مجله زمین شناسی مهندسی
سال شانزدهم شماره 3 (پاییز 1401)

Electromagnetic methods in applied geophysics are advancing rapidly. Since the TDR system has grown, its use has led to innovative applications and comparisons with other previous measurement methods. A TDR system consists of a radar (electromagnetic) receiver and generator, a transmission line, and a waveguide. The electromagnetic pulse generated from inside the conductor cable moves towards the waveguide and is tested through the waveguide into the environment under test. In the last few years, the use of the TDR system to identify water leakage situations has been expanding. In this article, by performing tests on two-strand telecommunication cables as TDR sensors, the ability and accuracy of the time domain reflectometry method in detecting leakage situations has been evaluated. In this research, the two-stranded cable was buried under GC gravel clay material, and by increasing the percentage of soil moisture stepwise at two points, the sensitivity of the TDR method to the changes in moisture around the cable was investigated. Based on the TDR waveforms, the points of reflection coefficient changes are located at the distances of 9.5-9 and 4.5 meters, which is completely consistent with the actual distance of the test points. In this research, TDR moisture meter made by soil moisture company model 6050x1 was used. The results of this research show that the TDR method has the ability to be used as a monitoring system to detect leakage in dams, dikes and other geotechnical structures.

Shear strength parameters are important for assessing the stability of structures, and are costly to calculate using conventional methods. In this research, simple geotechnical techniques and artificial intelligence were used to calculate the angle of internal friction and soil cohesion without the need for more complex testing. To this end, intact samples from 14 boreholes in Bandar Abbas, which had undergone primary geotechnical testing and direct cutting, were selected and used to train neural networks. 195 networks were trained in in this research. To achieve the best performance, feedforward neural networks were first trained in single and double layer modes with a low number of neurons in the middle layer, and the TRAIN BR function was selected due to the high ratio of R (0.97). Then, by incorporating additional layers, the Median model was trained using configurations of 3, 4, and 5 layers, each with varying numbers of neurons in the intermediate layer (50, 40, 30, 20, and 10). The results show that the four-layer MLP network gives the best results, for this mode R training 1, the test R is 0.90 and the total R is 0.98. Finally, to validate the neural network, 15 samples were selected and the input parameters of the network were trained in the optimal states of 2, 3, and 4 layers, then the output of the network was evaluated. For cohesion prediction, the neural network in 4-layer mode (R2=0.99) and 2, 3 and 4-layer networks (R2=0.99) have the best output for the friction angle.

This research is a laboratory study to improve the geotechnical properties of fine-grained soils. For this purpose, agricultural waste ash such as sugarcane bagasse, rice husk and almond husk have been used. In this regard, the effect of using ash of the mentioned fibers with at 4, 8 and 12 weight percentages on fine grain clay soils has been investigated. The compaction test results indicate that these additives generally increase the optimum soil moisture and the maximum optimum moisture was observed for the samples made with 12% ash. Also, based on the results of the unconfined compressive strength test, the studied additives have increased the uniaxial strength of the soil. The samples made with 12% ash were the most effective, so that the addition of 12% bagasse ash increased the soil resistance by 117%, and the addition of 12% rice husk ash and almond husk ash increased the soil resistance by 89, 80% respectively.

In most current seismic codes, the stiffness and strength of seismic members are considered to be independent, so that a change in the strength of the members does not result in a change in the stiffness of the members. Recent studies show that these parameters are interdependent. Therefore, the way these parameters are calculated and the arrangement of centers of mass, stiffness and strength can be effective in determining the seismic response. In this research, buildings with different levels of normalized yield eccentricity (ed/A) were designed according to the ASCE/SEI 07-22 seismic code (Code Design models) and compared with the Balance-25% and Symmetric Strength models. The results of the nonlinear static analysis and incremental dynamic analysis showed that the average spectral acceleration at the level of collapse in the Balance-25% and Symmetric Strength models increased by approximately 18% compared to the Code Design model. Therefore, these models are safer than the Code Design model. In addition, the average of the peak rotation of floors and the maximum inter-story drift at the collapse level in the Balance-25% and Symmetric Strength models has decreased by 100% and 12% respectively compared to the Code Design model. Therefore, the Code Design model had the lowest and the Balance-25% and Symmetric Strength models had the highest dynamic seismic performance.

Droughts caused by precipitation deficits and increasing water consumption are intensifying worldwide, with negative economic and environmental consequences. The negative impacts can be mitigated by using optimized reservoir operation patterns and implementing rationing rules during droughts. These approaches involve meeting only a portion of total demand, allowing for water storage and accepting a small current deficit to mitigate severe future shortages. This research presents a case study to determine the operational command curves for Jareh Dam and to investigate the impact of reservoir operation under two management policies, Standard Operating Procedure (SOP) and rationing, on downstream drought indices, an aspect not previously studied. To achieve this, an optimization model coupled with a genetic algorithm was linked to a simulation model to determine the optimal values of command curves and rationing coefficients based on historical inflow data to the reservoir. The performance of the model was evaluated in the Allah River water resources system. In addition, the drought severity index (SDI), SOP performance, and rationing model performance during the base period were evaluated by calculating the objective function value or modified shortage index (MSI) and the resilience, vulnerability, and reversibility indices. The results showed that under the rationing model during the study period, the MSI value improved by 41% compared to the SOP method. In addition, the implementation of the rationing policy significantly improved the vulnerability of the system compared to the SOP method, reducing it from 64% to 26%.