57 research outputs found
Assessment of uncertainties in hot-wire anemometry and oil-film interferometry measurements for wall-bounded turbulent flows
In this study, the sources of uncertainty of hot-wire anemometry (HWA) and
oil-film interferometry (OFI) measurements are assessed. Both statistical and
classical methods are used for the forward and inverse problems, so that the
contributions to the overall uncertainty of the measured quantities can be
evaluated. The correlations between the parameters are taken into account
through the Bayesian inference with error-in-variable (EiV) model. In the
forward problem, very small differences were found when using Monte Carlo (MC),
Polynomial Chaos Expansion (PCE) and linear perturbation methods. In flow
velocity measurements with HWA, the results indicate that the estimated
uncertainty is lower when the correlations among parameters are considered,
than when they are not taken into account. Moreover, global sensitivity
analyses with Sobol indices showed that the HWA measurements are most sensitive
to the wire voltage, and in the case of OFI the most sensitive factor is the
calculation of fringe velocity. The relative errors in wall-shear stress,
friction velocity and viscous length are 0.44%, 0.23% and 0.22%, respectively.
Note that these values are lower than the ones reported in other wall-bounded
turbulence studies. Note that in most studies of wall-bounded turbulence the
correlations among parameters are not considered, and the uncertainties from
the various parameters are directly added when determining the overall
uncertainty of the measured quantity. In the present analysis we account for
these correlations, which may lead to a lower overall uncertainty estimate due
to error cancellation. Furthermore, our results also indicate that the crucial
aspect when obtaining accurate inner-scaled velocity measurements is the
wind-tunnel flow quality, which is more critical than the accuracy in
wall-shear stress measurements
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Model selection for tumor growth with nonlinear mechanical effects
Accurately modeling in vivo tumor growth is a persistent challenge due to the complexity of tumors and their environments. Accurate models are sought after for their potential to guide treatments and help researchers discover or better understand the underlying biological processes. Previous research has identified a reaction-diffusion formulation coupled with mechanical forces that performs well at modeling tumor growth. The focus of the current research was a similar formulation with a nonlinear constitutive equation instead of a linear constitutive equation for the mechanical forces. In this study the models performed similarly, with the nonlinear model predictions being slightly closer to the actual actual tumor growth on average. This indicates that the linear model may be a sufficiently close approximation, though the parameter estimation procedure needs improvement. Then other nonlinear models can be studied easily using the code developed for this work.Computational Science, Engineering, and Mathematic
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