EPA Report Number
                                                                June, 1991
        PARAMETERS AFFECTING THE MEASUREMENT OF
HYDRAULIC CONDUCTIVITY FOR SOLIDIFIED/STABILIZED WASTES
                                by

         DJ. Conrad, S.A. Shumborski, L.Z. Florence, AJ. Liem
                     Alberta Environmental Centre
                 Vegreville, Alberta, Canada  TOB 4LO
                           CR814860-01-1
                           Project Officer

                             C. Mashni
                   Risk Reduction Engineering Lab.
                 U.S. Environmental Protection Agency
                       Cincinnati, Ohio  45268
              This study was conducted in cooperation with
                   the Alberta Environmental Centre,
                Vegreville, Alberta, Canada TOB 4LO
                Risk Reduction Engineering Laboratory
                 Office of Research and Development
                U.S. Environmental Protection Agency
                       Cincinnati, Ohio  45268

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                                    NOTICE
      The information in this document has been funded in part by the U.S. Environmental
Protection Agency  under  Cooperative Agreement  #  CR814860-01  with  the  Alberta
Environmental Centre, Vegreville, Alberta, Canada.  It has been subjected to the Agency's
peer and administrative review and approved for publication as an EPA document.  Mention
of trade names or commercial products does not constitute endorsement or recommendation
for use.
                                      - 11 -

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                                 FOREWORD

      Today's rapidly developing and changing technologies and industrial products and
practices frequently carry with them the increased  generation of materials that, if
improperly dealt with, can threaten both public health and the environment. The U.S.
Environmental Protection Agency is charged by Congress with protecting the Nation's
land, air, and water resources.  Under a mandate of national environmental laws,  the
Agency strives to formulate and implement actions leading to a  compatible balance
between improving the quality of life and minimizing the risks to the environment. These
laws direct the EPA to perform research to define our environmental problems, measure
the impacts, and search for solutions.

      The  Risk Reduction Engineering  Laboratory is responsible  for planning,
implementing, and managing research, development, and demonstration programs to
provide an authoritative and defensible information that can be used by both regulators
and the regulated in their common efforts to protect the environment from the hazards
of industrial and municipal waste.   This publication is one of the products of that
research and provides a vital communication between the researcher and  the user
community.

      This  report describes the effects of varying cement content on the hydraulic
conductivity of a solidified hazardous waste. The goal of this work is to gain a better
understanding of the mobility of constituents of solidified/stabilized hazardous waste and
how to minimize that mobility.  This information should be of assistance to regulators
and businesses subjected to the  waste  management requirements  of  the Resource
Conservation and Recovery Act.

                                      E. Timothy Oppelt, Director
                                      Risk Reduction Engineering Laboratory

                                      - iii -

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                                    ABSTRACT
       A series of experiments conducted at the Alberta Environmental Centre examined the
variation in hydraulic conductivity (K) within and among three matrices formed by steel mill
baghouse dust treated with 8%, 9% and 10% Normal Portland Cement at a water/cement ratio
of 1:1. Within the 8% and 9% matrices, test gradient (i) and back pressure (P) were combined
into 3x3 factorial treatments. Commercially available equipment was modified to  allow
sensitive and .continuous monitoring of hydraulic conductivity. A permeant-matrix interaction
was indicated by K decreasing with time at a rate which increased with higher cement
contents.  After hydraulic conductivity  testing, the samples were examined by  scanning
electron microscopy and energy dispersive x-ray  analysis.  A cement  hydration product,
identified as  ettringite, had formed in the solidified/stabilized waste pores.  This product
reduced hydraulic conductivity by two orders of magnitude by restricting conducting pores.
Four to seven weeks  of testing were required before an acceptable equilibrium had been
reached and statistical comparisons among the i x P treatments  were made.  Within each
matrix, gradient was statistically the most significant parameter accounting for 60% of the
variation in results.  The response to gradient was different than that observed with clay and
soil-liners  in the literature.   The overall mean hydraulic conductivity (p<0.01) of the  8%
matrix (10 ± 5 x 10"6 crasec"1) was significantly greater than that of the  9% matrix (0.06 ±
0.03 x 10'6 cm-sec'1) (p<0.01).

       Temporal effects, gradient and cement content were identified as important factors
affecting hydraulic conductivity measurements and must be considered by regulatory tests.
Bulk density was a useful quality control criterion for minimizing sample variance within each
matrix.
                                       - iv -

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This work was submitted in fulfillment of Assistance ID No. 814860-01-1 under the partial
sponsorship of the U.S. Environmental Protection Agency. This report covers a period from
October 14, 1988 to December 31, 1990 and work was completed as of December 31, 1990.
                                      - v -

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                               CONTENTS

FOREWORD	  iii
ABSTRACT	  iv
FIGURES	  viii
TABLES	x
ACKNOWLEDGEMENTS			  xi
   1.0 INTRODUCTION	 1
   2.0 CONCLUSIONS AND RECOMMENDATIONS	4
   3.0 LITERATURE SEARCH	6
   4.0 MATERIALS AND METHODS	10
       Raw Materials	10
       Sample Preparation and Acceptance	10
       Instrumentation	 .  14
       Sample Saturation		16
       Sample Porosity .	16
       Sample Characterization		17
       Electron Microscopy	1 .....  17
       Chemical Analyses . .	17
   5.0 EXPERIMENTAL PROCEDURES	,	20
       Sample Preparation	20
       Hydraulic Conductivity Data Recording  	20
       Determination of Hydraulic Conductivity
          Equilibrium Conditions	20
       Model Testing and Test Precision	21
       Experimental Design	21
       Physical Characteristics .	22
   6.0 RESULTS AND DISCUSSION 	23
       Choice of Raw Materials	23
       Bulk Density Measurements	25
       Temporal Effects During Equilibration	  26

                                  - vi -

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       Model Testing and Test Precision	....... 37
       Solubility Effects During Testing	  38
       Response Surface Regression Analysis	„	 42
          Effect of Matrix	;	42
          Effect of Instrument Parameters	44
       Effect of Sample Porosity	50
       Saturation Considerations	51
       Comparison of Solidified/Stabilized Waste
          to Soil/Clay Liners	53

REFERENCES  	55
APPENDICES		 59
   A.  Calibration of Geotest Permeameter Interfaces	59
   B.  In-House Computer Program	•	62
   C.  Experimental Data	65
                                      vii -

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                                   FIGURES

1.  Modified Sample Support	  12
2.  Modified Tamping Bar	13
3.  Schematic of Hydraulic Conductivity Apparatus  	15
4.  Flexible Wall Membrane Arrangement	18
5.  Variation of Hydraulic Conductivity at
    8%, 9% and 10% Cement	27
6.  Fibrous Growth in Tested 8% Matrix (lOOOx)	  30
7.  Fibrous Growth in Tested 8% Matrix Showing
    Morphological Similarities to Ettringite (6000x)	30
8.  X-ray Analysis of Individual Fibres	31
9.  Ettringite Growth in Pores of the 9% Matrix
    Sample (lOOOx)	32
10. Ettringite Growth Blocking Pores in the 9%
    Matrix Sample (lOOOx)	32
11. Ettringite Growth in the 10% Matrix Pores (200x)  	34
12. Ettringite Growth in the 10% Matrix Pores (lOOOx)	  34
13. Samples Cured in Humidity Chamber Showing No
    Evidence of Ettringite	.35
14. Cement Control  Sample Cured Under Water	  36
15. Cement Control  Sample Cured in the Humidity Chamber	36
16. Deviation from the Predicted 8% Model   ...'..	  39
17. Hydraulic Conductivity Replicates for 8% Matrix
    at Median Levels of i and P  	39
18. Leaching of Hydraulic Conductivity Samples During Testing	40
19. Log K vs Cumulative TDS of Median Levels of i and P	42
20. Predicted Values for the 8% Matrix Showing the Predicted Maxima  . .  47
21. Contour Plot of Predicted Values for the 8% Matrix Showing Hydraulic
    Conductivity Contour Intervals	  47
                                     - vui -

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22. Response Surface Plot of Predicted Values for the 9% Matrix Showing
    the Linear Relationship of Gradient and Back Pressure	48
23. Contour Plot of Predicted Values for the 8% Matrix Showing
    Hydraulic Conductivity Intervals	48
A.1  Apparatus for Calibration of Geotest Permeameter Interfaces	60
                                       - rx -

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                                  .  TABLES

.1.   Hydraulic Conductivity Sample Formulations	  11
2.   Sample Compaction Procedure Modifications	11
3.   Physical Test Methods	19
4.   Test Parameters and Levels	21
5.   Baghouse Dust Metal Analyses	24
6.   Sample Bulk Densities	  25
7.   Model Coefficients for the Change in Hydraulic Conductivity
    with Time	.26
8.   Descriptive Statistics of Log10k for the 8% Matrix Replicates	38
9.   Composite Permeant Analyses of the 9% Matrix	  41
10. Response Surface Regression Analyses 	46
11. Sample Porosity  	-.50
12. Sample Saturation	52
13. Unconfined Compressive Strength Tests (kPa)  ..	  53
A.1 Interface Calibrations ...'..	  61
C.I Experimental Trial Data  	64
C.2 8% Matrix Replicate Data	.66
                                      - x -

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                             ACKNOWLEDGEMENTS

       The authors wish to thank the contributors in Alberta business, research institutions and
the Alberta Environmental Centre who assisted in the production of this study.  Specifically
the contributions of the following individuals and companies are noted:  Mr. A. Slessor of
Lafarge Canada Inc. and Stelco, Edmonton (Alberta)  Works for contributing raw materials;
Ms. P. Soldan, Ms. C. Jackson and Ms. M. Zadkovich (Environmental Technology Division)
for their assistance and patience in manuscript preparation; Mr. J. Kirtz, Mr. P. Henry (Animal
Sciences Division), Mr. K. Klingbeil (Environmental Technology) and Mr. M. Herbut (Plant
Sciences Division) for computer graphics; Dr. M. Wilson for his valuable suggestions during
the course of this project; and Dr.  D.  Ivey (University of Alberta), Dr. R. Mikula (Energy,
Mines and Resources Canada), and Dr. M. Neuwirth (Chemistry Division) hi providing SEM,
STEM and X-ray analyses.
                                       - xi -

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                                    SECTION 1.0
                                  INTRODUCTION
       Solidification and stabilization (SS) technologies are often used to treat -hazardous
wastes to reduce the environmental impact of then- disposal.  Solidification removes free
water, usually by the  hydration reactions of lime or cementitious materials, producing  a
monolithic solid with reduced surface area. Stabilization with cementitious materials reduces
the  solubility of wastes by the  alkaline  precipitation  of metal  hydroxides  or metal
incorporation into the hydration products of cement.

