An evaporation system for spray evaporating undesired water comprising: a first pump, a container comprising a sump, a second pump, a spray manifold comprising a spray nozzle, a packing system disposed within the container, a third pump, and an air system comprising an air blower and an air preheater is disclosed. An outlet of a water inlet is connected to an inlet of the first pump. A first portion of a ceiling of the container is constituted by a demister element such that the first portion of the ceiling is entirely configured as an outlet for evaporated water. A second portion of the ceiling is adjacent to an upper edge of a wall of the container. An outlet of the first pump is connected to an inlet of the container. An inlet of a draw line is disposed in the sump; and an outlet of the draw line is connected to an inlet of the second pump. An outlet of the second pump is connected to an inlet of the spray manifold. The spray nozzle discharges water droplets onto the packing system. An inlet of the third pump is connected to an outlet of the sump. An outlet of the third pump is connected to a discharge outlet. The air system is disposed through the wall of the container; and the air system discharges air flow counter to and/or crossways to the water droplets from the spray nozzle. A method of using the evaporation system is also disclosed.

A method of operating a sequencing batch reactor process includes introducing wastewater to be treated into the sequencing batch reactor and subjecting the wastewater to treatment in the sequencing batch reactor in an aerated anoxic mode in in which a quantity of oxygen is supplied at a level insufficient to meet a biological oxygen demand of the wastewater, but sufficient to cause simultaneous nitrification and denitrification reactions to occur in the wastewater.

A device for monitoring evaporation capacity of a water surface evaporator in a process includes a water surface evaporator and a rain collector, the rain collector and the water surface evaporator having a same size of orifice area, height, and contour profile of a monitoring device. One side of the water surface evaporator is connected with a first measuring well through a pipeline, and another side of the water surface evaporator is connected with a first electromagnetic flowmeter, a water supplementing electromagnetic valve and an overflow electromagnetic valve through a water pipe. The water supplementing electromagnetic valve is connected with a water supplementing barrel through a water supplementing pipe. A water collecting barrel is installed below the special rain collector. A second magnetostrictive water level meter, a starting drainage switch and a stopping drainage switch are installed in the second measuring well.

A transitional water treatment wall for kidney dialysis is provided. The transitional wall includes several devices positioned on a mobile frame, the devices establishing fluid communication between a water source, pre-RO treatment equipment, and an RO system. The transitional water treatment wall also provides pressure and temperature control of the water being circulated. The mobile frame of the transitional water treatment wall includes wheels for providing ease of movement of the transitional water treatment wall. The mobile frame also limits space requirements for the various devices. The transitional wall also includes electrical outlets.

An apparatus and method for determining an amount of chemical input, and more particularly to an apparatus and method for determining the amount of a chemical to be added, which is necessary to achieve target water quality, wherein a required chemical concentration can be accurately calculated based on the temperature of the water and the target turbidity of the water includes an information-receiving unit configured to receive at least one of environmental information, chemical information, and water-quality information of the water present in a specific area and a chemical input determination unit configured to derive a multiple regression equation based on the received environmental information, chemical information, and water-quality information and to determine the future input of a chemical that is added to satisfy a target turbidity of the water present in the specific area based on the multiple regression equation.

A future state of a separation membrane is inferred to perform a stable membrane filtration operation. A learning model generation device (1) includes: an input data acquisition section (21) configured to acquire input data derived from operation data that is measured during a membrane filtration operation, the operation data including a membrane filtration pressure and a diffused air volume; and a learning section (13) configured to generate a learning model (31) for inferring the state of the separation membrane, by means of machine learning using the acquired input data as an input.

A method for collaborative optimization control method for organic nitrogen and inorganic nitrogen in a denitrification process is provided. The method includes: establishing ASM-mDON-DIN models for simultaneous simulation of microbial dissolved organic nitrogen (mDON) and inorganic nitrogen (DIN) in denitrification processes; and selecting a corresponding ASM-mDON-DIN model according to a set carbon/nitrogen ratio to collaboratively optimize the concentration values of mDON and DIN in the effluent in the denitrification process, to obtain best process operation parameter values.

An apparatus for controlling chemical dosing optimization in a water treatment plant treating feed water includes: a control value derivation part configured to receive real-time data, analyze the real-time data through a water treatment model and a controller in response to receiving the real-time data, and calculate a control value, such that the control value is to set a minimum of a chemical dosage while maintaining a state of treated water of the water treatment plant in a normal range, the water treatment model simulating the water treatment plant and the controller being an optimization algorithm; and a chemical dosing output control part configured to provide the control value to a water treatment control device.

An apparatus for controlling output in a water treatment plant treating water includes: a chemical dosing management part configured to analyze real-time data to determine a control mode of chemical dosing optimization, and provide the determined control mode as a management command; a chemical dosing optimization part configured to analyze the real-time data to derive a control value such that the control value is to set a minimum of a chemical dosage to be dose in the water while a state of treated water of the water treatment plant is maintained in a normal range; and a chemical dosing output control part configured to provide the control value to a water treatment control device for controlling the water treatment plant, according to the control mode of the management command.

A device for selecting an optimal model includes: a model storage part including a seed model storage place in which a seed model is stored, and an optimal model storage place in which an existing optimal model is stored; a model generation part configured to use training data to generate a variable model; and a model evaluation part configured to prepare evaluation data, and use the evaluation data to select a champion model from among a plurality of evaluation target models including the seed model, the existing optimal model, and the variable model by evaluating the plurality of evaluation target models.