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Dynamic Performance Evaluation of Machine Foundations Using Multi-approach Investigation
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Dynamic Performance Evaluation of Machine Foundations Using Multi-approach Investigation
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Dynamic Performance Evaluation of Machine Foundations Using Multi-approach Investigation
Dynamic Performance Evaluation of Machine Foundations Using Multi-approach Investigation
Journal Article

Dynamic Performance Evaluation of Machine Foundations Using Multi-approach Investigation

2024
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Overview
The current investigation examines the influence of footing shape, the base area of footing ( A ), the mass of footing-machine assembly ( m ), and eccentric force settings ( m e e ) on the dynamic response and performance of machine foundation systems. Five different footing configurations are employed to perform field block vibration tests involving three square, one circular and one rectangular footing. The experiments are performed at the geotechnical field laboratory of IIT Kanpur, India (N26°30′59.0892″, E80°13′51.6888″). The accuracy and reliability of the experimental results are endorsed by the results obtained from the mass-spring-dashpot (MSD) analysis. In addition, an artificial neural network (ANN) model is created to anticipate the dynamic behaviour of the soil-foundation system. A thorough parametric study demonstrates the efficacy of the developed ANN model. It is revealed from the investigation that the stiffness ( k ) and the damping ratio ( D ) of the soil for square foundations increase by 7% and 3%, respectively, with a 40% increase in A . Similarly, the circular foundation exhibits 7 and 3% higher k and 4 and 3% higher D than those obtained for square and rectangular foundations, respectively. For square foundations, a 24% enhancement in m leads to a 42 and 4% increase in k and D , respectively. In contrast, for circular and rectangular foundations, a 13% increase in m results in a 27 and 19% increase in k and D , respectively. In this study, experimental testing, analytical validation, and ANN modelling provide insight into the response of machine foundations under various operating conditions. The results of this study can be utilized to optimize the design of machine foundations.