323,458 research outputs found
Closure to “Extending the Global-Gradient Algorithm to Solve Pressure-Control Valves”
No full textNot Available - Closure to "Extending the Global-Gradient Algorithm to Solve Pressure-Control Valves" by Gioia Foglianti, Stefano Alvisi, Marco Franchini, and Ezio Todin
Determination of S-allele combination in an italian apple (Malus × domestica Borkh.) germplasm core collection
No full textAn S-RNase-based gametophytic self-incompatibility (GSI) system, a mechanism that forces outbreeding by preventing self-fertilization, characterizes the genus Malus. Knowledge of the self-incompatibility (S) genotypes of apple cultivars is crucial for choosing pollen donors for fruit production and breeding. Even though the S-allele of most commercial apple cultivars has already been identified, limited information is available about the S-allele diversity within local germplasm collections. In this study, 67 S-allele combinations of local apple accessions were identified. The allele S3 was the most common among local apple accessions followed by S1 and S7. The main aim of this study is to provide new information on cultivar compatibility, and these results will be used to set up new parent selection in apple breeding programmes as well as pollinator selection for the commercial orchard
Evaluating water demand shortfalls in segment analysis
No full textIn this paper, two procedures for assessing water demand shortfalls following segment isolation are compared. The first (topological) procedure is based on a simple topological network analysis, and identifies the water demand shortfall as the water demand (under normal operational conditions) relative to the directly and/or indirectly isolated segment(s). The second (hydraulic) procedure is based on a pressure-driven hydraulic simulation of the network after segment isolation. Each of the two procedures was applied to two case studies, and the reliability (expressed in terms of maximum D max and weighted average D¯¯¯¯ water demand shortfall) and economic burden (expressed in terms of number N val or cost C val of installed valves) of the resulting isolation valve system solution were compared. As a whole, the results show that network analysis and redesign are affected by the choice of the global variables (D max or D¯¯¯¯) used to characterize the demand shortfalls in network segments. Analysis of the case studies is followed by a discussion of the rationale behind the choice between the two procedures, which needs to balance accurate demand shortfall characterization with limited computation times, particularly in the multi-objective design stage.E. Creaco, M. Franchini, S. Alvis
Segment identification in water distribution systems
No full textThis paper presents a new method for identifying the segments that are formed after the installation and closure of isolation valves in a water distribution network. This method is able to identify segments also when one-way devices are installed in the network. Thanks to its short computing times, the method enables the analysis of real networks which always comprise a large number of nodes and pipes.
The numerical examples presented in this paper refer to two real water distribution networks. The first network is a part of a provincial network where two one-way devices are present; the second is a complex urban network without one-way devices. The method was first used to analyse the existing situation in both networks, i.e. the set of segments that are formed as a consequence of the present valve system. The method was subsequently used for the problem of the hypothetic redesign of the isolation valve system in the second urban network, i.e. the search for the optimal positions of the isolation valves in the network; in the redesign phase it provided solutions which are more cost-effective than the configuration of isolation valves currently present, the level of water service reliability being the same
A robust approach based on time variable trigger levels for pump control
No full textAn approach for the control of a pumping plant feeding a tank at the inlet of a water distribution system is presented. The approach is aimed at minimizing the energy costs by maximizing pumping during off-peak electricity tariff periods. It is based on trigger levels which are variable during the day according to a prefixed pattern in order to ensure that the water level in the elevated tank is at its minimum and maximum values at the end of the peak and off-peak tariff periods, respectively. The pattern of the trigger levels is defined by solving a multi-objective problem aimed at minimizing the energy costs and the number of pump switches.
The approach was applied to a couple of real cases with a single tank. The approach was compared with other methodologies typically used for pump control, i.e. fixed trigger levels and pump scheduling. The results show for the two particular cases that the proposed approach achieves energy costs that are lower than those obtainable by using fixed trigger levels, and comparable with those obtainable by using pump scheduling. This is based on achieving a similar number of pump switches
Crisp discharge forecasts and grey uncertainty bands using data-driven models
No full textA data-driven artificial neural network (ANN) model and a data-driven evolutionary polynomial regression (EPR) model are here used to set up two real-time crisp discharge forecasting models whose crisp parameters are estimated through the least-square criterion. In order to represent the total uncertainty of each model in performing the forecast, their parameters are then considered as grey numbers. Comparison of the results obtained through the application of the two models to a real case study shows that the crisp models based on ANN and EPR provide similar accuracy for short forecasting lead times; for long forecasting lead times, the performance of the EPR model deteriorates with respect to that of the ANN model. As regards the uncertainty bands produced by the grey formulation of the two data-driven models, it is shown that, in the ANN case, these bands are on average narrower than those obtained by using a standard technique such as the Box-Cox transformation of the errors; in the EPR case, these bands are on average larger. These results therefore suggest that the performance of a grey data-driven model depends on its inner structure and that, for the specific models here considered, the ANN is to be preferred
A Methodology for Pumping Control Based on Time Variable Trigger Levels
