443 research outputs found
Synthetic Turbulence, Fractal Interpolation and Large-Eddy Simulation
Fractal Interpolation has been proposed in the literature as an efficient way
to construct closure models for the numerical solution of coarse-grained
Navier-Stokes equations. It is based on synthetically generating a
scale-invariant subgrid-scale field and analytically evaluating its effects on
large resolved scales. In this paper, we propose an extension of previous work
by developing a multiaffine fractal interpolation scheme and demonstrate that
it preserves not only the fractal dimension but also the higher-order structure
functions and the non-Gaussian probability density function of the velocity
increments. Extensive a-priori analyses of atmospheric boundary layer
measurements further reveal that this Multiaffine closure model has the
potential for satisfactory performance in large-eddy simulations. The
pertinence of this newly proposed methodology in the case of passive scalars is
also discussed
Dynamical analysis of extreme precipitation in the US northeast based on large-scale meteorological patterns
This is the author accepted manuscript. The final version is available from Springer via the DOI in this record.Previous work has identified six large-scale meteorological patterns (LSMPs) of dynamic tropopause height associated with extreme precipitation over the Northeast US, with extreme precipitation defined as the top 1% of daily station precipitation. Here, we examine the three-dimensional structure of the tropopause LSMPs in terms of circulation and factors relevant to precipitation, including moisture, stability, and synoptic mechanisms associated with lifting. Within each pattern, the link between the different factors and extreme precipitation is further investigated by comparing the relative strength of the factors between days with and without the occurrence of extreme precipitation. The six tropopause LSMPs include two ridge patterns, two eastern US troughs, and two troughs centered over the Ohio Valley, with a strong seasonality associated with each pattern. Extreme precipitation in the ridge patterns is associated with both convective mechanisms (instability combined with moisture transport from the Great Lakes and Western Atlantic) and synoptic forcing related to Great Lakes storm tracks and embedded shortwaves. Extreme precipitation associated with eastern US troughs involves intense southerly moisture transport and strong quasi-geostrophic forcing of vertical velocity. Ohio Valley troughs are associated with warm fronts and intense warm conveyor belts that deliver large amounts of moisture ahead of storms, but little direct quasi-geostrophic forcing. Factors that show the largest difference between days with and without extreme precipitation include integrated moisture transport, low-level moisture convergence, warm conveyor belts, and quasi-geostrophic forcing, with the relative importance varying between patterns.National Science FoundationSwiss National Science Foundation (SNSF
Revisiting the Local Scaling Hypothesis in Stably Stratified Atmospheric Boundary Layer Turbulence: an Integration of Field and Laboratory Measurements with Large-eddy Simulations
The `local scaling' hypothesis, first introduced by Nieuwstadt two decades
ago, describes the turbulence structure of stable boundary layers in a very
succinct way and is an integral part of numerous local closure-based numerical
weather prediction models. However, the validity of this hypothesis under very
stable conditions is a subject of on-going debate. In this work, we attempt to
address this controversial issue by performing extensive analyses of turbulence
data from several field campaigns, wind-tunnel experiments and large-eddy
simulations. Wide range of stabilities, diverse field conditions and a
comprehensive set of turbulence statistics make this study distinct
Injury Risk Estimation Expertise Assessing the ACL Injury Risk Estimation Quiz
Background: Available methods for screening anterior cruciate ligament (ACL) injury risk are effective but limited in application as
they generally rely on expensive and time-consuming biomechanical movement analysis. A potential efficient alternative to biomechanical
screening is skilled movement analysis via visual inspection (ie, having experts estimate injury risk factors based on
observations of athletesâ movements).
Purpose: To develop a brief, valid psychometric assessment of ACL injury risk factor estimation skill: the ACL Injury Risk Estimation
Quiz (ACL-IQ).
Study Design: Cohort study (diagnosis); Level of evidence, 3.
Methods: A total of 660 individuals participated in various stages of the study, including athletes, physicians, physical therapists,
athletic trainers, exercise science researchers/students, and members of the general public in the United States. The ACL-IQ was
fully computerized and made available online (www.ACL-IQ.org). Item sampling/reduction, reliability analysis, cross-validation,
and convergent/discriminant validity analysis were conducted to optimize the efficiency and validity of the assessment.
