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A decision support system for water management based on convex optimization, is applied to a water system containing river branches connected by weirs. This paper describes a convex approximation approach for the model predictive control of weirs implemented using RTC-Tools 2. Model predictive control using RTC-Tools 2 is implemented for a river that contains 12 river reaches divided by controllable weirs and it is tested in closed loop simulation with a non-linear model. By controlling the weir heights, it is shown how the discharge wave is dispatched in the river without the water levels exceeding the bounds.

A decision support system for water management based on convex optimization, is applied to a water system containing river branches connected by weirs. This paper describes a convex approximation approach for the model predictive control of weirs implemented using RTC-Tools 2. Model predictive control using RTC-Tools 2 is implemented for a river that contains 12 river reaches divided by controllable weirs and it is tested in closed loop simulation with a non-linear model. By controlling the weir heights, it is shown how the discharge wave is dispatched in the river without the water levels exceeding the bounds.

Magnesium alloys with various content of zinc (Zn) and yttrium (Y) were extruded with an extrusion ratio of 1:18 at 350 °C. The alloying elements in these Mg alloys formed a long period stacking ordered (LPSO) phase, which was characterized by transmission electron microscopy (TEM). The microstructure of the alloys was further examined by light microscopy and scanning electron microscopy (SEM), where LSPO phase in all alloys was found to be elongated along the extrusion direction (ED). Mechanical properties of the extruded alloys were investigated during compression loading at various temperatures between room temperature and 350 °C at a constant strain rate of 10-3 s-1. Concurrently with the deformation tests, the acoustic emission (AE) response of the specimens was recorded, in order to reveal the active deformation mechanisms. The conclusions of the AE experiments were proved by the microstructure investigations.

The effect of the orientation of the non-recrystallized grains (non-DRX) and the LPSO phase on plasticity in extruded MgYZn alloy with a bimodal grain structure have been studied in-situ using the combination of synchrotron diffraction and acoustic emission techniques during compression tests. The adaptive sequential k-means (ASK) procedure was applied to analyze the acoustic emission signal. This method can successful separate the signal for each possible deformation systems. Combining both techniques, the deformation mechanisms that take place during the compression tests under different loading directions have been distinguish. Independently of the loading direction, the beginning of the macroscopic plasticity is always controlled by the activation of basal slip system in the DRX grains. However, highly oriented non-DRX grains and LPSO phase have a strong influence over the compressive deformation of the MgYZn alloy. The basal planes in the non-DRX grains were oriented parallel to the extrusion direction (ED). Thus, the activation of the extension twinning was found to be significant only in the ED mode. In the other two loading cases, TD and 45, the activation of non-basal slip systems has been detected. On the other hand, the reinforcing effect of the elongated LPSO phase is the most effective, if the loading axis is aligned with the fiber direction (extrusion direction) since the load transfer mechanism is more effective. In this loading case, the LPSO can be plastically deformed due to kinking. This deformation mode has been isolated by the ASK procedure and characterized by in-situ scanning electron microscopy.

This article regards the development of an analytical redundancy-based approach for detecting and isolating both sensor and actuator faults in flat inland navigation canals. Inland navigation networks are principally used for transport and are composed of many canalized natural rivers and artificial canals characterized by no slope. These canals are strongly affected by resonance phenomena, which can create waves such that the navigation condition might not be guaranteed. It is, therefore, required to ensure dealing with fault-free measured data and actuators. The proposed approach is based on the integrator delay zero model of the flat inland navigation canal. The proposed method is tested by considering the Cuinchy–Fontinettes navigation reach (in the north of France) to detect and isolate the occurrence of faults in the Cuinchy and Fontinettes level sensors and in the Cuinchy gate.

