Browsing by Author "Mulas, Michela"

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About the classical and structural controllability and observability of a common class of activated sludge plants
(2022-03) Neto, Otacilio B. L.; Mulas, Michela; Corona, Francesco
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
In this work, the stability, controllability and observability properties of a class of activated sludge plants are analysed. Specifically, the five biological reactors and the secondary settler in the Benchmark Simulation Model no. 1 (BSM1) are studied. For the task, we represented the plant as a dynamical system consisting of 145 state variables, 13 controls, 14 disturbances and 15 outputs and as a complex networks to study its full-state controllability and observability properties from a structural and a classical point of view. By analysing the topology of the network, we show how this class of systems is controllable but not observable in a structural sense, and thus how it is controllable but not observable in a classical sense for almost all possible realisations. We also show how a linearisation commonly used in the literature is neither full-state controllable nor full-state observable in the classical sense. The control and observation efforts are quantified in terms of energy- and centrality-based based metrics.
Cross-domain fault diagnosis through optimal transport for a CSTR process
(2022-08-05) Montesuma, Eduardo Fernandes; Mulas, Michela; Corona, Francesco; Mboula, Fred Maurice Ngole
A4 Artikkeli konferenssijulkaisussa
Fault diagnosis is a key task for developing safer control systems, especially in chemical plants. Nonetheless, acquiring good labeled fault data involves sampling from dangerous system conditions. A possible workaround to this limitation is to use simulation data for training data-driven fault diagnosis systems. However, due to modelling errors or unknown factors, simulation data may differ in distribution from real-world data. This setting is known as cross-domain fault diagnosis (CDFD). We use optimal transport for: (i) exploring how modelling errors relate to the distance between simulation (source) and real-world (target) data distributions, and (ii) matching source and target distributions through the framework of optimal transport for domain adaptation (OTDA), resulting in new training data that follows the target distribution. Comparisons show that OTDA outperforms other CDFD methods.
Development of an Extended ASM3 Model for Predicting the Nitrous Oxide Emissions in a Full-Scale Wastewater Treatment Plant
(2018-05-15) Blomberg, Kati; Kosse, Pascal; Mikola, Anna; Kuokkanen, Anna; Fred, Tommi; Heinonen, Mari; Mulas, Michela; Lübken, Manfred; Wichern, Marc; Vahala, Riku
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
An Activated Sludge Model #3 (ASM3) based, pseudomechanistic model describing nitrous oxide (N2O) production was created in this study to provide more insight into the dynamics of N2O production, consumption, and emissions at a full-scale wastewater treatment plant (WWTP). N2O emissions at the studied WWTP are monitored throughout the plant with a Fourier transform infrared analyzer, while the developed model encountered N2O production in the biological reactors via both ammonia oxidizing bacteria (AOB) nitrification and heterotrophic denitrifiers. Additionally, the stripping of N2O was included by applying a K(L)a-based approach that has not been widely used before. The objective was to extend the existing ASM3-based model of the plant and assess how well the full-scale emissions could be predicted with the selected model. The validity and applicability of the model were tested by comparing the simulation results with the comprehensive online data. The results show that the ASM3-based model can be successfully extended and applied to modeling N2O production and emissions at a full-scale WWTP. These results demonstrate that the biological reactor can explain most of the N2O emissions at the plant, but a significant proportion of the liquid-phase N2O is further transferred during the process.
Evidence of waste management impacting severe diarrhea prevalence more than WASH : An exhaustive analysis with Brazilian municipal-level data
(2023-12-01) Juvakoski, Anni; Rantanen, Henrik; Mulas, Michela; Corona, Francesco; Vahala, Riku; Varis, Olli; Mellin, Ilkka
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Adequate housing protects from diarrhea, which is a substantial health concern in low- and middle-income countries. The purpose of this study was to quantify the relationship between severe diarrhea and housing features at the municipal level to help in public health planning. Regression analyses were performed on annual (2000–2012) datasets on Brazilian municipalities (5570) in six household feature categories (e.g., waste management) and four severe diarrhea outcomes (e.g., diarrhea deaths of under-5 children). Household data were not available elsewhere of this magnitude and granularity, highlighting the scientific value-add of this study. Municipalities were clustered prior to regression analysis because of data heterogeneity. The compositional household feature data were also subjected to principal component analysis to diminish feature variable multicollinearity. The highest explanatory power was found for diarrhea deaths of under-5 children (R2 = 10–22 %), while those in the over-5 population were the least best explained (R2 = 0.3–7 %). Household features predicted diarrhea outcomes more accurately in the “advanced” housing municipality cluster (R2 = 16–22 %) than in the “mid-level” (R2 = 7–20 %) and “basic” (R2 = 6–12 %) ones (over-5 diarrhea deaths excluded). Under-5 children's diarrhea death prevalence was three times higher in the “basic” cluster than in the “advanced” cluster. Importantly, the impact of waste management was overall the largest of all household features, even larger than those of WASH, i.e., water supply, sanitation, and household drinking water treatment. This is surprising in the context of existing literature because WASH is generally regarded as the most important household factor affecting gastrointestinal health. In conclusion, public health interventions could benefit from customizing interventions for diarrhea outcomes, municipality types, and household features. Waste management's identified stronger association with diarrhea compared to WASH may have important implications beyond the water field and Brazil.
