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Official Journal of the Japan Wood Research Society

Table 1 Relationships between the calculated strains (\({\varepsilon _x}\), \({\varepsilon _y}\), \({\gamma _{xy}}\)) and the artificially imposed strains (\({\varepsilon _{\text{n}}}\), \({\gamma _{\text{n}}}\))

From: Strain analysis near the cutting edge in orthogonal cutting of hinoki (Chamaecyparis obtusa) using a digital image correlation method

 

Artificially imposed strain \({\varepsilon _{\text{n}}}\), \({\gamma _{\text{n}}}\) (%)

Mean

\(- 0.94\)

\(- 0.83\)

\(- 1.04\)

\(- 5.00\)

\(- 10.00\)

\(- 15.00\)

\(- 20.00\)

\(- 25.00\)

Mean ± SD (%) (n = 25)

 \(\overline {{{\varepsilon _x}}} \pm {\text{SD}}\_{\varepsilon _x}\)

\(- 0.90 \pm 0.21\)

  

\(- 4.96 \pm 0.44\)

\(- 10.02 \pm 1.32\)

\(- 14.95 \pm 2.25\)

\(- 19.35 \pm 3.39\)

\(- 24.44 \pm 4.99\)

 

 \(\overline {{{\varepsilon _y}}} \pm {\text{SD}}\_{\varepsilon _y}\)

 

\(- 0.78 \pm 0.17\)

 

\(- 5.06 \pm 0.52\)

\(- 10.10 \pm 1.14\)

\(- 14.93 \pm 1.90\)

\(- 20.08 \pm 2.92\)

  

 \(\overline {{{\gamma _{xy}}}} \pm {\text{SD}}\_{\gamma _{xy}}\)

  

\(- 1.00 \pm 0.34\)

\(- 5.07 \pm 0.91\)

\(- 10.12 \pm 1.72\)

\(- 15.17 \pm 2.70\)

\(- 20.22 \pm 3.70\)

\(- 25.37 \pm 5.10\)

 

Coefficient of variation (%)

 \({\text{CV}}\_{\varepsilon _x}={\text{SD}}\_{\varepsilon _x}/\overline {{{\varepsilon _x}}} \times 100\)

\(- 24\)

  

\(- 9\)

\(- 13\)

\(- 15\)

\(- 18\)

\(- 20\)

\(- 16\)

 \({\text{CV}}\_{\varepsilon _y}={\text{SD}}\_{\varepsilon _y}/\overline {{{\varepsilon _y}}} \times 100\)

 

\(- 20\)

 

\(- 10\)

\(- 11\)

\(- 13\)

\(- 15\)

 

\(- 14\)

 \({\text{CV}}\_{\gamma _{xy}}={\text{SD}}\_{\gamma _{xy}}/\overline {{{\gamma _{xy}}}} \times 100\)

  

\(- 34\)

\(- 18\)

\(- 17\)

\(- 18\)

\(- 18\)

\(- 20\)

− 21

Error rate (%)

 \({\text{ER}}\_{\varepsilon _x}=(\overline {{{\varepsilon _x}}} - {\varepsilon _{\text{n}}})/{\text{~}}{\varepsilon _{\text{n}}} \times 100\)

\(- 4.00\)

  

\(- 0.81\)

\(0.16\)

\(- 0.33\)

\(- 3.27\)

\(- 2.23\)

\(- 1.75\)

 \({\text{ER}}\_{\varepsilon _y}=(\overline {{{\varepsilon _y}}} - {\varepsilon _{\text{n}}})/{\text{~}}{\varepsilon _{\text{n}}} \times 100\)

 

\(- 6.62\)

 

\(1.19\)

\(0.97\)

\(- 0.50\)

\(0.41\)

 

\(- 0.91\)

 \({\text{ER}}\_{\gamma _{xy}}=(\overline {{{\gamma _{xy}}}} - {\gamma _{\text{n}}})/{\text{~}}{\gamma _{\text{n}}} \times 100\)

  

\(- 3.99\)

\(1.53\)

\(1.17\)

\(1.10\)

\(1.12\)

\(1.48\)

\(0.40\)