The WZ21 and the WZ72 magnesium alloys containing long period stacking ordered (LPSO) phase extruded with an extrusion ratio of 4:1 at 350C. The microstructure was analyzed by scanning electron microscopy using electron backscattered diffraction. Both alloys exhibit bimodal microstructure of the Mg matrix and elongated LPSO phase along the extrusion direction. Using kernel average misorientation (KAM) maps it was shown that the dynamic recrystallization starts at the grain boundaries of the initial coarse grains. Both alloys exhibit fiber basal texture. The maxima of the basal planes are reduced by increasing content of alloying elements. Uniaxial compression tests along extrusion direction with concurrent acoustic emission measurements were performed to reveal mechanical properties and active deformation mechanisms of the studied alloys. The acoustic emission source mechanisms were identified by statistical analysis of the raw acoustic emission signal.

Magnesium alloys with different content of zinc (Zn) and yttrium (Y) were extruded at an extrusion ratio of 18:1 at 350 °C. The alloying elements in both Mg alloys formed a long period stacking ordered (LPSO) phase, which during the extrusion process was elongated along the extrusion direction (ED). The magnesium matrix has bimodal character composed by fine dynamically recrystallized (DRX-ed) grains and initial coarse grains elongated along ED. Compression tests with concurrent acoustic emission (AE) measurements were performed along ED at 200, 300, and 400 °C. The deformation mechanisms and the mechanical properties at 200 °C are very similar to those obtained at ambient temperatures, i.e. in the alloy with low volume fraction of the LPSO phase (<10%) twinning controls the yielding, while in the alloy with high volume fraction of the LPSO phase (around 35%) dislocation slip and kink formation are dominant. At 300 °C the reinforcing effect of the LPSO phase is reduced and at 400 °C it is not effective anymore.

The interaction of the I-phase with twins during compression has been studied in a Mg-6Zn-1Y (wt.%) alloy using the combination of Synchrotron Radiation Diffraction and Acoustic Emission experiments during compression tests. The I-phase occurs as coarse particles at grain boundaries and nanosized precipitates within magnesium grains. Their interaction with twins depends on their shape and size. The presence of coarse I-phase particles with higher Young Modulus requires an additional stress for the activation of twinning since they induce tensile residual stresses in the magnesium matrix. Besides twinning, the basal and non-basal slip systems are also activated. Non-basal slip is observed after macroscopic yield stress within twins. The fine I-phase precipitates within grains interacts with the dislocations and the twins. In the latter case a back-stress arises, which acts against the compressive applied stress. This back stress hinders the twin growth more than the effect of the coarse particles.

The Mg–Y–Zn alloys with different contents of alloying elements are extruded at an extrusion ratio of 4:1 at 350 °C. The microstructure of the alloys is of an inhomogeneous character showing fine grains produced due to dynamic recrystallization and coarse original grains elongated along the extrusion direction (ED). Moreover, Y and Zn form a long-period stacking-ordered (LPSO) phase whose volume fraction increases with their increasing content in the alloy. All investigated alloys exhibit distinct fiber textures with basal planes oriented parallel to ED. It is seen that increasing content of alloying elements leads to a weaker texture. Compression tests with concurrent acoustic emission (AE) measurements are performed along ED at room temperature and a constant strain rate in order to reveal active deformation mechanisms in the alloys and to relate them to their mechanical properties. The AE response is also discussed with respect to the volume fraction of the LPSO phase.

Twinning in extruded AZ31 alloy with a bimodal grain structure is studied under compression along the extrusion direction. This study has combined in-situ measurements during the compression tests by Synchrotron Radiation Diffraction and Acoustic Emission techniques and the evaluation of the microstructure and texture in post-mortem compression samples deformed at different strains. The microstructure of the alloy is characterized by the coexistence of large areas of fine dynamic recrystallized grains and coarse non-recrystallized grains elongated along extrusion direction. Twinning occurs initially in large elongated grains before the macroscopic yield stress which is controlled by the twinning in equiaxed dynamically recrystallized grains.

