Optimization Design of Groundwater Pollution Monitoring Scheme and Inverse Identification of Pollution Source Parameters Using Bayes’ Theorem

Zhang, Shuangsheng; Qiang, Jing; Liu, Hanhu; Li, Yanyan

doi:10.1007/s11270-019-4369-5

Cited by 14 publications

(7 citation statements)

References 27 publications

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“…19,20 These recent methods rely on predictive and, in most cases, complex modeling of the polymerization. 21 Here, we demonstrate that synthesis of the starting polymers through RAFT control provides a simple, reproducible, scalable, and, importantly, almost kinetic model-free method. By using only a mixture of a few of these starting polymers, we are able to produce near-square, slanted, and even chair-shaped MWDs, with high predictability.…”

Section: ■ Introductionmentioning

confidence: 83%

“…However, not being able to reproducibly and consistently produce the starting polymers with the same MWD prior to mixing has been a major challenge. Recent attempts to overcome this blending hurdle are to create the desired overall MWD directly through the polymer synthesis by modifying the polymerization kinetics through machine learning-assisted kinetic modeling, controlling catalytic reactivity, − and flow chemistry. , These recent methods rely on predictive and, in most cases, complex modeling of the polymerization . Here, we demonstrate that synthesis of the starting polymers through RAFT control provides a simple, reproducible, scalable, and, importantly, almost kinetic model-free method.…”

Section: Introductionmentioning

confidence: 83%

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Shape Control over the Polymer Molecular Weight Distribution and Influence on Rheological Properties

et al. 2022

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The shape, breadth, and average molecular weight of the overall molecular weight distribution (MWD) largely define polymer properties. In conventional free-radical polymerization, control over this distribution is through the many competing kinetic pathways dominated by radical termination events. “Living” radical polymerization mechanistically minimizes these termination events, providing a facile route to a desired Gaussian distribution with the distribution breadth dependent upon the activity of the catalyst or modulating agent. However, producing unusually shaped distributions can only be achieved through modeling of the complex polymerization kinetics and invoking feeding and other methods. Here, we construct square, slanted, and chair-like MWDs by blending two to four polymers made using a low-reactive RAFT agent with dispersities close to 2. The synthesis of these polymers, unlike that of polymers made with high-reactive RAFT agents, is simple, scalable, and importantly reproducible as the MWD is independent of conversion, making this polymerization method virtually and kinetically model-free. The blending method described here overcomes many of the difficulties in producing unusually shaped MWDs and allows control over the shape and breadth of the MWD. The concept further provides a general synthetic strategy for studying important structure–property relationships of polymers with desired processing and performance characteristics. This is demonstrated by measurement and modeling analysis of the linear viscoelastic properties of selected samples, which provides a way to tailor the properties of polymers by controlling the form of their MWD via blending. Unlike conventional approaches analyzing the effects of the MWD, its actual shape is considered and its effect on the properties is addressed.

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Section: ■ Introductionmentioning

confidence: 83%

Section: Introductionmentioning

confidence: 83%

Shape Control over the Polymer Molecular Weight Distribution and Influence on Rheological Properties

et al. 2022

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“…Most previous studies on groundwater CSC are based on two-dimensional (2D) conceptualizations (e.g. Essouayed et al, 2020;Zhang et al, 2020;Chang et al, 2021;Todaro et al, 2021), and just a few studies (such as Mirghani et al, 2009;Wang and Jin, 2013) address three-dimensional (3D) cases. The majority of studies assume that all hydrogeological and contaminant transport parameters are known (e.g.…”

Section: Introductionmentioning

confidence: 99%

Joint identification of contaminant source characteristics and hydraulic conductivity in a tide-influenced coastal aquifer

Dodangeh

Rajabi

Carrera

et al. 2022

Journal of Contaminant Hydrology

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“…Emergency identification problems are relatively difficult to identify under high-dimensional unsteady flow, and the stability of the method requires further study. The Bayesian inference method is another stochastic method based on probability theory, and it transforms emergency identification problems into the posterior estimation of unknown parameters on the basis of Bayesian inference and Markov chain Monte Carlo sampling technique (Bayesian-MCMC) (Han et al, 2014;Yang et al, 2016;Yu et al, 2020;Zhang et al, 2020). For example, Jiang et al (2017) studied the source identification problem of SWPAs that occur in rivers on the basis of Bayesian theory and the tracer experiment.…”

Section: Introductionmentioning

confidence: 99%

Identification of source information for sudden hazardous chemical leakage accidents in surface water on the basis of particle swarm optimisation, differential evolution and Metropolis–Hastings sampling

Yang

Liu

2021

Environ Sci Pollut Res

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A quick and accurate identification of source information on sudden hazardous chemical leakage accident is crucial for early accident warning and emergency response. This study firstly regards source identification problem of sudden hazardous chemical leakage accidents as an inverse problem and constructs a source identification model based on the Bayesian framework. Secondly, a new identification method is designed on the basis of particle swarm optimisation (PSO), differential evolution (DE) and the Metropolis-Hastings (M-H) sampling method. Lastly, the designed method, i.e. PSO-DE-MH, is verified by an outdoor experiment analyses in a section of the South-North Water Transfer Project. Results show that the number of iterations, the average absolute error, the average relative error and the average standard deviations of the identification results obtained by PSO-DE-MH are less than those of PSO-DE and DE-MH. Moreover, the relative error and the sampling relative error of the identification results under five different measurement errors (MEs) (σ = 0.01, 0.05, 0.1, 0.15, 0.2) are less than 9.5% and 0.2%, respectively. The designed method is effective even when the standard deviation of the ME increases to 0.2. Therefore, the designed method can effectively and accurately obtain the source information of sudden hazardous chemical leakage accidents. This study provides a new idea and method to solve the difficult problems of emergency management.

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Optimization Design of Groundwater Pollution Monitoring Scheme and Inverse Identification of Pollution Source Parameters Using Bayes’ Theorem

Cited by 14 publications

References 27 publications

Shape Control over the Polymer Molecular Weight Distribution and Influence on Rheological Properties

Shape Control over the Polymer Molecular Weight Distribution and Influence on Rheological Properties

Joint identification of contaminant source characteristics and hydraulic conductivity in a tide-influenced coastal aquifer

Identification of source information for sudden hazardous chemical leakage accidents in surface water on the basis of particle swarm optimisation, differential evolution and Metropolis–Hastings sampling

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