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regression algorithm

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Series: ASM Handbook
Volume: 21
Publisher: ASM International
Published: 01 January 2001
DOI: 10.31399/asm.hb.v21.a0003386
EISBN: 978-1-62708-195-5
... the implementation of a damage tolerance analysis methodology in terms of the mechanics based model, the regression algorithm, and the semi-empirical analysis. References References 1. “Proposed Issuance of Policy Memorandum, Material Qualification and Equivalency for Polymer Matrix Composite Material...
Series: ASM Handbook
Volume: 22A
Publisher: ASM International
Published: 01 December 2009
DOI: 10.31399/asm.hb.v22a.a0005407
EISBN: 978-1-62708-196-2
... Regression Analysis and Neural Network-Based Approaches , J. Mater. Process. Technol. , 184 ( 1–3 ), 2007 , p 56 – 68 10.1016/j.jmatprotec.2006.11.004 32. Kutuk M.A. , Atmaca N. , and Guzelbey I.H. , Explicit Formulation of SIF Using Neural Networks for Opening Mode of Fracture...
Series: ASM Handbook
Volume: 20
Publisher: ASM International
Published: 01 January 1997
DOI: 10.31399/asm.hb.v20.a0002476
EISBN: 978-1-62708-194-8
... function for tensile strength. It reviews life prediction reliability models used for predicting the life of a component with complex geometry and loading. The article outlines reliability algorithms and presents several applications to illustrate the utilization of these reliability algorithms...
Series: ASM Handbook
Volume: 24
Publisher: ASM International
Published: 15 June 2020
DOI: 10.31399/asm.hb.v24.a0006568
EISBN: 978-1-62708-290-7
... , 2002 , p 107 10.1118/1.1455742 43. Soleimani M. and Pengpen T. , Introduction: A Brief Overview of Iterative Algorithms in X-Ray Computed Tomography , Philos. Trans. R. Soc. A, Math. Phys. Eng. Sci. , Vol 373 , 2015 , p 20140399 10.1098/rsta.2014.0399 44. Dowd B.A...
Series: ASM Handbook
Volume: 4A
Publisher: ASM International
Published: 01 August 2013
DOI: 10.31399/asm.hb.v04a.a0005796
EISBN: 978-1-62708-165-8
Series: ASM Handbook
Volume: 22B
Publisher: ASM International
Published: 01 November 2010
DOI: 10.31399/asm.hb.v22b.a0005544
EISBN: 978-1-62708-197-9
.... LAMMPS features parallelism via a spatial decomposition algorithm; short-range pairwise Lennard-Jones and Coulombic interactions; long-range Coulombic interactions via Ewald or particle-mesh Ewald; harmonic molecular potentials; class II molecular potentials; NVE, NVT, and NPT dynamics; constraints...
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
... Y.-T. and Wirsching P. , New Algorithm for Structural Reliability Estimation , J. Eng. Mech. , Vol 113 , 1987 , p 1319 – 1336 10.1061/(ASCE)0733-9399(1987)113:9(1319) 12. Metropolis N. and Ulam S. , The Monte Carlo Method , J. Am. Stat. Assoc. , Vol 44 , 1949 , p...
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
... by a linear regression on the logarithms of the data: (Eq 3) ln ( N ) = ln ( C 0 ) + ( − b 0 ) ln ( S ) solving for the slope, − b 0 , and intercept, ln( C 0 ). The result is a good estimate of the median curve, because a best fit will, on average, result in half...
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
.... , and Sudjianto A. , Algorithmic Construction of Optimal Symmetric Latin Hypercube Designs , J. Stat. Plan. Infer. , Vol 90 , 2000 , p 145 – 159 46. Meckesheimer M. , Barton R.R. , Simpson T.W. , Limagem F. , and Yannou B. , Metamodeling of Combined Discrete/Continuous...
Book Chapter

By S. Lampman
Series: ASM Handbook
Volume: 10
Publisher: ASM International
Published: 15 December 2019
DOI: 10.31399/asm.hb.v10.a0006645
EISBN: 978-1-62708-213-6
...., Handbook of X-Ray Spectrometry , CRC Press , 2001 36. Sherman J. , Theoretical Derivation of Fluorescent X-Ray Intensities from Mixtures , Spectrochim. Acta , Vol 7 , 1955 , p 283 – 306 10.1016/0371-1951(55)80041-0 37. Rousseau R.M. , The Quest for a Fundamental Algorithm...
