| 1. |
- Diehl, Stefan, et al.
(författare)
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Analysis of photobioreactors in series
- 2018
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Ingår i: Mathematical Biosciences. - : ELSEVIER SCIENCE INC. - 0025-5564 .- 1879-3134. ; 306, s. 107-118
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Tidskriftsartikel (refereegranskat)abstract
- A photobioreactor (PBR) contains microalgae which under illumination consume carbon dioxide and substrate dissolved in water, and produce oxygen. The process is used in water recovery resource facilities with a continuous flow of wastewaster through the PBR. With several PBRs in series the reduction of substrate can be improved. This paper contains a thorough analysis of a model of PBRs in series, where each PBR is modelled with a system of three ordinary differential equations for the concentrations of dissolved substrate and biomass (algae), and the internal cell quota of substrate to biomass. Each PBR has a certain volume and irradiation. The absorption rate of substrate into the cells is modelled with Monod kinetics, whereas the biomass growth rate is modelled with Droop kinetics, in which both a minimum and a maximum internal cell quota are assumed. The main result is that the model has a unique stable steady-state solution with algae in all PBRs. Another stable steady-state solution is the wash-out solution with no algae in the system. Other steady-state solutions are combinations of these two with no algae in some of the first PBRs and algae in the rest of the PBRs in the series. Conditions on the illumination, volumetric flow and volumes of the PBRs are given for the respective solution. Numerical solutions illustrate the theoretical results and indicate further properties.
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| 2. |
- Diehl, S., et al.
(författare)
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Steady-state analyses of activated sludge processes with plug-flow reactor
- 2017
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Ingår i: Journal of Environmental Chemical Engineering. - : Elsevier BV. - 2213-3437. ; 5:1, s. 795-809
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Tidskriftsartikel (refereegranskat)abstract
- Activated sludge processes (ASPs) consisting of a plug-flow reactor (PFR) and a settler are analyzed in steady-state operation using a reduced model consisting of one soluble substrate and one particulate biomass component modelling the dominating biological process. Monod biomass growth rate is assumed. Two settler models are studied. One is the commonly used ideal settler, or point settler, which is assumed to never be overloaded and to have unlimited flux capacity. The other recently published steady-state settler model includes hindered and compressive settling, and models a realistic limiting flux capacity. Generally, the steady-state concentration profiles within the PFR and the settler are governed by nonlinear ordinary differential equations. It is shown that the steady-state behaviour of the ASP can, however, be captured by equations without derivatives. New theoretical results are given, such as conditions by means of inequalities on input variables and parameters for a steady-state solution to exist. Another novel finding is that, if the incoming substrate concentration is increased from a low or moderate stationary value and the solids residence time is kept fixed, then this results in a lower effluent concentration in the new steady state. The steady-state equations are solved numerically for different operating conditions. For common parameter values, numerical solutions reveal that an ASP having a PFR, instead of a continuously stirred tank reactor, is far more efficient in reducing the effluent substrate concentration and this can be obtained for much lower recycle ratios, which reduces the pumping energy considerably.
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| 3. |
- Pierong, Rasmus, et al.
(författare)
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Algae Based Wastewater Treatment Model Using The RWQM1
- 2016
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Ingår i: Proc. IWA World Water Congress & Exhibition. - Brisbane, Australia.
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Konferensbidrag (refereegranskat)abstract
- In this paper, we propose a model describing the dynamics of an algae based wastewater treatment process in an activated sludge environment. As the basis for the process modelling, the River Water Quality Model no. 1 (RWQM1) is chosen. In order to evaluate the applicability of the model to an activated sludge process, the proposed model is compared to the Activated Sludge Model no. 1 (ASM1).
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| 4. |
- Samuelsson, Oscar, et al.
(författare)
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Fault signatures and bias progression in dissolved oxygen sensors
- 2018
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Ingår i: Water Science and Technology. - : IWA Publishing. - 0273-1223 .- 1996-9732. ; 78:5, s. 1034-1044
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Tidskriftsartikel (refereegranskat)abstract
- Biofilm fouling is known to impact the data quality of sensors, but little is known about the exact effects. We studied the effects of artificial and real biofilm fouling on dissolved oxygen (DO) sensors in full-scale water resource recovery facilities, and how this can automatically be detected. Biofilm fouling resulted in different drift direction and bias magnitudes for optical (OPT) and electrochemical (MEC) DO sensors. The OPT-sensor was more affected by biofilm fouling compared to the MEC-sensor, especially during summer conditions. A bias of 1 mg/L was detected by analysing the impulse response (IR) of the automatic air cleaning system in the DO sensor. The IR is an effect of a temporal increase in DO concentration during the automatic air cleaning. The IRs received distinct pattern changes that were matched with faults including: biofilm fouling, disturbances in the air supply to the cleaning system, and damaged sensor membrane, which can be used for fault diagnosis. The results highlight the importance of a condition-based sensor maintenance schedule in contrast to fixed cleaning intervals. Further, the results stress the importance of understanding and detecting bias due to biofilm fouling, in order to maintain a robust and resource-efficient process control.
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| 5. |
- Samuelsson, Oscar, et al.
(författare)
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Gaussian process regression for monitoring and fault detection of wastewater treatment processes
- 2017
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Ingår i: Water Science and Technology. - UK : IWA Publishing. - 0273-1223 .- 1996-9732. ; 75:12, s. 2952-2963
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Tidskriftsartikel (refereegranskat)abstract
- Monitoring and fault detection methods are increasingly important to achieve a robust and resource efficient operation of wastewater treatment plants (WWTPs). The purpose of this paper was to evaluate a promising machine learning method, Gaussian process regression (GPR), at WWTP monitoring applications. We evaluated GPR at two WWTP monitoring problems: estimate missing data in a flow rate signal (simulated data), and detect a drift in an ammonium sensor (real data). We showed that GPR with the standard estimation method, maximum likelihood estimation (GPR-MLE), suffered from local optima during estimation of kernel parameters, and did not give satisfactory results in a simulated case study. However, GPR with a state-of-the-art estimation method based on sequential Monte Carlo estimation (GPR-SMC) gave good predictions and did not suffer from local optima. Comparisons with simple standard methods revealed that GPR-SMC performed better than linear interpolation in estimating missing data in a noisy flow rate signal. We conclude that GPR-SMC is both a general and powerful method for monitoring full-scale WWTPs. However, this paper also shows that it does not always pay off to use more sophisticated methods. New methods should be critically compared against simpler methods, which might be good enough for some scenarios.
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| 6. |
- Zambrano, Jesús, et al.
(författare)
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A simple model for algae-bacteria interaction in photo-bioreactors
- 2016
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Ingår i: Algal Research. - : Elsevier. - 2211-9264. ; 19:nov, s. 155-161
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Tidskriftsartikel (refereegranskat)abstract
- This work presents a simple model to describe the consortia of algae-bacteria in a photo-bioreactor. The model is inspired by the Activated Sludge Model (ASM) structure, which includes different process rates and stoichiometric parameters. The model comprises two main biomass populations (algae and bacteria), two dissolved substrates (ammonium and nitrate) and two dissolved gases (oxygen and carbon dioxide) in the reactor. The model was calibrated with data from batch experiments performed in two lab-scale photo-bioreactors. A sensitivity analysis was done to identify the parameters to be considered for the model calibration. Results indicate that the maximum algae and bacteria growth rate, bacteria growth yield and half-saturation constant for carbon were the most sensitive parameters. Moreover, the comparison between the experiments and the model shows good agreement in terms of predicting the ammonium, nitrate and oxygen concentrations in the photo-bioreactor.
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| 7. |
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