Méthodologie de validation des données hydrométriques en temps réel dans un réseau d'assainissement urbain

L'objectif du présent travail est l'élaboration d'une méthodologie de validation des données hydrométriques mesurées dans un réseau d'assainissement. L'information validée est utilisée aussi bien en temps réel, pour optimiser les consignes de gestion, qu'en temps différé, pour poser le véritable diagnostic et évaluer, sur une base quotidienne, l'efficacité des systèmes d'assainissement.Le principe de base de la méthodologie proposée repose sur la redondance analytique de l'information provenant d'une part de la mesure directe du débit sur le terrain et d'autre part du débit simulé à partir des variables météorologiques. On compare ainsi d'une part, l'écart entre la valeur prévue par un modèle autorégressif (AR) et la valeur mesurée et d'autre part, l'écart entre la valeur prévue par ce même modèle AR et la valeur simulée par un modèle hydrologique. Parmi les valeurs, mesurée et simulée, celle qui se rapproche le plus de la valeur prévue est retenue. Afin de considérer des modèles non stationnaires et d'éviter le biais d'estimation des paramètres de régression par la méthode standard des moindres carrés, le filtre de Kalman est utilisé pour identifier les paramètres du modèle AR.La méthodologie proposée a été testée avec succès sur un bassin urbain de la municipalité de Verdun. L'hydrogramme mesuré a été bruité artificiellement à la fois par un bruit blanc et par un certain nombre de perturbations de grandes amplitudes et de différentes formes. Le processus de validation a permis de retrouver pratiquement les mesures initiales, non bruitées. Les critères de performance introduits sont largement concluants.We developed an automated methodology for real-time validation of hydrometric data in a sewer network. Our methodology uses real-time validated data to optimise system management and non-real-time data to evaluate day-to-day performance.Two approaches can be used to validate and correct hydrometric data; the choice depends on the number of level gauges present in a system. In single gauge systems, univariate filtering is used to smooth data. For example, frequency filtering systematically eliminates values corresponding to frequencies higher than a predetermined threshold frequency. In systems with several gauging stations-duplex, triplex, or multiplex systems-the multivariate filtering method proposed here can be used to validate data series from each gauge. Material redundancy in duplex or higher order systems makes it possible to detect a deficient gauge, using a decision rule to set aside erroneous readings before averaging accepted values. Part of the underlying principle of this methodology is heavier reliance on gauges that give readings consistent with previous and subsequent validated values in a given series. Thus isolated positive or negative variations within a series are eliminated if corresponding variation values at other gauges are more consistent. To evaluate persistence, a reading is compared to a value predicted by an autoregressive (AR) model calibrated by the previous validated reading.This filtering technique constitutes an intelligent alternative to the frequency filtering method mentioned above. In more practical terms, it compares the deviation of an AR model prediction from a measured value with the deviation of the same AR model prediction from a value estimated by a regressive model at other stations in the network. Among the values measured and estimated by the regressive model, the one nearest the AR model prediction is retained.Our methodology also relies on analytical redundancy generated by direct measurement of flow and hydrological simulation. More precisely, the deviation of the AR model prediction from the measured value is compared with the deviation of the same AR model prediction from a value obtained from a hydrological simulation model. Among measured and simulated values, the one nearest the AR model prediction is retained. To allow consideration of nonstationary models and to avoid the well-known bias of the least squares method, the Kalman filter is used to identify the parameters of the AR model.The methodology we propose employs three models. The first generates analytical redundancy using hydrological modelling. An autoregressive model is then used to predict future runoff rate values. Finally, a voting process model is used to compare measured and simulated values.The proposed methodology was tested on the Verdun sewer system in Quebec with successful results. Two types of artificial disturbance of the measured hydrograph were created: white noise was added to measured values and disturbances of large amplitude and various forms were introduced. The methodology produced the initial values and performance criteria were conclusive. Thus on-site testing confirms that this approach allows completely automated detection and correction of most anomalies. Flood peaks were neither underestimated nor overestimated, and total runoff volumes were retained

Emission spectrum and geometric phase in deformed Jaynes-Cummings model

Abstract The emission spectrum of a qubit (two-level atom) system that interacts with a field in the framework of parity deformations is investigated in this paper. The model consists of a qubit coupled to a single-mode field within the parity deformed Jaynes-Cummings model (PDJCM) based on the λ -analog of the quantum harmonic oscillator algebra. We numerically evaluate the atomic emission spectrum (AES), by considering the influence of the deformed parameter and half-band-width of the spectrometer. Moreover, the dependence of the spectrum peaks on the detuning parameter is discussed. Finally, we study the variation of the geometric phase of the whole system state modelled by the PDJCM in terms of the main physical parameters

Entanglement and photon statistics of two dipole–dipole coupled superconducting qubits with Kerr-like nonlinearities