Inland navigation networks are composed of several artificial canals that are characterized by no slope. These canals are particularly subject to resonance phenomena, which can create waves such that the navigation condition might not be guaranteed. It is therefore required to ensure dealing with freefault measured data and actuators. In this work, a fault detection and isolation method based on the Integrator Delay Zero model (IDZ) is designed for flat navigation canals. The proposed method is dedicated to the detection and isolation of sensor and actuator faults. Finally, it is tested by considering the Cuinchy-Fontinettes canal located in the north of France.

Navigation canals are used for transport purposes. In order to allow safe navigation the water level should be kept in a certain range around the Normal Navigation Level (NNL). The water level is disturbed by known and unknown inputs, like tributaries, municipal water flows, rain, etc. Some of these inputs can be used to control the water level. If the geometry requires it, canal reaches are connected by locks. The operation of these locks sometimes can disturb the water level, if the difference between the upstream and downstream water level is large. The objective is to minimize the disturbances caused by these lock operations on the water level in order to maintain the NNL. In this work the global management of the canal reach is discussed and an option to maintain the NNL by active control is introduced. Some inputs to the system, such as other confluences or gates on the side of the locks, can be controlled automatically to react to the disturbances caused by the lock operations using model predictive control to maintain the desired water level.

This paper reports the initial steps in the development of WaterLab, an ambitious experimental facility for the testing of new cyber-physical technologies in drinking water distribution networks (DWDN). WaterLab's initial focus is on wireless control networks and on data-based, distributed anomaly detection over wireless sensor networks. The former can be used to control the hydraulic properties of a DWDN, while the latter can be used for in-situ detection and isolation of contamination and hydraulic faults., Comment: 4 pages

Irrigation or drainage canals can be controlled by model predictive control (MPC). Applying MPC with an internal model in the presence of unknown disturbances in some cases can lead to steady state offset. Therefore an additional component should be implemented along with the MPC. A new method eliminating the offset has been developed in this paper for MPC. It is based on combining two basic approaches of MPC. It has been implemented to control water levels in the three-pool UPC laboratory canal and further numerically tested using a test case benchmark proposed by the American Society of Civil Engineers (ASCE). It has been found that the developed offset-free method is able to eliminate the steady-state offset, while taking into account known and unknown disturbances., Peer Reviewed, Postprint (author's final draft)

Centralized model predictive controllers are common in water systems. The control action variable can be the discharge, and the subsystems (canal pools) are modeled separately. This paper focuses on short canal pools where the interactions are stronger between canal pools. Could this procedure be better if gate openings were used as control action variables and the interconnected system were modeled for the controller? Model predictive controllers (MPCs) were developed using the discharge and the gate opening as control action variable and tested experimentally using the laboratory canal of the Technical University of Catalonia. It was found that for centralized MPCs for short canal pools, the use of gate opening as control action variable is more beneficial than discharge. Another additional advantage is that in this way it is possible to put constraints on the gate opening and the change of gate opening, which are important to the limitations of the physical system. (C) 2014 American Society of Civil Engineers., Peer Reviewed, Postprint (author's final draft)

Navigation canals are used for transport purposes. In order to allow safe navigation the water level should be kept in a certain range around the Normal Navigation Level (NNL). The water level is disturbed by known and unknown inputs, like tributaries, municipal water flows, rain, etc. Some of these inputs can be used to control the water level. If the geometry requires it, canal reaches are connected by locks. The operation of these locks sometimes can disturb the water level, if the difference between the upstream and downstream water level is large. The objective is to minimize the disturbances caused by these lock operations on the water level in order to maintain the NNL. In this work the global management of the canal reach is discussed and an option to maintain the NNL by active control is introduced. Some inputs to the system, such as other confluences or gates on the side of the locks, can be controlled automatically to react to the disturbances caused by the lock operations using model predictive control to maintain the desired water level., Postprint (published version)

