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Low thermal conductivity boulder with high porosity identified on C-type asteroid (162173) Ryugu
(2019)
C-type asteroids are among the most pristine objects in the Solar System, but little is known about their interior structure and surface properties. Telescopic thermal infrared observations have so far been interpreted in terms of a regolith-covered surface with low thermal conductivity and particle sizes in the centimetre range. This includes observations of C-type asteroid (162173) Ryugu1,2,3. However, on arrival of the Hayabusa2 spacecraft at Ryugu, a regolith cover of sand- to pebble-sized particles was found to be absent4,5 (R.J. et al., manuscript in preparation). Rather, the surface is largely covered by cobbles and boulders, seemingly incompatible with the remote-sensing infrared observations. Here we report on in situ thermal infrared observations of a boulder on the C-type asteroid Ryugu. We found that the boulder’s thermal inertia was much lower than anticipated based on laboratory measurements of meteorites, and that a surface covered by such low-conductivity boulders would be consistent with remote-sensing observations. Our results furthermore indicate high boulder porosities as well as a low tensile strength in the few hundred kilopascal range. The predicted low tensile strength confirms the suspected observational bias6 in our meteorite collections, as such asteroidal material would be too frail to survive atmospheric entry7
Tomographic Reservoir Imaging with DNA-Labeled Silica Nanotracers: The First Field Validation
(2018)
This study presents the first field validation of using DNA-labeled silica nanoparticles as tracers to image subsurface reservoirs by travel time based tomography. During a field campaign in Switzerland, we performed short-pulse tracer tests under a forced hydraulic head gradient to conduct a multisource-multireceiver tracer test and tomographic inversion, determining the two-dimensional hydraulic conductivity field between two vertical wells. Together with three traditional solute dye tracers, we injected spherical silica nanotracers, encoded with synthetic DNA molecules, which are protected by a silica layer against damage due to chemicals, microorganisms, and enzymes. Temporal moment analyses of the recorded tracer concentration breakthrough curves (BTCs) indicate higher mass recovery, less mean residence time, and smaller dispersion of the DNA-labeled nanotracers, compared to solute dye tracers. Importantly, travel time based tomography, using nanotracer BTCs, yields a satisfactory hydraulic conductivity tomogram, validated by the dye tracer results and previous field investigations. These advantages of DNA-labeled nanotracers, in comparison to traditional solute dye tracers, make them well-suited for tomographic reservoir characterizations in fields such as hydrogeology, petroleum engineering, and geothermal energy, particularly with respect to resolving preferential flow paths or the heterogeneity of contact surfaces or by enabling source zone characterizations of dense nonaqueous phase liquids.
In this paper, we bring together the worlds of model order reduction for stochastic linear systems and H-2-optimal model order reduction for deterministic systems. In particular, we supplement and complete the theory of error bounds for model order reduction of stochastic differential equations. With these error bounds, we establish a link between the output error for stochastic systems (with additive and multiplicative noise) and modified versions of the H-2-norm for both linear and bilinear deterministic systems. When deriving the respective optimality conditions for minimizing the error bounds, we see that model order reduction techniques related to iterative rational Krylov algorithms (IRKA) are very natural and effective methods for reducing the dimension of large-scale stochastic systems with additive and/or multiplicative noise. We apply modified versions of (linear and bilinear) IRKA to stochastic linear systems and show their efficiency in numerical experiments.