Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the deterioration models' application showed that NNDM gave the highest overall prediction efficiency of 93.6% by adapting the confusion matrix test, while multinomial logistic regression was inconsistent with the data. The error in prediction of related model was due to its inability to reflect the dependent variable (condition classes) ordered nature.
As tight gas reservoirs (TGRs) become more significant to the future of the gas industry, investigation into the best methods for the evaluation of field performance is critical. While hydraulic fractured well in TRGs are proven to be most viable options for economic recovery of gas, the interpretation of pressure transient or well test data from hydraulic fractured well in TGRs for the accurate estimation of important reservoirs and fracture properties (e.g. fracture length, fracture conductivity, skin and reservoir permeability) is rather very complex and difficult because of the existence of multiple flow profiles/regimes. The flow regimes are complex in TGRs due to the large hydraulic fractures n
Abstract
The Non - Homogeneous Poisson process is considered as one of the statistical subjects which had an importance in other sciences and a large application in different areas as waiting raws and rectifiable systems method , computer and communication systems and the theory of reliability and many other, also it used in modeling the phenomenon that occurred by unfixed way over time (all events that changed by time).
This research deals with some of the basic concepts that are related to the Non - Homogeneous Poisson process , This research carried out two models of the Non - Homogeneous Poisson process which are the power law model , and Musa –okumto , to estimate th
... Show MoreIn this paper, we investigate two stress-strength models (Bounded and Series) in systems reliability based on Generalized Inverse Rayleigh distribution. To obtain some estimates of shrinkage estimators, Bayesian methods under informative and non-informative assumptions are used. For comparison of the presented methods, Monte Carlo simulations based on the Mean squared Error criteria are applied.
Computer simulations were carried out to investigate the dependence of the main perturbation parameters (Sun and Moon attractions, solar radiation pressure, atmosphere drag, and geopotential of Earth) on the orbital behavior of satellite. In this simulation, the Cowell method for accelerations technique was adopted, the equation of motion with perturbation was solved by 4th order Runge-Kutta method with step (1/50000) of period to obtain the state vectors for position and velocity. The results of this simulation have been compared with data that available on TLEs (NORD data in two line elements). The results of state vectors for satellites (Cartosat-2B, Gsat-14 an
In the petroleum industry, multiphase flow dynamics within the tubing string have gained significant attention due to associated challenges. Accurately predicting pressure drops and wellbore pressures is crucial for the effective modeling of vertical lift performance (VLP). This study focuses on predicting the multiphase flow behavior in four wells located in the Faihaa oil field in southern Iraq, utilizing PIPESIM software. The process of selecting the most appropriate multiphase correlation was performed by utilizing production test data to construct a comprehensive survey data catalog. Subsequently, the results were compared with the correlations available within the PIPESIM software. The outcomes reveal that the Hagedorn and Brown (H
... Show MoreIn this paper has been one study of autoregressive generalized conditional heteroscedasticity models existence of the seasonal component, for the purpose applied to the daily financial data at high frequency is characterized by Heteroscedasticity seasonal conditional, it has been depending on Multiplicative seasonal Generalized Autoregressive Conditional Heteroscedastic Models Which is symbolized by the Acronym (SGARCH) , which has proven effective expression of seasonal phenomenon as opposed to the usual GARCH models. The summarizing of the research work studying the daily data for the price of the dinar exchange rate against the dollar, has been used autocorrelation function to detect seasonal first, then was diagnosed wi
... Show MoreThis research deals with a part of our heritage and Arab culture, which is the poetry of contemporary Islamic poets, especially the poetry that was said in the mother in contemporary Islamic poetry, when extrapolating the offices of some contemporary Islamic poets found a clear presence of the mother, and during the search for the subject or its I found that the subject did not receive research and study, although the bureaus of contemporary Islamic poets included in it a huge amount of verses in which they stood at the mother Pharthua, and expressed their feelings and emotions towards them, and accordingly this research tagged (mother in contemporary Islamic poetry _ Dr Artistic models in models of contemporary Islamic poetry) to stand
... Show MoreThe region-based association analysis has been proposed to capture the collective behavior of sets of variants by testing the association of each set instead of individual variants with the disease. Such an analysis typically involves a list of unphased multiple-locus genotypes with potentially sparse frequencies in cases and controls. To tackle the problem of the sparse distribution, a two-stage approach was proposed in literature: In the first stage, haplotypes are computationally inferred from genotypes, followed by a haplotype coclassification. In the second stage, the association analysis is performed on the inferred haplotype groups. If a haplotype is unevenly distributed between the case and control samples, this haplotype is labeled
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