scholarly journals An Experimental Data Base for the Computational Fluid Dynamics of Reacting and Nonreacting Methanol Sprays

1995 ◽  
Vol 117 (1) ◽  
pp. 145-153 ◽  
Author(s):  
V. G. McDonell ◽  
G. S. Samuelsen
Keyword(s):  
Data Base ◽  
Gas Phase ◽  
Vapor Concentration ◽  
Data Sets ◽  
Size Distributions ◽  
Two Phase ◽  
Data Set ◽  
Phase Velocities ◽  
Spray Structure ◽  
Droplet Size Distributions

The present data set consists of detailed measurements obtained within methanol sprays produced by a research atomizer which is operated with three atomizing air modes: none, non-swirling, and swirling. In addition, the cases with nonswirling and swirling atomizing air are characterized under reacting conditions. In each case, state-of-the-art diagnostics are applied. Measurements of the gas phase velocities in both the single and two-phase cases, droplet size distributions, and vapor concentration are obtained. The data are reported in a standardized format to ensure usefulness as modeling challenges. The results obtained reveal the presence of significant interaction between phases and significant changes in spray structure as a result of altering the atomizing air characteristics. Efforts have been directed toward delineation of errors and comparison with existing data sets where possible. The results is a comprehensive data base for vaporizing sprays under reacting and non-reacting conditions which permit a systematic variation in aerodynamic effects to be explored.

Flow Resistance of Surface Micromachined Microfluidic Channels

2004 ◽  
Author(s):  
Paul Galambos
Keyword(s):  
Poiseuille Flow ◽  
Flow Resistance ◽  
Narrow Channel ◽  
Wall Friction ◽  
Microfluidic Channels ◽  
Data Sets ◽  
Two Phase ◽  
Data Set ◽  
Flow Phenomena ◽  
Predicted Values

In this paper measured pressure vs. flow and flow resistance are compared with theoretical predictions (Poiseuille flow) for surface micromachined microfluidic channels with thin-film deformable covers. Three sets of data are compared. In data set 3 the channel width is narrow, channel deflections are relatively small, and there is very little deviation from the theoretical flow resistance prediction. In data sets 1 and 2 there is significant deviation from Poiseuille flow predictions—with flow resistances as little as 1/2 the predicted values that decrease with increasing pressure. Two hypotheses to explain this discrepancy are discussed: (1) channel cover deflection leading to deeper, lower resistance flow channels, and (2) an observed two-phase, air/water, flow phenomena leading to reduced effective wall friction in the channel.

PEP725 a European phenological database

2021 ◽  
Author(s):  
Hans Ressl ◽  
Helfried Scheifinger ◽  
Thomas Hübner ◽  
Anita Paul ◽  
Markus Ungersböck
Keyword(s):  
Data Base ◽  
Science Research ◽  
Data Access ◽  
Data Sets ◽  
Ministry Of Education ◽  
Data Set ◽  
Phenological Data ◽  
Data Policy ◽  
Research And Education ◽  
Education Science

<p>“Phenology – the timing of seasonal activities of animals and plants – is perhaps the simplest process in which to track changes in the ecology of species in response to climate change” (IPCC 2007).</p><p>PEP725, the Pan-European Phenological Database, is a European research infrastructure to promote and facilitate phenological research. Its main objective is to build up and maintain a European-wide phenological database with an open, unrestricted data access for science, research and education. So far, 20 European meteorological services and 6 partners from different phenological network operators have joined PEP725.</p><p>The PEP725 phenological data base (www.pep725.eu) now offers more than 12 million phenological observations, all of them classified according to the so called BBCH scale. The first datasets in PEP725 date back to 1868; however, there are only a few observations available until 1950. Having accepted the PEP725 data policy and finished the registration, the data download is quick and easy and can be done according to various criteria, e.g., by a specific plant or all data from one country. The integration of new data sets for future partners is also easy to perform due to the flexible structure of the PEP725 database as well as the classification of the observed plants via the so-called gss format (genus, species and subspecies).</p><p>PEP725 is funded by EUMETNET, the network of European meteorological services, ZAMG, who is the acting host for PEP, and the Austrian ministry of education, science and research.</p><p>The phenological data set has been growing by about 100000 observations per year. Also the number of user registrations has continually been increasing, amounting to 305 new users and more than 28000 downloads in 2020. The greatest number of users are found in China, followed by Germany and the US. To date we could count 78 reviewed publications based on the PEP725 data set with 18 in 2020 and a total of 9 published in Nature and one in Science.</p><p>The data base statistics demonstrate the great demand and potential of the PEP725 phenological data set, which urgently needs development including a facilitated access, gridded versions and near real time products to attract a greater range of users.</p>

