Using Waste Vermiculite and Dolomite as Eco-Friendly Additives for Improving the Performance of Porous Concrete

The present study investigated the applicability of waste vermiculite and dolomite as fine aggregate, known as appropriate mineral adsorbents to enhance the quality of urban runoff, for improving the mechanical properties of porous concrete. 180 samples were mixed by adding 5-30% vermiculite and dolomite, as fine aggregate, and combining them with ordinary sand; lime sand (combining of 5-15% of each). Results showed that although adding dolomite culminated in a minor reduction of permeability– average of about 30%-, the average of compressive strength was augmented by 120%. Results of compressive strength of dolomite samples were repeated in mixtures containing vermiculite (an increase of 57%). While exploiting vermiculite in high percentages (20, 25, and 30) resulted in an extensive decrease in the permeability (94%), it was improved to an acceptable level (about 40%) after using vermiculite in combination with ordinary sand (lime sand). All dolomite and improved vermiculite mixtures, after combining vermiculite with ordinary sand, had appropriate performance in draining storm-urban runoff; such that in the weakest case, stimulated storm runoffs with heights of 10, 20, 30 and 40 cm were completely drained only after 17, 36, 59 and 87 seconds, respectively. Also, using vermiculite resulted in reducing the concrete weight (about 100 kg). Generally, although a little reduction in the permeability was seen, but using waste vermiculite and dolomite improved the mechanical properties of porous concrete significantly

Assessing Flow Characteristics in Chute Spillway of Neka-Gelvard Dam using Computational Fluid Dynamics

In recent years, as dam safety standards have increased, hydraulic engineers have become more eager to design an economical and safe energy dissipation system at the main flood evacuation course. Ogee spillway and flip bucket are the most used types of spillway and energy dissipation structures. The main aims of the present research were modeling and analyzing hydraulic characteristics of the flow over convergent chute and flip bucket with negative slope of Gelvard Dam, Neka, the north of Iran using Flow-3D software and comparing the results of spillway geometry modification in relation to the initial model. The validation results of numerical model with the experimental data showed that RNG model is the most appropriate turbulence model. Moreover, with respect to the dimensions of computational cells, sensitivity analysis showed that square mesh with dimensions of 0.6 m is appropriate. Considering the results of the numerical modeling, due to increasing the flow velocity more than 20 m/s at the end of chute and maximum pressure of -70000 pa in this area, cavitation threatens the circular arc. Therefore, the slope of the chute and circular arc radius was changed respectively and numerical analysis results were remeasured. The results showed that by reducing the chute slope, the critical points of cavitation decreased from 3 points to 1 point. In addition, it was indicated that changing circular arc radius had no considerable effect on hydraulic characteristics. It just showed that when arc radius increases, jet length increases up to 5 m

Comparison of DEEP-LSTM and MLP Models in Estimation of Evaporation Pan for Arid Regions

The importance of evaporation estimation in water resources and agricultural studies is undeniable. Evaporation pans (EP) are used as an indicator to determine the evaporation of lakes and reservoirs around the world due to the ease of interpreting its data. The purpose of this study is to evaluate the efficiency of the Long- Short Term Memory (LSTM) model to estimate evaporation from a pan and compare it with the Multilayer Perceptron (MLP) model in Semnan and Garmsar. For this purpose, daily meteorological data recorded between 2000 and 2018 (19 consecutive years) in Semnan and Garmsar synoptic stations were used. Minimum and maximum air temperature (Tmax, Tmin), wind speed (WS), sunshine hours (SH), air pressure (PA), relative humidity (RH) were selected as input data and evaporation data from the pan (EP) was considered as the output of the case. Also, in modeling both networks in the input section, 4 different scenarios were used. The two studied models were evaluated by the evaluation criteria of coefficient of determination (R2), root mean square error (RMSE) and mean absolute error (MAE). The results showed that among the studied scenarios, the fourth scenario (considering all input parameters) had the highest R2 and the lowest RMSE and MAE. In general, the two models performed well in predicting the rate of evaporation. Also, in both stations, the LSTM model had more R2 and less RMSE and MAE than the MLP model. The values of R2, RMSE and MAE for the best DEEP-LSTM model (LSTM4) for Semnan city were 0.9451, 1.8345 and 0.5437 and for Garmsar city 0.9204, 1.8323 and 1.3531 respectively

Reduction of local scouring with protective spur dike

One of the main parameters in design of spur dikes is the estimation of local scour depth around their tail. Spur dikes are usually built in series and their stability depends on the stability of the first spur dike. In this research, an experimental investigation is carried out in order to reduce local scouring around the first spur dike in a series of spur dikes (4 spur dikes). A smaller protective spur dike perpendicular to the flow direction is proposed to substantially reduce the local scouring. All experiments are performed in the experimental flume with moving bed. Also, all the spur dikes are rigid, and are made of pressurized plywood, straight and non-submerged. For various experimental lengths (L') and distances(X) of the protective spur dike, different value of relative velocity (u/uc) is calculated. Finally, in favor of statistical analysis which has been done on the experimental data, an empirical equation for the relative scouring is derived

Experimental investigation and flow analysis of clear-water scour around pier and abutment in proximity

