Mix Design Effects on the Durability of Alkali-Activated Slag Concrete in a Hydrochloric Acid Environment

Because of its high strength, energy reduction, and low environmental impact, researchers have encouraged considering alkali-activated slag concrete (AASC) as a potential alternative to conventional concrete. In this study, the impact of mix design parameters on the durability of AASC, made with ground granulated blast furnace slag and activated with different alkaline solutions (NaOH, KOH, and Na2SiO3 ) immersed up to six months in a hydrochloric acid bath with pH = 3, has been investigated. A total of 13 mix designs were made in a way that, in addition to the type of alkaline solution, considered three other parameters, namely the molarity of alkaline solutions, the weight ratio of alkaline solutions to slag, and the weight ratio of alkaline solutions to sodium silicate. Visual inspections displayed that the AASC samples almost remained intact after exposure to an HCl acid solution with pH = 3 for up to 6 months, while the OPC sample experienced deleterious deterioration. The results clearly show that AASC outperformed OPC concrete when it comes to durability in an HCl acid solution. The strength reduction and weight loss of AASC compared with OPC concrete were approximately one-tenth and one-fifth, respectively. The AASC samples containing potassium hydroxide showed a higher strength reduction and weight loss in the HCl acid solution than the samples made with sodium hydroxide

Effect of Micro-Silica Addition into Electric Arc Furnace Steel Slag Eco-Efficient Concrete

ABSTRACT: Concrete produced from electric arc furnace steel slag aggregates is one of the items that is highly regarded due to its strength, environmental friendliness and cost-effectiveness. Despite the growing interest in using this type of concrete, there are still doubts about the mix proportions and addition effects of electric arc furnace steel slags. In this paper, the performance of replacing natural aggregates by electric arc furnace steel slags aggregate is comprehensively investigated and its effect on mechanical properties is analysed. The relationship between the percentage of replacement of natural aggregate using electric arc furnace steel slags aggregate in two parts of coarse aggregate and fine-grained aggregate and the effect of each of these parts on mechanical properties in concrete is investigated, which may identify the optimal mix proportions of each aggregate that help to improve the strength of the eco efficient concrete using electric arc furnace steel slags

Retro MTA and tricalcium phosphate/retro MTA for guided tissue regeneration of periodontal dehiscence defects in a dog model: a pilot study

Objectives: Retro MTA is a fast setting Calcium silicate cement used in endodontic regeneration procedures in recent years. Beta-tricalcium phosphate (β-TCP) is another common biomaterial used for bone augmentation procedures. The present pilot study was undertaken to evaluate and compare the efficacy of Retro MTA and a mixture of Retro MTA / β-TCP for periodontal tissue regeneration. Materials and methods: In 4 beagle dogs, periodontal dehiscence type defects were created. In each side, one dehiscence defect was left empty as a control site and three treatment modalities were randomly applied for the others: Retro MTA covered with a collagen membrane, Retro MTA + β-TCP covered with a membrane and covering the defect with a membrane without any bone augmentation. After 8 weeks Animals were sacrificed and Histomorphometric and histologic analysis were conducted. Results: Histologic analysis showed more cementum formation for both Retro MTA+ β-TCP (3.74 ± 0.34 mm) and Retro MTA group (3.24 ± 0.56 mm) compared to control group 1 (1. 15 ± 0.45 mm) and control group 2 (0.78 ± 0.65 mm). Formation of newly formed bone and cementum in the experimental groups were significantly higher as compared to the control groups (P < 0.0001). Conclusions: Retro MTA or Retro MTA+ β-TCP covered with a collagen membrane resulted in regeneration of periodontal tissues. However, Retro MTA+ β-TCP showed tendency towards better results than the use of Retro MTA alone. KEYWORDS: Bone regeneration; Calcium silicate cement; Guided tissue regeneration; MT

Microstructural analysis of siderurgical aggregate concrete reinforced with fibers

The development of cracks in concrete structures is one of the significant issues with maintaining high strength after hardening. One way to prevent and control this problem is to use fibers. This paper investigates concrete containing electric arc furnace slag aggregates reinforced with fibers. The fibers used in this study are steel fibers and three kinds of polypropylene fibers; polyolefin fibers (modified polypropylene), polypropylene homopolymer, and high-toughness polypropylene. By checking the compressive and flexural strength of concretes made with fibers, it can be seen that the best results at 28 days are found for concrete with steel fibers, namely 62 MPa with 0.9% of fibers. On the contrary, the lowest values are for concrete containing polyolefin fibers, 51 MPa, and the same percentage of fibers. Additionally, under flexural strength testing, at the age of 28 days, the strength of these samples with 0.9% of fibers was 9.54 MPa, a value that is comparable to test concrete with the same percentage of steel fibers, 10.67 MPa, despite the low workability of concrete containing polyolefin fibers with a slump of 25 mm. Moreover, the boundary transition area analysis shows that the excellent connection between the fibers and cement paste near the siderurgical aggregate has caused no cracks in this area. In contrast, cracks can be observed in critical areas near the natural aggregates

The Use of Machine Learning Models in Estimating the Compressive Strength of Recycled Brick Aggregate Concrete

The focus of this study is to investigate the applicability of Adaptive Neuro-Fuzzy Inference System (ANFIS), Artificial Neural Network (ANN), and Multiple Linear Regression (MLR) in modeling the compressive strength of Recycled Brick Aggregate Concrete (RBAC). A comparative study on the application of the aforementioned models is developed based on statistical tools such as coefficient of determination, mean absolute error, root mean squared error, and some others, and the application potential of each of these models is investigated. To study the effects of RBAC factors on the performance of representative data-driven models, the Sensitivity Analysis (SA) method is used. The findings revealed that ANN with R2 value of 0.9102 has a great application potential in predicting the compressive strength of concrete. In the absence of ANN, ANFIS with R2 value of 0.8538 is also an excellent substitute for predictions. MLR was shown to be less effective than the preceding models and is only recommended for preliminary estimations. In addition, Subsequent sensitivity analysis on the database indicates the reliability of the prediction models have a strong correlation to the number of input parameters. The application of ANN and ANFIS as a precursor to traditional methods can eliminate the need for old-style tests, thus, constituting a significant reduction in time and expense needed for design and/or repairs

Message Passing for Analysis and Resilient Design of Self-Healing Interdependent Cyber-Physical Networks

Click on the DOI link to access the article (may not be free).Coupling cyber and physical systems gives rise to numerous engineering challenges and opportunities. An important challenge is the contagion of failure from one system to another, that can lead to large scale cascading failures. On the other hand, self-healing ability emerges as a valuable opportunity where the overlay cyber network can cure failures in the underlying physical network. To capture both self-healing and contagion, we introduce a factor graph representation of inter-dependent cyber-physical systems in which factor nodes represent various node functionalities and the edges capture the interactions between the nodes. We develop a message passing algorithm to study the dynamics of failure propagation and healing in this representation. Through applying a fixed-point analysis to this algorithm, we investigate the network reaction to initial disruptions. Our analysis provides simple yet critical guidelines for choosing network parameters to achieve resiliency against cascading failures