Henning Roedel¹, Isamar Rosa Plata¹, Michael Lepech^1,*, David Loftus²

Journal of Renewable Materials, Vol.3, No.3, pp. 183-194, 2015, DOI:10.7569/JRM.2015.634107

Abstract This article presents the sustainability assessment of a novel biocomposite material that is under investigation by NASA for use in construction in limited resource environments. The composite consists of soil particles solidified by a protein binding agent. Preliminary compressive strength data suggests the biocomposite could be used for numerous construction applications. To assess the biocomposite’s potential for use in sustainable construction, a comparative process-based life cycle assessment between biocomposite and concrete pavers was performed to analyze the life cycle primary energy and IMPACT 2002+ points of both types of pavers. Results show that the concrete More >

Z. Bouhssine¹, M. Faraji¹, M. Najam¹, M. El Alami^1,2

FDMP-Fluid Dynamics & Materials Processing, Vol.11, No.1, pp. 63-85, 2015, DOI:10.3970/fdmp.2015.011.063

Abstract The objective of this study is to optimize the thermal performance of a solar collector. The solar collector is coupled to a building slab with a PCM layer. A mathematical model for the thermal behavior of the studied system is developed using the enthalpy method. The model parameters are defined and the resulting equations are solved iteratively. Several simulations were carried out to optimize the proposed heating system. The results show that the inlet temperature fluctuations are less pronounced than those at the outlet. More >

Q.W. Yang¹, S.G. Du^1,2

CMC-Computers, Materials & Continua, Vol.47, No.3, pp. 217-236, 2015, DOI:10.3970/cmc.2015.047.217

Abstract Size effect is a major issue in concrete structures and occurs in concrete in any loading conditions. In this study, size effect on concrete cubic compressive strength is modeled with a back-propagation neural network. The main advantage in using an artificial neural network (ANN) technique is that the network is built directly from experimental data without any simplifying assumptions via the self-organizing capabilities of the neural network. The proposed ANN model is verified by using 27 experimental data sets collected from the literature. For the large specimens, a modified ANN is developed in the paper More >

Benjamin Lepers^a,*, Aditya Putranto^b,c, Martin Umminger^d, Guido Link^a, John Jelonnek^a

Frontiers in Heat and Mass Transfer, Vol.5, pp. 1-11, 2014, DOI:10.5098/hmt.5.13

Abstract The use of high power microwaves to perform explosive spalling of surface concrete is a promising technique with applications in the area of concrete facilities decommissioning. The mechanism that creates explosive spalling is an interactive process of the thermal stress from high temperature gradients and the pore pressure generated from the water vaporization. In order to better predict the total stress distribution, the temperature has to be calculated by including the effect of water vaporization and water transport through a porous medium. In this paper, a one dimensional model solving the heat and diffusion equation More >

Y. Zhang¹, Y. F. Nie², Y. T. Wu¹

CMC-Computers, Materials & Continua, Vol.40, No.3, pp. 203-218, 2014, DOI:10.3970/cmc.2014.040.203

Abstract The present study aims to evaluate the mechanical properties of steel fiber reinforced concrete (SFRC) by the statistical second-order two-scale (SSOTS) method. At first, the representation for microstructure of SFRC is described by a concept of statistical screen. According to the microstructure representation, the SSOTS method is displayed in a concise way. This method is on the basis of asymptotic expansion homogenization and Monte Carlo method, and can calculate the local strain and stress field through the two-order displacement solution. As the classical homogenization method, the expression of homogenized elastic modulus is derived analytically. Then More >

Yong-Lin Pi¹, Mark Andrew Bradford¹

CMES-Computer Modeling in Engineering & Sciences, Vol.99, No.3, pp. 233-253, 2014, DOI:10.3970/cmes.2014.099.233

Abstract Creep and shrinkage of the concrete core of a concrete-filled steel tubular (CFST) arch under sustained loading are inevitable, and cause a long-term change of the equilibrium configuration of the CFST arch. As the equilibrium configuration changes continuously, the long-term radial and axial displacements of the CFST arch, stress distributions as well as the internal forces in the steel tube and the concrete core change substantially with time. Creep and shrinkage of the concrete core are related to a number of its material parameters such as its creep coefficient, aging coefficient, and shrinkage strain. The… More >

Shantaram Parab¹, Shreya Srivastava², Pijush Samui³, A. Ramachandra Murthy⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.101, No.2, pp. 139-158, 2014, DOI:10.3970/cmes.2014.101.139

Abstract This paper studies the applicability of Gaussian Process Regression (GPR) and Least Squares Support Vector Machines (LSSVM) to predict fracture parameters and failure load (P_max) of high strength and ultra-high strength concrete beams. Fracture characteristics include fracture energy (G_F), critical stress intensity factor (K_IC) and critical crack tip opening displacement (CTOD_C) Mathematical models have been developed in the form of relation between several input variables such as beam dimensions, water cement ratio, compressive strength, split tensile strength, notch depth, modulus of elasticity and output fracture parameters. Four GPR and four LSSVM models have been developed using MATLAB… More >

S. Liu¹, X. Liu^2,3, Y. Yuan², H. A. Mang⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.100, No.3, pp. 157-200, 2014, DOI:10.3970/cmes.2014.100.157

Abstract A nonlinear viscoelastic constitutive model for early age concrete is presented in this paper. In this model, time-dependent properties, such as the elastic modulus, and thermal and autogenous shrinkage deformations, are computed by a stochastic multi-scale method, in which three different scales are specified according to the requirement of separation of scales, and different scales are linked by means of the asymptotic expansion theory with the help of specific representative volume elements (RVE). Thus, a cross-scale research from the cement paste to the macro structure of concrete is realized, and performance-based optimization of cement-based materials… More >

A. Ramach,ra Murthy^1,2, V. Ramesh Kumar¹, Smitha Gopinath¹, PrabhatRanjan Prem¹, Nagesh R. Iyer³, Reshmi Balakrishnan⁴

CMC-Computers, Materials & Continua, Vol.44, No.1, pp. 59-72, 2014, DOI:10.3970/cmc.2014.044.059

Abstract This paper investigates the flexural performance of a sandwich panel made up of ultra high strength concrete (UHSC) as top and bottom skin and cold formed steel as sandwich. A novel sandwich panel has been designed such a way that bottom skin of UHSC is of precast in nature and top skin of UHSC is cast-insitu and cold formed steel (profiled sheet) as sandwich. The connection between top skin of UHSC and cold formed steel is made with self tapping screws. Flexural performance of UHSC sandwich panel has been tested under flexural loading and it… More >

Vishal Shreyans Shah¹, Henyl Rakesh Shah², Pijush Samui³, A. Ramachra Murthy⁴

CMC-Computers, Materials & Continua, Vol.44, No.2, pp. 73-84, 2014, DOI:10.3970/cmc.2014.044.073

Abstract This paper deals with the development of models for prediction of facture parameters, namely, fracture energy and ultimate load of high strength and ultra high strength concrete based on Minimax Probability Machine Regression (MPMR) and Extreme Learning Machine (ELM). MPMR is developed based on Minimax Probability Machine Classification (MPMC). ELM is the modified version of Single Hidden Layer Feed Foreword Network (SLFN). MPMR and ELM has been used as regression techniques. Mathematical models have been developed in the form of relation between several input variables such as beam dimensions, water cement ratio, compressive strength, split More >