List of Articles mohammad ali izadbakhsh

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  1 - Sensitivity Analysis of Parameters Affecting Scour Depth at Downstream of Twin Bridge Piers Using Extreme Learning Machine
  siamak amiri mohammad ali izadbakhsh saeid shabanlou
  10.30495/wsrcj.2022.19223
  Background and Aim: Local scouring has been identified as one of the important factors that cause the structure of bridges, breakwaters, and piers to rupture. The complexity of the scouring mechanism has made this one of the most important fields of civil engineering st More

  Background and Aim: Local scouring has been identified as one of the important factors that cause the structure of bridges, breakwaters, and piers to rupture. The complexity of the scouring mechanism has made this one of the most important fields of civil engineering studies. In recent years, many studies have been performed on local scouring around bridge piers. Due to the great importance of predicting and estimating the scour pattern in the vicinity of bridge piers, many studies have been done on this type of structure.Method: In this study, for the first time, using a new extreme learning machine (ELM) method, the scour depth near the foundations of the twin bridges was simulated. First, effective parameters were identified and four ELM models were developed. Then, numerical results were validated using Monte Carlo simulation and the cross-validation method. Then the sin activation function was determined as the best activation function. In addition, ELM results were compared with artificial neural network (ANN) models that ELM models estimated scour values more accurately. Uncertainty analysis was performed for the superior ELM and ANN models and a relationship was proposed for the superior model. Partial derivative sensitivity analysis (PDSA) was also performed for all input parameters.Results: Among the existing activation functions, the sin function had the optimal performance compared to other activation functions. According to the analysis of modeling results, ELM 1 model was introduced as the superior model. This model was a function of all input parameters. Also, by removing the landing number, the accuracy of the numerical model was significantly reduced, so the mentioned parameter was identified as the most effective parameter in scouring modeling around the bases of the twin bridges by the model of Strength training machine.Conclusion: By analyzing the modeling results the superior ELM model was introduced. The results of ELM models were also compared with ANN models, which showed that ELM models simulate scour values more accurately. For the superior ELM model, a relation was proposed to calculate the scour hole depth, and further uncertainty analysis showed that this model had a higher performance than the actual value. In addition, the relative derivative sensitivity analysis for the input parameters showed that with increasing the landing number, the value of the objective function (scour depth) increases. Manuscript profile
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  2 - Simulation of Long-Term Rainfall in Babolsar City by Using Optimized Wavelet-Extreme Learning Machine
  hamed karimi mohammad ali izadbakhsh behrouz yaghoubi saeid shabanlou
  10.30495/wsrcj.2021.18077
  In this study, the long-term rainfall in Babolsar city was simulated by means of an optimized AI model. To do this, the extreme learning machine (ELM) and the wavelet transform (WT) were combined. It should be stated that the monthly rainfall values from 1951 to 2019 we More

  In this study, the long-term rainfall in Babolsar city was simulated by means of an optimized AI model. To do this, the extreme learning machine (ELM) and the wavelet transform (WT) were combined. It should be stated that the monthly rainfall values from 1951 to 2019 were applied, meaning that 70% of the observed values were employed to training the AI models and 30% of rest were utilized to testing these models. Firstly, the activation functions of the ELM models were evaluated; as a result, the sigmoid was chosen as the best activation function. Moreover, the lags of time series were introduced using the autocorrelation function (ACF) that four ELM models were defined through those identified lags. By performing a sensitivity analysis, the superior ELM model was introduced. The values of correlation coefficient (R), variance accounted for (VAF), and scatter index (SI) for the ELM model were respectively computed to be 0.524, 27.064, and 0.819. Furthermore, different mother wavelets were examined and the “dmey” was opted as the best mother wavelet. The wavelet transform enhanced the accuracy of the simulations significantly. For instance, the VAF index for the hybrid WELM model equaled to 86.461. It is noteworthy that the hybrid model was evaluated for different decomposition levels (DL) and then the best one was detected. Also, the (t-1) and (t-12) lags were identified as the most effective input lags. Manuscript profile
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  3 - Study the Long-Term Effects of Industrial and Agricultural Uses on the Fluctuations of the Groundwater Level of Shazand Plain
  Siamak Amiri Ahmad Rajabi Saeid Shabanlou Fariborz Yosefvand Mohammad ali Izadbakhsh
  10.30495/wsrcj.2023.72053.11360
  Background and Aim: Nowadays, by increasing the water demand in different sectors, the withdrawal amount from groundwater resources is increasing leading to more drawdown of Markazi province aquifers. One of the most suitable methods for the optimal management of ground More

  Background and Aim: Nowadays, by increasing the water demand in different sectors, the withdrawal amount from groundwater resources is increasing leading to more drawdown of Markazi province aquifers. One of the most suitable methods for the optimal management of groundwater resources is the analysis of the behavior of aquifers in various conditions using mathematical models. The objective of this paper is to investigate the effects of withdrawal for agricultural and industrial consumptions on the groundwater level of the Shazand plain located in Markazi Province and the impact of a 20% increase in irrigation efficiency of farms in the case of the development of under pressure and low-consumption systems using the GMS numerical model. Method: First, the conceptual and numerical model of the Shazand aquifer was executed in the GMS software and calibrated in the steady state. Then, the model was recalibrated in a transient state for the statistical period from October 2015 to September 2019. To examine the reactions of the model to the changes of important and effective parameters, the sensitivity analysis of the model was performed and the model was verified for the statistical period of October 2019 to September 2021. Then, the changes in the groundwater level in the aquifer under two reference management scenarios and increasing irrigation efficiency were investigated and compared. In the reference scenario assuming the continuation of the current conditions and in the efficiency increase scenario assuming a 20% increase in irrigation efficiency, the simulation of changes in the groundwater level in the entire Shazand plain for the upcoming 20 years from October 2021 to September 2041 was carried out. Results: Based on the obtained results, the RMSE error value related to the steady state recalibration is about 0.7 meters and the average RMSE error value in the transient state in all months of simulation in two recalibration and validation periods is less than 0.6 meters, which shows the high accuracy of the model in simulating the groundwater level in the whole plain. The sensitivity analysis showed that the changes in specific yield and hydraulic conductivity parameters have the greatest effect on the fluctuations of groundwater in the whole plain. The results showed that in the reference scenario, the drop in the groundwater level at the end of the 20-year operation period is 3.95 meters. In the scenario of a 20% increase in efficiency, with the reduction of extraction from wells due to the increase in irrigation efficiency, the amount of drop will reach 2.76 meters, in which case the amount of drop will be mitigated by 1.2 meters. Conclusion: According to the results, the highest drop in the groundwater level in both reference and increase in efficiency scenarios in the central areas of the plain is 9.2 and 6.9 meters, respectively, and the lowest drop in the western areas of the plain is 1 and 0.5 meters, respectively. Considering that the agricultural sector has the greatest impact on the level drop in the aquifer in the central areas of the plain, it is better to focus management plans to control withdrawal from the aquifer, such as increasing efficiency or modifying the cultivation pattern, on this sector. In case of the implementation of systems under pressure and increasing efficiency in the plain, the amount of drawdown in the region will be mitigated to some extent, but the problem will not be solved and it is necessary to implement supplementary programs to cultivate high consumption plants instead of high consumption crops and in the industry sector instead of extracting groundwater, treated municipal wastewater should be used. Manuscript profile