Effect of Cross-section Geometry on Air-Demand Ratio in High-head Conduits With Sluice Gate

When the researches on the gated conduits were examined, it was determined that the air-demand ratio changed according to the hydraulic and geometric parameters. However, no study investigated the effect of the cross-section geometry of gated conduits on the air-demand ratio. In this study, the effect of conduit cross-section geometry on the air-demand ratio was examined. Results showed that conduit cross-section geometry was an important effect on the air-demand ratio especially at 10% and 15% gate opening rates. It was seen that the effect of the conduit geometry on the air-demand ratio decreased at 20%, and greater gate opening rates. In addition, a design formula related to the gate opening rate, Froude number, hydraulic radius, and conduit length was presented for estimating the air-demand ratio.

Sedimentation of nanoparticle titanium dioxide in the presence of ammonium

Due to its physicochemical properties, nanoparticles titanium dioxide (nTiO2) is being put into mass production and widespread applications, which inevitably results in their increasing exposure to the water body. After it entering the water body, the chemical properties of nTiO2 can be influenced by ion compositions, ion strength and pH, which affects their ecological risk. Excess of ammonium (NH4+) fertilizer has contaminated soil and water environments. In this paper, the Zeta potentials and hydrodynamic radius of nTiO2 were studied in NH4+ solution compared to those in Na+ solution. In addition, the sedimentation rate of nTiO2 was also investigated. The experiment results show that high pH inhibits the sedimentation of nTiO2. Moreover, NH4+ increases the stability of nTiO2 more than Na+ at the same IS, which was attributed the more negative Zeta potentials and the smaller hydraulic radius. Our results provide a theoretical basis for evaluating the ecological risk of nTiO2 in aqueous solution containing NH4+.

Insights into the prediction capability of roughness coefficient in current ripple bedforms under varied hydraulic conditions

Ubiquitous flow bedforms such as ripples in rivers and coastal environments can affect transport conditions as they constitute the bed roughness elements. The roughness coefficient needs to be adequately quantified owing to its significant influence on the performance of hydraulic structures and river management. This work intended to evaluate the sensitivity and robustness of three machine learning (ML) methods, namely, Gaussian process regression (GPR), artificial neural network (ANN), and support vector machine (SVM) for the prediction of the Manning's roughness coefficient of channels with ripple bedforms. To this end, 840 experimental data points considering various hydraulic conditions were prepared. According to the obtained results, GPR was found to accurately predict the Manning's coefficient with input parameters of Reynolds number (Re), depth to width ratio (y/b), the ratio of the hydraulic radius to the median grain diameter (R/D50), and grain Froude number (). Moreover, sensitivity analysis was implemented with proposed ML approaches which indicated that the ratio of the hydraulic radius to the median grain diameter has a considerable role in modeling the Manning's coefficient in channels with ripple bedforms.

Pillar recovery using new wireless blasting technology: a case study in Vazante mine, Brazil

The application of explosives has never been considered as a major influencing factor during either the designing of a mine or the selection of the mining method. However, this has changed with the launch of WebGenTM wireless blasting system, which allowed underground mines to exploit their orebody applying methods previously not possible due to limitations imposed by the use of wired detonators. The wireless blasting system is based on magnetic induction communication, and its signal is capable of overcoming hundreds of meters through rock, water, and air, to reach individual primers in the blastholes without any physical connection.A noble application of wireless detonators is being used in Vazante mine, Brazil, an underground zinc mine where ore pillars are left in the mined stope to secure stability and minimize dilution by limiting the hydraulic radius. The recovery of these pillars is financially desirable but involves extra time and costs associated with scaling, backfilling, reinstalling infrastructure, accessing areas previously blasted (less stable), drilling, charging with explosives, and subsequently, firing and mucking out the blasted material with expected high dilution. Applying 100% wireless detonators made it possible to safely preload the pillar together with production blasts before losing access to the area, a method named Temporary Rib Pillar (TRP). After all the stope is mined and the pillar accomplished its objectives, the primers are initiated without neither the need for the extra cycles described previously, nor the need to re-enter the area. Thus, it was possible to reduce the exposure of people and equipment, reduce operational cycles, and increase ore recovery, directly contributing to anticipate the ore production while guaranteeing the safety of the teams involved.

