132 research outputs found

    GMUSTA method for numerical simulation of dam break flow on mobile bed

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    River hydrodynamicsUnsteady open channel flow and dam brea

    Modeling dam break granular flows

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    River morphodynamics and sediment transportMechanics of sediment transpor

    Greedy algorithms for sensor location in sewer systems

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    Wastewater quality monitoring is receiving growing interest with the necessity of developing new strategies for controlling accidental and intentional illicit intrusions. In designing a monitoring network, a crucial aspect is represented by the sensors’ location. In this study, a methodology for the optimal placement of wastewater monitoring sensors in sewer systems is presented. The sensor location is formulated as an optimization problem solved using greedy algorithms (GRs). The StormWater Management Model (SWMM) was used to perform hydraulic and water-quality simulations. Six different procedures characterized by different fitness functions are presented and compared. The performances of the procedures are tested on a real sewer system, demonstrating the suitability of GRs for the sensor-placement problem. The results show a robustness of the methodology with respect to the detection concentration parameter, and they suggest that procedures with multiple objectives into a single fitness function give better results. A further comparison is performed using previously developed multi-objective procedures with multiple fitness functions solved using a genetic algorithm (GA), indicating better performances of the GR. The existing monitoring network, realized without the application of any sensor design, is always suboptimal

    two dimensional two phase depth integrated model for transients over mobile bed

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    AbstractFast geomorphic transients may involve complex scenarios of sediment transport, occurring near the bottom as bed load (i.e., saltating, sliding, and rolling) or as suspended load in the upper portion of the flow. The two sediment transport modalities may even coexist or alternate each other during the same event, especially when the shear stress varies considerably. Modeling these processes is therefore a challenging task, for which the usual representation of the flow as a mixture may result in being unsatisfactory. In the present paper, a new two-phase depth-averaged model is presented that accounts for variable sediment concentration in both bed and suspended loads. Distinct phase velocities are considered for bed load, whereas the slip velocity between the two phases is neglected in the suspended load. It is shown that the resulting two-phase model is hyperbolic, and the analytical expression of the eigenvalues is provided. The entrainment/deposition of sediment between the bottom and the bed ..

    exploring the use of operational interventions in water distribution systems to reduce the formation of tthms

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    Abstract Trihalomethanes (TTHMs) are water disinfection by-products whose consumption via drinking water may eventually be harmful for human health, as they could have carcinogenic effects, also for the exposure to them via non-ingestion routes [1] . In the present work the possibility to reduce the vulnerability of the population exposed to TTHMs by the optimal operational interventions in water distribution systems is explored. The proposed approach is formulated as a multi-objective optimization problem with two objective functions, the number of the operations and the maximum TTHMs concentration that occurs at each node in the network during time, both to minimize. The feasible operational actions concern opening/closing valves and hydrants and turning pumping stations for a fixed time. The AMGA 2 optimizer [2] is used herein for solving the problem, coupled with a module coded in C++, where the implementation of the EPANET Programmers Toolkit functions allows to run the hydraulic and water quality simulations and to calculate the objective functions

    Optimal water quality sensor positioning in urban drainage system for illicit intrusion identification

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    In the last decade, the growth of the micro-industry in urban areas has produced an increase in the frequency of xenobiotic polluting discharges in drainage systems. Wastewater treatment plants are usually characterized by low removal efficiencies in respect of such pollutants, which may have an acute or cumulative impact on environmental and public health. To facilitate the early isolation of illicit intrusions, this study aims to develop an approach for positioning water quality sensors based on the Bayesian decision network (BDN). The analysis is focused on soluble conservative pollutants, such as metals. The proposed methodology incorporates several sources of information, including network topology, flows and non-formal ‘grey’ information about the possible locations of contamination sources. The methodology is tested using two sewer systems with increasing complexity: a literature scheme from the Storm Water Management Model (SWMM) manual and a real combined sewer in Italy. In both cases, the approach identifies the optimal sensor location gaining advantage from additional information, which reduces the computational effort needed to obtain the solution. In the real case, the application of the method yielded a better solution with regards to the real position of the implemented sensor network

    Robust optimization of valve management to improve water quality in WDNs under demand uncertainty

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    ABSTRACTWater quality deterioration in water distribution networks can be associated with high water residence time in the network. To this end, some previous studies have proposed optimization procedures for valve management. However, these studies generally come up with operational configurations assuming deterministic user demand patterns that may never occur in reality. In consequence, the proposed solutions may not be effective for improving water quality or do not comply with pressure constraints if different demand patterns are observed. This study proposes a methodology to determine robust configurations of the valves to keep water residence time at acceptable levels regardless of the variability in demand patterns. The methodology is tested on four different distribution systems of varying topology and size. Results show the importance of executing robust – instead of deterministic, optimization to find valve configurations that guarantee the performance of the networks in terms of hydraulics and..

    Multi-objective valve management optimization formulations for water quality enhancement in WDNs.

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    Water distribution networks (WDNs) need to guarantee that water is delivered with adequate quality. This paper compares the performance of 12 multiobjective procedures to limit water quality deterioration in a WDN through the optimal operation of valves. The first objective (ObF1) is to minimize the water age, chosen as a surrogate parameter of quality deterioration, and the second objective (ObF2) is to minimize the number of valve closures. The 12 procedures are derived from the combination of 4 different optimization algorithms and 3 formulations of ObF1, namely, to minimize the maximum, the arithmetic mean, and the demand-weighted mean water age. The optimization algorithms considered are random search (RS), Loop for Optimal Valve Status Configuration (LOC), and a combination of each of these two with the Archive-based Micro Genetic Algorithm. The procedures are tested on two networks of different complexity. Results show how LOC is able to find near-optimal solutions using a fraction of the computational time required by a brute force search. Furthermore, among the ObF1 formulations, the use of the averages (either arithmetic or demand-weighted) gives better results in terms of impact on the population served by a WDN
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