Sutrisno, Wahyuniarsih
Institut Teknologi Sepuluh Nopember

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INVESTIGATION OF THE EFFECT OF SANDBLASTING WASTE TREATMENT METHOD AS NANO-SILICA ON THE COMPRESSIVE STRENGTH OF CONCRETE MORTAR Abidin, Muhammad Zainal; Sutrisno, Wahyuniarsih; Sutrisno, Rahmat Dwi
Journal of Civil Engineering Vol 38, No 2 (2023)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20861206.v38i2.17125

Abstract

This study presents the effect of nano-silica (NS) from sandblasting waste as an additive on the mechanical properties of concrete mortar. The nano-silica was produced by using the sol-gel and mechanical grinding methods. In this research, nano silica material was added as an additive with a percentage varying from 0% to 5%. The results show that producing nano silica from sandblasting waste with a combination of sol-gel and mechanical grinding methods can produce an average size of 148.9 nm with 96.90% purities silica (SiO2). The compressive strength test also shows that adding NS can increase the compressive strength of the concrete. The highest compressive strength obtained from this research was. 29.76 MPa with the addition of 1% of nano-silica. This compressive strength is 37.5% higher than the control mixture.
Experimental Evaluation of Heat of Hydration in Concrete Incorporating Supplementary Cementitious Materials Lada, Adveni Hesty Altisari; Sutrisno, Wahyuniarsih; Piscesa, Bambang
Journal of Civil Engineering Vol 39, No 2 (2024)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20861206.v39i2.21651

Abstract

This research aims to study the impact of supplementary cementitious materials on the heat of hydration of concrete. The experimental tests were performed for concrete with three size variations and seven variations of supplementary cementitious materials (SCMs) to investigate its impact on the heat of hydration. The SCMs used in this research mainly come from industrial waste materials. Fly ash (FA), ground bottom ash (GBA), and silica fume (SF) were the waste materials used in this research. Tests were carried out for seven days for each variation to observe the effect of volume changes and the addition of SCMs on the change in concrete temperature. The experimental results indicated a direct correlation between concrete volume and maximum temperature, with notable variations in temperature distribution across the concrete mass. Typically, the highest temperature was observed at the core of the concrete. Fly ash (FA) and bottom ash (BA) demonstrated an inverse relationship between their content as supplementary cementitious materials (SCMs) and the maximum temperature achieved. Increasing the proportion of FA and BA in the concrete mixture resulted in a reduction of the hydration temperature. Additionally, silica fume (SF) was found to accelerate the hydration rate, though its efficacy in lowering the heat of hydration was significant only when its content exceeded 5%.
Modeling Reinforced Concrete Column with GRFP Transverse Reinforcement Adena, Haura; Alrasyid, Harun; Sutrisno, Wahyuniarsih; Piscesa, Bambang
Journal of Civil Engineering Vol 40, No 1 (2025)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20861206.v40i1.22019

Abstract

The utilization of GFRP (Glass Fiber Reinforced Polymer) in reinforced concrete structures is gaining attention due to its high strength and low corrosion. The application of GRFP rebar as longitudinal and tranverse reinforced columns has been studied through experimental testing. However it is important to understand the deformation responses and to predict the behavior of concrete columns with GRFP Rebar. This objective requires suitable and effective tools. This study presents Finite Element Analysis of Concrete Column reinforced with GRFP Rebar using 3DNLFEA. The result showed that The analysis result exhibited that the prediction of model behavior corresponds well with the experimental results.