3-Dimensional Nonlinear Finite Element Analysis of both Thermal and Mechanical Response of Friction Stir Welded 2024-T3 Aluminum Plates

This paper attempt to predict numerically both the temperature distribution during friction stir welding process of 2024-T3 aluminium plates and the resulting thermal residual stress by sequentially coupling the thermal histories into the mechanical model assuming elastic-perfectly plastic metal behaviour in accordance with the classical metal plasticity theory. The commercial code ANSYS 14 is used in Thermomechanical modelling of friction stir welding of aluminium 2024-T3.  Heat input from the tool shoulder and the tool pin are considered in the finite element analysis model. A moving heat source with a heat distribution simulating the heat generated from the friction between the tool shoulder and the work piece is used in the heat transfer analysis The longitudinal stress components are found to be the highest tensile stress components and correspond to the temperature profiles within the heat affected zone of the weld. The through-thickness (normal) stresses are found to be negligible compared with the longitudinal and transverse stress components. To facilitate simulation runs of the proposed model an APDL (ANSYS Parametric Design Language) code is developed to extract the thermal history and the subsequent thermal stresses. The effects of various heat transfer conditions at the bottom surface of the workpiece, thermal contact conductances at the work-piece and the backing plate interface on the thermal profile in the weld material are taken into considerations. The results of the simulation are compared to other published experimental results and the agreement was good. Keywords: Friction stir welding, Finite element, Three dimensional modeling, Thermal stresses

Utilization of High Volume Fraction of Binary Combinations of Supplementary Cementitious Materials in the Production of Reactive Powder Concrete

The reactive powder concrete (RPC) is one of the special concrete types that characteristics with high cement content which means high production cost and CO2 emissions to the atmosphere. Therefore, to enhance the environment as well as to develop green RPC, alternatives to cement, such as supplementary cementitious materials (SCMs) were used. Limited studies addressed the use of a high volume fraction of SCMs as a binary combination in the production of RPC. Thus, this study aims to replace a high percentage of cement (50%) with binary combinations of silica fume (SF), type F fly ash (FA) and metakaolin (MK). The experimental program included two phases. In phase one, two groups (SF+FA and MK+FA) were cast without steel fibers. Based on group performance in the first phase, one group was chosen to be used with steel fibers in the second phase. The flow rate, compressive and flexural strengths, density, ultrasonic pulse velocity and dynamic modulus of elasticity tests were conducted. The phase one results showed that SF+FA combination mixtures had better performance than MK+FA mixtures thus they were selected to be used in the second phase (with the addition of 1% volumetric fraction micro steel fibers). Results indicated that it is possible to produce sustainable RPC in which the cement can be replaced with 30% SF and 20% FA (the total replacement is 50%) in the presence of 1% steel fibers with a remarkable enhancement in compressive strength and flexural strength reached up to 44% and 10%, respectively

Variety of Antibody Responses to BNT162b2 and BBIBP-CorV Vaccinations Against COVID-19 Infections in Baghdad and Fallujah, Iraq

The huge impact of COVID-19 worldwide led to the rapid development of vaccines with inadequate data about its longevity, effectivity, and safety. This study aims to evaluate the effectiveness and safety of COVID-19 vaccines available in Iraq and to measure longevity of created antibody response among different time points of both Pfizer-BioNTech and Sinopharm vaccines in Baghdad and Fallujah, Iraq. A two-axis method was used: the first was cross sectional study on the vaccination state for COVID-19 in Baghdad and Fallujah, using an online survey contained questions about city, vaccine type, side effect, pre and post infections, and chronic diseases. The second part involved a prospective observational study of the vaccine’s immunological effectiveness and stability in 60 serum samples from completely vaccinated individuals (second dose) of Pfizer or Sinopharm along different time points (1 - 6 months) by measuring the SARS-CoV-2 Anti-RBD-IgG concentration and evaluating its correlation with pre-infection with COVID-19. Among different types of vaccines available in Iraq, people in Baghdad and Fallujah preferred Pfizer vaccine over other available types, particularly those with chronic diseases. No statistically significant difference was noticed between IgG concentrations at different points of time, IgG concentrations in Pfizer vaccinated individuals were more elevated than Sinopharm, and all of Pfizer vaccinated people showed positive results. Our study established a synergistic impact between recent COVID-19 infection and vaccination, leading to increased levels of IgG antibodies, notably in individuals who received the Pfizer vaccine. Additionally, our findings demonstrate that IgG concentrations remained stable in vaccinated individuals even six months after completing the vaccination with second dose

