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Validation of thermophysical data for scientific and engineering applications.

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).

SUBMITTER: Diky V

PROVIDER: S-EPMC7067062 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Validation of thermophysical data for scientific and engineering applications.

Diky Vladimir V Bazyleva Ala A Paulechka Eugene E Magee Joseph W JW Martinez Vikina V Riccardi Demian D Kroenlein Kenneth K

The Journal of chemical thermodynamics 20190101

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 Resea ...[more]

PMID: 32165767

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Project description:Hybrid nanofluids are considered as an alternative for conventional heat transfer fluids and mono nanofluids due to its remarkable enhancement in thermo-physical properties. However, there are some limitations in achieving the better thermo-physical properties due to the stability of nanoparticles in different base fluids at higher concentration. This work aims at synthesizing, thermo-physical characterization and thermal performance estimation of stable Cu-MXene based hybrid nanofluids using various base fluids at very low volume concentration of Cu and MXene nanostructures. Two step method is employed to prepare Cu-MXene hybrid nanofluids by dispersing the low volume concentration of as prepared Cu and MXene nanostructures (ranging from 0.01-0.05 vol%) containing SDS surfactant in various base fluids such as water, methanol, castor oil and silicon oil. Synthesized mono and hybrid nanofluids shows excellent stability against aggregation up to 7 days as evidenced from higher zeta potential values. Wettability studies conducted using contact angle measurement suggests that the castor oil, methanol and silicon oil based hybrid nanofluids exhibits hydrophilic behavior (showing contact angle less than 90°). Hybrid nanofluids display excellent enhancement in thermal conductivity at very low concentration of nanostructures (more than 70% for methanol based Cu-MXene hybrid nanofluid). Viscosity of the silicone oil based hybrid nanofluids show a remarkable enhancement followed by water, methanol and castor oil based hybrid nanofluids. Thermal conductivity and viscosity of hybrid nanofluids are effectively validated with existing theoretical models. Moreover, specific heat and pumping power of the hybrid nanofluids with respect to volume concentration of nanostructures are determined using the existing theoretical equations. Thermal performance of hybrid nanofluids was successfully estimated using Figure of Merit (FOM) analysis and suggested the better heat transfer fluid for improving the heat transfer performance under laminar and turbulent flow conditions for efficient cooling applications.

Dataset Information

Validation of thermophysical data for scientific and engineering applications.

Publications

Validation of thermophysical data for scientific and engineering applications.

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