In this study, several ionanofluids (INFs) were prepared in order to study their efficiency as a cooling medium at 25 °C. The two-step technique is used to prepare ionanofluid (INF) by dispersing multi-walled carbon nanotubes (MWCNTs) in two concentrations 0.5 and 1 wt% in ionic liquid (IL). Two types of ionic liquids (ILs) were used: hydrophilic represented by 1-ethyl-3-methylimidazolium tetrafluoroborate [EMIM][BF4] and hydrophobic represented by 1-hexyl-3-methylimidazolium hexafluorophosphate [HMIM][PF6]. The thermophysical properties of the prepared INFs including thermal conductivity (TC), density and viscosity were measured experimentally. The TC measurement showed an enhancement of about 3% for INF and of 1% MWCNT in [EMIM][BF4] at a temperature of 298.15 K: the TC was 0.186 W/m.K, the kinematic viscosity was 100 centistokes (cSt), and the density was 1.283 g.cm−3. On the other hand, the TC of 1% MWCNT in [HMIM][PF6] INF enhanced by 5%. In this case, at a temperature of 298.15 K, the TC was 0.158 W/m, the kinematic viscosity was 1200 cSt, and the density was 1.294 g.cm−3. Furthermore, the stability of the prepared INFs was measured using the zeta potential method after 28 days of preparation. The results show very good dispersion of the nanoparticles in the ILs for all the prepared INFs. The zeta potential was -69.30 mV and - 45.34 mV for 0.5% and 1% MWCNT in [EMIM][BF4], respectively. On the other hand, zeta potential was -51.78 and -46.67 mV for 0.5% and 1% MWCNT in [HMIM][PF6], respectively. According to the obtained results, the preferable INFs to use as a cooling medium at 25 °C was the INF of 1 wt% MWCNT in [EMIM][BF4], since it provides better thermophysical properties than the other prepared INFs.
The study area is located in the eastern part of the Diyala Governorate close to the Iraqi-Iranian border. This study was set to investigate the hydrogeological calculations of northeast of Qazaniyah wells where the groundwater moves in directions of from the northeastern parts towards the southwestern par, that is, the same direction of the topography and the same direction of the tendency of the layers t. The study‘s region is characterized by visible geological layers or those that can be penetrated to a reasonable depth by wells which are sedimentary rocks deposited in continental or semi-continental conditions in the bays. From the study of the hydraulic properties of the two hydrogeological and exemplary systems, the values of tr
... Show MoreIn this paper, author’s study sub diffusion bio heat transfer model and developed explicit finite difference scheme for time fractional sub diffusion bio heat transfer equation by using caputo fabrizio fractional derivative. Also discussed conditional stability and convergence of developed scheme. Furthermore numerical solution of time fractional sub diffusion bio heat transfer equation is obtained and it is represented graphically by Python.
Increased downscaling of CMOS circuits with respect to feature size and threshold voltage has a result of dramatically increasing in leakage current. So, leakage power reduction is an important design issue for active and standby modes as long as the technology scaling increased. In this paper, a simultaneous active and standby energy optimization methodology is proposed for 22 nm sub-threshold CMOS circuits. In the first phase, we investigate the dual threshold voltage design for active energy per cycle minimization. A slack based genetic algorithm is proposed to find the optimal reverse body bias assignment to set of noncritical paths gates to ensure low active energy per cycle with the maximum allowable frequency at the optimal supply vo
... Show MoreFacial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f
... Show More