Development Phase Of Intelligent Optimization System For Sustainable High Performance Concrete Mix Design
Sustainable high performance concrete is vital for maintaining the equilibrium for impact of environmental pollution, intelligent allocation of scarce resources and the development of economy. Mix design for sustainable High Performance Concrete (HPC) is more difficult compared to normal concrete because of high strength requirement together with super-workability and durability which involves mineral and chemical admixtures. It requires a lot of experience and judgment before selecting the actual mix design since prediction of strength and workability of HPC is very important task in construction work schedule. However, artificial neural networks have been applied as an efficient solution in modeling highly nonlinear and high complexity in many areas in engineering. An Intelligent Optimization System for Sustainable High Performance Concrete Mix Design (INOS-HPC) by means of using artificial neural network (ANN) has been successfully developed. The developed neural network model has ability to handle fusion of multiple sources of data and information. This study presents the effectiveness of adopting ANN in predicting the mix proportions of sustainable high performance concrete with specified compressive strength and workability.
Sustainable High Performance Concrete Mix Design Artificial Neural Network
M. Jamil M.F.M. Zain H.B.Basri
Faculty Of Engineering & Built Environment,Universiti Kebangsaan Malaysia,Malaysia
国际会议
2011 International Conference on Future Environment and Energy(ICFEE 2011)(2011年未来环境与能源大会)
三亚
英文
244-247
2011-03-25（万方平台首次上网日期，不代表论文的发表时间）