This paper presents some developments in the optimization effectiveness for the dynamic design of water distribution networks (WDNs), tackled employing multi-objective genetic algorithms. Unlike the ...traditional single-phase design, the dynamic multi-phase design operates on planning WDN upgrades on short time intervals, also called phases or stages, while fitting them into a long-term planning horizon, thus requiring bespoke research efforts for the improvement of the optimization effectiveness. A modified version of dynamic NSGA-II optimization is introduced here, including: no penalty on the objective functions for infeasible solutions, adoption of engineering judgments in the construction of optimization individuals, restricting the number of parallel pipes at each site. This results in the improvement of convergence speed and solution quality in two case studies with different complexities.
Abstract
Water distribution networks (WDNs) with other infrastructures constitute a complex and interdependent multi-utility system. Considering interdependencies between WDNs and other urban ...infrastructures, this work proposes WDN intervention planning using a dynamic multi-utility approach to tackle the challenges of pressure deficits and cascading failures by the decoupling of different infrastructure systems. For this purpose, the study develops reliability indices representing the hydraulic and decoupled statuses of WDNs with neighbor infrastructures; the hydraulic reliability represents the robustness of the network against the water pressure deficit, and decoupling reliability represents the extent to which WDN elements are decoupled from other assets elements. A multi-objective optimization algorithm is employed to develop rehabilitation strategies by introducing three approaches for WDN upgrade following a phased design and construction method. Evaluating intervention plans based on construction cost, reliability and cascade effects shows that, under budget limitation conditions, decoupling a WDN could significantly save the cascade cost such that 1% improvement in the decoupling reliability brings about 157.42 billion Rials cascade cost saving to asset managers. On the other hand, the decoupled network is weak against hydraulic reliability, which could make it by far less resilient network than the coupled network with around 75% hydraulic reliability difference.
Climate change increasingly is affecting every aspect of human life on the earth. Many regional climate models (RCMs) have so far been developed to carefully assess this important phenomenon on ...specific regions. In this study, ten RCMs captured from the European Coordinated Downscaling Experiment (EURO CORDEX) platform are evaluated on the river Chiese catchment located in the northeast of Italy. The models’ ensembles are assessed in terms of the uncertainty and error calculated through different statistical and error indices. The uncertainties are investigated in terms of signal (increase, decrease, or neutral changes in the variables) and value uncertainties. Together with the spatial analysis of the data over the catchment, the weighted averaged values are used for the models’ evaluations and data projections. Using weighted catchment variables, climate change impacts are assessed on 10 different hydro-climatological variables showing the changes in the temperature, precipitation, rainfall events’ features, and the hydrological variables of the Chiese catchment between historical (1991–2000) and future (2071–2080) decades under RCP (Representative Concentration Path for increasing greenhouse gas emissions) scenario 4.5. The results show that, even though the multi-model ensemble mean (MMEM) could cover the outputs’ uncertainty of the models, it increases the error of the outputs. On the other hand, the RCM with the least error could cause high signal and value uncertainties for the results. Hence, different multi-model subsets of ensembles (MMEM-s) of 10 RCMs are obtained through a proposed algorithm for different impact models’ calculations and projections, making tradeoffs between two important shortcomings of model outputs, which are error and uncertainty. The single model (SM) and multi-model (MM) outputs imply that catchment warming is obvious in all cases and, therefore, evapotranspiration will be intensified in the future where there are about 1.28% and 6% value uncertainties for monthly temperature increase and the decadal relative balance of evapotranspiration, respectively. While rainfall events feature higher intensity and shorter duration in the SM, there are no significant differences for the mentioned features in the MM, showing high signal uncertainties in this regard. The unchanged catchment rainfall events’ depth can be observed in two SM and MM approaches, implying good signal certainty for the depth feature trend; there is still high uncertainty about the depth values. As a result of climate change, the percolation component change is negligible, with low signal and value uncertainties, while decadal evapotranspiration and discharge uncertainties show the same signal and value. While extreme events and their anomalous outcomes direct the uncertainties in rainfall events’ features’ values towards zero, they remain critical for yearly maximum catchment discharge in 2071–2080 as the highest value uncertainty is observed for this variable.
