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Assessing Noise Reflections off the Underside of Elevated Bridge Structures: Procedures Using the FHWA Traffic Noise Model

Autor(en):

Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Transportation Research Record: Journal of the Transportation Research Board, , n. 1, v. 1792
Seite(n): 50-56
DOI: 10.3141/1792-07
Abstrakt:

Noise reflections off the underside of elevated bridge structures have the potential to increase traffic noise levels and to degrade the effectiveness of noise barriers at noise-sensitive land uses near proposed highway projects. Assessing the extent to which these reflections will occur requires identifying those roadway segments from which traffic noise will reflect off the underside of an elevated bridge structure and reach a receiver. The geometry involved in assessing noise reflections can often be complex, involving numerous receivers, roadways, and barriers. Because of this complex geometry, manual analysis is beyond the scope of most noise analyses. As a result, assessing noise reflections off the underside of elevated bridge structures has traditionally been difficult and time-intensive. A procedure can be used to assess noise reflections off the underside of elevated bridge structures using features of FHWA’s Traffic Noise Model. The procedure is intended to provide a screening level of analysis to determine whether or not noise reflections off the underside of elevated bridge structures will increase traffic noise levels or degrade noise barrier performance in noise-sensitive areas. If the results of the noise reflections analysis using this screening level procedure are found to increase traffic noise levels or degrade barrier effectiveness, more detailed analysis may be warranted.

Structurae kann Ihnen derzeit diese Veröffentlichung nicht im Volltext zur Verfügung stellen. Der Volltext ist beim Verlag erhältlich über die DOI: 10.3141/1792-07.
  • Über diese
    Datenseite
  • Reference-ID
    10778402
  • Veröffentlicht am:
    12.05.2024
  • Geändert am:
    12.05.2024
 
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