       The long term behaviour of these treated wastes is  the subject of much concern.
Depending on the disposal scenario, treated wastes are eventually subject to leaching by
ground water, precipitation, or leachate.  If the treated waste is relatively permeable, leachant
flow will be through the whole of the material rather  than being confined to the external
surface area.  Thus, a major benefit of SS  treatment, the reduction of surface area available
for leaching is compromised.

       The flow of liquid through a porous medium is described by Darcy's Law.  The liquid
superficial velocity (Flowrate/Area) per unit gradient is defined as hydraulic conductivity,
which is a function of the properties of the medium and the liquid. Gradient is defined as the
headloss  which occurs over the sample (cm of H2O)  divided  by the .sample length (cm).
Darcy's Law may be written as:
where  K  is hydraulic conductivity  (crasec"1), Q is  flow rate  (cm3.sec"1), i is  gradient
(dimensionless) and A is cross-sectional area (cm2).

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       Permeability, a property of the medium alone, is related to hydraulic conductivity by
the following relationship:
                                            PS
where K is permeability (cm2), u is absolute viscosity of the liquid (g.cm^.sec"1), p is density
of the liquid (g.crn"3) and g is acceleration of gravity (980 cm.sec"2).

       When there is no medium-liquid interaction, permeability is an intrinsic and useful
property of a medium.  The flow rates of different liquids through a medium can be readily
predicted from its permeability and the properties of the liquids. However, when there are
changes in liquid properties, due to dissolution, or in the internal structure of the medium, as
shown in this paper, the meaning of permeability becomes obscure. Since it is the flow rate
of  aqueous  permeant through  SS  waste which is of environmental  interest, hydraulic
conductivity  is the proper terminology and is used herein.

       The literature available on hydraulic conductivity measurement with environmental
implications  deals predominantly with clay and soil liners.  Researchers are interested in the
effects of permeants, specifically inorganic salt solutions (1), organic fluids (2) and landfill
leachates  (3). Test parameters such as saturation  (4), temporal effects (5, 6) and gradient (6,
7) have been studied.

       The corresponding information on solidified/stabilized waste is, however, practically
non-existent Nor is there sufficient information which' addresses the differences between clay
or soil liners and solidified/stabilized waste, such as compressive strength and permeant-matrix
interactions.

       This report deals with the effects of parameters affecting the measurement of hydraulic
conductivity  of solidified/stabilized waste. The study was  undertaken to form bases for the
development of a regulatory test method - to improve intra and inter-laboratory precision - and
to correlate accelerated laboratory test results to those occurring under field conditions.
                                         -2-

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       The scope of the investigation was confined to the following:
       one waste, steel mill baghouse dust, treated with three portions of Normal Portland
       .Cement to produce a range  of  hydraulic conductivities similar to those found  in
       commercial solidification/stabilization processes.
       the following test and instrument parameters:  sample preparation, temporal effects,
       gradient and back pressure.

       New equipment was  acquired and modified to  allow for  sensitive, accurate and
continuous flow measurements.  Particular attention was given to minimize variance due  to
sample preparation, and statistical methods and experimental designs were used to delineate
parametric effects.  Electron microscopy, chemical analyses and measurements of physical
properties were conducted to assist in the interpretation of the observed phenomena.
                                        -3-

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                                   SECTION 2.0

                    CONCLUSIONS AND RECOMMENDATIONS

1.     Hydraulic conductivity was sensitive to matrix composition.  Significantly different
       hydraulic conductivities  were measured between samples  differing only by 1%  in
       cement content.   The  ability to  distinguish such  samples  was  attributed to the
       institution of a strict quality control criterion for sample preparation based on bulk
       density.  The corollary is that the  variance of hydraulic conductivity due to sample
       preparation  can be minimized by using that criterion.
2.     Hydraulic conductivity decreased with elapsed time during testing.  A power function
       in the form  of y = axb describes the relationship.  The decrease could be explained by
       long-term cement hydration reactions forming ettringite in the permeant-conducting
       pores. Although matrix dissolution occurred, no effect was observed over the testing
       period of up to 80 days.
3.     The  effects of gradient and back  pressure on hydraulic  conductivity  were the
       following:
       -   Gradient was the most significant parameter and its correlation  with hydraulic
       conductivity was positive, the opposite to  that for  soil and  clay  liners.  This was
       attributed to the higher unconfined compressive strength and the corresponding lesser
       degree of sample consolidation.
       - Medium and high levels of gradient and back pressure were the less sensitive region
       for hydraulic conductivity measurements. Falling-head permeameters, in which low
       levels of these parameters are used, are thus operated hi the more sensitive  region.
       -  Over the entire region of the chosen experimental levels, the measured hydraulic
       conductivities varied by a factor of four or less. Values obtained in the laboratory are
       thus reasonable estimates of those in the field conditions, provided that compaction and
       curing conditions are similar.
                                        -4-

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4.     The precision attainable for hydraulic conductivity measurements utilizing the quality
       control criteria, waste type and instrumentation of this study was improved by nearly
       50% over that reported in the literature.
5.     An exponential relationship between hydraulic conductivity and sample porosity was
       shown to be statistically significant.  How such a relationship varies  with different
       matrices was not investigated.

       Recommendations for regulatory test development:

1.     Bulk density should be used as a quality control criterion to reduce variance due to
       sample preparation.
2.     To improve precision, temporal effects should be taken into account and measurements
       carried out at high levels of gradient and back pressure.
3.     To estimate maximum hydraulic conductivity, measurements should be  made as soon
       as  the sample is cured.

       Recommendations for future work:         .

1.     Different matrices should  be tested for morphological changes  during  testing and
       improving the confidence in the effect of instrument parameters.
2.     Saturation effects should be studied to predict field hydraulic conductivity.
                                        -5-

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                                    SECTION 3.0

                               LITERATURE SEARCH
       The literature available on hydraulic conductivity measurement with environmental
implications deals predominantly  with clay and soil-liners.  Few references exist in the
literature concerning the measurement of hydraulic conductivity of solidified/stabilized wastes.
This section will briefly review the available literature in terms of the research undertaken
from a variety of sources and the direction it suggests for solidified/stabilized waste.

       Clay and soil-liner researchers are interested in the effects of dissolved inorganic and
organic materials on clay-liner permeability as measured by changes in permeant velocities.

       A study by Ather et al (1) investigated the effects of inorganic permeants upon the
hydraulic conductivity of bentonite. Increased ionic strength and cationic valence increased
the measured hydraulic conductivity.  The Gouy-Chapman double layer model of hyclrated
ions was used to explain postulated changes in the flocculated nature of the bentonite. The
degree of flocculation would affect the permeability of the bentonite clay.

       Lentz et al (8) observed changes in hydraulic conductivity due to cation exchange and
salt precipitation in a magnesium - montmorillonite clay when an alkaline permeant (NaOH)
of pH 13 was  used.

       Acar et al (2) found that pore size distributions of a kaolinite clay were unaffected by
a change in permeant from 0.1 N CaSO4 to an organic fluid.  However, organic solvents of
low water solubility, such as benzene and nitrobenzene, were found to decrease the measured
hydraulic conductivity by three orders of magnitude.  Soluble organics, such  as phenol and
acetone, had minimal effects. Thus, differences in measured hydraulic conductivity were due
to the ability of solvents to displace pore water.
                                         -6-

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       The work of the above authors suggests that interactions between permeants and clays
have measurable effects on hydraulic conductivity.  Bowders  (9), discussing the work of
Pierce and Witter  (10)  in determining termination criteria for clay permeability testing,
stressed that  chemical equilibrium must be established when chemically reactive permeants
are used. For clays this would mean monitoring influent and effluent chemical characteristics.
Bowders agrees with Pierce and Witter on their termination criteria when water is used as the
permeant;  one pore volume of flow has been passed and hydraulic conductivity vs cumulative
pore volumes cannot be shown to differ significantly from zero.

       The degree of sample saturation has been found to affect hydraulic conductivity.
Elzeftawy  and  Cartwright (4) used soil  water retention  curves to  predict  hydraulic
conductivity.  They found that the hydraulic conductivity of a  soil at 100% saturation was
approximately four orders of magnitude  greater than at 50% saturation.   Carpenter and
Stephenson (6) observed that saturation generally increased during hydraulic conductivity
testing.

       Temporal effects have been noted.  Parker et al (5) observed that the permeability of
flyash stabilized  soils decreased over 13 days of testing  possibly due to a flyash - soil
interaction. Carpenter and Stephenson (6) noted decreased hydraulic conductivity for clays
over shorter time periods (2 hours).

