有无静流池情况下河床水力跃迁的概率模拟

IF 3.9 3区 环境科学与生态学 Q1 ENGINEERING, CIVIL Stochastic Environmental Research and Risk Assessment Pub Date : 2024-06-26 DOI:10.1007/s00477-024-02751-x
Farshad Hajizadehmishi, Seyed Mehrab Amiri, Ali Akbar Hekmatzadeh, Parjang Monajemi, Shahin Farahmandpey
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引用次数: 0

摘要

本研究探讨了曼宁系数(n)的变化如何影响水力结构下游的水力跃升位置。研究采用稳健有限体积法和随机场理论,探讨了 n 的空间变化对水力跃迁特性的影响。研究考虑了两种情况:一种是有静流池的情况,另一种是没有静流池的情况。对 n 的一维和二维空间分布进行了分析。结果表明,在没有静压池的情况下,河床中水力跃层的位置变化很大。水力跃层位置的不确定性远远大于共轭深度值的不确定性。此外,与二维分布相比,n 的一维空间分布导致估计位置的标准偏差更大。在有静压池的情况下,增加护坡长度会导致水力跃层向上游移动,而标准偏差保持不变。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Probabilistic simulation of hydraulic jump in a riverbed in presence and absence of stilling basin

This study examines how the variability of the Manning coefficient (n) affects the position of hydraulic jumps downstream of hydraulic structures. Using a robust finite volume method and random field theory, the study investigates the impact of spatial variations in n on hydraulic jump characteristics. Two scenarios are considered: one with a stilling basin and one without. Both one-dimensional and two-dimensional spatial distributions of n are analyzed. The results show that without a stilling basin, there are significant variations in the location of hydraulic jumps in the riverbed. The uncertainty in the location of the hydraulic jump is much higher than the uncertainty in the values of conjugate depths. Additionally, one-dimensional spatial distribution of n leads to higher standard deviations in the estimated location compared to two-dimensional distribution. In scenarios with a stilling basin, increasing riprap length causes the hydraulic jump to move upstream, while standard deviation remains constant.

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来源期刊
CiteScore
7.10
自引率
9.50%
发文量
189
审稿时长
3.8 months
期刊介绍: Stochastic Environmental Research and Risk Assessment (SERRA) will publish research papers, reviews and technical notes on stochastic and probabilistic approaches to environmental sciences and engineering, including interactions of earth and atmospheric environments with people and ecosystems. The basic idea is to bring together research papers on stochastic modelling in various fields of environmental sciences and to provide an interdisciplinary forum for the exchange of ideas, for communicating on issues that cut across disciplinary barriers, and for the dissemination of stochastic techniques used in different fields to the community of interested researchers. Original contributions will be considered dealing with modelling (theoretical and computational), measurements and instrumentation in one or more of the following topical areas: - Spatiotemporal analysis and mapping of natural processes. - Enviroinformatics. - Environmental risk assessment, reliability analysis and decision making. - Surface and subsurface hydrology and hydraulics. - Multiphase porous media domains and contaminant transport modelling. - Hazardous waste site characterization. - Stochastic turbulence and random hydrodynamic fields. - Chaotic and fractal systems. - Random waves and seafloor morphology. - Stochastic atmospheric and climate processes. - Air pollution and quality assessment research. - Modern geostatistics. - Mechanisms of pollutant formation, emission, exposure and absorption. - Physical, chemical and biological analysis of human exposure from single and multiple media and routes; control and protection. - Bioinformatics. - Probabilistic methods in ecology and population biology. - Epidemiological investigations. - Models using stochastic differential equations stochastic or partial differential equations. - Hazardous waste site characterization.
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