Heat capacity of liquid hafnium from the melting point to the boiling point at atmospheric pressure

Korobenko, V. N.; Polyakova, O. A.; Savvatimskii, A. I.

doi:10.1007/s10740-005-0044-1

Cited by 6 publications

(2 citation statements)

References 9 publications

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“…This indicates that weights determined by the automated weighting procedure described in section 3.1 are relatively insensitive to each other and, perhaps more surprisingly, to fluctuations in the model's parameterization. Looking at the values of the hyperparameters themselves, we can see that the Bayesian framework highly weights the measurements of Korobenko [63], Cagran [64] and Rösner-Kuhn [65] while assigning the measurements of Paradis [66] a low weight. Figures 3 and 4, which display the model predictions and experimental data sets confirm that the model prediction aligns closely with the prioritized data sets while effectively ignoring the Paradis measurements.…”

Section: Case Study: Hafniummentioning

confidence: 99%

Uncertainty quantification and propagation in CALPHAD modeling

Honarmandi

Paulson

Arróyave

et al. 2019

Modelling Simul. Mater. Sci. Eng.

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Design is about making decisions bounded by a quantifiable degree of certainty. In the context of alloy design, Integrated Computational Materials Engineering (ICME) provides the framework whereby performance requirements are ultimately transformed into alloy/processing specifications through the combination of (complex) computational models connecting processstructure-property-performance relationships and experiments. Most ICME approaches consider the models used as deterministic and thus do not provide the means to make alloy design decisions with proper confidence measures. At the root of ICME lie CALPHAD models that describe the thermodynamics and phase stability of phases under specific thermodynamic boundary conditions. To date, the vast majority of efforts within the CALPHAD community have been deterministic in that thermodynamic models and the resulting thermodynamic properties and phase diagram features do not explicitly account for the uncertainties inherent in the model formulation or in the experimental/computational data used. In this contribution, we provide an overview of the state of the field. We review major efforts thus far and we then provide a (brief) tutorial on basic concepts of uncertainty quantification and propagation (UQ/UP) in CALPHAD. We discuss the major features of frequentist and Bayesian interpretations of uncertainty and proceed with a discussion of recent case studies in which UQ has been used to parameterize models for the thermodynamic properties of phases. We follow our discussion by presenting frameworks and demonstrating the propagation of uncertainty in

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Section: Case Study: Hafniummentioning

confidence: 99%

Uncertainty quantification and propagation in CALPHAD modeling

Honarmandi

Paulson

Arróyave

et al. 2019

Modelling Simul. Mater. Sci. Eng.

View full text Add to dashboard Cite

show abstract

“…This procedure employed qualitatively is an adaptation of the method of rapid heating of thin metal samples under conditions of discharge of a high-voltage capacitor [12,13] to the conditions of our investigation. The general requirements apply to the operating speed of the power switch and to the val-ue of the time constant of the capacitor discharge circuit (less than 1 μs).…”

Section: Cooling Down Of Shock-heated Probementioning

confidence: 99%

An experimental investigation of heat transfer in thermally unstable polymer systems

et al. 2006

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An experimental study is made into the process of heat transfer from a pulse-superheated probe to a solidified polymer system at probe temperatures above the temperature T d∞ of the beginning of thermal destruction of matter in a quasi-static process. Use is made of the procedures of thermal stabilization of the pulse-superheated probe (with the characteristic time of constancy of superheated probe temperature of 1 ms) and of shock heating (with the characteristic time of increasing the probe temperature of 1 μs and that of monitoring its cooling-down of 1 ms). The effect of short-term thermal stability of polymers in the region of T > T d∞ is revealed. A procedure is developed for identifying the signs of thermal destruction of polymers in the pulsed process. The maximal values are estimated of the density of heat flux through samples without their thermal destruction.

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Bayesian strategies for uncertainty quantification of the thermodynamic properties of materials

Paulson

Jennings

Stan

2019

International Journal of Engineering Science

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Reliable models of the thermodynamic properties of materials are critical for industrially relevant applications that require a good understanding of equilibrium phase diagrams, thermal and chemical transport, and microstructure evolution. The goal of thermodynamic models is to capture data from both experimental and computational studies and then make reliable predictions when extrapolating to new regions of parameter space. These predictions will be impacted by artifacts present in real data sets such as outliers, systematics errors and unreliable or missing uncertainty bounds. Such issues increase the probability of the thermodynamic model producing erroneous predictions. We present a Bayesian framework for the selection, calibration and quantification of uncertainty of thermodynamic property models. The modular framework addresses numerous concerns regarding thermodynamic models including thermodynamic consistency, robustness to outliers and systematic errors by the use of hyperparameter weightings and robust Likelihood and Prior distribution choices. Furthermore, the framework's inherent transparency (e.g. our choice of probability functions and associated parameters) enables insights into the complex process of thermodynamic assessment. We introduce these concepts through examples where the true property model is known. In addition, we demonstrate the utility of the framework through the creation of a property model from a large set of experimental specific heat and enthalpy measurements of Hafnium metal from 0 to 4900K.

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Heat capacity of liquid hafnium from the melting point to the boiling point at atmospheric pressure

Cited by 6 publications

References 9 publications

Uncertainty quantification and propagation in CALPHAD modeling

Uncertainty quantification and propagation in CALPHAD modeling

An experimental investigation of heat transfer in thermally unstable polymer systems

Bayesian strategies for uncertainty quantification of the thermodynamic properties of materials

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