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PI: Erol Tutumluer RA: Tongyan Pan Testing of OMP Aggregates for Shape Properties O’HARE Airport Modernization Research Project.

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Presentation on theme: "PI: Erol Tutumluer RA: Tongyan Pan Testing of OMP Aggregates for Shape Properties O’HARE Airport Modernization Research Project."— Presentation transcript:

1 PI: Erol Tutumluer RA: Tongyan Pan Testing of OMP Aggregates for Shape Properties O’HARE Airport Modernization Research Project

2 Introduction Aggregates make up more than 85% of Portland cement concrete and 90% of asphalt pavements of which coarse aggregate constitute the skeleton and occupies by far the highest weight or volume Aggregates make up more than 85% of Portland cement concrete and 90% of asphalt pavements of which coarse aggregate constitute the skeleton and occupies by far the highest weight or volume Coarse aggregate are believed to significantly affect strength, stability and deformation properties, and therefore, field performances Coarse aggregate are believed to significantly affect strength, stability and deformation properties, and therefore, field performances This project provides testing and analysis to establish an improved aggregate selection and evaluation for O’Hare airport pavements This project provides testing and analysis to establish an improved aggregate selection and evaluation for O’Hare airport pavements

3 Shape Properties of An Aggregate Particle Surface Texture Angularity Shape or Form Key Physical Shape Properties of an aggregate particle Roughness or irregularity at a micro level in contrast with angularity at a macro level Surface Area Surface Area

4 Introduction (cont’d) Aggregate shape factors, such as flatness and elongation, angularity, surface texture and surface area influence pavement behavior and performance Aggregate shape factors, such as flatness and elongation, angularity, surface texture and surface area influence pavement behavior and performance Aggregate shape has been related to permanent deformation and fatigue/cracking resistance of the pavement Aggregate shape has been related to permanent deformation and fatigue/cracking resistance of the pavement Based on current knowledge & past experience: Based on current knowledge & past experience: Equi-dimensional preferred over Flat & Elongated (F&E) Equi-dimensional preferred over Flat & Elongated (F&E) Crushed (angular) preferred over rounded Crushed (angular) preferred over rounded Rougher surface textured preferred over smooth Rougher surface textured preferred over smooth Larger specific surface area preferred for better bonding/binding with Portland cement/asphalt cement Larger specific surface area preferred for better bonding/binding with Portland cement/asphalt cement

5 Research Objectives Quantify shape, texture, angularity, and surface area properties of the coarse aggregates to be used by OMP in the various layers of new runway, taxiway, and shoulder pavements Quantify shape, texture, angularity, and surface area properties of the coarse aggregates to be used by OMP in the various layers of new runway, taxiway, and shoulder pavements Provide OMP with an aggregate shape property database to efficiently rank and utilize the sources of aggregate stockpiles according to shape properties available to them Provide OMP with an aggregate shape property database to efficiently rank and utilize the sources of aggregate stockpiles according to shape properties available to them Establish a means to develop improved and adaptable Portland cement concrete and asphalt mixture design methods and specifications that can accommodate aggregates with a wide range of physical characteristics and aggregate blending alternatives Establish a means to develop improved and adaptable Portland cement concrete and asphalt mixture design methods and specifications that can accommodate aggregates with a wide range of physical characteristics and aggregate blending alternatives

6 Project Tasks Task 1: Collect information on the types, geologic origins, and quarry sources of the coarse aggregate designated for use by OMP This information is crucial for identifying the approved aggregate sources and collecting aggregate bag samples for imaging based shape analysis This information is crucial for identifying the approved aggregate sources and collecting aggregate bag samples for imaging based shape analysis Subsequently, the acquisition of aggregate bag samples will be facilitated through OMP Subsequently, the acquisition of aggregate bag samples will be facilitated through OMP

7 Project Tasks Task 2: Test OMP coarse aggregates using the UIAIA automated procedure to quantify 3-D shape, size, angularity, surface texture and surface area and define proper imaging based morphological indices (i) maximum, intermediate, and minimum dimensions; (ii) flat and elongated (F&E) ratio; (iii) volume (and weight knowing its specific gravity); (iv) a computed Angularity Index (AI) to indicate how many crushed faces are there or how rounded or angular the particle is; (v) a computed Surface Texture (ST) Index to indicate how smooth or rough the aggregate particle surface is; and finally, (vi) a computed Surface Area (SA)

