A Monte Carlo simulation approach for effective assessment of flyrock based on intelligent system of neural network

One of the undesirable phenomena in the surface mines, which results in various hazards for human and facilities, is flyrock. It seems that the careful study of the subject and its effects on the environment can affect the control of flyrock hazards in the studied area. Therefore, the use of intelligent models and methods which are capable of predicting and simulating the risk of flyrock can be considered as an appropriate solution in this regard. The current research was conducted using nonlinear models and Monte Carlo (MC) simulation. The data used in this study consist of 260 samples of rock thrown from a mine in Malaysia. The parameters used in these models include hole’s diameter (D), hole’s depth (HD), burden to spacing (BS), stemming (ST), maximum charge per delay (MC), and powder factor (PF). At first, multiple regression analysis (MRA) and artificial neural network (ANN) models were used in order to develop a non-linear relationship between dependent and independent parameters. The ANN model was an appropriate predictor of flyrock in the mine. Then using the best implemented model of ANN, the flyrock environmental phenomenon was simulated using MC technique. MC simulation showed a proper level of accuracy of flyrock ranges in the mine. Using this simulation, it can be concluded with 90% accuracy that the Flyrock phenomenon does not exceed 331 m. Under these conditions, this simulation can be used for various areas requiring risk assessment. Finally, a sensitive analysis was carried out on data. This analysis showed MC has the greatest effect on flyrock.     

Prediction of ultimate bearing capacity through various novel evolutionary and neural network models

Engineering with Computers - In the current study, various evolutionary artificial intelligence and machine learning models namely, optimized artificial neural network (ANN), genetic algorithm...     

A novel hybrid artificial intelligent approach based on neural fuzzy inference model and particle swarm optimization for horizontal displacement modeling of hydropower dam

Horizontal displacement of hydropower dams is a typical nonlinear time-varying behavior that is difficult to forecast with high accuracy. This paper proposes a novel hybrid artificial intelligent approach, namely swarm optimized neural fuzzy inference system (SONFIS), for modeling and forecasting of the horizontal displacement of hydropower dams. In the proposed model, neural fuzzy inference system is used to create a regression model whereas Particle swarm optimization is employed to search the best parameters for the model. In this work, time series monitoring data (horizontal displacement, air temperature, upstream reservoir water level, and dam aging) measured for 11 years (1999–2010) of the Hoa Binh hydropower dam were selected as a case study. The data were then split into a ratio of 70:30 for developing and validating the hybrid model. The performance of the resulting model was assessed using RMSE, MAE, and R ². Experimental results show that the proposed SONFIS model performed well on both the training and validation datasets. The results were then compared with those derived from current state-of-the-art benchmark methods using the same data, such as support vector regression, multilayer perceptron neural networks, Gaussian processes, and Random forests. In addition, results from a Different evolution-based neural fuzzy model are included. Since the performance of the SONFIS model outperforms these benchmark models with the monitoring data at hand, the proposed model, therefore, is a promising tool for modeling horizontal displacement of hydropower dams.

     

Physicochemical and Adhesion Characteristics of High-Density Polyethylene when Treated in a Low-Pressure Plasma under Different Electrodes

The present investigation studys the effects of different electrodes such as copper, nickel, and stainless steel under low-pressure plasma on physicochemical and adhesion characteristics of high-density polyethylene (HDPE). To estimate the extent of surface modification, the surface energies of the polymer surfaces exposed to low-pressure plasmas have been determined by measuring contact angles using two standard test liquids of known surface energies. It is observed that the surface energy and its polar component increase with increasing exposure time, attain a maximum, and then decrease. The increase in surface energy and its polar component is relatively more important when the polymer is exposed under a stainless-steel electrode followed by a nickel and then a copper electrode. The dispersion component of surface energy remains almost unaffected. The surfaces have also been studied by optical microscopy and electron spectroscopy for chemical analysis (ESCA). It is observed that when the HDPE is exposed under these electrodes, single crystals of shish kebab structure form, and the extent of formation of crystals is higher under a stainless-steel electrode followed by nickel and then copper electrodes. Exposure of the polymer under low-pressure plasma has essentially incorporated oxygen functionalities on the polymer surface as detected by ESCA. Furthermore the ESCA studies strongly emphasize that higher incorporation of oxygen functionalities are obtained when the polymer is exposed to low-pressure plasma under a stainless-steel electrode followed by nickel and then copper electrodes. These oxygen functionalities have been transformed into various polar functional groups, which have been attributed to increases in the polar component of surface energy as well as the total surface energy of the polymer. Therefore, the maximum increase in surface energy results in stronger adhesion of the polymer when the polymer is exposed under a stainless-steel electrode rather than nickel and copper electrodes.     

Electronic structure and magnetic properties of Al‐doped Ca2Fe2O5 brownmillerite compounds

Polycrystalline Ca₂Fe_2?xAl_xO₅ (x = 0‐1.4) samples were prepared by conventional solid‐state reactions. Their crystalline/electronic structures and magnetic properties were characterized in detail. Powder X‐ray diffraction analyses revealed that the samples crystallized in orthorhombic brownmillerite‐type structures with the occurrence of the Pcmn‐Ibm2 phase separation in the region between x = 0.4 and 0.6. The results obtained from analyzing Raman scattering and X‐ray‐absorption fine‐structure spectra also indicated this phase separation. Although x in Ca₂Fe_2?xAl_xO₅ varies in a wide range from 0 to 1.4, the +3 oxidation state of Fe remained almost unchanged. Magnetization measurements revealed that all Ca₂Fe_2?xAl_xO₅ samples have weak ferromagnetic order, and both the saturation magnetization and coercive force are dependent on the temperature, x, and structure phases.     

