Uncertainties In Thermodynamic Data Research Articles

Thermophysical properties of H2O and D2O ice Ih with contributions from proton disorder, quenching, relaxation, and extended defects: A model case for solids with quenching and relaxation.

Application of the coherent thermodynamic model [W. Holzapfel and S. Klotz, J. Chem. Phys. 155, 024506 (2021)] for H2O ice Ih to the more detailed data for D2O ice Ih provides better insight into the contributions from quenched proton disorder and offers a new basis for understanding the apparent differences between the data for thermal expansion measured with neutron diffraction on polycrystalline samples [A. Fortes, Acta Crystallogr., Sect. B: Struct. Sci., Cryst. Eng. Mater. 74, 196 (2018) and A. Fortes, Phys. Chem. Chem. Phys 21, 8264 (2019)] and macroscopic dilatation measurements on single crystals [D. Buckingham et al., Phys. Rev. Lett. 121, 185505 (2018)]. The comparison points to contributions from defects effecting the two techniques in different ways. The uncertainties in thermodynamic data due to the contributions from proton disorder and additional defects are compared with the "reference data" [R. Feistel and W. Wagner, J. Phys. Chem. Ref. Data 35, 1021 (2006)] for H2O ice Ih.

Development of a simple model for the simultaneous degradation of concrete and clay in contact

In nuclear waste repositories concrete and bentonite are used, sometimes in contact with each other. The rate of mutual degradation of concrete and bentonite by alkaline fluids from concrete is explored using a simple model. The model considers dissolution of a soluble compound in the concrete (e.g. portlandite), which is gradually dissolved as the solubilised hydroxide and the cation(s) diffuse towards and into the bentonite in which smectite degrades by interaction with the solutes. Accounting for only the diffusion resistances in concrete and clay, the solubility of the concrete compound and the hydroxide consumption capacity of the smectite, results in a very simple analytical model. The model is tested against several published modelling results that account for reaction kinetics, reactive surface, and equilibrium data for tens to many tens of different secondary minerals. In the models that include several specified minerals often assumptions need to be made on which minerals can form. This introduces subjective assumptions. The degradation rates using the simple model are within the range of results obtained by the complex models. In the studies of the data used in these models it was found that the uncertainties in thermodynamic data are considerable and can give contradictory information on under what conditions smectite degrades. Some smectite models and thermodynamic data suggest that smectite will transform to other minerals spontaneously if there were no kinetic restrictions.

Radioelement Solubilities in SR-Site, the Influence of Variability and Uncertainty

ABSTRACTIf groundwater enters a damaged canister and comes in contact with the spent fuel, radionuclides are released into the water in the void inside the canister when fuel dissolves. Solubility limits restrict the amount of radioelements that may migrate with the water flowing from the canister. In this study the impact of variability in groundwater chemistry compositions and the impact of uncertainties in thermodynamic data on solubility limits for Np, Pb, Pu, Ra, Se, Th, U and Zr were looked into. The solubility limits for all the studied radioelements seemed to be more sensitive to uncertainties in thermodynamic data than to differences in groundwater chemistry. The sole exception was radium, where variability in water composition has a somewhat larger impact. Radium is also the most safety critical element in the safety assessment SR-Site and groundwater compositions are expected to vary during the assessment period of one million years.

Reductive Transformation of Birnessite by Aqueous Mn(II)

Reaction of aqueous Mn(II) with hexagonal birnessite at pH 7.5 causes reductive transformation of birnessite into feitknechtite (β-Mn(III)OOH) and manganite (γ-Mn(III)OOH) through interfacial electron transfer from adsorbed Mn(II) to structural Mn(IV) atoms and arrangement of product Mn(III) into MnOOH, summarized by Mn(II) + Mn(IV)O(2) + 2 H(2)O → 2 Mn(III)OOH + 2 H(+). Feitknechtite is the initial transformation product, and subsequently converted into the more stable manganite polymorph during ongoing reaction with Mn(II). Feitknechtite production is observed at Mn(II) concentrations 2 orders of magnitude below thermodynamic thresholds, reflecting uncertainty in thermodynamic data of Mn-oxide minerals and/or specific interactions between Mn(II) and birnessite surface sites facilitating electron exchange. Under oxic conditions, feitknechtite formation through surface-catalyzed oxidation of Mn(II) by O(2) leads to additional Mn(II) removal from solution relative to anoxic systems. These results indicate that Mn(II) may be an important moderator of the reductive arm of Mn-oxide redox cycling, and suggest a controlling role of Mn(II) in regulating the solubility and speciation of phyllomanganate-reactive metal pollutants including Co, Ni, As, and Cr in geochemical environments.

