污水生化处理过程建模与控制

污水生化处理是利用微生物清除污水中有机污染物的一种有效方法, 是当前处理工业有机污水和城市生活污水的主要途径. 本文综述了污水生化处理过程, 尤其是活性污泥法处理过程的建模与控制. 从控制理论的角度, 生化污水处理过程是典型的非线性、时变、不确定性、时滞的复杂系统, 其建模与控制给控制界提出了严峻的挑战.     

Potentials of GHG reductions from wastewater treatment for the CDM

The study aims to evaluate the potential of GHG (greenhouse gas) reductions by installing an anaerobic digester in a wastewater treatment facility in Southeast Asia. Then the break-even point of additional investment to reduce GHG is obtained by exchanging carbon price as emissions credits. In the project scenario, the wastewater treatment system has the digester, where methane (biogas) is produced and recovered. Compared with the baseline scenario, the biogas has calorific value to produce heat and electri...     

Prioritisation approach for estimating the biophysical impacts of land-use change on stream flow and salt export at a catchment scale

Predicting the impacts of land-use change on stream flow and stream salt export at a catchment scale is hampered by limited detailed measured data, particularly with regard to hydrogeological information. A recently developed modelling approach is presented that can be used to predict the variation in likely catchment response to changes in woody cover using only broadly available data. The Biophysical Capacity to Change (BC2C) model combines a downward approach for water balance, with groundwater response using groundwater flow systems (GFS) mapping to provide hydrogeological and salinity parameters, into a spatial model for estimating the impacts of changes in woody vegetation cover across large areas. The results from the model are compared to gauged flow and salinity data for 14 stream gauging stations across the Murrumbidgee catchment, in south-eastern Australia. Considering the limited calibration of the model, the results compare favourably in broad terms, and provide a useful starting point for consideration of the impacts of land-use change on stream flow and salt load, and to guide catchment managers towards areas where more detailed study can be undertaken.     

Modeling and analysis of pumps in a wastewater treatment plant: A data-mining approach

A data-mining approach is proposed to model a pumping system in a wastewater treatment plant. Two parameters, energy consumption and wastewater flow rate after the pumping system, are used to evaluate the performance of 27 scenarios while the pump was operating. Five data-mining algorithms are applied to identify the relationships between the outputs (energy consumption and wastewater flow rate) and the inputs (elevation level of the wet well and the speed of the pumps). The accuracy of the flow rate and energy consumption models exceeded 90%. The derived models are deployed to optimize the pump system. The computational results obtained with the proposed models are discussed.     

The diversity of socio-economic pathways and CO2 emissions scenarios: Insights from the investigation of a scenarios database

The new scenario framework developed by the climate change research community rests on the fundamental logic that a diversity of socio-economic pathways can lead to the same radiative forcing, and therefore that a given level of radiative forcing can have very different socio-economic impacts. We propose a methodology that implements a “scenario discovery” cluster analysis and systematically identifies diverse groups of scenarios that share common outcomes among a database of socio-economic scenarios. We demonstrate the methodology with two examples using the Shared Socio-economic Pathways framework. We find that high emissions scenarios can be associated with either high or low per capita GDP growth, and that high productivity growth and catch-up are not necessarily associated with high per capita GDP and high emissions.     

Integration of Adaptive Neuro Fuzzy Inference Systems and principal component analysis for the control of tertiary scale formation on tinplate at a hot mill

Scale is highly detrimental to surface quality for tinplate products. There are a large number of process variables at a typical hot mill and principal component analysis is a well-known technique for reducing the number of process variables. This paper estimates the principal components associated with the hot mill process variables and puts these through an Adaptive Neuro Fuzzy Inference System (ANFIS) to find those hot mill running conditions that will minimise the amount of scale observed on the bottom of the rolled strip. It was found that the variation observed in all the hot mill process variables could be captured through the use of just six principal components, and that using just three of these in an ANFIS was sufficient to identify those operating conditions leading to coils being produced with a consistently low scale count. Specifically, it was found that the best operating conditions for the hot mill were when the first component was lower than −0.098 the second lower than 0.8058 and the third higher than −0.482. These ranges in turn corresponded to certain hot mill temperatures that depended to some extent on the base chemistry of the incoming slab.     

