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Soil disturbance cross-sectional model.
Published 2025“…Under these conditions, the maximum drag reduction rate reaches 16.66%, and the soil disturbance area increases by up to 22.48%, significantly enhancing the drag reduction effect and soil fragmentation efficiency during subsoiling operations. …”
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Test plan table.
Published 2025“…Under these conditions, the maximum drag reduction rate reaches 16.66%, and the soil disturbance area increases by up to 22.48%, significantly enhancing the drag reduction effect and soil fragmentation efficiency during subsoiling operations. …”
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Gas jet subsoiling model.
Published 2025“…Under these conditions, the maximum drag reduction rate reaches 16.66%, and the soil disturbance area increases by up to 22.48%, significantly enhancing the drag reduction effect and soil fragmentation efficiency during subsoiling operations. …”
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Schematic diagram of the airflow passage.
Published 2025“…Under these conditions, the maximum drag reduction rate reaches 16.66%, and the soil disturbance area increases by up to 22.48%, significantly enhancing the drag reduction effect and soil fragmentation efficiency during subsoiling operations. …”
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Variation in soil penetration resistance.
Published 2025“…Under these conditions, the maximum drag reduction rate reaches 16.66%, and the soil disturbance area increases by up to 22.48%, significantly enhancing the drag reduction effect and soil fragmentation efficiency during subsoiling operations. …”
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Supersonic gas jet subsoiler experiment.
Published 2025“…Under these conditions, the maximum drag reduction rate reaches 16.66%, and the soil disturbance area increases by up to 22.48%, significantly enhancing the drag reduction effect and soil fragmentation efficiency during subsoiling operations. …”
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Evaluation results.
Published 2024“…Evaluation metrics including signal-to-noise ratio (SNR), linearity of attenuation profiles, root mean square error (RMSE), and area under the curve (AUC) were employed to assess the energy and material-density images with and without metal inserts. Results show decreased metal artefacts and a better signal-to-noise ratio (up to 25%) with increased energy bins as compared to reference data. …”
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Dataset with steel insert.
Published 2024“…Evaluation metrics including signal-to-noise ratio (SNR), linearity of attenuation profiles, root mean square error (RMSE), and area under the curve (AUC) were employed to assess the energy and material-density images with and without metal inserts. Results show decreased metal artefacts and a better signal-to-noise ratio (up to 25%) with increased energy bins as compared to reference data. …”
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Reference dataset.
Published 2024“…Evaluation metrics including signal-to-noise ratio (SNR), linearity of attenuation profiles, root mean square error (RMSE), and area under the curve (AUC) were employed to assess the energy and material-density images with and without metal inserts. Results show decreased metal artefacts and a better signal-to-noise ratio (up to 25%) with increased energy bins as compared to reference data. …”