Lecture notes in chemistry, Год журнала: 2024, Номер unknown, С. 201 - 234
Опубликована: Янв. 1, 2024
Язык: Английский
Lecture notes in chemistry, Год журнала: 2024, Номер unknown, С. 201 - 234
Опубликована: Янв. 1, 2024
Язык: Английский
Water Air & Soil Pollution, Год журнала: 2025, Номер 236(2)
Опубликована: Янв. 20, 2025
Язык: Английский
Процитировано
1Journal of Water Process Engineering, Год журнала: 2024, Номер 66, С. 105997 - 105997
Опубликована: Авг. 17, 2024
Язык: Английский
Процитировано
5Separation and Purification Technology, Год журнала: 2025, Номер unknown, С. 131556 - 131556
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0Water, Год журнала: 2025, Номер 17(5), С. 742 - 742
Опубликована: Март 3, 2025
This study utilizes a novel self-excited oscillatory hydrodynamic cavitation (HC) device for tetracycline degradation. The effects of key parameters, including cavity length, inlet-to-outlet diameter ratio, and operational conditions (inlet pressure 0.3–0.8 MPa), as well the initial concentration (5.0–20.0 mg/L) addition common inorganic anions, on degradation are systematically explored. results show that oscillating cavitator, with length 23.0 mm an ratio 0.75 diameter: 3.0 mm; outlet 4.0 mm), generates strong HC effect. Under inlet 0.5 MPa 10.0 mg/L, rate reaches 51.32 ± 0.56%. three CO32−, NO3−, SO42−, all inhibit Fenton’s reagent further enhances efficiency via cavitation. optimal molar (TC:Fe2+:H2O2 = 1:1:10) is determined, resulting in 85.91 0.29% after 120 min reaction. cavitator proposed this offers simple structure, high reliability, improved efficiency, providing approach to antibiotic treatment.
Язык: Английский
Процитировано
0Brazilian Journal of Chemical Engineering, Год журнала: 2025, Номер unknown
Опубликована: Апрель 15, 2025
Язык: Английский
Процитировано
0Water Air & Soil Pollution, Год журнала: 2025, Номер 236(7)
Опубликована: Май 7, 2025
Язык: Английский
Процитировано
0Process Safety and Environmental Protection, Год журнала: 2025, Номер unknown
Опубликована: Май 1, 2025
Язык: Английский
Процитировано
0Advances in Environmental Protection, Год журнала: 2024, Номер 14(02), С. 361 - 366
Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
1Heliyon, Год журнала: 2024, Номер 10(16), С. e35580 - e35580
Опубликована: Авг. 1, 2024
Activated sludge models are increasingly being adopted to guide the operation of wastewater treatment plants. Chemical oxygen demand (COD) is an indispensable input for such models. To ensure that activated mathematical model can adapt various water quality conditions and minimize prediction errors, it essential predict parameters COD components in real-time based on actual influent concentrations. However, conventional methods determining components' contributions too intricate time-consuming be really useful. In this study, chemical waste plant was disassembled analyzed. The research involved proportions each component, assessing reliability measurement parameters, examining potential factors affecting accuracy, including weather conditions, pipeline residents' habits. Then, a backpropagation neural network developed which deliver predictions five important contributors real time. addition, using receiver operating characteristics curve accuracy evaluate performance model. For all components, SS, XS, SI, XA, XH, more than 80 %. maximum deviation values these fall within range detected values, suggesting model's align well with real-world observations, demonstrated adequate practical application treatment. This article provide basis engineering help intelligent upgrading
Язык: Английский
Процитировано
0Lecture notes in chemistry, Год журнала: 2024, Номер unknown, С. 201 - 234
Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
0