A methodology for quality control evaluation for laminated composites manufacturing

Morais, David T.S.; Ávila, Antônio F.

doi:10.1590/s1678-58782005000300006

Cited by 4 publications

(3 citation statements)

References 10 publications

(8 reference statements)

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“…In this section, we apply our modeling framework to active microrheology in disordered polymeric systems and other soft materials. Active microrheology can be used for medical diagnostics, such as monitoring the progression of a cancer 52 , and also for quality control during material fabrication 53,54 . Although previous studies have shown that active microrheology can be used to probe the properties of small systems 47 , it has remained unclear what this technique can learn about heterogeneous materials.…”

Section: Resultsmentioning

confidence: 99%

“…This strategy can allow the sensor to effectively average the material constant over a volume that grows with the spatial resolution of the sensor. Finally, we use our theoretical framework to bound the precision of mechanosensing in a biopolymer network, a sensory process that regulates cellular behavior in decisive ways 28,[49][50][51] and is used for medical diagnostics and material fabrication [52][53][54] .…”

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confidence: 99%

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Physical limits to sensing material properties

et al. 2020

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All materials respond heterogeneously at small scales, which limits what a sensor can learn. Although previous studies have characterized measurement noise arising from thermal fluctuations, the limits imposed by structural heterogeneity have remained unclear. In this paper, we find that the least fractional uncertainty with which a sensor can determine a material constant λ0 of an elastic medium is approximately $$\delta {\lambda }_{0}/{\lambda }_{0} \sim ({\Delta }_{\lambda }^{1/2}/{\lambda }_{0}){(d/a)}^{D/2}{(\xi /a)}^{D/2}$$ δ λ 0 / λ 0 ~ ( Δ λ 1 / 2 / λ 0 ) ( d / a ) D / 2 ( ξ / a ) D / 2 for a ≫ d ≫ ξ, $${\lambda }_{0}\gg {\Delta }_{\lambda }^{1/2}$$ λ 0 ≫ Δ λ 1 / 2 , and D > 1, where a is the size of the sensor, d is its spatial resolution, ξ is the correlation length of fluctuations in λ0, Δλ is the local variability of λ0, and D is the dimension of the medium. Our results reveal how one can construct devices capable of sensing near these limits, e.g. for medical diagnostics. We use our theoretical framework to estimate the limits of mechanosensing in a biopolymer network, a sensory process involved in cellular behavior, medical diagnostics, and material fabrication.

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Section: Resultsmentioning

confidence: 99%

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confidence: 99%

Physical limits to sensing material properties

et al. 2020

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“…By far, hand layup persists as the method by which a majority of all advanced composite structure is made [18]. The popularity is due to its features of low cost, flexibility and capability of making a wide variety of complex geometric shapes.…”

Section: Approaches To Planning and Automating The Layup Processmentioning

confidence: 99%