Description of a Website Resource for Turbulence Modeling Verification and Validation

The activities of the Turbulence Model Benchmarking Working Group - which is a subcommittee of the American Institute of Aeronautics and Astronautics (AIAA) Fluid Dynamics Technical Committee - are described. The group s main purpose is to establish a web-based repository for Reynolds-averaged Navier-Stokes turbulence model documentation, including verification and validation cases. This turbulence modeling resource has been established based on feedback from a survey on what is needed to achieve consistency and repeatability in turbulence model implementation and usage, and to document and disseminate information on new turbulence models or improvements to existing models. The various components of the website are described in detail: description of turbulence models, turbulence model readiness rating system, verification cases, validation cases, validation databases, and turbulence manufactured solutions. An outline of future plans of the working group is also provided

Incorporating basic calibrations in existing machine-learned turbulence modeling

This work aims to incorporate basic calibrations of Reynolds-averaged Navier-Stokes (RANS) models as part of machine learning (ML) frameworks. The ML frameworks considered are tensor-basis neural network (TBNN), physics-informed machine learning (PIML), and field inversion & machine learning (FIML) in J. Fluid Mech., 2016, 807, 155-166, Phys. Rev. Fluids, 2017, 2(3), 034603 and J. Comp. Phys., 2016, 305, 758-774, and the baseline RANS models are the one-equation Spalart-Allmaras model, the two-equation $k$-$\omega$ model, and the seven-equation Reynolds stress transport models. ML frameworks are trained against plane channel flow and shear-layer flow data. We compare the ML frameworks and study whether the machine-learned augmentations are detrimental outside the training set. The findings are summarized as follows. The augmentations due to TBNN are detrimental. PIML leads to augmentations that are beneficial inside the training dataset but detrimental outside it. These results are not affected by the baseline RANS model. FIML's augmentations to the two eddy viscosity models, where an inner-layer treatment already exists, are largely neutral. Its augmentation to the seven-equation model, where an inner-layer treatment does not exist, improves the mean flow prediction in a channel. Furthermore, these FIML augmentations are mostly non-detrimental outside the training dataset. In addition to reporting these results, the paper offers physical explanations of the results. Last, we note that the conclusions drawn here are confined to the ML frameworks and the flows considered in this study. More detailed comparative studies and validation & verification studies are needed to account for developments in recent years

Loma Linda University Dentistry - Volume 25, Number 2

Contents: 8-10 | New Positions Filled: Burdick, Li, Sherwin14 | Alumni Student Convention Class of \u276418 | Factors Affecting Pulp Regeneration30 | Student Research Winners34 | Commencement 2014: You Make Us Look Good 46 | Omni Dean49 | Marathon Manhttps://scholarsrepository.llu.edu/articulator/1007/thumbnail.jp

Surface-enhanced Raman spectral biomarkers correlate with Ankle Brachial Index and characterize leg muscle biochemical composition of patients with peripheral arterial disease

Peripheral arterial disease (PAD) is characterized by atherosclerotic blockages of the arteries supplying the lower extremities, which cause a progressive accumulation of ischemic injury to the skeletal muscles of the lower limbs. This injury includes altered metabolic processes, damaged organelles, and compromised bioenergetics in the affected muscles. The objective of this study was to explore the association of Raman spectral signatures of muscle biochemistry with the severity of atherosclerosis in the legs as determined by the Ankle Brachial Index (ABI) and clinical presentation. We collected muscle biopsies from the gastrocnemius (calf muscle) of five patients with clinically diagnosed claudication, five patients with clinically diagnosed critical limb ischemia (CLI), and five control patients who did not have PAD. A partial least squares regression (PLSR) model was able to predict patient ABI with a correlation coefficient of 0.99 during training and a correlation coefficient of 0.85 using a full cross-validation. When using the first three PLS factor scores in combination with linear discriminant analysis, the discriminant model was able to correctly classify the control, claudicating, and CLI patients with 100% accuracy, using a full cross-validation procedure. Raman spectroscopy is capable of detecting and measuring unique biochemical signatures of skeletal muscle. These signatures can discriminate control muscles from PAD muscles and correlate with the ABI and clinical presentation of the PAD patient. Raman spectroscopy provides novel spectral biomarkers that may complement existing methods for diagnosis and monitoring treatment of PAD patients

Surface-enhanced Raman spectral biomarkers correlate with Ankle Brachial Index and characterize leg muscle biochemical composition of patients with peripheral arterial disease

Peripheral arterial disease (PAD) is characterized by atherosclerotic blockages of the arteries supplying the lower extremities, which cause a progressive accumulation of ischemic injury to the skeletal muscles of the lower limbs. This injury includes altered metabolic processes, damaged organelles, and compromised bioenergetics in the affected muscles. The objective of this study was to explore the association of Raman spectral signatures of muscle biochemistry with the severity of atherosclerosis in the legs as determined by the Ankle Brachial Index (ABI) and clinical presentation. We collected muscle biopsies from the gastrocnemius (calf muscle) of five patients with clinically diagnosed claudication, five patients with clinically diagnosed critical limb ischemia (CLI), and five control patients who did not have PAD. A partial least squares regression (PLSR) model was able to predict patient ABI with a correlation coefficient of 0.99 during training and a correlation coefficient of 0.85 using a full cross-validation. When using the first three PLS factor scores in combination with linear discriminant analysis, the discriminant model was able to correctly classify the control, claudicating, and CLI patients with 100% accuracy, using a full cross-validation procedure. Raman spectroscopy is capable of detecting and measuring unique biochemical signatures of skeletal muscle. These signatures can discriminate control muscles from PAD muscles and correlate with the ABI and clinical presentation of the PAD patient. Raman spectroscopy provides novel spectral biomarkers that may complement existing methods for diagnosis and monitoring treatment of PAD patients

Separation between coherent and turbulent fluctuations. What can we learn from the Empirical Mode Decomposition?

The performances of a new data processing technique, namely the Empirical Mode Decomposition, are evaluated on a fully developed turbulent velocity signal perturbed by a numerical forcing which mimics a long-period flapping. First, we introduce a "resemblance" criterion to discriminate between the polluted and the unpolluted modes extracted from the perturbed velocity signal by means of the Empirical Mode Decomposition algorithm. A rejection procedure, playing, somehow, the role of a high-pass filter, is then designed in order to infer the original velocity signal from the perturbed one. The quality of this recovering procedure is extensively evaluated in the case of a "mono-component" perturbation (sine wave) by varying both the amplitude and the frequency of the perturbation. An excellent agreement between the recovered and the reference velocity signals is found, even though some discrepancies are observed when the perturbation frequency overlaps the frequency range corresponding to the energy-containing eddies as emphasized by both the energy spectrum and the structure functions. Finally, our recovering procedure is successfully performed on a time-dependent perturbation (linear chirp) covering a broad range of frequencies.Comment: 23 pages, 13 figures, submitted to Experiments in Fluid

An empirical test for cellular automaton models of traffic flow

Based on a detailed microscopic test scenario motivated by recent empirical studies of single-vehicle data, several cellular automaton models for traffic flow are compared. We find three levels of agreement with the empirical data: 1) models that do not reproduce even qualitatively the most important empirical observations, 2) models that are on a macroscopic level in reasonable agreement with the empirics, and 3) models that reproduce the empirical data on a microscopic level as well. Our results are not only relevant for applications, but also shed new light on the relevant interactions in traffic flow.Comment: 28 pages, 36 figures, accepted for publication in PR

Testing Inflation with Large Scale Structure: Connecting Hopes with Reality

The statistics of primordial curvature fluctuations are our window into the period of inflation, where these fluctuations were generated. To date, the cosmic microwave background has been the dominant source of information about these perturbations. Large scale structure is however from where drastic improvements should originate. In this paper, we explain the theoretical motivations for pursuing such measurements and the challenges that lie ahead. In particular, we discuss and identify theoretical targets regarding the measurement of primordial non-Gaussianity. We argue that when quantified in terms of the local (equilateral) template amplitude $f_{\rm NL}^{\rm loc}$ ($f_{\rm NL}^{\rm eq}$), natural target levels of sensitivity are $\Delta f_{\rm NL}^{\rm loc, eq.} \simeq 1$. We highlight that such levels are within reach of future surveys by measuring 2-, 3- and 4-point statistics of the galaxy spatial distribution. This paper summarizes a workshop held at CITA (University of Toronto) on October 23-24, 2014.Comment: 27 pages + reference

Ultrathin Oxide Films by Atomic Layer Deposition on Graphene

In this paper, a method is presented to create and characterize mechanically robust, free standing, ultrathin, oxide films with controlled, nanometer-scale thickness using Atomic Layer Deposition (ALD) on graphene. Aluminum oxide films were deposited onto suspended graphene membranes using ALD. Subsequent etching of the graphene left pure aluminum oxide films only a few atoms in thickness. A pressurized blister test was used to determine that these ultrathin films have a Young's modulus of 154 \pm 13 GPa. This Young's modulus is comparable to much thicker alumina ALD films. This behavior indicates that these ultrathin two-dimensional films have excellent mechanical integrity. The films are also impermeable to standard gases suggesting they are pinhole-free. These continuous ultrathin films are expected to enable new applications in fields such as thin film coatings, membranes and flexible electronics.Comment: Nano Letters (just accepted

Search for Exotic Strange Quark Matter in High Energy Nuclear Reactions

We report on a search for metastable positively and negatively charged states of strange quark matter in Au+Pb reactions at 11.6 A GeV/c in experiment E864. We have sampled approximately six billion 10% most central Au+Pb interactions and have observed no strangelet states (baryon number A < 100 droplets of strange quark matter). We thus set upper limits on the production of these exotic states at the level of 1-6 x 10^{-8} per central collision. These limits are the best and most model independent for this colliding system. We discuss the implications of our results on strangelet production mechanisms, and also on the stability question of strange quark matter.Comment: 21 pages, 9 figures, to be published in Nuclear Physics A (Carl Dover memorial edition