3D Particle Tracking Velocimetry Method: Advances and Error Analysis

A full three-dimensional particle tracking system was developed and tested. By using three separate CCDs placed at the vertices of an equilateral triangle, the threedimensional location of particles can be determined. Particle locations measured at two different times can then be used to create a three-component, three-dimensional velocity field. Key developments are: the ability to accurately process overlapping particle images, offset CCDs to significantly improve effective resolution, allowance for dim particle images, and a hybrid particle tracking technique ideal for three-dimensional flows when only two sets of images exist. An in-depth theoretical error analysis was performed which gives the important sources of error and their effect on the overall system. This error analysis was verified through a series of experiments, which utilized a test target with 100 small dots per square inch. For displacements of 2.54mm the mean errors were less than 2% and the 90% confidence limits were less than 5.2 μm in the plane perpendicular to the camera axis, and 66 μm in the direction of the camera axis. The system was used for flow measurements around a delta wing at an angle of attack. These measurements show the successful implementation of the system for three-dimensional flow velocimetry

Experiments on Passive Hypervelocity Boundary-Layer Control Using an Ultrasonically Absorptive Surface

Recently performed linear stability analyses suggested that transition could be delayed in hypersonic boundary layers by using an ultrasonically absorptive surface to damp the second mode (Mack mode). Boundary-layer transition experiments were performed on a sharp 5.06-deg half-angle round cone at zero angle of attack in the T5 Hypervelocity Shock Tunnel to test this concept. The cone was constructed with a smooth surface around half the cone circumference (to serve as a control) and an acoustically absorptive porous surface on the other half. Test gases investigated included nitrogen and carbon dioxide at M∞ ≃ 5 with specific reservoir enthalpy ranging from 1.3 to 13.0 MJ/kg and reservoir pressure ranging from 9.0 to 50.0 MPa. Comparisons were performed to ensure that previous results obtained in similar experiments (on a regular smooth surface) were reproduced, and the results were extended to examine the effects of the porous surface. These experiments indicated that the porous surface was highly effective in delaying transition provided that the pore size was significantly smaller than the viscous length scale

On imploding cylindrical and spherical shock waves in a perfect gas

The problem of a cylindrically or spherically imploding and reflecting shock wave in a flow initially at rest is studied without the use of the strong-shock approximation. Dimensional arguments are first used to show that this flow admits a general solution where an infinitesimally weak shock from infinity strengthens as it converges towards the origin. For a perfect-gas equation of state, this solution depends only on the dimensionality of the flow and on the ratio of specific heats. The Guderley power-law result can then be interpreted as the leading-order, strong-shock approximation, valid near the origin at the implosion centre. We improve the Guderley solution by adding two further terms in the series expansion solution for both the incoming and the reflected shock waves. A series expansion, valid where the shock is still weak and very far from the origin, is also constructed. With an appropriate change of variables and using the exact shock-jump conditions, a numerical, characteristics-based solution is obtained describing the general shock motion from almost infinity to very close to the reflection point. Comparisons are made between the series expansions, the characteristics solution, and the results obtained using an Euler solver. These show that the addition of two terms to the Guderley solution significantly extends the range of validity of the strong-shock series expansion

Block Forests:random forests for blocks of clinical and omics covariate data

Background In the last years more and more multi-omics data are becoming available, that is, data featuring measurements of several types of omics data for each patient. Using multi-omics data as covariate data in outcome prediction is both promising and challenging due to the complex structure of such data. Random forest is a prediction method known for its ability to render complex dependency patterns between the outcome and the covariates. Against this background we developed five candidate random forest variants tailored to multi-omics covariate data. These variants modify the split point selection of random forest to incorporate the block structure of multi-omics data and can be applied to any outcome type for which a random forest variant exists, such as categorical, continuous and survival outcomes. Using 20 publicly available multi-omics data sets with survival outcome we compared the prediction performances of the block forest variants with alternatives. We also considered the common special case of having clinical covariates and measurements of a single omics data type available. Results We identify one variant termed “block forest” that outperformed all other approaches in the comparison study. In particular, it performed significantly better than standard random survival forest (adjusted p-value: 0.027). The two best performing variants have in common that the block choice is randomized in the split point selection procedure. In the case of having clinical covariates and a single omics data type available, the improvements of the variants over random survival forest were larger than in the case of the multi-omics data. The degrees of improvements over random survival forest varied strongly across data sets. Moreover, considering all clinical covariates mandatorily improved the performance. This result should however be interpreted with caution, because the level of predictive information contained in clinical covariates depends on the specific application. Conclusions The new prediction method block forest for multi-omics data can significantly improve the prediction performance of random forest and outperformed alternatives in the comparison. Block forest is particularly effective for the special case of using clinical covariates in combination with measurements of a single omics data type

