Turbulence Intensity Coefficient Research Articles

Sensitivity of the Hawt noise level predicted based on Amiet’s theory on the value of a turbulence intensity coefficient determined numerically

In the paper the authors presented and compared two methods of the HAWT noise predicting. The priority, however, was to test the possibility of using Amiet's theory to determine the noise value in the far field. In this theory it is necessary to know the value of the turbulence intensity coefficient. The value of this coefficient was determined based on numerical modeling. The NACA 0012 profile was used for the airfoil shape. The ANSYS/Fluent program was used for numerical calculations, where the k-ω SST turbulence model was used to simulate the flow, and Ffocs- Williams and Hawkings model was used to determine the noise level. The turbulence intensity coefficient estimated in this way was then used to determine the noise value from the wind turbine airfoils using Amiet's theory.

Core impact force of vertical water jets on smooth and rough surfaces

A normal way to dissipate energy of the dam released high velocity jets is to allow them to free-fall in to a plunge pool or impact a plane surface in case of dam site limitations. The water jets have an undisturbed core from nozzle outlet to a certain falling height, which has more impact force and less turbulent intensity than the developed part of the free jet. Experiments are conducted to determine core impact pressure coefficient of a vertical jet on smooth and rough plane surfaces. The experiment results for different jet diameters and falling heights showed considerable increase of the mean dynamic pressure coefficient with increase of the jet Froude number for both smooth surface and rough surface. A simple Froude based mathematical model is correlated for estimation of jet core impact force on the smooth and rough plane surfaces. In addition, a considerable increase of the jet core length was indicated with increase of the jet Froude number. Results also showed a strong correlation between turbulence intensity coefficient and the jet core length.

Numerical prediction of 3-D periodic flow unsteadiness in a centrifugal pump under part-load condition

Numerical simulation and 3-D periodic flow unsteadiness analysis for a centrifugal pump with volute are carried out in whole flow passage, including the impeller with twisted blades, the volute and the side chamber channels under a part-load condition. The pressure fluctuation intensity coefficient (PFIC) based on the standard deviation method, the time-averaged velocity unsteadi- ness intensity coefficient (VUIC) and the time-averaged turbulence intensity coefficient (TIC) are defined by averaging the results at each grid node for an entire impeller revolution period. Therefore, the strength distributions of the periodic flow unsteadiness based on the unsteady Reynolds-averaged Navier-Stokes (URANS) equations can be analyzed directly and in detail. It is shown that under the 0.6Qdes. condition, the pressure fluctuation intensity is larger near the blade pressure side than near the suction side, and a high fluctuation intensity can be observed at the beginning section of the spiral of the volute. The flow velocity unsteadiness intensity is larger near the blade suction side than near the pressure side. A strong turbulence intensity can be found near the blade suction side, the impeller shroud side as well as in the side chamber. The leakage flow has a significant effect on the inflow of the impeller, and can increase both the flow velocity unsteadiness intensity and the turbulence intensity near the wall. The accumulative flow unstea- diness results of an impeller revolution can be an important aspect to be considered in the centrifugal pump optimum design for ob- taining a more stable inner flow of the pump and reducing the flow-induced vibration and noise in certain components.

Impacts of underwater turbulence on acoustical and optical signals and their linkage

Acoustical and optical signal transmission underwater is of vital interest for both civilian and military applications. The range and signal to noise during the transmission, as a function of system and water optical properties, in terms of absorption and scattering, determines the effectiveness of deployed electro-optical (EO) technology. The impacts from turbulence have been demonstrated to affect system performance comparable to those from particles by recent studies. This paper examines the impacts from underwater turbulence on both acoustic scattering and EO imaging degradation, and establishes a framework that can be used to correlate these. It is hypothesized here that underwater turbulence would influence the acoustic scattering cross section and the optical turbulence intensity coefficient in a similar manner. Data from a recent field campaign, Skaneateles Optical Turbulence Exercise (SOTEX, July, 2010) is used to examine the above relationship. Results presented here show strong correlation between the acoustic scattering cross-sections and the intensity coefficient related to the modulation transfer function of an EO imaging system. This significant finding will pave ways to utilize long range acoustical returns to predict EO system performance.

Study on the calibration coefficients of a quasi-dimensional model for HCNG engine

A quasi-dimensional model has been developed for an SI engine fuelled with natural gas/hydrogen blends, the combustion chamber was divided into two zones by the flame front, and a turbulent entrainment combustion model was conducted. This paper investigates the effects of calibration coefficients on the model, which includes the turbulence intensity coefficient C2, the Taylor length scale coefficient C3, and the Ignition lag coefficient Cig. Validation by experiments is carried out under various operating conditions including different ignition timing, excess air ratio, manifold ambient pressure (MAP) and fraction of hydrogen enrichment. The results show that Cig always stay the same at 1.52. When the fuel is pure natural gas, C3 plays an important role in the simulation which changes from 0.95 to 2. The main factor changes from C3 to C2 when the hydrogen fraction increases from 30% to 55%. When the engine is fuelled by pure hydrogen C2 to changes from 1.65 to 2.1.