8 Advanced Transportation Research & Engineering Laboratory (ATREL) - University of Illinois:

9 University of Illinois Aggregate Image Analyzer - UIAIA Developed with funding from FHWA & IDOT Developed with funding from FHWA & IDOT Used in various State and Federal pooled fund studies [for evaluating coarse aggregate & linking aggregate shape to pavement performance Used in various State and Federal pooled fund studies [TPF-5(023)] for evaluating coarse aggregate & linking aggregate shape to pavement performance In 2005, selected by the NCHRP 4-30 study as one of the 2 promising aggregate image analysis systems In 2005, selected by the NCHRP 4-30 study as one of the 2 promising aggregate image analysis systems The only system to use three-orthogonally positioned cameras to capture 3-D shape properties The only system to use three-orthogonally positioned cameras to capture 3-D shape properties

10 Conveyor speed of 3 in./second Particles placed 10 in. apart Images captured within 0.1 second in succession Progressive Scan Video Camera University of Illinois Aggregate Image Analyzer - UIAIA Fiber Optic Motion Sensor

11 National Instruments Labview IMAQ Vision Image Acquisition by Virtual Instrument (VI)

12 Image Acquisition by UIAIA Three Orthogonal Views Capture three orthogonal views of a particle Top Front Side SIDE VIEW FRONT VIEW TOP VIEW SIDE VIEW FRONT VIEW

13 Main Features Image Capturing – 1000 particles in 70 minutes Image Capturing – 1000 particles in 70 minutes Image Processing / Analysis – 2 to 3 sec./particle Image Processing / Analysis – 2 to 3 sec./particle Volume Calculation Volume Calculation Flat and Elongated Ratio Flat and Elongated Ratio Particle Size Distribution (Gradation) Particle Size Distribution (Gradation) Angularity Angularity Surface Texture Surface Texture Surface Area Surface Area

14 Perform Volume Calculation Determine if a given pixel in the XYZ space appears in all three orthogonal views Determine if a given pixel in the XYZ space appears in all three orthogonal views Count number of such pixels (“cubic pixels”) Count number of such pixels (“cubic pixels”) Estimate “cubic pixel or voxel” volume Estimate “cubic pixel or voxel” volume Convert to volume units Convert to volume units through calibration through calibration x y z Y max X Z

15 Coarse Aggregate Shape and Size Indices from Imaging Using UIAIA, developed imaging based shape indices to quantify size and the three key physical shape properties of a coarse aggregate particle Flat and Elongated (F&E) Ratio Gradation Angularity Index (AI) Surface Texture (ST) Index Surface Area (SA) Surface Area (SA)

16 Imaging Based Flat & Elongated (F&E) Ratio Shortest dimension, Perpendicular to the Longest Dimension Longest Dimension Plane of Longest and Shortest Dimensions F&E Ratio = Longest dimension / Shortest dimension All 3 views are analyzed for the longest and shortest dimensions

17 F&E Ratio Repeatability – Limestone Sample 62A F & E Ratio Category Test Method UIAIA trial 3 UIAIA trial 2 UIAIA trial 1 Manual UI Manual IDOT WipShape GA Tech > 5: > 3:1 & < 5: < 3:

18 Sieve Analysis Concept — “If two orthogonal dimensions of a particle are greater than a given sieve, then the particle is retained on it” Concept — “If two orthogonal dimensions of a particle are greater than a given sieve, then the particle is retained on it” The intermediate dimension controls the sieve size on which the particle is retained The intermediate dimension controls the sieve size on which the particle is retained square opening DiDi D i = intermediate dimension < diagonal opening

19 Gradation Repeatability – Limestone Sample

20 Imaging Based Angularity Index (AI) Extract coordinates of the outline Extract coordinates of the outline Approximate the particle to a n-sided polygon Approximate the particle to a n-sided polygon Compute angle at vertices,  1,  2,..  n Compute angle at vertices,  1,  2,..  n Determine change in angle at each vertex,  1,  2,..  n Determine change in angle at each vertex,  1,  2,..  n Obtain frequency distribution of  1,  2,..  n Obtain frequency distribution of  1,  2,..  n n = no. of sampling points = 24 Angle at Vertex ‘1’=  1 ….. Angle at Vertex ‘n’=  n  1 -  2 =    1 -  2 =   ………..  n -  1 =  n n = n=24 4  1  2  3  n n-1

21 Angularity Index = AI = A 1 *Area1 + A 2 *Area2 + A 3 *Area3 (Area1 + Area2 + Area3) Theoretically, A = 0 for a circle For, e = 0, 10, 20, 30….170 for Class Interval 0-10, 10-20, 20-30… Angularity, A =  e*P(e) / n e=0e=170 Frequency Distribution of  -values Class Interval Frequency Imaging Based Angularity Index (AI)

22 AI for Gravel, Crushed Stone, & Blend More than 750 AI with n=24 Percentage particles by weight Crushed Stone Gravel Blend