       The effect of applied gradient has been studied. Carpenter and Stephenson (6) and Edil
and Erikson (7) both noted that hydraulic conductivity declined for clays as the gradient was
increased when flexible  wall  permeameter cells were  used.  The authors explained  these
results as due to sample consolidation. Edil and Erikson (7) noted that at high gradients (290-
360) gas bubbles were evolved in the effluent lines. This suggests an alternative explanation.
High pressure drops across a sample produce unsaturated conditions, due to liquid degassing,
which result in decreased hydraulic conductivity.
                                        -7-

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       Bryant  and  Bodocsi  (11)  collected  historical  data on hydraulic conductivity
measurements for clay liners  and analyzed  them  for  the  effects  of sample variation,
preparation, equilibration and gradient.  They noted many confounding effects, and suggested
that suitable experimental  designs should be chosen to properly estimate parametric effects.
Longer test periods and statistical approaches to determine equilibrium, as indicated by stable
hydraulic conductivity, were suggested.  Soil hydraulic conductivity  was found to be very
sensitive to preparation technique.  Some results showing decreased hydraulic conductivity
were explained by sample consolidation resulting from increased gradients.  -

       Pierce et al (12), who conducted ruggedness tests using both rigid wall and triaxial cell
permeameters, found that water content, lift thickness and back pressure had the greatest effect
on the measured hydraulic conductivity of a clay liner. The first two factors pertain to sample
preparation while the third is an instrument measurement parameter. Gradient was not found
to be significant  at relatively high  levels (i = 100, 200), typical  of  laboratory  tests.   The
hydraulic conductivity results exhibited large variability.  Thus, inter-laboratory results could
exhibit large  variation due to individual laboratories performing hydraulic conductivity tests
at different levels of these sensitive parameters.

       Cement and concrete researchers have investigated the permeability of hardened cement
pastes, as cement permeability will affect the weathering properties and corrosion of metal
reinforcing rods. This work has some applications to solidified/stabilized wastes because low
permeability products are desired for both products and industrial cements are often used as
solidification/stabilization  additives.

       Powers et al (13) noted that long term curing of cement pastes revealed a seven order
of magnitude decline in permeability compared to that of the fresh paste. This was explained
by the fact that cement gel occupies 2.1 times the volume of the unhydrated paste.  Thus, long
term  curing  causes discontinuities  in capillary porosity (14)  and decreased hydraulic
conductivity.  Patel et al (15) noted a similar phenomena,  that large pore fractions decreased
while gel (paste) porosity  increased during cement hydration.  Later research has attempted
                                        -8-

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 to develop models for hydraulic conductivity based on pore parameters.  Nyame and Illston
 (16) described their hydraulic conductivity data in terms of hydraulic radius theory. Hughes
 (17) considered pore isotropy and tortuosity in developing a hydraulic conductivity model.

       Stegemann and  Cote (18) included hydraulic  conductivity in  an inter-laboratory
 evaluation of solidified/stabilized waste.  A falling head method with a triaxial cell was used
 to measure hydraulic conductivity for thirty-seven waste  samples.  Commercially available
 solidification/stabilization treatment processes yielded hydraulic conductivities between 3 x
 10"4 and  7 x  10"8 cm-sec"1.  At  the interlaboratory level, the variance was  too  large to
 determine differences between individual products.  A pooled estimate of intralaboratory
 variance (which does not include  the systematic error of  each laboratory) was made.  Four
 replicates of the test were estimated to yield a  one order of magnitude precision at  the 95%
 confidence level.  (Based on a log-normal data distribution, the actual precision is X/-T 7.3.)

       Stegemann and Cote (18)  felt that  "differences  between  specimens of the same
 solidified product  appeared to be the main cause of the variability observed for this method".
 This indicates  waste heterogeneity and  sample preparation as sources of variance.  Bulk
 density is one measure of sample homogeneity.  Stegemann and Cote (18) reported a precision
 for bulk density of ± 0.14 g.cmT3 for three replicates of the 95% confidence level. This would
 correspond to a relative standard deviation of 3.9% at the  reported median of 1.44 g.cm'3.

       In summary, a review of the pertinent literature suggests several areas of consideration.
 Clay and soil-liner research  indicates that the  instrument parameters of gradient and back
pressure, as well as sample preparation and temporal considerations, should be elements -of
a hydraulic conductivity study.  Cement research indicates that cement hydration reactions
continue over a long time period.  A study of solidified/stabilized waste indicates that, on an
interlaboratory  and intralaboratory level, hydraulic  conductivity as practiced offers poor
precision, but that  this may largely be due to sample variance.
                                         -9-

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                                  SECTION 4.0
                          MATERIALS AND METHODS
RAW MATERIALS
                                                                           <
      The following raw materials were used to produce the surrogate solidified/stabilized
waste studied:

      1.  Steel Mill Baghouse Dust

      2.  16 - 30 mesh silica sand (Badger/Cardium Service and .Supply)

      3.  ASTM Type I Normal Portland Cement (Canada Cement Lafarge)

      4. Tap Water (North Saskatchewan River, conventional solids removal and partial lime
          softening; typical, finished water pH 8.5, hardness 100 ppm as CaCO3)


SAMPLE PREPARATION AND ACCEPTANCE

      The sample formulations, shown in Table 1 were chosen to give a range of hydraulic
conductivities typical of solidified/stabilized wastes (10~6 to 10"8 cm-sec"1).

      Samples were prepared by adding weighed portions of the dry ingredients to a Hobart
(Model N-50) mixer and mixing for two minutes at low speed (62 rpm, 139 rpm planetary).
The required water was added and mixing continued for two minutes with three pauses to
scrape material from the side of the mixing bowl.
                                      - 10-

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                 Table 1.  Hydraulic Conductivity Sample Preparations


Matrix
8%
9%
10%
Steelmill
Foundry
Dust (wt.%)
• 42.0
41.0
40.0

Silica
Sand (wt.%)
42.0
41.0
40.0
Typel
Portland
Cement (wt.%)
8.0
9.0
10.0


Water (wt.%)
8.0
9.0
10.0
       Samples were compacted in plastic molds (M.A. Industries, Peachtree, Georgia) using
method ASTM D558-82 (19), modified for the smaller sample size according to Table 2. The
modified sample preparation support and tamping bar are detailed in Figures  1 and 2
respectively.


                Table 2.  Sample Compaction Procedure Modifications

                                           Present Study        ASTM D558-82
Mold: Diameter (cm)
Height (cm)
Volume (cm3)
Sample: Compacted Height (cm)
No. of lifts
Blows/layer
Rammer: Diameter (cm)
Area (cm2)
Mass (g)
Drop (cm)
Compactive Energy (J.cm"3)
7.62
15.2
693
16.5
3
25
3.805
11.37
1390
30.48
0.448
10.16
11.643
944
12.7
3
25
5.08
20.30
2490
30.48
0.591
                                      -11-

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       Samples were leveled to the top of the mold with a metal straight edge and cured at
95% min. relative humidity at 23°C for a minimum of 28 days.

       After curing, samples were removed from their, molds, trimmed to ensure parallel end
faces and their physical dimensions and mass  determined prior to hydraulic conductivity
testing.

INSTRUMENTATION

       Three flexible wall permeameters (Geotest Model S5425) were used in this study.
Materials of construction were compatible with hazardous waste testing.   Metal parts  in
contact with permeants were stainless steel (type 316). Permeant flow lines were made  of
teflon and permeant interfaces were teflon-lined. The piston interface was sealed with Viton
"o-rings". The permeameters were modified by the substitution of the Transtek #0243 linear
variable displacement transducers, with Mitutoyo Digimatic Indicators Type  ID-130ME
(accuracy of 0.001  mm over a 30 mm range)'to measure  interface piston displacement.
Digitized  signals of  interface displacements  were  recorded  by a Mitutoyo  DP2-DX
miniprocessor, which is capable  of storing up  to  678 displacement and time records. An
additional modification was the  introduction of a Brainard Kilman model S-545 bladder
interface.  This modification isolated the air pressurization system from permeameter cell
water.  A schematic of the permeameter/interface/datalogger arrangement is shown in Figure
3. Details of interface calibration are given in Appendix A.

       Permeameter system pressures were measured by a Shape Instruments Ltd pressure
transducer model #SP1020 and displayed  on a Shape Instruments Ltd transmitter model
#SD7500/C. The pressure measuring system was calibrated with a dead weight tester.

       Results were downloaded to a Fujikama Model #fK 286 MT computer using in-house
produced software..  The computer program is described in Appendix B.
                                       -  14-

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g

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SAMPLE SATURATION

       Cured and trimmed samples were inserted into a latex membrane capped with porous
stainless  steel disks (K > 1 x 10"4 cm-sec"1) and mounted on the permeameter pedestal.  A
layer of aluminum foil covered with vacuum grease (for caustic corrosion protection) and a
second latex membrane were added to provide a barrier to gas diffusion into the sample from
the cell water. Details of the modified flexible wall membrane are shown in Figure 4.  .

       Samples were saturated by evacuating the sample for one hour from the outlet side
with a model D150 Precision  vacuum pump protected by  a  liquid nitrogen  cold trap.
Degassed water was introduced to the evacuated sample from the inlet end to begin saturation
and completed with the permeant pressurized to 7 kPa.

SAMPLE POROSITY                 .          .

       Sample porosity is defined as the ratio of interstitial volume to the total sample
volume.  For a granular solid in the liquid saturated state, porosity is one of the parameters
affecting headless and thus flow rate. Porosity, (E, - dimensionless) may be determined by
the following relationship:

                               E = l-^-(l-W)
                                         P
where  pB is the  wet sample bulk density (g.cm"3), p is the density of the  solids or "true
density" (g.cm"3)  and W is the proportion of water content in the sample (dimensionless).

