کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5763798 1625608 2017 34 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Upscaling of dilution and mixing using a trajectory based Spatial Markov random walk model in a periodic flow domain
ترجمه فارسی عنوان
بالا بردن رقت و مخلوط کردن با استفاده از یک مدل پیاده روی تصادفی مارکف مبتنی بر مسیر در دامنه جریان دوره ای
کلمات کلیدی
تجزیه و مخلوط کردن، بالا بردن مدل مارکف فضایی،
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات فرآیندهای سطح زمین
چکیده انگلیسی
The Spatial Markov Model (SMM) is an upscaled model that has been used successfully to predict effective mean transport across a broad range of hydrologic settings. Here we propose a novel variant of the SMM, applicable to spatially periodic systems. This SMM is built using particle trajectories, rather than travel times. By applying the proposed SMM to a simple benchmark problem we demonstrate that it can predict mean effective transport, when compared to data from fully resolved direct numerical simulations. Next we propose a methodology for using this SMM framework to predict measures of mixing and dilution, that do not just depend on mean concentrations, but are strongly impacted by pore-scale concentration fluctuations. We use information from trajectories of particles to downscale and reconstruct pore-scale approximate concentration fields from which mixing and dilution measures are then calculated. The comparison between measurements from fully resolved simulations and predictions with the SMM agree very favorably.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Advances in Water Resources - Volume 103, May 2017, Pages 76-85
نویسندگان
, , ,