23 Imaging Based Surface Texture (ST) Index ErosionDilation Area A 1 Area A 2 Image Processing Technique: Erosion and Dilation Erosion cycles followed by the same number of dilation cycles change the original image Erosion cycles followed by the same number of dilation cycles change the original image The rougher the particle, the less close the rebuilt image is to the original The rougher the particle, the less close the rebuilt image is to the original

24 Imaging Based Surface Texture (ST) Index 100 * A1A1 ST   A1A1 A2A2 ST particle  Area (front)  Area (top) Area (side)  ST (front) ST (top) ST (side) Area (front)  Area (top) Area (side)  × × × A 1 = Area (in pixels) of the 2-D projection of the particle in the image A 2 = Area (in pixels) of the particle after performing a sequence of “n” cycles of erosion followed by “n” cycles of dilation A1A1A1A1 A2A2A2A2 Before After

25 Samples Used In ST Index Development & Calibration Rough Crushed Stone Smooth Gravel Approximately 100 particles each Limestone

26 ST for Gravel vs Limestone Surface Texture Index Max Intercept or Feret Dimension L (pixels) Average ST for Gravel = 0.47 Average ST for Limestone = 1.57

27 Typical Ranges of Angularity and Surface Texture Indices Crushed Granite Crushed Limestone Crushed Gravel Uncrushed Gravel MeanRangeMeanRange Surface Texture (ST) Index Angularity Index (AI) Aggregate Type

28 Surface Area (SA) Computation Summation of the 2-D ∆S i ’ contained in voxels forming the particle surface gives the surface area of the particle in units of voxels (pixel cuboids)

29 Surface Area (SA) Computation (a) (b) Central Voxel to be judged In the smallest containing rectangular box, Searching for the voxels: 1) Belonging to agg. Particle Intensity of three projection pixels 2) On particle surface Six surrounding voxels

30 Project Tasks Task 3: Establish a shape property database for the OMP approved aggregate sources for use in pavement construction and provide recommendations regarding preferred source Property variations reported by the various UIAIA imaging based indices will be linked to laboratory and field performances of Portland cement concrete and asphalt layers for establishing possible correlations Property variations reported by the various UIAIA imaging based indices will be linked to laboratory and field performances of Portland cement concrete and asphalt layers for establishing possible correlations

31 Performances of Aggregate Materials in Pavement Structural Layers Unbound Aggregate Base Resilient Response

32 Material Mean AI  (deg) Crushed Stone Stone Gravel Blend C (psi) Shear Properties Angularity Index  (degrees) Rutting is an aggregate performance indicator controlled by shear strength Crushed Stone Stone Gravel Blend Performances of Aggregate Materials in Pavement Structural Layers

33 Asphalt Concrete Mix Rutting Performances – NCAT Test Track

34 Performances of Aggregate Materials in Pavement Structural Layers Resilient Response of Asphalt Mix Specimens

35 Performances of Aggregate Materials in Pavement Structural Layers Early Age Cracking of Portland Cement Concrete 12-hour Fracture Energy

36 Project Tasks Task 4: Evaluate impact of aggregate shape properties on the performances of constructed pavement layers by utilizing the image analyzed coarse aggregate with cataloged shape properties Such evaluations will require establishing cracking and rutting performance records of the pavement layers to investigate possible linkages between imaging based coarse aggregate shape indices and the pavement performances Such evaluations will require establishing cracking and rutting performance records of the pavement layers to investigate possible linkages between imaging based coarse aggregate shape indices and the pavement performances

37 Project Deliverables Technical Notes will be prepared and submitted to the OMP throughout the duration of this project to communicate specific findings and recommendations to OMP engineers as needed Technical Notes will be prepared and submitted to the OMP throughout the duration of this project to communicate specific findings and recommendations to OMP engineers as needed A Technical Report will be prepared at the end of the laboratory study to document results and findings of the experimental work A Technical Report will be prepared at the end of the laboratory study to document results and findings of the experimental work The Project Tasks will be pursued in the listed order, and the specific delivery of results will be contingent upon availability of OMP aggregate samples and other factors that depend on coordination with OMP The Project Tasks will be pursued in the listed order, and the specific delivery of results will be contingent upon availability of OMP aggregate samples and other factors that depend on coordination with OMP

38 Significance of the Project Provide OMP with Provide OMP with improved aggregate selection criteria improved aggregate selection criteria optimized aggregate resource utilization optimized aggregate resource utilization construction cost reductions construction cost reductions Identification and quantification of the influence of aggregate properties on end-use performance to identify aggregate issues & optimize performance linked to acceptable limits of aggregate Identification and quantification of the influence of aggregate properties on end-use performance to identify aggregate issues & optimize performance linked to acceptable limits of aggregate shapeshape angularityangularity texturetexture surface areasurface area

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