       The actual pore volume (PV) in cm3 may be determined by:

                              PV = Vs - Ms (1 " *>
                                               P
where Vs is the sample volume (cm3) and Ms is the mass of the wet sample  (g).
                                       - 16-

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SAMPLE CHARACTERIZATION

      The methods used to measure the physical characteristics of the hydraulic conductivity
samples and the exuded permeants are listed in Table 3.

ELECTRON MICROSCOPY

      Electron microscopical analyses were performed on a Hitachi S510 scanning electron
microscope (SEM), a Hitachi X-650 (SEM) with energy dispersive x-ray spectrometer and a
Hitachi H-600 scanning transmission electron microscope (STEM) equipped with a Kevex Be
window X-ray detector.

CHEMICAL ANALYSES

      Chemical analyses of the foundry baghouse dust and exuded permeants was performed
utilizing the methods of ion coupled spectroscopy, atomic absorption spectroscopy, colorimetry
and potentiometric titration.
                                     - 17-

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                                                                                                                                           I

                                                                                                                                          co
Q.

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                         Table 3.  Physical Test Methods
      Parameter
             Method
     Modifications
       Moisture
ASTM D2216-80 (20)
Standard Method for Laboratory
Determination of Water Content of
Soil, Rock and Soil Aggregate
Mixtures
         60°C
    constant weight
     Bulk Density
ASTM D558-82 (19)
Standard Test Methods for
Moisture-Density Relations of Soil-
Cement Mixtures
     See Table 2
     True Density
ASTM C604-86 (21)
Standard Test Method for True
Specific Gravity of Refractory
Materials by Gas-Comparison
Pycnometer
Drie.d at 60°C, ground
to pass a 1.18 mm
screen.
     Unconfined
Compressive Strength
ASTM D1633-84 (22)
Standard Test Method for
Compressive Strength of Molded
Soil-Cement Cylinders.
Tested at 2.5 mm/min.
     Total Solids       AWWA #209 A (23)
                       Total Residue Dried at 103 - 105°C
                                     - 19-

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                                 SECTION 5.0

                        EXPERIMENTAL PROCEDURES
SAMPLE PREPARATION AND ACCEPTANCE

      Samples for hydraulic conductivity testing were prepared for each matrix in batches
of approximately eight samples. Samples accepted for testing met a quality assurance criteria
of ± 0.5% of the mean of batch bulk density. (See Bulk Density Measurements in Results and
Discussion)
HYDRAULIC CONDUCTIVITY DATA RECORDING

      Initial measurements were conducted at median experimental levels-of gradient (116)
and back pressure (69 kPa).  Data were  recorded when inflow and outflow rates were
determined to be within 5%.
DETERMINATION OF HYDRAULIC CONDUCTIVITY EQUILIBRIUM CONDITIONS

      Simple, linear regression was used to identify the time (x = day = independent
variable) when changes in hydraulic conductivity (y= K « 106  = dependent variable) had
attained sufficient stable equilibrium that the regression coefficient, or slope, was not different
than zero, as suggested by Pierce and Witter (10).
                                     -20-

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MODEL TESTING AND TEST PRECISION
       Three 8% matrix samples were tested concurrently on the three Geotest permeameters
of median levels of gradient and back pressure over a twenty-nine day period. Their measured
hydraulic conductivity was compared to that predicted from the equation derived previously
for the 8% matrix.
EXPERIMENTAL DESIGN

       Gradient and back pressure were varied and treated as independent continuous variables
at three levels in a completely randomized 3x3 factorial design (see Table 4). Gradient
levels corresponded to pressures of 10 kPa to 340 kPa.  Two independent experiments were
performed at 8%, and 9% matrix to provide a range of hydraulic conductivities.  Second-
degree polynomial  coefficients were calculated using response surface regression (SAS 1988
Release 6.03 (24)) to model the response of hydraulic conductivity to  varying levels  of
gradient and back pressure.

                        Table 4.  Test Parameters and Levels"1"

      Parameter                   .               Level
                              -1                   0                   +1
       Gradient                8                   116                 227
    Back Pressure
        (kPa)                 14                  69                  124"

* Performed at 8%  and 9% matrix
                                      -21 -

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PHYSICAL CHARACTERISTICS

       Companion samples were tested for the criteria listed in Table 3, before commencing
hydraulic conductivity testing, to determine the initial porosity, saturation and unconfined
compressive strength.  Hydraulic conductivity samples were tested for the same criteria to
determine if changes in physical characteristics  could account for the changes observed in
hydraulic conductivity.
                                       -22-

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                                    SECTION 6.0
                            RESULTS AND DISCUSSION
CHOICE OF RAW MATERIALS

       The raw materials used were chosen for this study to fulfill the following criteria:

       1)      the waste material should be  produced in high  volume, be amenable to
              solidification/stabilization treatment and have wide concern in terms of North
              American industry;

       2)      the solidification/stabilization treatment should be in common use  and generic
              rather than proprietary;

       3)      the solidified/stabilized waste treatments should produce values of measured
              hydraulic conductivity typical  of  commercially treated solidified/stabilized
              wastes.

       The waste material chosen was a baghouse dust collected from a steel mill paniculate
emission control system. Baghouse dusts constitute a large portion of the 9000 tonnes of
wastes produced annually by the foundry industry in Alberta (population 2.4 million). A nitric
acid digestate of the baghouse dust used in this  study was analyzed with an ion coupled
plasma spectrometer. Analyses are summarized in Table  5.
                                       -23-

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                       Table 5. Baghouse Dust Metal Analyses
Metal
Fe
Zn
Pb
Cu
Cr
No. of
Samples
3
3
3
3
3
Mean
(mg/kg)
372000
53700
9740
2510
1450
Standard
Deviation
(mg/kg)
5240
762
552
44
19
       This waste,  consisting of environmentally sensitive heavy metals in an inorganic
matrix, is suitable for treatment by solidification/stabilization technologies.  Foundry dusts are
classified in Canada under the Transportation of Dangerous Goods Act as Waste,Type 80.
In the United States the EPA specifies emission control dusts and sludges from the electric
furnace production of steel under Hazardous Waste No. K 061.

       The solidification/stabilization treatment chosen for this study utilized ASTM Type I
Normal Portland Cement  Cement treatment of wastes is widely practiced.

       During preliminary sample preparation studies it was noted that swelling and surface
cracking of the samples occurred during curing. Samples which remained intact during curing
demonstrated very low hydraulic conductivities (-  10"10 onusec"1).

       Diluting the  baghouse dust with 16-30 mesh silica sand allowed a range of cement
treatment levels to be tested without sample swelling and cracking. Furthermore, this addition
of silica sand allowed samples with a range of hydraulic conductivities to be tested.
                                       -24-

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BULK DENSITY MEASUREMENTS

       The samples prepared in this study had the consistency of soil-cement and thus a
standard compaction method for soil cements was used.  Bulk density measurements of these
samples are summarized in Table 6.

                           Table 6. Sample Bulk Densities
Matrix
n+
Bulk Density
(g.crn"3) Mean
Standard Deviation
Relative Standard
Deviation (%)
8%
16
2.398
0.024

1.00
9%
18
2.480
0.043

1.73
10%
16
2.527
0.009

0.363
+n is the number of samples                         •

       Results from Table 6 indicate that different nominal matrix content samples may have
similar bulk densities even when standard compaction procedures are used. Bulk density is
a function of gross sample porosity and has been implicated as  a source of variation in
hydraulic conductivity measurements. The degree of compaction has been found to affect the
measured permeability of clayey silt (25).  Stegemann and Cote (18) postulated that sample
differences were a major source of variation for hydraulic conductivity in their inter-laboratory
comparison study of solidified/stabilized wastes.  In this study, a concerted effort was made
to minimize  this source  of  variation  in  order  to  study  only the effects of instrument
parameters. Thus, a quality assurance criterion was instituted which rejected all samples with
bulk densities not within  0.5%. of the  sample mean.  This criterion ensured  that discrete
sample populations were obtained for each nominal matrix concentration.
                                       -25-

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TEMPORAL EFFECTS DURING EQUILIBRATION

       Steady state flow as indicated by equal inflow and outflow rates of permeant was
obtained on the first  or second day of testing.  This steady state flow was measured over
several weeks to study if the samples and permeants were in an equilibrium state.  Equilibrium
would be indicated by no significant change in hydraulic conductivity with time.  The results1
illustrated in Figure 5 show the temporal effects over 80 days of testing at constant gradient
and back pressure. All samples displayed a marked and rapid decrease with respect to lime.
(Note the different  scales.)   Hydraulic conductivity  decreased by  nearly two orders of
magnitude for the highest cement content sample.

       The decrease in hydraulic conductivity was modelled according to the equation:
                               K x 106 = A (T + 1)B
where T is the elapsed time measured from the first day of testing (T=0) and A and B are the
intercept (initial  condition) and  slope of the power  function, respectively.  The regression
results are summarized in Table 7, showing the statistical significance of the models.

