Dynamic uniaxial and biaxial stress-strain relationships for austenitic stainless steels

Albertini, C.; Montagnani, M.

doi:10.1016/0029-5493(80)90226-5

Cited by 38 publications

(19 citation statements)

References 4 publications

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“…This is further demonstrated in Fig. 15, which compares model predictions with measurements at elevated temperature by Albertini and Montagnani [30], Conway et al [31], and Steichen [34] (nitrogen content of 0.052 N). As shown in Fig.…”

Section: Modeling the Stress-strain Curvesupporting

confidence: 62%

“…Fig. 12 shows data in 316L stainless steel (nitrogen content wasn't specified) by Albertini and Montagnani [30] compared with model predictions (dashed line). These predictions were made with the model parameters listed in Table 5.…”

Section: Modeling the Stress-strain Curvementioning

confidence: 97%

“…(8) and (12a)Fig. 12Comparisons of the predicted stress strain curves with that measured by Aibertini and iVIontagnani[30] in 316L (ieft Ordinate) and by Conway et ai [31]. (right ordinate) in 316 stainless steei at the specified temperature and strain rate Tabie 5 iViodei parameters selected for comparisons between experiment and model prediction inFigs.…”

mentioning

confidence: 99%

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An Internal State Variable Constitutive Model for Deformation of Austenitic Stainless Steels

Follansbee

2012

Journal of Engineering Materials and Technology

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Austenitic stainless steels-particularly the 304 and 316 families of alloys-exhibit similar trends in the dependence of yield stress on temperature. Analysis of temperature and strain-rate dependent yield stress literature data in alloys with varying nitrogen content and grain size has enabled the definition of two internal state variables characterizing defect populations. The analysis is based on an internal state variable constitutive law termed the mechanical threshold stress model. One of the state variables varies solely with nitrogen content and is characterized with a larger activation volume. The other state variable is characterized by a much smaller activation volume and may represent interaction of dislocations with solute and interstitial atoms. Analysis of the entire stress-strain curve requires addition of a third internal state variable characterizing the evolving stored dislocation density. Predictions of the model are compared to measurements in 304, 304L, 316, and316L stainless steels deformed over a wide range of temperatures (up to one-half the melting temperature) and strain rates. Model predictions and experimental measurements deviate at temperatures above ~600 K where dynamic strain aging has been observed. Application of the model is demonstrated in irradiated 316LN where the defect population induced by irradiation damage is analyzed. This defect population has similarities with the stored dislocation density. The proposed model offers a framework for modeling deformation in stable austenitic stainless steels (i.e., those not prone to a martensitic phase transformation).

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Section: Modeling the Stress-strain Curvesupporting

confidence: 62%

Section: Modeling the Stress-strain Curvementioning

confidence: 97%

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An Internal State Variable Constitutive Model for Deformation of Austenitic Stainless Steels

Follansbee

2012

Journal of Engineering Materials and Technology

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“…Poisson ratio r 1 Outer radius of the balloon r 2 Middle radius of the balloon r 3 Inner radius of the balloon r s Initial inner radius of the stents d 1 Length of the first membrane of the balloon d 2 Length of the second membrane of the balloon d 3 Length of the third membrane of the balloon d f Target balloon diameter L Initial length of the stent L load Longitudinal length of the stent R load central Central radius of the stent R load…”

Section: Fementioning

confidence: 99%

“…1 The general mechanical properties of this material were 196 GPa for an elastic modulus (E), 308 MPa for a yield stress (Y s ), and 0.33 for a Poisson ratio (v). 1 The balloon was assumed to be made of highdensity polypropylene that had an isotropic linear elasticity. The mechanical properties of the material were then determined from literature (E: 1 GPa, Y s : 90 MPa, and v: 0.33).…”

Section: Constitutive Materials Modelsmentioning

confidence: 99%

Suggestion of Potential Stent Design Parameters to Reduce Restenosis Risk driven by Foreshortening or Dogboning due to Non-uniform Balloon-Stent Expansion

et al. 2008

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The foreshortening or dogboning of a stent that occurs due to transient non-uniform balloon-stent expansion can induce a vascular injury, resulting in restenosis of the coronary artery. However, previous studies rarely considered the effects of transient non-uniform balloon expansion on analysis of the mechanical properties and behaviors of stents during stent deployment, nor did they determine design parameters to minimize the restenosis risk driven by foreshortening or dogboning. The aim of the current study was, therefore, to suggest potential design parameters capable of reducing the possibility of restenosis risk driven by foreshortening or dogboning through a comparative study of seven commercial stents using finite element (FE) analyses of a realistic transient non-uniform balloon-stent expansion process. The results indicate that using stents composed of opened unit cells connected by bend-shaped link structures, in particular the MAC Plus stent, and controlling the geometrical and morphological features of the unit cell strut or the link structure at the distal ends of stent may prevent restenosis risk caused by foreshortening or dogboning. This study provides a first look at the realistic transient non-uniform balloon-stent expansion by investigating the mechanical properties, behaviors, and design parameters capable of reducing the possibility of restenosis risk induced by the foreshortening or the dogboning.

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Characterizing the Defect Population Introduced by Radiation Damage

Follansbee

2012

Ceramic Transactions Series

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Dynamic uniaxial and biaxial stress-strain relationships for austenitic stainless steels

Cited by 38 publications

References 4 publications

An Internal State Variable Constitutive Model for Deformation of Austenitic Stainless Steels

An Internal State Variable Constitutive Model for Deformation of Austenitic Stainless Steels

Suggestion of Potential Stent Design Parameters to Reduce Restenosis Risk driven by Foreshortening or Dogboning due to Non-uniform Balloon-Stent Expansion

Characterizing the Defect Population Introduced by Radiation Damage

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