IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v426y2022ics0096300322002107.html
   My bibliography  Save this article

A stochastic Hamiltonian formulation applied to dissipative particle dynamics

Author

Listed:
  • Peng, Linyu
  • Arai, Noriyoshi
  • Yasuoka, Kenji

Abstract

In this paper, a stochastic Hamiltonian formulation (SHF) is proposed and applied to dissipative particle dynamics (DPD) simulations. As an extension of Hamiltonian dynamics to stochastic dissipative systems, the SHF provides necessary foundations and great convenience for constructing efficient numerical integrators. As a first attempt, we develop the Störmer–Verlet type of schemes based on the SHF, which are structure-preserving for deterministic Hamiltonian systems without external forces, the dissipative forces in DPD. Long-time behaviour of the schemes is shown numerically by studying the damped Kubo oscillator. In particular, the proposed schemes include the conventional Groot–Warren’s modified velocity-Verlet method and a modified version of Gibson–Chen–Chynoweth as special cases. The schemes are applied to DPD simulations and analysed numerically.

Suggested Citation

  • Peng, Linyu & Arai, Noriyoshi & Yasuoka, Kenji, 2022. "A stochastic Hamiltonian formulation applied to dissipative particle dynamics," Applied Mathematics and Computation, Elsevier, vol. 426(C).
    • Handle: RePEc:eee:apmaco:v:426:y:2022:i:c:s0096300322002107
    DOI: 10.1016/j.amc.2022.127126
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300322002107
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2022.127126?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Liang Pan & Fan Wang & Yuan Cheng & Wan Ru Leow & Yong-Wei Zhang & Ming Wang & Pingqiang Cai & Baohua Ji & Dechang Li & Xiaodong Chen, 2020. "A supertough electro-tendon based on spider silk composites," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    2. J. B. Gibson & K. Chen & S. Chynoweth, 1999. "The Equilibrium Of A Velocity-Verlet Type Algorithm For Dpd With Finite Time Steps," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 10(01), pages 241-261.
    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. Songlin Zhang & Mengjuan Zhou & Mingyang Liu & Zi Hao Guo & Hao Qu & Wenshuai Chen & Swee Ching Tan, 2023. "Ambient-conditions spinning of functional soft fibers via engineering molecular chain networks and phase separation," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    2. Shijing Zhang & Yingxiang Liu & Jie Deng & Xiang Gao & Jing Li & Weiyi Wang & Mingxin Xun & Xuefeng Ma & Qingbing Chang & Junkao Liu & Weishan Chen & Jie Zhao, 2023. "Piezo robotic hand for motion manipulation from micro to macro," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    3. Wenqian He & Meilin Wang & Guangkai Mei & Shiyong Liu & Abdul Qadeer Khan & Chao Li & Danyang Feng & Zihao Su & Lili Bao & Ge Wang & Enzhao Liu & Yutian Zhu & Jie Bai & Meifang Zhu & Xiang Zhou & Zunf, 2024. "Establishing superfine nanofibrils for robust polyelectrolyte artificial spider silk and powerful artificial muscles," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    4. Ying Liu & Chan Wang & Zhuo Liu & Xuecheng Qu & Yansong Gai & Jiangtao Xue & Shengyu Chao & Jing Huang & Yuxiang Wu & Yusheng Li & Dan Luo & Zhou Li, 2024. "Self-encapsulated ionic fibers based on stress-induced adaptive phase transition for non-contact depth-of-field camouflage sensing," Nature Communications, Nature, vol. 15(1), pages 1-12, December.

    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:eee:apmaco:v:426:y:2022:i:c:s0096300322002107. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    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.