Open Access
Volume 3, 2006
Page(s) 25 - 42
Publié en ligne 9 octobre 2015
  • Aida M., 1982 : Urban albedo as a function of the urban structure – a model experiment (Part I). Boundary-Layer Meteorology, 23, 405–413. [Google Scholar]
  • Adelene N.G., 1995 : Assessment of five radiosity acceleration techniques. Comput. Graphics, 19, 5, 727–738. [Google Scholar]
  • Al-Sanea S.A., 2002 : Thermal performance of building roof elements. Building and Environment, 37, 7, 665–675. [Google Scholar]
  • Arnfield A.J., 2003 : Two decades of urban climate research: a review of turbulence, exchanges of energy and water, and the urban heat island. International Journal of Climatology, 23, 1–26. [CrossRef] [Google Scholar]
  • Arnfield A.J. et Grimmond C.S.B., 1998 : An Urban Canyon Energy Budget Model and itsApplication to Urban Storage Heat Flux Modelling. Energy and Buildings, 27, 61–68. [Google Scholar]
  • Badescu V. et Sicre B., 2003 : Renewable energy for passive house heating. Energy and Buildings, 35, 1085–1096. [Google Scholar]
  • Bozonnet E., Belarbi R. et Allard F., 2005 : Modelling solar effects on the heat and mass transfer in a street canyon, a simplified approach. Solar Energy, 79, 10–24. [Google Scholar]
  • Carslaw H.S. et Jaeger J.C., 1959 : Conduction of Heat in Solids. Oxford University Press, Oxford, 2nd edition, 520 p. [Google Scholar]
  • Chan T.L. et Dong G., 2002 : Validation of a two dimensional pollutant dispersion model in an isolated street canyon. Atmospheric Environment, 36, 861–872. [Google Scholar]
  • Chang C.C. et Shih Z.C., 1998 : An accuracy enhancement algorithm for hierarchical radiosity. Comput. Graphics, 22, 2–3, 225–232. [Google Scholar]
  • Davies M.G., 2003 : A rationale for nodal placement for heat flow calculations in walls. Building and Environment, 38, 247–260. [Google Scholar]
  • De La Flor F.S. et Dominguez S.A., 2004 : Modelling microclimate in urban environments and assessing its influence on the performance of surrounding buildings. Energy and Buildings, 36, 5, 403–413. [Google Scholar]
  • Edmonds I.R., 1968 : Stephan-Boltzmann Law in the Laboratory. American Journal of Physics, 36, 9, 845–846. [Google Scholar]
  • Eliasson I., Offerle B., Grimmond C.S.B. et Lindqvist S., 2006 : Wind fields and turbulence statistics in an urban street canyon. Atmospheric environment, 40, 1–16. [Google Scholar]
  • Grimmond C.S.B., Potter S.K., Zutter H.N. et Souch C., 2001 : Evaluation and application of automated methods for estimating sky view factors in urban areas. International Journal of Climatology, 21, 903–913. [Google Scholar]
  • Harman I.N., Best M.J. et Belcher S.E., 2004 : Radiative exchange in an urban street canyon. Boundary-Layer Meteorology, 110, 301–316. [Google Scholar]
  • Incropera F.P. et De Witt D.P., 1996 : Fundamentals of Heat and Mass Transfer. John Wiley & Sons 4th ed., 885. p. [Google Scholar]
  • Ito N., Kimura K. et Oka J., 1972 : A field experiment study on the convective heat transfer coefficient on the exterior surface of a building. ASHRAE Transactions, 78, 1. [Google Scholar]
  • Johnson G.T. et Watson I.D., 1984 : The determination of view-factors in urban canyons. Journal of Applied Climate and Meteorology. 23, 329–335. [Google Scholar]
  • Kamenetsky E. et Vieru N., 1995 : Model of air flow and air pollution concentration in urban canyons. Boundary-layer Meteorology, 73, 1–2, 203–206. [Google Scholar]
