Linear and nonlinear measures of ocean acoustic environmental sensitivity

Dosso, Stan E.; Giles, Peter M.; Brooke, Gary H.; McCammon, Diana F.; Pecknold, Sean; Hines, Paul C.

doi:10.1121/1.2382719

Cited by 26 publications

(11 citation statements)

References 3 publications

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“…The environmental parameters and uncertainties considered are based on the Malta Plateau, a well-studied shallow-water region of the Mediterranean Sea. 2,12 The environmental model, illustrated in Fig. 1, is comprised of a water column of depth D = 131 m over a seabed consisting of three homogeneous layers.…”

Section: A Test Case and Implementationmentioning

confidence: 99%

“…Although this comparison is often carried out qualitatively, quantitative sensitivity measures can be defined. 1, 2 The most sensitive parameters are those with the greatest effect on the fields; these parameters are often considered the most important, since errors or uncertainties in these parameters are potential sources of errors in model predictions.…”

Section: Introductionmentioning

confidence: 99%

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Spatial field shifts in ocean acoustic environmental sensitivity analysis

Dosso

Morley

Giles

et al. 2007

The Journal of the Acoustical Society of America

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This article examines the effects of spatial field shifts in ocean acoustic environmental sensitivity analysis. Acoustic sensitivity studies are typically based on comparing acoustic fields computed for a reference environmental model and for a perturbed model in which one or more parameters have been changed. The perturbation to the acoustic field due to the perturbed environment generally includes a component representing a spatial shift of the field (i.e., local field structure remains coherent, but shifts in range and/or depth) and a component representing a change to the shifted field. Standard sensitivity measures based on acoustic perturbations at a fixed point can indicate high sensitivity in cases where the field structure changes very little, but is simply shifted by a small spatial offset; this can conflict with an intuitive understanding of sensitivity. This article defines and compares fixed-point and field-shift corrected sensitivity measures. The approaches are illustrated with examples of deterministic sensitivity (i.e., sensitivity to a specific environmental change) and stochastic sensitivity (sensitivity to environmental uncertainty) in range-independent and range-dependent environments.

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Section: A Test Case and Implementationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatial field shifts in ocean acoustic environmental sensitivity analysis

Dosso

Morley

Giles

et al. 2007

The Journal of the Acoustical Society of America

Self Cite

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show abstract

“…Dosso, et al [4] recently commented on the difficulty of making the leap from local to global sensitivity measures, but they did not use this terminology. A more complete discussion will not fit here, but we recommend considering the following points:…”

Section: Applying Sensitivity Analysis To Computational Mechanics Modelsmentioning

confidence: 99%

Computing the parameter sensitivities of outdoor sound propagation in a random environment

Pettit

Wilson

2008

The Journal of the Acoustical Society of America

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Computational forecasts of near-ground sound levels are compromised by uncertainty (e.g., randomness) and error (e.g., grid resolution) in the atmosphere and terrain representations, and by simplified or incorrect physics. For an incompletely known environment, a model's predictive power cannot be assessed without first quantifying the sensitivity of its forecasts to the full range of every parameter. Knowledge of these sensitivities throughout the spatial domain also is essential for effectively investing data-gathering resources to support sound propagation forecasts. Sensitivity analysis therefore is central to raising the relevance of computational acoustics in practical applications. These considerations should motivate practitioners of computational acoustics to adopt a consistent framework for sensitivity and uncertainty analyses. Topics to be discussed include: (1) standard uncertainty taxonomies in computational mechanics, (2) why uncertainty about a parameter should be distinguished from sensitivity of a model to that parameter, (3) sources of uncertainty in the near-ground acoustics, (4) a sampling-based sensitivity analysis framework that facilitates estimating typical and extreme values of sensitivities at each point in the spatial domain (i.e., full-field sensitivities), (5) factors to be aware of when applying sensitivity analysis to forecasts of near-ground sound propagation, and (6) ways of representing sensitivity estimates to facilitate insight.

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“…In the mid-frequency range (1 to 10 kHz), typically used by anti-submarine warfare (ASW) sonars, uncertainty in sound speed profile (SSP) has significant impact on the modeled transmission loss (Dosso 2003;Dosso et al 2007;LePage 2006a, b, c;Finette 2006) used in sonar performance predictions. The output of sonar performance models is important when planning the placement of sonar assets during ASW sonar operations.…”

Section: Introductionmentioning

confidence: 99%

Classification of acoustically stable areas using empirical orthogonal functions

et al. 2011

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Sonar performance modeling is crucial for submarine and anti-submarine operations. The validity of sonar performance models is generally limited by environmental uncertainty, and particularly uncertainty in the vertical sound speed profile (SSP). Rapid environmental assessment (REA) products, such as oceanographic surveys and ocean models may be used to reduce this uncertainty prior to sonar operations. Empirical orthogonal functions (EOF) applied on the SSPs inherently take into account the vertical gradients and therefore the acoustic properties. We present a method that employs EOFs and a grouping algorithm to divide a large group of SSPs from an ocean model simulation into smaller groups with similar SSP characteristics. Such groups are henceforth called acoustically stable groups. Each group represents a subset in space and time within the ocean model domain. Regions with low acoustic variability contain large and geographically contiguous acoustically stable groups. In contrast, small or fragmented acoustically stable groups are found in regions with high acoustic variability. The main output is a map of the group distribution. This is a REA product in itself, but the map may also be used as a planning aid for REA survey missions.

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Linear and nonlinear measures of ocean acoustic environmental sensitivity

Cited by 26 publications

References 3 publications

Spatial field shifts in ocean acoustic environmental sensitivity analysis

Spatial field shifts in ocean acoustic environmental sensitivity analysis

Computing the parameter sensitivities of outdoor sound propagation in a random environment

Classification of acoustically stable areas using empirical orthogonal functions

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