Tikrit Journal of Engineering Sciences

The current study investigates the structural performance of lightweight concrete panels produced using ferrocement (wire-meshed), hybrid (wire-meshed and steel fiber), and sponge-cementitious immersed layers. These panels presented a novel approach to producing a lightweight concrete panel to be used as an alternative to the traditional Jack-arch masonry slab system. The panels were made in dimensions of 600mm length(l), 200mm width (w), and 54mm thickness (h), using locally available sponge materials and super cementitious mortar incorporated with ferrocement layers. To determine the proper thickness of a sponge layer to be used in panel manufacturing, a material characterization was performed. The obtained results from the material characterization indicated a significant reduction in the density compared with the conventional Jack-arch slab system. The sponge core thickness positively affected the developmental compressive strength. For all sponge thickness modes, the density of developed sponging concrete was within the acceptance criteria of lightweight structural concrete. The average density of developing sponge concrete was 15.6 kN/m3, and the average absorption ratio was 14.78 %, while the density of cementitious mortar was 21.96 kN/m3. As for the structural performance of the resulting lightweight concrete panel, the panel with a hybrid layer (incorporating short steel fiber with steel wire mesh) 10mm layer was the best reinforcement method compared with reinforcing with the wire mesh (ferrocement) solely. Furthermore, the findings of this study depicted that the bending moment capacity of the developed lightweight concrete panel was higher than the conventional Jack-arch masonry usually used in traditional residential housing and lower density.

The severity of traffic congestion has increased in Baghdad city and influenced the public’s perception of the community. Extended travel time is experienced by users of the urban street system, so optimal traffic operation with a coordinated traffic signal system becomes necessary. Also, it is needed to alleviate congestion and progress traffic movement along the urban corridor. This study aims to evaluate and optimize traffic signal timing for selected intersections on Palestine arterial corridor and apply the coordinated signal system to reduce the users’ travel time on the selected urban corridor. Analyzing and evaluating congested signalized intersections using Synchro (ver.9) (Al-Nakhala intersection, Al-Sakhra intersection, and Beirut intersection) were performed. Also, their adopted strategies for improving traffic performance and reducing delays were provided. The overall assessment in terms of the level of service for the current traffic states is (LOS F) with an average control delay of (197.2, 166.8, and 262.3) sec/veh. for the Al-Nakhala, Al-Sakhra, and Beirut intersections respectively. The queue length appears after two cycles, becoming more severe congestion at intersections under oversaturated traffic conditions. The performance operation efficiency improved by reducing the control delay from (197.2 to 88) sec/veh, (166.8 to 46) sec/veh, and (262.3 to 76) sec/veh for the Al-Nakhala, Al-Sakhra, and Beirut intersections respectively. Even at high volume and oversaturated conditions, the blocked intersections were effectively alleviated. Finally, it was observed that the proposed signal coordination, built on standard actuated control significantly performed along the urban corridor, reducing vehicles’ delay. However, there are still concerns regarding the flow-to-capacity ratio (v/c ratio is still greater than 1), and the level of service is still in poor conditions (LOS E) for Beirut and (LOS F) for Al-Nakhala intersections. The application of signal coordination improved traffic progression by reducing travel time, and vehicle delay and alleviating blocked intersections.

Groundwater quality is a topic that concerns millions of people because it is essential for agriculture and drinking. As a result, this paper aims to assess the groundwater quality of the northern region of Salah al-Din Governorate (Bayji as a case study) and the health risks posed by nitrate ions to infants, children, and adults living in villages. Samples were taken from 30 wells in the industrial district of the Baiji area in April 2022. Two water quality indices were applied to determine whether groundwater can be used for drinking and irrigation or not. The drinking water quality index (DWQI) found that 96.67% of the water samples were poor, and 3.33% were abysmal. Based on the values of the irrigation water quality index (IWQI), the tested water quality ranged from medium to high. In addition, the study required assessing the health risks posed by nitrate ions in the groundwater to residents. According to the oral hazard quotient (HQoral) calculation results, 93.33 and 96.67 % of the water samples were below one, indicating no health risks for children or infants. However, 6.67 and 3.33% of the total samples were above one, indicating health risks. All HQoral values were less than one when it came to the health effects of nitrates on adults, indicating that there were no risks. Because the Hazard Quotient (HQdermal) through the dermal pathway was less than one, showering posed no health risks for adults, children, or infants.

