Journal of Flow Visualization and Image Processing
Publication de 4 numéros par an
ISSN Imprimer: 1065-3090
ISSN En ligne: 1940-4336
IF:
0.6
Immediacy Index:
0.6
Eigenfactor:
0.00013
JCI:
0.14
SJR:
0.201
SNIP:
0.313
CiteScore™::
1.2
H-Index:
13
Indexed in
Objectifs et champs d'application
The Journal of Flow Visualization and Image Processing is a quarterly refereed research journal that publishes original papers to disseminate and exchange knowledge and information on the principles and applications of flow visualization techniques and related image processing algorithms.
Flow visualization and quantification have emerged as powerful tools in velocity, pressure, temperature and species concentration measurements, combustion diagnostics, and process monitoring related to physical, biomedical, and engineering sciences. Measurements were initially based on lasers but have expanded to include a wider electromagnetic spectrum. Numerical simulation is a second source of data amenable to image analysis. Direct visualization in the form of high speed, high resolution imaging supplements optical measurements. A combination of flow visualization and image processing holds promise to breach the holy grail of extracting instantaneous three dimensional data in transport phenomena.
Optical methods can be enlarged to cover a wide range of measurements, first by factoring in the applicable physical laws and next, by including the principle of image formation itself. These steps help in utilizing incomplete data and imperfect visualization for reconstructing a complete scenario of the transport process.
Many applications involve gas-liquid interfaces that move in time and over a solid surface. Locating such boundaries from image sequences is an important step that can provide considerable insight. Flow visualization data can also be the starting point of inversion algorithms for retrieval of material properties and boundary conditions such as wall heat fluxes and shear stresses.
Images acquired in an experiment or from simulation contain a wealth of data and on multiple scales. Useful information can then be extracted using statistical and image processing tools. New developments such as tomographic reconstruction, digital correlation technique, and data mining algorithms, including AI, are quite appropriate for interpreting flow visualization data.
The journal will promote academic and industrial advancement and improvement of flow imaging techniques internationally. It seeks to convey practical information in this field covering all areas in science, technology, and medicine for engineers, scientists, and researchers in industry, academia, and government.
Flow visualization and quantification have emerged as powerful tools in velocity, pressure, temperature and species concentration measurements, combustion diagnostics, and process monitoring related to physical, biomedical, and engineering sciences. Measurements were initially based on lasers but have expanded to include a wider electromagnetic spectrum. Numerical simulation is a second source of data amenable to image analysis. Direct visualization in the form of high speed, high resolution imaging supplements optical measurements. A combination of flow visualization and image processing holds promise to breach the holy grail of extracting instantaneous three dimensional data in transport phenomena.
Optical methods can be enlarged to cover a wide range of measurements, first by factoring in the applicable physical laws and next, by including the principle of image formation itself. These steps help in utilizing incomplete data and imperfect visualization for reconstructing a complete scenario of the transport process.
Many applications involve gas-liquid interfaces that move in time and over a solid surface. Locating such boundaries from image sequences is an important step that can provide considerable insight. Flow visualization data can also be the starting point of inversion algorithms for retrieval of material properties and boundary conditions such as wall heat fluxes and shear stresses.
Images acquired in an experiment or from simulation contain a wealth of data and on multiple scales. Useful information can then be extracted using statistical and image processing tools. New developments such as tomographic reconstruction, digital correlation technique, and data mining algorithms, including AI, are quite appropriate for interpreting flow visualization data.
The journal will promote academic and industrial advancement and improvement of flow imaging techniques internationally. It seeks to convey practical information in this field covering all areas in science, technology, and medicine for engineers, scientists, and researchers in industry, academia, and government.
Call for Papers: Special Issue on Visualization of Transport Phenomena and Image Analysis
Flow visualization and quantification have emerged as powerful tools in velocity, pressure, temperature and species concentration measurements, combustion diagnostics, and process monitoring related to physical, biomedical, and other engineering sciences. Numerical simulation is a second source of data amenable to image analysis. Many applications involve gas-liquid interfaces that move in time and over a solid surface. Locating such boundaries from high-speed image sequences is an important step that can provide considerable insight. Images acquired in an experiment or from simulation contain a wealth of data and on multiple scales. Useful information can then be extracted using statistical and image processing tools. New developments such as tomographic reconstruction, digital correlation technique, and data mining algorithms, including AI, are quite appropriate for interpreting flow visualization data.
The subject domain of fluid flow and heat transfer offers tremendous opportunity for recording unexpected and interesting image sequences that improve interpretation and provide utility. With the development of high-speed optical imaging systems as well as efficient CFD simulation tools, it is now possible to record details of flow structures and their evolution in diverse contexts.
The special issue stems from the Golden Jubilee Fluid Mechanics and Fluid Power Conference − 2023 held at IIT Jodhpur (India) in December 2023 under the aegis of the National Society of Fluid Mechanics and Fluid Power. It is intended to provide the readers with new developments in the exciting field of flow visualization. Topics of interest to the special issue include direct visualization, refractive index and scattering techniques, IR imaging and AI tools of data analysis. Explaining three-dimensional time-resolved measurements and simulation, particularly in the context of vortex structures and thermal plumes constitute the theme of this call.
Guest editors:
Hardik Kothadia − Lead editorIIT Jodhpur, India
Email: hardikkothadia@iitj.ac.in
Arun Kumar R
IIT Jodhpur, India
Jaywant Arakeri
IIT Jodhpur, India
Rajneesh Bhardwaj
IIT Bombay, India
K. Muralidhar
IIT Kanpur, India
Submission Deadline: July 31, 2024
Paper Length (Recommended): 5000 words text and up to 8 full-page figures
Submission Instructions
Manuscripts (original research or comprehensive review) must be prepared according to the Instructions to Authors on the journal website and submitted via the Begell House journal submission portal (Begell House − Journal of Flow Visualization and Image Processing). Please select "Special issue: Visualization of Transport Phenomena and Image Analysis" when submitting manuscripts.La plupart des articles téléchargés
BACKGROUND-ORIENTED SCHLIEREN FOR FLOW AND THERMAL SYSTEMS: PRINCIPLES OF IMAGE FORMATION AND APPLICATIONS
EDGE DETECTION AND MACHINE LEARNING FOR AUTOMATIC FLOW STRUCTURES DETECTION AND TRACKING ON SCHLIEREN AND SHADOWGRAPH IMAGES
VISUALIZATION OF PARALLEL AND DISTRIBUTED PROGRAMS
VISUALIZATION OF DROP AND BUBBLE DYNAMICS ON A HEATED SAPPHIRE PLATE BY HIGH-SPEED CAMERA ENHANCED BY STEREOMICROSCOPE
VISUALIZATION OF DROPWISE CONDENSATION OF WATER VAPOR FROM EXPERIMENTS AND SIMULATION
OBSERVATIONS OF THE EMULSION FUEL GENERATING PROCESS ON UNDERWATER EXPLOSION
Open Access Articles
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Visualization and analysis of accelerating transonic flow over typical launch vehicle model using image processing
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