Application of inverse analysis to illumination designFootnote†

^† Preliminary versions of this work were presented in the 10th Brazilian Congress of Thermal Sciences and Engineering (ENCIT 2004) and in the 19th International Congress of Mechanical Engineering (COBEM 2007).

References

• Boast, WB, 1953. Illumination Engineering. New York: McGraw-Hill; 1953.
   Google Scholar
• Lewis, PD, and Morris, TR, 1998. Responses to domestic poultry to various light sources, World Poultry Sci. J. 54 (1998), pp. 7–25.
   Web of Science ®Google Scholar
• Mark, S, 2000. The IESNA Lighting Handbook. New York: Illuminating Engineering Society of North America; 2000.
   Google Scholar
• Harrison, W, and Anderson, EA, 1916. Illumination efficiencies as determinated in an experimental room, Trans. Illum. Eng. Soc. 11 (1916), pp. 67–91.
   Google Scholar
• Harrison, W, and Anderson, EA, 1920. Coefficients of utilization, Trans. Illum. Eng. Soc. 15 (1920), pp. 97–123.
   Google Scholar
• Moon, P, 1941. Interreflections in rooms, J. Opt. Soc. Am. 31 (1941), pp. 374–382.
   Google Scholar
• Moon, P, and Spencer, DE, 1946a. Light distribution in rooms, J. Franklin Inst. 242 (1946a), pp. 111–141.
   PubMedGoogle Scholar
• Moon, P, and Spencer, DE, 1946b. Light design by the interreflection method, J. Franklin Inst. 242 (1946b), pp. 465–501.
   PubMedGoogle Scholar
• IESNA–Illuminating engineering society of North America, 2000. Rea, Mark Stanley, ed. The IESNA Lighting Handbook: Reference & Application. New York: IESNA; 2000. pp. 9.28–9.51.
   Google Scholar
• EEE – Empresa de Equipamento Elétrico SA, 2002. Portugal: Águeda; 2002, Available at www.eee.pt.
   Google Scholar
• Seewald, A, 2006. "Inverse design analysis with non-gray surfaces: An approach for illumination design". In: Masters Degree Thesis. Graduate of Mechanical Engineering, Federal University of Rio Grande do Sul; 2006.
   Google Scholar
• De Sousa, FL, Soeiro, FJCP, Silva Neto, AJ, and Ramos, FM, 2007. Application of the generalized extremal optimization algorithm to an inverse radiative transfer problem, Inverse Probl. Sci. Eng. 15 (2007), pp. 699–714.
   Web of Science ®Google Scholar
• Cuco, APC, Neto, AJSilva, Velho, HFCampos, and Sousa, FLDe, 2008. Solution of an adsorption problem with an epidemic genetic algorithm and the generalized extremal optimization algorithm, Inverse Probl. Sci. Eng. ifirst (2008), DOI: 10.1080/17415970802083201.
   Google Scholar
• Galski, RL, Sousa, FLDe, Ramos, FM, and Neto, AJSilva, Application of a GEO + SA hybrid optimization algorithm to the solution of an inverse radiative transfer problem, Inverse Probl. Sci. Eng., Accepted for publication.
   Web of Science ®Google Scholar
• Jr, JLugon, Neto, AJSilva, and Santana, CC, A hybrid approach with artificial neural networks, Levenberg–Marquardt and simulated annealing methods for the solution of gas-liquid adsorption inverse problems, Inverse Probl. Sci. Eng., Accepted for publication.
   Web of Science ®Google Scholar
• Hansen, PC, 1998. Rank-Deficient and Discrete Ill-Posed Problems: Numerical Aspects of Linear Inversion. Philadelphia: SIAM; 1998.
   Google Scholar
• França, F, Howell, J, Ezekoye, O, and Morales, JC, 2002. "Inverse design of thermal systems". In: Hartnett, JP, and Irvine, JP, eds. Advances in Heat Transfer. Vol. 36. San Diego: Academic Press; 2002. pp. 1–110.
   Google Scholar
• França, FHR, and Howell, JR, 2006. Transient inverse design of radiative enclosures for thermal processing of materials, Inverse Probl. Sci. Eng. 14 (2006), pp. 423–436.
   Web of Science ®Google Scholar
• Daun, K, França, FHR, Larsen, M, Leduc, G, and Howell, JR, 2006. Comparison of methods for inverse design of radiant enclosures, ASME J. Heat Transfer 128 (2006), pp. 269–282.
   Web of Science ®Google Scholar
• Schneider, PS, and França, FHR, Inverse analysis applied to an illumination design. Presented at Proceedings of the 10th Brazilian Congress of Thermal Sciences and Engineering. ENCIT, Rio de Janeiro, 2004, Brazil.
   Google Scholar
• Mossi, AC, Schneider, PS, França, FHR, Sousa, FLDe, and Neto, AJSilva, Application of the generalized extremal optimization (GEO) algorithm in an illumination inverse design. Presented at Proceedings of the 19th International Congress of Mechanical Engineering. COBEM, Brasília, 2007, Brazil.
   Google Scholar
• De Sousa, FL, Ramos, FM, Paglione, P, and Girardi, RM, 2003. New stochastic algorithm for design optimization, AAIA J. 41 (2003), pp. 1808–1818.
   Web of Science ®Google Scholar
• Hansen, PC, 1990. Truncated SVD solutions to discrete ill-posed problems with ill-determined numerical rank, SIAM J. Sci. Stat. Comp. 11 (1990), pp. 503–518.
   Web of Science ®Google Scholar
• Siegel, R, and Howell, JR, 2002. Thermal Radiation Heat Transfer. Washington: Hemisphere Publishing Corporation; 2002.
   Google Scholar
• Boettcher, S, and Percus, AG, 2001. Optimization with extremal dynamics, Phys. Rev. Lett. 86 (2001), pp. 5211–5214.
   PubMed Web of Science ®Google Scholar
• Bak, P, and Sneppen, K, 1993. Punctuated equilibrium and criticality in a simple model of evolution, Phys. Rev. Lett. 71 (1993), pp. 4083–4086.
   PubMed Web of Science ®Google Scholar