Latent heat

About: Latent heat is a research topic. Over the lifetime, 13503 publications have been published within this topic receiving 302811 citations.

Analytical Modeling of In-Process Temperature in Powder Bed Additive Manufacturing Considering Laser Power Absorption, Latent Heat, Scanning Strategy, and Powder Packing.

Abstract: Temperature distribution gradient in metal powder bed additive manufacturing (MPBAM) directly controls the mechanical properties and dimensional accuracy of the build part. Experimental approach and numerical modeling approach for temperature in MPBAM are limited by the restricted accessibility and high computational cost, respectively. Analytical models were reported with high computational efficiency, but the developed models employed a moving coordinate and semi-infinite medium assumption, which neglected the part dimensions, and thus reduced their usefulness in real applications. This paper investigates the in-process temperature in MPBAM through analytical modeling using a stationary coordinate with an origin at the part boundary (absolute coordinate). Analytical solutions are developed for temperature prediction of single-track scan and multi-track scans considering scanning strategy. Inconel 625 is chosen to test the proposed model. Laser power absorption is inversely identified with the prediction of molten pool dimensions. Latent heat is considered using the heat integration method. The molten pool evolution is investigated with respect to scanning time. The stabilized temperatures in the single-track scan and bidirectional scans are predicted under various process conditions. Close agreements are observed upon validation to the experimental values in the literature. Furthermore, a positive relationship between molten pool dimensions and powder packing porosity was observed through sensitivity analysis. With benefits of the absolute coordinate, and high computational efficiency, the presented model can predict the temperature for a dimensional part during MPBAM, which can be used to further investigate residual stress and distortion in real applications.

A spreadsheet-based (Microsoft Excel) point surface energy balance model for glacier and snow melt studies.

Abstract: This paper describes a point surface energy balance model which runs within the Microsoft Excel spreadsheet package. The study incorporates a large amount of previous energy balance work and presents it in a useable form. The core model calculates the net shortwave and longwave radiation fluxes, the turbulent sensible and latent heat fluxes and the surface melt rate at a point on a melting ice or snow surface, from hourly inputs of incoming shortwave radiation, vapour pressure, air temperature and wind speed data. The latitude, longitude, slope angle, aspect, elevation, local temperature lapse rate, albedo and aerodynamic roughness of the study site, and the elevation of the meteorological station, can all be specified in the model. An output file containing the hourly and daily rates, and the totals of the energy fluxes is generated. The main advantages of the model are: first, that it requires only a PC or laptop computer running standard Microsoft Windows software, enabling it to be used at a desktop or in the field; and second, that it can be adapted quickly to different sites, meteorological data formats and other application requirements. Model calculations are compared with measured surface melt rates at five points on Haut Glacier d'Arolla, Switzerland, over a 115 day ablation period. Allowing for differences in shading between the meteorological station and the glacier, the root mean square error of the calculated melt rates is 2·0 mm day−1 water equivalent melt (mean error +1·2 mm day−1), for measured melt rates in the range 23 to 42 mm day−1 water equivalent melt. Copyright © 2000 John Wiley & Sons, Ltd.

A unified approach for prediction of thermodynamic properties of aqueous mixed-electrolyte solutions. Part I: Vapor pressure and heat of vaporization

Abstract: The overall nonideality of an aqueous mixed electrolyte solution is characterized in terms of a newly defined parameter Γ*, called the overall reduced ionic activity coefficient. It is shown that Γ* for the mixed solution is simply related to the properties of single-electrolyte solutions. Γ* is related to the vapor pressure of a mixed-electrolyte solution through well-known thermodynamic equations. This leads to a predictive equation for the vapor pressure of a mixed-electrolyte solution in terms of the vapor pressures of single-electrolyte solutions of the components. This equation is valid over the entire concentration range encountered in practice, without any empirical constants, and has a predictive accuracy of 2%. A predictive equation for the latent heat of vaporization is also developed and tested against experimental data.

An assessment of air–sea heat fluxes from ocean and coupled reanalyses

Abstract: Sixteen monthly air–sea heat flux products from global ocean/coupled reanalyses are compared over 1993–2009 as part of the Ocean Reanalysis Intercomparison Project (ORA-IP). Objectives include assessing the global heat closure, the consistency of temporal variability, comparison with other flux products, and documenting errors against in situ flux measurements at a number of OceanSITES moorings. The ensemble of 16 ORA-IP flux estimates has a global positive bias over 1993–2009 of 4.2 ± 1.1 W m−2. Residual heat gain (i.e., surface flux + assimilation increments) is reduced to a small positive imbalance (typically, +1–2 W m−2). This compensation between surface fluxes and assimilation increments is concentrated in the upper 100 m. Implied steady meridional heat transports also improve by including assimilation sources, except near the equator. The ensemble spread in surface heat fluxes is dominated by turbulent fluxes (>40 W m−2 over the western boundary currents). The mean seasonal cycle is highly consistent, with variability between products mostly <10 W m−2. The interannual variability has consistent signal-to-noise ratio (~2) throughout the equatorial Pacific, reflecting ENSO variability. Comparisons at tropical buoy sites (10°S–15°N) over 2007–2009 showed too little ocean heat gain (i.e., flux into the ocean) in ORA-IP (up to 1/3 smaller than buoy measurements) primarily due to latent heat flux errors in ORA-IP. Comparisons with the Stratus buoy (20°S, 85°W) over a longer period, 2001–2009, also show the ORA-IP ensemble has 16 W m−2 smaller net heat gain, nearly all of which is due to too much latent cooling caused by differences in surface winds imposed in ORA-IP.