气-表面相互作用模拟对卫星空气动力学和热层质量密度的影响

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2021-09-09 DOI:10.1051/swsc/2021035
G. March, J. van den Ijssel, C. Siemes, P. Visser, E. Doornbos, M. Pilinski
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引用次数: 15

摘要

CHAMP、GRACE、GOCE和Swarm任务的卫星加速度数据提供了过去二十年热层密度的详细信息。最近在减少航天器几何建模误差方面的工作已经大大减少了这些任务的热层数据集之间的尺度差异。然而,数据集之间以及数据和模型之间仍然存在残余的不一致。在很大程度上,这些差异源于气体-表面相互作用(GSI)的建模,这是加速到密度数据处理中使用的卫星空气动力学建模的一部分。基于物理的GSI模型需要任何上述卫星都无法测量的现场大气成分和温度数据,因此,这些输入依赖于热层模型。为了减少对现有热层模型的依赖,我们在这项工作中选择了一个每次任务具有恒定能量适应系数的GSI模型,我们利用特定的姿态操纵和风分析对其进行优化,以提高多任务热层质量密度数据集的自一致性。我们将我们的结果与不同研究和半经验模型获得的基于可变能量调节的结果进行了比较,以显示主要差异。所提出的比较为量化当前GSI模型之间的差异提供了新的机会。在所提供的数据中,具有可变适应度的密度变化在+-10%以内,极点处的峰值可达15%。最大的差异出现在低太阳活动期。此外,我们利用2014年5月由近距离飞行的Swarm a和C卫星进行的一系列姿态操纵,来评估密度观测值作为能量调节系数函数的残余不一致性。我们的分析表明,0.85的能量调节系数最大限度地提高了姿态机动期间Swarm密度观测的一致性。使用这样的系数,对于Swarm-A和Swarm-C,新密度的大小会更低,相差4-5%。在最近的研究中,通过调查热层风,CHAMP和GOCE任务获得了类似的能量调节系数。这些新的能量容纳系数值在不同的任务和模型之间提供了更高的一致性。当前热层模型和观测值之间的中性密度比较表明,NRLMSISE-00和DTM-2013等半经验模型大大高估了密度,并且使用所提出的假设可以在不同任务的观测值之间实现更高的总体一致性。这项工作的新密度在NRLMSISE-00和DTM-2013的选定任务中提供了最小和最大平均比率之间分别为4.13%和3.65%的一致性。并与WACCM-X环流模型进行了比较。与其他模型类似,WACCM-X似乎提供了更高的质量密度估计,特别是在高和中等太阳活动的情况下。这项工作的目的是指导多个数据集的密度数据用户,并强调与不同GSI模型相关的剩余不确定性。
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Gas-surface interactions modelling infuence on satellite aerodynamics and thermosphere mass density
The satellite acceleration data from the CHAMP, GRACE, GOCE , and Swarm missions provide detailed information on the thermosphere density over the last two decades. Recent work on reducing errors in the modelling of the spacecraft geometry has already greatly reduced scale differences between the thermosphere data sets from these missions. However, residual inconsistencies between the data sets and between data and models are still present. To a large extent, these differences originate in the modelling of the gas-surface interactions ( GSI ), which is part of the satellite aerodynamic modelling used in the acceleration to density data processing. Physics-based GSI models require in- situ atmospheric composition and temperature data that are not measured by any of the above-mentioned satellites and, as a consequence, rely on thermosphere models for these inputs. To reduce the dependence on existing thermosphere models, we choose in this work a GSI model with a constant energy accommodation coefficient per mission, which we optimize exploiting particular attitude manoeuvres and wind analyses to increase the self-consistency of the multi-mission thermosphere mass density data sets. We compare our results with those based on variable energy accommodation obtained by different studies and semi-empirical models to show the principal differences. The presented comparisons provide the novel opportunity to quantify the discrepancies between current GSI models. Among the presented data, density variations with variable accommodation are within +- 10 % and peaks can reach up to 15 % at the poles. The largest differences occur during low solar activity periods. In addition, we utilize a series of attitude manoeuvres performed in May 2014 by the Swarm A and C satellites, which are flying in close proximity, to evaluate the residual inconsistency of the density observations as a function of the energy accommodation coefficient. Our analysis demonstrates that an energy accommodation coefficient of 0.85 maximizes the consistency of the Swarm density observations during the attitude manoeuvres. Using such coefficient, for Swarm-A and Swarm-C the new density would be lower in magnitude with a 4-5 % difference. In recent studies, similar energy accommodation coefficients were retrieved for the CHAMP and GOCE missions through investigating thermospheric winds. These new values for the energy accommodation coefficient provide a higher consistency among different missions and models. A comparison of neutral densities between current thermosphere models and observations indicates that semi-empirical models such as NRLMSISE -00 and DTM -2013 significantly overestimate the density, and that an overall higher consistency between the observations from the different missions can be achieved with the presented assumptions. The new densities from this work provide consistencies of 4.13 \ % and 3.65 \ % between minimum and maximum mean ratios among the selected missions with NRLMSISE -00 and DTM -2013, respectively. A comparison with the WACCM -X general circulation model is also performed. Similarly to the other models, WACCM -X seems to provide higher estimates of mass density especially under high and moderate solar activities. This work has the objective to guide density data users over the multiple data sets and highlight the remaining uncertainties associated with different GSI models.
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