Preparation and Characterization of Maleate, Tartarate,and Phthalate Modified Pectin

Nano γ-Al₂O₃ support was prepared by co-precipitation method by using different calcination temperatures (550, 600, and 750) ^oC. Then nano NiMo/γ-Al₂O₃ catalyst was prepared by impregnation method were nickel carbonate (source of Ni) and ammonium paramolybdate (source of Mo) on the best prepared nano γ-Al₂O₃ support at calcination temperature 550 ^oC. Make the characterizations for prepared nano γ-Al₂O₃ support at different temperatures and for nano NiMo/γ-Al₂O₃ catalyst like X-ray diffraction, X-ray fluorescent, AFM, SEM, BET surface area, and pore volume.

The N

Incremental sheet metal forming process is an advanced flexible manufacturing process to produce various 3D products without using dedicated tool as in conventional metal forming. There are a lot of process parameters that have effect on this process, studying the effect of some parameters on the strain distributions of the product over the length of deformation is the aim of this study.

In order to achieve this goal, three factors (tool forming shape, feed rate and incremental step size) are examined depending on three levels on the strain distributions over the wall of the product. Strain measurement was accomplished by using image processing technique using MATALB program. The significance of the control factors are explored u

The regression analysis process is used to study and predicate the surface response by using the design of experiment (DOE) as well as roughness calculation through developing a mathematical model. In this study; response surface methodology and the particular solution technique are used. Design of experiment used a series of the structured statistical analytic approach to investigate the relationship between some parameters and their responses. Surface roughness is one of the important parameters which play an important role. Also, its found that the cutting speed can result in small effects on surface roughness. This work is focusing on all considerations to make interaction between the parameters (position of influenc

A flexible pavement structure usually comprises more than one asphalt layer, with varying thicknesses and properties, in order to carry the traffic smoothly and safely. It is easy to characterize each asphalt layer with different tests to give a full description of that layer; however, the performance of the whole; asphalt structure needs to be properly understood. Typically, pavement analysis is carried out using multi-layer linear elastic assumptions, via equations and computer programs such as KENPAVE, BISAR, etc. These types of analysis give the response parameters including stress, strain, and deflection at any point under the wheel load. This paper aims to estimate the equivalent Resilient Modulus (MR) of the asphalt concrete

A flexible pavement structure usually comprises more than one asphalt layer, with varying thicknesses and properties, in order to carry the traffic smoothly and safely. It is easy to characterize each asphalt layer with different tests to give a full description of that layer; however, the performance of the whole; asphalt structure needs to be properly understood. Typically, pavement analysis is carried out using multi-layer linear elastic assumptions, via equations and computer programs such as KENPAVE, BISAR, etc. These types of analysis give the response parameters including stress, strain, and deflection at any point under the wheel load. This paper aims to estimate the equivalent Resilient Modulus (MR) of the asphalt concrete