Risk identification and assessment can be analysed using many risk management tools. Fishbone diagram is one of these techniques which can be employed, for the identification of the causes behind the construction failure, which has become a phenomenon that often gets repeated in several projects. If these failures are not understood and handled scientifically, it may lead to disputes between the project parties. Additionally, the construction failure also leads to an increase in the project budget, which in turn causes a delay in the completion of the projects. Punching shear in reinforcement slab may be one of the reasons for construction failures. However, there are many doubts about other causes that lead to this failure as well as the role of these causes in the construction failure. Also, there are many causes linked to this failure of which some fall on the designer and the others fall on the contractor. Thus, this research aims to determine the causes of punching shear failure in the concrete slab and its role in the failure using a logic managerial analysis. For this purpose, the applicability of the Fishbone diagram has been extended, for the analysis of probability as well as the impact of the risk of punching shear, thus elucidating the risk score of each category without ignoring the global risk. In this direction, interviews and questionnaires are conducted with numerous experts specialize in both the design and execution field of construction projects for identifying the most important causes that lead to the occurrence of punching shear failure. Further, the Fishbone diagram for punching shear’s risk illuminated that impact of some of the primary and secondary causes such as planning, designing, and maintenance is more than the expectation. Therefore, the concentration in these areas should be carried out by taking into consideration the adapt risk response plan to prevent or mitigate these risks.
Bored piles settlement behavior under vertical loaded is the main factor that affects the design requirements of single or group of piles in soft soils. The estimation of bored pile settlement is a complicated problem because it depends upon many factors which may include ground conditions, validation of bored pile design method through testing and validation of theoretical or numerical prediction of the settlement value. In this study, a prototype single and bored pile group model of arrangement (1*1, 1*2 and 2*2) for total length to diameter ratios (L/D) is 13.33 and clear spacing three times of diameter, subjected to vertical axial loads. The bored piles model used for the test was 2000
... Show MoreSteel–concrete–steel (SCS) structural systems have economic and structural advantages over traditional reinforced concrete; thus, they have been widely used. The performance of concrete made from recycled rubber aggregate from scrap tires has been evaluated since the early 1990s. The use of rubberized concrete in structural construction remains necessary because of its high impact resistance, increases ductility, and produces a lightweight concrete; therefore, it adds such important properties to SCS members. In this research, the use of different concrete core materials in SCS was examined. Twelve SCS specimens were subjected to push-out monotonic loading for inspecting their mechanical performance. One specimen was constructed from co
... Show MoreMagnetic nanoparticles (MNPs) of iron oxide (Fe3O4) represent the most promising materials in many applications. MNPs have been synthesized by co-precipitation of ferric and ferrous ions in alkaline solution. Two methods of synthesis were conducted with different parameters, such as temperature (25 and 80 ̊C), adding a base to the reactants and the opposite process, and using nitrogen as an inert gas. The product of the first method (MNPs-1) and the second method (MNPs-2) were characterized by x-ray diffractometer (XRD), Zeta Potential, atomic force microscope (AFM) and scanning electron microscope (SEM). AFM results showed convergent particle size of (MNPs-1) and (MNPs-2) with (86.01) and (74.14)
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreFourier Transform-Infrared (FT-IR) spectroscopy was used to analyze gasoline engine oil (SAE 5W20) samples that were exposed to seven different oxidation times (0 h, 24 h, 48 h, 72 h, 96 h, 120 h, and 144 h) to determine the best wavenumbers and wavenumber ranges for the discrimination of the oxidation times. The thermal oxidation process generated oil samples with varying total base number (TBN) levels. Each wavenumber (400–3900 cm−1) and wavenumber ranges identified from the literature and this study were statistically analyzed to determine which wavenumbers and wavenumber ranges could discriminate among all oxidation times. Linear regression was used with the best wavenumbers and wavenumber ranges to predict oxidation time.
... Show MoreThe study of biopolymers and their derivative materials had received a considerable degree of attention from researchers in the preparation of novel material. Biopolymers and their derivatives have a wide range of applications as a result of their bio-compatibility, bio-degradability and non-toxicity. In this paper, chitosan reacted with different aldehydes(2,4 –dichloro- benzaldehyde or 2-methyl benzaldehyde), different ketones (4-bromoacetophenone or 3-aminoacetophenone) to produce chitosan schiff base (1-4) . Chitosan schiff base (1-4) reacted with glutaric acid or adipic acid in acidic media in distilled water according to the steps of Fischer and Speier to produce compounds (5-12)
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