Two dimensional meso-scale concrete modeling was used in finite element analysis of plain concrete beam subjected to bending. The plane stress 4-noded quadrilateral elements were utilized to model coarse aggregate, cement mortar. The effect of aggregate fraction distribution, and pores percent of the total area – resulting from air voids entrapped in concrete during placement on the behavior of plain concrete beam in flexural was detected. Aggregate size fractions were randomly distributed across the profile area of the beam. Extended Finite Element Method (XFEM) was employed to treat the discontinuities problems result from double phases of concrete and cracking that faced during the finite element analysis of concrete beam. Cracking was initiated at a small notch located at the middle of the bottom face of the concrete beam. The response of plain concrete beam subjected to pure bending via two point load application was detected using (XFEM) analysis of meso-scale concrete model. Assuming full bond between aggregate particles, and mortar at interfacial zone, the flexural strength of plain concrete beam is increased when aggregate particles size is increased, so that bending and shear stress were affected by void percentage and aggregate particles distribution. The maximum deflection at midspan was increased when the aggregate particles size decreases.
In the 1970s, the world knew the long-tailed nesokia Nesokia bunnii (Khajuria, 1981) (Rodentia, Muridae) from the Mesopotamian marshes of Garden of Eden in Southern Iraq. This distinct rodent was known from only five voucher specimens collected at the confluence of Tigris and Euphrates Rivers in southern Iraq while its occurrence in Southwestern Iran had
never been reported. In the 1990s, a large extent of its natural habitat was catastrophically desiccated and the animal was last seen in the 1970s. Since then, the status of this elusive rodent was shrouded in mystery. In 2007, an extraordinary photograph of a carcass of this species came to the light from Hawizeh Marsh which was interpreted as concrete evidence of the species’ pers
Social responsibility has achieved tremendous attention by academicians and practitioners to focus on social responsibility accounting. However, many studies around the globe have been conduct to measure the outcomes of social responsibility accounting. This paper presents the impact of applying the supply chain strategy (SCS) on the agribusiness field to optimize productivity and decreasing cost which will have a direct impact on the net income of the organization. The inconclusive results of earlier studies stimulated this research to social responsibility accounting-financial performance. The equivocal results of this phenomenon urge this study to investigate the role of other factors in the relationship of social responsibility accounti
... Show MoreAs major nosocomial pathogens,
In this study, 20
The current study was carried out to investigate the correlation of gene expressions of ADA1 and ADA2 genes with the development of autoimmune thyroid disease (AITD) in a sample of Iraqi females. One hundred patients with AITD and 80 controls were included. Quantitative real time polymerase chain reaction (qRT–PCR) was utilized for investigation of ADA1 and ADA2 gene expression among patients and controls. The correlation of age and body mass index (BMI) with AITD occurrence comparing with controls was studied. Based on the results of this study, there is high expression level of ADA1 and ADA2 genes in patients compared with healthy controls; also, the gene expression fold (2-ΔΔCT) of ADA1 and ADA2 among AITD patients was recorded and a
... Show MoreThe prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices
... Show MoreLow-temperature stratification, high-volumetric storage capacity, and less-complicated material processing make phase-changing materials (PCMs) very suitable candidates for solar energy storage applications. However, their poor heat diffusivities and suboptimal containment designs severely limit their decent storage capabilities. In these systems, the arrangement of tubes conveying the heat transport fluid (HTF) plays a crucial role in heat communication between the PCM and HTF during phase transition. This study investigates a helical coil tube-and-shell thermal storage system integrated with a novel central return tube to enhance heat transfer effectiveness. Three-dimensional computational fluid dynamics simulations compare the proposed d
... Show MoreIn this work, we construct the projectively distinct (k, n)-arcs in PG (3, 4) over Galois field GF (4), where k 5, and we found that the complete (k, n)-arcs, where 3 n 21, moreover we prove geometrically that the maximum complete (k, n)-arc in PG (3, 4) is (85, 21)-arc. A (k, n)-arcs is a set of k points no n+ 1 of which are collinear. A (k, n)-arcs is complete if it is not contained in a (k+ 1, n)-arcs
The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti
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