A model-based framework for controlling activated sludge plants
(2024-05-15) Neto, Otacílio B.L.; Mulas, Michela; Corona, Francesco
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
This work presents a general framework for the advanced control of a common class of activated sludge plants (ASPs). Based on a dynamic model of the process and plant sensors and actuators, we design and configure a highly customisable Output Model-Predictive Controller (Output MPC) for the flexible operation of ASPs as water resource recovery facilities. The controller consists of a i) Moving-Horizon Estimator for determining the state of the process, from plant measurements, and ii) a Model-Predictive Controller for determining the optimal actions to attain high-level operational goals. The Output MPC can be configured to satisfy the technological limits of the plant equipment, as well as operational desiderata defined by plant personnel. We consider exemplary problems and show that the framework is able to control ASPs for tasks of practical relevance, ranging from wastewater treatment subject to normative limits, to the production of an effluent with varying nitrogen content, and energy recovery.
Modelling solution for estimating aeration energy of wastewater treatment plants
(2021-12-15) Poyry, Lauri; Ukkonen, Petri; Mulas, Michela; Mikola, Anna
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Energy costs in the wastewater industry are increasing due to increasing trends in electricity rates and more stringent requirements for effluent quality. Wastewater aeration process is typically the largest energy consumer of the treatment plant and the optimization of the aeration process can offer significant savings for the wastewater treatment plants (WWTPs). Utilization of dynamic models can offer optimization solutions for improving the energy efficiency and process performance. In this work a simplified modelling approach emphasizing the control valves and the blowers is tested by developing aeration system models for two Finnish WWTPs. The developed model requires calibration of only a single parameter and the results from the simulations showed that reasonable estimations of the aeration systems energy demand could be made with a limited knowledge on the details of the physical system. The promising results highlight the strong influence of the control valve positioning to the whole system and indicate that airflow distribution along the system could be estimated simply from the positioning of the valves. The presented modelling approach allows the comparison between different blower and control valve alternatives during operation and for the process upgrades and offers prospect for improving the aeration operation control strategies.
Network representation and analysis of a large-scale wastewater treatment plant
(2019) Corona, Francesco; Mulas, Michela; Mikola, Anna; Kuokkanen, Anna; Heinonen, Mari; Vahala, Riku
A4 Artikkeli konferenssijulkaisussa
We mapped a large-scale wastewater treatment plant onto a complex network and we investigated how the structural properties of the graph evolve in time as the facility is operated. The Viikinmaki plant is mapped onto a dependence network in which the nodes are online process measurements and interconnectivity between nodes encodes pairwise correlations between the corresponding time series, as estimated over moving-windows. In this initial study, the construction of a graph of Viikinmaki is presented and results are discussed with the goal of understanding its usability as model for process interactions and encoder of latent structures. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
On the observability of activated sludge plants
(2021-04-14) Bezerra Leite Neto, Otacilio; Mulas, Michela; Corona, Francesco
A4 Artikkeli konferenssijulkaisussa
In this work, the full-state observability properties of a class of biological wastewater treatment plants are analysed. Specifically, the five biological reactors and the secondary settler in the Benchmark Simulation Model no. 1 are studied. For the task, we represented the activated sludge plant as a dynamical system consisting of 145 states, 8 controls, 14 disturbances and 12 outputs and as a complex network to study its observability properties from a structural and a classical point of view. By analysing the topology of the network, we show how the system is not observable in the structural sense and thus how it is also not observable in the classical sense for all possible realisations of its parameters. As this is also true for a linearisation commonly used in the literature, we analysed a reduced-order system that, based on such linearisation, does not consider the state variables corresponding to dissolved oxygen and alkalinity in the upper-layers of the settler. We show how this system configuration is only observable in a structural sense.
Online optimal estimation and control for a common class of activated sludge plants
(2022-08-05) Neto, Otacílio B.L.; Mulas, Michela; Corona, Francesco
A4 Artikkeli konferenssijulkaisussa
In this work, we design an output predictive controller that operates a common class of activated sludge plants. The controller solves a state-feedback model predictive control problem in which the process state and disturbances are determined by a moving horizon estimator. We illustrate the behaviour of the controller when operating the plant to produce an effluent water of varying nitrogen content. The close tracking of the effluent profiles is enforced by stabilizing the system around optimal steady-state points that satisfy the output reference trajectories. Considering the generality of the formulation, the predictive controller can be configured to operate this class of activated sludge plants to achieve alternative objectives.
Predictive control of activated sludge plants to supply nitrogen for optimal crop growth
(2021-09-08) Bezerra Leite Neto, Otacilio; Haddon, Antoine; Aichouche, Farouk; Harmand, Jerome; Mulas, Michela; Corona, Francesco
A4 Artikkeli konferenssijulkaisussa
We report the preliminary results of a feasibility study in which we investigate the possibility to operate a common class of activated sludge plants to produce effluent wastewater of varying quality for crop irrigation. Firstly, a nitrogen reference trajectory is computed as solution to a higher-level optimal control problem that aims at maximizing plant biomass in a crop growth system. We then study how to control the treatment plant with a zero-offset predictive control strategy designed to operate the treatment process to supply nitrogen according to this optimal planning for crop growth. We show how an ad hoc tuning of the predictive controller allows to define alternative policies that favour the manipulation of different forms of nitrogen in the treatment plant. We show that the designed controllers are only partially capable to operate the treatment plant to meet the nitrogen demand, when subjected to typical municipal wastewater influent conditions. However, zero-offset can be achieved under constant influent conditions. We analyse the performance of the controller in terms of tracking accuracy and operational energy.
A study on Supercritical Water Gasification of black liquor conducted in Stainless Steel and Nickel-Chromium-Molybdenum reactors.
(2016-02-09) De Blasio, Cataldo; Lucca, Gaetano; Özdenkci, Karhan; Mulas, Michela; Lundqvist, Kurt; Koskinen, Jukka; Santarelli, Massimo; Westerlund, Tapio; Järvinen, Mika
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä