Sand Particle Size Analysis by SedImaging in a Kalamazoo

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Sand Particle Size Analysis by SedImaging in a Kalamazoo River Field LabJerry Eykholt+, Greg Horstmeier+, Carrie Kempf+, Roman Hryciw*, and Andrea Ventola*

[email protected] Associate – Environmental Engineer

+Wood E&IS, Madison WI and Novi MI*University of Michigan, Ann Arbor. MI

Battelle Tenth International Conference on the Remediation and Management of Contaminated Sediments, Session E6

• Sedimentation and digital image analysis technology developed by Prof. Roman Hryciw, University of Michigan

• First river sediments application and first field lab demonstration for SedImaging (2017, “FieldSed”)

• Kalamazoo River, Michigan. Area 5 Supplemental Remedial Investigation (SRI)– 9.1 miles of river, with associated floodplains &

110 acres of impounded lake– Reach from Trowbridge Township Dam to

Allegan City Dam – Part of Operable Unit 5 of the Allied Paper,

Inc./Portage Creek/Kalamazoo River Superfund Site

SedImaging testing at Kalamazoo River Project

2 A presentation by Wood.

• Concepts and goals of testing

• SedImaging technology as applied to Recon I/II phases of the SRI

• Results and insights

Organization


… to highlight possible sediment texture effects on PCBs and TOC

Concepts: particle size parameters D10 vs D50…


Total PCBs

Draft and preliminary, example data

TOC

sieve sieve

Physical conditions to guide stratified sampling

Relevance for spatial problem


Coarse & few fines(lower sample density)

Fine sand & silts

Fines(higher sample density)

Fine sands,few fines

Example only

Conceptual area and no set scale

• Field or field lab testing of sediment particle size distributions– Sample selection from geologists/loggers– More detailed, on-site analysis– Focus on fine sands and coarse silts (0.4 to 0.05 mm)

• Throughput and quality important

Concepts


• LISST (Sequoia Scientific) other laser particle sizers • Cone penetrometer

– In-Situ Friction-Sound Probe (Chadwick and Arias, 2014) – Hydraulic profiling tool (Dietrich et al., 2008)

• Sieve-hydrometer field lab• Pipette method• USGS underwater camera / microscope (Rubin, 2007)

Some options


SedImaging


Ohm, H-S, and R.D. Hryciw (2014)

• Proof of concept testing• Ponar sampling, 46 locations• Grab samples logged and shipped to University of

Michigan for SedImaging and LISST-Portable XR • Splits sent to commercial lab (Eurofins) for

sieve/hydrometer analysis

Recon I Event – spring/summer 2017


U of Michigan SedImaging Lab, Recon I Testing


LISST Portable XR, Sequoia ScientificSedImaging of sands, Andrea Ventola & Junxing Zheng

Overall good agreement between two datasets when <25% fines • U of M tests: Sedimaging + LISST• 31 of 46 SED samples have good agreement

Recon I – SedImaging results vs. sieve/hydrometer


LISST consistently shows higher percent fines when sieve/hydrometer results indicate >40% passing 0.1 mm size

• 15 of 46 showed sediments with higher fines due to LISST device, and less resolution/sharpness

Recon I – LISST vs sieve/hydrometer


• Advance SedImaging, apply in field lab (for first time) • U of M modifications on columns and methods to

– gain more throughput– eliminate any need for oven drying– estimate % fines– train Wood field lab staff

• Field lab set up by Wood• Camera and SedImaging supplies provided by U of M

Recon II field lab event – fall 2017


• Remove >2 mm sediment by #10 wet sieve• Prepare slurry with <2 mm sediments to fill line, weigh wet

column• Remove fines by multiple decants• With clear supernatant to fill line, weigh wet column

SedImaging:• Allow sedimentation to segregate size classes• Digital imaging and image analysis

Summary of main processes


Detailed processing for Recon II


Homogenized Soil or

Sediment

100 ± 50 g (wet)

Remove coarse

particles (#10 sieve, optional)

Air Dry

Load and weigh pre-segregation

tube

>2mm

<2mm Return soil retained to

pre-segregation

tube

Sedimaging

W1

WPreWPost

Agitate; settle T1; decant, discarding

suspension; repeat n-times

Agitate; settle T2; decant over #200

Remove fines

<75µm

>75µm

FinesWeigh pre-segregation

tube with water

WEW

Dry weights (calculated):

𝑾𝟐 𝟑𝑮𝑺 ∗ 𝑾𝑷𝒓𝒆 𝑾𝑬𝑾

𝑮𝑺 𝟏

𝑾𝟑 𝑾𝟐 𝟑 𝑮𝑺 ∗ 𝑾𝑷𝒐𝒔𝒕 𝑾𝑬𝑾

𝑮𝑺 𝟏Mass fines:

Mass soil passing #10:

T2 << T1

Steps at a glance


Prep tube with fines in suspension

After fines removed, sands loaded into sedimentation tube (square cross-section)

Settled sands to be imaged

Presegregation tube, steps prior to loading column


Coupling with gasket on top of column

Vacuum holds

sediment in place

Sedimentation


Release vacuum to charge column (remove stopper)

Same process, but on tube rack

video

Image analysis


Camera takes multiple images of full view at various foci, and rendering software optimizes and merges images into one.

Resulting image is high-resolution, and in focus from top to bottom.

Multiple sides of the column are usually imaged.

If selected, images for each side are processed by Matlabto generate size distributions.