Automated control of water systems (irrigation canals, navigation canals, rivers etc.) relies on the measured data. The control action is calculated, in case of feedback controller, directly from the on-line measured data. If the measured data is corrupted, the calculated control action will have a different effect than it is desired. Therefore, it is crucial that the feedback controller receives good quality measurement data. On-line fault detection techniques can be applied in order to detect the faulty data and correct it. After the detection and correction of the sensor data, the controller should be able to still maintain the set point of the system. In this paper this principle using the sensor fault masking is applied to model predictive control of open channels. A case study of a reach of the northwest of the inland navigation network of France is presented. Model predictive control and water level sensor masking is applied., Peer Reviewed, Postprint (published version)

In a context of global change, inland navigation transport has gained interest with economic and environmental benefits. The development of this means of conveyance requires the improvement of its management rules to deal with the increase of navigation (schedules and frequency) and the potential impact of global change. To achieve this aim, it is first necessary to have a better knowledge about the dynamics of inland navigation networks and their interaction with the environment. Second, the potential effects of global change have to be anticipated. This article focuses on the modeling of inland navigation reaches. An inland navigation network is a large-scale distributed system composed of several interconnected reaches. These reaches are characterized by non-linearities, time delays, and generally no significant slope. To deal with these particularities, a gray-box model is proposed. It consists in determining the delays according to the physical characteristics of the system. The parameters of the model are identified with measured data. The gray-box model is used to reproduce the dynamics of the Cuinchy–Fontinettes reach located in the north of France., Postprint (author’s final draft)

In recent years, inland navigation networks benefit from the innovation of the instrumentation and SCADA systems. These data acquisition and control systems lead to the improvement of the manage- ment of these networks. Moreover, they allow the implementation of more accurate automatic control to guarantee the navigation requirements. However, sensors and actuators are subject to faults due to the strong effects of the environment, aging, etc. Thus, before implementing automatic control strate- gies that rely on the fault-free mode, it is necessary to design a fault diagnosis scheme. This fault diagnosis scheme has to detect and isolate possible faults in the system to guarantee fault-free data and the efficiency of the automatic control algorithms. Moreover, the proposed supervision scheme could predict future incipient faults that are necessary to perform predictive maintenance of the equipment. In this paper, a general architecture of sensor fault detection and isolation using model-based approaches will be proposed for inland navigation networks. The proposed approach will be particularized for the Cuinchy-Fontinettes reach located in the north of France. The preliminary results show the effectiveness of the proposed fault diagnosis methodologies using a realistic simulator and fault scenarios., In recent years, inland navigation networks bene¿t from the innovation of the instrumentation and SCADA systems. These data acquisition and control systems lead to the improvement of the management of these networks. Moreover, they allow the implementation of more accurate automatic control to guarantee the navigation requirements. However, sensors and actuators are subject to faults due to the strong effects of the environment, aging, etc. Thus, before implementing automatic control strategies that rely on the fault-free mode, it is necessary to design a fault diagnosis scheme. This fault diagnosis scheme has to detect and isolate possible faults in the system to guarantee fault-free data and the efficiency of the automatic control algorithms. Moreover, the proposed supervision scheme could predict future incipient faults that are necessary to perform predictive maintenance of the equipment. In this paper, a general architecture of sensor fault detection and isolation using model-based approaches will be proposed for inland navigation networks. The proposed approach will be particularized for the Cuinchy-Fontinettes reach located in the north of France. The preliminary results show the effectiveness of the proposed fault diagnosis methodologies using a realistic simulator and fault scenarios., Peer Reviewed, Postprint (author's final draft)

Automated control of water systems (irrigation canals, navigation canals, rivers etc.) relies on the measured data. The control action is calculated, in case of feedback controller, directly from the on-line measured data. If the measured data is corrupted, the calculated control action will have a different effect than it is desired. Therefore, it is crucial that the feedback controller receives good quality measurement data. On-line fault detection techniques can be applied in order to detect the faulty data and correct it. After the detection and correction of the sensor data, the controller should be able to still maintain the set point of the system. In this paper this principle using the sensor fault masking is applied to model predictive control of open channels. A case study of a reach of the northwest of the inland navigation network of France is presented. Model predictive control and water level sensor masking is applied.

