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The objective of the Mars Environmental Survey (MESUR) Network Mission is to establish a global network of small science stations on the surface of Mars to operate concurrently over a minimum of one martian year.
The Mars Entry, Descent, and Landing Instrumentation (MEDLI2) sensor suite collected data during entry of the Mars 2020 Perseverance rover into Mars’ atmosphere. This suite included a network of MEDLI2 Instrumented Sensor Plugs (MISPs). Each MISP was comprised of a cylinder made of Thermal Protection System (TPS) material with 1-3 embedded thermocouples (TCs), and it was flush mounted into the heatshield or backshell. Data from these in-depth TCs were used to reconstruct the aeroheating environment of the vehicle throughout entry. Surface heating was posed as an inverse problem, with the goal of estimating the surface heating by minimizing an objective function of the difference between MISP temperature measurements during flight and the temperature predictions derived from the Fully Implicit Ablation and Thermal response (FIAT) program. Given an aerothermal environment, FIAT calculates the material response and provides in-depth temperatures throughout the TPS material. To achieve the reverse, an internal tool called FIAT_Opt runs through multiple different environments until the output temperature at the TC depth closely matches the flight data. 95% confidence intervals on the reconstructed surface heating were obtained using Monte Carlo analysis, in which uncertainties in the thermocouple depth and the TPS material properties (e.g., density, thermal conductivity, heat capacity, emissivity) based on flight-lot material testing were included. A variance decomposition method using Sobol indices was employed to assess the sensitivity of the reconstructed peak heating to the TC placement and material property uncertainties. Variance decomposition was found to require tens of thousands of FIAT_Opt runs in order for the Sobol indices to converge. With a single FIAT_Opt run taking on the order of 40 minutes, the required number of computations would take months to complete, even if using multiple CPUs. To mitigate this problem, three machine learning models (ridge regression with cross-validation, random forest regression, and a deep neural network) were trained and tested using the 2000 Monte Carlo runs that were already completed. A subset of 1600 runs were used to train the model (i.e., training set), while the remaining 400 runs were used as the test set. The predictions from the deep neural network (DNN) on the test set showed nearly perfect agreement to the actual values computed with FIAT_Opt (R2 > 0.99). Using the DNN as a surrogate model, the variance decomposition using 50,000 runs was completed within minutes. The resulting Sobol indices showed that the reconstructed peak surface heating was most sensitive to the uncertainties in the thermal conductivity (ST = 0.37) and heat capacity (ST = 0.26). This method can be leveraged to provide requirements for material property measurements needed to improve the accuracy of surface heating prediction and ultimately lead to the reduction of design margins in the future. This presentation will include background on the MEDLI2 suite; the method used for inverse heating estimation; the way that material property uncertainties were accounted for using Monte Carlo analysis; a brief background on variance decomposition; the motivation for using machine learning in this context; how a neural network was trained on the data to enable variance decomposition in a fraction of the time; and the variance decomposition results for one of the MISPs.
For the past 30 years there has been a strong consensus within the international scientific community in favor of sending a network of geophysical landers to Mars to characterize the near-surface weather and climate, determine the large-scale atmospheric dynamics and explore the interior structure and composition. Despite this scientific support, there has been an unbroken string of proposed missions over the past fifteen years which have failed for programmatic reasons to progress beyond the design stage (Mars Network Mission, MESUR, Marsnet, InterMarsnet, NetLander). In this presentation, we review the scientific rationale and technical requirements for such a mission, and discuss current activities aimed toward its implementation.
Nearly all data acquired by vehicles on the surface of Mars are returned to Earth via Mars orbiters – more than 1.7 terabits so far. Successful communication between the various spacecraft is achieved via the careful implementation of internationally recognized CCSDS telecommunications protocols and the use of planning and coordination services provided by NASA’s Mars Program Office and the Multimission Ground Systems and Services (MGSS) Program at the Jet Propulsion Laboratory in Pasadena, CA. This modern Mars relay network has evolved since its inception in 2004 with the addition and loss of several missions, but it has fundamentally remained unchanged. Ground interfaces between the various spacecrafts’ mission operations centers on Earth remain largely unique for each participant, each mission maintains its own interfaces with deep space communications networks (e.g. DSN, ESTRACK), which are similar but still unique; and relay sessions at Mars require careful ground planning, coordination, and implementation. This paper will discuss the existing architecture and consider how several technologies may be applied to the next generation of relay services at Mars. Ultimately, these are expected to lead to the implementation of a delay and disruption tolerant network at Mars, a precursor to becoming a major element in an emerging Solar System Internet.
