Réduction du modèle ASM 1 pour la commande optimale des petites stations d'épuration à boues activées

L'adoption par l'Union Européenne de normes de rejets plus contraignantes implique une meilleure gestion des stations d'épuration. L'utilisation de modèles de simulation dynamique dans des schémas de commande en boucle fermée constitue une alternative intéressante pour répondre à ce problème.Sur la base du modèle ASM 1, un modèle réduit est ici élaboré pour le procédé à boues activées en aération séquentielle, en vue de la commande optimale du système d'aération. Les simplifications considérées sont de deux types : (i) les dynamiques lentes du système sont identifiées au moyen d'une méthode d'homotopie, puis éliminées du modèle ; (ii) des simplifications plus heuristiques consistant à prendre en compte un composé organique unique et à éliminer la concentration des composés organiques azotés sont ensuite appliquées. Elles conduisent à un modèle simplifié de 5 variables. L'application d'une procédure d'identification paramétrique permet alors de démontrer que le comportement dynamique du modèle simplifié est en bonne adéquation avec celui du modèle ASM 1 sur un horizon de prédiction de plusieurs heures, même lorsque les concentrations de l'influent ne sont pas connues. Il est également vérifié que le modèle proposé est observable et structurellement identifiable, sous des conditions d'aérobiose et d'anoxie, à partir des mesures en ligne des concentrations en oxygène dissous, ammoniaque et nitrate.Le modèle simplifié développé présente ainsi toutes les propriétés requises pour une future utilisation au sein de schémas de commande en boucle fermée, en vue de la commande optimale des petites stations d'épuration à boues activées.In order to meet the stricter wastewater effluent guidelines adopted by the European Union, wastewater treatment plants require better management strategies. Wastewater treatment process models have become a major tool to design closed-loop control schemes. However, the dynamic models that are currently used in the simulation of activated sludge treatment plants (ASM 1, ASM 2 and, more recently, ASM 3 models) are highly dimensional and are not appropriate for on-line implementation (e.g., for model predictive control or optimal control). It is therefore important to develop reduced models that could be used for this purpose.A reduced model was developed to describe the behaviour of alternating activated sludge treatment plants, with the aim of applying it to the optimal control of an aeration system. The reduction scheme was based on appropriate simplifications to the ASM 1 model (which is more appropriate for open-loop control). The objective was to verify if accurate predictions could be made time periods of several hours (about 8 h).The present results are related to an existing small-size wastewater treatment plant. This plant was designed for 15,000 population-equivalents (p.e.) and consists of a primary treatment stage (screening, grit removal, primary sedimentation), followed by a secondary treatment stage (biological treatment). The latter consists of a single aeration tank of about 2,050 m3 equipped with 3 turbines which are operated cyclically to create alternating aerobic and anoxic conditions. Ammonia is converted into nitrate during air-on periods (nitrification step) and nitrate is subsequently removed during air-off periods (denitrification step). It is important to note that a dynamic model, based on the ASM 1 model and calibrated from a set of input/output measurements over a one-day period (Chachuat, 2001), was used here as a reference to perform model reduction. The following two-level simplification procedure was applied :· A homotopy method was first used to establish relationships between the states and the dynamics of the system, via an eigenvalue decomposition. The components that are associated with the slowest dynamics are then assumed constant to reduce the state space dimension. Heterotrophic (XB,H) and autotrophic (XB,A) biomass and inert particulate organic compounds (XI) were detected as the slow state variables. It was found that the short-term predictions of the dynamic model were not affected by assuming that XI, XB,H and XB,A concentrations were constant. Eliminating these 3 state variables, along with the concentrations of soluble inert organic compounds (SI), resulted in a 7-dimensional dynamic model.· However, further simplifications were required to enable the on-line optimisation of the bioreactor aeration profiles with reasonable computational times. These simplifications consisted of taking into account the process specifications in order to reduce the state space dimension to 4 or 5, and were therefore based on more heuristic considerations. Both organic and nitrogenous compounds are under consideration: (i) a single organic compound (denoted as XDCO) is formed by adding soluble and particulate organic compound concentrations, and (ii) the mathematical expression that describes the organic nitrogen hydrolysis process is simplified so that the dynamics with respect to soluble and particulate organic nitrogen are independent.The two previous simplification steps produced a reduced 5-dimensional dynamic model with state variables XDCO, SNO, SNH, SND and SO. It should also be noted that the resulting model involved the parameters YH, iNBM, KS, KNO, KO,H, KNH,A, ηNO,g and ηNO,h that are identical to those defined in the original ASM 1 model by Henze et al. (1987). In addition, 7 specific parameters were defined defined (θ1, θ2, θ3, θ4, θ5, KDCO, KND). These new parameters exhibited rather slow temporal variation, thus agreeing with the general ASM 1 model for short time periods.Afterwards, a two-step procedure was applied to calibrate the model. This procedure first consisted of determining a reduced set of identifiable parameters by the use of both sensitivity and principal component analyses. Note that the inlet concentrations of organic compounds, ammonia nitrogen and soluble organic nitrogen may be considered as additional parameters since they are generally not measured on-line. The selected parameters (θ1, θ2, θ3) and inlet concentrations (XinDCO, SinNH) were then estimated by the application of a local gradient search method (successive quadratic programming, SQP). Comparisons between the dynamic behaviour of both reduced and ASM 1 models show that accurate predictions can be obtained over time periods of several hours (8 h). It was also shown that the reduced model was observable and structurally identifiable under aerobic and anoxic conditions from dissolved oxygen, ammonia and nitrate concentration measurements. These results therefore demonstrate the ability of the reduced model to be embedded into closed-loop control schemes.The conclusions from this work are twofold: (i) The reduced model can be used as a basis to construct an on-line observer to estimate the unmeasured state variables, the unknown (most sensitive) parameters and inlet concentrations; (ii) Non-linear model predictive control (NMPC) schemes can then be implemented to operate the aeration system so that the nitrogen discharge or the energy consumption are minimised (optimal control).The initial results demonstrate that the application of NMPC strategies is likely to give large reductions of nitrogen discharge with respect to usual operating strategies (e.g., oxygen or redox control). Such closed-loop control schemes are particularly efficient in dealing with large influent variations (inlet flow rate, concentration and composition) resulting from both human activities and climatic conditions, and inherent modelling uncertainties. However, an experimental validation of this control strategy on a pilot scale or an industrial scale is required to confirm these results

