Al-Nahrain Journal for Engineering Sciences
Login
NJES
  • Home
  • Articles & Issues
    • Latest Issue
    • All Issues
  • Authors
    • Submit Manuscript
    • Guide for Authors
    • Submission Resources
    • Authorship
    • Article Processing Charges (APC)
  • Reviewers
    • Guide for Reviewers
    • Become a Reviewer
  • Policies
    • Publication Ethics
    • Plagiarism
    • Allegations of Misconduct
    • Appeals and Complaints
    • Corrections and Withdrawals
    • Open Access
    • Archiving Policy
    • Copyright Policy
  • About
    • About Journal
    • Aims and Scope
    • Editorial Team
    • Journal Insights
    • Peer Review Process
    • Abstracting and Indexing
    • Announcements
    • Contact

Search Results for Laith S. Mahmood

Article
Mathematical Modeling and Advanced Control of the Refinery Processes: A Review

Laith S. Mahmood, Khalid Alzobai, Salam K. Al-Dawery

Pages: 253-265

PDF Full Text
Abstract

The oil industry has a direct impact on the economic feasibility of other sectors and is considered to be the most important energy source used to turn the wheels of other industries. Therefore, it was necessary to pay attention and continuously develop this industry, to find the best modern techniques for designing, pre-commissioning and controlling process, to improve efficiency, preserve energy and achieve the highest production of costly components with the highest purity of the product. This study aims to provide a literary analysis of the stages of development and progress of the dynamics and control of the petroleum industry, in particular the distillation column, because it is multivariable with high interaction between control cycles, nonlinear behaviour and large gains. Control processes have undergone many developments and modernizations to achieve the best results. Various control methods have been used, ranging from simple proportional-integral-derivative controller (PID) to advanced control strategies such as model predictive control (MPC), multivariate model predictive control (MMPC), fuzzy logic control (FLC), quadratic dynamic matrix control (QDMC), artificial neural network control (ANN) and other advanced control techniques. The authors concluded from the review that the advanced control strategies superior than the conventional methods.

Article
Nonlinear Finite Element Analysis of RC Beams without Stirrups Strengthened by Longitudinal Soffit Bonded CFRP Strips for Shear

Laith Khalid Al-Hadithy, Mustafa Mahmood Al-Ani

Pages: 996-1004

PDF Full Text
Abstract

This study concerns utilization of nonlinear finite element method for to evaluate the role of longitudinal soffit-bonded CFRP strips in elevating the shear behavior of RC beams without stirrups. All beams cross-sections were of 150 mm breadth and 200 mm depth, the overall length was 1500 mm with clear span 1300 mm. One beam was provided by minimum web reinforcement according to the ACI 318M-14, while the other five were without web reinforcement but externally strengthened by a variety of CFRP-strip combinations consisting of longitudinal soffit-bonded strips. The predictions of a proposed ANSYS (version 14.5) model for six of the test beams including modeling of concrete, steel rebars, CFRP strips and supports and loading steel plates, by SOLID65, LINK180, SHELL41 and SOLID185 elements, respectively, show high agreements with experimental evidence, which stands as a definite witness to the efficiency and reliability of the present numerical model.

1 - 2 of 2 items

Search Parameters

×

The submission system is temporarily under maintenance. Please send your manuscripts to

Go to Editorial Manager
Journal Logo
Al-Nahrain Journal for Engineering Sciences (NJES)

College of Engineering, Al-Nahrain University

  • Copyright Policy
  • Terms & Conditions
  • Privacy Policy
  • Accessibility
  • Cookie Settings
Licensing & Open Access

CC BY NC 4.0 Logo Licensed under CC-BY-NC-4.0

This journal provides immediate open access to its content.

Editorial Manager Logo Elsevier Logo

Peer-review powered by Elsevier’s Editorial Manager®

Copyright © 2026 College of Engineering, Al-Nahrain University, its licensors, and contributors. All rights reserved, including those for text and data mining, AI training, and similar technologies. For all open access content, the relevant licensing terms apply.