Effect of Filling Height on Bulk Density of Wheat in a Test Weight Cup

Presented by: Marvin C. Petingco PhD Student, Biological & Agricultural Engineering Kansas State University

Definition the increase in grain bulk density due to the compressibility of grain when subjected to the cumulative weight of overlying material in a storage unit.

Related terms “packing factor”, “compaction”, “pack”

Use as an adjustment factor to accurately determine the mass of the grain stored in a bin

Different impacts on operations Grain elevators – inventory, auditing On-Farm bins – insurance

Packing

Description: A computer program for predicting packing and mass of stored grain in a bin

How it works? Use Jannsen’s equation and the relationship between overbearing pressure , moisture content and bulk density

Packing is dependent on the initial or uncompressed bulk density (Do) In practice, test weight is used as input for Do Q: Is the uncompressed in-bin bulk density = test weight?

WPACKING

Source: Thompson et al., 1987; Ross et al., 1979

Dx= weighted average of Di’s D0= initial uncompressed bulk density Di’s

Bulk density gradient

D1

Dn

D2

dy

Bulk Density is NOT an intrinsic property Test weight and hectoliter weight

oBoth standard measure of bulk density oUse different setups oGive two different values Conversion factor was developed

Q: How much does the uncompressed in-bin bulk density varies with the test weight?

We want to determine the in-bin bulk density before overbearing pressure is applied

Improve WPACKING prediction

A: They are NOT Equal.

Test weight Device (Seedburo)

Australia Chondrometer (Graintec)

Source: Greenaway, 1977,

Manner of filling: filling method, filling height, filling rate Size and type of confining space

Grain properties kernel density, moisture content, friction coefficients

size of the particles, size distribution, composition – amount of fines, broken,

and foreign materials, dockage

particle shape

Factors Affecting Bulk Density

Source: Stephens & Foster, 1978; Chang et al., 1983; Mosey, 1984; Molenda et al., 1993; Zhong et al., 2001; Montross & McNeill, 2005; Yang & Williams, 1990 -

Determine the effect of filling height on wheat bulk density in a test weight cup Use Discrete Element Method (DEM) simulation to predict the wheat bulk

density for different filling heights

Objectives of the Study

DEM models the true physics of every single particle

Sample hard red winter wheat (Varieties: Garrison, KanMark, 1863)

Materials and Methods

Grain Properties Garrison KanMark 1863

Test Weight, lb/bu 58.68 (0.14) 61.44 (0.09) 61.70 (0.07)

MC, % wb 11.1 (0.1) 11.5 (0.1) 12.4 (0.1)

Kernel Apparent Density (kg/m3) - 1370 (3) 1378 (4)

Mean Kernel Length (mm) - 5.3 (0.5) 5.6 (0.5)

Mean Kernel Width (mm) - 2.6 (0.6) 2.7 (0.5)

Mean Kernel Thickness (mm) - 2.5 (0.4) 2.5 (0.4)

Mean Equivalent Sphere Diameter (mm) - 3.2 (0.5) 3.4 (0.5) % Retained in Sieve

Variety #6 #7 #8 #10 Pan Total

Garrison 0.2 21.6 60.6 16.0 1.6 100.0

KanMark 14.2 67.3 15.5 2.8 0.3 100.0

1863 9.7 64.0 22.0 3.9 0.4 100.0

Setup Winchester bushel test with some modifications

Materials and Methods

Filling heights: 1h, 2h, 4h, 8h, 16h, 32h

DEM Simulation Particle models

Materials and Methods

Without Striking With Striking

Single-Sphere Seven-Sphere

Schemes

DEM Simulation Particle and Material Properties Input

Materials and Methods

Particle Properties Measured/ Published* 1s 7s

Particle – Wheat

Poisson’s ratio 0.2* 0.2 0.2

Solid Density (kg/m3) – KM,1863 1374 1374 1374

Shear Modulus (Pa) 7.65 x 107* 7.65 x 107 7.65 x 107

Coefficient of Restitution (wh-wh) 0.33* 0.50 0.33

Coefficient of Static Friction (wh-wh) 0.30*, 0.38* 0.30 0.38

Coefficient of Rolling Friction (wh-wh) 0.20*, 0.18* 0.15 0.05

Coefficient of Restitution (wh-b) 0.6* 0.50 0.50

Coefficient of Static Friction (wh-b) 0.37* 0.2 0.30

Coefficient of Rolling Friction (wh-b) 0.1* 0.05 0.05

Coefficient of Restitution (wh-w) - 0.40 0.40

Coefficient of Static Friction (wh-w) - 0.30 0.30

Coefficient of Rolling Friction (wh-w) - 0.01 0.01

Material Properties Input Values (1s,7s)

