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Archive

Volume 1, Issue 2, June 2026

  • Research Article
    Issue: Volume 1, Issue 2, June 2026
    Pages: 88-101
    Received: 23 February 2026
    Accepted: 4 March 2026
    Published: 16 March 2026
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    Abstract: Background: Polar vortex splits, a subset of sudden stratospheric warming, can drive extreme midlatitude cold outbreaks by coupling stratospheric disruptions downward to the troposphere. However, surface impacts vary widely, with some events producing severe, persistent cold and others remaining benign, highlighting the need to distinguish underlyi... Show More
  • Research Article
    Issue: Volume 1, Issue 2, June 2026
    Pages: 102-107
    Received: 26 February 2026
    Accepted: 9 March 2026
    Published: 19 March 2026
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    Abstract: This article provides a comprehensive theoretical basis for determining the structural and technological parameters of a roller-type working body, which is specifically designed to loosen the crust that forms on the inter-row soil of cotton crops. The formation of a dense soil crust in cotton fields negatively affects the emergence and growth of se... Show More
  • Research Article
    Issue: Volume 1, Issue 2, June 2026
    Pages: 108-117
    Received: 13 October 2025
    Accepted: 4 February 2026
    Published: 23 April 2026
    DOI: 10.11648/j.sdp.20260102.13
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    Abstract: To use the hole diameter variation method using the partial stress release method by parallel drilling in determining the initial plane stress state of the rock mass, the stress state change surrounding the main measuring hole by parallel drilling is derived and the results are verified by numerical simulations. In the partial stress relief method ... Show More
  • Methodology Article
    Issue: Volume 1, Issue 2, June 2026
    Pages: 118-130
    Received: 4 April 2026
    Accepted: 16 April 2026
    Published: 24 April 2026
    DOI: 10.11648/j.sdp.20260102.14
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    Abstract: Recently, physics-informed neural networks (PINNs) have become an encouraging computational approach to solving differential equations through the use of an explicit encoding of physical laws into the learning step of neural networks. The paper carries out a detailed comparison and contrast of PINNs with two well-established numerical approaches, i... Show More