Abstract
One of the main drawbacks of using evolutionary algorithms for the multi-objective design of water distribution networks (WDNs) is their computational inefficiency, particularly for ...large-scale problems. Recently, graph theory-based approaches (GTAs) have gained attention as they can help with the optimal WDN design (i.e., determining optimal diameters). This study aims to extend a GTA to further improve the quality of design solutions. The GTA design is based on a customized metric called ‘demand edge betweenness centrality’, which spatially distributes nodal demands through the weighted edges of a WDN graph and provides an estimation of water flows. Assigned edge weights can be constant (i.e., static) or modified iteratively (i.e., dynamic) during the design process, leading to different flow estimations and alternative design options. Three hydraulic-inspired dynamic weights are developed in this study to better reproduce hydraulic behavior and, consequently, find better solutions. Additionally, this work proposes a framework for the optimal design of multi-source WDNs and provides guidelines for obtaining near-optimal solutions in such networks. A comparative study between GTAs and evolutionary optimizations confirms the efficiency of the improved GTA in providing optimal/near-optimal solutions, especially for large WDNs, with a runtime reduction of up to seven orders of magnitude.
Abstract
The resilience of water distribution networks (WDNs) should be proactively evaluated to reduce the potential impacts of disruptive events. This study proposes a novel hydraulically-inspired ...complex network approach (HCNA) to assess and enhance WDN resilience in the case of single-pipe failure. Unlike conventional hydraulic-based models, HCNA requires no hydraulic simulations for resilience analysis. Instead, it quantifies the failure consequences of edges (pipes) on the WDN graph by incorporating topological attributes with flow redistribution triggered by failures. This HCNA procedure leads to the identification of critical edges (pipes), as well as impacted ones, representing edges more susceptible to the failure of others. The impacted edges are then systematically resized by integrating HCNA with a graph-based design approach, obtaining a wide range of resilience enhancement solutions. A comparative study between HCNA and a hydraulic-based model for three WDNs confirms HCNA's effectiveness in identifying the most critical pipes in various network sizes. Furthermore, HCNA provides comparable resilience enhancement solutions with a hydraulic-based evolutionary optimization but with significantly lower computational effort (1,400 times faster). Thus, it can efficiently be used for resilience enhancement of large-scale WDNs, where the application of conventional optimizations is limited due to the intensive computational workload.
OBJECTIVE: Schizophrenia, commonly develops in adolescents and young adults and Paranoid is the most common type. Newly progress in molecular biology and imaging techniques has enabled new insight ...into schizophrenia research. Recent research reveals the key roles of D3, D4 and D5 dopamine receptor in presenting types of schizophrenia, particularly the paranoid. The purpose of this study was to the evaluation of D5 along with D3 dopamine receptor expression in schizophrenia patients.
METHOD: 96 venous blood from 51 drug-free, 15 naive and 30 healthy were prepared and their expression level of mRNA for D3 and D5 dopamine receptor were investigated based on β-actin expression as housekeeping gene.
RESULTS: D3 expressed about 33.3%, 73.3% and 27.4% in healthy, naive and drug-free patients respectively, but D5 just expressed in 86.6% of healthy samples and none of the patients were expressed D5.
CONCLUSION: Expression frequency of D3 and D5 dopamine receptor reveals significant differences between naïve and drug-free patient against healthy individuals. D3 and D5, both have the possible potential for almost more accurate diagnosis usage, and the severity of the disease could be related to the D5 dopamine receptor.