Different properties of Self-compacting concrete (SCC) containing plastic waste aggregate (PWA) have been experimentally studied by researchers. However, most of these works focused on examining the properties of one type of PA. In the present paper, the influence of four different types; namely Polyvinyl chloride (PVC), Heat-treated plastic (PEL), Mixed plastic (Mix), and polyethylene terephthalate (PET) as a fine aggregate (FA) replacement; on fresh properties of SCC was examined. Results indicated that changing the PWA geometry influenced different properties of SCC. All concrete samples with PVC and PEL plastic were in the range of EFNARC classification (classified in VS2/PA2 class), causing no blocking in V-funnel and L-box test. Meanwhile, mixed plastic up to 7.5% and PET up to 5% fall within VS2/VF2 class; otherwise, the mixture was outside the range of EFNRAC standards. The best plastic waste aggregate regarding all new properties was PVC confirming all requirements for a successful SCC, causing no blocking or segregation. Thus, 10% was selected as the optimum percentage. Furthermore, PET was the worst, for PET-7.5% significant increase in the V-funnel (57.6 sec) and reduction in H2/H1 ratio (0.58) was obtained besides blocking in L-box tests, segregation, and bleeding in slump flow test. Thus, more than 5% is not recommended when using PET in Self-compacting concrete.

Recently, attention has been paid to nanofluids due to their contribution to enhancing heat and mass transfer in different industrial applications. Consequently, a nanofluid composed of SiO2 nanoparticles (NPs) and distilled water as base fluid was adopted as a solvent to promote the removal of impurities, methanol, and glycerol, from crude biodiesel using liquid-liquid extraction in the membrane contactor. The presence of NPs significantly enhanced the methanol and glycerol removal efficiency. The optimum concentration of NPs in nanofluid was 0.01 wt%. It was found that adding 0.01 wt% of NPs to the distilled water increased the methanol removal efficiency from 76.4% to 93.1% upon using crude biodiesel with methanol and glycerol content of 2000 ppm and 1 wt%, respectively, at a constant flow rate of solvent and biodiesel of 200 mL min⎼1. Meanwhile, the glycerol removal efficiency increased from 76.2% to 94.5%. The results revealed that the solvent flow rate was the controlling mass transfer step.

In this study, the oscillation technique was applied in a multi-tube heat exchanger with baffles. The Nusselt number was investigated in the heat exchanger (HE) over a wide range of operating conditions, Reynolds number (Re =205-3200), and oscillatory flow Reynolds number (Reo =0-3800). The results showed a significant enhancement in the tube-side Nusselt number, Nu. 5-fold heat transfer enhancement was achieved at maximum oscillatory and flow rates, the maximum Nu=180 at Re =1500 and Reo=3800. The flow rate had more impact on the heat transfer enhancement than the oscillatory flow by 1.25 when Re>1000. The thermal performance of the heat exchanger, TH, was also evaluated. TH decreased with the increasing flow rate and oscillatory flow due to the increase in the ΔP due to the increase in the mixing intensity. A high value of the thermal performance, TH=4.5, was achieved at Re=205, Reo=1500. According to the literature, this TH value indicated a significant improvement in heat transfer enhancement.

