Abstract

Stainless steel (AISI 304) has good electrical and thermal conductivities, good corrosion resistance at ambient temperature, apart from these it is cheap and abundantly available; but has good mechanical properties such as hardness. To improve the  hardness and corrosion resistance of stainless steel its surface can be modified by developing nanocomposite coatings applied on its surface. The main objective of this paper is to study effect of electroco-deposition method on microhardness and corrosion resistance of stainless steel, and to analyze effect of nanoparticles (Al₂O₃, ZrO₂ , and SiC)  on properties of composite coatings. I

A cantilever beam is made from composite material which is consist of (matrix: polyester) and (particles: Silicon-Carbide) with different volume fraction of particles. A force is applied at the free end of beam with different values. The experimental maximum deflection of beam which occurs at the point of the applied load is recorded. The deflection and slope of beam are analyzed by using FEM modeling. MATLAB paltform is built to assemble the equations, vector and matrix of FEM and solving the unknown variables (deflection and slope) at each node. Also ANSYS platform is used to modeling beam in finite element and solve the problem. The numerical methods are used to compare the results with the theoretical and experimental data. A good ag

Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

The depletion of petroleum reserves and increasing environmental concerns have driven the development of eco-friendly asphalt binders. This research investigates the performance of natural asphalt (NA) modified with waste engine oil (WEO) as a sustainable alternative to conventional petroleum asphalt (PA). The study examines NA modified with 10%, 20%, and 30% WEO by the weight of asphalt to identify an optimal blend ratio that enhances the binder’s flexibility and workability while maintaining high-temperature stability. Comprehensive testing was conducted, including penetration, softening point, viscosity, ductility, multiple stress creep recovery (MSCR), linear amplitude sweep (LAS), energy-dispersive X-ray spectroscopy (EDX), F

In this research we present An idea of setting up same split plots experiments in many locations and many periods by Latin Square Design. This cases represents a modest contribution in area of design and analysis of experiments. we had written (theoretically)  the general plans, the mathematical models for these experiments, and finding the derivations of EMS for each component (source) of sources of variation of the analysis of variance tables which uses for the statistical analysis for these expirements

Rapid worldwide urbanization and drastic population growth have increased the demand for new road construction, which will cause a substantial amount of natural resources such as aggregates to be consumed. The use of recycled concrete aggregate could be one of the possible ways to offset the aggregate shortage problem and reduce environmental pollution. This paper reports an experimental study of unbound granular material using recycled concrete aggregate for pavement subbase construction. Five percentages of recycled concrete aggregate obtained from two different sources with an originally designed compressive strength of 20–30 MPa as well as 31–40 MPa at three particle size levels, i.e., coarse, fine, and extra fine, were test