A compressive strength prediction model based on the hydration reaction of cement paste by rice husk ash. (18th July 2022)
- Record Type:
- Journal Article
- Title:
- A compressive strength prediction model based on the hydration reaction of cement paste by rice husk ash. (18th July 2022)
- Main Title:
- A compressive strength prediction model based on the hydration reaction of cement paste by rice husk ash
- Authors:
- Liu, Chao
Zhang, Wei
Liu, Huawei
Lin, Xin
Zhang, Rongfei - Abstract:
- Highlights: The compressive strength and workability of RHA concrete were studied. The effect of the hydration reaction of RHA on strength development was considered. A model to predict the compressive strength within 90d is was established. Good precision between the prediction model and compressive strength was observed. Abstract: The effect of partial replacement of cement by unground residual rice husk ash (RHA) on the workability and compressive strength of concrete was investigated in this work. In addition, the hydration products were also investigated in the blended cement paste by X-ray diffraction. An optimal replacement ratio model and a compressive strength prediction model were established based on the effect of RHA on the hydration reaction of cement paste. Evaluation of models was carried out using different statistical indicators. The results showed that the addition of RHA in concrete had a negative effect on the workability of fresh concrete, and the mechanical properties of concrete are optimal when the content of RHA is 20%. It has been verified that the established prediction model corrects well with the experimental results.
- Is Part Of:
- Construction & building materials. Volume 340(2022)
- Journal:
- Construction & building materials
- Issue:
- Volume 340(2022)
- Issue Display:
- Volume 340, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 340
- Issue:
- 2022
- Issue Sort Value:
- 2022-0340-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-07-18
- Subjects:
- Concrete -- Rice husk ash -- Compressive strength -- Prediction model
Building materials -- Periodicals
624.18 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09500618 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.conbuildmat.2022.127841 ↗
- 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:
- 21924.xml