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in most of the data analysis cases, the “reducing factor” n which lowers the number m...

in most of the data analysis cases, the “reducing factor” n which lowers the number m of dimensional variables to m-n dimensionless groups, exactly equals the number of relevant dimensions (M, L, T). In one case this was not so. Explain in words why this situation happens.

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In most data analysis cases, the reducing factor n lowers thr number m of dimensional variables to m-n dimensionless groups, exactly ewuals the number of relevant dimensions (M,L,T), but only in Fluid mechanics this was not happen, there are four relevant dimensions are used (M,L,T, )... = temperature.

The M is replaced by F (Force).

So in fluid mechanics, mainly four dimensions are used (F, L,T, ), because in fluid mechanics, force on the immersed body cause this extra dimension to add.

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