膜生物反应器及其控制系统的应用研究

膜生物反应器是一种由膜分离单元与生物处理单元相结合的新型水处理技术,可靠高效的自动控制系统不仅能保证膜生物反应器的正常运行,还能降低其运行成本,延长膜通量和膜的使用寿命。本文以四川科学城医院膜生物反应器污水处理系统为例,讨论了膜生物反应器在处理医院废水中的应用,并介绍了适用于膜生物反应器的控制策略及控制系统。     

厌氧菌/好氧菌生物脱氮技术处理高浓度化工废水

针对己内酰胺生产废水成分复杂、毒性大、难以处理的特点,应用先进的厌氧菌/好氧菌(A/O)生物脱氮技术对己内酰胺生产废水进行处理.实际运行结果表明,A/O生物脱氮技术处理己内酰胺废水具有良好的效果,各项出水水质均达到国家Ⅲ类水域一级排放标准.     

基于PLC的生物反应器监控系统硬件设计

为了获得适宜的动物细胞培养环境,设计了基于PLC控制器的生物反应器监控系统.从控制系统的设计思想、测控点数分析、硬件结构、参数检测、执行部件、上下位机硬件系统集成等方面详细地说明了监控系统的硬件设计.实验结果表明:所研制的监控系统硬件配置合理、运行稳定可靠、操作方便,系统对反应器中的温度,pH值与溶氧3个环境参数进行了有效控制,系统满足细胞培养过程的控制要求.     

石油烃降解细菌应用于中试反应器处理油污压舱水的研究

石油污染压舱水盐度高、成分复杂且常含有毒物质,因此对这种污水的处理,尤其是在较大体积的情况下十分困难。针对这一问题,该文通过利用海洋来源的石油烃降解菌株构建人工菌群的方法,进行生物强化,从而提高油污压舱水的处理效率。先后分别在简单的 500 L 金属槽和特殊设计的 600 L 中试生物反应器中进行了预实验和正式处理实验,处理过程中持续检测总石油烃含量,并通过变性梯度凝胶电泳和 Illumina 高通量测序仪对处理体系中的菌群结构变化进行监测。两次试验中总石油烃降解效率分别达 70%、90% 以上,且初始的人工菌群结构发生了重组,最终形成以 Marinobacter hydrocarbonoclasticus(除烃海杆菌)、Acinetobacter venetianus(威尼斯不动杆菌)和 Alcanivorax dieselolei(柴油食烷菌)为优势种的新菌群。综上,该文提出的采用海洋石油烃降解细菌构建人工菌群 用于生物强化,是一种潜在的能够有效提高大体积石油污染压舱水处理效率的方法。     

三相生物流化床处理氨氮废水模糊控制系统研究

以实现好氧三相内循环生物流化床废水处理过程的闭环控制,克服曝气造成能耗大的问题为目的,研究并提出以入、出水的氨氮浓度为输入、输出量的好氧三相内循环生物反应器氨氮废水处理过程的主导数学模型,并针对这种大惯性、大滞后的被控对象,给出模糊PD+I控制方案。用谐波平衡法分析闭环控制系统的稳定性。计算机仿真分析表明系统对不同的扰动信号,能通过经济调整曝气量实现以一定精度,平稳、迅速趋向设定值,具有好的抗干扰能力和控制精度。     

微生物传感器及其应用

自从Dives利用Acetobacter Xylinum制备的第一支测量乙醇的微生物传感器问世以来,用于不同测量目的的微生物传感器相继出现。特别是近十年来,随着生物技术和换能器技术的发展,生物传感技术取得了可喜的进展,为生物反应器工艺控制和环境监测及综合评价开辟了一条新途径。 大约可测量五十多种物质和几种酶活性,而且还可对废水中可降解的有机物及毒性进行综合评价。本文仅就微生物传感器的基本原理及其在有关方面的应用作一概述。     