Testing geochemical models of bentonite pore water evolution against laboratory experimental data

The determination of a bentonite pore water composition and understanding its evolution with time underpins many radioactive waste disposal issues, such as buffer erosion, canister corrosion, and radionuclide solubility, sorption, and diffusion, inter alia. Previous modelling approaches have tended to ignore clay dissolution–precipitation reactions, a consequence of which is that montmorillonite is theoretically preserved indefinitely in the repository system. Here, we investigate the applicability of an alternative clay pore fluid evolution model, that incorporates clay dissolution–precipitation reactions as an integral component and test it against well-characterised laboratory experimental data, where key geochemical parameters, Eh and pH, have been measured directly in compacted bentonite. Simulations have been conducted using different computer codes (Geochemist’s Workbench, PHREEQC, and QPAC) to test the applicability of this model. Thermodynamic data for the Gibb’s free energy of formation of MX-80 smectite used in the calculations were estimated using two different methods (‘Polymer’ and ‘Vieillard’ Models). Simulations of ‘end-point’ pH measurements in batch bentonite–water slurry experiments showed different pH values according to the complexity of the system studied. The most complete system investigated revealed pH values were a strong function of partial pressure of carbon dioxide, with pH increasing with decreasing PCO 2 (with log PCO 2 values ranging from −3.5 to −7.5 bars produced pH values ranging from 7.9 to 9.6). A second set of calculations investigated disequilibrium between clay and pore fluid in laboratory squeezing cell tests involving pure water (pH = 9.0) or a 1 M NaOH solution (pH = 12.1). Simulations carried out for 100 days (the same timescale as the experiments) showed that smectite remained far from equilibrium throughout, and that the lowering of pH due to smectite hydrolysis was trivial. However, extending the duration of the simulations to that required for clay–fluid equilibrium, necessitated timescales of 7 and 65 years for pure water and 1 M NaOH, respectively, but again produced relatively minor reduction in pH (in the order of 0.1–0.2 pH units). If the (equilibrium) precipitation of secondary minerals was included in the simulations, then not only was the clay–fluid equilibration period extended dramatically (from 7 to 360 years for pure water, and from 65 to 2600 years for 1 M NaOH), but concomitant changes in pH were significant, decreasing from 9.0 to 8.6 (pure water) and from 12.1 to 9.0 (1 M NaOH). Repetition of these latter calculations using an alternative method for Δ G f 0 smectite produced an increase in equilibration time for reaction with 1 M NaOH from 2600 to 5000 years, highlighting the potential effects of the uncertainty in thermodynamic data for smectite. A final set of calculations was carried out to investigate both the time- and space-dependent variations in pore fluid composition in laboratory in-diffusion experiments conducted for over 1200 days, initially with pure water and ‘spiked’ after 271 days with a Na–Ca–OH–Cl solution (pH = 11.7). Here, the sensitivity of the results to both variations in a number of parameters/conditions (porosity, reaction rate of secondary minerals, the degree of mixing of the external fluid reservoirs in the experiments, the effective diffusion coefficient) and the inclusion/exclusion of key processes (clay hydrolysis, secondary mineral precipitation, ion exchange, clay edge protonation–deprotonation reactions) was investigated. These calculations confirmed that smectite dissolution–precipitation reactions alone have an insignificant impact upon pH buffering over laboratory timescales and that the pH buffering observed is most likely controlled by clay protonation–deprotonation reactions, and kinetic secondary mineral (brucite + tobermorite) precipitation. Ion exchange reactions were found to have little effect on pH. Alternative data for the kinetic dissolution of smectite produced no observable differences, and the adoption of a reduced diffusion coefficient produced a poorer fit to experiment results. In conclusion, modelling predicts that the effects of smectite dissolution on the chemistry of bentonite pore waters would be essentially undetectable over experimental time scales, but when the model is combined with plausible constraints on the precipitation of secondary minerals, significant changes in solution chemistry and mineralogy are predicted to occur over time scales that are relevant to repository near-field evolution (hundreds to thousands of years). There are remaining fundamental uncertainties related to the variable chemistry of the smectite clays, the nature of porosity in highly compacted buffer materials, the reactive surface area of smectite, and the thermodynamic properties of these clay minerals.

