Assessment of likely consequences of a potential accident is a major concern for loss prevention and
safety promotion in process industry. Loss of confinement on a storage tank, vessel or piping on industrial
sites could imply atmospheric dispersion of toxic or flammable gases. Gas dispersion forecasting is a
difficult task since turbulence modeling at large scale involves expensive calculations. Therefore simpler
models are used but remain inaccurate especially when turbulence is heterogeneous. The present work
aims to study if Artificial Neural Networks coupled with Cellular Automata could be relevant to overcome
these gaps. Two methods are reviewed and compared. An example database was designed from RANS k-
ε CFD model. Both methods were then applied. Their efficiencies are compared and discussed in terms of
quality, real-time applicability and real-life plausibility.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Black Box for Accident Analysis Using MATLAB-Image ProcessingEditor IJCATR
The main purpose of this paper is to develop a prototype device that can be installed in automobile for accident analysis .in this paper I proposed a method to analysis the face of driver that weather he was felling doziness while driving. This is done by taking the image from the raspberry pi device and put it in an image processing method using MATLAB. Also, I used the method to store the data into the cloud as well as device which can be further used for analysis the cause of accident.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Design of Kalman filter for Airborne ApplicationsIJERA Editor
Today multiple multi-sensor airborne surveillance systems are available which comprises of primary radar and
secondary surveillance radar as the active sensor on board. The electronics and communication support measure
system (ECSMS) will aid in identification, detection and classification of targets. These systems will detect,
identify, classify the different threats present in the surveillance area and supports defense operation. These
systems contain multiple functional operations as detection of air borne and surface target, tracking, and Multisensor
data fusion. This paper presents the multi-sensor data fusion technique and how to detect and track
moving target in the surveillance area.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Black Box for Accident Analysis Using MATLAB-Image ProcessingEditor IJCATR
The main purpose of this paper is to develop a prototype device that can be installed in automobile for accident analysis .in this paper I proposed a method to analysis the face of driver that weather he was felling doziness while driving. This is done by taking the image from the raspberry pi device and put it in an image processing method using MATLAB. Also, I used the method to store the data into the cloud as well as device which can be further used for analysis the cause of accident.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Design of Kalman filter for Airborne ApplicationsIJERA Editor
Today multiple multi-sensor airborne surveillance systems are available which comprises of primary radar and
secondary surveillance radar as the active sensor on board. The electronics and communication support measure
system (ECSMS) will aid in identification, detection and classification of targets. These systems will detect,
identify, classify the different threats present in the surveillance area and supports defense operation. These
systems contain multiple functional operations as detection of air borne and surface target, tracking, and Multisensor
data fusion. This paper presents the multi-sensor data fusion technique and how to detect and track
moving target in the surveillance area.
T he SPL - IT Query by Example Search on Speech system for MediaEval 2014multimediaeval
This document briefly describes the system submitted by the Speech Processing Lab of Instituto de telecomunicações, pole of Coimbra (SPL-IT) to the Query by Example Search on Speech Task (QUESST) of MediaEval 2014. Our approach is based on merging results of a phoneme recognition system using three different languages. A version of Dynamic Time Warping (DTW) using posteriorgram distances was created to allow finding
some of the peculiar search cases of this task. Our primary submission merges two approaches: simple DTW
for detecting entire queries and a version where cutting final portions of queries is allowed. The late submission merges 5 approaches that account for all the search possibilities described for the task, though improved results
were only observed in the evaluation dataset for type 3 queries.
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_74.pdf
CupCarbon simulator: Simulating the D-LPCN algorithm to find the boundary nodes of a WSN by Ahcene Bounceur, University of Bretagne Occidentale, Brest, France
Paper presented @Tyrrhenian Workshop on the Internet of Things 2009
ZigBee is probably the most popular IEEE 802.15.4 implementation used for Wireless Sensor Networks (WSN). The radio communication can also be used for localization purposes using fixed network devices as reference points. In this paper, the authors describe a procedure for automatically configuring a ZigBee-based localization appli-cation with environment-optimized parameters.
Definition and Validation of Scientific Algorithms for the SEOSAT/Ingenio GPPEsri
Presentation by Eduardo de Miguel, Raúl Valenzuela, Teodoro Bernardino, Verena Rodríguez, Alberto Pizarro, Diana de Miguel and Severino Fernández from INTA, GMV and EADS-CASA made on Esri European User Conference 2011.
