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First, we used PCA to measure the main modes of boundary motion.
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The dominant modes of boundaries 1 and 3 are shown in Fig. 9.
Dominant oscillation modes of boundaries 1 and 3 are shown in Fig. 7, respectively.
Open image in new window Fig. 10 SSSR boundary of scenario c Open image in new window Fig. 11 Dominant oscillation modes of SSSR boundary (Scenario c) 4) Comparison of SSSR boundary .
Open image in new window Fig. 6 SSSR boundary of scenario a Open image in new window Fig. 7 Dominant oscillation modes of SSSR boundary (Scenario a) 2) Scenario b .
Open image in new window Fig. 9 Dominant oscillation modes of SSSR boundary (Scenario b) 3) Scenario c . Scenario c.
The correction solutions proposed here use the normal modes of the "boundary structure".
Furthermore, the effects of factors, such as floor span, occupant stride length, higher modes of vibration, boundary conditions and peak acceleration response, on the proposed spectrum have been investigated and a modification measure for each factor is suggested.
With this analysis tool we can tackle the question of how nanoridges affect the modes of cell boundary motion.
A mapping relationship between modes on surfaces of boundary and hologram is analytically derived by adopting the modes as FS in spherical coordinates.
As it follows from analysis of x3-x2-CDA modes for boundary 5 0 and 0 5 nanocomposites, unique As4S4-related trapping sites are rather o-Ps traps with τ int = 0.875 ns, which can be ascribed (due to bulk positron lifetime τ b ≈ 0.271 ns essentially increased in respect to τ b ≈ 0.223 ns proper for realgar α-As4S4 [19]) to interfacial TJ in a random network of loose-packed As4S4 NP (see Fig. 1a).
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