Comparative analysis on the application of neuro‐fuzzy models for complex engineered systems: Case study from a landfill and a boiler

This work aims at developing an explicit neuro‐fuzzy (NF) model to characterize complex engineered systems associated with high nonlinearity, uncertainties, and multivariable couplings. The NF model synergistically exploits the advantages of fuzzy belongingness of each input variable to all output variables and learning ability of neural networks. Owing to the inherent complexities associated with 2 complex engineered systems, a landfill and a boiler were selected to develop models that provide intelligent decisions for optimizing the operational parameters. Data compiled from field‐scale investigation/real plant operation involving various operating scenarios were used to develop the models. Predicting capability of the developed models was evaluated through the correlation coefficient and mean absolute percentage error values. Superiority of the proposed NF model to other similar models has been justified and demonstrated.     

On the role of individuals in models of coupled human and natural systems: Lessons from a case study in the Republican River Basin

In models of coupled human and natural systems (CHANS), the role of individuals and human behavior is often overlooked as data are scarce and assumptions hard to verify. To assess this role, we couple an agent-based model simulating farmers' behavior and a groundwater model and apply the models to the case of groundwater-fed irrigation in a river basin in the High Plains Aquifer region. Results show the crucial role of human behavior in driving the interactions between these coupled systems. Conversely, individuals are impacted by the systems’ dynamics in different ways depending on physical, economic and social characteristics. The findings provide implications for local policy making and education and demonstrate that assumptions on human behavior could be treated as an additional source of uncertainty. This work suggests that modeling individuals and human behavior can be an important step to simulate and understand the dynamics of CHANS in a holistic way.     

A separation method of transmission delays and data packet dropouts from a lumped input delay in the stability problem of networked control systems

This paper proposes a separation method of a transmission delay and data packet dropouts from a lumped input delay in the stability problem of a networked control system, where both the transmission delay and the data packet dropouts are involved. By modeling data packet dropouts as sampling processes and the transmission delay as a state delay, the networked control system is represented as a sampled‐data system with aperiodic sampling and a state delay. In order to separate the state delay and the sampling, the sampled‐data system is transformed into a new system with an integral operator, where the sampling is embedded into the integral operator. By investigating the integral operator's gain and passivity, a novel Lyapunov functional is constructed to address the stability problem. The obtained stability results are dependent on both the data packet dropouts and the time delay. A numerical example is provided to demonstrate that the stability results are less conservative than some existing ones. Copyright © 2016 John Wiley & Sons, Ltd.     

Good vacation and job rotation systems were beneficial for the hemoglobin level of workers at high altitude,a cross-sectional study along the Qinghai Tibet railway,China

Working and travelling in high-altitude regions have been associated with a variety of adverse health effects. The aim of this study was to explore a good vacation and job rotation system to prevent workers at high altitude from chronic altitude sickness. A total of 985 healthy male workers along the Qinghai-Tibet Railway, aged from 21 to 58 years (mean age 37.7 ± 8.6 years), were included into this study. The subjects took different short–term vacations, with different ratios of rest and work days. Furthermore, job rotation in low altitude was implemented in 127 (12.9%) subjects, who were transferred to relatively low altitude areas after working in plateau areas for more than three months. The association between vacation type and low altitude job rotation with prevalence of hyperhemoglobin (hemoglobin >175 g/L) was analyzed. Results showed that the risk of hyperhemoglobin decreased significantly with the increase of ratio of rest and work days, after adjusting for other confounding variables (age, ethnicity, education, body mass index, etc.) using multivariable logistic regression analysis. Meanwhile, the prevalence of hyperhemoglobin in job rotated workers was significantly lower than that in non-rotated workers [OR = 0.56, 95% CI: 0.37 to 0.84, p < 0.05]. Besides that, BMI, labor intensity, altitude at the workplace and frequency of oxygen supplementation were also closely related to the increase of hemoglobin level. We concluded that good vacation and job rotation system were effective means to prevent hyperhemoglobin and should be promoted in immigrants at high altitude for a long time.