A summary of NASTRAN fluid/structure interaction capabilities

A summary of fluid/structure interaction capabilities for the NASTRAN computer program is presented. Indirect applications of the program towards solving this class of problem were concentrated on. For completeness and comparitive purposes, direct usage of NASTRAN is briefly discussed. The solution technology addresses both steady state and transient dynamic response problems

Long duct nacelle aerodynamic development for DC-10 derivatives

The results are presented of a wind tunnel test utilizing a 4.7-percent-scale semispan model of the DC-10 in the Calspan 8-foot transonic wind tunnel. The effect of a revised long-duct nacelle shape on the channel velocities, the incremental drag relative to the baseline long-duct nacelle, and channel velocities for the baseline long-duct nacelle were determined and compared with data obtained at Ames. The baseline and the revised long-duct nacelles are representative of a CF6-50 mixed-flow configuration and were evaluated on a model of a proposed DC-10 stretched-fuselage configuration. The results showed that the revised long-duct nacelle has an appreciable effect on the inboard channel velocities, resulting in an increased channel Mach number. However, the pressure recovery on the nacelle afterbody was about the same for both nacelles. The lift curves for both long-duct nacelle configurations were the same. The channel pressures measured at Calspan were in good agreement with those measured at Ames for the baseline long-duct nacelle. The incremental drag for the revised nacelle was measured as two to four counts (three counts is approximately equal to one percent of the airplane drag) higher than that of the baseline long-duct nacelle

An application of the multivariate extended Poisson distribution in 2 times 2 contingency tables Final report

Application of multivariate extended Poisson distribution

A multi-spacecraft reanalysis of the atmosphere of Mars

We have conducted a nine-Mars Year (MY) consistent reanalysis of the martian atmosphere covering the period MY 24–32 and making use of data from three different spacecraft. Remotely-sensed measurements of temperature, dust opacity, water ice and ozone from NASA’s Mars Global Surveyor (MGS) and Mars Recconaisance Orbiter (MRO) and ESA’s Mars Express (MEx) were assimilated [1] into a single model simulation, sampled two-hourly over the whole period. This forms a large, regular reanalysis dataset that is being made publicly available as an output of the EU UPWARDS project. The same analysis technique, with an improved model and higher resolution will be conducted with ESA Trace Gas Orbiter (TGO) data as it becomes available

Trace gas assimilation of Mars orbiter observations

Ozone, water vapour and argon are minor constituents in the Martian atmosphere, observations of which can be of use in constraining atmospheric dynamical and physical processes. This is especially true in the winter season of each hemisphere, when the bulk of the main constituent in the atmosphere (CO2 ) condenses in the polar regions shifting the balance of atmospheric composition to a more trace gas rich air mass. Current Mars Global Circulation Models (MGCMs) are able to represent the photochemistry occuring in the atmosphere, with constraints being imposed by comparisons with observations. However, a long term comparison using data assimilation provides a more robust constraint on the model. We aim to provide a technique for trace gas data assimilation for the analysis of observations from current and future satellite missions (such as ExoMars) which observe the spatial and temporal distribution of trace gases on Mars

Investigating microstructural variation in the human hippocampus using non-negative matrix factorization

In this work we use non-negative matrix factorization to identify patterns of microstructural variance in the human hippocampus. We utilize high-resolution structural and diffusion magnetic resonance imaging data from the Human Connectome Project to query hippocampus microstructure on a multivariate, voxelwise basis. Application of non-negative matrix factorization identifies spatial components (clusters of voxels sharing similar covariance patterns), as well as subject weightings (individual variance across hippocampus microstructure). By assessing the stability of spatial components as well as the accuracy of factorization, we identified 4 distinct microstructural components. Furthermore, we quantified the benefit of using multiple microstructural metrics by demonstrating that using three microstructural metrics (T1-weighted/T2-weighted signal, mean diffusivity and fractional anisotropy) produced more stable spatial components than when assessing metrics individually. Finally, we related individual subject weightings to demographic and behavioural measures using a partial least squares analysis. Through this approach we identified interpretable relationships between hippocampus microstructure and demographic and behavioural measures. Taken together, our work suggests non-negative matrix factorization as a spatially specific analytical approach for neuroimaging studies and advocates for the use of multiple metrics for data-driven component analyses