OPTIMIZATION OF THE PERFORMANCE OF MULTI-STORY REINFORCED CONCRETE BUILDINGS USING CLOUD COMPUTING

Optimizing the performance of multi-story reinforced concrete buildings is crucial to ensure their structural integrity, safety, and efficiency. Traditionally, this optimization process involves extensive computational simulations and analysis, which can be time-consuming and resource-intensive. This abstract presents an approach to optimize the performance of multi-story reinforced concrete buildings using cloud computing. The proposed approach leverages the power of cloud computing, which provides a scalable and cost-effective solution for handling largescale computational tasks. By harnessing the computational resources of cloud platforms, the optimization process can be expedited, allowing for the exploration of a wider range of design variables and performance criteria. To implement the optimization process, a comprehensive set of design variables and performance criteria are considered. Design variables may include structural dimensions, reinforcement ratios, and material properties, while performance criteria encompass factors such as structural strength, stiffness, and serviceability requirements. These variables and criteria are formulated into mathematical models that capture the behaviour of the multi-story reinforced concrete building. Through cloud computing, the optimization process involves iteratively evaluating different combinations of design variables and assessing their impact on performance criteria. This is achieved by running computational simulations and analyses on the cloud infrastructure, utilizing parallel processing capabilities to expedite the calculations. Advanced optimization algorithms, such as genetic algorithms, particle swarm optimization, or evolutionary algorithms, are employed to efficiently explore the design space and identify optimal solutions.