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Published: 01 December 2004
Fig. 20 Disector sampling method for estimation of number density of tungsten grains in the 3-D microstructure of liquid phase sintered W-Ni-Fe alloy. The three grains in (a) at the arrows are sampled by the unbiased counting frame, which are not present in the second disector plane segment More
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Published: 01 December 2009
Fig. 5 Total number density of all voids in an Al-Mg-Cu-Mn superplastic alloy as a function of strain at various temperatures and strain rates, showing that voids nucleate continuously during deformation More
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Published: 01 December 2009
Fig. 12 Comparison of (a) measured number density of surface cracks of different lengths in low-cycle fatigue of polycrystalline martensitic-ferritic steel (Source: Ref 72 ) with (b) predicted distribution, assuming initial crack size of 10 μm in each grain, propagated using the fatigue More
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Published: 01 January 1996
Fig. 16 Microcrack density in dependence on relative number of cycles in α-iron for two strain amplitudes. ε a , strain amplitude; N , number of cycles; N f , number of cycles to fracture More
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Published: 01 December 2009
Fig. 33 Load density and number of parts affecting quenchant flow around parts in a production quench tank More
Series: ASM Handbook
Volume: 9
Publisher: ASM International
Published: 01 December 2004
DOI: 10.31399/asm.hb.v09.a0003759
EISBN: 978-1-62708-177-1
... Abstract The objective of quantitative metallography/stereology is to describe the geometric characteristics of the features. This article discusses the geometric attributes of microstructural features that can be divided into: the numerical extents and the number density of microstructural...
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Published: 01 October 2014
Fig. 11 Variation in microhardness as a function of aging time and aging temperature due to precipitation strengthening in an experimental copper steel. The microhardness is increasing during nucleation as the number density of the precipitates increases. The microhardness is relatively More
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Published: 15 June 2020
Fig. 12 Histogram binned by size of individually segmented powder particles and pores, overlaying powder and powder porosity size distributions along with the normalized number density of pores, thus showing the correlation between powder size and porosity size More
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Published: 01 January 1990
Fig. 3 Effect of prior deformation and aging time on the amount of T 1 precipitates in aluminum-lithium alloy 2090 (2.4% Li, 2.4% Cu, 0.18% Zr, bal aluminum). (a) Volume fraction of T 1 . (b) Number density of T 1 More
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Published: 01 October 2014
Fig. 10 Copper-rich precipitate morphology as determined from atom probe tomography reconstructions in an iron-copper steel. The precipitates are delineated by 10 at.% Cu isoconcentration surfaces. The increasing precipitate size is depicted as a function of aging time. The change in number More
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Published: 31 October 2011
Fig. 14 Comparison between observed and predicted microstructural stability of Gleeble simulated specimens after various thermal treatments. (a) Variation in particle number density, N v , with distance from centerline of specimen. (b) Variation in mean particle radius, r More
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Published: 01 November 2010
Fig. 17 Comparison of precipitation parameters for a Ni-14Al (at, %) alloy between the predicted values and those determined experimentally. KWN, Kampmann-Wagner model in the numerical framework; 83Wen, Ref 60 . (a) Evolution of the average γ′ particle size. (b) Evolution of the γ′ number More
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Published: 31 October 2011
Fig. 15 Industrial case study showing the sequence of reactions occurring during artificial aging (AA), welding (W), and postweld heat treatment (PWHT) of 5 mm (0.2 in.) AA6005 plate material. (a) Record of thermal history. (b) Predicted change in particle number density, N v More
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Published: 31 October 2011
Fig. 13 Examples of outputs from the precipitation model following prolonged artificial aging at 180 °C (355 °F). (a) Change in nucleation rate, j , and particle number density, N v , with time. (b) Increase in the mean particle radius, r ¯ , and the critical radius, r More
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Published: 01 November 2010
Fig. 13 (a) Image of a cellular automaton simulation of solidification in a Zn-0.2wt%Al galvanized coating. The 5 by 3 mm domain is cooled at –12 K/s with a positive temperature gradient from left to right. (b) Experimental and calculated number densities of grains as a function of the cooling More
Book Chapter

By P.S. Grant
Book: Casting
Series: ASM Handbook
Volume: 15
Publisher: ASM International
Published: 01 December 2008
DOI: 10.31399/asm.hb.v15.a0005225
EISBN: 978-1-62708-187-0
... density distribution on a number basis, with the same superimposed boundaries Deposition and Grain Multiplication When droplets/particles arrive at the mushy preform top surface, some solid particles bounce from the preform surface and are lost as overspray, while substantially liquid droplets...
Book Chapter

By Arun M. Gokhale
Series: ASM Handbook Archive
Volume: 11
Publisher: ASM International
Published: 01 January 2002
DOI: 10.31399/asm.hb.v11.a0003536
EISBN: 978-1-62708-180-1
... is particularly useful for quantitative characterization of specific features (for example, dimples, striations, pores, facets, inclusions, etc.) present in the fracture surface ( Ref 35 , 36 ). The features of interest are characterized via estimation of their number density, average size, shape, spacing...
Book Chapter

Series: ASM Desk Editions
Publisher: ASM International
Published: 01 December 1998
DOI: 10.31399/asm.hb.mhde2.a0003082
EISBN: 978-1-62708-199-3
... include density, linear thermal expansion, thermal conductivity, electrical conductivity, resistivity, and approximate melting temperature. The tables also present approximate equivalent hardness numbers for austenitic steels, nonaustenitic steels, austenitic stainless steel sheet, wrought aluminum...
Book Chapter

Series: ASM Handbook
Volume: 12
Publisher: ASM International
Published: 01 June 2024
DOI: 10.31399/asm.hb.v12.a0007033
EISBN: 978-1-62708-387-4
... by specific fracture micromechanisms, such as ductile fracture, cleavage fracture, intergranular fracture, and fatigue. Once the features of interest are uniquely identified, they can be quantitatively characterized via estimation of their number density, average size, spacing, and area fraction, as well...
Series: ASM Handbook
Volume: 4D
Publisher: ASM International
Published: 01 October 2014
DOI: 10.31399/asm.hb.v04d.a0005962
EISBN: 978-1-62708-168-9
...), as shown in the binary phase diagram in Fig. 1 ( Ref 38 ). The eutectoid temperature is 850 °C. The small maximum solubility combined with a rapidly sloping solvus curve and a concomitant decrease in the solubility limit enables the nucleation of a high number density of copper precipitates in the α-Fe...