  • Kastner-Klein P. et Federovich E.A., 2001 : Wind-tunnel study of organized and turbulent air motions in street canyons. Engeneering and Industrial Aerodynamics, 89, 849–861. [Google Scholar]
  • Kondo A., Ueno M., Kaga A. et Yamaguchi K., 2001 : The influence of urban canopy configuration on urban albedo. Boundary-Layer Meteorology, 100, 225–242. [Google Scholar]
  • Kusaka H., Kondo H., Kikegawa Y. et Kimura F., 2001 : A simple single-layer urban canopy model for atmospheric models: Comparison with multi-layer and SLAB models. Bound.-Layer Meteor., 101, 329–358. [Google Scholar]
  • Masson V., 2000 : A physically-based scheme for the urban energy budget in atmospheric models. Boundary-layer Meteorology, 94, 357–397. [Google Scholar]
  • Mills G.M., 1993 : Simulation of the energy budget of an urban canyon. I. Model structure and sensitivity test. Atmospheric Environment, 27B(2), 157–170. [Google Scholar]
  • Mills G., 1997a : Building density and interior building temperatures: A physical modeling experiment. Physical Geography, 18 (3), 195–214. [Google Scholar]
  • Mills G., 1997b : The radiative effects of building groups on single structures. Energy and Buildings, 25, 51–61. [Google Scholar]
  • Moller T. et Trumbore B., 1997 : Fast, minimum storage ray-triangle intersection. Journal on Graphic Tools, 2, 1, 21–28. [Google Scholar]
  • Najjar G., Kastendeuch P.P., Stoll M.-P., Colin J.R., Nerry F., Ringenbach N., Bernard J., De Hatten A., Luhahe R. et Viville D., 2004 : Le projet Reclus, télédétection, rayonnement et bilan d’énergie en climatologie urbaine à Strasbourg. La Météorologie, 46, 44–50. [Google Scholar]
  • Nayard S.K., Ikeuchi K. et Kanade T., 1991 : Surface reflection: Physical and geometrical perspectives. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(7), 611–634. [Google Scholar]
  • Oke T.R., 1981 : Canyon geometry and the nocturnal urban heat island: comparison of scale model and field observations. Journal of Climatology, 1, 237–254. [Google Scholar]
  • Ozisik N., 1973 : Radiative transfer and interactions with conduction and convection. Wiley-Interscience Publication, 575 p. [Google Scholar]
  • Pearlmutter D., Berliner P. et Shaviv E., 2005 : Evaluation of urban surface energy fluxes using an open-air scale model. Journal of Applied Meteorology, 44, 532–545. [Google Scholar]
  • Perez R., Seals R., Michalsky J., 1993 : An All-Weather Model for Sky Luminance Distribution - A Preliminary Configuration and Validation. Solar Energy, 50, 3, 235–245. [CrossRef] [Google Scholar]
  • Pianykh O.S., Tyler J.M. et Waggenspack W.N., 1998 : Improved monte carlo form factor integration. Computer Graphics, 22, 6, 723–734. [CrossRef] [Google Scholar]
  • Picot X., 2004 : Thermal comfort in urban spaces: impact of vegetation growth Case study: Piazza della Scienza, Milan, Italy. Energy and Buildings, 36, 329–334. [CrossRef] [Google Scholar]
  • Pitman A.J., 2003 : The evolution of, and revolution in, land surface schemes designed for climate models. International Journal of Climatology, 23, 479–510. [CrossRef] [Google Scholar]
  • Reda I. et Andreas A., 2004 : Solar position algorithm for solar radiation applications. Solar Energy, 76, 577–589. [CrossRef] [Google Scholar]
  • Ringenbach N., 2004 : Bilan radiatif et flux de chaleur en climatologie urbaine : mesures, modélisation et validation sur Strasbourg. Thèse de l’Université Louis Pasteur, Strasbourg I, 166 p. [Google Scholar]
