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Arrhenius model

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Published: 15 May 2022
Fig. 23 Shift factors relative to 15 °C (59 °F) with Arrhenius model employed to fit shift factor data More
Series: ASM Handbook
Volume: 11B
Publisher: ASM International
Published: 15 May 2022
DOI: 10.31399/asm.hb.v11B.a0006921
EISBN: 978-1-62708-395-9
... the hydrostatic design basis approach, Miner's rule, the Arrhenius model, and the Paris Law for fatigue crack propagation, are discussed. accelerated testing Arrhenius model chemical degradation environmental stress cracking fatigue crack propagation Miner's rule Paris law polymeric materials...
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Published: 01 June 2016
Fig. 21 Calibration of isothermal aging model. (a) Arrhenius plot to find the activation energy, Q . (b) Plot to find T s and ( S 0 ) max based on the temperature dependence of the volume fraction of the precipitate. Data from 6061. Source: Ref 65 More
Series: ASM Handbook
Volume: 11B
Publisher: ASM International
Published: 15 May 2022
DOI: 10.31399/asm.hb.v11B.a0006930
EISBN: 978-1-62708-395-9
... viscous and elastic properties. Thus, models that represent the behavior of plastics need to incorporate viscous along with elastic behavior. Two of the models used for such studies are the Maxwell model ( Fig. 3a ) and the Kelvin–Voigt model ( Fig. 3b ). The Maxwell model consists of a spring...
Series: ASM Handbook
Volume: 11B
Publisher: ASM International
Published: 15 May 2022
DOI: 10.31399/asm.hb.v11B.a0006909
EISBN: 978-1-62708-395-9
... degradation processes (e.g., thermooxidation); mass is measured as a function of time at constant temperature. Service Life Prediction The Arrhenius equation, which describes the relation between rate of reaction and temperature, is one of the best-known models for assessing the lifetime of polymers...
Series: ASM Handbook
Volume: 22A
Publisher: ASM International
Published: 01 December 2009
DOI: 10.31399/asm.hb.v22a.a0005430
EISBN: 978-1-62708-196-2
... Abstract Diffusion is the process by which molecules, atoms, ions, point defects, or other particle types migrate from a region of higher concentration to one of lower concentration. This article focuses on the diffusivity data and modeling of lattice diffusion in solid-state materials...
Series: ASM Handbook
Volume: 22A
Publisher: ASM International
Published: 01 December 2009
DOI: 10.31399/asm.hb.v22a.a0005425
EISBN: 978-1-62708-196-2
... Abstract This article provides a brief historical perspective, a classification of metallurgical processes, basic model development efforts, and an overview of the potential future directions for the modeling of metals processing. It describes the classification of material behavior models...
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
... such as the Solver routine in Microsoft Excel. Grain-Size Predictions in JMAK Modeling Similar combinations of Arrhenius and power laws are used in JMAK models to quantify the dependence of recrystallized grain size on process variables and the initial grain size, D 0 . An expression for the recrystallized...
Series: ASM Handbook
Volume: 19
Publisher: ASM International
Published: 01 January 1996
DOI: 10.31399/asm.hb.v19.a0002410
EISBN: 978-1-62708-193-1
... oxide cracking would not be modeled well by the Arrhenius equation over all temperature ranges. Fig. 6 Effects of temperature on FCP rates of René 95 for constant Δ K. Source: Ref 61 Not all temperature-dependent increases in FCP rates can be modeled with Arrhenius-type equations...
Series: ASM Handbook
Volume: 22A
Publisher: ASM International
Published: 01 December 2009
DOI: 10.31399/asm.hb.v22a.a0005403
EISBN: 978-1-62708-196-2
... dynamic recrystallization (DDRX). The article discusses the assumptions and simplifications for the Avrami analysis. It describes the effects of nucleation and growth rates on recrystallization kinetics and recrystallized grain size based on the Johnson-Mehl-Avrami-Kolmogorov model for static...