Thermodynamic Analysis With Energy Recovery Comparison of Transcritical CO2 Heat Pump System Using Various Expansion Devices

The high irreversibility caused by the expansion valve in the conventional transcritical CO2 heat pump cycle has been reported as the major drawback on the overall system performance. To overcome this problem and recover some of the energy lost, different isentropic expansion devices such as turbine expander and two phase ejector have been proposed. This study aims to numerically compare the performance of the transcrtical CO2 heat pump in terms of first and second law of thermodynamics. In addition, the energy recovered by the two phase ejector and the turbine expander cycles have been evaluated. The pressure recovery and entrainment ratio in the ejector device were investigated comprehensively. Two numerical models using MATLAB and ASPEN PLUS software have been developed, and REFPROP database was used to estimate the refrigerant thermophysical properties. The results showed that the heating coefficient of performance (COPh) of the ejector cycle is higher than that of the turbine and valve cycles by 10.15 % and 20.84 % respectively. In addition, the ejector cycle has the highest second law efficiency (0.1) and the recovered energy is (0.63 kW) compared to (0.107 kW) gained by the turbine cycle. The ejector device has the least exergy destruction (0.2 kW) and can recover 0.7 Mpa of the pressure losses

COVID-19 anomaly detection and classification method based on supervised machine learning of chest X-ray images

The term COVID-19 is an abbreviation of Coronavirus 2019, which is considered a global pandemic that threatens the lives of millions of people. Early detection of the disease offers ample opportunity of recovery and prevention of spreading. This paper proposes a method for classification and early detection of COVID-19 through image processing using X-ray images. A set of procedures are applied, including preprocessing (image noise removal, image thresholding, and morphological operation), Region of Interest (ROI) detection and segmentation, feature extraction, (Local binary pattern (LBP), Histogram of Gradient (HOG), and Haralick texture features) and classification (K-Nearest Neighbor (KNN) and Support Vector Machine (SVM)). The combinations of the feature extraction operators and classifiers results in six models, namely LBP-KNN, HOG-KNN, Haralick-KNN, LBP-SVM, HOG-SVM, and Haralick-SVM. The six models are tested based on test samples of 5,000 images with the percentage of training of 5-folds cross-validation. The evaluation results show high diagnosis accuracy from 89.2% up to 98.66%. The LBP-KNN model outperforms the other models in which it achieves an average accuracy of 98.66%, a sensitivity of 97.76%, specificity of 100%, and precision of 100%. The proposed method for early detection and classification of COVID-19 through image processing using X-ray images is proven to be usable in which it provides an end-to-end structure without the need for manual feature extraction and manual selection methods.Web of Science31art. no. 10504

Numerical analysis of the energy-storage performance of a PCM-based triplex-tube containment system equipped with arc-shaped fins