  • Robinson D. et Stone A., 2004 : Solar radiation modelling in the urban context. Solar Energy, 77, 295–309. [CrossRef] [Google Scholar]
  • Robitu M., Musy M., Inard C. et Groleau D., 2006 : Modeling the influence of vegetation and water pond on urban microclimate. Solar Energy, 80, 435–447. [CrossRef] [Google Scholar]
  • Runnalls K.E. et Oke T.R., 2000 : Dynamics and controls of the near-surface heat island of Vancouver, British Columbia. Physical Geography, 21, 283–304. [CrossRef] [Google Scholar]
  • Sakakibara Y., 1996 : A numerical study of the effect of urban geometry upon the surface energy budget. Atmospheric Environment, 30, 3, 487–496. [CrossRef] [Google Scholar]
  • Schroder P. et Hanrahan P., 1993 : On the form factor between two polygons. Computer Graphics Proceedings. ACM SIGGRAPH’93 Proceedings. [Google Scholar]
  • Segura R.J. et Feito F.R., 1998 : An algoritm for determining intersection segment-polygon in 3D. Computer & Graphics, 22, 5, 587–592. [CrossRef] [Google Scholar]
  • Shewchuk J.R., 1996 : Triangle: Engineering a 2D Quality Mesh Generator and Delaunay Triangulator. In: Applied Computational Geometry: Towards Geometric Engineering (Ming C Lin and Dinesh Manocha, editors), volume 1148 of Lecture Notes in Computer Science, Springer, Berlin, 203–222 [CrossRef] [Google Scholar]
  • Shewchuk J.R., 2002 : Delaunay Refinement Algorithms for Triangular Mesh Generation. Computational Geometry: Theory and Applications, 22(1–3), 21–74. [CrossRef] [MathSciNet] [Google Scholar]
  • Smith W.S., Reisner J.M. et Kao C.-Y.J., 2001 : Simulations of flow around a cubical building: comparison with towing-tank data and assessment of radiatively induced thermal effects. Atmospheric Environment, 35, 3811–3821. [CrossRef] [Google Scholar]
  • Spronken-Smith R.A. et Oke T.R., 1999 : Scale modelling of nocturnal cooling in urban parks. Boundary-Layer Meteorology, 93, 287–312. [CrossRef] [Google Scholar]
  • Temps R.C. et Coulson K.L., 1977 : Solar radiation incident upon slopes of different orientations. Solar Energy, 19, 179–184. [CrossRef] [Google Scholar]
  • Terjung W. et O’Rourke P., 1980 : Influence of physical structures on urban energy budgets. Boundary-Layer Meteorology, 19, 421–439. [CrossRef] [Google Scholar]
  • Torrance K. et Sparrow E., 1967 : Theory for Off-Specular Reflection from Rough Surfaces. Journal of the Optical Society of America, 57, 9, 1105–1114. [CrossRef] [Google Scholar]
  • Tuomaala P., Piira K. et Vuolle M., 2000 : A rational method for the distribution of nodes in modelling of transient heat conduction in plane slabs. Building and Environment, 35, 397–406. [CrossRef] [Google Scholar]
  • Xie X., Zhen Huang Z., Jiasong Wang J. et Xie Z., 2005 : The impact of solar radiation and street layout on pollutant dispersion in street canyon. Building and Environment, 40, 201–212. [CrossRef] [Google Scholar]
  • Yamartino R.J. et Wiegand G., 1986 : Development and evaluation of simple models for the flow, turbulence and pollutant concentration fields within an urban street canyon. Athmospheric Environment, 20, 2137–2156. [CrossRef] [Google Scholar]

Les statistiques affichées correspondent au cumul d'une part des vues des résumés de l'article et d'autre part des vues et téléchargements de l'article plein-texte (PDF, Full-HTML, ePub... selon les formats disponibles) sur la platefome Vision4Press.

Les statistiques sont disponibles avec un délai de 48 à 96 heures et sont mises à jour quotidiennement en semaine.

Le chargement des statistiques peut être long.