RESUMEN
During the outbreak of the novel coronavirus pneumonia (COVID-19), there is a huge demand for medical masks. A mask manufacturer often receives a large amount of orders that must be processed within a short response time. It is of critical importance for the manufacturer to schedule and reschedule mask production tasks as efficiently as possible. However, when the number of tasks is large, most existing scheduling algorithms require very long computational time and, therefore, cannot meet the needs of emergency response. In this paper, we propose an end-to-end neural network, which takes a sequence of production tasks as inputs and produces a schedule of tasks in a real-time manner. The network is trained by reinforcement learning using the negative total tardiness as the reward signal. We applied the proposed approach to schedule emergency production tasks for a medical mask manufacturer during the peak of COVID-19 in China. Computational results show that the neural network scheduler can solve problem instances with hundreds of tasks within seconds. The objective function value obtained by the neural network scheduler is significantly better than those of existing constructive heuristics, and is close to those of the state-of-the-art metaheuristics whose computational time is unaffordable in practice.
RESUMEN
Using a 150 L moving bed biofilm reactor (MBBR), with the temperature controlled at 28â and high NH4+-N concentration (average concentration 350 mg·L-1), inorganic wastewater was used as an influent to start the completely autotrophic nitrogen removal over nitrite (CANON) process. Meanwhile, the flocculent sludge was taken into a 5 L sequencing batch reactor, and the influent NH4+-N concentration was maintained at 90-200 mg·L-1 for the recovery of short-cut nitrification. The results showed that in the MBBR reactor, when the average hydraulic retention time (HRT) was 12 h, short-cut nitrification and total nitrogen (TN) removal rate were mutually constrained, the average TN removal rate was 38.2%, and the average δNO3--N/TN value was 0.274; when the HRT dropped to 6 h, the δNO3--N/TN value decreased from 0.347 to 0.146. The sequencing batch reactor (SBR) maintained aeration and anoxic time for 30 min and 20 min, respectively, by intermittent aeration, while the dissolved oxygen concentration during the aerobic process was 0.5 mg·L-1 to 0.6 mg·L-1, the free nitrous acid concentration was higher than 0.18 mg·L-1 at the end of each cycle, NAR increased from 0 to 99.2% after 12 days, NUR decreased to 0 from an initial 24.8 mg·(g·h)-1, and the TN removal rate decreased from 13% to 3%; the system successfully converted to short-range nitrification. High-throughput sequencing results showed that the abundance of Candidatus Kuenenia in the flocculent sludge and biofilm in the MBBR reactor were 7.91% and 17.38% respectively, Nitrosomonas accounted for 27.43% and 2.55%, respectively, while Nitrospira accounted for 0.30% and 0.28%, respectively. After the recovery of short-cut nitrification in the SBR, the abundance of ammonia-oxidizing bacteria and anaerobic ammonia oxidation decreased to 1.18% and 0.01%, respectively, and the abundance of Nitrospira increased to 1.39%.
RESUMEN
The focus of this paper, was low temperature, high ammonia nitrogen wastewater. The operation characteristics of the biofilm CANON process during the temperature reduction process were determined, by continuously adjusting different operating conditions. The aim was to explore the methods needed for the CANON process to obtain stable shortcut nitrification and a good nitrogen removal effect, when the influent NH4+-N concentration is high and the temperature low. The results showed that, â compared with the biofilm CANON reactor temperature changing from medium to low temperature directly (30â±1ââ19â), it was more conducive to adapt the nitrogen-removing bacteria to the low-temperature environment, while the temperature was gradually lowered. Moreover, the extent of each reduction should be minimized. Besides, the operating conditions should be adjusted to ensure the nitrogen removal effect. â¡ The temperature was gradually reduced to about 19â after 25 d, and then decreased to about 15â after another 18 d. The NH4+-N and TN removal rates could be respectively stable at 90% and 70% over a long period of time. The TN removal rate and removal load could still reach 72.52% and 0.78 kg·(m3·d)-1, respectively, even when the temperature dropped to 12â. ⢠When adapting biological CANON sludge during the temperature reduction process, shortcut nitrification should be given priority. A stable shortcut nitrification effect should be obtained by maintaining a certain concentration of residual NH4+-N, and by strictly controlling the DO concentration to restrain NOB activity.
RESUMEN
To Explore a suitable C/N ratio for efficient nitrogen removal and simultaneously achieving N2O release reduction, ammonia-rich wastewater with sodium acetate as an organic carbon source in a granular sludge completely autotrophic nitrogen removal over nitrite (CANON) reactor under different C/N water conditions were studied to determine the reactor's nitrogen removal performance and N2O release. The results showed that the total nitrogen (TN) removal rate and the removal load tended to increase gradually with the increase of C/N, ranging from 0 to 2.0. When C/N=0, the TN removal rate was 56.50 mg·L-1 in 7 h; the highest TN removal efficiency was 49%. When C/N=2.0, the highest TN removal rate was 71.42 mg·L-1 in 7 h; the highest TN removal efficiency was 59.52%, and the contribution of CANON to nitrogen removal gradually decreased, whereas the denitrification contribution gradually increased. When â³NO3--N/â³TN=0.086, the contribution of CANON nitrogen removal was only 51.48% and that of denitrification was 48.52%. The N2O release volume and release ratio decreased with increasing C/N. When C/N=0, the N2O release volume and rate were the highest, namely 3.60 mg and 2.13%, respectively. The lowest N2O release volume and rate were 1.61 mg and 0.75%, respectively, when C/N=2.0.