Uncertainties Connected with Geochemical Modelling of Waste Disposal in Mines

When trying to model the chemical behaviour within a mine or rock system, there are several uncertainties to take into account. Among these are thermodynamic uncertainties and water composition uncertainties. Due to such uncertainties, results ought to be given as confidence intervals rather than fixed values. However, when dealing with uncertainties in thermodynamic data, it is important to remember that the uncertainty interval is not simply the uncertainty interval used in probabilistic calculations buth rather the interval determined when several investigations are compared.

Database uncertainty as a limiting factor in reactive transport prognosis

The effect of uncertainties in thermodynamic databases on prediction performances of reactive transport modeling of uranium (VI) is investigated with a Monte Carlo approach using the transport code TReaC. TReaC couples the transport model to the speciation code PHREEQC by a particle tracking method. A speciation example is given to illustrate the effect of uncertainty in thermodynamic data on the predicted solution composition. The transport calculations consequently show the prediction uncertainty resulting from uncertainty in thermodynamic data. A conceptually simple scenario of elution of uranium from a sand column is used as an illustrating example. Two different cases are investigated: a carbonate-enriched drinking water and an acid mine water associated with uranium mine remediation problems. Due to the uncertainty in the relative amount of positively charged and neutral solution species, the uncertainty in the thermodynamic data also infers uncertainty in the retardation behavior. The carbonated water system shows the largest uncertainties in speciation calculation. Therefore, the model predictions of total uranium solubility have a broad range. The effect of data uncertainty in transport prediction is further illustrated by a prediction of the time when eluted uranium from the column exceeds a threshold value. All of these Monte Carlo transport calculations consume large amounts of computing time.

Dry melting of high albite

The properties of albitic melts are central to thermodynamic models for synthetic and natural granitic liquids. We have analyzed published phase-equilibrium and thermodynamic data for the dry fusion of high albite to develop a more accurate equation for the Gibbs free energy of this reaction to 30 kbar and 1400 °C. Strict criteria for reaction reversal were used to evaluate the phase-equilibrium data, and the thermodynamic properties of solid and liquid albite were evaluated using the published uncertainties in the original measurements. Results suggest that neither available phase-equilibrium experiments nor thermodynamic data tightly constrain the location of the reaction. Experimental solidus temperatures at 1 atm range from 1100 to 1120 °C. High-pressure experiments were not reversed completely and may have been affected by several sources of error, but the apparent inconsistencies among the results of the various experimentalists are eliminated when only half-reversal data are considered. Uncertainties in thermodynamic data yield large variations in permissible reaction slopes. Disparities between experimental and calculated melting curves are, therefore, largely attributable to these difficulties, and there is no fundamental disagreement between the available phase-equilibrium and thermodynamic data for the dry melting of albite. Consequently, complex speciation models for albitic melts, based on the assumption that these discrepancies represent a real characteristic of the system, are unjustified at this time.