El 29 de febrero y el 1 de marzo de 2016, la Fundación Ramón Areces analizó la relación entre 'Big Data y el cambio climático' en unas jornadas. ¿Puede el Big Data ayudar a reducir el cambio climático? ¿Cómo contribuirá ese análisis masivo de datos a prevenir y gestionar catástrofes naturales? Son solo algunas de las preguntas a las que intentarán responder los ponentes. Las ciencias vinculadas al clima tienen en el Big Data una herramienta muy prometedora para afrontar diferentes fenómenos asociados al cambio climático.
Principal component analysis based approach for fault diagnosis in pneumatic ...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Outstanding advancements in imaging technology have made cryogenic electron microscopy a powerful technique for the nanocharacterization of biological macromolecular complexes, reaching atomic levels of resolution and being applicable to a wider set of samples than the other competing technologies. The real breakthrough in the development of cryo-EM has happened less than a decade ago, with the introduction of direct detection devices. These cameras allow unprecedented speed and resolution, and Lawrence Berkeley National Lab is developing a new detector, the 4D cam- era, that can operate at 87000 frames per second, revealing exclusive temporal dynamics of the investigated processes.
The current bottlenecks of the 4D camera, however, are the management of the large amount of data generated (around 50 GB/s) and the intrinsic noise level characterizing the signal acquired at that speed. Yet, the high frame rate enables the recognition of single electrons when they strike the detector, as opposed to traditional electron microscopy, where the charge is cumulated for every frame. Electron counting has remarkable advantages since it completely rejects electrical background noise as well as the variability in the electron charge deposition phenomena and it dramatically compresses images by saving them as lists of events coordinates.
With this work, the counting efficiency of the algorithm is enhanced, through the introduction of a denoising step before thresholding out the background noise, rising the precision by 7.11% with respect to the reference implementation. Furthermore, the localization of the events is refined to allow super-resolution, and a classification step is added to reduce the is- sue of collision losses, caused by overlapping electrons. In the end, a 10000x compression ratio is achieved thanks to electron counting. A GPU acceleration of the final algorithm is also proposed, achieving, in the best case, a speed up of 284x. The timing performances of the developed tool, in fact, are crucial for its real time execution on the microscope output.
Ultimately, this work aims at enabling a more efficient data management between the microscopy center and the supercomputing facility, both involved in the data processing pipeline, by moving part of the computation towards the instrumentation and transferring only a compressed version of the datasets. The intelligent redistribution of workloads, in fact, removes the bottleneck in data transfer and grants the use of the microscope at its maximum frame rate.
Techniques for the evaluation of complex polynomials with one and two variables are
introduced.Polynomials arise in may areas such as control systems, image and signal processing, coding
theory,electrical networks, etc., and their evaluations are time consuming. This paper introduces new
evaluationalgorithms that are straightforward with fewer arithmetic operations and a fast matrix
exponentiation technique.
Techniques for the evaluation of complex polynomials with one and two variables are introduced.Polynomials arise in may areas such as control systems, image and signal processing, coding
theory,electrical networks, etc., and their evaluations are time consuming. This paper introduces new evaluation algorithms that are straightforward with fewer arithmetic operations and a fast matrix exponentiation technique.
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
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T he SPL - IT Query by Example Search on Speech system for MediaEval 2014multimediaeval
This document briefly describes the system submitted by the Speech Processing Lab of Instituto de telecomunicações, pole of Coimbra (SPL-IT) to the Query by Example Search on Speech Task (QUESST) of MediaEval 2014. Our approach is based on merging results of a phoneme recognition system using three different languages. A version of Dynamic Time Warping (DTW) using posteriorgram distances was created to allow finding
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for detecting entire queries and a version where cutting final portions of queries is allowed. The late submission merges 5 approaches that account for all the search possibilities described for the task, though improved results
were only observed in the evaluation dataset for type 3 queries.
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_74.pdf
CupCarbon simulator: Simulating the D-LPCN algorithm to find the boundary nodes of a WSN by Ahcene Bounceur, University of Bretagne Occidentale, Brest, France
Paper presented @Tyrrhenian Workshop on the Internet of Things 2009
ZigBee is probably the most popular IEEE 802.15.4 implementation used for Wireless Sensor Networks (WSN). The radio communication can also be used for localization purposes using fixed network devices as reference points. In this paper, the authors describe a procedure for automatically configuring a ZigBee-based localization appli-cation with environment-optimized parameters.