This study investigates the behavior of SCC hollow beams reinforced by GFRP bars, which have lighter weight, lower cost, and high corrosion resistance compared to conventional steel reinforcement. Eighteen SCC beams with dimensions of (1200×225×150) mm were divided into three groups. Each group had 5-beams according to the types of stirrups (steel, (full, 2L-, 4bar, and 4U) GFRP)) stirrups in all groups with three reference beams. The longitudinal reinforcement was 6Ø10mm steel bars, 6Ø10mm GFRP bars, and (3steel+ 3GFRP) bars for the first, second, and third groups respectively. All beams were SCC concrete with a longitudinal rectangular hollow (50×100) mm. The results showed that the ultimate load of a hollow beam was decreased by the ratio of (13%, 11%, and 8%) compared to the first, second, and third groups respectively. In the first group, the ultimate load of a hollow beam reinforced with (steel stirrups) increased by about (3%), (6%), (21%), and (11%) compared to the hollow beam reinforced with (full, 2L, 4bar, 4U-bar) GFRP stirrups respectively. In the second group, the ultimate load of a hollow beam reinforced with (steel stirrups) increased by about (4%), (9%), (49%), and (14%) compared to the hollow beam reinforced with (full, 2L, 4bar, 4U-bar) GFRP stirrups respectively. In the third group, the ultimate load of a hollow beam reinforced with (steel stirrups) increased by about (3%), (6%), (23%), and (14%) compared to the hollow beam reinforced with (full, 2L, 4bar, 4Ubar) GFRP stirrups respectively. The best case, according to the ultimate load among the stirrups, was steel stirrups, which gave the highest shear strength compared to the other stirrups because of the low elasticity of the GFRP stirrups. While compared to the other GFRP stirrups, GFRP full stirrups had the highest shear strength because there is one connection point compared to two or four connecting points for other types.

Hallucinations and delusions are symptoms of schizophrenia. Due to persistent auditory and visual hallucinations, a person with schizophrenia cannot process reality clearly. Abnormal brain activity results from delusion and hallucination. During the capture of EEG signals, aberrant behavior is detected. The EEG electrodes do not well detect the brain's current distribution. Schizophrenia causes the EEG signal to be warped and less sensitive, which results in incorrect interpretation of brain activity. In this paper, an EEG electrode constructed of graphene nanopowder is suggested that is sensitive to the brain's weak electrical activity. The cold spray approach created graphene EEG electrodes, improving the material bonding and chemical characteristics. By obtaining EEG readings from schizophrenic patients, the sensitivity of the graphene electrode was assessed. The EEG signal was collected from the subject when taking part in cognitive tests like question sessions and numerical problems. Several neural networks (NN) algorithms can be used to identify hallucination and delusion aspects in EEG recordings. Further details regarding the hallucination and delusion aspects in the EEG signal were provided by the NN, showing a Graphene electrode. As compared to other NN models, the comparative study of several NN models revealed that the BFGS quasi-Newtonian backpropagation algorithm accurately recognized hallucination and delusion features.

This work deals with a composite catalyst preparation, Pt/HY-H-Mordenite, for isomerization of Iraqi light naphtha produced from Baiji North Refinery in a pilot plant fixed bed reactor under operating conditions with the following ranges: temperature 150–250 °C, LHSV 2.46–4.7 hr-1, pressure 6 bar, and hydrogen to hydrocarbon ratio 3.7 mol/mol. The prepared nano-silica, Na-mordenite, H-mordenite, and Pt/HY-H-Mordenite catalysts were described by X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), Fourier transform infrared spectroscopy (FTIR), and Brunauer-Emmett-Teller (BET) surface area analysis. The investigation results showed that the light naphtha isomerization conversion and yield increased with increasing the temperature and decreasing the liquid-hour space velocity. The highest conversion and yield, obtained at 250 °C and LHSV of 2.46 hr-1, were 89.38% and 76.36%, respectively.

