Variation orders are an on-going phenomenon in construction and industry projects worldwide, particularly in the province of Sulaimani, where the project's damage from cost and schedule overrun because of variation orders. However, the effect on project costs and time overrun of variation order has yet to be identified. This study evaluates the impact of variation orders on the cost and time off in the Sulaimani governorate. Two hundred twenty-eight projects from various construction sectors built between 2007-2012 were adopted to calculate the contract cost and schedule overruns due to variation orders. Data analysis was applied in the study were descriptive statistics. One-way ANOVA was also applied to determine whether the overrun of project cost and schedule significantly varied depending on project type, size, duration, location, and awarded years. The findings indicated that cost overruns are very common due to variation orders. 95.6% of the projects were studied being impacted, and overrun in project cost are also huge, with 16%. Time also overruns more common than cost overruns due to the variation orders. 98.7% of the projects were studied in Sulaimani were affected by time overrun with an average of 46.3% of initial duration observed. Findings also indicated that two out of five parameters measured in the analysis had a significant correlation with project cost overruns. Three out of five considered variables correlated with construction time overruns.
This researd exhibit's a method to determine the change in Gibbs function,(enthai py,entropy. and specific heat capacity) tor monovariant heterogeneous equilibria .The thermodynamical quan.tities were obtained jndirectly with m the measurment of temperature dependent on eql,lilibrium system.
Research objective to identify the degree of environmental sustainability values of the student-teacher in the College of Education for Pure Sciences. In this research the methodology of relational descriptive research was adopted, and the research sample consisted of (116) students from the College of Education for Pure Sciences / Ibn Al-Haytham / University of Baghdad From the Department of Chemistry (fourth stage), that is, 54% of the research community were randomly selected. The research tool was prepared, represented by a measure of environmental sustainability values of (20) items, the results of the research showed: The poor degree of environmental sustainability values. The Statistical Portfolio of Social Sciences (SPSS) was adopte
... Show MoreAn assembled pulsed Nd:YAG laser-robot system for spot welding similar and dissimilar metals is presented in this paper. The study evaluates the performance of this system through investigating the possibility and accuracy of executing laser spot welding of 0.2 mm in thickness stainless steel grade AISI302 to 0.5 mm in thickness low carbon steel grade AISI1008. The influence of laser beam parameters (peak power, pulse energy, pulse duration, repetition rate, and focal plane position on the final gained best results are evaluated. Enhancement of the experimental results was carried by a computational simulation using ANSYS FLUENT 6.3 package code.
This study is dedicated to solving multicollinearity problem for the general linear model by using Ridge regression method. The basic formulation of this method and suggested forms for Ridge parameter is applied to the Gross Domestic Product data in Iraq. This data has normal distribution. The best linear regression model is obtained after solving multicollinearity problem with the suggesting of 10 k value.
In this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes
This research includes a detaile description of new species Rhyncomya irakensis sp. nov.
from Iraq.
Localities distribution, host plants and data of collection were recorded.
This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur
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