A control system for monitoring a filter in a subsea control module (SCM) of an underwater hydrocarbon well is presented. The control system includes an upstream pressure transducer disposed upstream of a filter of the SCM and configured to sense an upstream pressure. The control system further includes a downstream pressure transducer disposed downstream of the filter and configured to sense a downstream pressure. Furthermore, the control system includes a subsea electronics module (SEM) coupled to the upstream pressure transducer and the downstream pressure transducer. The SEM is configured to determine average pressure differential values at different instances based on the upstream pressure and the downstream pressure. Moreover, the control system also includes a master control station (MCS) coupled to the SEM and configured to predict a filter maintenance generate an indication of the predicted filter maintenance due time for an operator of the underwater hydrocarbon well.

A method for determining at least one pore-related parameter of a porous material is provided. The method includes supplying a volatile liquid into a chamber, placing a porous material within the chamber, spaced apart from and over the volatile liquid, determining an effective mass of the chamber over a period of time, and determining at least one pore-related parameter of the porous material based on the effective mass determined. An arrangement for determining at least one pore-related parameter of a porous material is also provided.

Multicomponent copolymers including two or more types of repeat units is presented. In one example, the multicomponent copolymer includes at least one repeat unit AC having a structure (I), at least one repeat unit DC having a structure (II), and at least one repeat unit BC having a structure (III) or (V). The multicomponent copolymer may be cross-linked via a cross-linking agent. A polymer blend including the multicomponent copolymer or a cross-linked copolymer and a second polymer is also provided. The multicomponent copolymer may be a random or a block copolymer. The structural units of the multicomponent copolymers provide improved, tunable properties, such as improved biocompatibility and hydrophilicity, protein fouling, and mechanical properties, to the copolymers and/or the membranes fabricated from the copolymers.

A water treatment apparatus is provided with: a treatment vessel into which a solution of interest S is fed; a hollow fiber membrane which is immersed in the solution of interest S in the treatment vessel and has gas permeability; and a biological membrane which is formed on the outer surface of the hollow fiber membrane and utilizes oxygen-containing air fed into the hollow fiber membrane. In the water treatment apparatus, the solution of interest S is treated with the biological membrane. The water treatment apparatus is also provided with a gas-diffusing tube which is located below the hollow fiber membrane and ejects a washing gas to wash the biological membrane; and an oxygen concentration meter which measures the oxygen concentration in discharged air that has passed through the hollow fiber membrane.

The present application introduces a membrane fouling warning methodology grounded in machine learning. It utilizes a machine learning-based membrane fouling prediction model to automatically forecast and generate electrochemical information values, which characterize the extent of membrane fouling at various time points, based on influent water quality parameters. It then acquires the electrochemical information values Z.sub.t at a moment t and Z.sub.++t at a moment t+t. Subsequently, it computes and assesses the respective fouling levels using the electrochemical information values derived from the membrane fouling prediction model. Finally, it issues an early warning signal contingent upon the determined warning level. This methodology facilitates proactive understanding and management of membrane fouling, thereby sustaining the normal operation of the membrane fouling treatment system, mitigating the propensity for membrane assembly fouling, and prolonging the operational lifespan of the membrane assembly.

A benchtop device flow setup for determining the effectiveness of magnetic treatment of feed water for reducing mineral scaling includes two similar branches, both equipped with a reverse osmosis membrane and a pump that operate in the transient regime at the same flow rate and transmembrane pressure. The flow setup is further fed with a solution at the same level of supersaturation measured in a stirred reactor, however, only one branch exposes the feed to a magnetic field.

A method for assessing a state of fouling of a reverse osmosis system is provided. The method comprises deriving a plurality of impedance values from a low frequency region of an electrical impedance spectrum of a reverse osmosis membrane comprised in the reverse osmosis system, and determining a state of fouling of the reverse osmosis system based on 10 the plurality of derived impedance values. Use of the method for in-situ monitoring of fouling on a reverse osmosis membrane, and an apparatus for assessing a state of fouling of a reverse osmosis system are also provided.

The present application introduces a membrane fouling warning methodology grounded in machine learning. It utilizes a machine learning-based membrane fouling prediction model to automatically forecast and generate electrochemical information values, which characterize the extent of membrane fouling at various time points, based on influent water quality parameters. It then acquires the electrochemical information values Z.sub.t at a moment t and Z.sub.t+t at a moment t+t. Subsequently, it computes and assesses the respective fouling levels using the electrochemical information values derived from the membrane fouling prediction model. Finally, it issues an early warning signal contingent upon the determined warning level. This methodology facilitates proactive understanding and management of membrane fouling, thereby sustaining the normal operation of the membrane fouling treatment system, mitigating the propensity for membrane assembly fouling, and prolonging the operational lifespan of the membrane assembly.

A novel fluid filtration system that exhibits antifouling properties against a variety of potential foulants includes at least one filtration membrane placed in a cross-flow filtration module. The module is subjected to microwave irradiation at a certain power or intensity over a controlled time interval. At least one microwave generator produces microwaves and may be fixed or movable to treat the fluid. Dislodged foulants are removed by the microwave electromagnetic energy from the filtration membrane and carried away in a cross-flow stream and wasted or recycled back to a feed solution container. The filtration system may use different filtration configurations such as, but not limited to, flat sheet, hollow fiber, spiral wound and tubular membranes. The filtration membrane materials may be polymeric, ceramic, and combinations. The functionalized membranes can be such as, but not limited to, membranes coated or blended or cross-linked with materials displaying strong microwave absorption; and combinations.

This disclosure relates to an apparatus and method for analyzing an influence variable on membrane fouling of a seawater desalination system, wherein influence variables other than variables having a low degree of influence, among variables affecting the membrane, are selected, and the influence thereof on membrane fouling is used to derive an equation. The apparatus includes a variable storage unit configured to store variables affecting membrane fouling of a seawater desalination system, a dominant variable selection unit configured to select at least one dominant variable among the variables through at least one algorithm, and an equation derivation unit configured to derive a specific equation based on a correlation between the selected dominant variable and the membrane fouling.