Abstract: There is a great challenge for civil engineering field to contribute in environment prevention by finding out alternatives of cement and natural aggregates. There is a problem of global warming due to cement utilization in concrete, so it is necessary to give sustainable solution to produce concrete containing waste. It is very difficult to produce designated grade of concrete containing different ingredient and water cement ratio including waste to achieve desired fresh and harden properties of concrete as per requirement and specifications. To achieve the desired grade of concrete, a number of trials have to be taken, and then after evaluating the different parameters at long time performance, the concrete can be finalized to use for different purposes. This research work is carried out to solve the problem of time, cost and serviceability in the field of construction. In this research work, artificial neural network introduced to fix proportion of concrete ingredient with 50% waste replacement for M20, M25, M30, M35, M40, M45, M50, M55 and M60 grades of concrete. By using the neural network, mix design of high performance concrete was finalized, and the main basic mechanical properties were predicted at 3 days, 7 days and 28 days. The predicted strength was compared with the actual experimental mix design and concrete cube strength after 3 days, 7 days and 28 days. This experimentally and neural network based mix design can be used practically in field to give cost effective, time saving, feasible and sustainable high performance concrete for different types of structures.
Abstract: When a building is located in an urban area, it is
exposed to a wind of different characteristics then wind over an open
terrain. This is development of turbulent wake region behind an
upstream building. The interaction with upstream building can
produce significant changes in the response of the tall building. Here,
in this paper, an attempt has been made to study wind induced
interference effects on tall building. In order to study wind induced
interference effect (IF) on Tall Building, initially a tall building
(which is termed as Principal Building now on wards) with square
plan shape has been considered with different Height to Width Ratio
and total drag force is obtained considering different terrain
conditions as well as different incident wind direction. Then total
drag force on Principal Building is obtained by considering adjacent
building which is termed as Interfering Building now on wards with
different terrain conditions and incident wind angle. To execute
study, Computational Fluid Dynamics (CFD) Code namely Fluent
and Gambit have been used.
Abstract: Particle swarm optimization (PSO) technique is applied to design the water distribution pipeline network. A simulation-optimization model is formulated with the objective of minimizing cost and is applied to a benchmark water distribution system optimization problem. The benchmark problem taken for the application of PSO technique to optimize the pipe size of the water distribution network is New York City water supply system problem. The results from the analysis infer that PSO is a potential alternative optimization technique when compared to other heuristic techniques for optimal sizing of water distribution systems.