An experimental study was performed to estimate the forced convection heat transfer performance and the pressure drop of a single layer graphene (GNPs) based DI-water nanofluid in a circular tube under a laminar flow and a uniform heat flux boundary conditions. The viscosity and thermal conductivity of nanofluid at weight concentrations of (0.1 to 1 wt%) were measured. The effects of the velocity of flow, heat flux and nanoparticle weight concentrations on the  enhancement of the heat transfer are examined. The Nusselt number of the GNPs nanofluid was enhanced as the heat flux and the velocity of flow rate  increased, and the maximum Nusselt number  ratio (Nu nanofluid/ Nu base fluid)   and thermal performance factor

Copper and Zinc powders with different particle sizes were subjected to sieving of range (20-100?m) and He-Ne laser system to determine the particle size . 1wt% from each powders was blended carefully with 99wt% from Iraqi oil . Microscopic examination were carried for all samples to reveal the particle size distribution . XRF intensity measurements were conducted for all suspended samples , and the relation between XRF intensity and the particle size was found .

One of the goals of adding adjuvants to agricultural spray solutions is to enhance the droplet size characteristics of this spray. Droplet size, in turn, has an influence in the deposited spray quality, in addition to the drift and losses of spray to off-target places. The aim of this research was to evaluate the effect of adding adjuvants to two types of water from different sources on the droplet size characteristics. Two types of adjuvants were employed in the tests: the active substance content of the first adjuvant was a 50% aqueous solution of sodium salt of alkylbenzenesulfonic acid—10% (HY), whereas the second was from rapeseed oil (natural origin)—85% (OL). Both adjuvants were tested in two concentrations: the first was

By driven the moment estimator of ARMA (1, 1) and by using the simulation some important notice are founded, From the more notice conclusions that the relation between the sign   and moment estimator for ARMA (1, 1) model that is: when the sign is positive means the root      gives invertible model and when the sign is negative means the root      gives invertible model. An alternative method has been suggested for ARMA (0, 1) model can be suitable when