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International Journal of Heat and Mass Transfer

ISSN: 0017-9310

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Datasets associated with articles published in International Journal of Heat and Mass Transfer

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1970
2024
1970 2024
58 results
  • Data for: Using Optical Fibers to Examine Thermal Mixing of Liquid Sodium in a Pool-Type Geometry
    TC&Flow Data for the PLOF and ULOF experiment are strictly from measurements made by the thermocouples at distinct heights within the test section. The thermocouples protrude approximately 1" into the test section. The flow data is from a flow meter measuring flow in a 1 inch schedule 40 stainless steel pipe upstream from the inlet into the test section. Fiber Data given demonstrates a unique temperature measurement at each location on the fiber over time. The length of the fiber is measured where '0' is the bottom of the test section and the maximum length measured is roughly the sodium level. The provided parasolid is a model of the test section as-built. If a different model is required inquires can be made to the contributing author.
    • Dataset
  • Data for: Width of Thermal Features Induced by a 2-D Moving Heat Source
    Collected published data of six fusion welding processes and additive manufacturing with 19 different alloys to validate predictive scaling law of isotherm width induced by a 2-D moving heat source.
    • Dataset
  • Data for: An Experimental Investigation of the Effect of Multiple Inlet Restrictors on the Heat Transfer and Pressure Drop in a Flow Boiling Microchannel Heat Sink
    • In this study, experimental investigations were performed to quantify the effect of different configurations of inlet restrictors on the heat transfer performance and pressure drop in a flow boiling microchannel heat sink. • Multiple IRs performs best in CHF enhancement at low mass flux, and the 1IR case performs best at high mass flux. • For lower mass flow rates, cases with multiple-opening inlet restrictors generally work better (e.g., higher CHF) than cases with the single-opening inlet restrictor. • The optimum configuration was obtained by maximizing the heat transfer performance (e.g., in terms of CHF enhancement) and minimizing the pressure drop penalties.
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  • Data for: Numerical and Experimental Study of the Glass-Transition Temperature of a non-Newtonian Fluid in a Dynamic Scraped Surface Heat Exchanger
    Time dependent simulation capturing heat transfer in DSSHE
    • Dataset
  • Supplemental data for: The effects of outdoor air-side fouling on frost growth and heat transfer characteristics of a microchannel heat exchanger: an experimental study
    We investigated the frost formation and heat transfer rates under different inlet air relative humidities (2 cases), initial air face velocities(2 cases), and fouling levels (4 cases). We selected the following condition as our baseline: R= 75%, v=1.0 m/s (S=2510 rpm), clean surface. While studying the effects of one parameter on the performance of the heat exchanger, all other parameters were kept constant. For example, we only increase the inlet RH from baseline (R=75%) to R= 85% for R85 condition. There are eight data sheets in this file, all of them have the same column names. Therefore, we only selected “Baseline” sheet to explain each column meaning: 1. Sensor monitoring variable columns: (A-J). The 1st column (A) is testing time, the interval of each row is one minute. The 2nd (B) and 3rd (C) columns are inlet air temperature parameters, representing inlet air dry-bulb and wet-bulb temperatures, respectively. The 4th (D) column is the air pressure drop across the coil. The 5th (E) column is the air volumetric flow rate across the coil. The 6th (F) column is the anti-freezing solution outlet temperature leaving the coil. The 7th (G) column is the anti-freezing solution inlet temperature entering the coil. The 8th (H) column is the outlet air average temperature of nine RTD sensors downstream of the coil. The 9th (I) and 10th (J) columns are outlet air RH sensors downstream of nine RTD sensors, representing outlet air dry-bulb temperature and relative humidity, respectively. 2. Resultant variable columns: (A-J). The 11th column (K) is inlet air humidity ratio, calculated by inlet air dry-bulb ratio (column B) and wet-bulb (column C) temperatures. The 12th column (L) is the outlet air humidity ratio, calculated by the RH sensor’s outlet air temperature (column I) and relative humidity (column J). The 13th column (M) is the outlet air specific volume, calculated by outlet air humidity ratio (column L) and outlet air temperature (column I). The 14th column (N) is the dry air mass flow rate, calculated by air volumetric flow rate (column E) and outlet air specific volume (column M). The 15th column (O) is inlet air specific enthalpy, calculated by dry air mass flow rate (column N), inlet air dry-bulb temperature (column B) and humidity ratio (column K). The 16th column (P) is outlet air specific enthalpy, calculated by dry air mass flow rate (column N), outlet air dry-bulb temperature downstream of the coil (column H) and humidity ratio (column L). The 17th column (Q) is the heat transfer rate, calculated by dry air mass flow rate (column N), inlet (column O) and outlet (column P) air specific enthalpy. The 18th column (R) is the frost formation rate, calculated by dry air mass flow rate (column N), inlet (column K) and outlet (column L) air humidity ratio. The 19th column (S) is accumulated frost mass, calculated by integrating the frost formation rate (column R) over time.
    • Dataset
  • Data for: Experimental and Modeling Investigations of Dropwise Condensation out of Convective Humid Air Flow
    Additional figures for the current article
    • Dataset
  • Data for: Numerical Modeling of a Benchmark Experiment on Equiaxed Solidification of a Sn-Pb alloy with Electromagnetic Stirring and Natural Convection
    Boundary conditions for AFRODITE benchmark solidification experiment with the electromagnetic stirring opposite to the direction of the flow initiated by the buoyancy force. Size of the cavity is 10cm x 6 cmx 1cm. Given data are obtained from the experimental measurements of temperature at the right and left heat exchangers and in the liquid in assumption of the conductive heat transport in the horizontal direction. Thus convective heat transfer near the boundary is neglected (cf. related publication). These are "raw data" without additional treatment
    • Dataset
  • Data for: Numerical simulation of entropy generation due to natural convection heat transfer using a Kernel Derivative-Free (KDF) incompressible smoothed particle hydrodynamics (ISPH) model
    This file contains 18 animations related to the current work as a supplementary material
    • Dataset
  • Data for: Numerical Investigation of the Gas–Solid Heat Transfer Characteristics of Packed Multi-size Particles
    The data files are named as their figure number
    • Dataset
  • Data for: Direct tests of fluid-to-fluid scaling expressions for supercritical heat transfer in tubes
    Wall temperature measurements were obtained with closely spaced T-type thermocouples in an electrically heated tube with 8 mm ID containing Refrigerant R134a flowing vertically upwards. The applied pressure, mass flux, heat flux and local bulk temperature were determined by scaling the conditions in previous measurements in CO2 following the fluid-to-fluid scaling expressions of Zahlan, Groeneveld and Tavoularis (2014). Two data sets are provided, containing, respectively, measurements under conditions for normal and deteriorated heat transfer. The ranges of conditions are: pressure fixed at 1.13 times the critical pressure; mass flux from 212 to 1609 kg /(m^2 s); heat flux from 2 to 137 kW/m^2; inlet temperature from 62 to 105 deg C. The bulk fluid enthalpy along the heated tube was calculated using the energy equation. Local values of the thermophysical properties were computed from specified values of pressure and bulk temperature using the NIST software. The files also contain values of previous measurements in carbon dioxide and estimates in water (computed from look-up tables) at equivalent conditions to the R134a data.
    • Dataset
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