Modelling of Biological Decontamination of a Water Resource in Natural Environment and Related Feedback Strategies

Barbier, S.; Rapaport, Alain; Rousseau, Antoine

doi:10.1007/s10915-016-0178-9

Cited by 6 publications

(5 citation statements)

References 18 publications

(19 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These models represent a reactor in 1 or 2 spatial dimensions with simple fluid dynamics or even assuming that fluid velocity is constant in space to focus on bioreactions [9], [10]. The advantage of reducing complexity is that it allows a more indepth analysis or the consideration of optimization problems [11], [12], [13], [14].…”

Section: Introductionmentioning

confidence: 99%

Simulation of spatially distributed intensive biological systems

Haddon

Alcaraz-González

Hmissi

et al. 2020

2020 European Control Conference (ECC)

View full text Add to dashboard Cite

We introduce a new type of bioreactor model that offers a representation of the spatial features of a pilot scale upflow fixed bed reactor. This model couples fluid dynamics and biological activity in order to obtain the internal gradient of substrate and biomass concentrations. We take advantage of reactor geometry to reduce the model to a single spatial dimension in the section containing the fixed bed but in other sections, we consider a 3D model with Navier-Stokes equations for the fluid dynamics. To represent the biological activity, we use a 2 step model and for the substrates, advectiondiffusion-reaction equations. We only consider the biomasses that are attached in the fixed bed section and to take into account crowding effects, we model their growth with a density dependent function. We show that this model can reproduce the spatial gradient of experimental data and helps to better understand the internal dynamics of the reactor.

show abstract

Section: Introductionmentioning

confidence: 99%

Simulation of spatially distributed intensive biological systems

Haddon

Alcaraz-González

Hmissi

et al. 2020

2020 European Control Conference (ECC)

View full text Add to dashboard Cite

show abstract

“…Double modelling is a term already used to refer to multiscale modelling, for the representation and understanding of the emergence of macroscopic laws (Lesne, 2006). However, double modelling has been very rarely considered with the primary objective of designing control strategies, apart from a few particular studies (Hassam et al, 2015;Barbier et al, 2016). The present work goes further towards the integration of both models, and we show how the double modelling method can be an iterative process, going back and forth between models to compute controls.…”

Section: Double Modeling Methodsmentioning

confidence: 89%

Model based optimization of fertilization with treated wastewater reuse

Haddon,

Rapaport,

Roux

et al. 2023

Advances in Water Resources

View full text Add to dashboard Cite

“…In [4], it has been proved the remarkable property that the expres-sion of the optimal feedback control is preserved when considering one (or more) "dead" areas in the modeling of heterogeneity of the pollutant concentration in water resources. This has led to a validation of this feedback control on realistic simulations of the hydrodynamics of the resource based on the Navier-Stokes equations [1,2], justifying then the derivation of optimal control laws from simple o.d.e. models, without requiring the precise knowledge of the heterogeneity.…”

Section: Introduction and Definitionsmentioning

confidence: 85%

Controlling recirculation rate for minimal-time bioremediation of natural water resources

Rapaport

Riquelme

2019

Automatica

View full text Add to dashboard Cite

We revisit the minimal time problem of in-situ decontamination of large water resources with a bioreactor, considering a recirculation flow rate in the resource as an additional control. This new problem has two manipulated inputs : the flow rate of the treatment in the bioreactor and the recirculation flow rate of the water resource between the pumping and reinjection locations. Although the velocity set of the dynamics is non convex, we show that the optimal control is reached among nonrelaxed controls. The optimal strategy consists in three sequential steps: 1. do not mix and take the flow rate of treatment that maximizes the concentration decay in the resource. 2. mix as much as possible and carry on with the flow rate that maximizes the concentration decay. 3. carry on mixing but do not treat the water. Finally, we show on numerical simulations that a significant gain in processing time can be achieved time when controlling in addition the recirculation flow rate.

show abstract

Modelling of Biological Decontamination of a Water Resource in Natural Environment and Related Feedback Strategies

Cited by 6 publications

References 18 publications

Simulation of spatially distributed intensive biological systems

Simulation of spatially distributed intensive biological systems

Model based optimization of fertilization with treated wastewater reuse

Controlling recirculation rate for minimal-time bioremediation of natural water resources

Contact Info

Product

Resources

About