A Bayesian real-time electric vehicle charging strategy for mitigating renewable energy fluctuations

A novel pricing and scheduling mechanism is proposed here for Plug-in electric vehicles (PEVs) charging/discharging to track and synchronize with a renewable power generation pattern. Moreover, the proposed mechanism can be used in the demand-side management and ancillary service applications, respectively for the peak shaving and frequency regulation responding. We design a fully distributed stochastic optimization mechanism using Bayesian pure strategic repeated game by which the PEVs optimally schedule their demands. We also use a mixed Bayesian-diffusion Kalman filtering strategy for the customers to collaboratively estimate and track the stochastic price and regulation signals for the upcoming scheduling window. In the proposed paper all the characteristics of the PEVs, as well as the uncertainty about their deriving patterns are considered. As our framework converges to an equilibrium even with incomplete information, is agent-based, and the agents share the information only with their optional neighbors, it is scale-free, robust, and secure

Prevalence of Cryptosporidium Infection in Immunocompromised Patients, In South-West of Iran, 2009–10

Background: Cryptosporidium is a protozoan parasite with worldwide distribution. The aim of this study was to estimate the prevalence of Cryptosporidium infection by antigen detection in faeces among immunocompromised patients referred to educational hospitals of Ahvaz City, South-West of Iran, 2009-2010.Methods: Fecal samples from 176 immunocompromised patients were collected and Cryptosporid­ium coproantigen test was performed using ELISA method (DRG kit, Germany). A questionnaire was completed for each case and the results were analyzed using descriptive and Chi-Square tests, by SPSS statistical software (15th version).Results: Our study indicated 5.1% Cryptosporidium infection prevalence in the immunocompro­mised participated population. Furthermore, 4.2 %, 4%, 4.5 % and 9.1% infection rates were identi­fied in children suffered from hematopoietic malignancy, adult cancer patients, renal trans­plant recipients, and HIV+ cases, respectively. There was not significant correlation between the infection and age and gender (P>0.05). Infection was most frequent among HIV+ patients.Conclusion: The present study confirmed the high prevalence of Cryptosporidium antigen in fe­cal samples of immunocompromised patients in the region. As no chemotherapeutic agents have yet proven, especially in immunosuppressed patients, therefore our results highlight the impor­tance of preventive intervention in these groups