Design of Collection System Parameters Using Known Reference Pipe Method (KRPM)

The storm water drainage network is generally calculated based on the Manning equation, where the slope, roughness of the pipe wall, and flow are known, while conversely the velocity, diameter, and hydraulic radius are unknown characteristics, although they are very important for the work done by a hydraulic engineer who needs these parameters to find their values, including the students taking coursework relating to waste-water engineering. The computation of these parameters in partially full pipes and based on the Manning equation is implicit and needs to be computed using iterative and laborious methods. In this paper, a new, simple and easy method is presented based on a reference pipe with known characteristics (Known Reference Pipe Method: KRPM), as well as the effect of the up-pipe parameters on the down-pipes according to each case that is possible through the watershed drainage system arrangement, for both full and partially filled circular pipes.

Error analysis of hydraulic radius evaluation in hydraulic calculation

Hydraulic radius is an important parameter in hydraulic calculation. It is often deemed that hydraulic radius can be replaced by the cross-sectional average water depth when the width to depth ratio (B/H) is greater than a certain value in traditional. Based on the various artificial cross-section and natural ones, value-taking errors of hydraulic radius are studied in this paper. The results show that it is feasible to adopt the average water depth as the hydraulic radius when B/H of rectangular section is larger than 40 or B/H of isosceles triangular section is larger than 12. But for natural river, B/H is different when water level changes and there is no single-valued corresponding relationship between relative error and B/H. Therefore, we advise that hydraulic radius could not be replaced by other variables in hydraulic calculation of natural rivers.

Discharge estimation in converging and diverging compound open channels by using adaptive neuro-fuzzy inference system

The computation of total flow in a flooded river is very crucial work in designing economical flood defense schemes and drainage systems. Further, under non-uniform flow conditions like in converging and diverging compound channel, the traditional methods provide poor results with high errors. The analytical methods require the system of nonlinear equations to be solved, which is very complex. So, mathematical models that prompt in taking care of a complex system of problems are solved here through an artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS). By utilizing ANN and ANFIS, an attempt is made to predict the discharge in converging and diverging compound channels. In the analysis, the most influencing dimensionless parameters such as friction factor ratio, area ratio, hydraulic radius ratio, bed slope, width ratio, relative flow depth, angle of converging or diverging, relative longitudinal distance, and flow aspect ratio are taken into consideration for computation of discharge. Gamma test and M-test have been performed to achieve the best combinations of input parameters and training length respectively. The significant input parameters that influence the discharge are found to be friction factor ratio, hydraulic radius ratio, relative flow depth, and bed slope. A suitable performance is achieved by the ANFIS model as compared to ANN model with a high coefficient of determination of 0.86 and low root mean square error of 0.005 in predicting the discharge of non-prismatic compound channels taken under consideration.

Evaluation of the parameters of the porous structure and permeability of monofraction ceramics

A method for assessing the structure parameters of porous ceramic materials by porosity and particle size is presented. Based on it, a physically more rigorous than the well-known Cozeny formula is obtained, a formula for determining the average (hydraulic) radius of the capillaries of permeable materials. The presented results of the calculation of the average radius of the capillaries of porous ceramics based on electrocorundum according to the obtained formula are in better agreement with experimental data than the calculations by the Cozeny formula.

Deep learning under H2O framework: A novel approach for quantitative analysis of discharge coefficient in sluice gates

Gates in dams and irrigation canals have been used for the purpose of controlling discharge or water surface regulation. To compute the discharge under a gate, discharge coefficient (Cd) should be first determined precisely. From a novel point of view, this study investigates the effect of sill shape under the vertical sluice gate on Cd using four artificial intelligence methods, which are used to estimate Cd, (i) random forest (RF), (ii) deep learning (DL), (iii) gradient boosting machine (GBM), and (iv) generalized linear model (GLM). A sluice gate along with twelve different forms of sills was fabricated and tested in the University of Tabriz, Iran. Different flow rates were considered in the hydraulic laboratory with four gate openings. As a result, a total of 180 runs could be tested. The results showed that the installation of sill under the vertical gate has a positive effect on flow discharge. Sill shapes can be characterized by their hydraulic radius (Rs). Sensitivity analysis among the dimensionless parameters proved that Rs/G (the ratio of the hydraulic radius of the sills with respect to the gate opening) has a significant role in the determination of Cd. A semi-circular sill shape has a more positive effect on the increase of Cd than the other shapes.