Research Papers/Topics in Structural Engineering

Models For Predicting the Structural Characteristics of Sand-Quarry Dust Blocks

ABSTRACT In this work, models for predicting six structural characteristics and cost of sand-quarry dust blocks were developed. Three model equations namely Scheffe’s simplex lattice design (pseudo component), Scheffe’s simplex lattice design (component proportion) and Osadebe’s model were developed for each property. The properties investigated were Compressive strength, Water absorption and Split tensile strength. The others are Static modulus of elasticity, Flexural strength and She...

Application of UBC and IBC Seismic Codes For R.C. Buildings Design in Sudan

ABSTRACT  This research dealt with the investigation of possibility of the use of the two representative seismic codes, UBC 1997, and IBC 2006, for seismic force analysis of R.C. buildings in Sudan. The theory of the seismic forces analysis was studied and presented. A R.C. building of eight storeys constructed in two sites, a very low seismic active site and a moderate seismic active site in Sudan which was analyzed by using ETABSv9.7.4 computer program. Utilizing data of the two sites, app...

Structural Characteristics Of Soilcrete Blocks

ABSTRACT    This work investigates the structural characteristics of soilcrete blocks (lateritecement blocks and laterite-sand-cement blocks) produced with locally available and affordable laterite. Scheffe’s simplex method and Osadebe’s regression theory were used to formulate mathematical models for optimisation of properties of soilcrete blocks which include compressive strength, split tensile strength, shear strength, flexural strength, Poisson’s ratio, modulus of elasticity, shea...

Artificial Neural Network Model For The Prediction Of Elastic Modulus Of Concrete

ABSTRACT This research presents Artificial Neural Network Model for the prediction of the Modulus of Elasticity of Concrete. Egbulonu (2011) equation derived from Scheffe’s (4, 2) simplex equation for predicting the Modulus of Elasticity (MOE) was used to generate 800 values. These data represent different values of Modulus of Elasticity (MOE) out of which, 571 values were selected randomly by the artificial neural network. From the selected values, 400 were used for training the network,...