Different injection material types were tried in the injection of soft clay, such as lime (L), silica fume (SF), and leycobond-h (LH). In this study, experiments were made to study the effect of injection on soft clay consolidation settlement. A sample of natural soft clayey soil was investigated in the laboratory and the sample was injected with each of the grout materials used, L, SF, L + SF, and L + SF + LH. A 20 cm3 of each slurry grout was conducted into the soil, which was compacted in California Bearing Ratio (CBR) mold and cured for 7 days, and then the sample was loaded to 80 N load by a circular steel footing 60 mm in diameter. The settlement was recorded. The sample of each slurry grout, which provided minimum settlement, was chosen (L + SF + LH). To reduce soft clay settlement before and after footing construction, four cases were investigated. The impact of injection hole spacing and grout depth was studied. It was discovered that injecting a slurry of (L + SF + LH) into the soft clay beneath or surrounding the footing increased bearing capacity by 5–88%. Due to the shape of shear failure of the soft clay around the footing, grouting near the footing at a distance of 0.5 diameter of the footing is more effective than grouting at a distance of 1.0 diameter of the footing, and grouting near the footing at a distance of 0.5 diameter of the footing is more effective than grouting at a distance of 1.0 diameter of the footing.
Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.
In the present study, a low cost adsorbent is developed from the naturally available sawdust
which is biodegradable. The removal capacity of chromium(VI) from the synthetically prepared
industrial effluent of electroplating and tannery industrial is obtained.
Two modes of operation are used, batch mode and fixed bed mode. In batch experiment the
effect of Sawdust dose (4- 24g/L) with constant initial chromium(VI) concentration of 50 mg/L and
constant particle size less than1.8 mm were studied.
Batch kinetics experiments showed that the adsorption rate of chromium(VI) ion by Sawdust
was rapid and reached equilibrium within 120 min. The three models (Freundlich, Langmuir and
Freundlich-Langmuir) were fitted to exper
Human beings are starting to benefit from the technology revolution that witness in our time. Where most researchers are trying to apply modern sciences in different areas of life to catch up on the benefits of these technologies. The field of artificial intelligence is one of the sciences that simulate the human mind, and its applications have invaded human life. The sports field is one of the areas that artificial intelligence has been introduced. In this paper, artificial intelligence technology Fast-DTW (Fast-Dynamic Time Warping) algorithm was used to assess the skill performance of some karate skills. The results were shown that the percentage of improvement in the skill performance of Mai Geri is 100%.
Elemental capture spectroscopy (ECS) is an important tool in the petroleum industry for determining the composition and properties of rock formations in a reservoir. Knowledge of the types and abundance of different minerals in the reservoir is crucial for accurate petrophysical interpretation, reservoir engineering practices, and stratigraphic correlation. ECS measures the elemental content of the rock, which directly impacts several physical properties that are essential for reservoir characterization, such as porosity, fluid saturation, permeability, and matrix density. The ability to accurately determine these properties leads to better reservoir mapping, improved production, and more effective resource management. Accurately de
... Show MoreThe present investigation is concerned for the purification of impure zinc oxide (80-85 wt %) by using petroleum coke
(carbon content is 76 wt %) as reducing agent for the impure zinc oxide to provide pure zinc vapor, which will be
oxidized later by air to the pure zinc oxide.
The operating conditions of the reaction were studied in detail which are, reaction time within the range (10 to 30 min),
reaction temperature (900 to 1100 oC), air flow rate (0.2 to 1 l/min) and weight percentage of the reducing agent
(petroleum coke) in the feed (14 to 30 wt %).
The best operating conditions were (30 min) for the reaction time, (1100 oC) for the reaction temperature, (1 l/min) for
the air flow rate, and (30 wt %) of reducing
A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.