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Evaluation of the Variation in Dynamic Load Factor Throughout a Highly Skewed Steel I-Girder Bridge
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The Dynamic Load Factor (DLF) is defined as the ratio between the maximum dynamic and static responses in terms of stress, strain, deflection, reaction, etc. DLF adopted by different design codes is based on parameters such as bridge span length, traffic load models, and bridge natural frequency. During the last decades, a lot of researches have been made to study the DLF of simply supported bridges due to vehicle loading. On the other hand, fewer works have been reported on continuous bridges especially with skew supports. This paper focuses on the investigation of the DLF for a highly skewed steel I-girder bridge, namely the US13 Bridge in Delaware State, USA. Field testing under various load passes of a weighed load vehicle was used to validate full-scale three-dimensional finite element models and to evaluate the dynamic response of the bridge more thoroughly. The results are presented as a function of the static and dynamic tensile and compressive stresses and are compared to DLF code provisions. The result shows that most codes of practice are conservative in the regions of the girder that would govern the flexural design. However, the DLF sometimes exceeds the code-recommended values in the vicinity of skewed supports. The discrepancy of the DLF determined based on the stress analysis of the present study, exceeds by 13% and 16% the values determined according to AASHTO (2002) for tension and compression stresses respectively, while, in comparison to BS5400, the differences reach 6% and 8% respectively.

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Publication Date
Thu Nov 21 2019
Journal Name
Journal Of Engineering
A Neural Networks based Predictive Voltage-Tracking Controller Design for Proton Exchange Membrane Fuel Cell Model
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In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

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Publication Date
Sun Jun 23 2019
Journal Name
American Rock Mechanics Association
Using an Analytical Model to Predict Collapse Volume During Drilling: A Case Study from Southern Iraq
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Zubair Formation is one of the richest petroleum systems in Southern Iraq. This formation is composed mainly of sandstones interbedded with shale sequences, with minor streaks of limestone and siltstone. Borehole collapse is one of the most critical challenges that continuously appear in drilling and production operations. Problems associated with borehole collapse, such as tight hole while tripping, stuck pipe and logging tools, hole enlargement, poor log quality, and poor primary cement jobs, are the cause of the majority of the nonproductive time (NPT) in the Zubair reservoir developments. Several studies released models predicting the onset of borehole collapse and the amount of enlargement of the wellbore cross-section. However, assump

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Publication Date
Tue Jan 01 2019
Journal Name
The 53rd U.s. Rock Mechanics/geomechanics Symposium
Using an analytical model to predict collapse volume during drilling: A case study from southern Iraq
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Publication Date
Fri Jan 01 2016
Journal Name
Advances In Computing
A New Abnormality Detection Approach for T1-Weighted Magnetic Resonance Imaging Brain Slices Using Three Planes
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Generally, radiologists analyse the Magnetic Resonance Imaging (MRI) by visual inspection to detect and identify the presence of tumour or abnormal tissue in brain MR images. The huge number of such MR images makes this visual interpretation process, not only laborious and expensive but often erroneous. Furthermore, the human eye and brain sensitivity to elucidate such images gets reduced with the increase of number of cases, especially when only some slices contain information of the affected area. Therefore, an automated system for the analysis and classification of MR images is mandatory. In this paper, we propose a new method for abnormality detection from T1-Weighted MRI of human head scans using three planes, including axial plane, co

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Publication Date
Sat Apr 01 2017
Journal Name
Iosr Journal Of Computer Engineering (iosr-jce)
A New Approach to DNA, RNA, and Protein Motifs Templates Visualization and Analysis via Compilation Technique
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Motifs template is the input for many bioinformatics systems such codons finding, transcription, transaction, sequential pattern miner, and bioinformatics databases analysis. The size of motifs arranged from one base up to several Mega bases, therefore, the typing errors increase according to the size of motifs. In addition, when the structures motifs are submitted to bioinformatics systems, the specifications of motifs components are required, i.e. the simple motifs, gaps, and the lower bound and upper bound of each gap. The motifs can be of DNA, RNA, or Protein. In this research, a motif parser and visualization module is designed depending on a proposed a context free grammar, CFG, and colors human recognition system. GFC describes the m

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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
On Generalized Continuous Fuzzy Proper Function from a Fuzzy Topological Space to another Fuzzy Topological Space
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The purpose of this paper is to introduce and study the concepts of fuzzy generalized open sets, fuzzy generalized closed sets, generalized continuous fuzzy proper functions and prove results about these concepts.

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Publication Date
Tue Oct 01 2024
Journal Name
Journal Of Engineering
A Comprehensive Review for Integrating Petrophysical Properties, Rock Typing, and Geological Modeling for Enhanced Reservoir Characterization
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Reservoir characterization is an important component of hydrocarbon exploration and production, which requires the integration of different disciplines for accurate subsurface modeling. This comprehensive research paper delves into the complex interplay of rock materials, rock formation techniques, and geological modeling techniques for improving reservoir quality. The research plays an important role dominated by petrophysical factors such as porosity, shale volume, water content, and permeability—as important indicators of reservoir properties, fluid behavior, and hydrocarbon potential. It examines various rock cataloging techniques, focusing on rock aggregation techniques and self-organizing maps (SOMs) to identify specific and

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Publication Date
Sat Jan 01 2022
Journal Name
The 2nd Universitas Lampung International Conference On Science, Technology, And Environment (ulicoste) 2021
A comparison between IRI-2016 and ASAPS models for predicting foF2 ionospheric parameter over Baghdad city
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Publication Date
Tue Apr 26 2022
Journal Name
Journal Of Contemporary Medical Sciences
Doxorubicin Immobilization on chitosan-modified silver Nanoparticles as a drug delivery method for effective anticancer treatment
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Objective: The goal of this research is to load Doxorubicin (DOX) on silver nanoparticles coupled with folic acid and test their anticancer properties against breast cancer. Methods: Chitosan-Capped silver nanoparticles (CS-AgNPs) were manufactured and loaded with folic acid as well as an anticancer drug, Doxorubicin, to form CS-AgNPs-DOX-FA conjugate. AFM, FTIR, and SEM techniques were used to characterize the samples. The produced multifunctional nano-formulation served as an intrinsic drug delivery system, allowing for effective loading and targeting of chemotherapeutics on the Breast cancer (AMJ 13) cell line. Flowcytometry was used to assess therapy efficacy by measuring apoptotic induction.  Results: DOX and CS-Ag

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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Physics
A Cut-off low at 500 hPa Geopotential Height and Rainfall Events over Iraq: Case Studies
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A cut-off low is a closed low with a low value of geopotential height at the upper atmospheric levels that has been fully detached (cut-off) from the westerly flow and move independently. A cut-off low causes extreme rainfall events in the mid-latitudes regions. The main aim of this paper is to investigate the cut-off low at 500 hPa over Iraq from a synoptic point of view and the behavior of geopotential height at 500 hPa. To examine the association of the cut-off low at 500 hPa with rainfall events across Iraq, two case studies of heavy rainfall events from different times were conducted. The results showed that the cut-off low at 500 hPa with a low value of geopotential height will strengthen the low-pressure system at the surface, lea

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