UPPER-TRUNCATED POWER LAW DISTRIBUTIONS

Fractals ◽  
2001 ◽  
Vol 09 (02) ◽  
pp. 209-222 ◽  
Author(s):  
STEPHEN M. BURROUGHS ◽  
SARAH F. TEBBENS
Keyword(s):  
Power Law ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Generalized Function ◽  
Data Sets ◽  
Scaling Exponent ◽  
Cumulative Number ◽  
Size Distributions ◽  
Data Set ◽  
Binned Data

Power law cumulative number-size distributions are widely used to describe the scaling properties of data sets and to establish scale invariance. We derive the relationships between the scaling exponents of non-cumulative and cumulative number-size distributions for linearly binned and logarithmically binned data. Cumulative number-size distributions for data sets of many natural phenomena exhibit a "fall-off" from a power law at the largest object sizes. Previous work has often either ignored the fall-off region or described this region with a different function. We demonstrate that when a data set is abruptly truncated at large object size, fall-off from a power law is expected for the cumulative distribution. Functions to describe this fall-off are derived for both linearly and logarithmically binned data. These functions lead to a generalized function, the upper-truncated power law, that is independent of binning method. Fitting the upper-truncated power law to a cumulative number-size distribution determines the parameters of the power law, thus providing the scaling exponent of the data. Unlike previous approaches that employ alternate functions to describe the fall-off region, an upper-truncated power law describes the data set, including the fall-off, with a single function.

scholarly journals Modeling the Formation of Urea-Water Sprays from an Air-Assisted Nozzle

2020 ◽  
Vol 10 (16) ◽  
pp. 5723
Author(s):  
Jens Frühhaber ◽  
Christian Lieber ◽  
Dominik Mattes ◽  
Thomas Lauer ◽  
Rainer Koch ◽  
...  
Keyword(s):  
Catalytic Reduction ◽  
Turbulent Dispersion ◽  
Size Distributions ◽  
Two Phase ◽  
Validation Data ◽  
Spray Formation ◽  
Fine Spray ◽  
Computational Fluid Dynamics Cfd ◽  
Breakup Model ◽  
Droplet Size Distributions

Ammonia preparation from urea-water solutions is a key feature to ensure an effective reduction of nitrogen oxides in selective catalytic reduction (SCR) systems. Thereby, air-assisted nozzles provide fine sprays, which enhance ammonia homogenization. In the present study, a methodology was developed to model the spray formation by means of computational fluid dynamics (CFD) for this type of atomizer. Experimental validation data was generated in an optically accessible hot gas test bench using a shadowgraphy setup providing droplet velocities and size distributions at designated positions inside the duct. An adaption of the turbulence model was performed in order to correct the dispersion of the turbulent gas jet. The spray modeling in the near nozzle region is based on an experimentally determined droplet spectrum in combination with the WAVE breakup model. This methodology was applied due to the fact that the emerging two-phase flow will immediately disintegrate into a fine spray downstream the nozzle exit, which is also known from cavitating diesel nozzles. The suitability of this approach was validated against the radial velocity and droplet size distributions at the first measurement position downstream the nozzle. In addition, the simulation results serve as a basis for the investigation of turbulent dispersion phenomena and evaporation inside the spray.