Results: Psychometric optimization techniques identified a short (mean time, 2 min 24 s), robust, 5-item assessment with high
reliability (test-retest: r = 0.90) and consistent discriminability (average difference of exercise science professionals vs general
population: Cohen d = 1.98). Exercise science professionals and general population individuals scored 74% and 53% correct,
respectively. Convergent and discriminant validity was demonstrated. Scores on the ACL-IQ were most associated with ACL
knowledge and various cue utilities and were least associated with domain-general spatial/decision-making ability, personality,
or other demographic variables. Overall, 23% of the total sample (40% exercise science professionals; 6% general population)
performed better than or equal to the ACL nomogram.
Conclusion: This study presents the results of a systematic approach to assess individual differences in ACL injury risk factor
estimation skill; the assessment approach is efficient (ie, it can be completed in\3 min) and psychometrically robust. The results
provide evidence that some individuals have the ability to visually estimate ACL injury risk factors more accurately than other
instrument-based ACL risk estimation methods (ie, ACL nomogram). The ACL-IQ provides the foundation for assessing the efficacy
of observational ACL injury risk factor assessment (ie, does simple skilled visual inspection reduce ACL injuries?). It also
provides a representative task environment that can be used to increase our understanding of the perceptual-cognitive mechanisms
underlying observational movement analysis and to improve injury risk assessment performance
A hybrid actuator disc - full rotor CFD methodology for modelling the effects of wind turbine wake interactions on performance
The performance of individual wind turbines is crucial for maximum energy yield, however, their performance is often reduced when turbines are placed together in an array. The wake produced by the rotors interacts with downstream turbines, resulting in a reduction in power output. In this paper, we demonstrate a new and faster modelling technique which combines actuator disc theory, modelled using wind tunnel validated Computational Fluid Dynamics (CFD), and integrated into full rotor CFD simulations. This novel hybrid of techniques results in the ability to analyse performance when simulating various array layouts more rapidly and accurately than using either method on its own. It is shown that there is a significant power reduction from a downstream turbine that is subjected to the wake of an upstream turbine, and that this is due to both a reduction in power in the wind and also due to changes in the aerodynamics. Analysis of static pressure along the blade showed that as a result of wake interactions, a large reduction in the suction peak along the leading edge reduced the lift generated by the rotor and so reduced the torque production and the ability for the blade to extract energy from the wind
Analysis of control-oriented wake modeling tools using lidar field results
The objective of this paper is to compare field data from a
scanning lidar mounted on a turbine to control-oriented wind turbine wake
models. The measurements were taken from the turbine nacelle looking
downstream at the turbine wake. This field campaign was used to validate
control-oriented tools used for wind plant control and optimization. The
National Wind Technology Center in Golden, CO, conducted a demonstration of
wake steering on a utility-scale turbine. In this campaign, the turbine was
operated at various yaw misalignment set points, while a lidar mounted on the
nacelle scanned five downstream distances. Primarily, this paper examines
measurements taken at 2.35 diameters downstream of the turbine. The lidar
measurements were combined with turbine data and measurements of the
inflow made by a highly instrumented meteorological mast on-site. This paper
presents a quantitative analysis of the lidar data compared to the
control-oriented wake models used under different atmospheric conditions and
turbine operation. These results show that good agreement is obtained between the
lidar data and the models under these different conditions.</p
North American extreme precipitation events and related large-scale meteorological patterns: a review of statistical methods, dynamics, modeling, and trends
This paper surveys the current state of knowledge regarding large-scale meteorological patterns (LSMPs) associated with short-duration (less than 1 week) extreme precipitation events over North America. In contrast to teleconnections, which are typically defined based on the characteristic spatial variations of a meteorological field or on the remote circulation response to a known forcing, LSMPs are defined relative to the occurrence of a specific phenomenon-here, extreme precipitation-and with an emphasis on the synoptic scales that have a primary influence in individual events, have medium-range weather predictability, and are well-resolved in both weather and climate models. For the LSMP relationship with extreme precipitation, we consider the previous literature with respect to definitions and data, dynamical mechanisms, model representation, and climate change trends. There is considerable uncertainty in identifying extremes based on existing observational precipitation data and some limitations in analyzing the associated LSMPs in reanalysis data. Many different definitions of "extreme" are in use, making it difficult to directly compare different studies. Dynamically, several types of meteorological systems-extratropical cyclones, tropical cyclones, mesoscale convective systems, and mesohighs-and several mechanisms-fronts, atmospheric rivers, and orographic ascent-have been shown to be important aspects of extreme precipitation LSMPs. The extreme precipitation is often realized through mesoscale processes organized, enhanced, or triggered by the LSMP. Understanding of model representation, trends, and projections for LSMPs is at an early stage, although some promising analysis techniques have been identified and the LSMP perspective is useful for evaluating the model dynamics associated with extremes.11Ysciescopu
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