جستجوی مقالات مرتبط با کلیدواژه « مقاومت تراکمی » در نشریات گروه « مهندسی معدن »

Corrosion is one of the destructive factors that causes a lot of damage to the reinforcement inside the concrete and causes irreparable damage to the economy. Chlorine ion penetration in concrete is one of the most important factors affecting concrete corrosion. Therefore, it is necessary to refine corrosion by identifying the concrete properties using proper methods. In this study, the effect of adding zeolite (0, 10 and 15%) to concrete on the uniaxial compressive strength and penetration rate of chlorine ion in concrete was investigated. According to the tests result performed by adding zeolite at the beginning concrete compressive strength decreases but after 90 days the compressive strength increases and is approximately equal to the strength of control samples. Zeolite also reduces the penetration rate of chlorine ions into concrete by 30% on average (compared to the control sample). Finally, it can be concluded that using 10% zeolite improves the concrete properties.

It is important to determinate the elastic modulus of intact rock in many engineering projects relating to rock such as tunnels, slopes and foundations. Determination of this parameter need of high quality core samples and sophisticated test equipment because these make performing this test difficult and costly. There for in current years, researches have tried to produce relationships for prediction of this parameter using physical and index characteristics of rocks. So here an attempt has been made to predicate the elastic modulus of limestone by uniaxial compress strength, porosity and longitudinal wave velocity. So we used multiple variable regression method and perceptron artificial neural network with 3-4-1 architecture. Data base contains 123 samples that 70% and 30% of them has been used for train and test respectively in ANN. The models have been compared using coefficients of R2, RMSE and VAF. The coefficient of determination (R2) using multiple variable regression was 0.738. it was 0.805 and 0.832 for ANN train data set and ANN test data set respectively. This shows the ANN method have more accuracy than regression.