Design, Modeling, Optimization and Control of Flotation Process

The ultimate goal of a flotation process is to achieve the economically optimum combination of the desired mineral grade and recovery in the final concentrate from a feed of varying composition. The industrial operation of froth flotation faces many challenges, such as sudden decreases in the recove...

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অনলাইন ব্যবহার করুন:ONIX_20240704_9783725813964_170
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collection Directory of Open Access Books
description The ultimate goal of a flotation process is to achieve the economically optimum combination of the desired mineral grade and recovery in the final concentrate from a feed of varying composition. The industrial operation of froth flotation faces many challenges, such as sudden decreases in the recovery and grade of recovered materials. The quality of the final concentrate determines the success of the downstream processes, and achieving optimum metallurgical performance requires proper characterization, optimization, and control of the process. The efficiency of a flotation circuit operation relies on several factors that are pertinent to mineral nature and structure (variability of ore feed, particle size, mineralogy, and morphology) and the type of instrumentation and operational parameters (design parameters, reagents, quality of process water, air flow rate, and solid content) used, which require both advanced theoretical and practical studies. Hence, new techniques in the fields of design, modeling, optimization, and control of flotation processes have attracted much attention.This Special Issue is dedicated to the latest findings on methodologies, applications, and case studies regarding flotation to improve process efficiency, reduce energy consumption, and increase the sustainability of these processes. It provides a wide range of research and practical topics, including those related to design, simulation and instrumentation, and process control.
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language eng
publishDate 2024
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publisher MDPI - Multidisciplinary Digital Publishing Institute
publisherStr MDPI - Multidisciplinary Digital Publishing Institute
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spelling doab-20.500.12854ir-1393742024-07-04T09:47:39Z Design, Modeling, Optimization and Control of Flotation Process Nakhaei, Fardis Hassanzadeh, Ahmad Cisternas, Luis A. global sensitivity analysis uncertainty control structure SX process SAG mill copper ore flotation recurrent neural network predictive geometallurgy long short-term memory (LSTM) gated recurrent unit (GRU) flotation foam image processing image segmentation machine vision intelligent column flotation sulfur removal iron ore prediction multiple linear regression neural network k-means clustering convolutional neural network copper flotation fuzzy logic artificial neural network mathematical modeling gas dispersion flotation bubble size Sauter diameter froth flotation drainage drift flux mathematical model partial differential equation steady state numerical simulation PGM species PGE floatability kinetic model Platreef recovery gold-bearing ore fine particles flotation scheme carrier minerals wall correction slip correction field experiments gold microdispersions wetting film stability slip correction n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBC Engineering: general thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TT Other technologies and applied sciences::TTU Mining technology and engineering The ultimate goal of a flotation process is to achieve the economically optimum combination of the desired mineral grade and recovery in the final concentrate from a feed of varying composition. The industrial operation of froth flotation faces many challenges, such as sudden decreases in the recovery and grade of recovered materials. The quality of the final concentrate determines the success of the downstream processes, and achieving optimum metallurgical performance requires proper characterization, optimization, and control of the process. The efficiency of a flotation circuit operation relies on several factors that are pertinent to mineral nature and structure (variability of ore feed, particle size, mineralogy, and morphology) and the type of instrumentation and operational parameters (design parameters, reagents, quality of process water, air flow rate, and solid content) used, which require both advanced theoretical and practical studies. Hence, new techniques in the fields of design, modeling, optimization, and control of flotation processes have attracted much attention.This Special Issue is dedicated to the latest findings on methodologies, applications, and case studies regarding flotation to improve process efficiency, reduce energy consumption, and increase the sustainability of these processes. It provides a wide range of research and practical topics, including those related to design, simulation and instrumentation, and process control. 2024-07-04T09:47:37Z 2024-07-04T09:47:37Z 2024 book ONIX_20240704_9783725813964_170 9783725813964 9783725813957 https://directory.doabooks.org/handle/20.500.12854/139374 eng application/octet-stream Attribution-NonCommercial-NoDerivatives 4.0 International https://mdpi.com/books/pdfview/book/9372 https://mdpi.com/books/pdfview/book/9372 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-1395-7 10.3390/books978-3-7258-1395-7 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725813964 9783725813957 254 open access
spellingShingle global sensitivity analysis
uncertainty
control structure
SX process
SAG mill
copper ore flotation
recurrent neural network
predictive geometallurgy
long short-term memory (LSTM)
gated recurrent unit (GRU)
flotation foam
image processing
image segmentation
machine vision
intelligent
column flotation
sulfur removal
iron ore
prediction
multiple linear regression
neural network
k-means clustering
convolutional neural network
copper flotation
fuzzy logic
artificial neural network
mathematical modeling
gas dispersion
flotation
bubble size
Sauter diameter
froth flotation
drainage
drift flux
mathematical model
partial differential equation
steady state
numerical simulation
PGM species
PGE floatability
kinetic model
Platreef
recovery
gold-bearing ore
fine particles
flotation scheme
carrier minerals
wall correction
slip correction
field experiments
gold microdispersions
wetting film
stability
slip
correction
n/a
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBC Engineering: general
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TT Other technologies and applied sciences::TTU Mining technology and engineering
Design, Modeling, Optimization and Control of Flotation Process
title Design, Modeling, Optimization and Control of Flotation Process
title_full Design, Modeling, Optimization and Control of Flotation Process
title_fullStr Design, Modeling, Optimization and Control of Flotation Process
title_full_unstemmed Design, Modeling, Optimization and Control of Flotation Process
title_short Design, Modeling, Optimization and Control of Flotation Process
title_sort design modeling optimization and control of flotation process
topic global sensitivity analysis
uncertainty
control structure
SX process
SAG mill
copper ore flotation
recurrent neural network
predictive geometallurgy
long short-term memory (LSTM)
gated recurrent unit (GRU)
flotation foam
image processing
image segmentation
machine vision
intelligent
column flotation
sulfur removal
iron ore
prediction
multiple linear regression
neural network
k-means clustering
convolutional neural network
copper flotation
fuzzy logic
artificial neural network
mathematical modeling
gas dispersion
flotation
bubble size
Sauter diameter
froth flotation
drainage
drift flux
mathematical model
partial differential equation
steady state
numerical simulation
PGM species
PGE floatability
kinetic model
Platreef
recovery
gold-bearing ore
fine particles
flotation scheme
carrier minerals
wall correction
slip correction
field experiments
gold microdispersions
wetting film
stability
slip
correction
n/a
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBC Engineering: general
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TT Other technologies and applied sciences::TTU Mining technology and engineering
topic_facet global sensitivity analysis
uncertainty
control structure
SX process
SAG mill
copper ore flotation
recurrent neural network
predictive geometallurgy
long short-term memory (LSTM)
gated recurrent unit (GRU)
flotation foam
image processing
image segmentation
machine vision
intelligent
column flotation
sulfur removal
iron ore
prediction
multiple linear regression
neural network
k-means clustering
convolutional neural network
copper flotation
fuzzy logic
artificial neural network
mathematical modeling
gas dispersion
flotation
bubble size
Sauter diameter
froth flotation
drainage
drift flux
mathematical model
partial differential equation
steady state
numerical simulation
PGM species
PGE floatability
kinetic model
Platreef
recovery
gold-bearing ore
fine particles
flotation scheme
carrier minerals
wall correction
slip correction
field experiments
gold microdispersions
wetting film
stability
slip
correction
n/a
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBC Engineering: general
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TT Other technologies and applied sciences::TTU Mining technology and engineering
url ONIX_20240704_9783725813964_170