Evolution of antiferromagnetic domains in the all-in-all-out ordered pyrochlore Nd2_2Zr2_2O7_7

We report the observation of magnetic domains in the exotic, antiferromagnetically ordered all-in-all-out state of Nd$_2$Zr$_2$O$_7$, induced by spin canting. The all-in-all-out state can be realized by Ising-like spins on a pyrochlore lattice and is established in Nd$_2$Zr$_2$O$_7$ below 0.31 K for external magnetic fields up to 0.14 T. Two different spin arrangements can fulfill this configuration which leads to the possibility of magnetic domains. The all-in-all-out domain structure can be controlled by an external magnetic field applied parallel to the [111] direction. This is a result of different spin canting mechanism for the two all-in-all-out configurations for such a direction of the magnetic field. The change of the domain structure is observed through a hysteresis in the magnetic susceptibility. No hysteresis occurs, however, in case the external magnetic field is applied along [100].Comment: Accepted for publication in Phys. Rev. B, 6 pages, 6 figure

Near-inertial wave scattering by random flows

The impact of a turbulent flow on wind-driven oceanic near-inertial waves is examined using a linearised shallow-water model of the mixed layer. Modelling the flow as a homogeneous and stationary random process with spatial scales comparable to the wavelengths, we derive a transport (or kinetic) equation governing wave-energy transfers in both physical and spectral spaces. This equation describes the scattering of the waves by the flow which results in a redistribution of energy between waves with the same frequency (or, equivalently, with the same wavenumber) and, for isotropic flows, in the isotropisation of the wave field. The time scales for the scattering and isotropisation are obtained explicitly and found to be of the order of tens of days for typical oceanic parameters. The predictions inferred from the transport equation are confirmed by a series of numerical simulations. Two situations in which near-inertial waves are strongly influenced by flow scattering are investigated through dedicated nonlinear shallow-water simulations. In the first, a wavepacket propagating equatorwards as a result from the $\beta$-effect is shown to be slowed down and dispersed both zonally and meridionally by scattering. In the second, waves generated by moving cyclones are shown to be strongly disturbed by scattering, leading again to an increased dispersion.Comment: Accepted for publication in Phys. Rev. Fluid

The influence of lipids on the fate of nitrogen during hydrothermal liquefaction of protein-containing biomass

Nitrogen (N) in the bio-crude obtained from hydrothermal liquefaction (HTL) of protein-containing biomass not only reduces the heating value of fuels, but also increases cost for upgrading to meet the existing fuel standards. Considerable work so far had been focused on N-containing heterocycles formed via Maillard reactions. However, limited information is available on the influence of lipids, as the amides formation could compete with the Maillard reactions, further affecting the fate of N. The objective of this work is therefore to identify the influence of lipids on the nitrogen distribution in the different product phases, with a particular focus on the reaction of N-containing compounds, trying to achieve deeper understanding about reaction mechanism of HTL. In this study, we tested a set of model compounds (lactose as model carbohydrate, lysine as model protein, palmitic acid as model component of a lipid) to conduct HTL. The model compounds were treated individually and in mixtures at 250 - 350 °C for batch reaction times of 20 min. We investigated the N-distribution in the different HTL-products, mainly focusing on the bio-crude. At 300 °C, only 4.9 wt.% of N distribution (defined as the amount of N in the product relative to that in the feedstocks) is found from HTL of single lysine, while 43.6 wt.% of that is obtained from HTL of the ternary mixture. This is most likely because the higher yield (54.1wt.%) of bio-crude produced from mixture. Specific N-containing compounds in the bio-crude were quantified. With addition of lipids, less yields of typical Maillard reaction products like pyrazines and caprolactam, generated from HTL of carbohydrates and proteins, were obtained, while amides are revealed with significant yield of 2.1 wt.%, indicating that in the presence of lipids, amide formation competes with the generation of Maillard reaction products. These results provide valuable insights for the transformation of nitrogen as well as the reaction pathways of complex systems such as sewage sludge, micro algae, food waste and on the like