    Table 7.  Model  Coefficients* for the Change hi Hydraulic Conductivity with Tune
     Matrix      Initial Value (A)   Standard Error     Slope (B)      Standard Error
8%
9%
10%
82.400
1.571
1.356
±4.361
±0.044
±0.148
-0.413
-0.743
-1.476
±0.025
±0.032
±0.070
'regressions are significant at p<0.001; the models explain 98% (minimum) of the variation
 in hydraulic conductivity.
            : Hydraulic conductivity results are summarized in Appendix C.  For the purpose
             of easy comparison, all hydraulic  conductivity measurements discussed in
             figures and surface response regressions have been multiplied by 1 x 106 unless
             specified otherwise.
                                       -26-

-------
                     100
                     0.2
                .§• _~
                6 -o

                1 *
                1 *
                     0.0
                                                           10%
                           10   20   30   40    SO    60    70

                                  . H«pjcd Time (days)
FIGURE 5.  Variation of Hydraulic Conductivity With Time at 8%, 9% and 10% Cement
                                      -27-

-------
       The models  are highly significant and explain a large portion of the variation in
hydraulic conductivity with time. Temporal effects could be a source of variance within and
between laboratories if not accounted for.

       The results of hydraulic conductivity suggest that permeants and samples are not in
physical/chemical equilibrium, but that some change in physical parameters is occuring.

       The models also predict that with time hydraulic conductivity approaches "zero", but,
in fact, this will never be achieved. However, if no future dissolution occurred, hydraulic
conductivity for the  system studied would have a decreased impact on environmental loading.
Leaching from sample surfaces and gross defects (cracks) would have the largest impact on
waste transport, rather than transport from within the interior by permeant flow.

       The hydraulic conductivity results show large differences for the initial conditions
between the 8%  and 9% matrices (8.24 x 10~5 crn-sec"1 vs 1.57 x  10~6 cnxsec"1 respectively).
The initial .conductivity for the 10% matrix (1.36 x 10"6 cm.sec"1) is not significantly different
from the 9% matrix. The differences in initial hydraulic conductivity may be due to different
mechanisms.  The connected porosity of the 8% matrix may be greater than those of the 9%
and 10% matrices such that  it behaves as a granular material. The 9% and. 10% matrices
behave as pastes because of their higher cement and water contents.

       The change in hydraulic conductivity with respect to time, (the "B" coefficient in Table
7) shows that hydraulic conductivity decreases more rapidly as the cement content increases.
This suggests that the aqueous permeant-matrix interactions may be some form of cement
hydration reaction which is promoted by passing aqueous permeant through the sample.

       The phenomenon of reduced hydraulic conductivity with time has been observed with
hardened cement pastes. Powers et al. (13) noted that the hydraulic conductivity of cement
pastes  cured underwater was  reduced by six orders  of magnitude due to increased hydration.
Powers et al. (14) described the mechanism of this phenomenon.  The volume of hydrated
                                       -28-

-------
paste is 2.1 times greater than unhydrated paste and hydration products fill pores and cavities,
causing discontinuities, effectively reducing the number of flow channels.  The number and
radii of conducting capillary pores appear to define hydraulic conductivity in cement pastes.
Nyame and Illston (16) compared their hydraulic  conductivity data to that predicted by
hydraulic radius theory and suggested a correlation.  Hughes (17) considered the effects of
pore characteristics (isotropy and tortuosity) in developing a model for cement-paste hydraulic
conductivity, which considered conducting channels  as Poiseuille tubes.

       Visual inspections of tested  samples revealed inclusions of  white material in the
normally  dark solidified/stabilized samples.  Examination  of  the 8% matrix by scanning
electron microscopy (SEM) revealed profuse fibrous growth (see Figure 6).  Examination of
this  material  at  enhanced magnification  revealed  a material morphologically  similar to
ettringite (3CaO.Al2O3.CaSO4.31H2O) (see Figure 7) rather than one of the major hydration
products of normal portland  cement,  such as calcium silica hydrate (CSH) or calcium.
hydroxide (CH).

       The morphology of the observed fibres was similar to that of the Aft fibres described
by Dalgliesh and Pratt (26). Analysis of individual fibres by SEM with an energy dispersive
x-ray spectrometer, revealed the presence of Ca, Al, S and traces of Fe (see  Figure 8).  This
result als.o suggests the presence of minor cement phases similar to ettringite, specifically the
aluminoferrite monosulphate (Afm) and aluminoferrite trisulphate (Aft) phases.

       Individual fibres were  subsequently analyzed by  a scanning  transmission electron
microscope coupled with an X-ray analyzer.  Ca:S ratios were determined to be 2.62 ± 6.52.
The trisulphate form and monosulphate form of the aluminoferrites have Ca:S ratios of 2.1 and
4.1 respectively. Thus, the phase found in this solidified/stabilized waste matrix is composed
largely of the Aft phase.
                                       -29-

-------
FIGURE 6. Fibrous Growth in Tested 8% Matrix (1000X)
FIGURE 7. Fibrous Growth in Tested 8% Matrix
           Showing Morphological Similarities to Ettringite (6000X)
                                     -'30-

-------
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       The ettringite phase was found in all matrices.  Figures 9 and 10 show the presence
of ettringite in the 9% matrix which formed larger structures and in some cases blocked off
pores.  Patel  et al. (15) noted a similar phenomenon that large pore fractions decreased while
gel (paste) porosity increased during cement paste hydration. Figures 11  and 12 show the
presence of ettringite in the 10% matrix.  No evidence of ettringite was found in companion
samples of 8%, 9% and 10% matrices which were cured over a similar time period in a .
humidity chamber at 95% minimum Relative Humidity, as shown by Figures  13a to 13c.
      Control samples containing only 23% Normal Portland Cement, 68% sand and 9%
were cured under water or in an environmental chamber for 28 days. Ettringite was found in
the cement samples cured under water (Figure 14) but not in the samples cured in the
                                      -31-

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FIGURE 9.  Ettringite Growth in Pores of the 9% Matrix'Sample (1000X)
FIGURE 10.  Ettringite Growth Blocking Pores in the 9% Matrix Sample (X1000)
                                    -32-

-------
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-------
FIGURE 11. Ettringite Growth in the 10% Matrix Pores (X200)

FIGURE 12. Ettringite Growth in the 10% Matrix Pores (X1000)
                                    -34-

-------
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-------
FIGURE 14. Cement Control Sample Cured Under Water
FIGURE 15. Cement Control Sample Cured in the Humidity Chamber
                                  -36-

-------
MODEL TESTING AND TEST PRECISION
                     .-  _       -   JL'       .4  *
       The results from testing three 8% matrix samples on three hydraulic conductivity
apparatus termed #925, #929 and #930, against the model derived previously for the 8%
matrix are shown in Figure  16.  The y axis represents the difference between observed and
predicted hydraulic conductivity.  Thus "zero" on this axis would represent perfect agreement
between  predicted and observed values.  Machine #925  demonstrated a nearly constant
difference (-6 x 10~6).  This machine was used to generate the original 8% matrix model and
so represents variance between sample preparations.   The deviations from the model of
machines 928  and 930 reflect variances due to between sample preparation and between
machine. Results from Machines 928 and 930 tend to converge to the predicted model values
with time. Thus, the temporal changes observed in this' solidified waste cause differences in
observed hydraulic conductivity between the same matrix samples  to become smaller with
time.

       Figure 17 illustrates the experimental results of hydraulic conductivity for the replicate
8% samples (Raw Data is  shown  in Appendix C).  The graph shows that the range of
observed values decreases with time. Table 8 summarizes the means and standard deviations
of the log transformed data.  A log transformation has been applied by Bryant and Bodocsi
(11) for clay and soil-liners  and Stegemann and Cote (18) for solidified/stabilized
wastes.   Bryant and  Bodocsi (11) demonstrated that  the log of hydraulic conductivity
measurements should stabilize variance,  are more meaningful because of the large ranges of
data, cause sources of variance  to become additive rather than multiplicative and simplify
relationships between hydraulic  conductivity and related quantities such  as void ratios.
Appendix C shows that dfter a log transformation of the raw hydraulic conductivity data the
null hypothesis of a normal  distribution  cannot be rejected at <0.10.

       Precision is defined in Table 8 as the 95% confidence limits for the estimate of the
mean with three samples.  This allows direct comparison of precision estimates for hydraulic
conductivity measurements with those obtained by Stegemann and Cote (18) who report a
                                       -37-

-------
         Table 8. Descriptive Statistics of Logi0 K for the 8% Matrix Replicates
      Test Day           Mean log K       Standard Deviation        Precision*
r
8
15
22
29
-3.924
-4.308
-4.475
-4.613
-4.782
0.184
0.248
0.233
0.256
0.244
x/-r 3.80
x/4- 4.40
x/+ 4.25
x/-r 4.48
x/+ 4.36
* 95% confidence limit of mean K for. 3 samples

precision of x/-r 7.3 among four replicates. In this study a precision of x/-f 4.36 (median
estimate) was obtained with only three samples.  The estimate in this study contains both
machine and sample variance.  Recall that a strict quality control criterion was instituted for
sample preparation and this is reflected by the small deviation from the model predictions for
machine # 925. The hydraulic  conductivity measurements were obtained at median levels of
gradient and back pressure.  It will be shown later that hydraulic conductivity is least sensitive
to gradient and back pressure at these levels.
SOLUBILITY EFFECTS DURING TESTING

       During hydraulic conductivity  testing  solidified/stabilized  wastes are subject to
dissolution by permeants. In the absence of waste/permeant hydration products, as discussed
previously, the processes of leaching will enlarge conducting pores, which theoretically should
increase sample permeability and measured hydraulic conductivity.  The extent of leaching
was studied as the surrogate waste chosen did not display this behaviour.

