Dynamic compression of copper to over 450 GPa: A high-pressure standard

Kraus, R. G.; Davis, JP; Seagle, Christopher T; Fratanduono, D. E.; Swift, Damian; Brown, Justin; Eggert, J. H.

doi:10.1103/physrevb.93.134105

Cited by 57 publications

(27 citation statements)

References 45 publications

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“…shows the propagation of the posterior of the physical parameters through the material model (equation ) in comparison with two previously published estimates. First, the loading path was determined analytically by using the standard techniques within the dynamic materials community (Brown et al ., ); this analytic solution lies slightly above our estimated posterior mean, which is consistent with the expected bias when using the analytic analysis (Vogler, ; Kraus et al ., ). Second, we compare with a state of the art theoretical calculation given by Greeff et al .…”

Section: Resultsmentioning

confidence: 99%

Estimating Material Properties Under Extreme Conditions by Using Bayesian Model Calibration with Functional Outputs

Brown

Hund

2018

Journal of the Royal Statistical Society Series C: Applied Statistics

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Summary Dynamic material properties experiments provide access to the most extreme temperatures and pressures attainable in a laboratory setting; the data from these experiments are often used to improve our understanding of material models at these extreme conditions. We apply Bayesian model calibration to dynamic material property applications where the experimental output is a function: velocity over time. This framework can accommodate more uncertainties and facilitate analysis of new types of experiments relative to techniques traditionally used to analyse dynamic material experiments. However, implementation of Bayesian model calibration requires more sophisticated statistical techniques, because of the functional nature of the output as well as parameter and model discrepancy identifiability. We propose a novel Bayesian model calibration process to simplify and improve the estimation of the material property calibration parameters. Specifically, we propose scaling the likelihood function by an effective sample size rather than modelling the auto‐correlation function to accommodate the functional output. Additionally, we propose sensitivity analyses by using the notion of 'modularization' to assess the effect of experiment‐specific nuisance input parameters on estimates of the physical parameters. The Bayesian model calibration framework proposed is applied to dynamic compression of tantalum to extreme pressures, and we conclude that the procedure results in simple, fast and valid inferences on the material properties for tantalum.

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Section: Resultsmentioning

confidence: 99%

Estimating Material Properties Under Extreme Conditions by Using Bayesian Model Calibration with Functional Outputs

Brown

Hund

2018

Journal of the Royal Statistical Society Series C: Applied Statistics

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“…Ramp compression is a technique for dynamic loading of materials to very high pressures without the large temperature increases and sample melting associated with shock loading 41,42 . Ramp loading can be achieved in laser compression experiments by applying a time-dependent ramped increase in laser intensity onto a material surface.…”

Section: Introductionmentioning

confidence: 99%

X-ray diffraction of molybdenum under ramp compression to 1 TPa

et al. 2016

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Molybdenum (Mo) is a transition metal with a wide range of technical applications. There has long been strong interest in its high-pressure behavior and it is often used as standard for high-pressure experiments. Combining powder x-ray diffraction and dynamic ramp compression, structural and equation of state data were collected for solid Mo to 1 TPa (10 Mbar). Diffraction results are consistent with Mo remaining in the body-centered cubic structure into the TPa regime. Stress-density data show that Mo under ramp loading is less compressible than the room-temperature isotherm but more compressible than the single-shock Hugoniot.

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“…A recent magnetically driven, ramp loading experiment on Z provides limited validation of the EOS 3325 to 450 GPa. 51 The iterative analysis technique can be simplified in several ways. We have partially validated models of electrical conductivity and EOS for Al through numerous flyer plate and ramp loading experiments on Z.…”

Section: Discussionmentioning

confidence: 99%

“…Table 3325 has been partially validated to a pressure of 450 GPa in recent ramp loading experiments on Z. 51 The Steinberg-Guinan-Lund viscoplastic model 53,54 is used for Cu. The yield strength and shear modulus depend linearly on the pressure.…”

Section: Appendix: Materials Models For Cumentioning

confidence: 99%

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Magnetically launched flyer plate technique for probing electrical conductivity of compressed copper

Cochrane

Lemke

Riford

et al. 2016

Journal of Applied Physics

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The electrical conductivity of materials under extremes of temperature and pressure is of crucial importance for a wide variety of phenomena, including planetary modeling, inertial confinement fusion, and pulsed power based dynamic materials experiments. There is a dearth of experimental techniques and data for highly compressed materials, even at known states such as along the principal isentrope and Hugoniot, where many pulsed power experiments occur. We present a method for developing, calibrating, and validating material conductivity models as used in magnetohydrodynamic (MHD) simulations. The difficulty in calibrating a conductivity model is in knowing where the model should be modified. Our method isolates those regions that will have an impact. It also quantitatively prioritizes which regions will have the most beneficial impact. Finally, it tracks the quantitative improvements to the conductivity model during each incremental adjustment. In this paper, we use an experiment on Sandia National Laboratories Z-machine to isentropically launch multiple flyer plates and, with the MHD code ALEGRA and the optimization code DAKOTA, calibrated the conductivity such that we matched an experimental figure of merit to +/−1%.

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Dynamic compression of copper to over 450 GPa: A high-pressure standard

Cited by 57 publications

References 45 publications

Estimating Material Properties Under Extreme Conditions by Using Bayesian Model Calibration with Functional Outputs

Estimating Material Properties Under Extreme Conditions by Using Bayesian Model Calibration with Functional Outputs

X-ray diffraction of molybdenum under ramp compression to 1 TPa

Magnetically launched flyer plate technique for probing electrical conductivity of compressed copper

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