Different frequency distributions models were fitted to the monthly data of raw water Turbidity at water treatment plants (WTPs) along Tigris River in Baghdad. Eight water treatment plants in Baghdad were selected, with raw water turbidity data for the period (2008-2014). The frequency distribution models used in this study are the Normal, Log-normal, Weibull, Exponential and two parameters Gamma type. The Kolmogorov-Smirnov test was used to evaluate the goodness of fit. The data for years (2008-2011) were used for building the models. The best fitted distributions were Log-Normal (LN) for Al-Karkh, Al-Wathbah, Al-Qadisiya, Al- Dawrah and, Al-Rashid WTPs. Gamma distribution fitted well for East Tigris and Al-Karamah WTPs. As for Al-Wehda WTP Weibull distributions, was the best model. The best fitted distributions were used to forecast ten sets of monthly data for each plant that were compared with the observed data for years (2012-2014). The Kolmogorov-Smirnov test results indicated the capability of these models to produce data that has the same frequency distribution of the observed data. Moreover the frequency of occurrence of the observed and generated series in each plant indicated the capability of the model to produce results with frequency occurrence of probabilities of turbidity values > 50, 80, 100, 120, and 150 NTU.
In this research, the theme for employing a simple and sensitive method is to employ a new Schiff base ligand (N’-(4- (dimethyl amino) benzylidene)-3, 5-dinitrobenzohydrazide) to estimate Ni (II) to form orange complex (N-(4-(dimethyl amino) benzylidene)-3, 5-dinitrobenzohydrazide nickel (II) chloride) in acid medium (hydrochloric acid), it gives an absorption peak at the wavelength 485 nm. The preferred conditions were studied to form the complex and obtain the highest absorbance including concentration of Schiff base ligand, the best medium for complex formation, effects of addition sequence on complex formation, the effect of temperature on the absorbance of the complex formed, and the setting time of the formed complex. The obtained r
... Show MoreThe research included preparation of new iron(II) complexes with mixed ligands including benzilazine(BA) and semicarbazone ligands {benzilsemicarbazone- BSCH or benzilbis(semicarba-zone)- BBSCH2 or salicylaldehydesemicarbazone- SSCH2 or benzoinsemicarbazone- B'SCH2}.by classical and microwave methods. The resulted complexes have been characterized using chemical and physical methods. The study suggested that the above ligands form ionic complexes having formulae [Fe(SCHi)(BA)(Cl)m](Cl)2-m {where SCH, BSCH, BBSCH2, SSCH¬2 or B'SCH2 ligands; m=1 or 2}. Hexacoordinated mononuclear complexes have been investigated by this study and having octahedral geometries. The effect of laser ray type visible region have been studied on solid ligands and
... Show MorePromoting the production of industrially important aromatic chloroamines over transition-metal nitrides catalysts has emerged as a prominent theme in catalysis. This contribution provides an insight into the reduction mechanism of p-chloronitrobenzene (p-CNB) to p-chloroaniline (p-CAN) over the γ-Mo2N(111) surface by means of density functional theory calculations. The adsorption energies of various molecularly adsorbed modes of p-CNB were computed. Our findings display that, p-CNB prefers to be adsorbed over two distinct adsorption sites, namely, Mo-hollow face-centered cubic (fcc) and N-hollow hexagonal close-packed (hcp) sites with adsorption energies of −32.1 and −38.5 kcal/mol, respectively. We establish that the activation of nit
... Show MoreCoupling reaction of 2-amino benzoic acid with 8-hydroxy quinoline gave bidentate azo ligand. The prepared ligand has been identified by Microelemental Analysis,1HNMR,FT-IR and UV-Vis spectroscopic techniques. Treatment of the prepared ligand with the following metal ions (ZnII,CdII and HgII) in aqueous ethanol with a 1:2 M:L ratio and at optimum pH, yielded a series of neutral complexes of the general formula [M(L)2]. The prepared complexes have been characterized by using flame atomic absorption, (C.H.N) Analysis, FT-IR and UV-Vis spectroscopic methods as well as conductivity measurements. The nature of the complexes formed were studied following the mole ratio and continuous variation methods, Beer's law obeyed over a concentration ra
... Show MoreAdvanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
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