Apr'20

The IUP Journal of Structural Engineering

Focus

ndian Standard guidelines have been used to prepare M30 concrete for computing control mix ratio. The literature study indicated that optimum percentage of quarry dust to be used could be 25% as replacement for fine aggregate. Polyethylene glycol has been used in the concrete mix for self-curing. Cubes and cylinders were casted as per the code specifications for test. From the test results, it is concluded that optimum percentage of lightweight aggregate for maximum compressive, tensile strength and modulus of rupture is about 25% for M30 grade concrete. With 25% lightweight aggregate as replacement, the optimum dose of polyethylene glyclol will be 1% for obtaining maximum concrete strength. When the percentage of lightweight aggregate increases in the mix, the slump value decreases. It is also observed that flexural behavior of self-curing concrete is the same as that of the conventional concrete.

The second paper, "Foamed Concrete with GGBS, Fly Ash, Polypropylene and Recron3s Fibers: An Experimental Study", by Suhas H B, Nikhil A Jambhale and K B Prakash, investigates the physical and mechanical properties of foamed concrete with addition of fly ash as replacement for fine aggregate. The foamed concrete is a lightweight concrete with density ranging from 400 to 1,600 kg/m3. Use of low density concrete decreases the self-weight of concrete, which further reduces the weight of column, beam and slabs, and thus a reduction in total weight of the structure could be achieved. But it may lead to other design problems as concrete will have low density. In the preliminary investigation, fly ash and ground granulated blast furnace slag are subjected to physical and mechanical analysis to decide whether the silica fumes are in compliance with the prescribed standard. Synthetic-based foaming agent is used in the study to produce foam. Recron3 fibers, an industrial waste, is added to concrete mix. Polypropylene is a non-synthetic thermoplastic polymer and when added to concrete, it improves the performance even after cracking. This polymer is rustproof, alkali-resistant, nonmagnetic and has low thermal conductivity. The study aimed at producing a foamed concrete with density of 1,200 kg/m3, and for this density all ingredients required were calculated. The concrete mixture was thoroughly mixed in rotating drum and specimens for tests were casted as cubes and cylinders. The results indicate that the maximum strength of concrete is achieved by addition of about 0.2% of recron3s and polypropylene fibers. Any further increase of fibers decreases the strength of foamed concrete. The study concludes that foamed concrete has less compressive strength than normal conventional concrete and thus not suitable to be used for main structural work but could be effectively utilized for partition walls, and hence reduction in weight of structure could be achieved.

The last paper, "ANN-Based Shear Capacity of Steel Fiber-Reinforced Concrete Beams Without Stirrups", by M Abambres and E Lantsoght, evaluates the shear capacity of steel fiber reinforced concrete beam without mild steel stirrups. The normal practice in reinforced beam construction is to provide stirrups for improving shear strength of beams, but the study evaluates the capacity without any stirrups using ANN technique. From the available literature, a database of 430 test results were used to develop artificial neural network-based formula to predict the shear capacity of beams without stirrups. It is well-known that concrete is strong in compression but weak in tension, hence addition of steel fibers to concrete mix could be a solution to increase its strength in tension to a limited value. Further, this addition also helps in crack prevention in concrete. The study exhaustively uses available publications in this regard. The whole analysis was done using MATLAB and making use of its neural network tool box. Parametric analysis was conducted to select the best ANN according to certain chosen criteria. Nine input variables were taken to describe the problem, whereas the maximum sectional shear force at collapse was the selected target variable. After several ANN-based parametric analyses, the resulting optimal model yielded maximum and mean relative errors of 0.0% for all the chosen data points. This proposed model outperforms the currently available formulas and code provisions. The study shows how ANN can be used to predict shear capacity of steel fiber reinforced concrete beams without stirrups. This study has limitations, and for generalizations, more work requires to be done using large sized beams.

- Satyendra P Gupta
Consulting Editor

CheckOut
Article   Price (₹) Buy
Improvement of the Strength Properties of Self-Curing Concrete with Partial Replacement of Fine Aggregate Using Quarry Dust
50
Foamed Concrete with GGBS, Fly Ash, Polypropylene and Recron3s Fibers: An Experimental Study
50
ANN-Based Shear Capacity of Steel Fiber-Reinforced Concrete Beams Without Stirrups
50
     
Contents : (Apr 2020)

Improvement of the Strength Properties of Self-Curing Concrete with Partial Replacement of Fine Aggregate Using Quarry Dust
Muthuraman P, Thangapandi K and R Anuradha

Self-curing concrete is one of the special concretes in mitigating insufficient curing due to human negligence, paucity of water in arid areas, inaccessibility of structures in difficult terrains and in areas where the presence of fluorides in water badly affects the characteristics of concrete. The aim of the paper is to evaluate the use of water-soluble Polyethylene Glycol (PEG) as self-curing agent with partial replacement of conventional fine aggregate with lightweight fine aggregate and to optimize the quantity of PEG. Flexural behavior of self-curing concrete of M30 grade is casted by replacing optimum percentage of natural fine aggregate with lightweight fine aggregate and optimum percentage of PEG by weight of cement. The fine aggregate was partially replaced with 25% quarry dust. From the optimum percentage of lightweight fine aggregate replacement, optimum percentage of PEG -400 was found out by varying the percentage of PEG from 0%, 0.5%, 1% and 1.5% by weight of cement for M30 grade of concrete. The compressive strength, split tensile strength and flexural strength of self-curing concrete with varying quantity of polyethylene glycol are evaluated and compared with the conventional concrete specimen.


© 2020 IUP. All Rights Reserved.

Article Price : ₹ 50

Foamed Concrete with GGBS, Fly Ash, Polypropylene and Recron3s Fibers: An Experimental Study
Suhas H B, Nikhil A Jambhale and K B Prakash

The paper presents foamed concrete with a density of 1000 kg/m3 by replacing fine aggregate of 50% fly ash and 50% GGBS with addition of different percentages of polypropylene and recron3s fibers (0%, 0.1%, 0.2%, 0.3%, 0.4% and 0.5%). Also, the physical and mechanical properties of foam concrete are studied. The results indicate that fibers gave the optimum result by a certain percentage of fiber dosage by increasing compressive strength, flexural strength and split tensile strength. The water absorption properties are also measured. The foam concrete also tested the bonding properties of fiber, foam and cementation materials. The total number of specimens included 24 beam, 24 cylinder and 24 cubes. They kept curing for 28 days. To check the bonding of material, Scanning Electron Microscopy (SEM) and Energy Dispersive X-Ray Spectroscopy (EDS) tests were conducted.


© 2020 IUP. All Rights Reserved.

Article Price : ₹ 50

ANN-Based Shear Capacity of Steel Fiber-Reinforced Concrete Beams Without Stirrups
M Abambres and E Lantsoght

Comparing experimental results on the shear capacity of Steel Fiber-Reinforced Concrete (SFRC) beams without mild steel stirrups to the ones predicted by current design equations and other available formulations still shows significant differences. The paper proposes the use of Artificial Intelligence (AI) to estimate the shear capacity of these members. A database of 430 test results reported in the literature is used to develop an Artificial Neural Network (ANN)-based formula that predicts the shear capacity of SFRC beams without shear reinforcement. The proposed model yields maximum and mean relative errors of 0.0% for the 430 data points, which represents a better prediction (mean Vtest/VANN = 1.00 with a coefficient of variation of 1'10-15) than the existing expressions, where the best model yields a mean value of Vtest/Vpred = 1.01 and a coefficient of variation of 27%.

© 2020 IUP. All Rights Reserved.

Article Price : ₹ 50

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