Machine learning-supported inverse measurement procedure for broadband, temperature dependent piezoelectric material parameters

Open Access

Table 1

Intervals for the material parameters to generate synthetic training data.

Param.	$c_{11}^{E}$ $c_{11}^{\mathrm{E} }$	$c_{12}^{E}$ $c_{12}^{\mathrm{E} }$	$c_{13}^{E}$ $c_{13}^{\mathrm{E} }$	$c_{33}^{E}$ $c_{33}^{\mathrm{E} }$	$c_{44}^{E}$ $c_{44}^{\mathrm{E} }$	$ε_{11}^{S}$ $\varepsilon _{11}^{\mathrm{S} }$	$ε_{33}^{S}$ $\varepsilon _{33}^{\mathrm{S} }$
a	110	60	60	110	18	3	4
b	165	150	100	140	30	12	8
Unit	GPa	GPa	GPa	GPa	GPa	nF m⁻¹	nF m⁻¹
Param.	e₁₅	e₃₁	e₃₃	α_M	α_K	ρ
a								6	−1	8	0.2	0.01	7600
b							20	−7.5	20	150	1	7850
Unit						C m⁻²	C m⁻²	C m⁻²	ms⁻¹	ns	kg m⁻³

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