CSTB, Centre Scientifique et Technique du B�timent

CSTB is the French National Center for Building Science and Technology. Its main activities are scientific and applied research, technical consulting, product quality assessment and knowledge dissemination. CSTB employs about 600 persons, including more than 300 engineers, working in a wide range of domains such as building materials, aerodynamics, acoustics, lighting, computer aided design, economics, sociology, health,...

The acoustics department counts 35 engineers and high level technicians working in all domains related to building acoustics: room acoustics, outdoor propagation, sound and vibration insulation, product testing and certification, virtual reality, training,...

CSTB has more than 30 years of experience in the domain of outdoor sound propagation, covering standard and experimental measurement techniques, scale models, numerical modelling and virtual reality techniques. CSTB is also the author of the commercial MITHRA software package, a reference for outdoor traffic noise prediction in France and now available in over 25 countries.

Many numerical tools have been developed and extensively used in operational work for the prediction of the efficiency of complex screens, long-range propagation under real meteorological conditions over hilly ground or through forests. These tools are based on such different methods as Gaussian Beams, Uniform Theory of Diffraction, Boundary Element Method or the Parabolic Equation. Recent research work aims the coupling of these methods to provide a more comprehensive model taking into account the combined effects of ground, screens and meteorology.

CSTB has actively participated in the development and the validation of the NMPB standard: the New French Model for Noise Prediction, taking into account meteorological conditions in a more realistic way than any other national or international standard.

CSTB is a partner in the Harmonoise project and has a major role in WP2, Reference Propagation Models, and WP3, Building the Engineering Prediction Model.