22nd Mediterranean Conference on Control and Automation 2014
DOI: 10.1109/med.2014.6961422
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PSO algorithm based thermal contact resistance estimation for variable force hand/object interaction

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Cited by 3 publications
(8 citation statements)
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“…σ % σ skin . With this assumption and substitution of the range of skin properties indicated in Table 1 into Equations (5) and (6), Figure 3(a) shows that PM model predictions are in remarkably good agreement with data for finger contact with an aluminum plate from Maamir et al [12]. This agreement is not surprising since Equation (6) was obtained by fitting data on comparably soft materials and metal surface interfaces where k 2 ) k 1 .This notion, however, starts to be questionable for marble (k marble ¼ 2.9 Wm −1 K −1 ) and is not valid for wood (k wood ¼ 0.23-0.4 Wm −1 K −1 [38] that is comparable to k skin ¼ -0.37 Wm −1 K −1 ).…”
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confidence: 66%
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“…σ % σ skin . With this assumption and substitution of the range of skin properties indicated in Table 1 into Equations (5) and (6), Figure 3(a) shows that PM model predictions are in remarkably good agreement with data for finger contact with an aluminum plate from Maamir et al [12]. This agreement is not surprising since Equation (6) was obtained by fitting data on comparably soft materials and metal surface interfaces where k 2 ) k 1 .This notion, however, starts to be questionable for marble (k marble ¼ 2.9 Wm −1 K −1 ) and is not valid for wood (k wood ¼ 0.23-0.4 Wm −1 K −1 [38] that is comparable to k skin ¼ -0.37 Wm −1 K −1 ).…”
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confidence: 66%
“…The most commonly utilized model for predicting R c at finger-object interfaces [7,9,[12][13][14][15][16][17][18][19][20] was developed in the 1960s by Cooper, Mikic and Yovanovich (CMY) to predict thermal contact resistance between two contacting materials (subscript 1 and 2) with random surface roughness that are much harder CONTACT Konrad Rykaczewski konradr@asu.edu Supplemental data for this article can be accessed here. TEMPERATURE 2019, VOL.…”
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confidence: 99%
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