No full textAbstractA methodology for the control of a pumping plant feeding a tank is presented. This methodology is aimed at minimizing the energy costs by maximizing pumping during off-peak electricity tariff periods. It is based on trigger levels which are variable during the day according to a prefixed pattern in order to ensure that the water level in the elevated tank is at its minimum and maximum values at the end of the peak and off-peak tariff periods respectively. The pattern of the trigger levels is defined by solving a multi-objective problem aimed at minimizing the energy costs and the number of pump switches.The methodology was applied to the real case of a pumping plant feeding an elevated tank for daily balance which, in turn, feeds a small town in northern Italy; one week of hourly observed total consumptions was considered. This methodology was compared with other two methodologies typically used for pump control, i.e. pump scheduling and fixed trigger levels. The results show that the proposed methodology allows for achieving energy costs that are definitively lower than those obtainable by using fixed trigger levels, and comparable with those obtainable by using pump scheduling, being the number of pump switches the same. On the other hand, unlike the pump scheduling, the methodology presented does not require any water demand forecast and scheduling optimization to be repeated daily, thus representing an effective and efficient tool for pumping plant operation
Stochastic approach for the analysis of demand induced transients in real water distribution systems
No full textA stochastic approach for modelling and analysing the transients due to the users’ water consumptions in a real water distribution system is presented. The analysis is based on field measurements of water consumption at each user and pressure at three nodes, acquired at 1 min and 0.01 s time step, respectively. The hydraulic numerical model used is based on the Method of Characteristics and includes the unsteady friction. Several scenarios of water consumptions at 1-s time step are generated starting from those observed. The corresponding pressure variation scenarios are given by the numerical model and stochastically compared with the measured values. The analysis of the results shows that the approach is capable of stochastically reproduce the dynamic behaviour of the system. Specifically, the generated water consumption scenarios with random manoeuvring times allow properly reproducing the main statistics (mean, variance and minimum and maximum values) of the observed pressures. Finally, the average cumulative distribution of the simulated pressure viably simulates the cumulative distribution of the observed ones from a stochastic point of view
Short-Term Efficacy and Safety of Non-Ablative Laser Treatment Alone or with Estriol or Moisturizers in Postmenopausal Women with Vulvovaginal Atrophy
No full textBackground: Among treatments for vulvo-vaginal atrophy (VVA), there is a new kind of energy-based device, the non-ablative CO2 laser. Aim: This study aimed to assess the efficacy and safety of the non-ablative CO2 laser in menopausal women with VVA as a monotherapy or in association with vaginal estriol or moisturizer. Methods: Seventy-five women with VVA received laser treatment (Laser group), laser plus estriol gel (Laser+E) or laser plus moisturizers (Laser+M). The study protocol consisted of 3 monthly laser sessions (t0, t1, t2) and a gynecological examination at baseline and 1 month after last laser treatment (t3). Objective measures included VHI (Vaginal Health Index) and VuHI (Vulvar Health Index); subjective symptoms of VVA (Dryness, Burning, Itching, Dysuria) evaluated via visual analog scales, sexual function evaluated by FSFI (Female Sexual Function Index), FSDS (Female Sexual Distress Score) and MENQOL (Mopause-specific Quality Of Life). Adverse events and discomfort encountered during the procedure were also assessed. Outcomes: Primary outcomes were the evaluation of VHI and VuHI and secondary outcomes were changes in VVA symptoms (VAS), sexual function (MENQOL, FSFI, FSDS) and discomfort during the procedure. Results: Seventy-five women (25 in Laser, 25 in Laser+E and 25 in Laser+M group) completed the study. At t3, mean VHI, VuHI, dryness, burning and itching VAS scores improved significantly with no differences between the groups. The lubrication domain of FSFI improved significantly only in the Laser+M group, while the pain domain improved significantly in all women with no differences between the groups. FSFI and FSDS overall scores and MENQOL sexual domain improved in all women with no significant difference between the groups. The mean score of the pain during the procedure was low at t0 and did not change throughout the study. Clinical implications: This study extends knowledge concerning the effectiveness of a new non-ablative CO2 laser in post-menopausal women with VVA. Strengths & limitations: This is one of the first studies on this kind of laser and is the first to compare the effectiveness of laser treatment alone or in combination with vaginal estriol or moisturizers. Parameters of VVA and sexual function were evaluated using validated tools. Study limitations include short follow-up time, the limited number of participants and the absence of a sham-controlled group. Conclusion: Non-ablative CO2 laser seems to be an effective treatment for VVA in menopausal women. Our preliminary data shows that it can be effective as monotherapy or with adjuvant treatments. Alvisi S, Lami A, Baldassarre M, et al. Short-Term Efficacy and Safety of Non-Ablative Laser Treatment Alone or with Estriol or Moisturizers in Postmenopausal Women with Vulvovaginal Atrophy. J Sex Med 2022;19:761–770
Data-Driven Control Techniques for Renewable Energy Conversion Systems: Wind Turbine and Hydroelectric Plants
No full textThe interest in the use of renewable energy resources is increasing, especially towards wind and hydro powers, which should be efficiently converted into electric energy via suitable technology tools. To this end, data-driven control techniques represent viable strategies that can be employed for this purpose, due to the features of these nonlinear dynamic processes of working over a wide range of operating conditions, driven by stochastic inputs, excitations and disturbances. Therefore, the paper aims at providing some guidelines on the design and the application of different data-driven control strategies to a wind turbine benchmark and a hydroelectric simulator. They rely on self-tuning PID, fuzzy logic, adaptive and model predictive control methodologies. Some of the considered methods, such as fuzzy and adaptive controllers, were successfully verified on wind turbine systems, and similar advantages may thus derive from their appropriate implementation and application to hydroelectric plants. These issues represent the key features of the work, which provides some details of the implementation of the proposed control strategies to these energy conversion systems. The simulations will highlight that the fuzzy regulators are able to provide good tracking capabilities, which are outperformed by adaptive and model predictive control schemes. The working conditions of the considered processes will be also taken into account in order to highlight the reliability and robustness characteristics of the developed control strategies, especially interesting for remote and relatively inaccessible location of many plants
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