Experimental measurements were done for characterizing current-voltage and power-voltage of two types of photovoltaic (PV) solar modules; monocrystalline silicon (mc-Si) and copper indium gallium di-selenide (CIGS). The conversion efficiency depends on many factors, such as irradiation and temperature. The assembling measures as a rule cause contrast in electrical boundaries, even in cells of a similar kind. Additionally, if the misfortunes because of cell associations in a module are considered, it is hard to track down two indistinguishable photovoltaic modules. This way, just the I-V, and P-V bends' trial estimation permit knowing the electrical boundaries of a photovoltaic gadget with accuracy. This measure gives extremely significant data to the plan, establishment, and upkeep of PV frameworks. Three methods, simplified explicit, slope, and iterative, are used to compute two solar models' parameters using MATLAB code. The percentage maximum power errors at (600 and 1000) W/m2 for both current-voltage and power-voltage values with the corresponding measured ones using the slope method are 0.5% and 3% for monocrystalline silicon copper indium gallium di-selenide, respectively. The iterative method is 5 % and 10% for monocrystalline silicon and copper indium gallium di-selenide. Finally, for the simplified explicit 8% and 9%, for monocrystalline silicon and copper indium gallium di-selenide, respectively. The slope method gives more close results with the corresponding measured values than the other two methods for the two PV solar modules used. Consequently, the slope method is less influenced by the meteorological condition.
This research studies the development and synthesis of blended nanocomposites filled with Titanium dioxide (TiO2). Blended nanocomposites based on unsaturated polyester resin (UPR) and epoxy resins were synthesized by reactive blending. The optimum quantity from nano partical of titanium dioxide was selected and different weight proportions 1%, 3%, 5%, and 7% ratios of new epoxy are blended with UPR resin. The dielectric breakdown strength and thermal conductivity properties of the blended nanocomposites were compared with those of the basis material (UPR and 3% TiO2).The results show good compatibility epoxy resins with the UPR resin on blending, dielectric breakdown strength values are higher while thermal conductivity values of
... Show MoreThis paper presents the effect of Cr doping on the optical and structural properties of TiO2 films synthesized by sol-gel and deposited by the dip- coating technique. The characteristics of pure and Cr-doped TiO2 were studied by absorption and X-ray diffraction measurement. The spectrum of UV absorption of TiO2 chromium concentrations indicates a red shift; therefore, the energy gap decreases with increased doping. The minimum value of energy gap (2.5 eV) is found at concentration of 4 %. XRD measurements show that the anatase phase is shown for all thin films. Surface morphology measurement by atomic force microscope (AFM) showed that the roughness of thin films decrease with doping and has a minimum value with 4 wt % doping ratio.
The CuInSe2 (CIS) nanocrystals are synthesized by arrested precipitation from molecular precursors are added to a hot solvent with organic cap- ping ligands to control nanocrystal formation and growth. CIS thin films deposited onto glass substrate by spray - coating, then selenized in Ar- atmosphere to form CIS thin films. PVs were made with power conversion efficiencies of 0.631% as -deposited and 0.846% after selenization, for Mo coated, under AM 1.5 illumination. X-ray diffraction (XRD) and energy dispersive spectroscopy (EDS) analysis it is evident that CIS have the chalcopyrite structure as the major phase with a preferred orientation along (112) direction and the atomic ratio of Cu : In : Se in the nanocrystals is nearly 1 : 1 : 2
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This study is concerned with the estimation of constant and time-varying parameters in non-linear ordinary differential equations, which do not have analytical solutions. The estimation is done in a multi-stage method where constant and time-varying parameters are estimated in a straight sequential way from several stages. In the first stage, the model of the differential equations is converted to a regression model that includes the state variables with their derivatives and then the estimation of the state variables and their derivatives in a penalized splines method and compensating the estimations in the regression model. In the second stage, the pseudo- least squares method was used to es
... Show MoreThroughout this paper we introduce the notion of coextending module as a dual of the class of extending modules. Various properties of this class of modules are given, and some relationships between these modules and other related modules are introduced.
Poverty phenomenon is very substantial topic that determines the future of societies and governments and the way that they deals with education, health and economy. Sometimes poverty takes multidimensional trends through education and health. The research aims at studying multidimensional poverty in Iraq by using panelized regression methods, to analyze Big Data sets from demographical surveys collected by the Central Statistical Organization in Iraq. We choose classical penalized regression method represented by The Ridge Regression, Moreover; we choose another penalized method which is the Smooth Integration of Counting and Absolute Deviation (SICA) to analyze Big Data sets related to the different poverty forms in Iraq. Euclidian Distanc
... Show MoreLet R be a ring with 1 and W is a left Module over R. A Submodule D of an R-Module W is small in W(D ≪ W) if whenever a Submodule V of W s.t W = D + V then V = W. A proper Submodule Y of an R-Module W is semismall in W(Y ≪_S W) if Y = 0 or Y/F ≪ W/F ∀ nonzero Submodules F of Y. A Submodule U of an R-Module E is essentially semismall(U ≪es E), if for every non zero semismall Submodule V of E, V∩U ≠ 0. An R-Module E is essentially semismall quasi-Dedekind(ESSQD) if Hom(E/W, E) = 0 ∀ W ≪es E. A ring R is ESSQD if R is an ESSQD R-Module. An R-Module E is a scalar R-Module if, ∀ , ∃ s.t V(e) = ze ∀ . In this paper, we study the relationship between ESSQD Modules with scalar and multiplication Modules. We show that
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