In this paper, the main factors impacting the plug flow pattern of a clearwell were investigated by integrating pilot-scale,
full-scale clearwell tracer testing and computational fluid dynamics (CFD) simulation. It was found that pilot tracer testing,
full-scale tracer testing and CFD simulation all demonstrated that the correlation between the ratio of t10/T and L/W can be approximately expressed by: t10/T = 0.189 4ln(L/W)-0.049 4. This study confirmed that the installation of baffles within clearwells is an efficient way to optimize their configuration.
In addition, the inlet velocity has a minimal contribution to the ratio of t10/T. However, the ratio of turning channel width to channel width (d/W) significantly contributes to the ratio of t10/T. The optimal ratio of d/W is 0.8–1.2 for maintaining better plug flow pattern. The number of turning channels is one of the main factors that impact
the ratio of t10/T. When increasing the number of turning channels, a lower ratio of t10/T is obtained. 相似文献
In this paper, the main factors impacting the plug flow pattern of a clearwell were investigated by integrating pilot-scale, full-scale clearwell tracer testing and computational fluid dynamics (CFD) simulation. It was found that pilot tracer testing, full-scale tracer testing and CFD simulation all demonstrated that the correlation between the ratio of t10/T and L/W can be approximately expressed by: t10/T = 0.189 4ln(L/W)-0.049 4. This study confirmed that the installation of baffles within clearwells is an efficient way to optimize their configuration. In addition, the inlet velocity has a minimal contribution to the ratio of t10/T. However, the ratio of turning channel width to channel width (d/W) significantly contributes to the ratio of t10/T. The optimal ratio of d/W is 0.8–1.2 for maintaining better plug flow pattern. The number of turning channels is one of the main factors that impact the ratio of t10/T. When increasing the number of turning channels, a lower ratio of t10/T is obtained. 相似文献
Objective: This article investigated and compared frequency domain and time domain characteristics of drivers' behaviors before and after the start of distracted driving.
Method: Data from an existing naturalistic driving study were used. Fast Fourier transform (FFT) was applied for the frequency domain analysis to explore drivers' behavior pattern changes between nondistracted (prestarting of visual–manual task) and distracted (poststarting of visual–manual task) driving periods. Average relative spectral power in a low frequency range (0–0.5 Hz) and the standard deviation in a 10-s time window of vehicle control variables (i.e., lane offset, yaw rate, and acceleration) were calculated and further compared. Sensitivity analyses were also applied to examine the reliability of the time and frequency domain analyses.
Results: Results of the mixed model analyses from the time and frequency domain analyses all showed significant degradation in lateral control performance after engaging in visual–manual tasks while driving. Results of the sensitivity analyses suggested that the frequency domain analysis was less sensitive to the frequency bandwidth, whereas the time domain analysis was more sensitive to the time intervals selected for variation calculations. Different time interval selections can result in significantly different standard deviation values, whereas average spectral power analysis on yaw rate in both low and high frequency bandwidths showed consistent results, that higher variation values were observed during distracted driving when compared to nondistracted driving.
Conclusions: This study suggests that driver state detection needs to consider the behavior changes during the prestarting periods, instead of only focusing on periods with physical presence of distraction, such as cell phone use. Lateral control measures can be a better indicator of distraction detection than longitudinal controls. In addition, frequency domain analyses proved to be a more robust and consistent method in assessing driving performance compared to time domain analyses. 相似文献
To manage potential microbial risks and meet increasingly strict drinking water health standards, UV treatment has attracted increasing attention for use in drinking water systems in China. However, the effects of UV treatment on microbial control and disinfection by-products (DBPs) formation in real municipal drinking water systems are poorly understood. Here, we collected water samples from three real drinking water systems in Beijing and Tianjin to investigate the impacts of UV treatment on microbial control and DBP formation. We employed heterotrophic plate count (HPC), flow cytometry (FCM), quantitative PCR analysis, and high-throughput sequencing to measure microorganisms in the samples. Different trends were observed between HPC and total cell count (measured by FCM), indicating that a single indicator could not reflect the real degree of biological re-growth in drinking water distribution systems (DWDSs). A significant increase in the 16S rRNA gene concentration was observed when the UV system was stopped. Besides, the bacterial community composition was similar at the phylum level but differed markedly at the genera level among the three DWDSs. Some chlorine-resistant bacteria, including potential pathogens (e.g., Acinetobacter) showed a high relative abundance when the UV system was turned off. It can be concluded that UV treatment can mitigate microbial re-growth to some extent. Finally, UV treatment had a limited influence on the formation of DBPs, including trihalomethanes, haloacetic acids, and nitrogenated DBPs. The findings of this study may help to understand the performance of UV treatment in real drinking water systems. 相似文献