This paper presents a multistep approach for the rehabilitation of the deteriorated and intermittently operated water distribution network (WDN) proposed by the organizers of the joint WDSA CCWI 2022 ...Conference as the case study for the battle. In the rehabilitation, various interventions are considered with the final objective to improve the operation of the WDN in terms of hours of service to users and total volume supplied to meet their demands, including pipe and device (pump/valve) replacements, leak repairs, and extended period optimization of device settings. The multistep approach is proposed to tame the extremely large space of decision variables and includes the following steps: (1) subdivision of the WDN into main chain and district metered areas (DMAs), rehabilitation of (2) the main chain and (3) the DMAs while looking at the final year of the rehabilitation, (4) sequencing of the interventions, and (5) optimization of device settings. Compared to other methodologies in the literature, the main novelty and merit of the present approach consist of the way the rehabilitation interventions are selected, i.e., by using engineering judgment and by maximizing the flow capacity of the main chain and the global resilience–failure index in the DMAs.
AbstractThis study introduces a decision support system for upgrading aged water distribution mains. The network hydraulics is simulated and evaluated by a hybrid reliability measure, and the design ...period is divided into multiple upgrade phases. In each phase, a multiobjective optimization problem is solved to derive the trade-off between construction cost and network performance reliability. Subject to budget constraints, upgrade decisions, including those related to pipe replacement and laying parallel pipe, are made, leading to a more robust hydraulic performance of the network over time. To implement multiphase upgrade programs, three approaches are introduced, varying in their assumptions regarding design and construction methods. These approaches are applied to a real case study, and results indicate that the dynamic phase-by-phase design and construction approach is computationally efficient and cost-effective while satisfying physical and performance constraints over the simulation time horizon.
Abstract
Water Distribution Networks (WDNs) along with other utilities are among the most important assets in every industrialized society. The rehabilitation and upgrade of WDNs refer to a very ...complex and multi-criteria problem which needs a comprehensive decision support system providing optimal renewal plans for the asset managers. There is a multitude of real-world problems faced with such activities. In this regard, this study aims to propose a novel method to cope with three practical challenges in WDNs rehabilitation activities including 1-budget limitation, 2- hydraulic deficiency and 3- correlation of WDNs with other infrastructures bringing the risk of cascading failures to a multiplex network. This results in a multi-objective optimization problem with three objectives which are cost, hydraulic and decoupled reliabilities. The problem is solved dynamically with the contribution of a nature inspired optimization algorithm, the Non-Dominated Sorting Genetic Algorithm (NSGA-II). The method is applied to a deteriorated water pipe network, and the results are compared with the ones obtained only by the consideration of two objectives, costs and hydraulic reliability showing how much the objectives are conflicted with each other.
•A novel graph-theory-based model for missing data reconstruction is developed.•The model uses topological metrics and hydraulic features for reconstructing data.•Missing diameter information can be ...retrieved systematically and automatically.•The new model is computationally efficient, especially for large networks.
Dealing with missing data is a critical challenge in analyzing water distribution networks (WDNs). These unknown data are often associated with the physical characteristics of pipes, like diameter, which are the foundations of several modeling endeavors. This study develops a fully automated model to reconstruct missing diameter information in WDNs within the complex network theory (CNT) framework. The newly developed model employs customized graph measures to systematically retrieve missing diameters based on the topological (e.g., connectivity) and hydraulic (e.g., flow) features of edges with available information. The proposed model is validated by testing it on three real-world WDNs located in Iran and Austria, where data gaps are created by randomly and progressively eliminating the pipe diameter information. Subsequently, the model's accuracy is assessed by comparing the diameter, pressure, and hydraulic-based resilience of the reconstructed WDNs with those of the complete dataset. The results indicate that the proposed reconstruction model can successfully retrieve missing information up to 90% of the data gap. In addition, the model is highly computationally efficient and can quickly reconstruct thousands of missing diameters. Our novel approach can benefit water utilities that frequently encounter incomplete data in their models and require missing data retrieval from large-scale WDNs.
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