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Conduction and Radiation Equation Discretization in Thermal Analysis

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This lecture focuses on the discretization of the conduction equation and the linearization of the radiation equation. Students will learn to manipulate equations for surface radiation, including internal surfaces and unsteady problems, using previous time step temperatures to calculate heat transfer coefficients. The session emphasizes the importance of utilizing weather data, particularly the Typical Meteorological Year (TMY) datasets, to analyze design and operational conditions across different climates. A practical overview of the eQUEST software will also be included for HVAC control issues.

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Conduction and Radiation Equation Discretization in Thermal Analysis

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Presentation Transcript

  1. Lecture Objectives: • Finish with discretization for conduction equitation • Learn about linearization of radiation equation • Learn about eOUEST

  2. Top view Homework assignment 2 T_north_o Tnorth_i 2.5 m Tair_in Surface radiation Tinter_surf 8 m IDIR 8 m conduction Idif East North Teast_i Teast_o Tair_out Glass Surface radiation Idif IDIR

  3. Tj Ti Linearization of radiation equationsSurface to surface radiation Equations for internal surfaces radiation Last term in equation can be rearranged: For unsteady steady problem: Linearized equations: Calculate h based on temperatures from previous time step Where “radiation coefficient” is:

  4. Weather data Design condition vs. Operation condition Design whether parameters Winter • Temperature Summer • Temperature and RH - Solar radiation – clear sky no pollution

  5. Weather data for ES analyses • Representative (typical) data • Characteristic for the location and longer period of time • TMY , TMY2, TMY3 database • Typical Meteorological Year 2 (TMY2) • data files are created from the National Solar Radiation Data Base (NSRDB) • a solar radiation and meteorological database (1961-1990 for TMY2 and 1991-2005 for TMY3)

  6. Typical Meteorological Year • http://rredc.nrel.gov/solar/old_data/nsrdb/1991-2005/tmy3/ • Large number of locations • Very compact data base • http://www.nrel.gov/docs/fy08osti/43156.pdf • You need to use data reader converter • write your one ore use already developed

  7. Typical Meteorological Year • Structure (many weather parameters) • Real data (no averaging) 1960 1961 1962 ………………….. 1990 January February December August

  8. Case when HVAC controls T air Initial condition and “Warming-up” Solution Internal air Day 3 Day 1 Day 2

  9. eQUESTsoftware http://www.doe2.com/equest/

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