Definition and Validation of Scientific Algorithms for the SEOSAT/Ingenio GPPEsri
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El 29 de febrero y el 1 de marzo de 2016, la Fundación Ramón Areces analizó la relación entre 'Big Data y el cambio climático' en unas jornadas. ¿Puede el Big Data ayudar a reducir el cambio climático? ¿Cómo contribuirá ese análisis masivo de datos a prevenir y gestionar catástrofes naturales? Son solo algunas de las preguntas a las que intentarán responder los ponentes. Las ciencias vinculadas al clima tienen en el Big Data una herramienta muy prometedora para afrontar diferentes fenómenos asociados al cambio climático.
Principal component analysis based approach for fault diagnosis in pneumatic ...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Outstanding advancements in imaging technology have made cryogenic electron microscopy a powerful technique for the nanocharacterization of biological macromolecular complexes, reaching atomic levels of resolution and being applicable to a wider set of samples than the other competing technologies. The real breakthrough in the development of cryo-EM has happened less than a decade ago, with the introduction of direct detection devices. These cameras allow unprecedented speed and resolution, and Lawrence Berkeley National Lab is developing a new detector, the 4D cam- era, that can operate at 87000 frames per second, revealing exclusive temporal dynamics of the investigated processes.
The current bottlenecks of the 4D camera, however, are the management of the large amount of data generated (around 50 GB/s) and the intrinsic noise level characterizing the signal acquired at that speed. Yet, the high frame rate enables the recognition of single electrons when they strike the detector, as opposed to traditional electron microscopy, where the charge is cumulated for every frame. Electron counting has remarkable advantages since it completely rejects electrical background noise as well as the variability in the electron charge deposition phenomena and it dramatically compresses images by saving them as lists of events coordinates.
With this work, the counting efficiency of the algorithm is enhanced, through the introduction of a denoising step before thresholding out the background noise, rising the precision by 7.11% with respect to the reference implementation. Furthermore, the localization of the events is refined to allow super-resolution, and a classification step is added to reduce the is- sue of collision losses, caused by overlapping electrons. In the end, a 10000x compression ratio is achieved thanks to electron counting. A GPU acceleration of the final algorithm is also proposed, achieving, in the best case, a speed up of 284x. The timing performances of the developed tool, in fact, are crucial for its real time execution on the microscope output.
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Techniques for the evaluation of complex polynomials with one and two variables are
introduced.Polynomials arise in may areas such as control systems, image and signal processing, coding
theory,electrical networks, etc., and their evaluations are time consuming. This paper introduces new
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exponentiation technique.
Techniques for the evaluation of complex polynomials with one and two variables are introduced.Polynomials arise in may areas such as control systems, image and signal processing, coding
theory,electrical networks, etc., and their evaluations are time consuming. This paper introduces new evaluation algorithms that are straightforward with fewer arithmetic operations and a fast matrix exponentiation technique.
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Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
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Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
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This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
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Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
1. Institut des Sciences
des Risques
Atmospheric Turbulent Dispersion
Modeling Methods using Machine
Learning Tools
Laureta P., Heymesa F., Aprina L.,
Johanneta A., Dusserrea G., Lapébieb E., Osmontb A.
