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Dynamic Simulation Model for tracking grain lots in an elevator AE 503 Term Project

2. Food Traceability. ISO definition Traceability is the

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Dynamic Simulation Model for tracking grain lots in an elevator AE 503 Term Project

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    1. 1 Dynamic Simulation Model for tracking grain lots in an elevator AE 503 Term Project Maitri Thakur Agricultural and Biosystems Engineering May 2, 2007

    2. 2 Food Traceability ISO definition Traceability is the ability to trace the history, application, or location of that which is under consideration. A grain of wheat or a truckload A standard location size (field, farm, or county) A list of processes that must be identified (pesticide applications or animal welfare)

    3. 3 Food Traceability Respond to security threats Respond to food safety problems Document chain-of-custody Document production practices (e.g. organic) Meet consumer desires or social preferences Provide due diligence for safety/quality assurance Protect integrity of brand name Authenticate claims (e.g. Bordeaux wine)

    4. 4 Traceability ?

    5. 5 Movement of grains for export in the U.S.

    6. 6 Traceability in Bulk Grain Handling

    7. 7 Problem Statement Grain lots commingled: To meet buyer specifications as close as possible and to maximize the profit. Lot identity is not maintained. Recent experiences with regulatory issues have introduced a growing need to track product identity Grain elevators facing the problem of having to segregate their incoming products in batches of different end use quality (e.g. GMO and non-GMO)

    8. 8 Storage Bin- Grain Flow Methods FIFO First In, First Out Mass Flow LIFO Last In, First Out Funnel Flow NIFO Next In, First Out Simultaneous Bin emptying and filling with Funnel Flow

    9. 9 Objective The objective of this project is to build a dynamic simulation model that tracks individual grain lots in the outbound load from a grain bin following funnel flow

    10. 10 Grain and Bin Specifications Shape : Cylindrical, Flat-bottom, Bottom-draw Diameter (D): 15 feet (4.6 m) Opening diameter (d) : 30 cm (0.3 m) Grain : Soybeans Angle of Repose (T) : 35 Coefficient of friction (c) : 0.3 Bulk Density (?) : 770 Kg/m3

    11. 11

    12. 12 Differential Equations Forces acting on m1: m1g + ?gAh Fc - Fc=m1d2x/dt2 . (1) where, m1 = Mass of load 1 g = Acceleration due to Gravity ? = Bulk Density of Grain A = Surface area of mass m2 h = Height of mass m2 Fc = Frictional Force = cdx/dt c = Coefficient of friction of grain x = Displacement of mass m1

    13. 13 Differential Equations

    14. 14 Differential Equations

    15. 15 Model Inputs and Outputs Inputs Mass of load 1 (m1) Mass of load 2 (m2) Outputs Proportion of load 1 in outbound load (c1) Proportion of load 2 in outbound load (c2)

    16. 16 Simulink Model

    17. 17 Inputs

    18. 18 Results

    19. 19 Results

    20. 20 Results

    21. 21 Conclusions Proportions of loads m1 and m2 in the outbound load can be determined at any given time At t = 0: Proportion of m1 = 1 and Proportion of m2 = 0 Proportion of m1 decreases and m2 increases with increasing time (FUNNEL FLOW). As m2 empties out, proportion of m1 starts increasing exponentially till it reaches an equilibrium value Profiles of c1 and c2 vary depending on m1 and m2

    22. 22 Further Development More grain loads Experimental determination of flow dynamics Relation with Angle of Repose Model applicable for different grains LIFO (Real world application) Simultaneous filling and emptying

    23. 23

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