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Monte Carlo sampling

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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
..., the response surface method, and Monte Carlo sampling. A brief introduction to importance sampling, time-variant reliability, system reliability, and risk analysis and target reliabilities is also provided. The article examines the various application problems for which probabilistic analysis is an essential...
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
..., as discussed in the following section. The Monte Carlo sampling method is popular in industry. Because it involves repeated sampling of the output based on randomly generated input, it is suitable for computer experimentation, but it is very inefficient. However, it can be useful for situations in which...
Series: ASM Handbook
Volume: 22A
Publisher: ASM International
Published: 01 December 2009
DOI: 10.31399/asm.hb.v22a.a0005401
EISBN: 978-1-62708-196-2
.... , and Semiatin S.L. , “3D Monte-Carlo Simulation of Texture-Controlled Grain Growth,” Acta Mater. , 2003 , Vol 51 , pp. 1019 – 1034 . 26. Abbruzzese G. and Lücke K. , “A Theory of Texture Controlled Grain Growth—Derivation and General Discussion of the Model,” Acta Metall. , 1986...
Series: ASM Handbook
Volume: 22A
Publisher: ASM International
Published: 01 December 2009
DOI: 10.31399/asm.hb.v22a.a0005428
EISBN: 978-1-62708-196-2
... represent stored energies that arise in the case of deformed structures and so provide a driving force for recrystallization. Microstructural evolution is simulated by using a Monte Carlo method to sample different states of the system. The method is extremely simple in principle: Choose...
Series: ASM Handbook
Volume: 22A
Publisher: ASM International
Published: 01 December 2009
DOI: 10.31399/asm.hb.v22a.a0005410
EISBN: 978-1-62708-196-2
.... , and Sigli C. , Nucleation of Al 3 Zr and Al 3 Sc in Aluminum Alloys: From Kinetic Monte Carlo Simulations to Classical Theory , Phys. Rev. B , 69 , 2004 , p 064109 18. Soisson F. and Martin G. , Monte-Carlo Simulations of the Decomposition of Metastable Solid Solutions...
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
... the grayness. These involve probabilistic methods such as Monte Carlo-Potts (MC-P) or cellular automata (CA) in which the consequences of using certain selection rules for the evolution of a microstructure can be computed and pictorially represented for comparison with observed microstructures. Local...
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
... Turbine Components,” SAND94-2460, Sandia National Laboratories , Nov 1994 56. Rubenstein R.Y. , Simulation and the Monte Carlo Method , John Wiley & Sons , 1981 10.1002/9780470316511 57. Melchers R.E. , Structural Reliability Analysis and Prediction , Ellis Horwood...
Series: ASM Handbook
Volume: 11
Publisher: ASM International
Published: 15 January 2021
DOI: 10.31399/asm.hb.v11.a0006770
EISBN: 978-1-62708-295-2
... accelerating voltages and lower atomic number compositions, the interaction area can be substantially larger. Fig. 8 Monte-Carlo-predicted interaction volume Often it is not possible in failure investigations to polish the sample. Many times, the desire is to examine the surface of a sample...
Series: ASM Handbook
Volume: 22A
Publisher: ASM International
Published: 01 December 2009
DOI: 10.31399/asm.hb.v22a.a0005432
EISBN: 978-1-62708-196-2
... that distinguish CA simulations (and other representational simulations such as Monte Carlo simulations) from mean field analytical models and models employing a homogeneous effective medium. This article examines how CA can be applied to the simulation of static and dynamic recrystallization. It describes...
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
.... Hammersley J.M. and Handscomb D.C. , Monte Carlo Methods , Chapman and Hall , London , 1964 32. Saliby E. , Descriptive Sampling: A Better Approach to Monte Carlo Simulation , J. Oper. Res. Soc. , Vol 41 ( No. 12 ), 1990 , p 1133 – 1142 33. Hasofer A.M...
Series: ASM Handbook
Volume: 14B
Publisher: ASM International
Published: 01 January 2006
DOI: 10.31399/asm.hb.v14b.a0005169
EISBN: 978-1-62708-186-3
...; friction factor; strain-rate sensitivity exponent M bending moment mA milliampere max maximum MC Monte Carlo MCS Monte Carlo step MDO multidisciplinary optimization MDOL multidisciplinary design optimization language MDRX metadynamic recrystallization...
