1,720,985 research outputs found
A comparison between eddy-viscosity models and direct numerical simulation: the response of turbulent flow to a volume force
No full textInspired by P. Luchini \& F. Charru's\footnote{Luchini, P., Charru, F., The phase lead of shear stress in shallow-water flow over a perturbed bottom, \textit{J. Fluid Mech.} \textbf{665}, 516-539 (2010)} analysis of the phase lead of the wall-shear stress at a channel's perturbed bottom, we identified a benchmark problem simple enough that it can be solved both by an eddy-viscosity model, similar to those typically used in shallow-water flow calculations, and by direct numerical simulation.
This is the linear response of a turbulent flow's mean-velocity profile to an external volume force. Such a force, of unspecified origin in the present context, was found in to be representative of the perturbation induced by bottom topography, and its consequences were analysed by means of an eddy-viscosity model.
On the other hand, a modification of Luchini, Quadrio \& Zuccher's\footnote{Luchini, P., Quadrio, M., Zuccher, S., The phase-locked mean impulse response of a turbulent channel flow, \textit{Phys. Fluids} \textbf{18}, 121702 (2006).} method to compute the linear impulse response of a wall-bounded turbulent flow allows the response to a volume force to be computed directly.
The comparison exhibits significant differences and suggests that there might be fundamental obstacles to designing an eddy-viscosity model that provides the correct result
A fast algorithm for the estimation of statistical error in DNS (or experimental) time averages
No full textA standard final step in the DNS (but the same can be said of experimental measurements) of turbulence, is the time- and space-averaging of the instantaneous results in order to give their means or correlations or other statistical properties. These averages are necessarily performed over a finite time and space window, and are therefore more correctly just estimates of the ``true'' statistical averages. The choice of the appropriate window size is most often subjectively based on individual experience, but as subtler statistics enter the focus of investigation, an objective criterion becomes desirable. Classical estimators of the averaging error of finite time series fall in two categories: ``batch means'' algorithms, fast but not very accurate, and ARMA methods, slower because they estimate the complete correlation function to start with. Here a modification of the batch means algorithm will be presented, which retains its speed while removing its biasing error. As a side benefit, an automatic determination of batch size is also included. Examples will be given involving both an artificial time series of known statistics and an actual DNS of turbulence
The linear response of turbulent flow to a volume force: Comparison between eddy-viscosity model and DNS
No full textWe identify a benchmark problem simple enough that it can be solved both by an
eddy-viscosity model and by direct numerical simulation: this is the linear response of
a turbulent flow’s mean-velocity profile to an external volume force. An example of
such a force was found in a study of the perturbation induced by bottom topography
by Luchini & Charru (J. Fluid Mech., vol. 656, 2010, pp. 337–341). On the other
hand, a modification of the method by Quadrio & Luchini (Proceedings of the IX
European Turbulence Conference, Southampton, UK, 2002, pp. 715–718) and Luchini
et al. (Phys. Fluids, vol. 18, 2006, 121702) to compute the linear impulse response of
a wall-bounded turbulent flow allows the response to a volume force to be computed
directly. The comparison exhibits significant differences and suggests that there might
be fundamental obstacles to designing an eddy-viscosity model that provides the
correct result
A fast algorithm for the estimation of statistical error in DNS (or experimental) time averages
Full text linkTime- and space-averaging of the instantaneous results of DNS (or experimental measurements) represent a standard final step, necessary for the estimation of their means or correlations or other statistical properties. These averages are necessarily performed over a finite time and space window, and are therefore more correctly just estimates of the âtrueâ statistical averages. The choice of the appropriate window size is most often subjectively based on individual experience, but as subtler statistics enter the focus of investigation, an objective criterion becomes desirable. Here a modification of the classical estimator of averaging error of finite time series, i.e. âbatch meansâ algorithm, will be presented, which retains its speed while removing its biasing error. As a side benefit, an automatic determination of batch size is also included. Examples will be given involving both an artificial time series of known statistics and an actual DNS of turbulence
A comparison between eddy-viscosity models and direct numericalsimulation: the response of turbulent flow to volume forcing
No full textRevisiting negative pressure wound therapy from a mechanobiological perspective supported by clinical and pathological data
No full textNegative pressure wound therapy is used often in the management of surgical incisions, chronic wounds and subacute lesions, and there are numerous publications discussing its clinical application and outcomes. However, whilst clinical use and associated literature have expanded since these systems became commercially available in the 90s, important research and discussion around the mode of action have waned, leading to a deficit in the understanding of how this important therapy influences healing. Further, much research and many publications are predominantly reflective, discussing early theorem, some of which have been proven incorrect, or at least not fully resolved leading to misunderstandings as to how the therapy works, thus potentially denying the clinician the opportunity to optimise use towards improved clinical and economic outcomes. In this narrative review, we discuss established beliefs and challenges to same where appropriate and introduce important new research that addresses the manner in which mechanical strain energy (i.e., deformations) is transferred to tissue and how this influences biological response and healing. In addition, we assess and discuss the effect of different negative pressure dressing formats, how they influence the mode of action and how this understanding can lead to more efficient and effective use and clinical economic outcomes.Funding informationMinistry of Innovation, Science andTechnology, Grant/Award Number:001702603; Mölnlycke Health Car
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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