Determining the specific surface area of coarse aggregate based on sieving curve via image-analysis approach. (25th October 2021)
- Record Type:
- Journal Article
- Title:
- Determining the specific surface area of coarse aggregate based on sieving curve via image-analysis approach. (25th October 2021)
- Main Title:
- Determining the specific surface area of coarse aggregate based on sieving curve via image-analysis approach
- Authors:
- Wang, Qing
He, Jianqiang
Sun, Jing
Ho, Johnny - Abstract:
- Highlights: Paste-wrapping method is applied in SSA evaluation. Size parameters are obtained through image-analysis approach. Cylindrical model with average ferret diameter exhibits the lowest error. Numerical computation of SSA is established based on aggregate sieving. Abstract: Coarse aggregate composes the highest volume in concrete and affects the fresh and hardened performance significantly. To analyze the distribution status of coarse aggregate in cementitious system, the specific surface area (SSA) stays one of the essential parameters but relatively complicated to be determined by traditional ways. Due to the easy acquirement of the sieving characteristics in coarse aggregate, its relationship with SSA is explored and established in the present study. Initially, 20 coarse aggregate samples are obtained by quartering method with similar sieving curves of the same patch. Then, SSA of the samples is evaluated experimentally via paste-wrapping method. Afterwards, the shape parameters of individual aggregate samples are analyzed via image-analysis approach. Herein, cylindrical, prismatic and ellipsoid models, in total 11 models, are utilized to simulate the SSA of the selected samples. Results show that the cylindrical model adopting the parameter of average feret diameter best describes the SSA in comparison with the experimental results. On account of the relationship between the surface area/volume and diameter of the samples, a numerical method of SSA is establishedHighlights: Paste-wrapping method is applied in SSA evaluation. Size parameters are obtained through image-analysis approach. Cylindrical model with average ferret diameter exhibits the lowest error. Numerical computation of SSA is established based on aggregate sieving. Abstract: Coarse aggregate composes the highest volume in concrete and affects the fresh and hardened performance significantly. To analyze the distribution status of coarse aggregate in cementitious system, the specific surface area (SSA) stays one of the essential parameters but relatively complicated to be determined by traditional ways. Due to the easy acquirement of the sieving characteristics in coarse aggregate, its relationship with SSA is explored and established in the present study. Initially, 20 coarse aggregate samples are obtained by quartering method with similar sieving curves of the same patch. Then, SSA of the samples is evaluated experimentally via paste-wrapping method. Afterwards, the shape parameters of individual aggregate samples are analyzed via image-analysis approach. Herein, cylindrical, prismatic and ellipsoid models, in total 11 models, are utilized to simulate the SSA of the selected samples. Results show that the cylindrical model adopting the parameter of average feret diameter best describes the SSA in comparison with the experimental results. On account of the relationship between the surface area/volume and diameter of the samples, a numerical method of SSA is established using the sieving characteristics of coarse aggregate, thus providing an effective and simple solution in determining the SSA of coarse aggregate in concrete. … (more)
- Is Part Of:
- Construction & building materials. Volume 305(2021)
- Journal:
- Construction & building materials
- Issue:
- Volume 305(2021)
- Issue Display:
- Volume 305, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 305
- Issue:
- 2021
- Issue Sort Value:
- 2021-0305-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-10-25
- Subjects:
- Specific surface area -- Coarse aggregate -- Image analysis -- Feret diameter -- Numerical analysis
Building materials -- Periodicals
624.18 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09500618 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.conbuildmat.2021.124728 ↗
- Languages:
- English
- ISSNs:
- 0950-0618
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3420.950900
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 18906.xml