Anbar Journal of Engineering Sciences
Login
Anbar Journal of Engineering Sciences
  • Home
  • Articles & Issues
    • Latest Issue
    • All Issues
  • Authors
    • Submit Manuscript
    • Guide for Authors
    • Authorship
    • Article Processing Charges (APC)
  • Reviewers
    • Guide for Reviewers
    • Become a Reviewer
    • Reviewers of AJES
  • About
    • About Journal
    • Aims and Scope
    • Editorial Board
    • Journal Insights
    • Peer Review Process
    • Publication Ethics
    • Plagiarism
    • Allegations of Misconduct
    • Appeals and Complaints
    • Corrections and Withdrawals
    • Open Access
    • Copyright Policy
    • Archiving Policy
    • Journal Funding Sources
    • Announcements
    • Contact

Search Results for fso

Article
Latency Budgeting of Dynamic Cloud Radio Access Network

Basim K. J. Al-Shammari

Pages: 213-224

PDF Full Text
Abstract

5G networks aim to improve capacity, reliability, and energy efficiency while reducing latency and increasing connection density. A vital goal is enabling real time communication, which demands extremely low latency, particularly within Dynamic Cloud Radio Access Network (DC-RAN) architectures designed for high coverage density. The FrontHaul (FH) link is a critical component for achieving this, as different FH technologies directly impact performance, latency and coverage in dense areas. This paper focuses on latency budgeting within a DC—RAN, analysing how FH technologies – millimetre wave (mmWave), optical fiber; and Free Space Optics (FSO) – affect overall End-to-End delay (E2E) and Round-Trip Time (RTT). By calculating the propagation and processing delays for various cell types, the analysis provides a comparative performance evaluation. The key finding is that, while processing delay dominates the total latency, the choice of FH link significantly influences performance and practicality. mmWave and FSO are suitable for short-range, dense deployments, whereas optical fiber offers stable, low latency over longer distances. Thus, the optimal FH selection depends on specific network objectives, including coverage, density, and weather conditions; toward meeting Ultra-Reliable Low-Latency Communication (URLLC) targets.

Article
OPTIMUM DESIGN OF BUTTRESS DAM USING GENETIC ALGORITHM

Noor ALBayati, Chelang Arslan

Pages: 40-52

PDF Full Text
Abstract

Designing large structures like dams requires carefully selecting various geometric, hydraulic, and structural characteristics. The required structural design and performance criteria are considered when selecting these characteristics. In order to find the best solution, a variety of restrictions must simultaneously be carefully taken into account. This study presents an effective method for determining the optimal shape design for concrete buttress dams. The research was divided into two crucial phases. The dam's initial design and subsequent modeling were mostly done using DIANA FEA and traditional design and stability analysis. After that, a genetic algorithm was used on the MATLAB platform to control optimizing the dam's shape.  Three design factors were used in this phase to alter the goal function and to reduce the amount of Concrete used, which decreased project costs. These variables covered three areas of the buttress's cross-section. Two important limitations were scrutinized during this optimization process: establishing a safety margin against overtopping and preventing sliding. The analysis included a detailed assessment of Shear friction stability to complete a thorough stability study. The optimization efforts had a spectacular result, resulting in a significant 52.365% reduction in the total volume of Concrete used, dropping from 19147.5 cubic meters to 9122.55 cubic meters. This decrease was made possible by reducing three distinct components (X1, X2, X3), with respective proportions of 37.5%, 13.33%, and 30%, including two segments related to the buttress and the final segment linked (slab) to the strip footing.

1 - 2 of 2 items

Search Parameters

Journal Logo
Anbar Journal of Engineering Sciences

University of Anbar

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

CC BY 4.0 Logo Licensed under CC-BY-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 © 2025 College of Engineering, University of Anbar. All rights reserved, including those for text and data mining, AI training, and similar technologies.