Performance optimization of water distribution network using meta-heuristic algorithms from the perspective of leakage control and resiliency factor (case study: Tehran water distribution network, Iran)

In the context of sustainable development and considering water distribution networks (WDNs) as vital infrastructure systems, designing a resilient and efficient network to deliver water demand to consumption nodes while adhering to engineering standards is of utmost importance. This study specifically focused on the complex structure of the north-west Tehran's WDN, encompassing 1124 pipes totaling 92552 m in length, along with four gravity reservoirs and 988 nodes. Genetic Algorithm (GA) and Nonlinear Programming (NLP) were employed as optimization techniques to enhance the WDN by minimizing leakage and improving its resilience. The study involved determining leakage coefficients for nodes using measured data and GA. Subsequently, the WDN was optimized by defining an objective function, constraints, and decision variables using both GA and NLP. The results demonstrated the superiority of GA in terms of pressure reduction, achieving a significant decrease of 23.7%. Additionally, GA outperformed NLP in enhancing the resiliency index, underscoring its effectiveness in optimizing the network's performance and ensuring its robustness against potential disruptions

Multistage Models for Flood Control by Gated Spillway: Application to Karkheh Dam

The paper demonstrates a simulation optimization framework for enhancing the real-time flood control with gated spillways at places where no flood forecasting data are available. A multiobjective modeling scheme is presented for the flood management in a gated spillway in which the operator may specify the priorities on floods based on their different return periods. Two different operation strategies were devised. Both operating strategies employ ten-stage policies, which rely on the reservoir water level as the input data. The second strategy benefits from both the observed reservoir water level and the flood peak. The optimal values of the models’ parameters were obtained using a genetic algorithm. This is a novel approach because none of its policies needs flood forecasting data, thus, making them adaptable to any flood with any return period. To evaluate the performances of the proposed models, the flood control through a gated spillway of the Karkheh reservoir was considered, where flood hydrographs with different return periods were routed through the reservoir

The Sensitivity Analysis of the Drainage Unsteady Equations against the Depth of Drain Placement and Rainfall Time at the Shallow Water-Bearing Layers: A Case Study of Markazi Province, Iran

This research investigated various drainage parameters for unsteady conditions, including depth of installation, reflection coefficient, and depth of water table. For this purpose, Bouwer & Van Schilfgarrd, Dumm, Glover, Hemmad, and Bouwer equations were used. For the distance of computed drainage compared with measured data in central Iran, the results showed that the Bouwer & Van Schilfgaarde equation is better than others. Additionally, the installed depth was obtained 130 cm below the exiting underground, and this depth was applicable more than other depths; 1, 3, and 5-day precipitation were used to determine water table changes. The results illustrated that a 5-day duration had a better effect, which appeared in the existing condition drainage area. The reflection coefficient for the superior equation was also obtained as 0.65, which was very close to the measured data in the area. Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Standard deviation (σ) were used to evaluate the results. MAE, RMSE, and σ were computed as 1.78, 2.02, and 0.02, for the superior equation respectively, and the appropriate distance between the two drains was determined as 51.26 m. The obtained results have a close agreement with other researchers in this regard

The Sensitivity Analysis of the Drainage Unsteady Equations against the Depth of Drain Placement and Rainfall Time at the Shallow Water-Bearing Layers: A Case Study of Markazi Province, Iran

This research investigated various drainage parameters for unsteady conditions, including depth of installation, reflection coefficient, and depth of water table. For this purpose, Bouwer & Van Schilfgarrd, Dumm, Glover, Hemmad, and Bouwer equations were used. For the distance of computed drainage compared with measured data in central Iran, the results showed that the Bouwer & Van Schilfgaarde equation is better than others. Additionally, the installed depth was obtained 130 cm below the exiting underground, and this depth was applicable more than other depths; 1, 3, and 5-day precipitation were used to determine water table changes. The results illustrated that a 5-day duration had a better effect, which appeared in the existing condition drainage area. The reflection coefficient for the superior equation was also obtained as 0.65, which was very close to the measured data in the area. Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Standard deviation (σ) were used to evaluate the results. MAE, RMSE, and σ were computed as 1.78, 2.02, and 0.02, for the superior equation respectively, and the appropriate distance between the two drains was determined as 51.26 m. The obtained results have a close agreement with other researchers in this regard

Investigation into the Effects of Climatic Change on Temperature, Rainfall, and Runoff of the Doroudzan Catchment, Iran, Using the Ensemble Approach of CMIP3 Climate Models

This study investigated the effects of climatic changes on temperature, rainfall, and runoff in the Doroudzan catchment in the northeast of Fars province, Iran. Temperature and rainfall changes in three periods including 2011–2030, 2046–2065, and 2080–2099 were downscaled and studied using 15 Coupled Model Intercomparison Project, Phase 3 (CMIP3) climatic models, under three scenarios of greenhouse gas emissions A2, B1, and A1B, from the database of the LARS-WG model. The difference in the amount of changes in temperature and rainfall in these three periods and the observational amounts under the 15 models indicated the uncertainty of the changes values. To reduce this uncertainty and limit the results to the management and planning of water resources, ensemble approach was considered. For the preparation of the ensemble approach, the parameters from the files of the 15-model scenarios were averaged so that a climatic ensemble model could be obtained for each period. Then, the runoffs of the next three periods, under the second approach and three emission scenarios, were produced using the feedforwad neural network. The results indicated an increase in the average monthly maximum temperature and the minimum temperature in all three periods under the three scenarios. The results also showed a decrease in the rainfall in the early months of the year as well as an increase in the rainfall in the spring in most scenarios. Generally, the average annual rainfall in all these three periods under the climatic ensemble model, and three emission scenarios showed a reduction in the average annual rainfall in the three periods. The maximum amount of reduction was in 2080–2099 (101 mm) under the scenario B1. Besides, a reduction occurred in the average runoff of the catchment under three ensemble models and the emission scenario in all three periods, as compared to the average of the long-term observational values in most years

Preparation of a Selective L-Phenylalanine Imprinted Polymer Implicated in Patients with Phenylketonuria

Background: Molecular imprinting is a method for synthesizing polymers with structure-selective adsorption properties with applications such as, selectivity binding, drug delivery systems and anti-bodies. The present study aims at optimizing the preparation of molecularly imprinted polymer (MIP) against l-phenylalanine, in order to increase phenylalanine-binding in Enzymatic Intestinal Simulated Fluid (ESIF). Methods: The MIP for l-phenylalanine, as a water-soluble template, was successfully synthesized without derivatization. Synthesization was done by a UV polymerization method in which methacrylic acid (MAA), as a functional monomer, and ethylene glycol dimethacrylate (EGDMA), as a cross-linker, were used in the presence of five different porogenic solvents including; acetonitrile, tetrahydrofuran (THF), chloroform, toluene and dimethyl sulfoxide (DMSO). The selectivity of the MIP was examined using 19 different amino acids in human serum and was evaluated by HPLC. In addition, morphological studies were conducted using SEM. Results: The results showed that the obtained MIP with acetonitrile had the highest capacity and selectivity compared with other solvents. The data indicated that Phe-binding to MIP was significantly more than the former binding to NIP in EISF (P≤0.05). Moreover, in comparison with NIP and control group, MIP showed a better selectivity and binding for Phe. This could be used for the reduction of Phe in human serum samples of Phenylketonuria. Conclusion: Our findings suggest that the MIP against Phe prepared with acetonitrile, showed a good selectivity and binding, which caused a reduction of blood Phe concentration in enzymatic simulated intestinal fluid and human serum sample of Phenylketonuria