Camera software in active view mode, full view

Setting best focus at top

Setting best focus at bottom

Resulting image of a fine sand (part 1 of 6, top)


2 mm

1 mm

0.4 mm

0.1 mm

0.2 mm

Resulting image (2 of 6)


2 mm

1 mm

0.4 mm

0.1 mm

0.2 mm



2 mm

1 mm

0.4 mm

0.1 mm

0.2 mm



2 mm

1 mm

0.4 mm

0.1 mm

0.2 mm



2 mm

1 mm

0.4 mm

0.1 mm

0.2 mm

Resulting image (6 of 6, bottom)


2 mm

1 mm

0.4 mm

0.1 mm

0.2 mm

SedImaging to particle size distributions

26 A presentation by Wood.26

Corecollected &

logged

Is the sample interval mostly fines, mostly coarse, or

intermediate?

Preprocess intermediate samples, weigh coarse particles, weigh fines

SedImaging PSD raw curve

generation (U of M)

Adjust PSD to percent passing #10

and #200 sieves(Wood)

Final PSD and gradation parameters

Fine and coarse samples not SedImaged

80 samples processed in field lab• 60% sands with trace fines• 20% sands with 5-12% fines• 20% silty sands with > 12 % fines

SedImaging to particle size distributions


USCS: Poorly graded (fine) sand with silt (SP-SM)

D10 = 0.07 mmD50 = 0.20 mm

Cu = 3.0 (uniformity)

10.3% fines3.4% as imaged6.9% decanted

Total PCBs = 0.033 mg/kg

QA/QC


• Several samples repeated at Univ. of Michigan lab

A5-SED-068-G-0-6-1017 A5-SED-083-G-60-72-1017

Throughput – breakdown of processing times


Homogenized Soil or

Sediment

100 ± 50 g (wet)

Remove coarse

particles (#10 sieve, optional)

Air Dry

Load and weigh pre-segregation

tube

>2mm

<2mm Return soil retained to

pre-segregation

tube

Sedimaging

W1

WPreWPost

Agitate; settle T1; decant, discarding

suspension; repeat n-times

Agitate; settle T2; decant over #200

Remove fines

<75µm

>75µm

Fines

T2 << T1

If applicable:5 min.

10-15 min.If applicable: 10-20 min. 10-20 min. 10 min.

Cleaning (column,

sieves, station)

10 min.

Shortest scenario total: 45 min.Longest scenario total: 85 min.

Average scenario: 60 min.

Summary of QA/QC and field lab throughput


Recon I Recon IISedImaging tests 46 80

U of Michigan – split sample N/A 6

U of Michigan – pre-processed /imaged portion only

0 5

External Lab (sieve & hydrometer) 46 0

Processing rate N/A 12/day

• Field lab demonstrated overall good performance of SedImaging technology– Based on peer-reviewed and reproducible method for sands– High resolution method

• Less throughput than expected (higher labor costs)– Slower on pre-processing (#10 sieve, fines removal)– Image analysis conducted off-site– Potential for rapid-analysis, same-day field decisions

• Advantages over conventional sieve/hydrometer testing– Higher resolution for sand size, down to 50 microns– Particle shape, color, and other factors collected in images– May be combined with on-site analysis of fines

Summary


Acknowledgements


Prof. Roman Hryciw

Greg Horstmeier, Carrie Kempf, David Miller, Nick Rogers, Bonny Gibney, and our field sampling and logging crews

Evan Thomas, Cynthia Draper, and Joe Abid

Junxing Zheng (Iowa St. Univ.)

Andrea Ventola

• Amec Foster Wheeler (2017), Area 5 Draft Reconnaissance II Technical Memorandum Appendix F. OU-5 Allied Paper, Inc./Portage Creek/ Kalamazoo River Superfund Site. September 27.

• Wood (2018), Area 5 Draft Phase I Field Sampling Plan, Appendix D, OU-5 Allied Paper, Inc./Portage Creek/ Kalamazoo River Superfund Site. July 13.

SedImaging references• Ohm, Hyon-Sohk, and Roman D. Hryciw (2014), “Size Distribution of Coarse-Grained Soil by SedImaging,” Journal of

Geotechnical and Geoenvironmental Engineering, 140(4).• Zheng, Junxing, and Roman D. Hryciw (2016a), “Index Void Ratios of Sands from Their Intrinsic Properties,” Journal of

Geotechnical and Geoenvironmental Engineering, 142(12). • Zheng, Junxing, and Roman D. Hryciw (2016b), ‘Roundness and sphericity of soil particles in assemblies by computational

geometry,” J. Computing in Civil Engineering. 30(6).• Zheng, J. and R. Hryciw (2017), “Soil Particle Size and Shape Distributions by Stereophotography and Image Analysis”,

Geotechnical Testing Journal, ASTM, March 2017.

Other technologies• Chadwick, D.B., and E. Arias (2014), “Demonstration of an In-Situ Friction-Sound Probe for Mapping Particle Size at

Contaminated Sediment Sites”, Technical Report 2040, SPAWAR Systems Center Pacific, April 201https://clu-in.org/download/contaminantfocus/sediments/Sediment-ER-200919-FR.pdf

• Dietrich, P., J.J. Butler, and K. Fai. (2007), “A rapid method for hydraulic profiling in unconsolidated formations,” Groundwater, 46(2):323-328.

• Rubin, D.M, et al (2007), “Underwater microscope for measuring spatial and temporal changes in bed-sediment grain size”, Sedimentary Geology, 202:202-408.

References


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Sand Particle Size Analysis by SedImaging in a Kalamazoo