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Calibration design evaluations through computational analysis and investigation of a six-component wind tunnel balance

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Abstract

The calibration and validation of a low-cost external six-component wind tunnel balance (WTB), designed based on Stewart platform configuration, are reported using four different calibration designs. The balance can be easily customised to measure the aerodynamics loads acting on half-wing and drone models in a wind tunnel. Four calibration designs—central composite design (CCD), Box–Behnken design (BBD), BBD with two active filters and decoupling (BBD-2A), and the modern design of experiments (MDOE)—were thoroughly investigated using different computational and statistical techniques to find the right candidate through analysis of variance (ANOVA). A novel approach employed to find reduced model for each loading component in the four calibration designs is described. Systematic validation of the reduced models is performed by benchmarking them against the standard second-order models. These reduced models will play a vital role during actual calibration and measurements to lower the final uncertainty in the measured force and moment components and reduce the time and cost involved in calibrating a WTB.

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Acknowledgements

The last author thanks the Indian Institute of Technology (IIT) Tirupati for funding this research through a New Faculty Initiation Grant (NFIG).

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Authors and Affiliations

  1. Department of Mechanical Engineering, Indian Institute of Technology Tirupati, Tirupati, Andhra Pradesh, India

    Rohit Kumar, B N Ravi Srivatsa & Balaji Subramanian

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  1. Rohit Kumar
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  2. B N Ravi Srivatsa
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  3. Balaji Subramanian
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Correspondence to Balaji Subramanian.

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A Appendix

A Appendix

Figs. 7, 8, 9, and 10.

Fig. 7
figure 7

Two-factor load plots for CCD

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Fig. 8
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Two-factor load plots for BBD

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Fig. 9
figure 9

Two-factor load plots for BBD with two active filters and decoupling

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Fig. 10
figure 10

Two-factor load plots for MDOE

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Tables 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, and 13.

Table 3 The maximum deviations and standard deviations of the residual lack-of-fit errors in second- and third-order models with the four calibration designs
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Table 4 Variable j and k can take up different combinations, for easy understanding they have been mapped to a new variable m which is used in Table 5
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Table 5 The list of significant coefficients identified as parameters of the reduced models in the four calibration designs
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Table 6 For CCD design, the reduced models validated at six different factor levels by benchmarking them with second-order models
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Table 7 For BBD design, the reduced models validated at six different factor levels by benchmarking them with second-order models
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Table 8 For BBD-2A design, the reduced models validated at six different factor levels by benchmarking them with second-order models
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Table 9 For MDOE design, the reduced models validated at six different factor levels by benchmarked them with second-order models
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Table 10 For CCD design, validation of residual models at factor levels 0.05, 0.55, and 0.95, by benchmarking them against their second-order model counterparts
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Table 11 For BBD design, validation of residual models at factor levels 0.05, 0.55, and 0.95, by benchmarking them against their second-order model counterparts
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Table 12 For BBD-2A design, validation of residual models at factor levels 0.05, 0.55, and 0.95, by benchmarking them against their second-order model counterparts
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Table 13 For MDOE design, validation of residual models at factor levels 0.05, 0.55, and 0.95, by benchmarking them against their second-order model counterparts
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Kumar, R., Srivatsa, B.N.R. & Subramanian, B. Calibration design evaluations through computational analysis and investigation of a six-component wind tunnel balance. ISSS J Micro Smart Syst 10, 7–31 (2021). https://doi.org/10.1007/s41683-021-00066-5

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  • DOI: https://doi.org/10.1007/s41683-021-00066-5

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