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experimental uncertainty

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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
..., standard addition, and serial dilution methods. In addition, it includes information on the traceability of true value of a measured quantity. external standard methods abbreviated external standard methods calibration experimental uncertainty instruments internal normalization method internal...
Image
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
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
... it is needed, the history behind the development of POD, how POD assessments are performed, and how modeling and simulation can be integrated into the execution of a POD assessment. It describes the methods by which POD is determined. This includes detail on the experimental process to acquire the needed data...
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
... because the decisions are made under considerable uncertainty. In general, the earlier the uncertainty is introduced, the greater its impact will be on the final result. Therefore, it is especially important to focus on choosing a tolerable amount of uncertainty in the early stages of experimentation...
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
... linear and the other nonlinear ( Ref 6 ): (Eq 3) y = − x 3 / 44 + 3 x 2 / 11 + 34 / 11 Fig. 5 Types of error. (a) Noise. (b) Uncertainty Both of the functions illustrated reproduce these experimental data precisely but behave quite differently...
Image
Published: 01 December 2009
Fig. 7 Comparison of the predictions of a neural-network model (central curve) with experimental data that were not included in the creation of the model. The modeling uncertainty is indicated by the upper and lower error bounds (broken lines). Source: Ref 6 , 8 More
Series: ASM Handbook
Volume: 22B
Publisher: ASM International
Published: 01 November 2010
DOI: 10.31399/asm.hb.v22b.a0005514
EISBN: 978-1-62708-197-9
... be particularly difficult if there is a high-temperature phase transition (which is frequently the case for commercial materials). The experimental uncertainties in enthalpy H T − H 298 are estimated to be ±1 to 2%. Microsecond Heating This technique is also known as pulse heating or explosive...
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
..., the uncertainty distribution is constructed by gathering a sample of potential values for the variable of interest, either numerically or experimentally. The results can be represented as a vector: O = ( o 1 , o 2 , … , o M ) where o i represents the i th observation, and M...
Series: ASM Handbook
Volume: 19
Publisher: ASM International
Published: 01 January 1996
DOI: 10.31399/asm.hb.v19.a0002367
EISBN: 978-1-62708-193-1
... Abstract This article examines the factors influencing the fatigue behavior of an individual weldment, using extensive experimental data and a computer model, which simulates the fatigue resistance of weldments. It discusses the process of fatigue in weldments. The service conditions, which...
Series: ASM Handbook Archive
Volume: 10
Publisher: ASM International
Published: 01 January 1986
DOI: 10.31399/asm.hb.v10.a0001727
EISBN: 978-1-62708-178-8
... on sample quality. A poorly devised sampling plan or uncertainties in the sampling process, in sample storage, preservation, or pretreatment may obscure results or prevent their interpretation. This article will primarily consider the problem of sampling bulk materials, including minerals, metals...
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...
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
... decreases significantly as more experimentation and analysis work is done. This uncertainty is commonly described in terms of confidence limits, tolerance limits, or prediction limits. Each of these limits are quantified in statistical terms later in this discussion. Variability is an important element...
Series: ASM Handbook
Volume: 22A
Publisher: ASM International
Published: 01 December 2009
DOI: 10.31399/asm.hb.v22a.a0005438
EISBN: 978-1-62708-196-2
... be found in the appropriate references. There is an intrinsic interplay between model building and experimental data development for calibration, verification, and validation purposes. This interplay is best represented by the Sargent circle in Fig. 1 . The first step involves the development...
Series: ASM Handbook
Volume: 8
Publisher: ASM International
Published: 01 January 2000
DOI: 10.31399/asm.hb.v08.a0003274
EISBN: 978-1-62708-176-4
... the entire hardness-load curve, but in practice testers often chose one reference or standard load to allow comparisons between materials. It is preferable to make the indentations as large as possible to reduce measurement uncertainties, yet not so large as to induce excessive cracking that interferes...
Series: ASM Handbook
Volume: 22B
Publisher: ASM International
Published: 01 November 2010
DOI: 10.31399/asm.hb.v22b.a0005505
EISBN: 978-1-62708-197-9
... ) , i = 1 , 2 , … , N A good example of a single-objective material-processing application is data matching (also know as model fitting or parameter estimation), shown in Fig. 2 . Here, the objective is to minimize an error function between a parametric model and experimental data...
Series: ASM Handbook
Volume: 20
Publisher: ASM International
Published: 01 January 1997
DOI: 10.31399/asm.hb.v20.a0002468
EISBN: 978-1-62708-194-8
..., can be grouped into: Uncertainties associated with material properties due to variations in composition, heat treatment, and processing conditions as well as environmental variables such as temperature, time, humidity, and ambient chemicals. Manufacturing processes also contribute...
Series: ASM Handbook
Volume: 4C
Publisher: ASM International
Published: 09 June 2014
DOI: 10.31399/asm.hb.v04c.a0005885
EISBN: 978-1-62708-167-2
... to experimentally evaluate the austenitization process for steels using various compositions, microstructures, heating rates, and heating methods. Some of the most comprehensive are the studies of Orlich et al. ( Ref 7 , 8 ), who evaluated the austenitization kinetics of a wide range of steel alloys as a function...
Series: ASM Handbook
Volume: 22B
Publisher: ASM International
Published: 01 November 2010
DOI: 10.31399/asm.hb.v22b.a0005537
EISBN: 978-1-62708-197-9
... in a production environment. aerospace components aircraft engine finite-element analysis machining residual stress residual stress analysis THE INSERTION OF NEW MATERIALS into aircraft systems takes several years and many millions of dollars. Experimental trials to define the manufacturing...
Series: ASM Handbook
Volume: 22A
Publisher: ASM International
Published: 01 December 2009
DOI: 10.31399/asm.hb.v22a.a0005402
EISBN: 978-1-62708-196-2
... compositions in each of the single phases does not add up to 100%. The difference is the oxygen contents, also measured experimentally. The measured compositions of (Mg) had large uncertainties, since they were obtained from energy-dispersive spectroscopy. Using the measured contents of the metals, the ranges...
Series: ASM Handbook
Volume: 8
Publisher: ASM International
Published: 01 January 2000
DOI: 10.31399/asm.hb.v08.a0009218
EISBN: 978-1-62708-176-4
... to experimental curves will, in general, yield slightly different values of ε ˙ m than graphical measurement, this difference is insignificant compared to the overall uncertainty in creep strain/time predictions. Techniques for analysis of minimum creep rate data are similar to those used for rupture...