环隙气升式生物反应器三维CFD建模与仿真

气升式生物反应器被广泛地用于低耗氧微生物发酵过程中,如维生素C的发酵生产。采用计算流体力学对一个缩小的、工业环隙气升式生物反应器内的流体流动进行了建模与仿真,寻找该反应器内流体流动状态的规律。结果表明,在通气量比较小的情况下,生物反应器内的流体流动是极为复杂的,气含率分布和液体速度分布都存在着很大的不均匀性。但通过三维CFD仿真可以近似地确定流态接近CSTR和PFR的区域,从而为简化的CSTR-PFR组合流动模型的建模提供依据。     

生物表面活性剂在石油污染土壤生物预制床修复中的应用研究

通过拮抗实验选用高效降解菌B2020,真菌F2006、F2008、F6、F9904、F9902进行互配,对生物预制床中的高凝油、稠油、特稠油、稀油进行处理,发现生物表面活性剂对石油的降解有促进降解作用,在90~120d降解率提高较大。如果空气温度较高,无论是否施用生物表面活性剂,石油的降解速率都得到了大幅度提高,平均提高幅度为15%左右。因此,生物修复应尽量选择在温度较高的季节进行。     

上流式厌氧污泥反应器在石化高浓度废水预处理中的应用

为了更加有效地处理己内酰胺高浓度废水,在原A/O处理系统前采用上流式厌氧污泥反应器先对高浓度己内酰胺废水进行预处理.工业应用结果表明:由于己内酰胺高浓度废水中含有大量的硫酸盐、磷酸盐和硝酸盐等无机酸盐,因此必须严格控制反应系统进水的pH值在5.5～6.5之间,以有效保证系统平稳运行,防止酸化;当COD控制在8000～12000mg/L时,COD的去除率可达到55%以上,达到了处理后的水质要求.     

含酚废水的超声-活性炭联合处理

含酚废水对环境具有较大危害,去除废水中的酚含量对环境安全具有重要的意义.活性炭吸附和超声降解技术都被应用于废水处理中,本文首次将这2种技术联合起来处理含酚废水,并比较了活性炭吸附、超声降解和超声-活性炭联合技术3种方浇法的效果,表明超声-活性炭联合技术对苯酚的去除率高于单独使用活性炭吸附或超声降解,探讨了溶液pH值、超声时间、活性炭投加量等因素对联合处理含酚废水效果的影响,发现处理100 ml的0.01 mol/L的模拟含酚废水,溶液pH值为5,超声处理20 mins,0.4 g活性炭振荡吸附20 mins,可使苯酚去除率达到83.9%.联合技术可以综合2种技术的优势,在废水处理中有着广阔的应用前景.     

Near optimal interval observers bundle for uncertain bioreactors

In this paper we design an interval observer for the estimation of unmeasured variables of uncertain bioreactors. The observer is based on a bounded error observer, as proposed in [Lemesle, V., & Gouzé, J.-L. (2005). Hybrid bounded error observers for uncertain bioreactor models. Bioprocess and Biosystems Engineering, 27, 311-318], that makes use of a loose approximation of the bacterial kinetics. We first show how to generate guaranteed upper and lower bounds on the state, provided that known intervals for the initial condition and the uncertainties are available. These so-called framers depend on a tuning gain. They can be run in parallel and the envelope provides the best estimate. An optimality criterion is introduced leading to the definition of an optimal observer. We show that this criterion provides directly a gain set containing the best framers. The method is applied to the estimation of the total biomass of an industrial wastewater treatment plant, demonstrating its efficiency.     

A multivariable control scheme in a two-stage anaerobic digestion system described by partial differential equations

This paper deals with the design and application of a nonlinear multivariable controller in an anaerobic digestion system (AD) carried out in two interconnected fixed bed bioreactors. The proposed control scheme is derived from a mathematical model of the AD system described by a set of partial differential equations and consists of an estimator and two nonlinear control laws. The first law is developed to regulate the volatile fatty acids in the first bioreactor while the second aims at maintaining the chemical oxygen demand at predetermined set-points in the second bioreactor. The performance of the control algorithm is evaluated via numerical simulations in the face of load disturbances, parameter kinetic uncertainties and set-point changes. Stability and convergence properties of the proposed control scheme are also addressed in this paper.     

