Academic literature on the topic 'Root-mean-square fluctuation'

The detailed unsteady turbulent flow inside a centrifugal fan and its downstream pipe was studied using detached eddy simulation (DES) at three flowrates, namely, the best efficiency point (BEP), 0.75BEP, and 1.49BEP. Both the mean and fluctuating flow fields were analyzed on the basis of the root-mean-square value as the indication of fluctuating intensity. Results showed that the pressure fluctuation had the minimum value at BEP, but the velocity fluctuation increased with the flowrate. Most regions inside the centrifugal fan underwent large pressure fluctuation with the magnitude of about 10~20% of pref = 0.5 ρu22, where u2 is the blade velocity at the impeller outlet. The pressure fluctuation had a maximum value at the impeller side of the tongue tip rather than the stagnation point, and it decreased rapidly along the outlet pipe with magnitude about 1% of pref after distance of five pipe diameters. The spectra of hydrodynamic pressure showed conspicuous spikes at the blade passing frequency (BPF) in the volute but not in the downstream pipe. At the downstream pipe entrance, pressure fluctuation spectra agreed with experimental results, showing that hydrodynamic pressure fluctuations were dominant; however, the experimental data showed a much slower decreasing rate due to the acoustic fluctuations.

Velocity fluctuations in a mixing T-junction were simulated in FLUENT using large-eddy simulation (LES) turbulent flow model with sub-grid scale (SGS) Smagorinsky–Lilly (SL) model. The normalized mean and root mean square velocities are used to describe the time-averaged velocities and the velocities fluctuation intensities. Comparison of the numerical results with experimental data shows that the LES model is valid for predicting the flow of mixing in a T-junction junction. The numerical results reveal the velocity distributions and fluctuations are basically symmetrical and the fluctuation at the upstream of the downstream of the main duct is stronger than that at the downstream of the downstream of the main duct.

Statistical properties of pressure fluctuations on the surface of a hemisphere immersed in a thick turbulent boundary layer are described. The height of the hemisphere tested was 0.275 thicknesses of the boundary layer. Reynolds number based on the model diameter D and the time-mean approaching flow velocity at the level of the top Ur was 3.0 × 105. Time-mean and root-mean-square (rms) values, probability density and power spectra of the pressure fluctuations are presented and discussed. The pressure fluctuations are related to the fluctuating approaching-flow velocity in terms of the pressure-velocity admittance and the cross correlation. Main results are that the time-mean and rms pressures attained a primary maximum at the front stagnation point; that the pressure-velocity admittance near the front stagnation point was approximately unity at frequencies less than about 0.4 Ur/D; that the pressure fluctuation in front of the hemisphere is positively correlated with that in the rear side and negatively correlated with that in the middle.

A Brownian harmonic oscillator, which dissipates energy either by friction or via emission of electromagnetic radiation, is considered. This Brownian emitter is driven by the surrounding thermo-quantum fluctuations, which are theoretically described by the fluctuation–dissipation theorem. It is shown how the Abraham–Lorentz force leads to dependence of the half-width on the peak frequency of the oscillator amplitude spectral density. It is found that for the case of a charged particle moving in vacuum at zero temperature, its root-mean-square velocity fluctuation is a universal constant, equal to roughly 1/18 of the speed of light. The relevant Fokker–Planck and Smoluchowski equations are also derived.

The fluctuation of groundwater causes a change in the groundwater environment and then affects the migration and transformation of pollutants. To study the influence of water level fluctuations on nitrogen migration and transformation, physical experiments on the nitrogen migration and transformation process in the groundwater level fluctuation zone were carried out. A numerical model of nitrogen migration in the Vadose zone and the saturated zone was constructed by using the software HydrUS-1D. The correlation coefficient and the root mean square error of the model show that the model fits well. The numerical model is used to predict nitrogen migration and transformation in different water level fluctuation scenarios. The results show that, compared with the fluctuating physical experiment scenario, when the fluctuation range of the water level increases by 5 cm, the fluctuation range of the nitrogen concentration in the coarse sand, medium sand and fine sand media increases by 37.52%, 31.40% and 21.14%, respectively. Additionally, when the fluctuation range of the water level decreases by 5 cm, the fluctuation range of the nitrogen concentration in the coarse sand, medium sand and fine sand media decreases by 36.74%, 14.70% and 9.39%, respectively. The fluctuation of nitrogen concentration varies most significantly with the amplitude of water level fluctuations in coarse sand; the change in water level has the most significant impact on the flux of nitrate nitrogen and has little effect on the change in nitrite nitrogen and ammonium nitrogen, and the difference in fine sand is the most obvious, followed by medium sand, and the difference in coarse sand is not great.

The electromagnetic field commutation relations are defined in terms of geometric factors that are double averages over two finite four-dimensional space-time regions. The square root of any of the uncertainty relations derived from the aforementioned commutators is taken as a critical field, in the sense that any electromagnetic field much larger than it can be treated as classical. Another critical electromagnetic field associated with the quantum information control of vacuum fluctuations can be chosen as the square root of the mean quadratic fluctuation of each quantity of electromagnetic field, when the number of photons is defined and is equal to zero. Any electromagnetic field expectation value could be measured if it is much greater than the last critical field. This article covers a magnitude order comparison between the critical fields and its consequences for measuring the electromagnetic field information.