       Total dissolved solids (TDS) analysis of effluent from hydraulic conductivity samples
were routinely performed for each matrix.  Results are illustrated in Figure 18.
                                       -38-

-------
         so
         70
         6O
         GO
   ••s
   8  2  20
   t p!  C
   O ^  10
   'i
   •>     o
   «•   -
                                       --B-	
        '«	0	
1
o
                                        I
                                       1O
                                       Test Day
FIGURE 16.  Deviation from the Predicted 8% Model
                                             I
                                            20
                                          T
                                         ao
                     I.80&04-
        I1
        I
        HM
                     1.60&04-
                    1.4000&04-
1.0000&04-

8.0000&05-

6.00(X)E-05-

4.0000&05-

2.0000&OS-

O.OOOOE+00
Machine #
0925
CI928
x930
                                     10
                                                20
                                                           30
FIGURE 17. Hydraulic Conductivity Replicates for 8% Matrix at Median Levels of i and P
                                         -39-

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       I
       1
             24-
             20-
             16-
             12-
8-
              4-
                                       0 8% Matrix
                                       D9% Matrix
                                       x 10% Matrix
                       200.
                                400
                                         600
                                                  800
                                                          1000
                                                                   1200
                              Cumulative Volume (mL)

FIGURE 18.  Leaching of Hydraulic Conductivity Samples During Testing

A measurable portion of the sample was leached during testing. More than 20 grams of solids
were leached from each sample which corresponds to slightly more than 1% of the sample
weight.  The leaching rate appears to be proportional to the matrix which implicates cement
and water content as the controlling parameters for leaching.

      Chemical analysis of a composite permeant sample from a 9% matrix scoping sample
is shown in Table 9.  Analyses show that the permeant is highly basic, and that the freely
soluble sulphate, chloride and hydroxide salts of Na and K  are the largest components of
dissolved solids. Calcium is relatively insoluble at high pH which explains its low value. Zn
and Cr analyses are included to demonstrate that amphoteric metals can be quite soluble at
high pH.
                                       -40-

-------
               Table 9. Composite Permeant Analyses of the 9% Matrix
Analyte
pH
Na
K
OH-
Cl-
S042-
Ca
Zn
Cr
Concentration (mg/L)*
14 (standard units)
20800
17000
12300
10100
14900
59.2
69.3
44.0
* Unless specified

       Figure 19 shows the relationship  between the log of hydraulic conductivity and
cumulative total dissolved  solids.   The  graph,  demonstrates  that hydraulic conductivity
continues to decline even under conditions which leach alkali which has been attributed to
ettringite formation.

       A comprehensive explanation for the behaviour of the solidified/stabilized waste is now
possible.  In low  porosity  products, produced by low water-contents  and no aggregate,
ettringite can cause swelling cracks. In the surrogate waste matrix chosen for this study, the
added  sand  increases sample porosity to  such an extent that ettringite can form without
forming swelling cracks.  During hydraulic conductivity testing, soluble alkali, including
sulphates, dissolve and attack the tricalcium aluminate phases forming ettringite. This material
swells  and fills  sample pores causing reduced hydraulic conductivity as shown in this study.

       The beneficial formation of ettringite may be more specific to this waste matrix than
general in application.  Waste treatment engineers normally try to minimize sample porosity
                                        -41-

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               •3.0-r

               -35-

               -4.0-

               -45-

               -5.0-

               -55-

               -6.0-

               -65-

               -7.0-

               -75-

               -8.0-
                            5         10        15
                                Cumulative IDS (g)
20
          25
          FIGURE 19.  Log K vs Cumulative IDS at Median Levels of i and P

and water content.  Swelling hydration products, such as ettringite, would cause cracking,
resulting in an increase in surface area and hydraulic conductivity.
RESPONSE SURFACE REGRESSION ANALYSES

Effect of Matrix

      Hydraulic conductivity data were collected for the 8%, 9% and 10% matrix over 80
days of testing at the  various trial  levels of gradient and back pressure  outlined  in the
experimental design.  The overall mean  hydraulic conductivity was significantly greater
(p<0.01) for the 8% matrix (10 ± 5 x W6 cm.sec'1) compared to the 9% matrix (0.06 ±0.03
                                       -42-

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x  10~6 cm-sec"1).   For the waste  system and  measurement method chosen, hydraulic
conductivity could differentiate between the 8% and 9% matrix treatments even when the
confounding factors of time and instrument measurement parameters are retained.

       The overall mean of the 10% matrix was not significantly different than the 9% matrix.
As discussed previously, the 9% and 10% matrices behave as pastes in sample preparation;
but the 8% matrix behaves as a soil-cement (granular solid).

       The matrix-permeant interactions caused a decrease.in hydraulic  conductivity with
time.  If the differences between matrices are analyzed with non-parametric statistics (sign
test)  or treated as dependant samples paired according to date and instrument conditions,
differences between all matrices would likely become significant.

       Hydraulic conductivity  has been shown to be very sensitive to matrix for the waste
treatment system chosen, if temporal and machine conditions are considered.
                                       -43-

-------
Effect of Instrument Parameters

       After equilibrium had been reached as indicated by the criteria outlined previously, the
variation in hydraulic conductivity with gradient and back pressure was modelled by a second
order polynomial:

                  K x 106 = b0 + b^j + b2x2 + bnx2! + b^i22 + b^x^

where xt and x2 are the coded (-1 to +1) design coefficients of gradient and back pressure,
respectively.

       Regressions were performed for the 8% and 9%  matrices.  The  10% matrix reached
such a low value of K that single measurements often required more than 1 week of testing.
Eight and nine percent matrices could  be tested concurrently over much  shorter periods.
Because our goal was to compare matrices under similar test conditions,  the 10% matrix tests
were not deemed to be comparable and thus were not included.

       The  results of the response surface regression analyses are  summarized in Table 10
using coded levels of the test parameters.

       For  the 8% matrix,  only  gradient has a  significant effect on  measured hydraulic
conductivity.  Both linear (bt positive) and quadratic (bu negative) terms of gradient are
significant.  Back pressure at the levels chosen in this experiment did not have a significant
effect on measured hydraulic  conductivity.  Figure 20 shows  the  values of hydraulic
conductivity predicted by the response surface regression as a function of gradient and back
pressure using decoded (actual)  levels.  Hydraulic conductivity is maximized  at the median
levels of gradient (154) then declines due to the quadratic effect and is minimized at the low
levels of gradient.  Figure 21 displays a contour plot of hydraulic conductivity from the same
model. In addition to predicting maximum values for measured hydraulic conductivity at the
median levels of gradient (and back pressure), the hydraulic conductivity intervals (conditions
                                        -44-

-------
yielding equal values of K) show that the sensitivity of K to gradient and back pressure is
minimized at median levels.

       For the 9% matrix, Table 10 shows that only linear terms of gradient (positive) and
back pressure (positive) are significant.  The effect of gradient is estimated to be double that
of back pressure.  Figure 22 displays the values of hydraulic conductivity predicted by the
response surface regression for the 9% matrix. Maximum hydraulic conductivity is predicted
to be at the highest levels of gradient and back pressure which is different from that observed
with the 8% matrix.

       Figure 23 is the 2 dimensional contour plot of the response surface regression for the
9% matrix.  The K intervals suggest that K is least sensitive to gradient at high  levels.  This
observation must be with reservation, because although the quadratic term of gradient appears
as large as the effect of back pressure, it is statistically less significant.
                                        -45-

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        7.55 •
        4.67
           227
                         154
                            GRADIENT
                                      81
                                                                     124
FIGURE 20. Response Surface Plot for the 8% Matrix Showing the Predicted Maxima
        227
                          42
       69

BACK PRESSURE
     (kPa)
97
                                                                         124
FIGURE 21. Contour Plot of Predicted Values for the 8% Matrix Showing
            Hydraulic Conductivity is Maximized -at Median Levels of i and P
                                     -47-

-------
   0.042
                                                                          124
   0.022
        227
                       154
                            GRADIENT
                                       81
FIGURE 22.  Response Surface Plot of Predicted Values for the 9% Matrix Showing the

             Linear Relationship of Gradient and Back Pressure
     t-
     z
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     DC

     CD
        227
        172
        117
           14
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       69


BACK PRESSURE

     (kPa)
124
FIGURE 23.  Contour Plot of Predicted Values for the 8% Matrix
                                      -48-

-------
       The variation in hydraulic conductivity was less than four-fold for the 9% matrix and
less than three-fold for the 8% matrix as a result of increasing gradient and back pressure from
low-levels close to field conditions to the high levels used in accelerated testing.  Therefore
laboratory measurements conducted to accelerate testing are a reasonable approximation of
field conditions. The gradient was varied by a factor of twenty-five while the back pressure
was varied by a factor of eight. This relative insensitivity to pressure terms suggests that the
samples are highly liquid saturated.

       Hydraulic conductivity measurement appears to be most sensitive to gradient at low
levels.   This has implications  for falling-head permeameters  which measure hydraulic
conductivity at very low gradients where hydraulic conductivity is most sensitive. Regulatory
tests could minimize variance  by specifying relatively high levels of gradient (i = 150, 220
kPa across a 15 cm sample).

       The models developed for hydraulic conductivity based on the parameters of gradient
and back pressure  describe 58% - 68% of .the variance in experimental results.  A portion of
the variance  not explained is  likely due to the temporal effects noted previously.  Linear
regression was used to identify equilibrium, when temporal changes in hydraulic conductivity
at constant gradient and back pressure (median levels) were not different than zero.

       Equilibria were reached by 59,  34 and 27 days for 8, 9 and 10 percent matrices
respectively; the null hypothesis, that the estimated slope equalled zero, could not be rejected
for any of the three matrices with a probability of Type I error less than 0.13.

