Literature DB >> 32165767

Validation of thermophysical data for scientific and engineering applications.

Vladimir Diky1, Ala Bazyleva1, Eugene Paulechka1, Joseph W Magee1, Vikina Martinez1, Demian Riccardi1, Kenneth Kroenlein1.   

Abstract

High quality thermophysical property data are essential to many scientific and engineering applications. These data are produced at a high rate and are affected by a range of experimental and reporting error sources that often exceed stated uncertainties. As a result, critical evaluation is required to establish the limits of reliability in a quantified way. The present work describes reporting recommendations and property data validation methods developed and applied at the Thermodynamics Research Center at NIST through the use of the ThermoData Engine (TDE; SRD 103a/b) software. Examples are provided with an emphasis on various consistency checks, which may include the use of equations of state (EOS).

Entities:  

Keywords:  Equations of state (EOS); Good reporting practices; Models; Thermophysical data; Uncertainties

Year:  2019        PMID: 32165767      PMCID: PMC7067062          DOI: 10.1016/j.jct.2019.01.029

Source DB:  PubMed          Journal:  J Chem Thermodyn        ISSN: 0021-9614            Impact factor:   3.178


  9 in total

1.  Observation of liquid-crystal formation during melting of D-(+)-glucose.

Authors:  S Reza Bagheri; John M Shaw
Journal:  J Agric Food Chem       Date:  2011-11-04       Impact factor: 5.279

2.  ThermoData Engine (TDE): software implementation of the dynamic data evaluation concept. 2. Equations of state on demand and dynamic updates over the web.

Authors:  Vladimir Diky; Chris D Muzny; Eric W Lemmon; Robert D Chirico; Michael Frenkel
Journal:  J Chem Inf Model       Date:  2007-05-23       Impact factor: 4.956

3.  ThermoData Engine (TDE): software implementation of the dynamic data evaluation concept. 9. Extensible thermodynamic constraints for pure compounds and new model developments.

Authors:  Vladimir Diky; Robert D Chirico; Chris D Muzny; Andrei F Kazakov; Kenneth Kroenlein; Joseph W Magee; Ilmutdin Abdulagatov; Michael Frenkel
Journal:  J Chem Inf Model       Date:  2013-11-27       Impact factor: 4.956

4.  An epidemic of false claims. Competition and conflicts of interest distort too many medical findings.

Authors:  John P A Ioannidis
Journal:  Sci Am       Date:  2011-06       Impact factor: 2.142

5.  Efficient Estimation of Formation Enthalpies for Closed-Shell Organic Compounds with Local Coupled-Cluster Methods.

Authors:  Eugene Paulechka; Andrei Kazakov
Journal:  J Chem Theory Comput       Date:  2018-10-05       Impact factor: 6.006

6.  Modeling and measurements of solid-liquid and vapor-liquid equilibria of polyols and carbohydrates in aqueous solution.

Authors:  Svava Osk Jónsdóttir; Stephen A Cooke; Eugénia A Macedo
Journal:  Carbohydr Res       Date:  2002-09-27       Impact factor: 2.104

7.  Data Quality and Assessment, Validation Methods and Error Propagation through the Simulation Software: Report from the Round-Table Discussion at the 10th World Congress of Chemical Engineering in Barcelona (October 1-5, 2017).

Authors:  P M Mathias; A Soto; L Fele-Zilnik; J-C de Hemptinne; A Bazyleva; J Abildskov
Journal:  Chem Eng Res Des       Date:  2018       Impact factor: 3.739

8.  A Cross-Sectional Survey Study to Assess Prevalence and Attitudes Regarding Research Misconduct among Investigators in the Middle East.

Authors:  Marwan Felaefel; Mohamed Salem; Rola Jaafar; Ghufran Jassim; Hillary Edwards; Fiza Rashid-Doubell; Reham Yousri; Nahed M Ali; Henry Silverman
Journal:  J Acad Ethics       Date:  2017-10-13

9.  Why most published research findings are false.

Authors:  John P A Ioannidis
Journal:  PLoS Med       Date:  2005-08-30       Impact factor: 11.613

  9 in total

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