6th International Conference on Safety
& Environment in Process & Power Industry
Tuesday, April 15, 2014, Bologna, Italy
bCEA, DAM, GRAMAT, F-46500 Gramat, France
aLaboratoire de Génie de l’Environnement Industriel (LGEI), Ecole des Mines d’Alès, Alès, France
2. Institut des Sciences des Risques (France)
Institut des Sciences
des Risques
Modeling Experimental
15/04/2014 2 Institut Mines-Telecom CISAP6 13-16 April, 2014, Bologna, Italy
3. Institut des Sciences using Machine Learning Tools
Contents
Atmospheric Turbulent Dispersion Modeling Methods
Context of the study
Artificial Neural Networks
Methodology
Results
Improvements & Conclusion
des Risques
3 15/04/2014 Institut Mines-Telecom CISAP6 13-16 April, 2014, Bologna, Italy
4. Atmospheric Turbulent Dispersion Modeling Methods using Machine Learning Tools
Methodology Conclusion
Institut des
Sciences des
Risques Context Artificial Neural Networks Results
Industrial Site – Flammable/Toxic material storage - Dispersion
Leakage accident
Petrochemical site, Martigues,
France
Impact distance < 1 000 m
Exposure time < 1 h
4 15/04/2014 Institut Mines-Telecom CISAP6 13-16 April, 2014, Bologna, Italy
5. Atmospheric Turbulent Dispersion Modeling Methods using Machine Learning Tools
Methodology Conclusion
2. Turbulence modeling
Turbulent Diffusion
coefficient estimation
Institut des
Sciences des
Risques Context Artificial Neural Networks Results
Main goals of this work
1. From quickness to accuracy
CFD
RANS
LES
Accuracy
Quickness
Gaussian
Integrals
DNS
Closure
equations
Turbulent
diffusion
coefficient
calculation
Direct
resolution
5 15/04/2014 Institut Mines-Telecom CISAP6 13-16 April, 2014, Bologna, Italy
6. Atmospheric Turbulent Dispersion Modeling Methods using Machine Learning Tools
Methodology Conclusion
Institut des
Sciences des
Risques Context Artificial Neural Networks Results
Main goals of this work
1. From quickness to accuracy
Gaussian
Integrals
CFD
Developed
model
RANS
LES
DNS
2. Turbulence modeling
Turbulent Diffusion
coefficient estimation
Turbulent diffusion
coefficient forecasting
by Artificial Neural
Networks
Closure
equations
Turbulent
diffusion
coefficient
calculation
Direct
resolution
Accuracy
Quickness
6 15/04/2014 Institut Mines-Telecom CISAP6 13-16 April, 2014, Bologna, Italy
7. Atmospheric Turbulent Dispersion Modeling Methods using Machine Learning Tools
Methodology Conclusion
Institut des
Sciences des
Risques Context Artificial Neural Networks Results
Main goals of this work
3. Goals
Quickness
Developed
model
Accuracy
Developed
model
Consider
cylinder
obstacles
Real
experiments
designed
Near field
No expert
knowledge
required
7 15/04/2014 Institut Mines-Telecom CISAP6 13-16 April, 2014, Bologna, Italy
8. Atmospheric Turbulent Dispersion Modeling Methods using Machine Learning Tools
Methodology Conclusion
1. Re = 0,16 2. Re = 26
4. Re>2 x 104
3. 48<Re<180
Institut des
Sciences des
Risques Context Artificial Neural Networks Results
Flow around cylinder
5. Shape of flow
Behind a cylinder
1,2,3 from Taneda – 4,5 from Mines Alès
Atmospheric flow: Re > 106
Turbulence modeling is required
Unsteady behavior at Re >
2.104
Generally considered as steady
in modeling due to random
initialization of vortex
Modeling dispersion around cylinder
Once wind flow and turbulence
are solved
Eulerian: Advection Diffusion
Equation
Lagrangian: Particle tracking
8 15/04/2014 Institut Mines-Telecom CISAP6 13-16 April, 2014, Bologna, Italy
10. Atmospheric Turbulent Dispersion Modeling Methods using Machine Learning Tools
Methodology Conclusion
Institut des
Sciences des
Risques Context Artificial Neural Networks Results
Artificial Neural Networks (ANN) – Nonlinear phenomenon approximation
Non-linear statistical data modelling tools
Parameters modification to minimize the ANN error
Database of the phenomenon required
Field
Experiments
Phenomenon database
Wind Tunnel
Experiments
CFD
10 15/04/2014 Institut Mines-Telecom CISAP6 13-16 April, 2014, Bologna, Italy
11. Atmospheric Turbulent Dispersion Modeling Methods using Machine Learning Tools
Methodology Conclusion
Institut des
Sciences des
Risques Context Artificial Neural Networks Results
Artificial Neural Networks (ANN) – Nonlinear phenomenon approximation
Non-linear statistical data modelling tools
Parameters modification to minimize the ANN error
Database of the phenomenon required
Field
Experiments
Phenomenon database
Wind Tunnel
Experiments
CFD
11 15/04/2014 Institut Mines-Telecom CISAP6 13-16 April, 2014, Bologna, Italy
12. Atmospheric Turbulent Dispersion Modeling Methods using Machine Learning Tools
Methodology Conclusion
Institut des
Sciences des
Risques Context Artificial Neural Networks Results
ANN in Atmospheric Dispersion
Determination of important parameters (Cao, 2007)
Position of a plume
forecast of continuous standard deviation for gaussian plume
Filter for a gaussian model (Pelliccioni, 2006)
Concentrations levels predicted by gaussian model as an input of ANN
Other inputs used to refine results are atmospheric conditions parameters
Gaussian model improvement
Conclusions
Three different variables are used:
Spatial inputs
Atmospheric conditions inputs
Case configuration inputs
Database of the phenomenon required
12 15/04/2014 Institut Mines-Telecom CISAP6 13-16 April, 2014, Bologna, Italy
13. Atmospheric Turbulent Dispersion Modeling Methods using Machine Learning Tools
Methodology Conclusion
Institut des
Sciences des
Risques Context Artificial Neural Networks Results
Using the 2D-Advection Diffusion Equation (ADE) to solve atmospheric dispersion around
cylinder
ui and Dt are required
휕푐
휕푡
+ 푢푖
휕푐
휕푥푗
=
휕
휕푥푗
퐷푡 .
