Prediction of compressive strength of SCC and HPC with high volume fly ash using ANN

An artificial neural network (ANN) is presented to predict a 28-day compressive strength of a normal and high strength self compacting concrete (SCC) and high performance concrete (HPC) with high volume fly ash. The ANN is trained by the data available in literature on normal volume fly ash because data on SCC with high volume fly ash is not available in sufficient quantity. Further, while predicting the strength of HPC the same data meant for SCC has been used to train in order to economise on computational effort. The compressive strengths of SCC and HPC as well as slump flow of SCC estimated by the proposed neural network are validated by experimental results.

Durability indicators of SCC towards performance-based specifications for the durability of SCC

The fundamental principle behind the development of SCC has been the nanoscale tailoring of cementitious matrices. Although self-compacting concrete (SCC) is currently used in many countries, there is a fundamental lack of the intrinsic durability of the material itself. The scope of the current paper is to present the outcomes of a research study on some principal indicators (porosity and capillary absorption) that define the durability of SCC, and how these are compared with the corresponding parameters of conventional concrete. Furthermore, this paper investigates the addition of industrial by-products, such as fly-ash or lime powder, to SCC mixtures and their effect on the durability indicators.

稀土铒和铬离子注入对电机护环钢SCC性能的影响

研究了铒和铬离子高、中能量重迭注入对50Mn18Cr4电机护环钢SCC性能的影响。SCC对比试验结果表明:(1)在QHJ-79标准硝酸盐介质中,离子注入试样的SCC出现时间(t_f)比不经注入试样的延长了6倍以上,致钝和维钝电流密度下降了一个数量级; (2)在阴极充氢条件下,两种试样均对氢致开裂(HIC)不敏感,但离子注入可抑制氢诱发腐蚀。用AES-PRO、RBS、XPS-PRO、EDAX、金相及电化学方法分析讨论了护环钢在QHJ-79标准介质中的SCC机 理和离子注入改善SCC抗力及抗氢锈发腐蚀性能的机制。

Performance of sustainable SCC mixes with mineral additions for use in precast concrete industry

The aim of this research was to study the impact that different mineral powders have on the properties of self-compacting concrete (SCC) in order to obtain relations that make it possible to optimize their dosages for being used in precast concrete applications. Different combinations and contents of cement, mineral additions (active and inert), superplasticizers, and aggregates are considered. A new approach for determining the saturation point of superplasticizers is introduced. The fresh state performance was assessed by means of the following tests: slump flow, V-funnel, and J-ring. Concrete compressive strength values at different ages up to 56 days have been retained as representative of the materials’ performance in its hardened state. All these properties have been correlated with SCC proportioning. As a result, a number of recommendations for the precast concrete industry arise to design more stable SCC mixes with a reduced carbon footprint.