Effect of hygroscopic materials on water vapor permeation and dehumidification performance of poly(vinyl alcohol) membranes

In this study, two hygroscopic materials, inorganic lithium chloride (LiCl) and organic triethylene glycol (TEG) were separately added to poly(vinyl alcohol) (PVA) to form blend membranes for air dehumidification. Water vapor permeation, dehumidification performance and long‐term durability of the membranes were studied systematically. Membrane hydrophilicity and water vapor sorbability increased significantly with higher the hygroscopic material contents. Water vapor permeance of the membranes increased with both added hygroscopic material and absorbed water. Water permeation energy varied from positive to negative with higher hygroscopic content. This observation is attributed to a lower diffusion energy and a relatively constant sorption energy when hygroscopic content increases. Comparatively, PVA/TEG has less corrosive problems and is more environmentally friendly than PVA/LiCl. A membrane with PVA/TEG is observed to be highly durable and is suitable for dehumidification applications. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 44765.     

A new cutting depth model with rapid calibration in abrasive water jet machining of titanium alloy

Titanium alloys are widely used in the aeronautical and engineering fields as they show an excellent trade-off between the mass and mechanical properties, but as hard materials, they are difficult to machine using cutting tools. The abrasive water jet affords a good solution to produce titanium parts, especially slim ones. To do so, there is a need to adopt a modelling approach for the depth milled. However, a general methodology that takes into account all the parameters leads to complex models based on a large number of experiments. The present article proposes a depth of cut model combined with a rapid calibration method. The case addressed is that of open rectangular pockets on a Ti-6AL-4V titanium alloy. The approach introduces the machine configuration notion considering that a given machine, pressure level and abrasive impose the abrasive flow rate needed in order to obtain an optimal material removal rate. For a chosen configuration, calibration of the model is performed from a series of elementary passes and just three pocket machining passes. The method is rapid and effective as the accuracy of the models obtained over a number of configurations was to within the order of 5%.     

Stress-Strain State of Weak Saturated Clay Beds of Embankments

Results are presented for laboratory and field tests of weak saturated soils serving as beds for embankments in Ho Chi Min City and various regions of the Mekong River Delta (Vietnam). A method is outlined for quantitative evaluation of the stress-strain state (SSS) of the weak saturated clayey beds (plane problem). A method is described for quantitative evaluation of the deformation and stability of weak beds in the initial, intermediate, and stabilized stages of the formation and transformation of the SSS. __________ Translated from Osnovaniya, Fundamenty i Mekhanika Gruntov, No. 5, pp. 2–6, September–October, 2005.     

Environmental green chemistry as defined by photocatalysis

Photocatalysis is efficient in several fields. Firstly, in selective mild oxidation: oxidation of gas and liquid hydrocarbons (alkanes, alkenes, cyclo-alkanes, aromatics) into aldehydes and ketons. Primary and secondary alcohols are also oxidized into their corresponding aldehydes or ketones. The high selectivity was ascribed to a photoactive neutral, atomic oxygen species. Once platinized (only 0.5wt.% Pt) titania may catalyze reactions involving hydrogen (deuterium-alkane isotopic exchange and alcohol dehydrogenation). For fine chemicals, high initial selectivities enable titania to address most of the twelve principles of "green chemistry", such as the synthesis of 4-tert-butyl-benzaldehyde, an important intermediate in perfume industry by direct selective oxidation of 4-tert-butyl-toluene with air. A new field recently appeared: thio-photocatalysis. Oxygen was replaced by sulfur, using H(2)S as a convenient and reactive source. For instance, the conversion of propene in 1-propanthiol was successfully obtained. The reaction was performed using either CdS or TiO(2). The latter was much more active than CdS. In environmental photocatalysis, titania becomes a total oxidation catalyst once in presence of water because of the photogeneration of OH radicals by neutralization of OH(-) surface groups by positive holes. Many toxic inorganic ions are oxidized in their harmless upper oxidized state. The total degradation of organic pollutants (pesticides, herbicides, insecticides, fungicides, dyes, etc. ...) is the main field of water photocatalytic decontamination. The UVA solar spectrum can de advantageously used as demonstrated by many campaigns performed in the solar pilot plant at the "Plataforma Solar de Almeria" (Spain).     

Folates in Asian noodles: II. A comparison of commercial samples and the impact of cooking

ABSTRACT:  The folate contents of 26 commercial noodle samples were investigated. The impact of ingredients, pH, and cooking on folate content was studied for the 3 predominant styles of noodles: white salted, yellow alkaline, and instant. Some variability was found in the proportion of folate present in the free form and the noodles generally had low total folate contents. The pH values of the samples covered a wide range, varying from 3.7 to 10.3; however, the results did not provide strong evidence for a relationship between pH and folate content for any of the noodle styles studied. Higher folate levels were typically found in yellow alkaline samples compared to white salted and instant noodles. The storage of noodles in dry or moist forms did not appear to influence total folate contents, and subsequent losses during cooking depended upon the time of exposure to elevated temperatures. The enzymatic treatment of samples was particularly important for cooked noodles, indicating that folates were bound or entrapped during this process.