Local scour around bridge piers and abutments is one of the most important causes of bridge failure. Despite a plethora of studies on scour around individual bridge piers or abutments, few studies focused on the joint impact of a pier and an abutment in proximity on scour. This study conducted laboratory experiments and flow analyses to examine the interaction of piers and abutments on clear-water scour. The experiments were conducted in a rectangular laboratory flume, including 18 main tests (combination of different types of piers and abutments) and five control tests (individual piers or abutments). Three types of piers (a rectangular pier with a rounded edge, a group of three cylindrical piers, a single cylindrical pier) and two types of abutment (a wing-wall abutment and a semi-circular abutment) were used. Acoustic Doppler Velocimeter (ADV) was used to measure the three-dimensional flow velocity for analyses of streamline, velocity magnitude, vertical velocity, and bed shear stress. The results showed the velocity near the pier and abutment increased by up to 80%. The maximum scour depth around the abutment increased by up to 19%. In contrast, the maximum scour depth around the pier increased significantly by up to l71%. The presence of the pier in the vicinity of the abutment led to an increase in the scour hole volume by up to 87% relative to the case with an individual abutment. The empirical equations were also derived to accurately estimate the maximum scour depth at the pier adjacent to the abutment

Radiobiological effects of wound fluid on breast cancer cell lines and human-derived tumor spheroids in 2D and microfluidic culture

Intraoperative radiotherapy (IORT) could abrogate cancer recurrences, but the underlying mechanisms are unclear. To clarify the effects of IORT-induced wound fluid on tumor progression, we treated breast cancer cell lines and human-derived tumor spheroids in 2D and microfluidic cell culture systems, respectively. The viability, migration, and invasion of the cells under treatment of IORT-induced wound fluid (WF-RT) and the cells under surgery-induced wound fluid (WF) were compared. Our findings showed that cell viability was increased in spheroids under both WF treatments, whereas viability of the cell lines depended on the type of cells and incubation times. Both WFs significantly increased sub-G1 and arrested the cells in G0/G1 phases associated with increased P16 and P21 expression levels. The expression level of Caspase 3 in both cell culture systems and for both WF-treated groups was significantly increased. Furthermore, our results revealed that although the migration was increased in both systems of WF-treated cells compared to cell culture media-treated cells, E-cadherin expression was significantly increased only in the WF-RT group. In conclusion, WF-RT could not effectively inhibit tumor progression in an ex vivo tumor-on-chip model. Moreover, our data suggest that a microfluidic system could be a suitable 3D system to mimic in vivo tumor conditions than 2D cell culture

Toward bridging future irrigation deficits utilizing the shark algorithm integrated with a climate change model

Climate change is one of the most effectual variables on the dam operations and reservoir water system. This is due to the fact that climate change has a direct effect on the rainfall–runoff process that is influencing the water inflow to the reservoir. This study examines future trends in climate change in terms of temperature and precipitation as an important predictor to minimize the gap between water supply and demand. In this study, temperature and precipitation were predicted for the period between 2046 and 2065, in the context of climate change, based on the A1B scenario and the HAD-CM3 model. Runoff volume was then predicted with the IHACRES model. A new, nature-inspired optimization algorithm, named the shark algorithm, was examined. Climate change model results were utilized by the shark algorithm to generate an optimal operation rule for dam and reservoir water systems to minimize the gap between water supply and demand for irrigation purposes. The proposed model was applied for the Aydoughmoush Dam in Iran. Results showed that, due to the decrease in water runoff to the reservoir and the increase in irrigation demand, serious irrigation deficits could occur downstream of the Aydoughmoush Dam

Hybrid model of support vector regression and fruitfly optimization algorithm for predicting ski-jump spillway scour geometry

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Investigating the Performance of Neural Network Based Group Method of Data Handling to Pan's Daily Evaporation Estimation (Case Study: Garmsar City)

Evaporation is a complex and nonlinear phenomenon due to the interactions of different climatic factors. Therefore, advanced models should be used to estimate evaporation. In the present study, the Neural Network-Based Group Method of Data Handling was used to estimate and simulate the evaporation rate from the pan in the synoptic station of Garmsar city located in Semnan province, Iran. For this purpose, the daily meteorological data of evaporation, minimum and maximum temperature, wind speed, relative humidity, air pressure, and sunny hours of the said station during the nine years (2009-2018) were used. The percent of data on training, test, number of the used layers, and the highest number of neurons were considered as 60%, 40%, 5%, and 30%, respectively. The studied method's accuracy was investigated using the statistical parameter of Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and correlation coefficient, and. Sensitivity analysis of the input parameters was performed using the GMDH-NN model. This study showed that R2, RMSE, and MAE values in the test phase were obtained as 0.84, 2.65, and 1.91, respectively, in the most optimal state. From the third layer onwards, the amount of the best mean squared errors of the ‎Validation data have converged to 0.062, and it is not affordable to use more layers ‎for the modeling of the evaporation pan in the Garmsar station.‎ The standard deviation and mean amounts of the errors are -0.1210 and 2.552 ‎respectively.‎ The amounts of the best mean squared errors of the validation data are presented. ‎It shows that although the layers are increased, the amounts of the mean squared ‎errors have not changed considerably. (Maximum 0.003). The sensitivity analysis results showed that the two input parameters of minimum temperature and relative humidity percent have a higher effect on evaporation pan modeling than other input parameters