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Table 22. Rating of test methods' operational characteristics.
Applicability to
Ability to Ease of Aggregate Type and
Estimated Readiness for
Test Method Interpret Use by Portability (c) Size(d)
Price ($) Implementation(a)
Data(b) Technician (b)
Coarse Fine
Uncompacted Void Content of Fine
250 1 1 1 1 N/A 1
Aggregates AASHTO T 304
Uncompacted Void Content of Coarse
500 1 1 1 1 1 N/A
Aggregates AASHTO T P56
Compacted Aggregate Resistance
500 1 1 1 1 N/A 1
(CAR)
Percentage of Fractured Particles in
0 1 1 1 1 (N/A) 1 N/A
Coarse Aggregate ASTM D 5821
Flat and Elongated Coarse Aggregates
250 1 1 1 1 1 N/A
ASTM D 4791
Multiple Ratio Shape Analysis 1,500 2 2 2 1 1 N/A
VDG-40 Videograder 40,000 - 50,000 2 3 2 2 1 1
Buffalo Wire Works PSSDA -Large 30,000 - 40,000 3 3 3 2 1 N/A
Buffalo Wire Works PSSDA -Small 30,000 - 40,000 2 3 2 2 N/A 1
Camsizer 40,000 - 50,000 2 3 2 2 2 1
WipShape 30,000 - 40,000 2 3 3 2 1 N/A
University of Illinois Aggregate Image
30,000 - 40,000 3 3 3 2 3 N/A
Analyzer (UIAIA)
Aggregate Imaging System (AIMS) 30,000 - 40,000 2 3 3 2 1 1
(a)
Notes: 1: Available commercially. Wide use in laboratories. 2: Available commercially. Limited use in laboratories. 3: Not available commercially. Limited use in
research laboratories. Can be made available commercially.
(b)
1: Very Easy, 2: Easy, 3: Intermediate, 4: Difficult.
(c)
1: Can be used in central and field laboratories. Requires less than 1 hr to move it. 2: Can be used in central and field laboratories. Requires less than 4 hrs to
move it. 3: Not portable. Cannot be used in central and field laboratories.
(d)
1: Measure all aggregate sizes and types, 2: Measure all aggregate types but not all sizes, 3: Measure all sizes but not very dark colored aggregates, N/A: Not
Applicable.
by the user based on a pairwise comparison judgment scale of column are divided by the sum of that column, and then
1 to 9 (also known as standard preference table). Then the user the elements in each resulting row are added and divided by
calculates priorities, using a simple mathematical procedure, the sum of the numbers in that row.
to arrive at overall priorities for the alternatives. The sum of The program uses a graphical interface environment; the
all the criteria beneath a given parent criterion in each level of process is summarized in the following steps (for illustration,
the model must equal one. Each priority list shows its relative fine aggregate angularity is used to describe the operation steps
importance within the overall structure. From the overall pri- of the new program): (1) The user enters the number of testing
ority list, the decision maker can choose among alternatives methods being compared and the characteristics determining
by selecting the highest priority alternative. The mathematical the performance of the test method (Figure 5a). (2) Generic
functions involved in AHP can be found in Saaty (21). text boxes are generated and the user inputs the names of
each of the characteristics and testing methods (Figure 5b).
(3) The user enters the weights assigned to test methods when
Program Description
pairwise comparison is conducted with respect to each char-
Computational software was developed to make the calcula- acteristic (Figure 6a). Note that because the lower triangle of
tion process easier and faster. The program provides the user these matrices is the reciprocal of the upper triangle with ones
flexibility in changing objectives or selection criteria weights along the diagonal, the user inputs the upper half of the matrix
before making the final selection from available alternatives. The and the other values are updated automatically. (4) The user
software was created using VC++ programming language that is prompted to enter the weights comparing the various char-
can be run on any computer irrespective of the operating system. acteristics with respect to overall satisfaction with a method
The program uses the crude estimate, specified by Saaty (21), in a new interface (Figure 6b). (5) The program calculates the
to calculate the priority vector through the process of averaging priority vectors for each of the matrices and displays them
over normalized columns technique. The elements of each in a new interface window (Figure 7a). (6) The program also
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(a) Number of Characteristics and Test Methods
(b) Names of Characteristics and Test Methods
Figure 5. Screens of interface to enter numbers and names of characteristics and test methods.
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(a) Weights Comparing Test Methods to Characteristics
(b) Weights Comparing Characteristics
Figure 6. Screens of interface to enter weights comparing test methods to
characteristics, and characteristics with respect to overall satisfaction with method.
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(a) Priority Vectors
(b) Overall Ranking
Figure 7. Screens of priority vectors and overall ranking of test methods.
