针对某企业生产的果葡糖浆在生产过程中出现的产品微生物污染情况,通过对生产果葡糖浆的不同环节取样进行微生物检测,对主要污染菌进行16S r DNA或26S r DNA D1/D2区域序列分析比对,鉴定为杆菌和酵母。通过污染微生物鉴定结果,结合实际...针对某企业生产的果葡糖浆在生产过程中出现的产品微生物污染情况,通过对生产果葡糖浆的不同环节取样进行微生物检测,对主要污染菌进行16S r DNA或26S r DNA D1/D2区域序列分析比对,鉴定为杆菌和酵母。通过污染微生物鉴定结果,结合实际生产过程中的情况,从不同生产环节入手,最后确定出污染源,从而为有效地控制生产工艺过程中潜在的微生物危害提供帮助。展开更多
It is necessary to identify a gaseous pollutant source rapidly so that prompt actions can be taken, but this is one of the difficulties in the inverse problem areas. In this paper, an approach to identifying a sudden ...It is necessary to identify a gaseous pollutant source rapidly so that prompt actions can be taken, but this is one of the difficulties in the inverse problem areas. In this paper, an approach to identifying a sudden continuous emission pollutant source based on single sensor information is developed to locate a source in an enclosed space with a steady velocity field. Because the gravity has a very important influence on the gaseous pollutant transport and the source identification, its influence is analyzed theoretically and a conclusion is drawn that the velocity of fluid is a key factor to effectively help weaken the gravitational influence. Further studies for a given 2-D case by using the computational fluid dynamics （CFD） method show that when the velocity of inlet is less than one certain value, the influence of gravity on the pollutant transport is very significant, which will change the velocity field obviously. In order to quantitatively judge the practical applicability of identification approach, a synergy degree of the velocity fields before and after a source appearing is proposed as a condition for considering the influence of gravity. An experimental device simulating pollutant transmission was set up and some experiments were conducted to verify the practical application of the above studies in the actual gravitational environment. The results show that the proposed approach can successfully locate the sudden constant source when the experimental situations meet the identified conditions.展开更多
环境水力学系统存在诸多不确定性,如测量数据的不确定性等,这导致水体中污染源识别这一类反问题具有不适定性,尤其表现为反演结果的非唯一性。经典的正则化方法和最优化方法由于只能获得参数的"点估计",因而在求解不确定性较...环境水力学系统存在诸多不确定性,如测量数据的不确定性等,这导致水体中污染源识别这一类反问题具有不适定性,尤其表现为反演结果的非唯一性。经典的正则化方法和最优化方法由于只能获得参数的"点估计",因而在求解不确定性较强的问题时存在较大的困难。此外水质模型和流场控制方程(Navier-Stokes方程)耦合,使得正问题的解具有较强的非线性特征。为解决上述问题,针对水动力-水质耦合模型,建立了基于贝叶斯推理的污染物点源识别的数学模型,通过马尔科夫链蒙特卡罗(Markov chain Monte Carlo,MCMC)后验抽样获得了污染源位置和强度的后验概率分布和估计量,较好地处理了模型的不确定性和非线性。算例结果表明,结合MCMC抽样的贝叶斯推理方法能很好地描述及求解水动力-水质耦合场条件下的污染源识别反问题。展开更多
文摘针对某企业生产的果葡糖浆在生产过程中出现的产品微生物污染情况,通过对生产果葡糖浆的不同环节取样进行微生物检测,对主要污染菌进行16S r DNA或26S r DNA D1/D2区域序列分析比对,鉴定为杆菌和酵母。通过污染微生物鉴定结果,结合实际生产过程中的情况,从不同生产环节入手,最后确定出污染源,从而为有效地控制生产工艺过程中潜在的微生物危害提供帮助。
基金supported by the National Natural Science Foundation of China (No. 50808007)
文摘It is necessary to identify a gaseous pollutant source rapidly so that prompt actions can be taken, but this is one of the difficulties in the inverse problem areas. In this paper, an approach to identifying a sudden continuous emission pollutant source based on single sensor information is developed to locate a source in an enclosed space with a steady velocity field. Because the gravity has a very important influence on the gaseous pollutant transport and the source identification, its influence is analyzed theoretically and a conclusion is drawn that the velocity of fluid is a key factor to effectively help weaken the gravitational influence. Further studies for a given 2-D case by using the computational fluid dynamics （CFD） method show that when the velocity of inlet is less than one certain value, the influence of gravity on the pollutant transport is very significant, which will change the velocity field obviously. In order to quantitatively judge the practical applicability of identification approach, a synergy degree of the velocity fields before and after a source appearing is proposed as a condition for considering the influence of gravity. An experimental device simulating pollutant transmission was set up and some experiments were conducted to verify the practical application of the above studies in the actual gravitational environment. The results show that the proposed approach can successfully locate the sudden constant source when the experimental situations meet the identified conditions.
文摘环境水力学系统存在诸多不确定性,如测量数据的不确定性等,这导致水体中污染源识别这一类反问题具有不适定性,尤其表现为反演结果的非唯一性。经典的正则化方法和最优化方法由于只能获得参数的"点估计",因而在求解不确定性较强的问题时存在较大的困难。此外水质模型和流场控制方程(Navier-Stokes方程)耦合,使得正问题的解具有较强的非线性特征。为解决上述问题,针对水动力-水质耦合模型,建立了基于贝叶斯推理的污染物点源识别的数学模型,通过马尔科夫链蒙特卡罗(Markov chain Monte Carlo,MCMC)后验抽样获得了污染源位置和强度的后验概率分布和估计量,较好地处理了模型的不确定性和非线性。算例结果表明,结合MCMC抽样的贝叶斯推理方法能很好地描述及求解水动力-水质耦合场条件下的污染源识别反问题。