Series: ASM Handbook
Volume: 4A
Publisher: ASM International
Published: 01 August 2013
DOI: 10.31399/asm.hb.v04a.a0005814
EISBN: 978-1-62708-165-8
... as a function of time during quenching in water at 60 °C (140 °F). Data (symbols); linear regression (line). (b) Wetting front velocity as a function of water temperature. Source: Ref 36 Fig. 14 Rewetting behavior at different times for horizontal (top row) and vertical (bottom row) ring...
Series: ASM Handbook
Volume: 17
Publisher: ASM International
Published: 01 August 2018
DOI: 10.31399/asm.hb.v17.a0006439
EISBN: 978-1-62708-190-0
.... , Computer Vision , North-Holland , 1982 • Davies E.R. , Computer and Machine Vision: Theory, Algorithms, Practicalities , 4th ed , Academic Press , 2012 • Faugeras O. , Fundamentals of Computer Vision , Cambridge University Press , 1983 • Hollingum J. , Machine...
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
.... Gelman A. and Hill J. , Data Analysis Using Regression and Multilevel/Hierarchical Models , Cambridge University Press , 2007 50. Rummel W.D. and Matzkanin G.A. , Nondestructive Evaluation Capabilities Data Book , 3rd ed. , Defense Technical Information Center , 1997...
Series: ASM Handbook
Volume: 14A
Publisher: ASM International
Published: 01 January 2005
DOI: 10.31399/asm.hb.v14a.a0004027
EISBN: 978-1-62708-185-6
... Issue, Vol 32 ( No. 3 ), 1992 , p 261 – 449 15. Somani M.C. , Karjalainen L.P. , Porter D.A. , and Morgridge R.A. , Regression Modeling of the Recrystallization Kinetics of Austenite , Int. Conf. on Thermomechanical Processing: Mechanics, Microstructure and Control...
Series: ASM Handbook
Volume: 17
Publisher: ASM International
Published: 01 August 2018
DOI: 10.31399/asm.hb.v17.a0006438
EISBN: 978-1-62708-190-0
..., infrared; UV, ultraviolet; UT, ultrasonic testing; EMAT, electromagnetic acoustic transducer; ET, electromagnetic testing; ACFM, alternating current field measurement; PEC, pulsed eddy current; RT, radiographic testing Fig. 2 Phased array UT depth sizing regression (in mm) for dissimilar metal...
Series: ASM Handbook
Volume: 22B
Publisher: ASM International
Published: 01 November 2010
DOI: 10.31399/asm.hb.v22b.a0005540
EISBN: 978-1-62708-197-9
... forming and springback analysis: the type of solution algorithm/governing equation and the type of element. The article provides information on various models for material yield criteria. finite element methods friction sheet metal forming springback analysis SOFTWARE PROGRAMS continue...
Series: ASM Handbook
Volume: 10
Publisher: ASM International
Published: 15 December 2019
DOI: 10.31399/asm.hb.v10.a0006640
EISBN: 978-1-62708-213-6
... to improve with each additional free parameter, but with too few calibration samples, the results can be incorrect or even nonsensical. What happens is the calibration algorithm begins to fit noise into the spectra rather than elemental information. To alleviate this problem, most OES regression software...
Series: ASM Handbook
Volume: 10
Publisher: ASM International
Published: 15 December 2019
DOI: 10.31399/asm.hb.v10.a0006632
EISBN: 978-1-62708-213-6
... algorithms, severe preferred orientation causing variation in the elastic constants with ψ, and/or nonuniform stress in the irradiated area varying with ψ. In such cases, simply fitting a straight line by linear regression to the data will not produce a valid result. In XRD residual-stress measurement...
Series: ASM Handbook
Volume: 11
Publisher: ASM International
Published: 15 January 2021
DOI: 10.31399/asm.hb.v11.a0006781
EISBN: 978-1-62708-295-2
... / dN , and Δ J : (Eq 29) da dN = C ( Δ J ) q where C and q are material parameters that are obtained from regression of the fatigue crack growth data. Also, under elastic conditions, the following relationship holds ( Ref 11 , 12 , 31 ): (Eq 30) Δ J = Δ K 2 E...
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
... components to design for appropriate levels of safety. Computational resources are becoming less of an impediment through enhancements in computational algorithms and computer efficiency. Factor of safety approaches may not give the desired reliability or may lead to overdesigned structures...