Influence of a Meandering Channel on the Threshold of Sediment

Author:

Rismani Nasim1,Afzalimehr Hossein1,Asghari-Pari Seyed-Amin2ORCID,Nazari-Sharabian Mohammad3ORCID,Karakouzian Moses4ORCID

Affiliation:

1. Faculty of Civil Engineering, Iran University of Science and Technology, Tehran 16846-13114, Iran

2. Department of Civil Engineering, Behbahan Khatam Alanbia University of Technology, Behbahan 63616-47189, Iran

3. Department of Mathematics, Engineering and Computer Science, West Virginia State University, Institute, WV 25112, USA

4. Department of Civil and Environmental Engineering and Construction, University of Nevada Las Vegas, Las Vegas, NV 89154, USA

Abstract

River meanders and channel curvatures play a significant role in sediment motion, making it crucial to predict incipient sediment motion for effective river restoration projects. This study utilized an artificial intelligence method, multiple linear regression (MLR), to investigate the impact of channel curvature on sediment incipient motion at a 180-degree bend. We analyzed 42 velocity profiles for flow depths of 13, 15, and 17 cm in a laboratory flume. The results indicate that the velocity distribution was influenced by the sediment movement threshold conditions due to channel curvature, creating a distinct convex shape based on the bend’s position and flow characteristics. Reynolds stress distribution was concave in the upstream bend and convex in the downstream bend, underscoring the bend’s impact on incipient motion. Bed Reynolds stress was highest in the first half of the bend (0 to 90 degrees) and lowest in the second half (90 to 180 degrees). The critical Shields parameter at the bend was approximately 8–61% lower than the values suggested by the Shields diagram, decreasing from 0.042 at the beginning to 0.016 at the end of the bend. Furthermore, our findings suggest that the MLR method does not significantly enhance the understanding of sediment movement, highlighting the need for a more comprehensive physical rationale and an expanded dataset for studying sediment dynamics in curved channels.

Publisher

MDPI AG

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3