基于神经网络的活性污泥系统建模及其控制

针对松江污水厂污水处理活性污泥系统,采用神经网络技术进行建模试验研究,在对实际运行数据剔除异常数据后,将样本数据随机分成训练样本、检验样本和测试样本.用试凑法确定合理的神经网络隐层节点数,用检验样本实时监控训练过程从而避免"过训练"现象,用多次改变网络初始连接权值求得全局极小点,从而建立了泛化能力较好的基于神经网络的活性污泥系统数学模型.利用建立的神经网络模型,对活性污泥系统运行情况的仿真与控制进行了分析研究.示例研究表明:神经网络技术能较好地应用于活性污泥系统的建模与控制,有很好的理论与实践意义.     

垃圾填埋场水分迁移模型的应用研究

以渗滤液回灌为核心的填埋场生化反应器是当今国际固体废物研究的新方向 ,其具有减少渗滤液处理难度和加速填埋场稳定化的作用 ,其中控制填埋场水分是关键。本文通过对填埋场水分运移特征的分析 ,建立了渗滤液回灌条件下 ,生化反应器填埋场水分迁移的饱和 -非饱和三维非稳定数学模型 ,并求其有限单元数值解 ,定量模拟和预报不同回灌条件下填埋场水分的时空分布规律并进行实用研究。针对重庆市长生桥卫生填埋场设计情况和实际条件 ,运移模拟模型分析了水平沟和竖式井回灌条件下填埋场内水分的分布规律 ,证明了协同回灌方式的有效性     

Estimating uncertainties and uncertainty contributors of CMB PM2.5 source apportionment results

The chemical mass balance (CMB) model was applied for source apportionment of PM_2.5 in Atlanta in order to explore levels and causes of uncertainties in source contributions. Monte Carlo analysis with Latin hypercube sampling (MC-LHS) was performed to evaluate the source impact uncertainties and quantify how uncertainties in ambient measurement and source profile data affect results. In general, uncertainties in the source profile data contribute more to the final uncertainties in source apportionment results than do those in ambient measurement data. Uncertainty contribution estimates suggest that non-linear interactions among source profiles also affect the final uncertainties although their influence is typically less than uncertainties in source profile data.     

Investigation of hydrogeologic processes in a dipping layer structure: 2. Transport and biodegradation of organics

Numerical simulation tools have been used to study the dominating processes during transport of aromatic hydrocarbons in the unsaturated soil zone. Simulations were based on field observations at an experimental site located on a glacial delta plain with pronounced layered sedimentary structures. A numerical model for transport in the unsaturated zone, SWMS-3D, has been extended to incorporate coupled multispecies transport, microbial degradation following Monod kinetics and gas diffusive transport of oxygen and hydrocarbons. The flow field parameters were derived from previous work using nonreactive tracers. Breakthrough curves (BTC) from the hydrocarbon field experiment were used to determine sorption parameters and Monod kinetic parameters using a fitting procedure. The numerical simulations revealed that the assumption of homogeneous layers resulted in deviations from the field observations. The deviations were more pronounced with incorporation of reactive transport, compared with earlier work on nonreactive transport. To be able to model reasonable BTC, sorption had to be reduced compared to laboratory experiments. The initial biomass and the maximum utilisation rate could be adjusted to capture both the initial lag phase and the overall degradation rate. Nevertheless, local oxygen limitation is predicted by the model, which was not observed in the field experiment. Incorporation of evaporation and diffusive gas transport of the hydrocarbons did not significantly change the local oxygen demand. The main cause of the observed discrepancies between model and field are attributed to channelling as a result of small-scale heterogeneities such as biopores.     

Using stochastic risk assessment in setting information priorities for managing dioxin impact from a municipal waste incinerator

The objectives of this study were to assess site-specific carcinogenic risk of incinerator-emitted dioxins in a manner reflecting pollutant transfer across multimedia and multi-pathways. The study used site-specific environmental and exposure information and combined the Monte Carlo method with multimedia modeling to produce probability distributions of risk estimates. The risk estimates were further categorized by contaminated environmental media and exposure pathways that are experienced by human receptors in order to pinpoint significant sources of risk. Rank correlation coefficients were also calculated along with the Monte Carlo sampling to identify key factors that influenced estimation of risk. The results showed that ingestion accounted for more than 90% of the total risk and that risk control on ingestion of eggs, aboveground vegetables, and poultry should receive priority. It was also found that variation of parameters with variability accounted for around 35% of the total risk variance, while uncertainty contributed to the remaining 65%. Intake rates of aboveground vegetables, eggs, and poultry were the key parameters with the largest contribution to variance. In addition, sufficient sampling and analysis of dioxin contents in eggs, aboveground vegetables, poultry, soil, and fruit should be performed to improve risk estimation because the variation in concentrations in these media accounted for the largest overall risk variance. Finally, focus should be placed on reduction of uncertainty associated with the risk estimation through ingestion of aboveground vegetables, eggs, poultry, fruit, and soil because the risk estimates associated with these exposure pathways had the largest variance.     

