In this paper, the problem of developing turbulent flow in rectangular duct is investigated by obtaining numerical results of the velocity profiles in duct by using large eddy simulation model in two dimensions with different Reynolds numbers, filter equations and mesh sizes. Reynolds numbers range from (11,000) to (110,000) for velocities (1 m/sec) to (50 m/sec) with (56×56), (76×76) and (96×96) mesh sizes with different filter equations. The numerical results of the large eddy simulation model are compared with k-ε model and analytic velocity distribution and validated with experimental data of other researcher. The large eddy simulation model has a good agreement with experimental data for high Reynolds number with the first, second and third mesh sizes and the agreement increase near the wall of the duct. The percentage error for the large eddy simulation model with experimental data of the (56×56) mesh size is less than 18 % and for the (76×76) mesh size is also less than 17% and for the (96×96) mesh size is less than 16 %. The large eddy simulation model show high stability and do not need extra differential equation like the k-ε model and a great saving in time and computer memory was achieved.
Flexible pipes, such as GRP pipes, serve as effective underground infrastructure especially as sewer pipeline. This study is an attempt for understanding the effects of bedding types on the behavior of large diameter GRP flexible sewer pipes using three dimensional finite element approaches. Theoretical and numerical analyses were performed using both BS EN 1295-1 approach and finite element method (ABAQUS software). The effects of different parameters are studied such as, depth of backfill, bedding compaction, and backfill compaction. Due to compaction, an increase in the bedding compaction modulus (E’1) results in a reduction of both stresses and displacements of the pipe, especially, for well compacted ba
... Show MoreMishrif Formation was deposited during The Cenomanian-Early Turonian, which has been studied in selected Tuba and Zubair OilFields, these wells (TU-5, TU-24, TU-40, ZB-41, ZB-42, and ZB-46) are located within Mesopotamian basin at southern Iraq and considered as a major carbonate reservoir in Iraq and the Arabian Gulf. The palaeontological investigations mainly depending on benthonic foraminifera of the studied wells of Tuba and Zubair Oilfields in Mishrif Formation, twenty-four species belonging to fourteen genera are recognized of benthonic foraminifera, which has been recognized through this study, especially benthonic foraminiferal, indicating four zones as follows:
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One of the most powerful tools for any stellar dynamics is the N-body simulation. In an N-body simulation the motion of N particles is followed under their mutual gravitational attraction. In this paper the gravitational N-body simulation is described to investigate Newtonian and non- Newtonian (modified Newtonian dynamics) interaction between the stars of spiral galaxies. It is shown that standard Newtonian interaction requires dark matter to produce the flat rotational curves of the systems under consideration, while modified Newtonian dynamics (MOND) theorem provides a flat rotational curve and gives a good agreement with the observed rotation cu |
This research aimed to develop a simulation traffic model for an urban street with heterogeneous traffic capable of analyzing different types of vehicles of static and dynamic characteristics based on trajectory analysis that demonstrated psychophysical driver behavior. The base developed model for urban traffic was performed based on the collected field data for the major urban street in Baghdad city. The parameter; CC1 minimum headway (represented the speed-dependent of the safety distance from stop line that the driver desired) justified in the range from (2.86sec) to (2.17 sec) indicated a good match to reflect the actual traffic behavior for urban traffic streets. A good indication of the convergence between simulat
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Abstract
In this paper presents two dimensional turbulent flow of different nanofluids and ribs configuration in a circular tube have been numerically investigation using FLUENT 6.3.26. Two samples of CuO and, ZnO nanoparticles with 2% v/v concentration and 40 nm as nanoparticle diameter combined with trapezoidalribs with aspect ratio of p/d=5.72 in a constant tube surface heat flux were conducted for simulation. The results showed that heat flow as Nusselt number for all cases raises with Reynolds number and volume fraction of nanofluid, likewise the results also reveal that ZnO with volume fractions of 2% in trapezoidal ribs offered highest Nusselt number at Reynolds number of Re= 30000.
Key
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One and two-dimensional hydraulic models simulations are important to specify the hydraulic characteristics of unsteady flow in Al-Gharraf River in order to define the locations that facing problems and suggesting the necessary treatments. The reach in the present study is 58200m long and lies between Kut and Hai Cities. Both numerical models were simulated using HEC-RAS software, 5.0.4, with flow rates ranging from 100 to 350 m3/s. Multi-scenarios of gates openings of Hai Regulator were applied. While the openings of Al-Gharraf Head Regulator were ranged between 60cm to fully opened. The suitable manning roughness for the unsteady state was
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This research basically gives an introduction about the multiple intelligence
theory and its implication into the classroom. It presents a unit plan based upon the
MI theory followed by a report which explains the application of the plan by the
researcher on the first class student of computer department in college of sciences/
University of Al-Mustansiryia and the teacher's and the students' reaction to it.
The research starts with a short introduction about the MI theory is a great
theory that could help students to learn better in a relaxed learning situation. It is
presented by Howard Gardener first when he published his book "Frames of
Minds" in 1983 in which he describes how the brain has multiple intelligen
With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se
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