       This suggests that considering only Type I error may be inappropriate for determining
termination criteria for hydraulic conductivity tests.   Type II error should be considered in
determining hydraulic conductivity equilibria by considering the power of the  test.  Proper
sample size must be determined for an experiment to have sufficient power to detect a given
effect size from the null condition with a fixed Type I error rate.
                                        -49-

-------
EFFECT OF SAMPLE POROSITY
       Sample porosities and the equilibrium value of K (mean of trial 5 data after attaining
"equilibrium") are shown in Table 11.                                        '

                             Table 11. Sample Porosity
                                                            Hydraulic Conductivity
     Matrix            Porosity*       Pore Volume (cm3)          (cm.sec"1)
8%
9%
10%
0.321
0.301
0.272
236
223
201
(1.36 ± 0.14) x lO'5'
(6.62 ± 1.44) x 10'8
(3.95 ± 0.48) x 10'9
"*  determined after hydraulic conductivity testing

       The samples tested demonstrate a negative correlation between matrix and porosity.
Higher cement content is associated with lower sample porosity.  Lower sample porosity is
also associated with lower hydraulic conductivity.

       The relationship of porosity (E) and hydraulic conductivity from Table C.I (all trial
5 data after attaining "equilibrium" rather than the means) may be modelled according to:
                                     K = c 10bE
where c is a constant and b is the slope of the regression.  The coefficients are c = 2.834 x
10'29, and b = 72.495 (r2 = 0.891) (p<0.0001).

       Porosity appears to  have some merit as a predictor of  hydraulic conductivity.
However, bulk porosity does not define pore parameters such as  hydraulic radii or whether
pores are discrete or capillary.
                                       -50-

-------
       Cement researchers have studied the relationship of porosity to hydraulic conductivity.
 Nyame and Hlston  (16)  showed a  relationship between hydraulic conductivity  and pore
 structure in cement pastes using hydraulic radius theory. Hydraulic conductivity is related to:
 r\f(E) where rh is the hydraulic radius. This relationship suggests that porosity is not a unique
 function of hydraulic  conductivity.  Hughes (17)  developed the Poiseuille formula which
 shows the importance of pore size distribution rather than total porosity.  The flow rate across
 a unit cross section is  given by:
                                        32 N2 ji h
 where F is the flow rate (nr'.sec"1), r is pore radius (m), Ap is the pressure difference (N.rrf2),
 N is the tortuosity factor, u is the viscosity (N.sec.m"2) and h is the specimen thickness (m).
 This  model was successful in predicting hydraulic conductivity within half an order of
 magnitude when simplifying assumptions on pore connectivity were made.  The dependence
 of flow on r2 shows that large pores account for a disproportionate amount of flow.  Hydration
 reactions serve to connect particles as .shown above and as suggested by Nyame and Hlston
 (16) subdivide the interstitial space resulting in smaller flow channels.  This reduction in flow
 channel radii may not result in a detectable change in bulk porosity.

       In conclusion, porosity has some value as a predictor of hydraulic conductivity within
 a specific waste/treatment  as  shown in Table 1 1.  Within a waste/treatment  type sample
 preparation such as additives, compaction and water content etc. may be controlled and the
 hydraulic conductivity/porosity relationship defined.  For between treatment comparisons,
 independent pore parameters would be required to predict hydraulic conductivity.
SATURATION CONSIDERATIONS

       Sample saturation was determined by the ratio of pore water (or free water) to pore
volume.  Free water was determined as the sample weight loss at 60°C.
                                       -51-

-------
       Moisture content is a destructive test and thus could only be conducted on test samples
after hydraulic conductivity testing.  Companion samples prepared under standard conditions
were tested to estimate the degree of saturation before subjecting the test samples to standard
vacuum saturation.  Results from these companion samples and test samples after hydraulic
conductivity testing are shown hi Table 12.
                             Table 12. Sample Saturation
                                H2O
Matrix (%)
8+
9+
10+
8*
9'
10*
4.92
5.66
- 6.14
12.94
11.71
10.55
(cm3)
79.5
94.2
. ' 105.4
226.5
206.4
189.6
rore voiumc
(cm3)
227.3
223.3
204.4
235.5
222.6
201.4
OM.LUJ.a.UUU
35.0
42.2
51.6
96.2
92.7
94.1
       t Companion samples after curing
       * Samples after hydraulic conductivity testing

       Results show that samples are highly liquid saturated, which may explain the relative
insensitivity  of hydraulic  conductivity  to  the  instrument pressure  parameters  discussed
previously.

       In the field, solidified stabilized wastes will be in the unsaturated state.  Flow in
solidified/stabilized wastes in the unsaturated state will be different from that measured for
saturated wastes in the laboratory.  The nature of this unsaturated flow was beyond the scope
of this study and should be considered as an area for further research.
                                        -52-

-------
COMPARISON OF SOLIDIFIED/STABILIZED WASTE TO SOIL/CLAY LINERS

       Results of the regression analysis showed that the  hydraulic conductivity of the
solidified/stabilized waste studied responded in a positive linear fashion for both 8% and 9%
matrices.  A negative quadratic term was significant for the 8% matrix.

       Clay and soil-liner researchers suggested that high gradients could lead.to sample
consolidation and thus lower measured hydraulic conductivity.  Bryant and Bodocsi (11) noted
that the experimental results of various researchers displayed a negative relationship between
hydraulic conductivity and gradient.                                        -

       The applied gradients for clay and soil liners reported were as high as 300. This would
correspond to approximately a 450 kPa pressure drop across a 15 cm sample.  A compacted
wet clay which had an unconfined compressive strength of 100 kPa would thus be subjected
to pressures which would tend to consolidate, these samples.
                      \
       This was not the case with the solidified/stabilized waste studied.  The samples studied
were molded as monolithic solids with dimensions of 7.62 cm diameter and 15.2 cm height.
Companion samples were sacrificed in unconfined compressive strength tests  after curing a
minimum of forty-one days. Results are summarized in Table 13.

               Table 13. Unconfined Compressive Strength Tests (kPA)
Trial
' 1
2
3
Mean
Standard Deviation
8 %
3380
3080
3830
3430
380
Matrix
9 %
3900
3000
-
3450
640
10%
5320
6340
6460
6040
630
                                      -53-

-------
       The sample matrices studied displayed an unconfined compressive strength at least ten
times greater than the highest pressure drop tested (340 kPa). This may explain the different
behaviour noted for solidified/stabilized  wastes.   The  positive correlation of hydraulic
conductivity'with gradient for solidified/stabilized wastes may represent a response in liquid
parameters rather than a response to pore parameters, as is likely the case for clay and soil
liners.
                                         -54-

-------
                                  REFERENCES
1.     Ather, G., Evans, J.C., Fang, H.-Y., and Witmer, K. Influence of Inorganic Permeants
       upon the Permeability of Bentonite. In:  Hydraulic Barriers in Soil and Rock. ASTM
       STP 874. American Society for Testing and Materials, Philadelphia, 1985. pp 64-73

2.     Acar, Y.B., Olivieri, L, and Field, S.D.  The Effects of Organic Fluids on Compacted
       Kaolinite.  In:  Hydraulic Barriers in Soil and Rock. ASTM STP 874. American
       Society for Testing and Materials, Philadelphia, 1985. pp 203-212.

3.     Fang,  H.-Y. and Evans, J.C.  Long-Term Permeability Tests Using Leachate on a
       Compacted Clayey Liner Material.  In: Ground-Water Contamination: Field Methods,.
       ASTM STP963., American Society for Testing and Materials, Philadelphia, 1988. pp
       397-404.

4.     Elzeftawy, A. and Cartwright, K. Evaluating the Saturated and Unsaturated Hydraulic
       Conductivity of Soils.  In: Permeability and Groundwater Contaminant Transport.
       ASTM STP 746. American Society for Testing and Materials, 1981.  pp 168-181.

5.     Parker, D.G., Thornton, S.I., and Cheng, C.W.  Permeability of Fly-Ash Stabilized
       Soils.  Paper presented at 1977 Specialty Conference of the Geotechnical Engineering
       Division.  American Society of .Civil Engineers. Ann Arbour, Michigan. June 13-15,
       1977.

6.     Carpenter,  G.W. and Stephenson,  R.W.   Permeability Testing in  the Triaxial Cell.
       Geotechnical Testing Journal.  9:1, March 1986. pp 3-9
                                      -55-

-------
7.     Edil, T.B.  and  Erickson, A.E.   Procedure  and Equipment Factors Affecting
       Permeability Testing of a Bentonite-Sand Liner Material.  In:  Hydraulic Barriers in
       Soil and Rock.   ASTM STP  874.   American Society for Testing and Materials,
       Philadelphia, 1985.  pp 155-170.

8.     Lentz, R.W., Horst, W.D., and Uppot, J.O. The Permeability of Clay to Acidic and
       Caustic Permeants.   In:  Hydraulic Barriers  in Soil and Rock.  ASTM STP 874.
       American Society for Testing and Materials, Philadelphia, 1985. pp 127-139.

9.     Bowders, JJ. Termination Criteria for Clay Permeability Testing Discussion.  Journal
       of Geotechnical Engineering.  114:8,1988. pp 947-950.

10.    Pierce,  JJ.  and Witter, K.A.  Termination Criteria for Clay  Permeability  Testing.
       Journal of Geotechnical Engineering.  112:1,1986. pp 841-854.

11.    Bryant, J. and Bodocsi, A.  Precision  and Reliability of Laboratory Permeability
       Measurements.  EPA Contract No. 68-03-3210-03 U.S.  Environmental Protection
       Agency, Cincinnati Ohio, 1985. 177 pp.

12.    Pierce,  J.J., Salfors,  G. and  Peterson, E.   Parameter  Sensitivity  of Hydraulic
       Conductivity Testing Procedure. Geotechnical Testing Journal.  10:4, December 1987.
       pp 223-228.

