Hydrophobic silica aerogels were successfully preparation by an ambient pressure drying method from sodium silicate (Na2SiO3) with different pH values (5, 6, 7, 8, 9 and 10). In this study, acidic HCl (1M), a basic NH4OH (1M) were selected as a catalyst to perform the surface modification in a TMCS (trimethylchlorosilane) solution. The surface chemical modification of the aerogels was assured by the Fourier transform infrared (FTIR) spectroscopic studies. Other physical properties, such as pore volume and pore size and specific surface area were determined by Brunauer-Emmett- Teller (BET) method. The effect of pH values on the bulk density of aerogel. The sol–gel parameter pH value in the sol, have marked effects on the physical proper

the shear strength parameters of the treated and untreated gypsum soil under the effect of four soaking and drying cycles has studied in this paper, moreover examined the effect of wetting and drying cycles on the collapse potential of the soil and comparing between the behavior of the treated and untreated gypsum soil under the effect of the two conditions. Gypsum soil sample brought from Sawa lake in Al Muthana governorate with the content of gypsum 65.5%, the polyurethane polymer (PP) was used with different percentages 3, 6, and 10% to enhance the mechanical properties of gypsum soil, model was prepared to achieve four soaking and drying cycle to the samples before testing, this model consists of an Aluminum plate base with dimensions 7

Although allowable amounts of glycol contamination in diesel engine oil, no research has been conducted on how these levels and varying loads affect engine performance. The research used a four-stroke diesel engine to investigate the effect of different glycol contamination levels (0, 120, and 220 ppm) under two engine loads (4.5 and 9 kW). Brake specific fuel consumption, brake thermal efficiency, friction power, and exhaust gas temperature were measured to determine the engine performance. The experiment used the factorial arrangement in a completely randomized design (CRD) with three replicates. Increasing the contamination levels from 0 to 120 and then to 220 ppm under constant engine load significantly increased brake specific fuel con

In this study, the response and behavior of machine foundations resting on dry and saturated sand was investigated experimentally. In order to investigate the response of soil and footing to steady state dynamic loading, a physical model was manufactured to simulate steady state harmonic load at different operating frequencies. Total of 84 physical models were performed. The footing parameters are related to the size of the rectangular footing and depth of embedment. Two sizes of rectangular steel model footing were tested at the surface and at 50 mm depth below model surface. Meanwhile the investigated parameters of the soil condition include dry and saturated sand for two relative densities 30% and 80%. The response of the footing was ela

The change in project cost, or cost growth, occurs from many factors, some of which are related to soil problem conditions that may occurs during construction and/or during site investigation period. This paper described a new soil improvement method with a minimum cost solution by using polymer fiber materials having a length of (3 cm) in both directions and (2.5 mm) in thickness, distributed in uniform medium dense .
sandy soil at different depths (B, 1.5B and 2B) below the footings. Three square footings has been used (5,7.5 and 10 cm) to carry the above investigation by using lever arm loading system design for such purposes.
These fibers were distributed from depth of (0.1B) below the footing base down to the investigated dep

Intrusion Detection Systems (IDS) is the main defense mechanism deployed by the current networks to prevent cyber threats. Recurrent Neural Network (RNN) are also a novel IDS structure that replaces the conventional training and testing mechanism. The strategy encodes network traffic data as biological sequences using amino acid codons in such a fashion that the RNN is capable of effectively analyzing temporal and sequence data patterns. RNN architecture design adopts embedding layers to handle codon representations and Long Short-Term Memory (LSTM) layers to perform sequential data learning, which is followed by a fully connected network to perform classification functions, which preserve high feature extraction and classification