FYFD

Tag: numerical simulation

  • Martian Landing Physics

    Martian Landing Physics

    A little over a week ago, NASA’s Curiosity rover landed on Mars, the culmination of years of engineering. The mission’s landing, in particular, was the subject of intense scrutiny as Curiosity’s size necessitated some new techniques in the final segments of the landing sequence. As it hit the Martian atmosphere at 13,000 mph, the compression of the carbon dioxide behind the capsule’s shock wave slowed the descent.  At roughly 1,000 mph–speeds still large enough to be supersonic–Curiosity deployed its parachute. Shown above are the parachute in numerical simulation (from Karagiozis et al. 2011), wind tunnel testing at NASA Ames, and during descent thanks to the Mars Reconnaissance Orbiter. The simulation shows contours of streamwise velocity at different configurations; note the bow shock off the capsule and the additional shocks off the parachute. These help generate the drag needed to slow the capsule. For an interesting behind-the-scenes look at the wind tunnel testing for Curiosity’s parachute check out JPL’s four–part video series. Congratulations to all the scientists and engineers who’ve made the rover a success. We look forward to your discoveries! (Photo credits: K. Karagiozis et al., NASA JPL, NASA MRO)

  • The Olympic Torch

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    Today marks the beginning of the 2012 Olympic Games in London. In the opening ceremony, the Olympic flame will complete its journey from Olympia to London, having been carried by some 8,000 torch bearers. Modern Olympic torches are expected to withstand wind, rain, snow, and human error to keep the flame alive and are specially designed and tested for these conditions. Each individual torch is fueled by a mixture of propane and butane stored as a pressurized liquid. The liquid fuel travels through a series of evaporation coils around the burner before combustion. Each torch carries sufficient fuel to burn about fourteen minutes. In addition to computer simulation, the 2012 Olympic torch design was tested in BMW’s Environmental Wind Tunnel to ensure a visible, stable flame for orientations within 45 degrees of vertical in conditions ranging from -5 degrees to 40 degrees Celsius, rain, snow, 35 mph winds, and 50 mph wind gusts. For more on the current torch and previous designs, see How Stuff Works, E&T, and the BBC.

    FYFD is celebrating the Olympics by featuring the role of fluid dynamics in sports starting Monday. If you have any burning questions, feel free to ask or email!

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    Sea Surface Temperatures

    This video shows sea surface temperature results and their seasonal variation from a numerical simulation modeling circulation in the atmosphere and oceans. Modeling such enormous problems requires the development of reasonable models of the turbulent physics, clever algorithms to quickly progress the solutions, relatively low-fidelity (a single grid node may cover tens of kilometers), and enormous computing power. (Video credit: NOAA; via Gizmodo)

  • Fractal Fluids

    Fractal Fluids

    These images from a numerical simulation of a mixing layer between fluids of different density show the development and breakdown to Kelvin-Helmholtz waves.  The black fluid is 3 times denser than the white fluid, and, as the two layers shear past one another, billow-like waves form (Fig 1(a)). Inside those billows, secondary and even tertiary billows form (Fig 1(a) and (b)).  Fig 1 (c)-(e) show successive closeups on these waves, showing their beautiful fractal-like structure. (Photo credit: J. Fontane et al, 2008 Gallery of Fluid Motion) #

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    Salinity Near the Amazon

    This numerical simulation shows the variation of salinity in the Atlantic Ocean near the mouth of the Amazon River over the course of 36 months. The turbulent mixing of the fresh river water and salty ocean shifts with the ebb and flooding of the river. Salt content causes variations in ocean water density, which can strongly affect mixing and transport properties between different depths in the ocean due to buoyancy. Understanding this kind of flow helps predict climate forecasts, rain predictions, ice melting and much more. (Video credit: Mercator Ocean)

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    Visualizing Ocean Currents

    Researchers used computational models of ocean currents to produce this video visualizing worldwide ocean surface currents from June 2005 through December 2007. Dark patterns under the ocean are representative of ocean depths and have been exaggerated to 40x; land topography is exaggerated to 20x. Notice the wide variety of behaviors exhibited in the simulation: some regions experience strong recirculation and eddy production, while others remain relatively calm and unmoving. Occasionally strong currents sweep long lines across the open waters, carrying with them warmth and nutrients that encourage phytoplankton blooms and other forms of ocean life. (Video credit: NASA; submitted by Jason S)

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    Mackerel vs. Eel: Who Swam It Better?

    Which matters more, form or function? This simulation sets out to answer that question by comparing the swimming motion of eels and mackerels. Eels have longer, more rounded body shapes and swim in an undulatory fashion with their whole body, whereas mackerels have shorter bodies with a more elliptical cross-section and primarily move their tails when swimming. The simulation separates body type from swimming motion by creating virtual races between fishes of the same body type using the two forms of swimming. Eels swim at moderate Reynolds numbers where viscous and inertial effects are reasonably balanced.  Under those conditions, eel-like swimming was faster, even with a mackerel’s body type.  At the higher Reynolds numbers where mackerels usually swim, inertial forces domination and the racing fish moved faster if they swam like a mackerel, even with the body of an eel. The results suggest that the swimming motion matters more in each Reynolds number range than the shape of the swimmer. This is a neat way that simulation can answer questions we cannot test with an experiment! (Video credit: I. Borazjani and F. Sotiropoulos)

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    Supersonic Flow Around a Cylinder

    This numerical simulation shows unsteady supersonic flow (Mach 2) around a circular cylinder. On the right are contours of density, and on the left is entropy viscosity, used for stability in the computations. After the flow starts, the bow shock in front of the cylinder and its reflections off the walls and the shock waves in the cylinder’s wake relax into a steady-state condition. About halfway through the video, you will notice the von Karman vortex street of alternating vortices shed from the cylinder, much like one sees at low speeds. The simulation is inviscid to simplify the equations, which are solved using tools from the FEniCS project. (Video credit: M. Nazarov)

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    Atomizing Jets

    The breakup of impinging jets into droplets (also called atomization) and the subsequent dynamics of those droplets are important in applications like jet and rocket engines where the mixing of liquid fuel with oxygen is necessary for efficient combustion. This video showcases recent efforts in high fidelity numerical simulation and modeling of such flows. The complexity of the problem requires clever ways of reducing the computational efforts required. One such method uses adaptotive meshing to concentrate grid points in areas where variables are changing quickly while leaving the grid sparse in areas of less interest. Because the flow is constantly evolving, the mesh must be able to adapt as the simulation steps forward in time. Even so, such calculations typically require supercomputers to complete. (Video credit: X. Chen et al)

  • Jump Rope Aerodynamics

    Jump Rope Aerodynamics

    Researchers have used high-speed video and numerical simulation to capture the effects of aerodynamics on jump roping. After videoing an athlete jumping rope and constructing a jump roping robot (shown above imaged multiple times with a strobe light), they found that the U-shaped tip of the jump rope bends away from the direction of motion. When they built a computer model capable of deforming the jump rope based on its drag, they found the same behavior. They concluded that the “best” jump ropes are lightweight, short, and have small diameters to maximize speed and minimize the drag. #