Robust reservoir rock fracture recognition based on a new sparse feature learning and data training method

Multidimensional Systems and Signal Processing - In this paper, the main goal is to identify the sine fractures of reservoir rock automatically. Therefore, a five-step algorithm is applied on the...     

Preparation and photocatalytic study of CoFe2O4/TiO2/Au nanocomposites and their applications in organic pollutant degradation and modeling by an artificial neural network (ANN)

Journal of Materials Science: Materials in Electronics - Due to the increase of environmental pollution by various industries in recent decades, preparing drinking water has become one of the most...     

Artificial neural network to predict the effects of coating parameters on layer thickness of chromium carbonitride coating on pre-nitrided steels

Chromium carbonitride coatings were formed on plain carbon and alloy steels by pre-nitrocarburizing, followed by thermoreactive deposition and diffusion in a salt bath below 700 °C. In the present study, an artificial neural network-based model (ANNs) was developed to predict the layer thickness of pre-nitrided steels. Seventeen parameters affecting the layer thickness were considered as inputs, including the pre-nitriding time, salt bath compositions ratio, salt bath aging time, ferrochromium particle size, ferrochromium weight percent, salt bath temperature, coating time, and different chemical compositions of steels. The network was then trained to predict the layer thickness amounts as outputs. A 2-feed-forward back-propagation network was developed and trained using experimental data form literatures. Five steels were investigated. The effects of coating parameters on the layer thickness of steels were modeled by ANNs as well. The predicted values are in very good agreement with the measured ones indicating that the developed model is very accurate and has the great ability for predicting the layer thickness.     

ANN-based prediction of ferrite fraction in continuous cooling of microalloyed steels

In the present study, an artificial neural networks-based model was developed to predict the ferrite fraction of microalloyed steels during continuous cooling. Fourteen parameters affecting the ferrite fraction were considered as inputs, including the cooling rate, initial austenite grain size, and different chemical compositions. The network was then trained to predict the ferrite fraction amounts as outputs. A multilayer feed-forward back-propagation network was developed and trained using experimental data form literatures. The predicted values are in very good agreement with the measured ones indicating that the developed model is very accurate and has the great ability for predicting the ferrite fraction.     

Greener energy: Issues and challenges for Pakistan—Solar energy prospective

Energy plays a pivotal role in socio-economic development by raising standard of living. It is becoming gradually accepted that current energy systems, networks encompassing every thing from primary energy sources to final energy services, are becoming unsustainable. Development of conventional forms of energy for meeting the growing energy needs of society at a reasonable cost is the responsibility of the Governments. In recent years, public and political sensitivities to environmental issues and energy security have led to the promotion of renewable energy resources. Diversification of fuel sources is imperative to address these issues; and limited fossil resources and environmental problems associated with them have emphasized the need for new sustainable energy supply options that use renewable energies. Development and promotion of new non-conventional, alternate and renewable sources of energy such as solar, wind and bio-energy, etc. are now getting sustained attention. Solar power is one of the hottest areas in energy investment right now, but there is much debate about the future of solar technology and solar energy markets. This investigates the progress and challenges for solar power in Pakistan according to the overall concept of sustainable development, and identifies the region wise potential of solar power in Pakistan and its current status. Barriers are examined over the whole solar energy spectrum and policy issues and institutional roles and responsibilities are discussed.     

Study the Output Characteristics of a 90 kJ Filippove-Type Plasma Focus

The output characteristics of a Filippove-Type plasma focus “Dena” (288 μF, 25 kV, 90 kJ) is numerically investigated by considering the voltage, current, current derivative, and maximum current as a function of capacitor bank energy in the constant Argon gas pressure and compared to the experiment. It is shown that increase on the bank energy leads to the increment on the maximum current and decrement on the pinch time.     

Antioxidant,antifungal, water binding,and mechanical properties of poly(vinyl alcohol) film incorporated with essential oil as a potential wound dressing material

In this study, the properties of poly (vinyl alcohol) (PVA) films incorporated with Zataria multiflora essential oil (ZMO) as a potential antioxidant/antibacterial material was investigated. PVA films were prepared from PVA solutions (2% w/v) containing different concentrations of ZMO. Water solubility, moisture absorption, water swelling, and water vapor permeability for pure PVA films were 57 ± 1.1, 99 ± 3.2%, 337 ± 8%, and 0.453 ± 0.015 g mm/m² h, respectively. Incorporation of ZMO into PVA films caused a significant decrease in water swelling and moisture absorption and increase in solubility and water vapor permeability. Tensile strength, elastic modulus, and elongation at break for pure PVA films were 13.5 ± 0.61 MPa, 15.2 ± 0.8 MPa, and 216 ± 4%, respectively. Incorporation of ZMO into the PVA films caused a significant decrease in tensile strength and elastic modulus and increase in elongation at break of the films. Pure PVA film showed UV‐visible light absorbance ranging from 280 to 440 nm with maximum absorbance at 320 nm. Addition of ZMO caused a significant increase in light absorbance and opacity. PVA films exhibited no antioxidant and antifungal activities, whereas PVA/ZMO films exhibited excellent antioxidant and antifungal properties. Although the bioactivity PVA films were improved by the addition of ZMO, however, the mechanical properties and water binding capacity of the films were weaken slightly. Thus, ZMO emulsified in the ethanol not compatible with PVA matrix and more suitable emulsifier was needed in order to obtain strong film with higher mechanical properties. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40937.     

Environmental impacts of desalination on the ecology of Lake Urmia

Lake Urmia, the second largest hypersaline lake by area in the world, has fluctuated in salinity over time, but in recent years, it has reached a maximum of 340 g/L. The lake is the main habitat for the endemic Iranian brine shrimp, Artemia urmiana, and is a protected aquatic environment. Efforts have been made by the Iranian government to enhance the diversity of its wildlife. One approach has been to look for a method to reduce the salt content of the lake. We investigate the feasibility of this by first considering the water chemistry of Lake Urmia and then the various technologies used to extract salt from marine and brackish waters. Average concentrations of Na, Mg, K, Ca, Cl, SO₄, and HCO₃ were 125 g/L, 11.3 g/L, 2.63 g/L, 0.55 g/L, 216 g/L, 22.4 g/L, and 1.38 g/L, respectively, and cations and anions were balanced, However, Lake Urmia waters have a ‘very high’ salinity hazard and a high sodium adsorption ratio (SAR). Moreover, the saturation index (SI) for each of the major cations was greater than zero, indicating that the water in Lake Urmia is supersaturated, and precipitation is likely. The extraction of available salts from the lake for the use in petrochemical industries is economically feasible. However, technologies based on removing salts by distillation or reverse osmosis and then using this fresh water to dilute lake salinity are problematic. A better strategy would be better to allow more fresh water to reach the lake rather than creating fresh water through reverse osmosis and distillations processes. While concerns have been raised about the salinity tolerance of A.urmiana, it has successfully tolerated various salinity ranges from 166 to 340 g/L, and so the species is not threatened, unless the lake desiccates. Because the lake is saturated with salts, it seems unlikely that salinity could increase much higher.