Guerriero, Grazia
(2022)
A MODELLING AND NUMERICAL STUDY OF S-BASED DENITRIFICATION SYSTEMS.
[Tesi di dottorato]
| Item Type: |
Tesi di dottorato
|
| Resource language: |
English |
| Title: |
A MODELLING AND NUMERICAL STUDY OF S-BASED DENITRIFICATION SYSTEMS |
| Creators: |
| Creators | Email |
|---|
| Guerriero, Grazia | grazia.guerriero@unina.it |
|
| Date: |
10 October 2022 |
| Number of Pages: |
153 |
| Institution: |
Università degli Studi di Napoli Federico II |
| Department: |
Matematica e Applicazioni "Renato Caccioppoli" |
| Dottorato: |
Matematica e Applicazioni |
| Ciclo di dottorato: |
34 |
| Coordinatore del Corso di dottorato: |
| nome | email |
|---|
| Moscariello, Gioconda | gioconda.moscariello@unina.it |
|
| Tutor: |
| nome | email |
|---|
| Frunzo, Luigi | UNSPECIFIED |
|
| Date: |
10 October 2022 |
| Number of Pages: |
153 |
| Keywords: |
mathematical model; ordinary differential equations; numerical simulations; sensitivity analysis |
| Settori scientifico-disciplinari del MIUR: |
Area 01 - Scienze matematiche e informatiche > MAT/07 - Fisica matematica |
[error in script]
[error in script]
| Date Deposited: |
12 Oct 2022 11:08 |
| Last Modified: |
28 Feb 2024 11:31 |
| URI: |
http://www.fedoa.unina.it/id/eprint/14359 |
Collection description
This thesis work concerns the mathematical modeling of an innovative biological process for wastewater treatment and its global sensitivity analysis. The aim of the presented mathematical model is to evaluate the effect of production and consumption of soluble microbial products (SMP) and addition of an external carbon source during a sulfur-based autotrophic denitrification. Such compounds during elemental sulfur-based autotrophic denitrification promotes the natural growth of heterotrophic microbial families, which are mainly represented by denitrifiers and sulfate-reducing bacteria.
First, a state of art of the biological process from both experimental and modelling points of view is provided. An overview on autotrophic denitrification driven by elemental sulfur is given as well as a critical analysis on the existing experimental and mathematical studies on the process investigated.
Afterwards, the mathematical model proposed is accurately described in the second chapter, and all mathematical and biological assumptions are detailed. The process was supposed to occur in a sequencing batch reactor to investigate the effects of the COD injection and the time in which this injection occurs on all the processes considered. To model this reactor configuration, a system of nonlinear impulsive differential equations was defined to simulate a system undergoing to instantaneous changes after a continuous period. The equations were solved numerically. The model was tested under ideal conditions where the settling efficiency of the reactor is supposed to be perfect. The model was tested varying different parameters: cycle duration, day of the injection of external COD and quantity of COD added. Albeit the high amount of sludge produced, it appears that SMP are not able to significantly support sulfate reduction. However, when an adequate amount of external carbon source is provided, the system is able to remove high nitrate concentrations without having high sulfate concentrations in the effluent, due to the work of both heterotrophic families involved in the model.
In the following part, the perfect settling efficiency assumption was removed, and the volume of treated influent was increased in each cycle, testing the model under more real conditions. From the simulations performed, it was observed that an efficient settlement is needed to improve the concentration of microorganisms and increase the removal of nitrate and sulfate. In both this case and the previous one, in all simulations performed, even when COD is added, autotrophic denitrifiers remain the predominant microbial family in the reactor.
Finally, a global sensitivity analysis was carried out to find out the parameters more affecting the process. All kinetic parameters involved in the model were first screened using the Morris method. From this initial analysis, it was evident that the removal of nitrogen compounds and the effluent sulfate concentration are mainly sensitive to parameters related to the hydrolysis of elemental sulfur into bioavailable sulfur and maximum growth rate of autotrophic denitrifiers. Then, a second analysis was carried out with machine learning systems, considering only the most sensitive kinetic parameters. The results confirmed those obtained with the previous method and showed that the decay constants of heterotrophic biomasses also turn out to be sensitive parameters. This last study will represent the major tool for the future experimental calibration and validation of the model.
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