Material-Brass

Poisson’s ratio 0.31*

Solid Density (kg/m3) 8490*

Shear Modulus (Pa) 3.70 x 1010*

Material-Wood

Poisson’s ratio 0.4*

Solid Density (kg/m3) 5000*

Shear Modulus (Pa) 1.00 x 107*

Properties Input Values (1s,7s)

Size Distribution

Mean – KM, 1863 1.00 (3.3 mm)

Std Dev – KM, 1863 0.15 (0.5 mm)

Scale by Radius

Laboratory Test: Filling Height Vs Bulk Density

Results and Discussion

Variety Bulk Density (kg/m3) at Different Filling Heights

1h 16h 32h

KanMark 791.1 (1.3) 802.1 (0.5) 808.3 (0.3)

1863 794.5 (1.0) 806.3 (0.3) 811.5 (0.6)

Garrison 756.3 (1.8) 766.0 (4.3) 774.3 (4.0)

643216842

780

775

770

765

760

755

Filling Height (in)

Bulk

Den

sity

(kg/

m3)

95% CI for the Mean

Individual standard deviations are used to calculate the intervals.

Interval Plot of Bulk Density vs Filling Height

Increase in bulk density as filling height is increased

1h

16h

32h

DEM simulation is done at particle level

Results and Discussion

Time to Fill the Test Cup: DEM Simulation Vs Laboratory Results

Results and Discussion

Filling Height Time to Fill (s) % Difference from Actual

Actual 1s 7s 1s 7s 1h 5.4 (0.2) 6.1 5.9 13 9

16h 5.4 (0.1) 6.1 6.1 13 13 32h 5.4 (0.2) 6.3 6.2 17 15

Simulation time ~ 10 – 20 % difference with the actual Time for mass to stabilize after overflowing in the test cup takes a lot of time in simulation as compared with laboratory experiment

DEM Simulation: Filling Height Vs Heap Profile Results and Discussion

Single-Sphere Particle Model Seven-Sphere Particle Model

1h

1h

16h

16h

32h

32h

Z

X

Z

X

Z

Y

Similarity of heap profile in ellipsoidal particle model with laboratory experiment

Importance of shape of particle model

Bulk Density: DEM Simulation Vs Laboratory Results

Results and Discussion

Filling Height Bulk Density, (kg/m3) % Difference from Actual

Actual 1s 7s 1s 7s

1h 792.8 789.1 798.7 -0.5 0.7

16h 804.2 803.9 807.9 0.0 0.5

32h 809.9 815.6 821.2 0.7 1.4

Filling Height Bulk Density, kg/m3) % Difference from Actual

Actual 1s 7s 1s 7s

1h 792.8 780.7 790.5 -1.5 -0.3

16h 804.2 792.8 798.6 -1.4 -0.7

32h 809.9 801.8 810.4 -1.0 0.1

DEM simulation without striking

DEM simulation with striking

Simulated and actual bulk densities are in good agreement for both schemes

Bulk density of wheat increases with filling height DEM simulation can predict the bulk density of wheat (KanMark, 1863) at

different filling heights Single-sphere particle model

oWithout striking predicted with lower percentage error (-0.5% to +0.7%) compared with striking (-1.0 % to -1.5%)

Seven-sphere particle model oWith striking predicted with lower percentage difference (-0.7% to +0.1%)

compared with without striking (+0.5 % to +1.4 %) Actual particle shape is critical to get accurate surface or heap profile

Conclusion

Example: Filling Height and Bin Diameter

d , h , H d , h , H’ d', h , H’ Initial Bulk Density or

Test Weight BD

d*, h , H* Bulk Density as

affected by filling height BD(H’)

Bulk Density as affected by filling height and bin

diameter BD(H’, d’)

Uncompressed In-Bin bulk density

BD0

Average In-Bin Bulk Density at depth y using

WPACKING

d*, h , H*, y

Laboratory Experiment and DEM Simulation DEM Simulation DEM-ANSYS Simulation and WPACKING

d

h d

h

d'

h

d*

h

d*

h

H

H’ H’ H*

H*

y

What we want to do…

Acknowledgements The Andersons Grant Funding Program Team Competition USDA and Kansas Ag Experiment Station Dan Brabec, Jonathan Zeller, Alex King, Elizabeth Maghirang, Dennis Tilley, Austin

Ebert, Josephine Boac, Fei Xyza Asuncion

Funding Source: The Andersons Grant Funding Program Team Competition Project Title: Determining Time, Aeration, and Loading Cycle Effects on Grain Packing Project objective being addressed: Effect of secondary crop quality parameters on packing Team Members: Mark Casada - USDA Ronaldo Maghirang –Kansas State University Marvin Petingco – Kansas State University Sidney Thompson – University of Georgia Michael Montross – University of Kentucky Samuel McNeill – University of Kentucky Aaron Turner – University of Kentucky Rumela Bhadra – Kansas Department of Health & Environment

THANK YOU!