Recently, the world has been moving towards reusing wastes in many industrial applications, such as buildings and automotive, to eliminate the environmental pollution impact due to increasing waste worldwide. Besides, waste reuse also leads to cost savings and improves sustainability. Therefore, this short review aims to present and discuss the recently used methods of utilizing feather waste as sustainable and renewable insulation instead of traditional petroleum-derived materials. The father's low thermal conductivity ranges from 0.024 W/(m. K) to 0.034 W/(m. K), and it's chemical composition and microstructure effectively trap air and produce a good barrier. So, feather waste fibers can be used as an effective thermal and acoustic insulation material with the same or better performance than commercially available products. However, several significant barriers and limitations associated with the manufacturing process of feathers insulations were identified in this review. These limitations make the commercial development of insulation materials based on feather waste a challenge. They need to be appropriately addressed to realize the potential of feather waste as a reliable insulation material.

The study of flood risks has a fundamental role in ensuring the safety of cities near rivers and drawing up plans to protect them during future floods. This study aims to manage potential flood risks, and Tikrit city was used as a case study. The daily discharge of the Tigris River in the study area was provided by the Iraqi Ministry of Water Resources from 2019 to 2022. The HEC-RAS software was utilized to build a 2-D flood model to simulate potential flood scenarios. First, the model was calibrated by adjusting the value of Manning's coefficient (n), and it was found that n = 0.031 reflects the nature of the region because the Nash-Sutcliff Error (NSE) was 0.93. Then, the efficiency of the 2-D flood model was verified by comparing the model’s results with the study area’s satellite images, and the results showed a great match. Following that, the 2-D model was used under different flooding scenarios. The results showed that the size of areas exposed to flooding increased with the discharges passing through the Tigris River. For instance, increasing the discharge to 800m3/s increased the flooded areas by 13.7%, while increasing the discharge to 1500 m3/s increased the flooded areas by 90.7 % compared to the river’s normal flow. Also, the results showed that the eastern regions of the riverbanks are more vulnerable to flooding than the western side because the ground levels are low on the eastern side compared to the western part of the riverbanks.

The Internet of Things (IoT) has recently become an essential ingredient of human life. The main critical challenges that confront IoT are security and protection. Several methods have been developed to protect the IoT; among these methods is Intrusion Detection System (IDS) Deep Learning-based. On the other hand, these types of IDS have a complex operation that takes a long time when applied on IoT devices and is inconvenient for a massive system that includes many connected devices. Thus, this paper suggested a Lightweight Intrusion Detection System (LIDS) IoT model that depends on deep learning using a Multi-Layer Perceptron (MLP) network. LIDS has the following characteristics lightweight, high accuracy, high speed in detection, and deals with a few features in MQTT protocol. The MQTTset dataset was used in training, validating, and testing the proposed model to investigate the performance of the proposed LIDS. The achieved performance ratios for the proposed LIDS, as measured by accuracy and F1-score. The experiment results showed that for the balanced MQTTset dataset, the number of obtained features was 15 with accuracy (95.06) and F1_score (95.31). Also, for the imbalanced MQTTset, the number of obtained features was 12 with accuracy (96.97) and F1-score (98.24). The obtained results have shown the deep learning efficiency role in improving the accuracy of an intrusion detection model by approximately 3.5% compared to other methods in the literature. In addition, the proposed methods reduced the number of features by around 50% of the total number of features, leading to a LIDS operating in a constrained environment.

In this study, a model was proposed based on calculating the total surface area of aggregate to assess fresh density, compressive, and splitting tensile strengths of plastic aggregate (PA) recycled concrete. The key factor is the change in the total surface area of the natural aggregate by the PA. For a given PA volume, the change in the property could be assessed. The prediction well depends on the natural and plastic aggregates distribution size, specific gravity, and bulk density. The proposed model prediction was accurate when applied to high-strength, and lightweight concretes. The reason is attributed to the relatively good bond between PA and hardened cement paste in these concretes. However, for the majority of concrete mixes investigated, the model moderately underestimated strength loss, and this underestimation could be attributed to the PA- hardened cement paste bond deficiency. An attempt was made to assess the bond deficiency parameter for a more accurate prediction.