Predicting Outdoor Sound

Exploiting ground effects for surface transport noise abatement

“…This results in a complex ground impedance, defined as the ratio of sound pressure to (the normal component of particle) velocity at the surface, and, not only is the magnitude of sound reduced on reflection, but also the phase change due to the finite (complex) ground impedance combines with the phase change due to path length difference. This has the consequence that, for a given source-receiver geometry, the first destructive interference occurs at a lower frequency than over hard ground and leads to the well-known reduction in outdoor noise levels, often called ground attenuation, that features in many prediction schemes and has been studied extensively [2]. Even if the ground is flat, alongside typical surface transport corridors the ground impedance varies with range.…”

“…The distribution of the scattered sound depends on the roughness topology, the ratio of the roughness dimensions to the incident wavelength and the relative locations of source and receiver [2]. As long as a sufficient fraction of the reflected sound retains a phase relationship with the incident sound (i.e.…”

“…Not surprisingly, the most common ground type for which data are available is "grassland". Table 2 lists values of effective flow resistivity and effective depth for several types of grassland obtained by using the physically admissible two-parameter variable porosity impedance model [2,10,13] to fit data for short range level difference magnitudes [10,13]. The second parameter of the variable porosity model, other than effective flow resistivity, can be stated either as rate of change of porosity with depth (abbreviated later to porosity rate) or as effective depth.…”

“…Moreover it is pointed out in detail elsewhere [10][11][12] that it is not advisable to use single parameter semiempirical models for representing ground impedance since (a) they are not physically admissible (for example at low frequencies they lead to predictions of negative real parts of the surface impedance and complex density), (b) they do not perform as well in fitting short range propagation data as other physically admissible impedance models and (c) that a result of the different frequency dependence of impedance spectra they predict, if used to predict long range ground effect spectra, they yield predic- (a) Predictions of the potential variation in excess attenuation spectra with source height 0.05 m, receiver height 4 m and horizontal separation 100 m over "grassland" with highest and lowest impedance spectra represented by the 2-parameter variable porosity model (solid and dot-dash black lines respectively see Table 2) and by the Delany and Bazley single parameter empirical model for categories D and E in Table 1 (broken and solid blue lines respectively) (b) predictions of the seasonal variation in excess attenuation spectra over "lawn" for the same geometry using the 2-parameter variable porosity model parameters for mean (solid line), maximum and minimum (broken lines) impedance spectra. Moderate turbulence is assumed [2]. tions that differ significantly from those resulting from use of physically admissible models that, in any case, give better fits to short range data.…”

“…Figure 1 5 Table 3: Mean, maximum and minimum parameter values corresponding to fits to short range level difference spectra over lawn using the two-parameter variable porosity impedance model [11]. cess attenuation spectra in a moderately turbulent atmosphere [2] for (point) source height 0.05 m, receiver height 4 m and range 100 m using the two-parameter variable porosity model for the lowest and highest effective flow resistivity values listed in Table 2 and the single parameter empirical model with the flow resistivity values listed for ground categories D and E in Table 1. Figure 1(b) shows excess attenuation spectra for the same geometry and turbulence parameters for the maximum, minimum and mean parameter values listed in Table 3.…”