Fuzzy servo controller for CSTB with substrate inhibition kinetics

Continuous stirred tank bioreactors with non-monotonic growth kinetics can exhibit bifurcation and multiple equilibrium points. Maximum productivity for this bioreactor is located at the limit of a bifurcation. Therefore, when the desired operating point is near optimal productivity, even small perturbations may drive the system from stability to an undesired, unstable condition. This work describes a fuzzy servo controller that was designed based on sector nonlinearities to force the bioreactor to stay near its optimal productivity point. The designed controller enables tracking of a reference signal that switches between stable and unstable nodes and finally stabilizes at the optimal operating point. Two reference signals were evaluated for the substrate and the biomass respectively. The performance of the proposed controller was compared to PID and LQ controllers. Linear matrix inequalities were used to prove the closed-loop stability.     

A Luenberger-type observer for the AM2 model

In this paper, we deal with the problem of designing a new observer for bioreactor models. The main idea is to construct a nonlinear observer with linear errors, which has an adjustable and robust convergence. Simulation results are presented using a model of Chemostat and a model of an anaerobic digestion process for the treatment of wastewater.     

基于Hopfield 神经网络的污水处理过程优化控制

针对前置反硝化污水处理过程的优化控制问题,提出一种基于拉格朗日乘子法的Hofield神经网络优化方法.构造了污水处理过程约束优化问题的数学表达式,通过Hopfield神经网络优化计算生化池第5分区溶解氧浓度和第2分区硝态氮浓度的设定值,并采用PID控制器实现底层的跟踪控制.基于国际标准的Benchmark基准仿真平台进行仿真实验,结果表明污水处理系统在出水关键水质达标的基础上,能够显著降低能耗.     

End-point detection of the aerobic phase in a biological reactor using SOM and clustering algorithms

The estimation of the aerobic phase end-point is usually used to improve the operating capacity in a sequencing batch reactor. In this paper, a software tool and a configuration of the dissolved oxygen control closed loop are proposed to achieve the aerobic end-point detection of a sequencing batch reactor in a coke wastewater treatment plant. The proposed software tool consists of self-organizing map (SOM) and clustering algorithms. Moreover a validation method for SOM training is outlined and a predefined criterion to determine the SOM size is tested.     

Optimizing energy productivity of microbial electrochemical cells

Microbial electrochemical cells, such as microbial fuel cells (MFCs) and microbial electrolysis cells (MECs) are bioreactors that produce energy from organic matter, e.g. wastewater. The goal of this work is to optimize their product generation, either electricity or hydrogen, by selecting optimum operating current, with the influent flow (organic load) being adjusted to guarantee a given treatment capacity. Analysis of a multi-population model of a microbial electrochemical cell reveals that the ratio between different microbial populations in the anodic biofilm is determined by the current. Furthermore, the optimal operating current varies considerably with the internal resistance.     

Acclimatization model of an aerobic bioreactor for the treatment of toxic wastewater

This work proposes a mathematical model for the acclimatization process of a bioreactor treating toxic wastewater. Experimental data was used to identify the changing kinetic parameters of the model as acclimatization progresses. It was found that only one key parameter, the specific biomass growth rate function, changed during the acclimatization process. Therefore, an acclimatization model was proposed to explain the changes of this parameter.     

An integrated knowledge-based and optimization tool for the sustainable selection of wastewater treatment process concepts

The increasing demand on wastewater treatment plants (WWTPs) has involved an interest in improving the alternative treatment selection process. In this study, an integrated framework including an intelligent knowledge-based system and superstructure-based optimization has been developed and applied to a real case study. Hence, a multi-criteria analysis together with mathematical models is applied to generate a ranked short-list of feasible treatments for three different scenarios. Finally, the uncertainty analysis performed allows for increasing the quality and robustness of the decisions considering variation in influent concentrations. For the case study application, the expert system identifies 5 potential process technologies and, using this input, the superstructure identifies membrane bioreactors as the optimal and robust solution under influent uncertainties and tighter effluent limits. A mutual benefit and synergy is achieved when both tools are integrated because expert knowledge and expertise are considered together with mathematical models to select the most appropriate treatment alternative.