Large outdoor chamber experiments and computer simulations: (I) Secondary organic aerosol formation from the oxidation of a mixture of d-limonene and α-pinene

This work merges kinetic models for α-pinene and d-limonene which were individually developed to predict secondary organic aerosol (SOA) formation from these compounds. Three major changes in the d-limonene and α-pinene combined mechanism were made. First, radical–radical reactions were integrated so that radicals formed from both individual mechanisms all reacted with each other. Second, all SOA model species from both compounds were used to calculate semi-volatile partitioning for new semi-volatiles formed in the gas phase. Third particle phase reactions for particle phase α-pinene and d-limonene aldehydes, carboxylic acids, etc. were integrated. Experiments with mixtures of α-pinene and d-limonene, nitric oxide (NO), nitrogen dioxide (NO₂), and diurnal natural sunlight were carried out in a dual 270 m³ outdoor Teflon film chamber located in Pittsboro, NC. The model closely simulated the behavior and timing for α-pinene, d-limonene, NO, NO₂, O₃ and SOA. Model sensitivities were tested with respect to effects of d-limonene/α-pinene ratios, initial hydrocarbon to NO_x (HC₀/NO_x) ratios, temperature, and light intensity. The results showed that SOA yield (Y_SOA) was very sensitive to initial d-limonene/α-pinene ratio and temperature. The model was also used to simulate remote atmospheric SOA conditions that hypothetically could result from diurnal emissions of α-pinene, d-limonene and NO_x. We observed that the volatility of the simulated SOA material on the aging aerosol decreased with time, and this was consistent with chamber observations. Of additional importance was that our simulation did not show a loss of SOA during the daytime and this was consistent with observed measurements.     

Space-time modeling for the Missouri Turkey Hunting Survey

The Missouri Turkey Hunting Survey (MTHS) is a postseason mail survey conducted by the Missouri Department of Conservation. The 1996 MTHS provides information concerning the number of turkeys harvested by hunters on each day and the total number of trips made to the counties by these hunters on each day of the hunting season. The success rates are then found from this information. Small sample sizes produce large standard errors for the estimates at the county level. We use a Bayesian hierarchical generalized linear model to estimate daily hunting success rates at the county level. The model includes an autoregressive process for the days of the hunting season and spatially correlated random geographic effects. The computations are performed using Gibbs sampling and adaptive rejection sampling techniques. Results show that there are significant spatial corelations between counties and correlations between days of the hunting season. The estimates are close to the frequency estimates at the state level and much more stable at the county level.     

Modeling Prescribed Surface-Fire Regimes for Pinus strobus Conservation

Abstract:  We developed a simple model of   Pinus strobus L. stand dynamics to compare the impacts of different temporal arrangements of surface fires designed to reflect the application of fire as both an essential ecosystem process (natural fire) and as an efficient means of producing specific habitat features or other values (optimal fire). We used a stochastic simulation model of fire processes to estimate the mean fire-return interval that would maximize stand structural diversity. We investigated trade-offs between structural diversity and temporal population stability associated with changes in the fire interval and used a deterministic version of the model to explore the effects of scheduling fires at fixed intervals. In stochastic simulations, maximum structural diversity occurred at intermediate levels of disturbance (40-year mean fire interval). When fires were scheduled at fixed intervals, a longer, 100-year return interval maximized diversity. Mean fire-return interval was a mitigating factor in the diversity-stability relationship, which changed from positive to negative as the fire interval was reduced progressively from 250 to 5 years. As an alternative to scheduling fires at specified mean intervals, we developed a goal-programming model (a form of linear programming model) and used it to identify an optimal fire schedule for achieving habitat and visual-quality objectives. In comparison with the 40-year stochastic mean fire interval, which maximized structural diversity, the optimal schedule produced comparable levels of both diversity and fire frequency. Our results show how simulation and goal-programming models can be used to evaluate prescribed fire-scheduling alternatives and to explore the comparative advantages of natural and optimal fire-management approaches.     

Wind Tunnel Experiments and Numerical Simulation of Snow Drifting around an Avalanche Protecting Dam

To learn about wind flow and snow drifting around avalanche dams, experiments were done in the Jules Verne Climatic Wind Tunnel. The paper reports the results from numerical wind flow simulations that were done to support the findings from the wind tunnel. Satisfying the model similitude criteria for the wind tunnel configuration was difficult due to the inevitable small geometric scale of the model, while on the contrary the snow drifting conditions in the facilities were full scale. By comparing numerical wind flow results of full scale and model scale dams with the snow pattern observed in the wind tunnel, it was possible to conclude that albeit poor model similitude, the snowdrifts on the windward side of the wind tunnel model are likely to indicate the full scale natural situation.