Radiative heat transfer in the discrete element method using distance based approximations

Johnson E. F., TARI İ., BAKER D. K.

POWDER TECHNOLOGY, cilt.380, ss.164-182, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 380
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1016/j.powtec.2020.11.050
  • Dergi Adı: POWDER TECHNOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Applied Science & Technology Source, Chemical Abstracts Core, Chimica, Communication Abstracts, Compendex, Computer & Applied Sciences, EMBASE, INSPEC, Metadex, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.164-182
  • Anahtar Kelimeler: Discrete Element Method, Monte Carlo, Particle-particle radiation, Particle-wall radiation, Heat transfer in particle beds, Solid particle solar receiver, EFFECTIVE THERMAL-CONDUCTIVITY, PACKED PEBBLE BEDS, PARTICLE SCALE, DEM, SIMULATION, MODEL
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

A model to estimate radiative heat transfer in particle beds is developed for use in the Discrete Element Method (DEM). Monte Carlo ray tracing simulations are run to find the Radiation Distribution Factor (RDF) between pairs of particles and between particles and a wall, in particle beds with random packing. Curves are found to express the average RDF as a function of distance, and within DEM these aims arc used to estimate particle-particle and particle-wall radiative transfer. The resulting Distance Based Approximation model is computationally efficient and simple to implement. RDF-distance curves are given as a set of tables covering two particle emissivitics (0.65, 0.86), four wall emissivities (0.4, 0.6, 0.8,1.0), and five solid fractions (0.25, 035, 0.45, 0.55, 0.64). The accuracy of the model is investigated, with accuracy sufficient for many engineering applications shown. An initial implementation is demonstrated for a heat exchanger with a dense granular flow. (C) 2020 Elsevier B.V. All rights reserved.