Towards the Understanding of Transformation of Annular to Droplet-Annular Gas-Liquid Flow

2016 ◽  
Author(s):  
Parmod Kumar ◽  
Sushanta K. Mitra ◽  
Arup Kumar Das
Keyword(s):  
Liquid Film ◽  
Gas Phase ◽  
Gaseous Phase ◽  
Annular Flow ◽  
Clear Understanding ◽  
Gravitational Acceleration ◽  
Liquid Droplets ◽  
Two Phase ◽  
Phase Velocities ◽  
Gas Liquid Flow

Annular flow and its deviations due to change of phase velocities in parallel and counter flows are very common in many adiabatic and non-adiabatic applications of two phase flow. The transformation from annular flow to its counterpart droplet-annular flow is often poorly understood as it needs to handle multi scale interfaces experimentally or numerically. In the present work, attempts have been made to capture both wavy annular interface and dynamics of tiny droplets throughout its life cycle using grid based volume of fluid framework. 3-D simulation domain with length (L)/diameter (D) ratio as 6 is considered under the effect of gravitational acceleration and phase inertial field. Wavy interface is observed numerically between the phases using phase fraction contours along with the occurrence of three very interesting phenomena, which include rolling, undercutting and orificing. At low liquid and gas velocities orificing has been observed which restricts the path of gaseous phase. Departure from the orificing phenomenon has been seen at higher gas phase velocities which transforms to other phenomenon called rolling. Rolling is the folding of liquid film by the high velocity gaseous phase towards the radially outward direction. Further, increase in liquid phase velocities above gaseous phase velocities results in undercutting of liquid film by the gas phase. Moreover the liquid droplets can be seen in the entire phenomenon through the gas phase in the core of the tube. We presented a regime map of gas liquid velocities to segregate clear understanding of annular to droplet-annular flow due to orificing, rolling and undercutting. The present study will enrich the knowledge of multiphase flow transportation in process plants, chemical reactors, nuclear reactors and refineries where gas-liquid annular flow is most widely used flow pattern.

Detailed Characterisation of a Swirled Air/Kerosene Spray in Reactive and Non-Reactive Conditions Downstream From an Actual Turbojet Injection System

2011 ◽  
Author(s):  
Renaud Lecourt ◽  
Guillaume Linassier ◽  
Ge´rard Lavergne
Keyword(s):  
Data Base ◽  
Gas Phase ◽  
Two Phase Flow ◽  
Flame Structure ◽  
Original Method ◽  
Injection System ◽  
Spray Combustion ◽  
Phase Flow ◽  
Two Phase ◽  
Axial Velocity Component

As part of the investigations of the ignition of jet-engines under altitude conditions, a detailed data base was built with the results of experiments on the two-phase flow produced by an actual swirl air/kerosene turbojet injection system. The injection system had a fairly simple geometry. It was used with liquid kerosene injected through a pressure-swirl fuel atomiser. In this case the measurements were carried out at atmospheric pressure in a windowed combustion chamber, with air at ambient temperature. The tested equivalence ratio was 0.95 which corresponds to an air mass flow rate of 0.035 kg/s. For this operating point, we obtained the velocity field of the gas phase under non-reactive conditions by LDA. The axial velocity component of the gas phase was also measured in the burning spray using an original method with a phase Doppler device. The data recorded with the PDA were also processed to obtain the kerosene droplet sizes and velocities under reactive conditions. The same phase Doppler device was used in non-reactive conditions to measure the size and velocity distributions of the kerosene droplets in a section close to the injection system exit in order to complete the data base with the boundary conditions for the liquid phase. In addition the flame was visualised qualitatively. The picture of the stabilized flame was processed with an Abel transform to compare the LDA/PDA measurements with the flame structure, obtained under the reactive conditions. Finally, unsteady pressure measurements were taken under non-reactive conditions and the LDA measurements processed, close to the injection system exit, to get the PVC (Precessing Vortex Core) frequency. The data were analysed to determine the influence of the spray combustion on the two-phase flow. The geometry of the whole experimental setup and the data base are available to other researchers for testing and validating spray combustion models and unsteady two-phase flow numerical simulations.

