Modern asphalt technology has adopted nanomaterials as an alternative option to assert that asphalt pavement can survive harsh climates and repeated heavy axle loading during service life and prolong pavement life. This work aims to elucidate the behavior of the modified asphalt mixture fracture model and assess the fatigue and Rutting performance of Hot Mix Asphalt (HMA) mixes using the outcomes of indirect Tensile Strength (IDT), Semicircular bend (SCB) and rutting resistance; for this, a single PG (64−16) nanomodified asphalt binder with 5 % SiO2 and TiO2 have been investigated through a series of laboratory tests, including: Resilient modulus, Creep compliance, and tensile strength, SCB, and Flow Number (FN) to study their potential

In this paper, we derived an estimators and parameters of Reliability and Hazard function of new mix distribution ( Rayleigh- Logarithmic) with two parameters and increasing failure rate using Bayes Method with Square Error Loss function and Jeffery and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived of Bayesian estimator compared to the to the Maximum Likelihood of this function using Simulation technique by Monte Carlo method under different Rayleigh- Logarithmic parameter and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator in all sample sizes with application

Experimental and numerical studies have been conducted on the effects of bed roughness elements such as cubic and T-section elements that are regularly half-channel arrayed on one side of the river on turbulent flow characteristics and bed erosion downstream of the roughness elements. The experimental study has been done for two types of bed roughness elements (cubic and T-section shape) to study the effect of these elements on the velocity profile downstream the elements with respect to different water flow discharges and water depths. A comparison between the cubic and T-section artificial bed roughness showed that the velocity profile downstream the T-section increased in smooth side from the river and decrease in the rough side

     A partial temporary immunity SIR epidemic model involv nonlinear treatment rate is proposed and studied. The basic reproduction number  is determined. The local and global stability of all equilibria of the model are analyzed. The conditions for occurrence of local bifurcation in the proposed epidemic model are established. Finally, numerical simulation is used to confirm our obtained analytical results and specify the control set of parameters that affect the dynamics of the model.

12 membered Schiff base macrocyclic ligands, 6,7,14,15-tetra phenyl-1,2,3,4, 4a,8a, 9,10, 11,12, 12a,16a-dodecahydro dibenzo [b,h] [1,4,7,10] tetraazacyclododecine L1, and 14 membered Schiff base macrocyclic ligands, 6,8,15,17-tetramethyl-1,2,3,4, 4a,7,9a, 10,11,12,13,13a,16,18a-tetra decahydro dibenzo[b,i] [1, 4,8,11] cyclotetradecine tetraaza L2, 7,16-bis(2,4- dichloro benz ylidene)-6,8,15,17-tetra methyl-1,2,3,4, 4a,7,9a, 10, 11,12, 13, 13a,16,18a-tetra deca hydro dibenzo [b,i] [1,4,8,11] tetra azacyclo tetra decine L3 and 6,8,15, 17-tetramethyl-1,2,3, 4,4a,9a,10, 11,12,13,13a,18a-dodecahydro dibenzo [b,i] [1,4,8, 11] tetraazacyclo tetradecine (7,16-diylidene) bis(methanylyli dene) bis (N,N-dimethylaniline) L4 were synthesized by condens

This paper is focused on orthogonal function approximation technique FAT-based adaptive backstepping control of a geared DC motor coupled with a rotational mechanical component. It is assumed that all parameters of the actuator are unknown including the torque-current constant (i.e., unknown input coefficient) and hence a control system with three motor control modes is proposed: 1) motor torque control mode, 2) motor current control mode, and 3) motor voltage control mode. The proposed control algorithm is a powerful tool to control a dynamic system with an unknown input coefficient. Each uncertain parameter/term is represented by a linear combination of weighting and orthogonal basis function vectors. Chebyshev polynomial is used