The main objective of this study is to develop predictive models using SPSS software (version 18) for Marshall Test results of asphalt mixtures compacted by Hammer, Gyratory, and Roller compaction. Bulk density of (2.351) gm/cc, at OAC of (4.7) % was obtained as a benchmark after using Marshall Compactor as laboratory compactive effort with 75-blows. Same density was achieved by Roller and Gyratory Compactors using its mix designed methods.

A total of (75) specimens, for Marshall, Gyratory, and Roller Compactors have been prepared, based on OAC of (4.7) % with an additional asphalt contents of more and less than (0.5) % from the optimum value. All specimens have been subjected to Marshall Test. Mathematical model

   Pressure retarded osmosis (PRO) can be considered as one of the methods for utilizing osmotic power, which is a membrane-based technology. Mathematical modeling plays an essential part in the development and optimization of PRO energy-generating systems. In this research, a mathematical model was developed for the hollow fiber module to predict the power density and the permeate water flux theoretically. Sodium chloride solution was employed as the feed and draw solution. Different operating parameters, draw solution concentration (1 and 2 M), the flow rate of draw solution (2, 3, and 4 L/min), and applied hydraulic pressure difference (0 - 90 bar) was used to evaluate the performance of PRO process of a hollow fiber module. The eff

Problem of water scarcity is becoming common in many parts of the world.  Thus to overcome this problem proper management of water and an efficient irrigation systems are needed.  Irrigation with buried vertical ceramic pipe is known as a very effective in management of irrigation water.  The two- dimensional transient flow of water from a buried vertical ceramic pipe through homogenous porous media is simulated numerically using the software HYDRUS/2D to predict empirical formulas that describe the predicted results accurately.   Different values of pipe lengths and hydraulic conductivity were selected.  In addition, different values of initial volumetric soil water content were assumed in this simulation a

Twisting and coiling actuators (TCAs) are lightweight artificial muscles that can produce large linear contractions while lifting heavy loads with low power. A TCA consists of two or more strings connected to a rotational motor and a load. When activated, the strings twist and coil, causing contraction. This study presents a data-driven framework for modeling TCA behavior using experimental data. Polynomial regression, Support Vector Regression (SVR), and symbolic regression were applied using the motor angle and payload weight as inputs. The models were evaluated under various loads and implemented in a neck-rehabilitation prototype. SVR showed the highest accuracy (RMSE: 6.17 mm upward, 4.98 mm downward); however, it lacks a closed-form e

A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was