Decision Tree Regressions Estimate Liquid Holdup in Two-Phase Gas/Liquid Flows

2021 ◽  
Vol 73 (11) ◽  
pp. 75-76
Author(s):  
Chris Carpenter
Keyword(s):  
Machine Learning ◽  
Decision Tree ◽  
Multiphase Flows ◽  
Data Sets ◽  
Liquid Holdup ◽  
Two Phase ◽  
Data Set ◽  
Feature Importance ◽  
Data Points ◽  
Liquid Flows

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 203448, “Decision-Tree Regressions for Estimating Liquid Holdup in Two-Phase Gas/Liquid Flows,” by Meshal Almashan, SPE, Yoshiaki Narusue, and Hiroyuki Morikawa, University of Tokyo, prepared for the 2020 Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, held virtually 9–12 November. The paper has not been peer reviewed. In the authors’ study, a machine-learning predictive model—boosted decision tree regression (BDTR)—is trained, tested, and evaluated in predicting liquid holdup (HL) in multiphase flows in oil and gas wells. Results show that the proposed BDTR model outperforms the best empirical correlations and the fuzzy-logic model used in estimating HL in gas/liquid multiphase flows. Using the BDTR model with its interpretable representation, the heuristic feature importance of the input features used in building the model can be determined clearly. Introduction Machine-learning approaches in predicting HL in multiphase flows have been recently studied to improve prediction accuracy compared with existing empirical correlations. However, these approaches ignore the heuristic feature importance of the input parameters to the predicted HL values. The heuristic feature importance can help provide better insight into the issues associated with HL studies, such as the liquid-loading phenomenon. To the best of the authors’ knowledge, the present study is the first work that shows how decision-forest regression predictive models can predict HL accurately. Data Acquisition The performance and the predictive power of a machine-learning model relies greatly on the quality and completeness of the data set used in building the model. The data sets used in training and testing the predictive model are experimental and were collected from the literature (111 data points). Air/kerosene and air/water mixtures were used in obtaining the 111 experimental data points. In this study, this data set is divided into three different subsets: training, validation, and testing. The data sets consist of the properties of HL, the superficial gas velocity (Vsg), the superficial liquid velocity (Vsl), pressure, and temperature (T). The statistical measures of the data sets are shown in Table 1 of the complete paper.

Minimum Data Base Determination using Machine Learning

2016 ◽  
Vol 13 (4) ◽  
pp. 1-18
Author(s):  
Angel Ferrnando Kuri-Morales
Keyword(s):  
Data Base ◽  
Multivariate Regression ◽  
Large Data ◽  
Original Data ◽  
Data Sets ◽  
Data Set ◽  
Combined Application ◽  
Time Required ◽  
High Degree ◽  
Reduced Data

The exploitation of large data bases frequently implies the investment of large and, usually, expensive resources both in terms of the storage and processing time required. It is possible to obtain equivalent reduced data sets where the statistical information of the original data may be preserved while dispensing with redundant constituents. Therefore, the physical embodiment of the relevant features of the data base is more economical. The author proposes a method where we may obtain an optimal transformed representation of the original data which is, in general, considerably more compact than the original without impairing its informational content. To certify the equivalence of the original data set (FD) and the reduced one (RD), the author applies an algorithm which relies in a Genetic Algorithm (GA) and a multivariate regression algorithm (AA). Through the combined application of GA and AA the equivalent behavior of both FD and RD may be guaranteed with a high degree of statistical certainty.

DROPLET SIZE DISTRIBUTIONS OF ADJUVANT-AMENDED SPRAYS FROM AN AIR-ASSISTED FIVE-PORT PWM NOZZLE

2011 ◽  
Vol 21 (3) ◽  
pp. 263-274 ◽  
Author(s):  
Jiabing Gu ◽  
Heping Zhu ◽  
Weimin Ding ◽  
Hong Young Jeon
Keyword(s):  
Droplet Size ◽  
Size Distributions ◽  
Droplet Size Distributions
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