IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i14p4957-d857281.html
   My bibliography  Save this article

Using Spatial Data Science in Energy-Related Modeling of Terraforming the Martian Atmosphere

Author

Listed:
  • Piotr Pałka

    (Faculty of Electronics and Information Technology, Warsaw University of Technology, Nowowiejska 15/19, 00-665 Warsaw, Poland)

  • Robert Olszewski

    (Faculty of Geodesy and Cartography, Warsaw University of Technology, Pl. Politechniki 1, 00-661 Warsaw, Poland)

  • Agnieszka Wendland

    (Faculty of Geodesy and Cartography, Warsaw University of Technology, Pl. Politechniki 1, 00-661 Warsaw, Poland)

Abstract

This paper proposes a methodology for numerical modeling of terraforming Mars’ atmosphere using high-energy asteroid impact and greenhouse gas production processes. The developed simulation model uses a spatial data science approach to analyze the Global Climate Model of Mars and cellular automata to model the changes in Mars’ atmospheric parameters. The developed model allows estimating the energy required to raise the planet’s temperature by sixty degrees using different variations of the terraforming process. Using a data science approach for spatial big data analysis has enabled successful numerical simulations of global and local atmospheric changes on Mars and an analysis of the energy potential required for this process.

Suggested Citation

  • Piotr Pałka & Robert Olszewski & Agnieszka Wendland, 2022. "Using Spatial Data Science in Energy-Related Modeling of Terraforming the Martian Atmosphere," Energies, MDPI, vol. 15(14), pages 1-24, July.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:14:p:4957-:d:857281
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/14/4957/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/14/4957/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhang, Tao & Li, Yiteng & Chen, Yin & Feng, Xiaoyu & Zhu, Xingyu & Chen, Zhangxing & Yao, Jun & Zheng, Yongchun & Cai, Jianchao & Song, Hongqing & Sun, Shuyu, 2021. "Review on space energy," Applied Energy, Elsevier, vol. 292(C).
    2. Tao Zhang & Shuyu Sun, 2021. "Thermodynamics-Informed Neural Network (TINN) for Phase Equilibrium Calculations Considering Capillary Pressure," Energies, MDPI, vol. 14(22), pages 1-16, November.
    3. Delgado-Bonal, Alfonso & Martín-Torres, F. Javier & Vázquez-Martín, Sandra & Zorzano, María-Paz, 2016. "Solar and wind exergy potentials for Mars," Energy, Elsevier, vol. 102(C), pages 550-558.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hu, Dinghua & Li, Mengmeng & Li, Qiang, 2021. "A solar thermal storage power generation system based on lunar in-situ resources utilization: modeling and analysis," Energy, Elsevier, vol. 223(C).
    2. Xiao, Xu & Zhang, Zhuojun & Yu, Wentao & Shang, Wenxu & Ma, Yanyi & Tan, Peng, 2022. "Achieving a high-specific-energy lithium-carbon dioxide battery by implementing a bi-side-diffusion structure," Applied Energy, Elsevier, vol. 328(C).
    3. Sun, Yinong & Frew, Bethany & Dalvi, Sourabh & Dhulipala, Surya C., 2022. "Insights into methodologies and operational details of resource adequacy assessment: A case study with application to a broader flexibility framework," Applied Energy, Elsevier, vol. 328(C).
    4. Song, Haoran & Zhong, Zheng & Lin, Baiquan, 2023. "Mechanical degradation model of porous coal with water intrusion," Energy, Elsevier, vol. 278(C).
    5. Tao Liu & Chunsheng Li & Zongbao Liu & Kejia Zhang & Fang Liu & Dongsheng Li & Yan Zhang & Zhigang Liu & Liyuan Liu & Jiacheng Huang, 2022. "Research on Image Identification Method of Rock Thin Slices in Tight Oil Reservoirs Based on Mask R-CNN," Energies, MDPI, vol. 15(16), pages 1-16, August.
    6. Song, Hongqing & Zhang, Jie & Ni, Dongdong & Sun, Yueqiang & Zheng, Yongchun & Kou, Jue & Zhang, Xianguo & Li, Zhengyi, 2021. "Investigation on in-situ water ice recovery considering energy efficiency at the lunar south pole," Applied Energy, Elsevier, vol. 298(C).
    7. Chen, Siyuan & Li, Yu & Zhang, Tao & Zhu, Xingyu & Sun, Shuyu & Gao, Xin, 2021. "Lunar features detection for energy discovery via deep learning," Applied Energy, Elsevier, vol. 296(C).
    8. Zhang, Chong & Shi, Lingfeng & Pei, Gang & Yao, Yu & Li, Kexin & Zhou, Shuo & Shu, Gequn, 2023. "Thermodynamic analysis of combined heating and power system with In-Situ resource utilization for lunar base," Energy, Elsevier, vol. 284(C).
    9. Liu, Zekuan & Wang, Zixuan & Cheng, Kunlin & Wang, Cong & Ha, Chan & Fei, Teng & Qin, Jiang, 2023. "Performance assessment of closed Brayton cycle-organic Rankine cycle lunar base energy system: Thermodynamic analysis, multi-objective optimization," Energy, Elsevier, vol. 278(PA).
    10. Wang, Ji-Xiang & Zhong, Mingliang & Wu, Zhe & Guo, Mengyue & Liang, Xin & Qi, Bo, 2022. "Ground-based investigation of a directional, flexible, and wireless concentrated solar energy transmission system," Applied Energy, Elsevier, vol. 322(C).
    11. Guanheng Fan & Yiqun Zhang & Xiangfei Ji & Yang Yang, 2022. "Two-Layer Ring Truss-Based Space Solar Power Station," Energies, MDPI, vol. 15(8), pages 1-21, April.
    12. Hariharan Ramachandran & Andreia Plaza-Faverola & Hugh Daigle, 2022. "Impact of Gas Saturation and Gas Column Height at the Base of the Gas Hydrate Stability Zone on Fracturing and Seepage at Vestnesa Ridge, West-Svalbard Margin," Energies, MDPI, vol. 15(9), pages 1-25, April.
    13. Hampton, Harrison & Foley, Aoife, 2022. "A review of current analytical methods, modelling tools and development frameworks applicable for future retail electricity market design," Energy, Elsevier, vol. 260(C).
    14. Liu, Yiwei & Shen, Tianrun & Lv, Xiaochen & Zhang, Guang & Wang, Chao & Gu, Junping & Zhang, Xian & Wang, Qinggong & Chen, Xiong & Quan, Xiaojun & Yao, Wei, 2023. "Investigation on a lunar energy storage and conversion system based on the in-situ resources utilization," Energy, Elsevier, vol. 268(C).
    15. Christian Truitt Lüddeke & Calvin Lumban Gaol & Gion Joel Strobel & Leonhard Ganzer, 2022. "Experimental and Analytical Investigation of an Immiscible Displacement Process in Real Structure Micromodels," Energies, MDPI, vol. 15(18), pages 1-20, September.
    16. Kun-Jung Kim & Kee-Ho Yu, 2020. "Multidisciplinary Design Optimization for a Solar-Powered Exploration Rover Considering the Restricted Power Requirement," Energies, MDPI, vol. 13(24), pages 1-28, December.
    17. Gisela Pujol-Vazquez & Leonardo Acho & José Gibergans-Báguena, 2020. "Fault Detection Algorithm for Wind Turbines’ Pitch Actuator Systems," Energies, MDPI, vol. 13(11), pages 1-14, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:14:p:4957-:d:857281. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.