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BSA Flow Software Installation and User's Guide - CSI

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Corrected particle<br />

Max<br />

d e ( Di<br />

)<br />

C ( Di<br />

) =<br />

d ( D )<br />

e<br />

i<br />

where d is the effective probe volume diameter for size class D <strong>and</strong> where<br />

e<br />

Max<br />

the maximum measured particle size D is the last non-em pty size bin.<br />

d e<br />

is calculated as for the flux <strong>and</strong> concentration algorithm:<br />

3 2<br />

d e(<br />

Di<br />

) = Li<br />

2<br />

where<br />

L is the mean burst length for each size class D .<br />

2<br />

i<br />

2<br />

Li i<br />

= Aln(<br />

D ) + B<br />

The corrected particle number for the size class D becomes:<br />

cor<br />

number n i = ni<br />

× C(<br />

Di<br />

) where ni<br />

is the measured number of particles per size.<br />

The corrected mean diameters can be written as follow:<br />

10 =<br />

Ni<br />

cor<br />

∑ ni<br />

Di<br />

i=<br />

1<br />

Ni<br />

cor<br />

∑ ni<br />

i=<br />

1<br />

D<br />

,<br />

D<br />

Ni<br />

cor 3<br />

∑ ni<br />

Di<br />

i=<br />

1<br />

32 = <strong>and</strong> so forth.<br />

Ni<br />

cor 2<br />

∑ ni<br />

Di<br />

i=<br />

1<br />

Note As described in chapter 7.11.2, the correction is by design implemented in<br />

the flux <strong>and</strong> concentration algorithms.<br />

7.12 Spectral analysis (two-time statistics)<br />

Definition of correlation <strong>and</strong> covariance<br />

As opposed to moment-calculation, spectral-analysis investigates the<br />

relations between samples <strong>and</strong> the timing of events. Since all of these<br />

calculations are based on pairs of values, this is sometimes referred to as<br />

two-time statistics.<br />

Consider an ideal experiment producing continuous measurements<br />

represented as time functions u(t) <strong>and</strong> v(t):<br />

[ ]<br />

i<br />

ut (), vt (), K t∈ 0 , T<br />

(7-53)<br />

In the context of LDA-measurements, u(t) <strong>and</strong> v(t) will normally be<br />

velocities, but may in principle represent temperature, pressure, or something<br />

else.<br />

Correlation The exact definition of the correlation function Ruv(t1,t2) is:<br />

{ }<br />

*<br />

( , ) ( ) ( )<br />

R t t ≡ E u t ⋅ v t<br />

(7-54)<br />

uv 1 2 1 2<br />

-where E{…} is the notation for the expectation value (mean).<br />

<strong>BSA</strong> <strong>Flow</strong> <strong>Software</strong>:Reference guide 7-121<br />

i<br />

i<br />

i

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