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Practical implications of the blade analysis

Practical implications of the blade analysis

Here we give some practical conclusions based on the results of blade work analysis made in the previous Newsletters. Nearly 200 variables were derived using previous definitions (RBN 2018/07) on a large data set measured with the BioRow system (n=28252, more than 5 million numbers altogether), and all variables were tested for their correlation with Blade Drag Factor DFbl and blade efficiency Ebl. The Pearson correlations were next ranked by strength. Starting with the strongest correlations, the following practical conclusions can be made.

1.                Average normal blade velocity in the water (slippage) has the highest correlations with both DFbl (r=-0.80) and Ebl (r=-0.82), which is quite a trivial conclusion: the faster the blade slippage in the water – the less efficient its work.

2.                The drive time with positive blade slippage velocity was divided into three equal periods, and the amount of wasted power was compared in each period: Pw1 is the power wasted during the drive beginning, Pw2 – in the middle, and Pw3 – at the end of the drive. We found that Pw1 had negative correlations with both DFbl (r=-0.57) and Ebl (r=-0.26), but Pw3 had positive correlations with DFbl (r=0.52) and Ebl (r=0.32). Interpretation: blade slippage during the beginning of the drive is the most harmful for blade efficiency, while slippage at the end of the drive is the most forgiving.

3.                To make the beginning of the drive efficient, the blade must be submersed into the water and force increased quickly after the catch, which was confirmed by negative correlation of DFbl with catch slip measured with vertical oar angle (r=-0.21, RBN 2009/10) and force “slip” (r=-0.17, RBN 2017/03): the shorter the slips, the higher blade efficiency. It is especially important to create a high force as early as possible when the blade is slipping: high positive correlations of blade force at this moment were found with both DFbl (r=0.42) and Ebl (r=0.25).

4.                If force F and power P applied by a rower were analysed similarly to Pw above, then emphasis on the middle of the drive F2 and P2 has both shown the highest negative correlation with DFbl (r=-0.35) and Ebl (r=-0.39). This means: a more even distribution of a rower’s effort during the drive (i.e. more rectangular force curve) helps to increase the blade efficiency. This was confirmed by positive correlation of average/maximal force ratio with DFbl (r=0.22).

5.                Surprisingly, a gearing ratio (actual outboard / inboard) had negative correlations with both DFbl (r=-0.45) and Ebl (r=-0.06): the lighter the gearing - the higher the blade DF, which contradicts our previous ideas and should be analysed further.

No significant correlations of DFbl and Ebl were found with the blade specific impulse (RBN 2013/11-12), Catch and Rowing Style factors and amount of force and power applied by rower.

The above findings can be illustrated by a case study based on the data of a quad at 37.5 spm (Fig.1, Tab.1).

The seat 3 rower (the most experienced and highly ranked one) inserts the blade into the water much quicker than other crew members (1), which is accompanied with fast force increase (2). Visually, the blade work of this rower looks like a solid, but not high front splash (Fig.1.f), sort of wall of water in front of the blade. The seat 3 rower had double the DFbl and a blade slip distance 40% less (Table 1) then the stroke rower, who had longer catch slip and slower force gradient. The difference of 4.7% in the blade efficiency between the 3 seat and stroke rower equates to 7s faster time in 2000m race.

©2018 Dr. Valery Kleshnev www.biorow.com