Series: ASM Handbook
Volume: 10
Publisher: ASM International
Published: 15 December 2019
DOI: 10.31399/asm.hb.v10.a0006637
EISBN: 978-1-62708-213-6
... predicted in 1912 ( Ref 11 ). In 1963, channeling was accidently observed through Monte Carlo simulations ( Ref 12 , 13 ), which immediately triggered intensive experimental and modeling studies ( Ref 14 , 15 ). In 1965, the systematic channeling theory was developed ( Ref 16 ). Ion channeling has...
Series: ASM Handbook
Volume: 22A
Publisher: ASM International
Published: 01 December 2009
DOI: 10.31399/asm.hb.v22a.a0005434
EISBN: 978-1-62708-196-2
.... The article mainly focuses on phenomena and modeling approaches that are specific to VPP; however, most of the complementary information needed on general or specialized topics of interest (nucleation, microstructure evolution, Monte Carlo methods, etc.) is found in the cited references or in other articles...
Series: ASM Handbook
Volume: 10
Publisher: ASM International
Published: 15 December 2019
DOI: 10.31399/asm.hb.v10.a0006668
EISBN: 978-1-62708-213-6
... , J. Phys. D. Appl. Phys. , Vol 5 (No. 1 ), Jan 1972 , p 308 10.1088/0022-3727/5/1/308 26. Demers H. et al. , Three-Dimensional Electron Microscopy Simulation with the CASINO Monte Carlo Software , Scanning , Vol 33 (No. 3 ), May 2011 , p 135 – 146 , 10.1002/sca.20262...
Series: ASM Handbook
Volume: 22A
Publisher: ASM International
Published: 01 December 2009
DOI: 10.31399/asm.hb.v22a.a0005422
EISBN: 978-1-62708-196-2
... of boundary junctions on grain growth. Various models have been used for the simulation of grain-boundary migration and related phenomena, in particular, grain growth and recrystallization, notably Monte Carlo ( Ref 1 , Ref 2 , Ref 3 , Ref 4 ), phase field ( Ref 5 , 6 ), and network models ( Ref 7...
Series: ASM Handbook
Volume: 10
Publisher: ASM International
Published: 15 December 2019
DOI: 10.31399/asm.hb.v10.a0006660
EISBN: 978-1-62708-213-6
... the sample perpendicular to the tilt axis, as shown in Fig. 6(b) . Due to the high sample tilt, the resolution parallel and perpendicular to the tilt axes is different. Fig. 6 Monte Carlo electron trajectory simulations for 20 kV primary beam energy. (a) Simulations of the backscattered electron...
Series: ASM Handbook
Volume: 22A
Publisher: ASM International
Published: 01 December 2009
DOI: 10.31399/asm.hb.v22a.a0005459
EISBN: 978-1-62708-196-2
... (Avrami) models, topological models, and last, mesoscale physics-based models. Additional related information on the general formulation of models for microstructure evolution is contained in the articles “Models of Recrystallization,”  “Cellular Automaton Models of Recrystallization,”  “Monte Carlo...
Series: ASM Handbook Archive
Volume: 11
Publisher: ASM International
Published: 01 January 2002
DOI: 10.31399/asm.hb.v11.a0003512
EISBN: 978-1-62708-180-1
..., including coating degradation, is excessive. Grain-boundary attack and/or pitting by oxidation/hot corrosion, is excessive. Foreign object damage is severe. Destructive sampling and testing indicate life exhaustion. Excessive deformation has occurred due to creep, causing distortion...
Series: ASM Handbook
Volume: 22A
Publisher: ASM International
Published: 01 December 2009
DOI: 10.31399/asm.hb.v22a.a0005429
EISBN: 978-1-62708-196-2
.... , and Olmsted D.L. , Prediction of Dislocation Cores in Aluminum from Density Functional Theory , Phys. Rev. Lett. , Vol 100 , 2008 , p 045507 11. Foulkes W.M.C. , Mitáš L. , Needs R.J. , and Rajagopal G. , Quantum Monte Carlo Simulations of Solids , Rev. Mod. Phys. , Vol...
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