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<p>This paper presents a physics-guided stepwise tomography framework that decouples the ill-posed tomography of temperature and concentration into three measurement- and prior-guided stages. By sequentially embedding two-line thermometry, projection matrix, and structural similarity, the framework first reconstructs a preliminary temperature field via a physics-data collaborative network, then employs it as a structural prior to guide iterative concentration inversion, and finally restores spatial details through a joint superresolution network, achieving high-fidelity reconstruction under a sparse optical layout with 40 optical paths and 2 absorption lines. Comprehensive validation in three cases supports improved robustness in the tested cases. In Case A, an in-distribution LES test dataset achieved dataset-averaged temperature/concentration mean relative errors (<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(E_T/E_X\)</EquationSource> </InlineEquation>) of 1.35%/2.51% and temperature/concentration structural similarity indices (<InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(SSIM_T/SSIM_X\)</EquationSource> </InlineEquation>) of 0.991/0.989. In Case B, an out-of-distribution LES flame with modified inlet conditions showed section-dependent performance, with representative noise-free longitudinal sections giving <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(E_T=4.54\%-7.67\%\)</EquationSource> </InlineEquation>, <InlineEquation ID="IEq4"> <EquationSource Format="TEX">\(E_X=5.55\%-14.11\%\)</EquationSource> </InlineEquation>, <InlineEquation ID="IEq5"> <EquationSource Format="TEX">\(SSIM_T=0.742-0.974\)</EquationSource> </InlineEquation>, and <InlineEquation ID="IEq6"> <EquationSource Format="TEX">\(SSIM_X=0.763-0.965\)</EquationSource> </InlineEquation>. In Case C, an experimentally derived axisymmetric flame case constructed from Sandia Flame D measurements further showed that the main jet, reaction-zone, and diffusion-region structures can still be captured; representative cross-sections achieved <InlineEquation ID="IEq7"> <EquationSource Format="TEX">\(E_T&lt;5\%\)</EquationSource> </InlineEquation>, <InlineEquation ID="IEq8"> <EquationSource Format="TEX">\(E_X&lt;8\%\)</EquationSource> </InlineEquation>, <InlineEquation ID="IEq9"> <EquationSource Format="TEX">\(SSIM_T&gt;0.98\)</EquationSource> </InlineEquation>, and <InlineEquation ID="IEq10"> <EquationSource Format="TEX">\(SSIM_X&gt;0.96\)</EquationSource> </InlineEquation>. This strategy provides a promising route toward real-time combustion diagnostics in geometrically complex environments with restricted optical access.</p>

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Physics-guided stepwise tomography framework for high-precision reconstruction of temperature and concentration

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  • 出版模式：

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  • 发表日期：

    2026年7月28日

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  • Yaojie Jia,
  • Dongdong Pang,
  • Jiarui Lei,
  • Peng Liu,
  • Xin Zhou

摘要

This paper presents a physics-guided stepwise tomography framework that decouples the ill-posed tomography of temperature and concentration into three measurement- and prior-guided stages. By sequentially embedding two-line thermometry, projection matrix, and structural similarity, the framework first reconstructs a preliminary temperature field via a physics-data collaborative network, then employs it as a structural prior to guide iterative concentration inversion, and finally restores spatial details through a joint superresolution network, achieving high-fidelity reconstruction under a sparse optical layout with 40 optical paths and 2 absorption lines. Comprehensive validation in three cases supports improved robustness in the tested cases. In Case A, an in-distribution LES test dataset achieved dataset-averaged temperature/concentration mean relative errors ( \(E_T/E_X\) ) of 1.35%/2.51% and temperature/concentration structural similarity indices ( \(SSIM_T/SSIM_X\) ) of 0.991/0.989. In Case B, an out-of-distribution LES flame with modified inlet conditions showed section-dependent performance, with representative noise-free longitudinal sections giving \(E_T=4.54\%-7.67\%\) , \(E_X=5.55\%-14.11\%\) , \(SSIM_T=0.742-0.974\) , and \(SSIM_X=0.763-0.965\) . In Case C, an experimentally derived axisymmetric flame case constructed from Sandia Flame D measurements further showed that the main jet, reaction-zone, and diffusion-region structures can still be captured; representative cross-sections achieved \(E_T<5\%\) , \(E_X<8\%\) , \(SSIM_T>0.98\) , and \(SSIM_X>0.96\) . This strategy provides a promising route toward real-time combustion diagnostics in geometrically complex environments with restricted optical access.