This study numerically intends to evaluate the effects of arc-shaped fins on the melting capability of a triplex-tube confinement system filled with phase-change materials (PCMs). In contrast to situations with no fins, where PCM exhibits relatively poor heat response, in this study, the thermal performance is modified using novel arc-shaped fins with various circular angles and orientations compared with traditional rectangular fins. Several inline and staggered layouts are also assessed to maximize the fin’s efficacy. The effect of the nearby natural convection is further investigated by adding a fin to the bottom of the heat-storage domain. Additionally, the Reynolds number and temperature of the heat-transfer fluid (HTF) are evaluated. The outcomes showed that the arc-shaped fins could greatly enhance the PCMs’ melting rate and the associated heat-storage properties. The melting rate is 17% and 93.1% greater for the case fitted with an inline distribution of the fins with a circular angle of 90° and an upward direction, respectively, than the cases with uniform rectangular fins and no fins, which corresponded to the shorter melting time of 14.5% and 50.4%. For the case with arc-shaped fins with a 90° circular angle, the melting rate increases by 9% using a staggered distribution. Compared to the staggered fin distribution, adding an extra fin to the bottom of the domain indicates adverse effects. The charging time reduces by 5.8% and 9.2% when the Reynolds number (Re) rises from 500 to 1000 and 1500, respectively, while the heat-storage rate increases by 6.3% and 10.3%. When the fluid inlet temperature is 55°C or 50°C, compared with 45°C, the overall charging time increases by 98% and 47%, respectively

Forebrain Cholinergic Signaling Regulates Innate Immune Responses and Inflammation

The brain regulates physiological functions integral to survival. However, the insight into brain neuronal regulation of peripheral immune function and the neuromediator systems and pathways involved remains limited. Here, utilizing selective genetic and pharmacological approaches, we studied the role of forebrain cholinergic signaling in the regulation of peripheral immune function and inflammation. Forebrain-selective genetic ablation of acetylcholine release and vagotomy abolished the suppression of serum TNF by the centrally-acting cholinergic drug galantamine in murine endotoxemia. Selective stimulation of acetylcholine action on the M1 muscarinic acetylcholine receptor (M1 mAChR) by central administration of the positive allosteric modulator benzyl quinolone carboxylic acid (BQCA) suppressed serum TNF (TNF alpha) levels in murine endotoxemia. This effect was recapitulated by peripheral administration of the compound. BQCA also improved survival in murine endotoxemia and these effects were abolished in M1 mAChR knockout (KO) mice. Selective optogenetic stimulation of basal forebrain cholinergic neurons innervating brain regions with abundant M1 mAChR localization reduced serum TNF in endotoxemic mice. These findings reveal that forebrain cholinergic neurons regulate innate immune responses and inflammation, suggesting the possibility that in diseases associated with cholinergic dysfunction, including Alzheimer\u27s disease this anti-inflammatory regulation can be impaired. These results also suggest novel anti-inflammatory approaches based on targeting forebrain cholinergic signaling in sepsis and other disorders characterized by immune dysregulation

Forebrain Cholinergic Signaling Regulates Innate Immune Responses and Inflammation

The brain regulates physiological functions integral to survival. However, the insight into brain neuronal regulation of peripheral immune function and the neuromediator systems and pathways involved remains limited. Here, utilizing selective genetic and pharmacological approaches, we studied the role of forebrain cholinergic signaling in the regulation of peripheral immune function and inflammation. Forebrain-selective genetic ablation of acetylcholine release and vagotomy abolished the suppression of serum TNF by the centrally-acting cholinergic drug galantamine in murine endotoxemia. Selective stimulation of acetylcholine action on the M1 muscarinic acetylcholine receptor (M1 mAChR) by central administration of the positive allosteric modulator benzyl quinolone carboxylic acid (BQCA) suppressed serum TNF (TNFα) levels in murine endotoxemia. This effect was recapitulated by peripheral administration of the compound. BQCA also improved survival in murine endotoxemia and these effects were abolished in M1 mAChR knockout (KO) mice. Selective optogenetic stimulation of basal forebrain cholinergic neurons innervating brain regions with abundant M1 mAChR localization reduced serum TNF in endotoxemic mice. These findings reveal that forebrain cholinergic neurons regulate innate immune responses and inflammation, suggesting the possibility that in diseases associated with cholinergic dysfunction, including Alzheimer's disease this anti-inflammatory regulation can be impaired. These results also suggest novel anti-inflammatory approaches based on targeting forebrain cholinergic signaling in sepsis and other disorders characterized by immune dysregulation