Nothing Special   »   [go: up one dir, main page]

Pascual et al., 2013 - Google Patents

Data-driven models of steady state and transient operations of spiral-wound RO plant

Pascual et al., 2013

View PDF
Document ID
6849070973651496754
Author
Pascual X
Gu H
Bartman A
Zhu A
Rahardianto A
Giralt J
Rallo R
Christofides P
Cohen Y
Publication year
Publication venue
Desalination

External Links

Snippet

The development of data-driven RO plant performance models was demonstrated using the support vector regression model building approach. Models of both steady state and unsteady state plant operation were developed based on a wide range of operational data …
Continue reading at www.researchgate.net (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
    • B01D—SEPARATION
    • B01D61/00—Processes of separation using semi-permeable membranes, e.g. dialysis, osmosis, ultrafiltration; Apparatus, accessories or auxiliary operations specially adapted therefor
    • B01D61/02—Reverse osmosis; Hyperfiltration; Nanofiltration
    • B01D61/025—Reverse osmosis; Hyperfiltration

Similar Documents

Publication Publication Date Title
Bartman et al. Minimizing energy consumption in reverse osmosis membrane desalination using optimization-based control
Pascual et al. Data-driven models of steady state and transient operations of spiral-wound RO plant
Abbas et al. Modeling of an RO water desalination unit using neural networks
Ray et al. A holistic review on how artificial intelligence has redefined water treatment and seawater desalination processes
Ferrero et al. Automatic control systems for submerged membrane bioreactors: A state-of-the-art review
Lee et al. Artificial neural network model for optimizing operation of a seawater reverse osmosis desalination plant
Madaeni et al. Modeling, optimization, and control of reverse osmosis water treatment in kazeroon power plant using neural network
Bartman et al. Nonlinear model-based control of an experimental reverse-osmosis water desalination system
Bartman et al. Model-predictive control of feed flow reversal in a reverse osmosis desalination process
KR101963124B1 (en) Remote diagnosing and managing system for small-scaled desalination equipment being separately installed in island area, and method for the same
Gao et al. Energy-optimal control of RO desalination
Sobana et al. Modeling and control of reverse osmosis desalination process using centralized and decentralized techniques
Toh et al. The techno-economic case for coupling advanced spacers to high-permeance RO membranes for desalination
Zhou et al. Modeling UF fouling and backwash in seawater RO feedwater treatment using neural networks with evolutionary algorithm and Bayesian binary classification
Ali et al. Robust model-based control of a tubular reverse-osmosis desalination unit
Bello et al. Fuzzy dynamic modelling and predictive control of a coagulation chemical dosing unit for water treatment plants
Gosmann et al. Data-driven forward osmosis model development using multiple linear regression and artificial neural networks
Adib et al. Experimental and computational investigation of polyacrylonitrile ultrafiltration membrane for industrial oily wastewater treatment
Stoller et al. Advanced control system for membrane processes based on the boundary flux model
US20230072711A1 (en) Apparatus and methods for cleaning reverse osmosis systems
Emad et al. Periodic control of a reverse osmosis desalination process
Rostamizadeh et al. Predicting gas flux in silicalite-1 zeolite membrane using artificial neural networks
Choi et al. Investigation of the filtration characteristics of pilot-scale hollow fiber submerged MF system using cake formation model and artificial neural networks model
Gaublomme et al. A hybrid modelling approach for reverse osmosis processes including fouling
Wang et al. Optimizing reverse osmosis desalination from brackish waters: Predictive approach employing response surface methodology and artificial neural network models