This research addresses the employment of public relations for foreign oil corporate social responsibility programs operating in Iraq. It is a study of the programmes of six petroleum companies operating in Basra Governorate, which were selected for research as the highest production of Iraqi oil, as well as its enjoyment of strategic oil stores in Iraq.It contains the largest oil fields operatedby major international companies. This study aims at a number of objectives, notably the following:1)Recognize the most prominent corporate social responsibility projects and initiatives the companies have introduced to the local public.2)Investigate the extent to which the Iraqi publ

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

The electrical and thermal performance of a typical single pass hybrid photovoltaic/thermal (PV/T) air collector is modeled, simulated and analyzed for two selected case studies in Iraq. An improved mathematical thermo-electrical model is derived in terms of design, operating and climatic parameters of the hybrid solar collector to evaluate its important characteristics: collector flow and heat removal factors, PV maximum power point and its temperature coefficient, and overall power and efficiency. Unlike previous PV/T thermal models, the present model is obtained with some additions and corrections in radiation and convection heat coefficients for the top loss and for the air duct with more applicable sky temperature correlation. The well

Glass fiber–reinforced polymer (GFRP) reinforcement provides an effective alternative to conventional steel in concrete structures due to its corrosion resistance. Nevertheless, the lower elastic modulus of GFRP necessitates careful consideration of serviceability behavior in GFRP-reinforced concrete members. This study presents a numerical sectional analysis model for predicting the flexural response and ultimate capacity of hybrid reinforced concrete beams incorporating embedded GFRP profiles in combination with either mild steel or GFRP reinforcement bars under monotonic static loading. The proposed model employs realistic nonlinear stress–strain relationships for concrete and steel, together with secant moduli of elasticity