휕푐
휕푥푗
+ 푆푖 + 푅푖
Then, ADE can be solve with existing numerical scheme
Methodology
ui and Dt forecast using ANN
Solving ADE: Finite differences scheme
Database characteristics:
푢푖 Wind velocity in i direction
t Times
C Concentration
Si Emission source
Ri Reaction
Dt Turbulent diffusion coefficient
Created from CFD model : RANS k-휖 standard with neutral conditions of stability
72 simulations : Diameter ∈ 10; 52 m, velocity ∈ 2; 10 m.s-1
Domain dimensions: 34 diameters long, 7 diameters large
Mesh: from 112 000 to
448 000 nodes
Time consuming
Sampling is required
to train the ANN
13 15/04/2014 Institut Mines-Telecom CISAP6 13-16 April, 2014, Bologna, Italy
14. Atmospheric Turbulent Dispersion Modeling Methods using Machine Learning Tools
Methodology Conclusion
Institut des
Sciences des
Risques Context Artificial Neural Networks Results
Inputs and outputs variables for the ANN
Ux, Uy and Dt are each one
the output of an ANN
Inputs variables:
Location: polar coordinates
Configuration: Diameter
Flow conditions: Inlet velocity
Training of the ANN Dt
Several ANN models are trained with
variations on:
Sampling
Number of neurons in hidden layer
Parameters initialization
Best model is selected using mean squared
error quality indicator.
14 15/04/2014 Institut Mines-Telecom CISAP6 13-16 April, 2014, Bologna, Italy
15. Atmospheric Turbulent Dispersion Modeling Methods using Machine Learning Tools
Methodology Conclusion
Institut des
Sciences des
Risques Context Artificial Neural Networks Results
Inputs and outputs variables for the ANN
Ux, Uy and Dt are each one
the output of an ANN
Inputs variables:
Location: polar coordinates
Configuration: Diameter
Flow conditions: Inlet velocity
Training of the ANN
Several ANN models are trained with
variations on:
Sampling
Number of neurons in hidden layer
Parameters initialization
Best model is selected using mean squared
error quality indicator.
15 15/04/2014 Institut Mines-Telecom CISAP6 13-16 April, 2014, Bologna, Italy
16. Atmospheric Turbulent Dispersion Modeling Methods using Machine Learning Tools
Methodology Conclusion
Institut des
Sciences des
Risques Context Artificial Neural Networks Results
Using the ANN for Ux/Uy/Dt determination
Unlearned test case: D = 12 m ; Uini = 2,5 m.s-1
Coefficient of determination (R²) and FACtor of two (FAC2) are used to qualify the model
Ux Uy Dt
R²: 0,97 FAC2: 0,99 R²: 0,99 FAC2: 0,52 R²: 0,98 FAC2: 0,99
CFD
ANN
m.s-1 m.s-1 m2.s-1
CFD
ANN
CFD
ANN
16 15/04/2014 Institut Mines-Telecom CISAP6 13-16 April, 2014, Bologna, Italy
17. Atmospheric Turbulent Dispersion Modeling Methods using Machine Learning Tools
Methodology Conclusion
Institut des
Sciences des
Risques Context Artificial Neural Networks Results
Flow visualization
Unlearned test case: D = 12 m ; Uini = 2,5 m.s-1
CFD
ANN
Velocity vectors
CFD
ANN
Streamlines
17 15/04/2014 Institut Mines-Telecom CISAP6 13-16 April, 2014, Bologna, Italy
18. Atmospheric Turbulent Dispersion Modeling Methods using Machine Learning Tools
Methodology Conclusion
Institut des
Sciences des
Risques Context Artificial Neural Networks Results
Using the ADE
Wind flow and Turbulent diffusion coefficient are used to solve the ADE
Finite differences are used
Explicit resolution for advection and diffusion terms
Stability criteria has to be set :
Courant number is used for the advection terms: 훥푘 ≤
훥푥
푚푎푥 푈푥
Diffusion terms has to respect: 훥푘 ≤
훥푥2
2퐷푡
Minimum 훥푘 is selected
Cylinder obstacle is detected and convert on a rectangular mesh
