High Temperature Data Sets Research Articles

Einstein\u2013Roscoe regression for the slag viscosity prediction problem in steelmaking

In classical machine learning, regressors are trained without attempting to gain insight into the mechanism connecting inputs and outputs. Natural sciences, however, are interested in finding a robust interpretable function for the target phenomenon, that can return predictions even outside of the training domains. This paper focuses on viscosity prediction problem in steelmaking, and proposes Einstein–Roscoe regression (ERR), which learns the coefficients of the Einstein–Roscoe equation, and is able to extrapolate to unseen domains. Besides, it is often the case in the natural sciences that some measurements are unavailable or expensive than the others due to physical constraints. To this end, we employ a transfer learning framework based on Gaussian process, which allows us to estimate the regression parameters using the auxiliary measurements available in a reasonable cost. In experiments using the viscosity measurements in high temperature slag suspension system, ERR is compared favorably with various machine learning approaches in interpolation settings, while outperformed all of them in extrapolation settings. Furthermore, after estimating parameters using the auxiliary dataset obtained at room temperature, an increase in accuracy is observed in the high temperature dataset, which corroborates the effectiveness of the proposed approach.

Modelling multiple cycles of static and dynamic recrystallisation using a fully implicit isotropic material model based on dislocation density

This paper presents the development and numerical implementation of a state variable based thermomechanical material model, intended for use within a fully implicit finite element formulation. Plastic hardening, thermal recovery and multiple cycles of recrystallisation can be tracked for single peak as well as multiple peak recrystallisation response. The numerical implementation of the state variable model extends on a $$J_{2}$$ isotropic hypo-elastoplastic modelling framework. The complete numerical implementation is presented as an Abaqus UMAT and linked subroutines. Implementation is discussed with detailed explanation of the derivation and use of various sensitivities, internal state variable management and multiple recrystallisation cycle contributions. A flow chart explaining the proposed numerical implementation is provided as well as verification on the convergence of the material subroutine. The material model is characterised using two high temperature data sets for cobalt and copper. The results of finite element analyses using the material parameter values characterised on the copper data set are also presented.

High-temperature structural study of decagonal Al–Cu–Rh

The structure of decagonal Al-Cu-Rh has been studied as a function of temperature by in-situ single-crystal X-ray diffraction in order to contribute to the discussion on energy or entropy stabilization of quasicrystals. The experiments were performed at 293, 1223, 1153, 1083 and 1013 K. A common subset of 1460 unique reflections was used for the comparative structure refinements at each temperature. A comparison of the high-temperature datasets suggests that the best quasiperiodic ordering should exist between 1083 and 1153 K. However, neither the refined structures nor the phasonic displacement parameter vary significantly with temperature. This indicates that the phasonic contribution to entropy does not seem to play a major role in the stability of this decagonal phase in contrast to other kinds of structural disorder, which suggests that, in this respect, this decagonal phase would be similar to other complex intermetallic high-temperature phases.

Non-Debye heat capacity formula refined and applied to GaP, GaAs, GaSb, InP, InAs, and InSb

Characteristic non-Debye behaviors of low-temperature heat capacities of GaP, GaAs, GaSb, InP, InAs, and InSb, which are manifested above all in form of non-monotonic behaviors (local maxima) of the respective Cp(T)/T3 curves in the cryogenic region, are described by means of a refined version of a recently proposed low-to-high-temperature interpolation formula of non-Debye type. Least-mean-square fittings of representative Cp(T) data sets available for these materials from several sources show excellent agreements, from the liquid-helium region up to room temperature. The results of detailed calculations of the respective material-specific Debye temperature curves, ΘD(T), are represented in graphical form. The strong, non-monotonic variations of ΘD(T) values confirm that it is impossible to provide reasonable numerical simulations of measured Cp(T) dependences in terms of fixed Debye temperatures. We show that it is possible to describe in good approximation the complete Debye temperature curves, from the cryogenic region up to their definitive disappearance (dropping to 0) in the high temperature region, by a couple of unprecedented algebraic formulas. The task of constructing physically adequate prolongations of the low-temperature Cp(T) curves up to melting points was strongly impeded by partly rather large differences (up to an order of 10 J/(K·mol)) between the high-temperature data sets presented in different research papers and/or data reviews. Physically plausible criteria are invoked, which enabled an a priori rejection of a series of obviously unrealistic high-temperature data sets. Residual uncertainties for GaAs and InAs could be overcome by re-evaluations of former enthalpy data on the basis of a novel set of properly specified four-parameter polynomial expressions applying to large regions, from moderately low temperatures up to melting points. Detailed analytical and numerical descriptions are given for the anharmonicity-related differences of isobaric vs. isochoric (harmonic) parts of heat capacities. Relevant sets of empirical parameters and representative collections of heat capacity and Debye temperature values for all materials under study are presented in tabulated form.

Solubility Measurements of Crystalline Cu2O in Aqueous Solution as a Function of Temperature and pH

The equilibrium solubility of crystalline cuprous oxide, cuprite, was measured in liquid water and steam using two flow-through reactors and a conventional batch autoclave. These measurements were carried out from 20 to 400 °C. Different batches of pretreated cuprite were thoroughly characterized prior to and following each set of experiments. Metallic copper beads were added to the inlet end of the reactors and to the solid charge in the autoclave to preserve the Cu(I) oxidation state, although one series of experiments produced some results which were only compatible with CuO(cr) as the solubility limiting phase. Comparison of the solubility data for Cu2O(cr) in aqueous solution with those from the only available high-temperature dataset (Var’yash, Geochem. Int. 26:80–90, 1989) showed that in near-neutral solutions the new data are lower by about four orders of magnitude at 350 °C. Moreover, the dominant species in solution at temperatures ≥100 °C were found to be only Cu+ and \(\mathrm{Cu(OH)}_{2}^{-}\) with Cu(OH)0 occurring over a narrow pH range at ≤75 °C rather than the reverse trend reported previously. Solubility equations were developed as a function of temperature and pH, based on these new results, which showed increased solubility with temperature in acidic and basic solutions. The solubility of Cu2O(cr) in steam decreased slightly with temperature and as expected increased with increasing pressure to supercritical conditions where limited, compatible data were available in the literature. The solubility at subcritical conditions was on the order of one to several parts per billion, ppb. A simple empirical fit was derived for the solubility in steam as a function of temperature and pressure.

A review of non-equilibrium dissociation rates and models for atmospheric entry studies

The appropriate simulation of vibrational exchange and dissociation processes in high-temperature (above 1000 K) plasmas mandates the application of more detailed state-to-state models, when compared with those based on first-order theories, utilized for the simulation of low-pressure plasmas. Such can be achieved through the application of approaches such as the forced harmonic oscillator model, or the quasi-classical trajectory model. This allows obtaining multiquantum state-resolved rates significantly more accurate at high temperatures, as compared with rates issued from first-order perturbation theories. This work reviews the more recent high-temperature datasets proposed by several groups, including our own. Such datasets have then been applied to the simulation of dissociation processes in high-temperature shock-heated nitrogen flows, and a comparison against traditional multi-temperature models has been carried out, for post-shock temperatures ranging from 20 000–100 000 K. Differences between the results predicted by the state-resolved and macroscopic models are significant, except in the high-temperature limit.