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- 저자 : M.P. Muthuraj (검색결과 3 건)
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Effect of medium coarse aggregate on fracture properties of ultra high strength concrete
B. Karthick,M.P. Muthuraj 국제구조공학회 2021 Structural Engineering and Mechanics, An Int'l Jou Vol.77 No.1
Ultra high strength concrete (UHSC) originally proposed by Richards and Cheyrezy (1995) composed of cement, silica fume, quartz sand, quartz powder, steel fibers, superplasticizer etc. Later, other ingredients such as fly ash, GGBS, metakaoline, copper slag, fine aggregate of different sizes have been added to original UHSC. In the present investigation, the combined effect of coarse aggregate (6mm – 10mm) and steel fibers (0.50%, 1.0% and 1.5%) has been studied on UHSC mixes to evaluate mechanical and fracture properties. Compressive strength, split tensile strength and modulus of elasticity were determined for the three UHSC mixes. Size dependent fracture energy was evaluated by using RILEM work of fracture and size independent fracture energy was evaluated by using (i) RILEM work of fracture with tail correction to load – deflection plot (ii) boundary effect method. The constitutive relationship between the residual stress carrying capacity (σ) and the corresponding crack opening (w) has been constructed in an inverse manner based on the concept of a non-linear hinge from the load-crack mouth opening plots of notched three-point bend beams. It was found that (i) the size independent fracture energy obtained by using above two approaches yielded similar value and (ii) tensile stress increases with the increase of % of fibers. These two fracture properties will be very much useful for the analysis of cracked concrete structural components.
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G. Velrajkumar,M.P. Muthuraj 사단법인 한국계산역학회 2020 Computers and Concrete, An International Journal Vol.26 No.1
Castellated beams fabricated from standard I-sections are being used for several structural applications such as commercial and industrial buildings, multistory buildings, warehouses and portal frames in view of numerous advantages. The advantages include enhanced moment of inertia, stiffness, flexural resistance, reduction in weight of structure, by passing the used plate girders, the passage of service through the web openings etc. In the present study, experimental and numerical investigations were carried out on concrete encased steel castellated beams with hexagonal openings under flexural loading. Various positions of openings such as along the neutral axis, above the neutral axis and below the neutral axis were considered for the study. From the experimental findings, it has been observed that the load-carrying capacity of the castellated beam with web opening above neutral axis is found to be higher compared to other configurations. Nonlinear finite element analysis was performed by using general purpose finite element software ABAQUS considering the material nonlinearities. Concrete damage plasticity model was employed to model the nonlinearity of concrete and elasto-plastic model for steel. It has been observed that FE model could able to capture the behaviour of concrete encased steel castellated beams and the predicted values are in good agreement with the corresponding experimental values.
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John Britto X.,Muthuraj M.P. 국제구조공학회 2019 Structural Engineering and Mechanics, An Int'l Jou Vol.70 No.6
This paper examines the applicability of artificial neural network (ANN) and multivariate adaptive regression splines (MARS) to predict the compressive strength of bacteria incorporated geopolymer concrete (GPC). The mix is composed of new bacterial strain, manufactured sand, ground granulated blast furnace slag, silica fume, metakaolin and fly ash. The concentration of sodium hydroxide (NaOH) is maintained at 8 Molar, sodium silicate (Na2SiO3) to NaOH weight ratio is 2.33 and the alkaline liquid to binder ratio of 0.35 and ambient curing temperature (28°C) is maintained for all the mixtures. In ANN, back-propagation training technique was employed for updating the weights of each layer based on the error in the network output. Levenberg-Marquardt algorithm was used for feed-forward back-propagation. MARS model was developed by establishing a relationship between a set of predictors and dependent variables. MARS is based on a divide and conquers strategy partitioning the training data sets into separate regions; each gets its own regression line. Six models based on ANN and MARS were developed to predict the compressive strength of bacteria incorporated GPC for 1, 3, 7, 28, 56 and 90 days. About 70% of the total 84 data sets obtained from experiments were used for development of the models and remaining 30% data was utilized for testing. From the study, it is observed that the predicted values from the models are found to be in good agreement with the corresponding experimental values and the developed models are robust and reliable.
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