A Novel Turbulent Inflow Data Generation Method and its Application to the Simulation of Primary Breakup

2019 ◽  
pp. 229-235
Author(s):  
S. Ketterl ◽  
M. Klein
Keyword(s):  
Data Generation ◽  
Turbulent Inflow ◽  
Primary Breakup

Selection of a leading edge noise prediction method for PNoise

2018 ◽  
pp. 214-223
Author(s):  
AM Faria ◽  
MM Pimenta ◽  
JY Saab Jr. ◽  
S Rodriguez
Keyword(s):  
Wind Turbine ◽  
Turbine Blades ◽  
Prediction Method ◽  
Leading Edge ◽  
Wind Farms ◽  
Broadband Noise ◽  
Turbulence Energy ◽  
Noise Prediction ◽  
Migration Routes ◽  
Turbulent Inflow

Wind energy expansion is worldwide followed by various limitations, i.e. land availability, the NIMBY (not in my backyard) attitude, interference on birds migration routes and so on. This undeniable expansion is pushing wind farms near populated areas throughout the years, where noise regulation is more stringent. That demands solutions for the wind turbine (WT) industry, in order to produce quieter WT units. Focusing in the subject of airfoil noise prediction, it can help the assessment and design of quieter wind turbine blades. Considering the airfoil noise as a composition of many sound sources, and in light of the fact that the main noise production mechanisms are the airfoil self-noise and the turbulent inflow (TI) noise, this work is concentrated on the latter. TI noise is classified as an interaction noise, produced by the turbulent inflow, incident on the airfoil leading edge (LE). Theoretical and semi-empirical methods for the TI noise prediction are already available, based on Amiet’s broadband noise theory. Analysis of many TI noise prediction methods is provided by this work in the literature review, as well as the turbulence energy spectrum modeling. This is then followed by comparison of the most reliable TI noise methodologies, qualitatively and quantitatively, with the error estimation, compared to the Ffowcs Williams-Hawkings solution for computational aeroacoustics. Basis for integration of airfoil inflow noise prediction into a wind turbine noise prediction code is the final goal of this work.

EMBEDDED DNS CONCEPT FOR SIMULATING THE PRIMARY BREAKUP OF AN AIRBLAST ATOMIZER

2016 ◽  
Vol 26 (3) ◽  
pp. 187-215 ◽  
Author(s):  
Benjamin Sauer ◽  
Amsini Sadiki ◽  
Johannes Janicka
Keyword(s):  
Primary Breakup

PRIMARY BREAKUP OF ROUND AERATED-LIQUID JETS IN SUPERSONIC CROSSFLOWS

2006 ◽  
Vol 16 (6) ◽  
pp. 657-672 ◽  
Author(s):  
K. A. Sallam ◽  
C. Aalburg ◽  
G. M. Faeth ◽  
K.-C. Lin ◽  
C. D. Carter ◽  
...  
Keyword(s):  
Liquid Jets ◽  
Primary Breakup

Application of modified differential evolution in test data generation

2009 ◽  
Vol 29 (6) ◽  
pp. 1722-1724
Author(s):  
Xiao-cheng HUANG ◽  
Xi-wu WANG ◽  
Dong-sheng CHANG ◽  
Gang HE
Keyword(s):  
Differential Evolution ◽  
Test Data ◽  
Test Data Generation ◽  
Data Generation

GAN-Based Data Generation for Speech Emotion Recognition

2020 ◽  
Author(s):  
Sefik Emre Eskimez ◽  
Dimitrios Dimitriadis ◽  
Robert Gmyr ◽  
Kenichi Kumanati
Keyword(s):  
Emotion Recognition ◽  
Speech Emotion Recognition ◽  
Data Generation

Fluoride Accumulation in Groundwater from Semi-arid Part of Deccan Volcanic Province, India: A Cause of Urolithiasis Outbreak

2017 ◽  
Vol 1 (1) ◽  
pp. 9-17 ◽  
Author(s):  
Sanjay Kale ◽  
N. J. Pawar
Keyword(s):  
Medical Records ◽  
Fluoride Concentration ◽  
Data Generation ◽  
Deccan Volcanic Province ◽  
Temporal And Spatial Distribution ◽  
Volcanic Province ◽  
Fluoride Accumulation ◽  
Hot Days ◽  
Geochemical Investigation ◽  
Relationship Of

Groundwater fluoride and health problem was meticulously studied for dental and skeleton fluorosis except few studies on urolithiasis. Urolithiasis is multi-factorial disease and excess fluoride consumption is one of the causal factors. In view of this, increase of fluoride in groundwater is reported in semiarid Deccan Volcanic Province (DVP), India. To understand the fluoride and urolithiasis association, present study was carried out in Karha river basin of DVP region. Three stages of data generation were adopted for present study such as procuring of medical records of urolithiasis, previous groundwater chemistry data and geochemical investigation of 50 groundwater samples from representative villages. Further, these variables were used for correlation analysis, temporal and spatial distribution to find out their relationships. Result shows medical records of hospitals indicating the gradual increase in urolithiasis is reported during drought situations. In temporal variation, annual fluoride concentration of groundwater and hot days are positively correlated with annual urolith patients as well as spatial study supports the same. In conclusion, present study highlights the relationship of urolith formation with number of hot days, groundwater electrical conductivity and fluoride. However, detailed biomedical study may lead towards understanding of fluoride- urolithiasis relationship.

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