Aggregates Geometric Parameters

Transcription

1 Aggregates Geometric Parameters On-Line or Lab Measurement of Size and Shapes by 3D Image Analysis Terry Stauffer Application Note SL-AN-48 Revision A Provided By: Microtrac Particle Characterization Solutions

2 Summary: Aggregates are a broad size range of common minerals used to mix with cement to make concrete or with asphalt to make asphalt concrete, both used in many types of construction, foremost in highways and runways. They re also used as is to provide base roadbeds for such construction as railways. A number of different test standards have been written by organizations around the world for measuring size distribution and for measuring various shape properties of the material which affect such final use characteristics such as load- bearing strength, wear resistance and internal frictional strength. These tests have traditionally been run manually by operators on such physical measuring devices as sieves and hand- held sizing gauges (load- bearing strength), tumbling mills (wear) and containers for measuring voids (frictional strength). This paper introduces an automated method for making these size and shape measurements much faster and accurately using 3- dimensional image analysis, either in the QC lab or on line in an aggregates processing plant. The Aggregates Industry: Crushed stone aggregates used for construction of highways, runways and other heavy load- bearing surfaces are typically the products of a quarry operation. The normally 3- step process includes blasting, crushing and size classification by screening. Types of stone most used are granite, limestone, gravel and slag. Coarse aggregates range generally in sieve sizes from 90 mm down to 4.75 mm. Fine aggregates are natural sand, manufactured sand, or a combination of both. They are normally measured in sieve sizes from 9.5 mm to pan, but the smallest sieve is 75 microns. These fines are typically blended into coarse aggregates at proportions optimum for the specific end use. End users of these construction materials are generally regulatory agencies like departments of transportation, airport and railroad authorities. These groups issue specifications to their suppliers based very closely on the various standard tests that have been written for large regions globally. Standard QC Tests for Aggregates: All of the Test Parameters listed below involve very time consuming manual measurements, which often are run on sample sizes too small to be considered representative. This paper will introduce and describe in detail the use of an automated three- dimensional image analyzer, which can report all parameters in one quick measurement. And it s available in an on- line real- time configuration or as a bench- top QC instrument. 2

3 Flat/Elongated (D 4791): This ASTM Test requires Length, Width and Thickness dimensions of a representative sample of aggregate from each Sieve fraction in the specified Sieve size distribution. It s carried out manually using two different hand- held gauges to measure those operator judged dimensions, on a very small group of particles for each size fraction. This test identifies the proportion of particles judged to be thin, which weakens the load- bearing strength of the road surface matrix. A dynamic image analyzer with 3- D mode of operation can measure all necessary parameters on large samples in a small fraction of the time required manually. Fractured Particles (Angularity) (D 5921 & IS 2386): This test attempts to describe quantitatively the number of very flat large surfaces that exist at sharp angles from adjacent faces on aggregate particles, again, measured within each Sieve fraction. Both the British and Indian standards describe manual techniques, the first is an objective operator visual inspection of the particles and the second involves measurement of the void space in a bed of particles as measured by the volume of water used to fill them. These measurements are indicators of the internal frictional strength within the road surface. A dynamic image analyzer with 3- D mode of operation can measure an adjustable parameter, Angularity, which gives an objective quantitative correlation to frictional strength on a large sample in a small fraction of the time required for manual testing. 3

4 Flakiness Index (BS- EN- 933 & IS 2386): This test, manual sequential sieving, is used to quantitatively describe the proportion of thin aggregate particles within each Sieve fraction, which lower the load- bearing strength of the road surface matrix. In IS 2386, the measurement is made manually on a hand- held gauge and is based on operator judgment about exactly where the three major axes are. A dynamic image analyzer with 3- D mode of operation can measure Flakiness Index on a large sample in a small fraction of the time required for manual testing. Elongation (IS 2386): This index gives information about aggregate which is very similar to that given by Flat/Elongated and Flakiness Index parameters in that it indicates the relative proportion of particles with a small thickness which leads to weakening the load- bearing strength of the road surface. It s defined as % by weight of particles whose length is greater than 1.8 times their mean sieve size, for each sieve fraction. It is not applicable to sizes smaller than 6.3 mm. A dynamic image analyzer with 3- D mode of operation can measure Elongation on a large sample in a small fraction of the time required for manual testing. Sieve Sizes: All these test standards list sieve sizes for two separate classes of aggregates Coarse aggregate and Fine aggregate. Coarse aggregate consists of gravel, crushed gravel, crushed stone (granite, limestone, dolomite) blast furnace slag or a combinations of these. Fine Aggregate consists of natural sand, manufactured sand or a combination of the two. Setting Specifications on Suppliers: The aggregates industry is very much dependent on the demand for its products being dependent on the demand for highway, runway, railway bed, dam and some commercial building construction. In these applications aggregates are most generally mixed into a cement matrix or asphalt (bitumen) matrix, both blends referred to as concrete. These aggregate blends are specified by the customer, or buyer, and depend on the specific final use of the concrete. The final concrete mix can be a blend of various size fractions of both coarse and fine aggregate. And the vast majority of customers for these construction concretes are government agencies, at one level or another. Therefore, the specifications imposed by these highly regulated agencies generally follow published standard tests. A good example is all the US state Departments of Transportation (DOT s). So, in the US, the ASTM standards are closely followed. But these agencies are free to modify the required test reports as they wish, and lower agencies at regional and local levels can do the same. AASHTO (American Association of State Highway and Transportation Officials), composed of all 52 US state DOT s, also has an influence at a high level on specification considerations by regulated transportation agencies. But overall, regardless of the 4

