VENUS Ranging Study – Transmission Loss

PDF

Authors
  1. Pelavas, N.
  2. Pecknold, S.
  3. Heard, G.J.
Corporate Authors
Defence Research and Development Canada, Atlantic Research Centre, Halifax NS (CAN)
Abstract
The underwater acoustic propagation models OASES and PECan are employed to study transmission loss (TL) to the Victoria Experimental Network Under the Sea (VENUS) sensor nodes in the Strait of Georgia as a consequence of Her Majesty’s Canadian (HMC) ships operating at the Canadian Forces Maritime Experimental and Test Ranges (CFMETR). Four representative frequencies are studied for a shallow acoustic source, and both hydrophones and bottom-mounted seismometers are considered as receivers at each VENUS node. Bathymetry, measured conductivity, temperature, depth (CTDs), and sediment type are taken into account to study TL as affected by monthly changes in sound velocity profile. It is found that the VENUS node, Delta Dynamics Laboratory (DDL-06), displays the minimum TL at 130 Hz with OASES results indicating horizontal/vertical particle velocity seismic losses of 114/124 dB in February/December, and a PECan result giving pressure loss of 90 dB in January. The VENUS node, East Node (EN), has similar minimal TL values, whereas the Central Node (CN) has higher TL due to a shallow bank off Gabriola Island interfering with line-of-sight acoustic transmissions from CFMETR. It is important to note that the OASES modelling presented in this report, which is mainly used to provide seismic TL, is derived from a range-independent environment. Therefore, the OASES results are inherently less accurate than corresponding PECan results especially in the case of modelling TL to CN where the

Il y a un résumé en français ici.

Keywords
Strait of Georgia;CFMETR;VENUS;underwater acoustics;transmission loss
Report Number
DRDC-RDDC-2014-R181 — Scientific Report
Date of publication
01 Dec 2014
Number of Pages
36
DSTKIM No
CA040187
CANDIS No
801275
Format(s):
Electronic Document(PDF)

Permanent link

Document 1 of 1

Date modified: