Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Applicability of Taylor's hypothesis in thermally driven turbulence.

ABSTRACT: In this paper, we show that, in the presence of large-scale circulation (LSC), Taylor's hypothesis can be invoked to deduce the energy spectrum in thermal convection using real-space probes, a popular experimental tool. We perform numerical simulation of turbulent convection in a cube and observe that the velocity field follows Kolmogorov's spectrum (k-5/3). We also record the velocity time series using real-space probes near the lateral walls. The corresponding frequency spectrum exhibits Kolmogorov's spectrum (f-5/3), thus validating Taylor's hypothesis with the steady LSC playing the role of a mean velocity field. The aforementioned findings based on real-space probes provide valuable inputs for experimental measurements used for studying the spectrum of convective turbulence.

SUBMITTER: Kumar A

PROVIDER: S-EPMC5936933 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Applicability of Taylor's hypothesis in thermally driven turbulence.

Kumar Abhishek A Verma Mahendra K MK

Royal Society open science 20180418 4

In this paper, we show that, in the presence of large-scale circulation (LSC), Taylor's hypothesis can be invoked to deduce the energy spectrum in thermal convection using real-space probes, a popular experimental tool. We perform numerical simulation of turbulent convection in a cube and observe that the velocity field follows Kolmogorov's spectrum (<i>k</i><sup>-5/3</sup>). We also record the velocity time series using real-space probes near the lateral walls. The corresponding frequency spect ...[more]

PMID: 29765668

Similar Datasets

Turbulence-driven instabilities limit insect flight performance.

Project description:Environmental turbulence is ubiquitous in natural habitats, but its effect on flying animals remains unknown because most flight studies are performed in still air or artificially smooth flow. Here we show that variability in external airflow limits maximum flight speed in wild orchid bees by causing severe instabilities. Bees flying in front of an outdoor, turbulent air jet become increasingly unstable about their roll axis as airspeed and flow variability increase. Bees extend their hindlegs ventrally at higher speeds, improving roll stability but also increasing body drag and associated power requirements by 30%. Despite the energetic cost, we observed this stability-enhancing behavior in 10 euglossine species from 3 different genera, spanning an order of magnitude in body size. A field experiment in which we altered the level of turbulence demonstrates that flight instability and maximum flight speed are directly related to flow variability. The effect of environmental turbulence on flight stability is thus an important and previously unrecognized determinant of flight performance.

| S-EPMC2690035 | biostudies-literature

Reconnection-driven energy cascade in magnetohydrodynamic turbulence.

Project description:Magnetohydrodynamic turbulence regulates the transfer of energy from large to small scales in many astrophysical systems, including the solar atmosphere. We perform three-dimensional magnetohydrodynamic simulations with unprecedentedly large magnetic Reynolds number to reveal how rapid reconnection of magnetic field lines changes the classical paradigm of the turbulent energy cascade. By breaking elongated current sheets into chains of small magnetic flux ropes (or plasmoids), magnetic reconnection leads to a previously undiscovered range of energy cascade, where the rate of energy transfer is controlled by the growth rate of the plasmoids. As a consequence, the turbulent energy spectra steepen and attain a spectral index of -2.2 that is accompanied by changes in the anisotropy of turbulence eddies. The omnipresence of plasmoids and their consequences on, for example, solar coronal heating, can be further explored with current and future spacecraft and telescopes.

| S-EPMC9728964 | biostudies-literature

Purely elastic turbulence in pressure-driven channel flows.

Project description:Solutions of long, flexible polymer molecules are complex fluids that simultaneously exhibit fluid-like and solid-like behavior. When subjected to an external flow, dilute polymer solutions exhibit elastic turbulence-a unique, chaotic flow state absent in Newtonian fluids, like water. Unlike its Newtonian counterpart, elastic turbulence is caused by polymer molecules stretching and aligning in the flow, and can occur at vanishing inertia. While experimental realizations of elastic turbulence are well-documented, there is currently no understanding of its mechanism. Here, we present large-scale direct numerical simulations of elastic turbulence in pressure-driven flows through straight channels. We demonstrate that the transition to elastic turbulence is sub-critical, giving rise to spot-like flow structures that, further away from the transition, eventually spread throughout the domain. We provide evidence that elastic turbulence is organized around unstable coherent states that are localized close to the channel midplane.

| S-EPMC10907231 | biostudies-literature

A curated dataset for data-driven turbulence modelling.

Project description:The recent surge in machine learning augmented turbulence modelling is a promising approach for addressing the limitations of Reynolds-averaged Navier-Stokes (RANS) models. This work presents the development of the first open-source dataset, curated and structured for immediate use in machine learning augmented corrective turbulence closure modelling. The dataset features a variety of RANS simulations with matching direct numerical simulation (DNS) and large-eddy simulation (LES) data. Four turbulence models are selected to form the initial dataset: k-ε, k-ε-ϕt-f, k-ω, and k-ω SST. The dataset consists of 29 cases per turbulence model, for several parametrically sweeping reference DNS/LES cases: periodic hills, square duct, parametric bumps, converging-diverging channel, and a curved backward-facing step. At each of the 895,640 points, various RANS features with DNS/LES labels are available. The feature set includes quantities used in current state-of-the-art models, and additional fields which enable the generation of new feature sets. The dataset reduces effort required to train, test, and benchmark new corrective RANS models. The dataset is available at https://doi.org/10.34740/kaggle/dsv/2637500 .

| S-EPMC8484471 | biostudies-literature

Thermally driven fission of protocells.

Project description:We propose a simple mechanism for the self-replication of protocells. Our main hypothesis is that the amphiphilic molecules composing the membrane bilayer are synthesized inside the protocell through exothermic chemical reactions. The slow increase of the inner temperature forces the hottest molecules to move from the inner leaflet to the outer leaflet of the bilayer. Because of this outward translocation flow, the outer leaflet grows faster than the inner leaflet. This differential growth increases the mean curvature and amplifies any local shrinking of the protocell until it splits in two. The proposed model, based on mere laws of physics, is a step in the study of the origin of life, as well as a clue for a better understanding of cell proliferation in cancer.

| S-EPMC8511175 | biostudies-literature

Explaining the physics of transfer learning in data-driven turbulence modeling.

Project description:Transfer learning (TL), which enables neural networks (NNs) to generalize out-of-distribution via targeted re-training, is becoming a powerful tool in scientific machine learning (ML) applications such as weather/climate prediction and turbulence modeling. Effective TL requires knowing (1) how to re-train NNs? and (2) what physics are learned during TL? Here, we present novel analyses and a framework addressing (1)-(2) for a broad range of multi-scale, nonlinear, dynamical systems. Our approach combines spectral (e.g. Fourier) analyses of such systems with spectral analyses of convolutional NNs, revealing physical connections between the systems and what the NN learns (a combination of low-, high-, band-pass filters and Gabor filters). Integrating these analyses, we introduce a general framework that identifies the best re-training procedure for a given problem based on physics and NN theory. As test case, we explain the physics of TL in subgrid-scale modeling of several setups of 2D turbulence. Furthermore, these analyses show that in these cases, the shallowest convolution layers are the best to re-train, which is consistent with our physics-guided framework but is against the common wisdom guiding TL in the ML literature. Our work provides a new avenue for optimal and explainable TL, and a step toward fully explainable NNs, for wide-ranging applications in science and engineering, such as climate change modeling.

| S-EPMC9991455 | biostudies-literature

Robust rotation of rotor in a thermally driven nanomotor.

Project description:In the fabrication of a thermally driven rotary nanomotor with the dimension of a few nanometers, fabrication and control precision may have great influence on rotor's stability of rotational frequency (SRF). To investigate effects of uncertainty of some major factors including temperature, tube length, axial distance between tubes, diameter of tubes and the inward radial deviation (IRD) of atoms in stators on the frequency's stability, theoretical analysis integrating with numerical experiments are carried out. From the results obtained via molecular dynamics simulation, some key points are illustrated for future fabrication of the thermal driven rotary nanomotor.

| S-EPMC5385497 | biostudies-literature

Chirality-Induced Magnetoresistance Due to Thermally Driven Spin Polarization.

Project description:Chirality-induced current-perpendicular-to-plane magnetoresistance (CPP-MR) originates from current-induced spin polarization in molecules. The current-induced spin polarization is widely recognized as a fundamental principle of chiral-induced spin selectivity (CISS). In this study, we investigate chirality-induced current-in-plane magnetoresistance (CIP-MR) in a chiral molecule/ferromagnetic metal bilayer at room temperature. In contrast to CPP-MR, CIP-MR observed in the present study requires no bias charge current through the molecule. The temperature dependence of CIP-MR suggests that thermally driven spontaneous spin polarization in chiral molecules is the key to the observed MR. The novel MR is consistent with recent CISS-related studies, that is, chiral molecules in contact with a metallic surface possess a finite spin polarization.

| S-EPMC9052755 | biostudies-literature

Are microbiome studies ready for hypothesis-driven research?

Project description:Hypothesis-driven research has led to many scientific advances, but hypotheses cannot be tested in isolation: rather, they require a framework of aggregated scientific knowledge to allow questions to be posed meaningfully. This framework is largely still lacking in microbiome studies, and the only way to create it is by discovery-driven, tool-driven, and standards-driven research projects. Here we illustrate these issues using several such non-hypothesis-driven projects from our own laboratories, including spatial mapping, the American Gut Project, the Earth Microbiome Project (which is an umbrella project integrating many smaller hypothesis-driven projects), and the knowledgebase-driven tools GNPS and Qiita. We argue that an investment of community resources in infrastructure tasks, and in the controls and standards that underpin them, will greatly enhance the investment in hypothesis-driven research programs.

| S-EPMC6153026 | biostudies-literature

Thermally Driven Continuous Rolling of a Thick-Walled Cylindrical Rod.

Project description:Self-sustained motion can take advantage of direct energy extraction from a steady external environment to maintain its own motion, and has potential applications in energy harvesting, robotic motion, and transportation. Recent experiments have found that a thermally responsive rod can perform self-sustained rolling on a flat hot plate with an angular velocity determined by the competition between the thermal driving moment and the friction moment. A rod with a hollow cross section tends to greatly reduce the frictional resistance, while promising improvements in thermal conversion efficiency. In this paper, through deriving the equilibrium equations for steady-state self-sustained rolling of the thick-walled cylindrical rod, estimating the temperature field on the rod cross-section, and solving the analytical solution of the thermally induced driving moment, the dynamic behavior of the thermally driven self-sustained rolling of the thick-walled cylindrical rod is theoretically investigated. In addition, we investigate in detail the effects of radius ratio, heat transfer coefficient, heat flux, contact angle, thermal expansion coefficient, and sliding friction coefficient on the angular velocity of the self-sustained rolling of the thick-walled cylindrical rod to obtain the optimal ratio of internal and external radius. The results are instructive for the application of thick-walled cylindrical rods in the fields of waste heat harvesters and soft robotics.

| S-EPMC9698442 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data