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In this report, we demonstrate a procedure for the construction of multivariate models based on frequency domain 2D NMR data where the loadings can be visualized as highly informative 2D loading spectra.
In order to predict the missing loading spectra a relationship between the operating conditions and the corresponding loading spectra must be known.
Besides the simulation of these processes the dynamic models capable of predicting loading spectra are presented.
To avoid these problems we have developed a new approach for predicting the loading spectra.
Although the loading spectra are completely uncorrelated, they cannot be directly associated with a single chemical compound always.
Retention time recalibration using iRT-peptide [11] characteristic peaks was done automatically when loading spectra in SpectroDive™.
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The FALSTAFF loading spectrum was applied.
Programmed loading spectrum is shown in Table 2.
Damage values were calculated and then accumulated over peak valley events of a block loading spectrum.
Also a method of generating the ship fatigue loading spectrum is demonstrated based on the design wave approach.
Two different VA loading spectrums, generated using traffic data and influence lines for highway bridge girders, were used.
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