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<p>The integration of computational simulations and experimental validation, particularly through photo elasticity, is a challenging approach. This investigation explores the application of experimental topology optimization to the bell crank lever, with the goal of minimizing its mass while ensuring structural integrity and performance. An iterative process is employed to validate the results using computational method, and also, investigations are conducted to understand variations in the outcomes. Both computational and experimental methods yield significant reductions in mass, with computational methods achieving a reduction of 35.45% and experimental methods reaching 48.45%. It has been observed that the differences in mass reduction between computational and experimental methods in bell crank lever optimization may stem from discrepancies in model complexity, material properties, boundary conditions, numerical errors, experimental uncertainties, model validation, and optimization algorithms. Integrating and validating both approaches are crucial for reliable results. A systematic comparison of principal stress values further validates these methods, highlighting their efficacy in enhancing performance while maintaining structural integrity.</p>

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Experiential and Computational Validation of Bell Crank Lever Topology Optimization

  • 期刊论文

  • 发表日期：

    2025年7月1日

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  • B. G. Avilasha,
  • T. Abhinav,
  • B. T. Ramesh,
  • Ashok R. Banagar

摘要

The integration of computational simulations and experimental validation, particularly through photo elasticity, is a challenging approach. This investigation explores the application of experimental topology optimization to the bell crank lever, with the goal of minimizing its mass while ensuring structural integrity and performance. An iterative process is employed to validate the results using computational method, and also, investigations are conducted to understand variations in the outcomes. Both computational and experimental methods yield significant reductions in mass, with computational methods achieving a reduction of 35.45% and experimental methods reaching 48.45%. It has been observed that the differences in mass reduction between computational and experimental methods in bell crank lever optimization may stem from discrepancies in model complexity, material properties, boundary conditions, numerical errors, experimental uncertainties, model validation, and optimization algorithms. Integrating and validating both approaches are crucial for reliable results. A systematic comparison of principal stress values further validates these methods, highlighting their efficacy in enhancing performance while maintaining structural integrity.