Prediction of pH in natural hydrothermal fluids at elevated P–T conditions

The pH of fluids at elevated temperature–pressure conditions are routinely calculated from fluid compositions measured in the laboratory. Numerical errors, uncertainties in thermodynamic data, and analytical errors can affect these computed values. An analysis of pH values computed at elevated temperature and pressure conditions for natural fluids reveals that the amount of error in computed pH values can be, but is not always, dependent on fluid composition. Not all reactions occurring in a fluid affect computed pH values. Therefore, inadequacies in the thermodynamic properties of a species may affect computed pH values in some fluid compositions but not others. When a single reaction controls the production/consumption of H +, the amount by which the pH changes as a function of temperature and pressure is independent of the measured pH. However, when two or more reactions produce/consume sufficient H + to change the pH, the amount by which the pH changes as a function of temperature and pressure is dependent on the measured pH. Uncertainties in the measured pH are magnified as temperature and pressure increase for some fluid compositions, while the uncertainty decreases in others. When small uncertainties in the measured pH are magnified, the activities of aqueous species calculated at elevated temperature and pressure conditions cannot be used to predict fluid–mineral equilibria.

Effects of Uncertainties in Thermodynamic Data and Models on Process Calculations

Thermodynamic models and experimental data exhibit systematic and random errors. The severity of their errors depends on their use, such as for process calculations in a process simulator. Similarly, the value of better thermodynamic models and/or data should be measured with reference to such use. Strategies for quantification of such thermodynamics-induced process uncertainties via Monte Carlo simulation, regression analysis, and analogies to optimization are described, with simple examples. Such approaches can be used for safety-factor/risk analysis, guidelines for process simulator use, experimental design, and model comparisons.

Detailed kinetic modeling of C1 — C3 alkane diffusion flames

A study of detailed chemical kinetics in coflow and counterflow diffusion flames is presented. The chemistry of diffusion flames is of fundamental importance from a practical as well as a mechanistic viewpoint. The present study uses systematic reaction path flux and sensitivity analyses to determine the crucial reaction paths in methane and propane diffusion flames. The formation of benzene and intermediate hydrocarbons via C3 and C4 species has been given particular attention and the relative importance of reaction channels has been assessed. The developed mechanism considers singlet and triplet CH2, isomers of C3H4, C3H5, C4H3,H5 and C4H6. Computational results show that benzene in methane — air diffusion flames is formed mainly via reactions involving propargyl radicals and that reaction paths via C4 species are insignificant. It is also shown that uncertainties in thermodynamic data may significantly influence predictions and that the reaction of acetylene with the hydroxyl radical to produce ketene may be an important consumption path for acetylene in diffusion flames. Quantitative agreement has been achieved between computational results and experimental measurements of major and minor species profiles, including benzene, in methane-air and propane-air flames. It is also shown that the mechanism correctly predicts laminar burning velocities for stoichiometric C1—C3 flames. Finally, results for a two-dimensional methane-air flame on a Wolfhard-Parker burner obtained with full detailed chemistry are presented along with flamelet computations and the accuracy of the latter are discussed.

Effect of uncertainties in thermodynamic data and model parameters on calculated process performance

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTEffect of uncertainties in thermodynamic data and model parameters on calculated process performanceWallace B. Whiting, Ting Man Tong, and Michael E. ReedCite this: Ind. Eng. Chem. Res. 1993, 32, 7, 1367–1371Publication Date (Print):July 1, 1993Publication History Published online1 May 2002Published inissue 1 July 1993https://doi.org/10.1021/ie00019a011RIGHTS & PERMISSIONSArticle Views200Altmetric-Citations32LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (564 KB) Get e-Alerts Get e-Alerts

Shock-tube measurement of the dissociation energy of NH using absolute band intensities

The NH radical has been observed spectroscopically in reflected shocks through nitrogen-hydrogen-krypton and ammonia-krypton mixtures. The (0, 0) band of the NH 3II-3Σ- system was photographed in absorption under high dispersion. From a knowledge of the temperature and partial pressures in the equilibrium region behind the reflected shock and the rotational line strengths, a band f value was deduced as a function of dissociation energy. Comparison with independently determined f values based on measurements of radiation lifetimes leads to the value D(NH) = 3 21 ± 0 16 eV. Experimental scatter and uncertainty in thermodynamic data have been included in the error quoted. Other sources of error are discussed.