5 exact specifications required, they will be able to be measured by a 3- D mode automated image analyzer on large samples very quickly. New Tests Under Consideration: The existing standard tests described above are all pretty old manual tests utilizing all types of equipment. They are subject to operator error, time consuming, and most often they measure small sample sizes, which are not large enough to be considered to be well representative of the bulk sample. However, technical groups within DOT s, AASHTO, Airport Authorities and Universities have been working together in various groups looking into new tests that could either add to the information needed or to replace to a degree some existing tests, which have some of the major shortcomings, mentioned. Some are discussed below. Measuring Surface Roughness as an Indicator of Wear Resistance: The wear on load bearing traffic surfaces is measured in the lab on aggregate particles by simulating how wear would affect the aggregate. A sample of aggregates from individual sieve fractions are abraded in a tumbling mill and the fines generated by abrasion of the particles rubbing over each other are collected by sieving the sample on a finer screen than its lower size, and then the fines collected are calculated by dividing the fines weight by the total weight of the sample. This number is an indicator of the wear resistance of the aggregate the larger the ratio, the lower the wear resistance. Automated image analysis calculates and reports a number of surface roughness parameters which could be quickly measured on the before and after abrasion surfaces to be an indicator of wear resistance, eliminating the need for manual fines collection and weighing. Surface Area: The 3D mode image analysis measures the surface area of all particles which would be an indicator of the bonding/binding strength of the aggregate with the mix matrix. Volume: Volume is measured in 3D image analysis as the product of length, width and thickness for each particle, which provides a true volume distribution, and it can be converted, if desired, to a mass distribution using a density correction. This would eliminate the bias of a sieve measurement basing its results on the middle, or width, dimension of a particle rather than on the volume. But if it s desirable to report size measurement using the sieve values, the 3D software calculates a Sieve parameter which directly overlays actual sieve data using an algorithm which includes some portion of the width parameter and the thickness parameter. 5

6 EXPERIMENTAL: 3- D Image Analysis: This is an automated particle characterization technique, which measures many different size, shape, intensity and other miscellaneous parameters, like the ones that have been discussed for aggregates in this document. The 3- D image analysis results reported in this section were all made on the PartAn 3D. This analyzer s 3- D mode of operation is patented by Microtrac and is the only 3- D mode of image analysis offered commercially today. It s also a part of the PartAn 3D Maxi, which is different only in that it covers a larger size range. Results of PartAn 3D Flat/Elongated Analysis per ASTM D X- Y Graph as Cumulative % Finer 1. actual sieve data 2. PartAn sieve data 3. PartAn Width 4. PartAn Thickness 5. L/T 1:3 Elongated Ratio as % of total 6. L/T 1:5 Elongated Ratio as % of total Tabular distribution data Columns 4 and 5 report Cum L/T Elongated ratio data for each size fraction Fig. 1. Following the numbers on the X- Y graph, 1 is a cumulative % finer plot of the actual sieve data size distribution; 2, the red curve, is the PartAn calculated sieve data; 3 is PartAn width; 4 is PartAn Thickness; 5 is the 1:3 Length to Thickness ratio and 6 is the 1:5 L/T ratio, both as a percentage of the total sample. Any ratio can be chosen and reported, L/W, W/T, & L/T On the Table to the right, number 1 is the tabular sieve distribution list and 2 points to the two aspect ratios in columns 4 and 5 which list the 1:3 and 1:5 L/T ratio % by size fraction. 6