Abstract The engineering of Kerr and time-dependent coupling interactions is of great attention for treating quantum information in quantum systems and for investigating the collective behavior of large numbers of interacting particles in a cavity-qubit network. In this manuscript, we investigate the time evolution of the entanglement and some nonclassical properties of two superconducting qubits interacting with a single-mode field in the presence of a Kerr-like medium and dipole–dipole interaction without and with time-dependent coupling effect. We show that a slight alteration in the interaction, detuning, and Kerr parameters might cause a change in the entanglement of subsystem states during the evolution. By taking into account the influence of the different physical parameters, we show the statistical distributions produced in the photons of the single mode field through the calculation of the Mandel's parameter. Finally, we find that the time-dependent Mandel's parameter not only provide the statistical properties of the field, but also include the information of quantum entanglement for the subsystem states

Quantum correlations between each qubit in a two-atom system and the environment in terms of interatomic distance

The quantum correlations between a qubit and its environment are described quantitatively in terms of interatomic distance. Specifically, considering a realistic system of two two-level atoms and taking into account the dipole-dipole interaction and collective damping, the quantum entanglement and quantum discord are investigated, during the dissipative process, as a function of the interatomic distance. For atoms that are initially maximally entangled, it turns out that there is a critical distance where each atom is maximally quantum correlated with its environment. Counterintuitively, the approach of the two atoms can maximize the entanglement between each one and the environment and, even at the same distance, minimize the loss of entanglement between the pair.Comment: 5 pages, 3 figure

Identifying effluents from a food processing industry

The agri-food industry in Morocco generates significant volumes of liquid waste, contributing to environmental challenges that directly impact public health. To address this issue, it is crucial to characterize this wastewater comprehensively, enabling the development of suitable treatment strategies to alleviate pollution and potentially facilitate recycling. This study focuses on the identification of effluents from an olive and caper preservation industry, employing physicochemical and bacteriological analyses on raw, decanted, and filtered effluent samples. The findings reveal that the effluent from the olive and caper preservation industry is characterized by high acidity and an exceptionally elevated mineral load. Notably, the application of decantation and filtration methods demonstrates a limited influence, primarily affecting the reduction of suspended solids. Understanding these physicochemical and bacteriological characteristics is pivotal for devising targeted treatment protocols, ensuring effective pollution reduction, and exploring avenues for potential recycling of this agri-food industry wastewater. This research serves as a foundation for informed decision-making in the development of sustainable and efficient wastewater management practices, balancing environmental preservation with industrial needs

Two-point phase correlations of a one-dimensional bosonic Josephson junction

We realize a one-dimensional Josephson junction using quantum degenerate Bose gases in a tunable double well potential on an atom chip. Matter wave interferometry gives direct access to the relative phase field, which reflects the interplay of thermally driven fluctuations and phase locking due to tunneling. The thermal equilibrium state is characterized by probing the full statistical distribution function of the two-point phase correlation. Comparison to a stochastic model allows to measure the coupling strength and temperature and hence a full characterization of the system

Atomistic to Circuit Level Modeling of Defective Doped SWCNTs with Contacts for On-Chip Interconnect Application

Carbon nanotubes (CNTs) due to their high electrical/thermal conductivity, high ampacity, high tolerance to electro-migration [1] and small dimensions make them an ideal candidate for future on-chip interconnects [2]. Fabricating the CNTs, random chirality and some defects are introduced which can degrade the CNT electrical properties [3]. Additionally, the contact resistance between metal and CNT presents additional parasitics that impose restraints on the electron transport. Electrical models of CNT for interconnect application were developed several years ago [4-5]. In this paper, we explored on doped and defective single-wall CNTs (SWCNT (24,0)) including contact resistance as important physical parameters to assess the performance of fabricated SWCNTs realistically for back-end-of-line (BEOL) on-chip interconnects on VLSI circuit application

Milk production of ewes of Timahdite, Sardi and Béni Gull breeds in purebreeding and crossbreeding

La production laitière, durant 8 semaines de lactation, de 144 brebis de races Sardi, Béni Guil et Timahdite luttées par les béliers de leurs races respectives et par ceux des races Île de France, Mérinos Précoce et Suffolk a été estimée par la méthode de pesée avant et après tétée (PAAT) pendant trois années. L'étude a montré que la production laitière est influencée par la race de la brebis mais non par la race du bélier, et que les agneaux issus de pères de races île de France, Suffolk et Sardi transforment mieux le lait que ceux issus des autres races de pères. Il semble impératif de supplémenter les agneaux croisés à partir du 2ème mois d'âge.Milk production of ewes of Timahdite, Sardi and Béni Gull breeds in purebreeding and crossbreedingEight weeks milk production of 144 Sardi, Béni Guil and Timahdite ewes mated to rams of their respective breeds and to rams of Île de France, Mérinos Précoce and Suffolk breeds was estimated during three years by the method of weighting lambs before and after suckling. Milk production was affected by the breed of ewe but not the breed of ram, Lambs sired by île de France, Suffolk and Sardi rams had a better milk efficiency than those produced by rams ofthe other breeds. It seems necessary to supplement crossbred lambs from the age oftwo months