Zainab S. Al-Khafaji

Bio: Zainab S. Al-Khafaji is an academic researcher from Ministry of Oil. The author has contributed to research in topics: Materials science & Cement. The author has an hindex of 9, co-authored 28 publications receiving 391 citations. Previous affiliations of Zainab S. Al-Khafaji include Al Turath University College & Islamic University.

Ultrasonic-Electrocoagulation method for nitrate removal from water

Abstract: Water contamination with nitrates is a serious problem due to the detrimental effects of nitrates on both human life and the global ecosystem; therefore, it is essential to remove nitrates using efficient methods. Accordingly, various methods have been used to treat nitrate-containing solutions, but recent studies focused on electrocoagulation (ELE) as it produces high quality water at low cost and it is environmentally friendly. However, passive layers are growing on the aluminum anodes after short time of treatment, which substantially affects the efficiency of ELE. In this investigation therefore, ultrasonic filed was used to remove these passive layers, and consequently improves the efficiency of ELE. This new method, ultrasonic-assisted ELE (U-ELE), was used to remove nitrates from water under various operational conditions. In particular, the impacts of water initial pH (WIP) (4.0-8.0), applied current densities (ACD) (6.0-9.0 mA/cm2), flow rates (FR) (60-100 ml/min), and initial nitrate concentrations (INC) (100-200 mg/L), which were optimized using the Central Composite Design (CCD). The ultrasonic irradiation time (UT) has been kept at 10 minutes for all experiments. The best possible removal of nitrate using only ELE method was about 77% at WIP of 6, UT of 10 minutes, FR of 40 ml/min, INC of 150 mg/l and ACD of 7.5mA/cm2. However, it was found that exerting ultrasonic for 10 minutes, U-ELE method, has increased nitrates removal to 87.80% under the same conditions of ELE treatment.

The impact of grinding time on properties of cement mortar incorporated high volume waste paper sludge ash

Abstract: Cement is considered a base material in preparing blending mixtures that applying in various projects in the civil engineering field. Nevertheless, the cement production process cause indubitable negative environmental influences such as emitting CO2. The production of cement produces around 7% of the global CO2 emissions. Thus, searching for alternate binders in building processes to minimise or substitute cement has been one of the social problems. A by-product or waste products are among the potential alternatives to the mentioned problem. The present investigation involves the consumption of paper sludge ash (PSA) waste as cement replacement to produce environmentally friendly, cementitious material. Limited studies were addressed the PSA grinding time impact on mortar or concrete properties. Moreover, limited studies replaced the cement with high volume of PSA. Therefore, during this study, the effect of grinding time and replacement level (up to 50%) of the PSA on the surface electrical resistivity and compressive strength of mortar were investigated. Three grinding periods (in addition to without grinding), two replacement levels and three testing ages were considered. The results indicated that grinding the PSA for 10 minutes and use it to replace up to 50% of the cement content have similar mechanical and durability performance to ordinary Portland cement after 28 curing days. This innovative binder will also cause a major difference in decreasing the building materials cost and CO2 emissions.

Reinforced concrete deep beam shear strength capacity modelling using an integrative bio-inspired algorithm with an artificial intelligence model

Abstract: The design and sustainability of reinforced concrete deep beam are still the main issues in the sector of structural engineering despite the existence of modern advancements in this area. Proper understanding of shear stress characteristics can assist in providing safer design and prevent failure in deep beams which consequently lead to saving lives and properties. In this investigation, a new intelligent model depending on the hybridization of support vector regression with bio-inspired optimization approach called genetic algorithm (SVR-GA) is employed to predict the shear strength of reinforced concrete (RC) deep beams based on dimensional, mechanical and material parameters properties. The adopted SVR-GA modelling approach is validated against three different well established artificial intelligent (AI) models, including classical SVR, artificial neural network (ANN) and gradient boosted decision trees (GBDTs). The comparison assessments provide a clear impression of the superior capability of the proposed SVR-GA model in the prediction of shear strength capability of simply supported deep beams. The simulated results gained by SVR-GA model are very close to the experimental ones. In quantitative results, the coefficient of determination (R2) during the testing phase (R2 = 0.95), whereas the other comparable models generated relatively lower values of R2 ranging from 0.884 to 0.941. All in all, the proposed SVR-GA model showed an applicable and robust computer aid technology for modelling RC deep beam shear strength that contributes to the base knowledge of material and structural engineering perspective.

The Environmental Protection Agency

Abstract: The Environmental Protection Agency (EPA) provides access to information on a variety of topics related to the environment and strives to inform citizens of health risks. The EPA also has an extensive library network that consists of 26 libraries throughout the United States, which provide access to a plethora of information to EPA employees, scientists, and researchers. The EPA implemented a reorganization project to digitize their materials so they would be more accessible to a wider range of users, but this plan was drastically accelerated when the EPA was threatened with a budget cut. It chose to close and reduce the hours and services of some of their libraries. As a result, the agency was accused of denying users the “right to know” by making information unavailable, not providing an adequate strategic plan, and discarding vital materials. This case study explores the background of the digitization project, the practices implemented, and the critiques of the project.

Recent Advancements in Non-Destructive Testing Techniques for Structural Health Monitoring

Abstract: Structural health monitoring (SHM) is an important aspect of the assessment of various structures and infrastructure, which involves inspection, monitoring, and maintenance to support economics, quality of life and sustainability in civil engineering. Currently, research has been conducted in order to develop non-destructive techniques for SHM to extend the lifespan of monitored structures. This paper will review and summarize the recent advancements in non-destructive testing techniques, namely, sweep frequency approach, ground penetrating radar, infrared technique, fiber optics sensors, camera-based methods, laser scanner techniques, acoustic emission and ultrasonic techniques. Although some of the techniques are widely and successfully utilized in civil engineering, there are still challenges that researchers are addressing. One of the common challenges within the techniques is interpretation, analysis and automation of obtained data, which requires highly skilled and specialized experts. Therefore, researchers are investigating and applying artificial intelligence, namely machine learning algorithms to address the challenges. In addition, researchers have combined multiple techniques in order to improve accuracy and acquire additional parameters to enhance the measurement processes. This study mainly focuses on the scope and recent advancements of the Non-destructive Testing (NDT) application for SHM of concrete, masonry, timber and steel structures.