7 Results of PartAn 3D Flakiness Index Measurement Standard FI Measurement Sieve Tables Stay column FI Measurement Results in PartAn 3D Mode Fig. 2.These are the results of the PartAn 3D analysis for Flakiness index. Pass column The table on the left lists columns of the screen designations and the size in mm of the square- holed screens used in the first screening operation and the third column lists the rod sieve sizes in mm. All results are given in the table to the Flakiness column right. is Square holed screen designations ratio of Pass value divided by Stay value are listed in the first column below a Stay value which indicates % by volume in those size fractions. The Pass column to the right is the list of % passing the rod screen from the stay screen. Total Flakiness Index for entire samplethe Flakiness column then lists the Flakiness Index for each fraction and for the total sample at the bottom. FI is the Pass value divided by the Stay value. 1 Angularity in PartAn 3D View Particles Display Image file of all particles reported, can be sorted (1) and searched in the Query window (2), and all 2D and 3D parameters for selected particle listed in table to right (3). 2 3 Fig. 3. Display of Angularity parameter sorted in descending order of the 3D value for Angularity. This is the PartAn 3D View Particles display, where the entire image file can be viewed, sorted by any parameter, number 1, searched to isolate different classes of particles,2, and display all 2D and 3D parameters for a selected particle in upper right table, 3. All D images are contained in this file, and all can be viewed by scrolling, exported by image or data and printed if desired. The images can be seen to have reasonably low surface roughness and low angularity, but good uni- dimensional shape for strong load- bearing strength. 7

8 PartAn 3D Surface Roughness Parameters Three roughness parameters Convexity, Solidity, Concavity Similar data for aggregate samples Any two parameters displayed with respect to each other Results presented in Scatter Diagram Display 3D Width Scatter Diagram Convexity (roughness) Summary Data Fig. 4. Surface Roughness. This is a slide showing a 3D surface roughness parameter, Convexity on the red Y graph, along with a 3D size parameter, Width, X graph. Any of PartAn s 36 parameters can be plotted relative to each other on this Scatter Diagram graph. The blue dots show where every particle is with respect to its x and y parameters. The roughness parameters available are Convexity, Solidity and Concavity For Aggregate samples these are all very similar in value and any can be used. Convexity is reported on the right side red distribution on a scale of 0 to 1-1 being a completely smooth convex surface. Summary data for each parameter are shown, in percentiles, means, relative standard deviations and number of particles on the list to the far right nearly 4 thousand particles were measured in this small sample, in less than 5 minutes, with complete data for all 36 parameters available immediately when the analysis ends. Fig. 5.This is a slide showing a 3D surface roughness parameter, along with a 3D size parameter, Width in this case. Any of PartAn s 36 parameters can be plotted relative to each other on this graph.the roughness parameters available are Convexity, Solidity and Concavity For Aggregate samples these are all very similar in value and any can be useda 3D size parameter, Width in this case, is shown in the top red volume distribution, which can be reported in Number, or Count, distribution form as well. Convexity is reported on the right side red distribution on a scale of 0 to 1-1 being a completely smooth convex surface. Summary data for each parameter are shown, in percentiles, means, relative standard deviations and number of particles on the list to the far right nearly 4 thousand particles were measured in this small sample, in less than 5 minutes, with complete data for all 36 parameters available immediately when the analysis ends. 8

9 PartAn 3D Surface Area Measurement 3D Surface Area, Y axis, displayed relative to 3D Thickness In Scatter Diagram 3D Thickness Surface Area Summary Data PartAn 3D PartAn 3D Maxi PRO On- Line Unit Mounted on Pipe PRO On Line Unit Un- mounted Range: 35 µ - 35 mm Lab Units Range: 0.28 mm 127 mm Fig. 6. Microtrac offers 4 different 3D automated image analyzers, all shown in this slide. At the bottom of the slide the two different ranges are given for the PartAn 3D series and the PartAn 3D Maxi series 35 um to 35 mm and 0.28 mm to 127 mm respectively. Both models come in on- line process versions and in lab versions. The upper left photo shows the PartAn 3D PRO, pro for 0n- line process version, and it s shown here mounted on a pipe, sampling and measuring the sample stream and returning it to the process. At lower left is the lab version. 9

10 The upper right photo shows the PartAn 3D Maxi PRO, un- mounted on a process stream, and below it the lab version. The on- line PRO versions provide continuous unmanned operation and sample measurement with turn around time averaging about 10 minutes, which greatly improves process control response time with the normal increase in both productivity and quality vs having to collect the samples manually, bring them to a lab, and then make the measurement. It s so labor intensive, manual sampling and measurement intervals generally end up being measured in hours not enough time to prevent the process from going out of control and possibly shutting down. Microtrac has over 40 on- line image analysis systems like these installed in various processes. For information, please visit the Microtrac website ( 10