An argon reflux condensation system and method in which a plurality of once-through heat exchangers are connected to an argon column of an air separation plant to condense argon-rich vapor streams for production of reflux to the argon column. Condensation of the argon-rich vapor streams is brought about through indirect heat exchange with crude liquid oxygen streams that partially vaporize and are introduced into a lower pressure column of the plant for further refinement. The flow rate of the crude liquid oxygen streams are sensed and controlled at locations in the plant where the crude liquid oxygen is in a liquid state and in proportion to the size of the once-through heat exchangers. Feed stream flow rate to the argon column is controlled in response to air flow rate to the plant and product flow rate is controlled in response to the feed stream flow rate to the argon column.

An air separation unit comprises a first rectification column, having a top condenser and a second rectification column placed side by side, a heat exchanger, a first pump and a second pump connected in parallel, the first pump being capable of producing liquid at a first liquid pressure and the second pump being capable of producing liquid at a second liquid pressure, higher than the first pressure, each pump having an inlet connected to the second column, a first outlet of the first pump being connected to a first outlet conduit, a second outlet of the second pump being connected to a second outlet conduit, the first and second outlet conduits being connected to the condenser section

A method for operating a process system, in which method one or more actuators in the process system are set by means of one or more manipulated variable values, whereby one or more operating parameters of the process system are influenced. The setting of the one or more manipulated variable values is carried out at least in an operating phase using a self-optimizing control process, wherein the self-optimizing control process comprises the use of model-based reinforcement learning using Gaussian processes, and wherein one or more components of the process system are imaged in a model by means of one or more Gaussian processes, which model is used in the model-based reinforcement learning. The present invention also relates to a corresponding process system and to a method for converting a process system.

A method for obtaining an air product from an air separation plant having a distillation column system and a tank system. The tank system includes a first tank and a second tank. Cryogenic liquid is withdrawn from the distillation column system, stored in the tank system, and used as the air product. The cryogenic liquid is supplied to the first tank and withdrawn from the second tank during a first period, and is supplied to the second tank and withdrawn from the first tank during a second period. The tank system has a third tank to which cryogenic liquid withdrawn from the first tank and the second tank is transferred unheated. The air product is withdrawn from the third tank in liquid state, vaporized and discharged. Alternatively, the cryogenic liquid can be withdrawn from the third tank and stored in the liquid state in a fourth tank.

A request to initiate startup of an air separation plant may be received, and, in response to receiving the request, startup information that identifies a sequence of steps to be automatically executed to start up the air separation plant is retrieved. Each step may be associated with a component of the air separation plant, and may be associated with an action and a set of permissives corresponding to the action. The set of permissives for each action may specify one or more parameters for controlling the execution of the corresponding action. After retrieving the startup information, the system may automatically initiate execution of the sequence of steps, and may monitor the execution of each of the steps. The system may determine, based on the monitoring, whether to modify a parameter specified by one of the permissives corresponding to an executed action.

A nitrogen generating method for producing product nitrogen using a nitrogen generating device comprising a main heat exchanger for cooling feed air, a nitrogen rectification column into which the feed air cooled in the main heat exchanger is introduced, and a nitrogen condenser which condenses a vapour stream fed from the nitrogen rectification column and circulates the same to the nitrogen rectification column, the method including a control step for discharging liquid nitrogen condensed by the nitrogen condenser and stored in a liquid nitrogen buffer, which is provided in an upper gas phase portion of the nitrogen rectification column or separately from the nitrogen rectification column, to a rectification portion of the nitrogen rectification column in response to an increase in an amount of product nitrogen or an increase in a flow rate of the feed air.

The invention relates to: a method for monitoring a process engineering installation, in which a model of the process engineering installation is used to ascertain values of at least one performance parameter of the process engineering installation from actual values of at least one operating parameter of the process engineering installation that occur during operation of the process engineering installation, wherein the model is used to ascertain comparison values of the at least one performance parameter of the process engineering installation from setpoint values of the at least one operating parameter, and wherein mutually corresponding values and comparison values of the at least one performance parameter are taken as a basis for ascertaining at least one performance gap in the operation of the process engineering installation and to a process engineering installation.

An apparatus for distributing a flow of a liquid descending in an inner space of a packed column includes: a collector to collect the flow of the liquid; a mixer below and vertically spaced apart from the collector to receive and mix the liquid collected; a first conduit to receive and transmit at least part of the liquid from a first sector of the collector to a first zone of the mixer; and a second conduit to receive and transmit at least part of the liquid from a second sector of the collector to a second zone of the mixer. A geometric center of the first sector of the collector is positioned circumferentially away from a geometric center of the first zone of the mixer and/or a geometric center of the collector's second sector is positioned circumferentially away from a geometric center of the mixer's second zone.

The process and the apparatus serve for the low-temperature fractionation of air in a distillation column system, which has at least one separating column. Feed air is compressed in a main air compressor. Compressed feed air is cooled in a main heat exchanger. Cooled feed air is introduced into the distillation column system. At least one product stream is drawn off from the distillation column system, heated in the main heat exchanger and drawn off as a gaseous end product. At least one process parameter is set by a basic controller. The control of the process parameter is set by a combination of an ALC control and an MPC controller. This involves the ALC control outputting a first target value to the MPC controller. The MPC controller calculates from the first target value a setpoint value or a change to a setpoint value for a primary setpoint value output by the ALC control. The setpoint value determined by the MPC controller or a secondary setpoint value, which is calculated from the primary setpoint value output by the ALC control and the change to the setpoint value, is transmitted to the basic controller.

A computer-implemented system and method for producing and distributing at least one product from at least one plant to at least one customer where discretized plant production data, filtered customer sourcing data, forecasted customer demand data, and forecasted plant electricity pricing data are input into a modified genetic algorithm and an electronic processor solves the modified genetic algorithm and outputs the solution to an interface. The system and method is flexible and can incorporate data as it becomes available to yield intermediate solutions for quick decision making.