"uuid","repository link","title","author","contributor","publication year","abstract","subject topic","language","publication type","publisher","isbn","issn","patent","patent status","bibliographic note","access restriction","embargo date","faculty","department","research group","programme","project","coordinates" "uuid:7e1ff16f-85ee-4078-b40c-ed7c44ed22a7","http://resolver.tudelft.nl/uuid:7e1ff16f-85ee-4078-b40c-ed7c44ed22a7","Gas-surface interactions modelling influence on satellite aerodynamics and thermosphere mass density","March, G. (TU Delft Astrodynamics & Space Missions; European Space Agency (ESA)); van den IJssel, J.A.A. (TU Delft Astrodynamics & Space Missions); Siemes, C. (TU Delft Astrodynamics & Space Missions); Visser, P.N.A.M. (TU Delft Space Engineering); Doornbos, Eelco N. (Royal Netherlands Meteorological Institute (KNMI)); Pilinski, Marcin (University of Colorado)","","2021","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 modelling the spacecraft geometry has 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 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 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 by 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 the 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. Similar 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.","Accelerometer; Atmospheric drag; Gas-surface interactions; Mass density; Satellite aerodynamics; Thermosphere","en","journal article","","","","","","","","","","Space Engineering","Astrodynamics & Space Missions","","","" "uuid:4c36a4f0-d434-4748-89aa-b30255bc9010","http://resolver.tudelft.nl/uuid:4c36a4f0-d434-4748-89aa-b30255bc9010","Lower-Thermosphere-ionosphere (LTI) quantities: Current status of measuring techniques and models","Palmroth, Minna (Viikki Biocenter 1; Finnish Meteorological Institute (FMI)); Grandin, Maxime (Viikki Biocenter 1); Sarris, Theodoros (Democritus University of Thrace); Doornbos, Eelco (Royal Netherlands Meteorological Institute (KNMI)); Tourgaidis, Stelios (Democritus University of Thrace; Athena Research and Innovation Centre); March, G. (TU Delft Astrodynamics & Space Missions); Siemes, C. (TU Delft Astrodynamics & Space Missions); van den IJssel, J.A.A. (TU Delft Astrodynamics & Space Missions); Visser, P.N.A.M. (TU Delft Astrodynamics & Space Missions)","","2021","The lower-Thermosphere-ionosphere (LTI) system consists of the upper atmosphere and the lower part of the ionosphere and as such comprises a complex system coupled to both the atmosphere below and space above. The atmospheric part of the LTI is dominated by laws of continuum fluid dynamics and chemistry, while the ionosphere is a plasma system controlled by electromagnetic forces driven by the magnetosphere, the solar wind, as well as the wind dynamo. The LTI is hence a domain controlled by many different physical processes. However, systematic in situ measurements within this region are severely lacking, although the LTI is located only 80 to 200 km above the surface of our planet. This paper reviews the current state of the art in measuring the LTI, either in situ or by several different remote-sensing methods. We begin by outlining the open questions within the LTI requiring high-quality in situ measurements, before reviewing directly observable parameters and their most important derivatives. The motivation for this review has arisen from the recent retention of the Daedalus mission as one among three competing mission candidates within the European Space Agency (ESA) Earth Explorer 10 Programme. However, this paper intends to cover the LTI parameters such that it can be used as a background scientific reference for any mission targeting in situ observations of the LTI.
.","","en","journal article","","","","","","","","","","","Astrodynamics & Space Missions","","","" "uuid:5bfa9cf4-93e0-4b4e-81be-fb970a4271a1","http://resolver.tudelft.nl/uuid:5bfa9cf4-93e0-4b4e-81be-fb970a4271a1","Horizontal and vertical thermospheric cross-wind from GOCE linear and angular accelerations","Visser, T. (TU Delft Astrodynamics & Space Missions); March, G. (TU Delft Astrodynamics & Space Missions); Doornbos, E.N. (TU Delft Astrodynamics & Space Missions); de Visser, C.C. (TU Delft Control & Simulation); Visser, P (TU Delft Astrodynamics & Space Missions)","","2019","Thermospheric wind measurements obtained from linear non-gravitational accelerations of the Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite show discrepancies when compared to ground-based measurements. In this paper the cross-wind is derived from both the linear and the angular accelerations using a newly developed iterative algorithm. The two resulting data sets are compared to test the validity of wind derived from angular accelerations and quantify the uncertainty in accelerometer-derived wind data. In general the difference is found to be less than 50 m/s vertically after high-pass filtering, and 100 m/s horizontally. A sensitivity analysis reveals that continuous thrusting is a major source of uncertainty in the torque-derived wind, as are the magnetic properties of the satellite. The energy accommodation coefficient is identified as a particularly promising parameter for improving the consistency of thermospheric cross-wind data sets in the future. The algorithm may be applied to obtain density and cross-wind from other satellite missions that lack accelerometer data, provided the attitude and orbit are known with sufficient accuracy.","Angular accelerations; Gravity field and steady-state Ocean Circulation Explorer (GOCE); Thermospheric wind; Vertical wind","en","journal article","","","","","","","","2021-02-01","","","Astrodynamics & Space Missions","","","" "uuid:b87d2505-3c8f-4e4d-8ed6-bb36c8f29c73","http://resolver.tudelft.nl/uuid:b87d2505-3c8f-4e4d-8ed6-bb36c8f29c73","Characterization of Thermospheric Vertical Wind Activity at 225- to 295-km Altitude Using GOCE Data and Validation Against Explorer Missions","Visser, T. (TU Delft Astrodynamics & Space Missions); March, G. (TU