ABSTRAKT

Inverse radiative design techniques can eliminate much of the trial and error used in conventional or “forward” thermal design. Accurate determination of initial design parameters by inverse analysis can provide the necessary starting point for a detailed design using conventional detailed programs. If successful, this will free designers to determine with more accuracy the best design that will meet their requirements, and will not require limitation to iterative solutions and to the few cases that can normally be examined using conventional techniques. Here, we discuss some of the mathematical techniques for inverse design (Monte Carlo, singular value decomposition (SVD), modified truncated singular value decomposition (MTSVD), and conjugate gradient), their relative strengths and weaknesses, show results generated by some of these techniques for some example problems, and we also indicate some remaining challenges and opportunities for inverse design.