In recent years, inland navigation networks benefit from the innovation of the instrumentation and SCADA systems. These data acquisition and control systems lead to the improvement of the management of these networks. Moreover, they allow the implementation of more accurate automatic control to guarantee the navigation requirements. However, sensors and actuators are subject to faults due to the strong effects of the environment, aging, etc. Thus, before implementing automatic control strategies that rely on the fault-free mode it is necessary to design a fault diagnosis scheme. This fault diagnosis scheme has to detect and isolate possible faults in the system to guarantee fault-free data and the efficiency of the automatic control algorithms. Moreover, the proposed supervision scheme could predict future incipient faults that are necessary to perform predictive maintenance of the equipment. In this paper, a general architecture of sensor fault detection and isolation using model-based approaches will be proposed for inland navigation networks. It will be particularized for the Cuinchy-Fontinettes reach located in the north of France in order to show the effectiveness of the proposed fault diagnosis scheme. The preliminary results show the effectiveness of the proposed fault diagnosis methodologies using a realistic simulator and fault scenarios.

In recent years, inland navigation networks benefit from the innovation of the instrumentation and SCADA systems. These data acquisition and control systems lead to a reactive asset-management of inland navigation networks. However, sensors and actuators are subject to faults due to the strong effects of the environment, aging, etc. In this paper, a sensor Fault Detection and Isolation (FDI) approach is proposed using an Integrator-Delay-Zero (IDZ) model, interval observers and the dynamic classification algorithm AUDyC. The combined use of these approaches allows the improvement of the sensor fault diagnosis. The proposed approach is introduced through the case study of the Cuinchy-Fontinettes reach in the north of France.

Saving water is an economic and ecological need. One way to save water is to reduce losses in irrigation networks by canal automation. The goal of canal automation is to make the right amount of water to at arrive in the right time. In order to achieve this goal, one of the ways is controlling the gates in the irrigation network by some control algorithm. In this work the control of a specific type of canal pools is studied: short and flat pools that are prone to resonance. The downstream water level control of this type of canals is investigated using the example of the 3-reach laboratory canal of the Technical University of Catalonia. Numerical and experimental studies are carried out to investigate the following: the choice of models for predictive control, the possibility to achieve offset-free control while using gravity offtakes and the best choice of control action variables. The objective of this work is to develop a well performing centralized model predictive controller (MPC) for the laboratory canal that is able to handle known and unknown setpoint changes and disturbances, and also to draw further conclusions about controller design for this type of canals. A recently developed model for resonant canals, the Integrator Resonance, is implemented and successfully tested experimentally for the first time. A new method to achieve offset free control for model predictive control is developed and tested numerically and experimentally. A choice of control variables are tested: As opposed to the discharge which is generally used as the control action variable, a state space model is formulated by using the gate opening as control variable without the need of water level measurement downstream of the gates. The results are summarized and conclusions are presented for control of short and flat canals that are prone to resonance., Postprint (published version)

Automated control of water systems (irrigation canals, navigation canals, rivers etc.) relies on the measured data. The control action is calculated, in case of feedback controller, directly from the on-line measured data. If the measured data is corrupted, the calculated control action will have a different effect than it is desired. Therefore, it is crucial that the feedback controller receives good quality measurement data. On-line fault detection techniques can be applied in order to detect the faulty data and correct it. After the detection and correction of the sensor data, the controller should be able to still maintain the set point of the system. In this paper this principle using the sensor fault masking is applied to model predictive control of open channels. A case study of a reach of the northwest of the inland navigation network of France is presented. Model predictive control and water level sensor masking is applied., Peer Reviewed, Postprint (published version)