Delft Astrodynamics & Space Missions); Doornbos, E.N. (TU Delft Astrodynamics & Space Missions); de Visser, C.C. (TU Delft Control & Simulation); Visser, P.N.A.M. (TU Delft Astrodynamics & Space Missions)","","2019","Recently, the horizontal and vertical cross wind at 225- to 295-km altitude were derived from linear acceleration measurements of the Gravity field and steady-state Ocean Circulation Explorer satellite. The vertical component of these wind data is compared to wind data derived from the mass spectrometers of the Atmosphere Explorer C and E and Dynamics Explorer 2 satellites. From a statistical analysis of the 120-s moving-window standard deviation of the vertical wind (σ(Vz)), no consistent discrepancy is found between the accelerometer-derived and the mass spectrometer-derived data. The validated Gravity field and steady-state Ocean Circulation Explorer data are then used to investigate the influence of several parameters and indices on the vertical wind activity. To this end, the probability distribution of σ(Vz) is plotted after distributing the data over bins of the parameter under investigation. The vertical wind is found to respond strongly to geomagnetic activity at high latitudes, although the response settles around a maximum standard deviation of 50 m/s at an Auroral Electrojet index of 800. The dependence on magnetic local time changes with magnetic latitude, peaking around 4:30 over the polar cap and around 01:30 and 13:30 in the auroral oval. Seasonal effects only become visible at low to middle latitudes, revealing a peak wind variability in both local summer and winter. The vertical wind is not affected by the solar activity level.","Atmosphere Explorers; Dynamics Explorer 2; Gravity field and steady-state Ocean Circulation Explorer (GOCE); thermospheric vertical wind","en","journal article","","","","","","","","","","","Astrodynamics & Space Missions","","","" "uuid:a33716dd-dea5-4320-a99b-198a8878bd4b","http://resolver.tudelft.nl/uuid:a33716dd-dea5-4320-a99b-198a8878bd4b","CHAMP, GRACE, GOCE and Swarm density and wind characterization with improved gas-surface interactions modelling (PPT)","March, G. (TU Delft Astrodynamics & Space Missions); Doornbos, E.N. (TU Delft Astrodynamics & Space Missions); Visser, P.N.A.M. (TU Delft Astrodynamics & Space Missions)","","2018","","","en","other","","","","","","PPT","","","","","Astrodynamics & Space Missions","","","" "uuid:5d79b7d0-4b84-47bc-a724-6d0b1e1ae228","http://resolver.tudelft.nl/uuid:5d79b7d0-4b84-47bc-a724-6d0b1e1ae228","Update on thermospheric density products from satellite observations","March, G. (TU Delft Astrodynamics & Space Missions); Visser, T. (TU Delft Astrodynamics & Space Missions); Doornbos, E.N. (TU Delft Astrodynamics & Space Missions); Iorfida, E. (TU Delft Astrodynamics & Space Missions); van den IJssel, J.A.A. (TU Delft Astrodynamics & Space Missions); Visser, P.N.A.M. (TU Delft Astrodynamics & Space Missions)","","2018","","","en","poster","","","","","","","","","","","Astrodynamics & Space Missions","","","" "uuid:16ee745a-cea9-4f38-ad7e-0dd635c9c0de","http://resolver.tudelft.nl/uuid:16ee745a-cea9-4f38-ad7e-0dd635c9c0de","Improving the consistency of aerodynamic models and thermospheric density and wind data (PP)","Visser, T. (TU Delft Astrodynamics & Space Missions); March, G. (TU Delft Astrodynamics & Space Missions)","","2018","","","en","other","","","","","","","","","","","Astrodynamics & Space Missions","","","" "uuid:73738044-c41a-4b8d-958f-c70d0fa2ceee","http://resolver.tudelft.nl/uuid:73738044-c41a-4b8d-958f-c70d0fa2ceee","CHAMP, GRACE, GOCE and Swarm Thermosphere Density Data with Improved Aerodynamic and Geometry Modelling","March, G. (TU Delft Astrodynamics & Space Missions); Doornbos, E.N. (TU Delft Astrodynamics & Space Missions); Visser, P.N.A.M. (TU Delft Astrodynamics & Space Missions)","","2017","Since 2000, accelerometers on board of the CHAMP, GRACE, GOCE and Swarm satellites have provided highresolution thermosphere density data, improving knowledge on atmospheric dynamics and coupling processes in the thermosphere-ionosphere layer. Most of the research has focused on relative changes in density. Scale differences between datasets and models have been largely neglected or removed using ad hoc scale factors. The origin of these variations arises from errors in the aerodynamic modelling, specifically in the modelling of the satellite outer surface geometry and of the gas-surface interactions. Therefore, in order to further improve density datasets and models that rely on these datasets, and in order to make them align with each other in terms of the absolute scale of the density, it is first required to enhance the geometry modelling. Once accurate geometric models of the satellites are available, it will be possible to enhance the characterization of the gassurface interactions, and to enhance the satellite aerodynamic modelling. This presentation offers an accurate approach for determining aerodynamic forces and torques and improved density data for CHAMP, GRACE, GOCE and Swarm. Through detailed high fidelity 3-D CAD models and Direct Simulation Monte Carlo computations, flow shadowing and complex concave geometries can be investigated. This was not possible with previous closed-form solutions, especially because of the low fidelity geometries and the incapability to introduce shadowing effects. This inaccurate geometry and aerodynamic modelling turned out to have relevant influence on derived densities, particularly for satellites with complex elongated shapes and protruding instruments, beams and antennae. Once the geometry and aerodynamic modelling have been enhanced with the proposed approach, the accelerometer data can be reprocessed leading to 81 higher fidelity density estimates. An overview of achieved improvements and dataset comparisons will be provided together with an introduction to the next gas-surface interactions research phase.","","en","poster","","","","","","","","","","","Astrodynamics & Space Missions","","",""