MOCAT-pySSEM: An open-source Python library and user interface for orbital debris and source sink environmental modeling

IF 2.4 4区 计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Indigo Brownhall , Miles Lifson , Stephen Hall, Charles Constant , Giovanni Lavezzi , Marek Ziebart , Richard Linares , Santosh Bhattarai
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Abstract

The rapid increase in the number of Low-Earth Orbit (LEO) satellites and reducing launch costs is likely to threaten the orbital environment. Understanding how this growth will affect the orbital debris population is paramount to designing effective policy, regulation and mitigation to protect the long term space sustainability of LEO. This will require interdisciplinary research of potential impacts, demanding contributions from social scientists, economists, astronomers, and alike. However, the complexity of astrodynamics and technical ability to build evolutionary space environment models often poses a significant barrier to interdisciplinary engagement, impeding critical research in this area. Previous models and tools have been developed, but are often not open-source nor accessible. MIT Orbital Capacity Assessment Tools (MOCAT) was developed to provide an open-source evolutionary space environment modeling capability to the broader space and policy communities, featuring both a computationally intensive but higher fidelity full-scale Monte Carlo model (MOCAT-MC) and a lower fidelity but significantly faster source sink evolutionary modeling framework, (MOCAT-SSEM). Here we continue this journey by presenting a Python version of the source sink tool, MOCAT-pySSEM with an accompanying web application (featuring cloud-hosted computation) to support future interdisciplinary research.

Abstract Image

MOCAT-pySSEM:用于轨道碎片和源汇环境建模的开源Python库和用户界面
近地轨道卫星数量的迅速增加和发射成本的降低可能会对轨道环境造成威胁。了解这种增长将如何影响轨道碎片数量,对于设计有效的政策、法规和减缓措施以保护近地轨道的长期空间可持续性至关重要。这将需要对潜在影响进行跨学科研究,要求社会科学家、经济学家、天文学家等做出贡献。然而,天体动力学的复杂性和建立演化空间环境模型的技术能力往往对跨学科参与构成重大障碍,阻碍了这一领域的关键研究。以前的模型和工具已经开发出来,但通常不是开源的,也不能访问。麻省理工学院轨道容量评估工具(MOCAT)旨在为更广泛的空间和政策社区提供开源的演化空间环境建模能力,具有计算密集型但高保真度的全尺寸蒙特卡罗模型(MOCAT- mc)和较低保真度但显著更快的源汇演化建模框架(MOCAT- ssem)。在这里,我们将继续这一旅程,介绍一个Python版本的源汇工具MOCAT-pySSEM及其附带的web应用程序(具有云托管计算功能),以支持未来的跨学科研究。
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来源期刊
SoftwareX
SoftwareX COMPUTER SCIENCE, SOFTWARE ENGINEERING-
CiteScore
5.50
自引率
2.90%
发文量
184
审稿时长
9 weeks
期刊介绍: SoftwareX aims to acknowledge the impact of software on today''s research practice, and on new scientific discoveries in almost all research domains. SoftwareX also aims to stress the importance of the software developers who are, in part, responsible for this impact. To this end, SoftwareX aims to support publication of research software in such a way that: The software is given a stamp of scientific relevance, and provided with a peer-reviewed recognition of scientific impact; The software developers are given the credits they deserve; The software is citable, allowing traditional metrics of scientific excellence to apply; The academic career paths of software developers are supported rather than hindered; The software is publicly available for inspection, validation, and re-use. Above all, SoftwareX aims to inform researchers about software applications, tools and libraries with a (proven) potential to impact the process of scientific discovery in various domains. The journal is multidisciplinary and accepts submissions from within and across subject domains such as those represented within the broad thematic areas below: Mathematical and Physical Sciences; Environmental Sciences; Medical and Biological Sciences; Humanities, Arts and Social Sciences. Originating from these broad thematic areas, the journal also welcomes submissions of software that works in cross cutting thematic areas, such as citizen science, cybersecurity, digital economy, energy, global resource stewardship, health and wellbeing, etcetera. SoftwareX specifically aims to accept submissions representing domain-independent software that may impact more than one research domain.
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