جستجوی مقالات مرتبط با کلیدواژه « Particle Swarm Optimization (PSO) algorithm » در نشریات گروه « اکولوژی »

One of the most important applications of rock-fill dams is to control flood by reducing the peak discharge of inflow. It is of great importance to study how much of the inflow to the rock-fill dam reservoir is transferred to the downstream under unsteady flow conditions. In the present study, flood routing in dual detention rock-fill dams was studied using four experimental data samples, linear Muskingum method, and particle swarm optimization (PSO) algorithm and the effect of rock-fill dam length, distance between two dams, and aggregate size was studied on the K coefficient of linear Muskingum method. The results showed that the mean relative error (MRE) of the four experiments used in the present study were equal to 4.9, 3.4, 4.35 and 3.55%, respectively, and the relative error of the peak discharge (DPO) of the mentioned experiments were calculated as 1.58, 0.47, 2.86 and 1.78%, respectively, which indicates the high accuracy of the linear Muskingum method in estimating the outflow hydrograph. The results also showed that, by increasing the distance between the inflow and outflow hydrographs, the K coefficient increased and by increasing the aggregates size, the flow velocity increased and consequently, the K coefficient decreased.

Unsteady flow analysis is performed using hydraulic and hydrological routing methods. Hydrological routing methods, while accurate, are much simpler and less expensive than hydraulic routing methods, and for flood routing calculations, only data related to hydrographs (flow changes over time) recorded at upstream and downstream hydrometric stations of the study area are needed. In the present study, the effect of the basic flood on the accuracy of flood routing in the Karun River was investigated using hydrological routing methods including linear Muskingum method, Working Values, Convex, and modified Att-Kin method. In other words, using the Particle Swarm Optimization (PSO) Algorithm and the 4 observational floods data recorded at the Mollasani (upstream) and Ahwaz (downstream) hydrometric stations of the Karun River, for each flood, separately, the linear Muskingum method parameters (X, K, ∆t) Optimized and used to calculate the outflow hydrograph of all floods. The results show that due to the effect of rivers flooding extent on the mentioned parameters if the range of inflow of basic flood changes is closer to the inflow of calculated flood, the accuracy of hydrological routing methods in outflow hydrograph estimation increases.