Boundary conditions are set as in CFD model
Comparison is made from same initial concentrations
CFD Wind flow and Dt are interpolated on the new mesh
ANN Wind flow and Dt are calculated on the center of
the mesh cells
18 15/04/2014 Institut Mines-Telecom CISAP6 13-16 April, 2014, Bologna, Italy
19. Atmospheric Turbulent Dispersion Modeling Methods using Machine Learning Tools
Methodology Conclusion
Institut des
Sciences des
Risques Context Artificial Neural Networks Results
Using the ANN for Ux/Uy/Dt determination
Unlearned test case: D = 12 m ; Uini = 2,5 m.s-1
CFD
ANN
19 15/04/2014 Institut Mines-Telecom CISAP6 13-16 April, 2014, Bologna, Italy
20. Atmospheric Turbulent Dispersion Modeling Methods using Machine Learning Tools
Methodology Conclusion
Institut des
Sciences des
Risques Context Artificial Neural Networks Results
Using the ANN for Ux/Uy/Dt determination
Unlearned test case: D = 12 m ; Uini = 2,5 m.s-1
CFD
ANN
20 15/04/2014 Institut Mines-Telecom CISAP6 13-16 April, 2014, Bologna, Italy
21. Atmospheric Turbulent Dispersion Modeling Methods using Machine Learning Tools
Methodology Conclusion
Institut des
Sciences des
Risques Context Artificial Neural Networks Results
Using the ANN for Ux/Uy/Dt determination
CFD
Flow field and Dt by CFD turbulence model: from 20 minutes to 1 hour
ANN
Unlearned test case: D = 12 m ; Uini = 2,5 m.s-1
Computing time:
Flow field and Dt by ANN model: less than 2 seconds
But with different resolutions
Advection diffusion equation
~3 minutes for 1 minute in simulation time
With spatial resolution of 0.5 m
Optimization has to be made
Computer used :
Classical workstation
Processor: Intel® Core™2 Duo CPU: E7500-2,93 GHz
RAM: 4 Go
Windows 7 Professionnal
CFD software: Ansys® Fluent 14 Academic Research
21 15/04/2014 Institut Mines-Telecom CISAP6 13-16 April, 2014, Bologna, Italy
22. Atmospheric Turbulent Dispersion Modeling Methods using Machine Learning Tools
Risques Context Artificial Neural Networks Results
Methodology Conclusion
Institut des
Sciences des
Conclusion
Wind flow and turbulent diffusion coefficient modeling is very fast
Accuracy is evaluated through CFD comparison
Model has to be confront to experimental data
Turbulent dispersion is correctly modeled around a cylinder
Data needed are only diameter and inlet velocity to compute
turbulence in neutral stability conditions
ANN in combination with ADE resolution act as a grey box.
Quickness
Accuracy
Developed
model
Consider
cylinder
obstacles
Real
experiments
designed
Near field
No expert
knowledge
required
Perspectives
Experimental data acquisition are needed:
Comparison with current model
Training on real life data
Future work will be focused on dispersion over multiple obstacles
Tridimensional modeling of the flow field and Dt will be implement
Numerical optimization has to be done
Acknowledgements
This research was supported by the CEA: French Alternative Energies and Atomic Energy Commission
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23. Institut des Sciences
des Risques
Atmospheric Turbulent Dispersion
Modeling Methods using Machine
Learning Tools
Laureta P., Heymesa F., Aprina L.,
Johanneta A., Dusserrea G., Lapébieb E., Osmontb A.
6th International Conference on Safety
& Environment in Process & Power Industry
Tuesday, April 15, 2014, Bologna, Italy
bCEA, DAM, GRAMAT, F-46500 Gramat, France
aLaboratoire de Génie de l’Environnement Industriel (LGEI), Ecole des Mines d’Alès, Alès, France