708-196-2
... in modeling noise and uncertainties in conducting experiments. The article also presents examples of the application of neural-network modeling to the behavior of metals. neural network modeling modeling noise overfitting uncertainty EMPIRICAL METHODS are regarded as less desirable than those...
Series: ASM Handbook
Volume: 17
Publisher: ASM International
Published: 01 August 2018
DOI: 10.31399/asm.hb.v17.a0006463
EISBN: 978-1-62708-190-0
..., the mathematical methods to obtain a POD curve, and techniques to assess uncertainty in the POD curve as it is obtained from a limited data set. The concept of model-assisted POD (MAPOD) is introduced, with additional details and representative examples of MAPOD. process modeling non-destructive evaluation...
Series: ASM Handbook
Volume: 20
Publisher: ASM International
Published: 01 January 1997
DOI: 10.31399/asm.hb.v20.a0002431
EISBN: 978-1-62708-194-8
... the basic statistical procedures that can be used to address variability and uncertainty in an engineering analysis. It contains a table that lists the relevant statistics standards published by the American Society of Testing and Materials. data-regression dscrete distributions goodness-of-fit test...
Series: ASM Handbook
Volume: 10
Publisher: ASM International
Published: 15 December 2019
DOI: 10.31399/asm.hb.v10.a0006638
EISBN: 978-1-62708-213-6
... spectrometry for electron probe microanalysis. Key concepts for performing qualitative analysis and quantitative analysis by electron-excited X-ray spectrometry are then presented. Several sources that lead to measurement uncertainties in the k-ratio/matrix corrections protocol are provided, along...
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Published: 01 January 1997
Fig. 8 Approximate confidence limits on a cumulative distribution function showing uncertainty in the mean and standard deviation More
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Published: 15 December 2019
Fig. 2 An example of a single-point calibration curve. The instrument response is represented by A , and the concentration resulting in that response is [ A ]. The origin (0,0) is assigned as part of the curve, and is assumed to have no uncertainty. More
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Published: 01 January 1996
Fig. 14 Variation in the log of the standard deviation in fatigue strength in ksi with fatigue notch factor ( K f ). The uncertainty in the fatigue strength of terminations would seem to be generally less than that of the toe and ripple. More