The performance of asphalt concrete pavement has affected by many factors, the temperature is the most important environmental one which has a large effect on the structural behavior of flexible pavement materials. The main cause of premature failure of pavement is the rutting, Due to the viscoelastic nature of the asphalt cement, rutting is more pronounced in hot climate areas because the viscosity of the asphalt binder which is
inversely related to rutting is significantly reduced with the increase in temperature resulting in a more rut susceptible paving mixtures. The objective of this study is to determine the effect of temperatures variations on the permanent deformation parameters (permanent strain (p), intercept (a), slope (b), Alpha and Mu) as well as resilient strain (r) and resilient modulus (Mr). To achieve this objective, one aggregate gradation with 12.5mm nominal maximum size, two grades of asphalt cements (40-50 and 60-70) brought form Al- Daurah refinery, limestone dust filler has been used to prepare the asphalt concrete mixtures. 30 Marshall specimens were prepared to determine the optimum asphalt cement content. Thereafter, 30 cylindrical asphalt concrete specimens (102mm in diameter and 203 mm in height) are prepared in optimum asphalt cement and optimum ±0.5 percent. The prepared specimens were used in uniaxial repeated load test to evaluate the permanent deformation parameters of asphalt concrete mixes under the following testing temperature (5, 15, 25, 40 and 60c). The test result analyses appeared that Mr is decrease 51 percent when temperature increased from 5 c to 25 c and then decrease 22 percent with further increase in temperature from 25 c to 60 c. Also, the Alpha value decreases by a factor of 1.25 and 1.13 when temperature increases from 5 c to 25 c and 25 c to 60 c, espectively.
Finally, statistical models were developed to predict the Alpha and Mu parameters of permanent deformation.
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Abstract The purpose of this paper is preparing exercises according to some biomechanical variables for women with low back pain and identifying the effect of exercise according to some biomechanical variables and relieving lower back pain for women. The researchers used the one-group experimental design. The sample was chosen by the intentional method to provide the necessary conditions for conducting the study, and they represent the research community and its sample. The researchers also excluded (2) of the injured women because they did not adhere to the rehabilitation sessions, and for the purpose of ensuring the homogeneity of the sample members, the researchers used the arithmetic mean, standard deviation, and the torsion coefficient
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This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big
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This paper analyzes the effect of scaling-up model and acceleration history on seismic response of closed-ended pipe pile using a finite element modeling approach and the findings of 1 g shaking table tests of a pile embedded in dry and saturated soils. A number of scaling laws were used to create the numerical modeling according to the data obtained from 1 g shake table tests performed in the laboratory. The current study found that the behaviors of the scaled models, in general have similar trends. From numerical modeling on both the dry and saturated sands, the normalized lateral displacement, bending moment, and vertical displacement of piles with scale factors of 2 and 35 are less than those of the pile with a scale factor of 1 and the
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The combined system of electrocoagulation (EC) and electro-oxidation (EO) is one of the most promising methods in dye removal. In this work, a solution of 200 mg/l of Congo red was used to examine the removal of anionic dye using an EC-EO system with three stainless steel electrodes as the auxiliary electrodes and an aluminum electrode as anode for the EC process, Cu-Mn-Ni Nanocomposite as anode for the EO process. This composite oxide was simultaneously synthesized by anodic and cathodic deposition of Cu (NO3)2, MnCl2, and Ni (NO3)2 salts with 0.075 M as concentrations of each salt with a fixed molar ratio (1:1:1) at a constant current density of 25 mA/cm2. The characteristics structure and surface morphology of the depo
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