21
Chapter one: Hydrodynamics
used to determine swimming gaits, speed, and body orientation dynamics (Miller et al.
2004; Watanabe et al. 2011; Goldbogen et al. 2013). Although animal-borne tag data rarely
inform hydrodynamic phenomena directly, they are important tools for assessing a variety swimming metrics that indirectly reflect hydrodynamic performance and its greater
physiological relevance (Potvin et al. 2009, 2012; Sato et al. 2011; Adachi et al. 2014).
Arguably the most difficult aspect of hydrodynamic research on marine mammals is
the quantification of the flows and the forces they generate. Recently, the flows around the
fluke of an actively swimming dolphin have been quantified using digital particle image
velocimetry (DPIV) to measure propulsive forces (Fish et al. 2014). DPIV is an experimental technique that enables the quantification of flow velocities and momentum changes
through the tracking of individual particles suspended in the fluid (Fish and Lauder 2006).
Such an approach is a major step forward for visualizing flows and understanding marine
mammal hydrodynamics, which in the past has been limited to opportunistic observations
with bioluminescent organisms suspended in the water (Rohr et al. 1998). When experimental approaches are not available, computer modeling (or simulation) of the flows about
a swimming animal, a technique known as computational fluid dynamics (CFD), can provide
important insights into how morphology can influence hydrodynamic performance (Fish
et al. 2008; Weber et al. 2009a).
CFD approaches exploit the capacity of modern computer processing power to calculate the motions of fluid particles down to scales of approximately one hundredth of
a millimeter, over body lengths spanning those up to the largest whales. This computational technique enables the visualization of fluid structures that cannot be resolved in
the laboratory due to their extreme scale or ephemeral nature. An important example is
the boundary layer found very close to the body, or the trail of vortices produced by the
sweeping motions of a fluke. One can also simulate, although imperfectly, the turbulence
trailing the body. These data allow the estimation of the force applied on and resulting
motions by a swimmer. Tag design has also involved the use of CFD, to identify the flow
characteristics moving past the sensors and the added drag associated with its attachment
(Hazekamp et al. 2010; Shorter et al. 2014). Such data can help inform tag placement-dependent hydrodynamic effects on the energetic cost of swimming (Pavlov et al. 2007; Pavlov
and Rashad 2012; van der Hoop et al. 2014).
1.5 Lingering mysteries and future challenges
Due to the logistical difficulties associated with research on marine mammals, there remain
extensive challenges and lingering mysteries related to hydrodynamic performance.
Despite the advent of animal-borne tags and significant advances in comparative scaling
analyses across taxa (Sato et al. 2007; Watanabe et al. 2011), there is still a dearth of information on the maneuvering performance envelope in the wild. Moreover, at the largest scale
it is difficult to obtain key data such as the precise length and mass of the tagged animal.
However, the emerging use of aerial vehicles equipped with cameras should make this possible in the future (Koski et al. 2013). Body size data are essential for understanding both the
biomechanics and biology of swimmers, as well as the scaling of drag, swimming speeds,
and ultimately, of the metabolic costs of foraging and living in water (Potvin et al. 2012).
Hydrodynamical modeling is also facing new challenges. In particular, modeling
approaches require more realistic body shapes, especially in the case of the very large
whales that cannot be photographed from all angles in the laboratory or in the field. Again,
the use of drones, together with image and fluid-lensing analysis that remove the distortion optics of water could bring quantum leaps of improvement (Chirayath et al. 2015).
Chapter one: Hydrodynamics
used to determine swimming gaits, speed, and body orientation dynamics (Miller et al.
2004; Watanabe et al. 2011; Goldbogen et al. 2013). Although animal-borne tag data rarely
inform hydrodynamic phenomena directly, they are important tools for assessing a variety swimming metrics that indirectly reflect hydrodynamic performance and its greater
physiological relevance (Potvin et al. 2009, 2012; Sato et al. 2011; Adachi et al. 2014).
Arguably the most difficult aspect of hydrodynamic research on marine mammals is
the quantification of the flows and the forces they generate. Recently, the flows around the
fluke of an actively swimming dolphin have been quantified using digital particle image
velocimetry (DPIV) to measure propulsive forces (Fish et al. 2014). DPIV is an experimental technique that enables the quantification of flow velocities and momentum changes
through the tracking of individual particles suspended in the fluid (Fish and Lauder 2006).
Such an approach is a major step forward for visualizing flows and understanding marine
mammal hydrodynamics, which in the past has been limited to opportunistic observations
with bioluminescent organisms suspended in the water (Rohr et al. 1998). When experimental approaches are not available, computer modeling (or simulation) of the flows about
a swimming animal, a technique known as computational fluid dynamics (CFD), can provide
important insights into how morphology can influence hydrodynamic performance (Fish
et al. 2008; Weber et al. 2009a).
CFD approaches exploit the capacity of modern computer processing power to calculate the motions of fluid particles down to scales of approximately one hundredth of
a millimeter, over body lengths spanning those up to the largest whales. This computational technique enables the visualization of fluid structures that cannot be resolved in
the laboratory due to their extreme scale or ephemeral nature. An important example is
the boundary layer found very close to the body, or the trail of vortices produced by the
sweeping motions of a fluke. One can also simulate, although imperfectly, the turbulence
trailing the body. These data allow the estimation of the force applied on and resulting
motions by a swimmer. Tag design has also involved the use of CFD, to identify the flow
characteristics moving past the sensors and the added drag associated with its attachment
(Hazekamp et al. 2010; Shorter et al. 2014). Such data can help inform tag placement-dependent hydrodynamic effects on the energetic cost of swimming (Pavlov et al. 2007; Pavlov
and Rashad 2012; van der Hoop et al. 2014).
1.5 Lingering mysteries and future challenges
Due to the logistical difficulties associated with research on marine mammals, there remain
extensive challenges and lingering mysteries related to hydrodynamic performance.
Despite the advent of animal-borne tags and significant advances in comparative scaling
analyses across taxa (Sato et al. 2007; Watanabe et al. 2011), there is still a dearth of information on the maneuvering performance envelope in the wild. Moreover, at the largest scale
it is difficult to obtain key data such as the precise length and mass of the tagged animal.
However, the emerging use of aerial vehicles equipped with cameras should make this possible in the future (Koski et al. 2013). Body size data are essential for understanding both the
biomechanics and biology of swimmers, as well as the scaling of drag, swimming speeds,
and ultimately, of the metabolic costs of foraging and living in water (Potvin et al. 2012).
Hydrodynamical modeling is also facing new challenges. In particular, modeling
approaches require more realistic body shapes, especially in the case of the very large
whales that cannot be photographed from all angles in the laboratory or in the field. Again,
the use of drones, together with image and fluid-lensing analysis that remove the distortion optics of water could bring quantum leaps of improvement (Chirayath et al. 2015).