The impact of some morphological characteristics on running 200 meters

The knowledge of morphological development and their impact on motor skills in short-distance athletes should be one of the main concerns of athletics coaches, because any scientific research in the field of physical culture and sports is about proving the development and evaluation of anthropological characteristics which are responsible for achieving success in athletics. This paper explores the impact of some anthropometric features on running 200 meters. The aim is to establish the link between the anthropometric and specific characteristics of running 200 meters, as a predictive system of running at 200 meters as a criterion system. The research was conducted by 60 male students aged 17±6months, in the gymnasium "Zenel Hajdini” Gjilan. The measurements were executed during September in the hall of the gymnasium, while the 200, meter runs in the stadium "City stadium "Gjilan. The only condition that was used during the determination of the sample was: that the students are involved in regular physical education classes (and on the day of the measurement be healthy, without the flu, cold or other symptoms).The variables which are applied in this research have been 8 anthropometric variables and 1 motor-specific variables. The results obtained after their processing indicate that the impact of anthropometric variables is higher in running at 200 meters. Short distance running and long-distance running reduces the impact of anthropometric parameters whereas the influence of metabolic factors of energy production is increased. These results were also confirmed using regression analysis, so that groups of predictors of anthropometric characteristics, specific motor skills that statistically significantly influenced each variable of individual criteria. The world records below the 19.20-second limit, in the 200 m, near the 19-meter limit, show not only the high level of sports, but also the strong impact on the growth, especially of strength indicators, speed-strength, explosive force, as main and applied motor skills in sports and athlete’s everyday life

The Vibration effect on the roughness surface of Ck35 steel during the turning operation

Vibrations in the turning process are an important issue of instability in the metal cutting process. This phenomenon is characterized by violent vibrations, loud sounds, wear of the metal cutting tool and poor quality in the final surface

A robust scalable demand-side management based on diffusion-ADMM strategy for smart grid

Demand-side management (DSM) involves a group of programs, initiatives, and technologies designed to encourage consumers to modify their level and pattern of electricity usage. This is performed following methods such as financial incentives and behavioral change through education. While the objective of the DSM is to achieve a balance between energy production and demand, effective and efficient implementation of the program rests within effective use of emerging Internet of things (IoT) concept for online interactions. Here, a novel DSM framework based on diffusion and alternating direction method of multipliers (ADMM) strategies, repeated under a model predictive control (MPC) protocol, is proposed. On the demand side, the customers autonomously and by cooperation with their immediate neighbors estimate the baseline price in real time. Based on the estimated price signal, the customers schedule their energy consumption using the ADMM cost-sharing strategy to minimize their incommodity level. On the supply side, the utility company determines the price parameters based on the customers real-time behavior to make a profit and prevent the infrastructure overload. The proposed mechanism is capable of tracking drifts in the optimal solution resulting from the changes in supply/demand sides. Moreover, it considers all classes of appliances by formulating the DSM problem as a mixed-integer programming (MIP) problem. Numerical examples are provided to show the effectiveness of the proposed framework

CHARACTERIZATION OF HONEY: DETERMINATION OF METAL AND SUGAR CONTENT

In this study, five samples of honey (4 from various beekeepers and 1 from a local supermarket) were analyzed to determine the presence of Pb, Fe, Mn, Al, Cu, Cr, Zn, Cd, As, Ni and Se content using atomic absorption spectrometry. Samples were collected from the following locations: 2 from Skopje, 2 from Kumanovo and 1 from Preshevo, Srbia. HPLC was applied to determine sugars in honey samples. Acid and moisture were also determined. The average values of concentration were from 0.033 to 0.055 mg/kg, 0.610to 2.498 mg/kg, 0.052 to 0.377 mg/kg, 2.133 to 3.474 mg/kg, 0.060 to 1.034 mg/kg, 0.005to 0.019 mg/kg, and 0.067 to 0.085 mg/kg for Pb, Fe, Mn, Al, Cu, Cr, and Zn, respectively. Cadmium was determined in one sample (0.040 mg/kg), while the presence of arsenic, nickel and selenium were not observed. The total amount of reductive sugars was within the standard value of min 60 g/100 g honey. The moisture was from 16.6 to 17.6% (max 20%). The acid content was recorded from 9 to 28mEq/1 kg honey (max 50mEq/1 kg honey). The results were compared with the safety standards established from the Ministry of Agriculture, Forestry and Water Economy. In general, the analyzed parameters are within the standards and honey can serve as good dietary source