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Annual Review of Heat Transfer
Vish Prasad (open in a new tab) Department of Mechanical Engineering, University of North Texas, Denton, Texas 76207, USA
Yogesh Jaluria (open in a new tab) Department of Mechanical and Aerospace Engineering, Rutgers-New Brunswick, The State University of New Jersey, Piscataway, NJ 08854, USA
Zhuomin M. Zhang (open in a new tab) George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA

ISSN Print: 1049-0787

ISSN Online: 2375-0294

SJR: 0.363 SNIP: 0.21 CiteScore™:: 1.8

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COMPUTATIONAL NEAR-FIELD RADIATIVE TRANSFER AND NF-RT-FDTD ALGORITHM

pages 59-93
DOI: 10.1615/AnnualRevHeatTransfer.2020032497
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Краткое описание

Understanding the fundamentals of near-field radiative transfer is essential for future development of new sensors and energy harvesting devices. Simulations of such problems would require a coupled solution of the electromagnetic wave equations along with the expressions for thermal emission from a body at finite temperature. Versatile computational tools, which account for the intricate physics and the computational challenges of the problems, are likely to help to the future nanomanufacturing systems and processes. These simulation methodologies should be valid for one-, two-, and three-dimensional geometries with inhomogeneities and arbitrary edges and should be applicable to different materials. In this chapter, we briefly review the recent works on numerical methods used to solve the computational near-field radiative transfer (NFRT) problems. Each of these methods has its own advantages and disadvantages, and no single technique can provide the complete and robust solution for all problems at hand. Then we outline an algorithm based on the finite difference time domain (FDTD) method for one- and two-dimensional NFRT problems. For this, we discuss the details of NF-RT-FDTD algorithm and show how this approach can be applied to surfaces covered with particles as well as with thin films with inhomogeneities. We also present simulations for more complicated biomimetic structures inspired by nature for possible sensing and energy harvesting applications.

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