13.    Powers, T.C., Copeland, L.E., Hayes,  J.C. and Mann, H.M. Permeability of Portland
       Cement Paste. Journal of the American Concrete Institute.  26:3, November 1954. pp
       285-298.

14.    Powers, T.C., Copeland, L.E. and Mann, H.M. Capillary Continuity or Discontinuity
       in Cement  Pastes.   Journal of the Portland  Cement Association Research  and
       Development Laboratories.  1:2, May, 1959.  pp 38-48.
                                      -56-

-------
 15.   Patel, R.G., Killoh, D.C., Parrott, LJ. and Gutteridge, W.A. Influence of Curing and
       Different Relative Humidities upon Compound Reactions and Porosity in Portland
       Cement Paste. Materials and Structures.  21:123, 1988. pp 192-197.

 16.   Nyame, B.K. and fllston, J.M. Relationships Between Permeability and Pore Structure
       of Hardened Cement Paste.  Magazine of Concrete Research. 33:116,1981.  pp 139-
       146.

 17.   Hughes, D.C. Pore Structure and Permeability of Hardened Cement Paste. Magazine
       of Concrete Research. 37:133, 1985.  pp 227-233.

 18.   Stegemann, J.A. and Cote, P.L, Summary of an Investigation of Test Methods for
       Solidified Waste Evaluation. Waste Management, 10:1990. pp 41-52.

 19.   ASTM D-558-82.  Standard Test  Methods for Moisture-Density Relations of Soil
       Cement Mixtures. American Society for Testing and Materials.  Philadelphia, 1988.
       V 04.08, pp 108-111.

. 20.   ASTM D2216-80.  Standard Test Method for Laboratory Determination of Water
       Content of  Soil, Rock and Soil Aggregate Mixtures American Society for Testing and
    ,   Materials.  Philadelphia,  1988.  V 04.08.  pp 262-264.

 21.   ASTM C604-86.  Standard Test Method for True Specific Gravity of Refractory
       Materials by Gas Comparison Pycnometer.   American  Society for  Testing and
       Materials.  Philadelphia,  1988.  V 15.01.  pp 159-161.

 22.   ASTM D1633-84. Standard Test Method for Compressive Strength of Molded Soil-
       Cement Cylinders. American Society for Testing and Materials.  Philadelphia, 1988.
       V 04.08. pp 229-231.
                                       -57-

-------
23.   AWWA #209A. Total Residue Dried at 103 - 105°C In:  Standard Methods for the
      Examination of Water and Wastewater.  15th Ed. American Water Works Association.
      Washington D'.C.,. 1981. pp 93-94.

24.   SAS Institute Inc.  SAS/STAT User's Guide.  Release 6.03 Edition., Gary, NC:SAS
      Institute Inc., 1988.  1028 pp.

25.   Garcia-Bengochea,  I. and Lovel, C.W.  Correlative Measurements  of Pore Site
      Distribution and Permeability in Soils. In: Permeability and Ground Water Transport.
      ASTM STP 746. American Society for Testing and Materials. Philadelphia, 1981.
      pp 137-150.

26.   Dalgleish, BJ. and Pratt, P.L. Fractographic Studies of Microstructural Development
      in Hydrated Portland Cement.  Journal of Materials Science.  17:8, 1982.  pp 2199-
      2207.
                                      -58-

-------
                                   APPENDIX A
CALIBRATION OF GEOTEST PERMEAMETER INTERFACES

       Calibration of the Geotest interface was conducted by measuring the mass of water
expelled from the interface as a function of interface piston displacement Linear regression
was used to determine the linear displacement/mass  response  of the interface,  used in
subsequent hydraulic conductivity determinations.

       Equipment required included a: Geotest Interface (Model S5425), Mitutoyo Digimatic
Indicator (Type ID-130ME), Mitutoyo miniprocessor (DP2-DX),  Mettler analytical balance
(HK 160) with RS232 Adapter (Mettler CL249) and computer (Fujikama Model #fk286MT).
The equipment layout is shown in Figure A.I.

       Open containers of water with paper towel wicks were placed in the balance weighing
chamber twenty minutes before commencing the calibration to saturate the local environment
and minimize evaporation loss.  Twenty data points were collected at each of 6, 12, 18 and
24 mm interface piston displacements.  Eighty data points were generated by  discharging ~
0.012 g of water into a 50 ml volumetric flask with a corresponding piston displacement of
~ 0.006 mm.

       Data collected were merged into a single file by matching time readings from the Data
Logger and Balance files.  Data in an ASCII format was imported into SAS (1988  Release
6.03) for statistical analysis.  A least squares estimate for a linear model of interface piston
displacement versus  mass of water was produced.

       Calibrations  were performed three times  over  a  fifteen  month period; an initial
calibration, prior to,  and at the end of hydraulic conductivity experiments. The results of the
three calibrations for the six interfaces are shown in Table A.I.
                                       -59-

-------
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                                           UJ
                                           a.
                                           a
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 ODD
 ODD
 ODD
 ODD
              UJ
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-------
       The  points  fit the linear  model  sufficiently  well  to generate a  coefficient  of
determination of 1.0000.  The standard error in the slope was less than 0.011% in all cases.
The deviation from the linear model was determined for each interface calibration.  The
maximum residual deviation was +0.0079 mm and -0.0077 mm. The predicted residual from
the sum of squares was a maximum of 0.0033 mm, which represents the machine error.
                           Table A.I.  Interface Calibrations
         Interface #
Slope # (mm.g  )
Std. Error of Slope
761


925


926


928


929


930


1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
0.500373
0.500949
0.502044
0.502238
0.502361
0.501614
0.499960
0.500320
0.501395
0.501553
0.502538
0.503015
0.501781
0.501484
0.501940
0.502952
0.504165
0.502900
0.000032
0.000015
0.000026
0.000017
0.000055
0.000029
0.000051
0.000034
0.000011
0.000008
0.000027.
0.000014
0.000022
0.000020
0.000020
0.000032
0.000013
0.000035
                                       -61 -

-------
                                   APPENDIX B
IN-HOUSE COMPUTER PROGRAM

       The computer program accepted data from the Miniprocessor and stored it in a file on
the hard drive. The program included several options for calibration, hydraulic conductivity
calculation and file management The file name was coded to the Geotest interface serial #
and the date of data acquisition. An example is shown below:

                                   761_1D90.019

This file indicates the:  Mitutoyo Indicator serial number, file status (original or edited), file
number of day, file type (balance file, data file, merged balance and data calibration file, or
hydraulic conductivity calibration file), year and Julian day.

       A header on the data file recorded the experimental conditions- (trial #, gradient, back
pressure and matrix) and the sample/test series numbers.

       A test pressure file was coded with the sample/test series number and contains the test
values for the head, back and cell pressures.                                  ;

       The sample file was coded to the sample number and contained the sample dimensions,
weight, moisture content and sample preparation compositions.

       The hydraulic conductivity calculation incorporated data from the sample, pressure and
data  files. The hydraulic  conductivity could be calculated for the entire data file or at a
specified time interval between any two data points. The hydraulic conductivity calculation
is shown below:
                                       -62-

-------
K=                                    ''
                S • p (HP - BP) • PH • TC (OD • 2.54)2
   D  = Interface displacement (mm)
   S  = Slope of calibration curve from regression analysis (mm/g)
   p  = Water density at 24°C (0.9973 g/cm3)
   L  = Mean sample length (cm)
   HP = Head pressure (psi)
   BP = Back pressure (psi)
   PH = Pressure to head conversion (70.47 cm water/psi)
   OD = Mean outside diameter (in.)
   t = Time of displacement reading (sec.)
                                   -63-

-------
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                                         Table C.2. 8% Matrix Replicate Data
    Test Day     K930 (cm-sec'1)   K928 (cm-sec'1)    K925 (cm.sec'1)     LOG K930
LOG K928
                LOG K92S
1
5
8
12
15
19
22
25
26
27
28
29
Mean
Std.
Deviation
Normality
Test Value*
1.37E-04
1.02E-04
8.22E-05
6.63E-05
5.64E-05
4.75E-05
4.15E-05
3.68E-05
3.49E-05
3.24E-05
3.08E-05
2.96E-05
5.81 x 10'5
3.36 x 10"s .
2.03
1.67E-04
8.20E-05
5.46E-05 '
4.19E-05
3.45E-05
2.78E-05
2.38E-05
2.02E-05
1.92E-05
1.74E-05
1.66E-05
1.59E-05
4.34 x 10'5
4.36 x 10'5
9.02
7.40E-05
3.20E-05
2.66E-Q5
2.29E-05
1.93E-05
1.67E-05
1.47E-05
1.28E-05
1.19E-05
1.07E-05
9.96E-06
9.61E-06
- 2.18 x 10'5
1.79 x 10'5
6.40
-3.863
-3.991
-4.085
-4.178
-4.249
-4.323
-4.382
-4.434
-4.457
-4.489
-4.511
-4.529
-4.29
0.22
1.08
-3.777
-4.086
-4.263
-4.378
-4.462
-4.556
-4.623
-4.695
-4.717
•-4.759
-4.780
-4.799 .
• -4.49
0.32 .
1.30
-4.131
-4.495
-4.575
-4.640
-4.714
-4.777
-4.833
-4.893
-4.924
-4.971
-5.002
-5.017
-4.75
0.26
1.28
' Critical Values 1.36 (a = 0.10), 1.72 (a = 0.05)
                                                     -66-

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DC/ps
ET-CW
2440-CW
91.06.21
                                      -67-

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