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United States Department of Agriculture

Agricultural Research Service

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Research Project: Mechanistic Modeling of Wind Barriers and Grain Commingling Using CFD and DEM


2011 Annual Report

1a. Objectives (from AD-416)
Develop mechanistic simulation models of: (1) airflow through and around vegetative wind barriers using Computational fluid dynamics (CFD) to facilitate improving the characterization of wind barriers in wind erosion modeling and (2) grain handling in elevator equipment using the discrete element method (DEM) to facilitate improved identity preserved (IP) grain handling operations.

1b. Approach (from AD-416)
Computational fluid dynamics (CFD) models of airflow around and through wind barriers will be developed for porous vegetative barriers. The standard k–e model will be used for modeling turbulence and the governing equations will be discretized using a first order upwind scheme. The models will be refined and then validated by comparing predicted air velocities with published data. The validated CFD model will be applied to simulate airflow through and dust particle collection by single rows of trees during different seasons and with different barrier heights. The discrete element method (DEM) will be used to model adventitious grain commingling in bucket elevator legs. Existing particle models for corn, soybeans, and wheat will be used to create grain handling models in 3-d and quasi-2-d. The models will be applied to full-scale legs to evaluate the effect of: (1) operating parameters (flow rate, grain type, and cleanout procedures) and (2) design factors (uptake side, boot size, and cup design) on adventitious commingling levels. Preferred operating conditions and design characteristics for reducing undesirable commingling will then be evaluated.

3. Progress Report
Grain commingling in a pilot-scale bucket elevator boot was modeled with quasi-two-dimensional and three-dimensional models and validated with experimental data. The quasi-two-dimensional model significantly reduced computational time without sacrificing the three-dimensional effects of interacting spheres as would happen in a normal two-dimensional model. The models were further refined to simulate longer actual commingling experiments. Particle models using from one to four sphere shapes for wheat and shelled corn were implemented in simulated bulk density and bulk angle of repose tests in DEM. The validated particle and boot models are being applied to pilot-scale and full-scale boots to determine best management practices for reducing unwanted grain commingling. To initiate the optimization of wind barrier performance using experimental and analytical (computational fluid dynamics (CFD) modeling) methods, a review of published models, wind barrier (from simple fence to vegetative barriers like trees) properties, and factors affecting barrier effectiveness was conducted. Measurements for porosity of vegetative barriers (e.g., photographic image analysis techniques) were also reviewed and are being compared with laser-based sampling technology for evaluating the best porosity measurement scheme prior to field tests. Factors affecting porosity identified for study include: height, age and types of species of trees, and thickness of leaves through time as affected by wind. These will be key factors included in the experimental study and the data gathered will be incorporated in the new model. Articles on particle deposition on trees affected by meteorological parameters are also being reviewed. Plans were developed for measuring wind parameters related to efficacy of vegetative barriers to minimize wind erosion at different locations in Kansas. Preparations are also underway for a wind tunnel study on simulating standing wheat stubble. Two plant heights, 150 mm and 220 mm above the ground, will be simulated in the wind tunnel along with realistic ranges of other important plant factors such as Stem Area Index (SAI). These activities were monitored via meetings and numerous conference calls with the cooperators to discuss project plans and review program goals and accomplishments, along with personal oversight of much of the research.

4. Accomplishments

Last Modified: 06/26/2017
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