Series: ASM Handbook
Volume: 13A
Publisher: ASM International
Published: 01 January 2003
DOI: 10.31399/asm.hb.v13a.a0003589
EISBN: 978-1-62708-182-5
... it becomes:) ∇ C i = i (∂ C i / ∂ x ), and D i is the proper diffusion coefficient, cm 2 /s. The term “proper” means the necessity of the careful examination of the process (experiment) and model of mass transport before using diffusivity data. To model the oxidation processes (i.e., the reactive...
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
... damage mechanisms and elucidate mechanism coupling interactions. In addition, life modeling in TMF conditions and a practical application of TMF life prediction are presented. coupling interactions fatigue life prediction thermomechanical fatigue THERMOMECHANICAL FATIGUE (TMF) is the general...
Series: ASM Handbook
Volume: 10
Publisher: ASM International
Published: 15 December 2019
DOI: 10.31399/asm.hb.v10.a0006661
EISBN: 978-1-62708-213-6
... = k − 1 β Θ n Desorption follows an Arrhenius behavior, so: (Eq 4) k − 1 = A e − E d R T where A is the pre-exponential factor for first-order desorption, E d is the activation energy, and R is the ideal gas constant. Combining...
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
..., distributing nuclei of recrystallized grains, growing the recrystallized grains, and updating the dislocation density. The article concludes with information on the developments in CA simulations. cellular automaton model static recrystallization dynamic recrystallization microstructure dislocation...
Series: ASM Handbook
Volume: 22B
Publisher: ASM International
Published: 01 November 2010
DOI: 10.31399/asm.hb.v22b.a0005503
EISBN: 978-1-62708-197-9
... strain-rate viscosity data, binder viscosity is obtained by curve fitting to a Newtonian binder viscosity model (η b ) with temperature ( T ) dependency: (Eq 12) η b = B b exp ( T b , b T ) where B b is the constant amplitude, and T b,b is an Arrhenius...
Series: ASM Handbook
Volume: 20
Publisher: ASM International
Published: 01 January 1997
DOI: 10.31399/asm.hb.v20.a0002477
EISBN: 978-1-62708-194-8
...) temperature dependence when available. If this advanced model is not available, the Arrhenius model is employed. Mold and melt temperatures can be chosen if default values are not adequate. The mold geometry is defined in terms of a nominal wall thickness and cavity radius that can be calculated by entering...
Series: ASM Handbook
Volume: 22B
Publisher: ASM International
Published: 01 November 2010
DOI: 10.31399/asm.hb.v22b.a0005507
EISBN: 978-1-62708-197-9
... discussed. atomistic modeling crystallographic orientation grain boundaries GRAIN BOUNDARIES are interfaces between crystallites of the same phase but different crystallographic orientation, that is, different spatial orientation of the crystallographic unit cell. At the same time...
Series: ASM Handbook
Volume: 21
Publisher: ASM International
Published: 01 January 2001
DOI: 10.31399/asm.hb.v21.a0003402
EISBN: 978-1-62708-195-5
... media methods. The article presents an overview of the modeling philosophy and approach that is useful in describing composite manufacturing processes. composite processing short-fiber suspension method squeeze flow method porous media method process modeling POLYMER COMPOSITES have been...
Series: ASM Handbook
Volume: 13B
Publisher: ASM International
Published: 01 January 2005
DOI: 10.31399/asm.hb.v13b.a0003842
EISBN: 978-1-62708-183-2
... can be introduced to more accurately model a real application. High-velocity, hydrocarbon-fueled burner rigs subject potential engine materials to an environment that closely approximates actual operating conditions. After these exposures, samples are typically analyzed with a variety of techniques...
Series: ASM Handbook
Volume: 22A
Publisher: ASM International
Published: 01 December 2009
DOI: 10.31399/asm.hb.v22a.a0005408
EISBN: 978-1-62708-196-2
... of the thermomechanical production of aluminum sheet and, in particular, highlights the main effects governing the evolution of microstructure and texture. The simulation tools used to model the evolution of microchemistry, microstructure, and texture upon deformation and recrystallization of aluminum alloys...