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Explore the source record for details and available documents.
Mariner Mars 1971 mission support, engineering, and design of Deep Space Network
Properties of Noachian valley networks on Mars suggest that the conditions under which they formed were marginal for liquid water formation. The networks are sparsely scattered, poorly dissected, and tend to be small; a majority occupy areas only a few hundred kilometers in extent. Models in which networks formed by mass wasting are contra-indicated by the discovery of channels within the valleys. Greenhouse hypotheses for the stability of liquid water have foundered on familiar problems: first, a very substantial CO2 atmosphere would be required to bring global average conditions to 273 K; the CO2 should still be present in extensive carbonate deposits that have not been detected. Explanations that call upon groundwater sapping are hampered by the need for a hydrologic system to recharge the groundwater system, which effectively reinstates the need for a heavy CO2 atmosphere. Based upon field experience and geomorphic similarities between drainage developed in the periglacial terrain in and around the Haughton impact structure, Devon Island, Nuunavuut, Canada, we have suggested that some of the channel networks may have formed either subglacially, or as ice marginal structures.
Deep Space Network telecommunication and ground support equipment for planetary and interplanetary flight projects
In this article we describe the analysis and simulation effort of the end-to-end traffic flow for the Deep Space Network (DSN) in the Human Exploration Era, when DSN will provide communication and navigation services for human missions to distant celestial objects like the Moon, asteroids, and Mars. Using the network traffic derived for the 30-day period within July/August 2039 from the Space Communications Mission Model (SCMM), we simulate the bandwidths of the ground links and the buffer profiles of the network nodes. We also use a 2-state Markov scheme that models the store-and-forward mechanism that regulates the ground network traffic. The network traffic modeling and simulation generates ground bandwidth and buffer statistics, which in turn are used to formulate the future DSN ground network bandwidth and storage requirements.
NASA and ESA have established an international network of Mars orbiters, outfitted with relay communications payloads, to support robotic exploration of the red planet. Starting in January, 2004, this network has provided the Mars Exploration Rovers with telecommunications relay services, significantly increasing rover engineering and science data return while enhancing mission robustness and operability. Augmenting the data return capabilities of their X-band direct-to-Earth links, the rovers are equipped with UHF transceivers allowing data to be relayed at high rate to the Mars Global Surveyor (MGS), Mars Odyssey, and Mars Express orbiters. As of 21 July, 2004, over 50 Gbits of MER data have been obtained, with nearly 95% of that data returned via the MGS and Odyssey UHF relay paths, allowing a large increase in science return from the Martian surface relative to the X-band direct-to-Earth link. The MGS spacecraft also supported high-rate UHF communications of MER engineering telemetry during the critical period of entry, descent, and landing (EDL), augmenting the very low-rate EDL data collected on the X-band direct-to-Earth link. Through adoption of the new CCSDS Proximity-1 Link Protocol, NASA and ESA have achieved interoperability among these Mars assets, as validated by a successful relay demonstration between Spirit and Mars Express, enabling future interagency cross-support and establishing a truly international relay network at Mars.
The Mars Entry, Descent, and Landing Instrumentation (MEDLI2) sensor suite collected data during entry of the Mars 2020 Perseverance rover into Mars’ atmosphere. An inverse estimation of the backshell and heatshield surface aeroheating was performed, using the data from the MEDLI2 Instrumented Sensor Plugs, a network of thermocouples embedded within the thermal protection system across the aeroshell. Monte Carlo analysis was conducted to assess the sensitivity of the surface heat rate, temperature, and heat load to uncertainties in thermocouple depth and material properties. In this paper, a variance decomposition method using Sobol indices was employed to understand the relative contributions of each uncertainty parameter. Performing this analysis using results from the inverse analysis tool FIAT_Opt was found to require incredibly high computation time, and thus machine learning models were trained and evaluated as a surrogate model for FIAT_Opt. This paper demonstrates that machine learning models can be an efficient, accurate alternative to state-of-the-art inverse analysis tools like FIAT_Opt, especially for computationally-expensive processes. Using these models, the sensitivity analysis showed that uncertainties in heat capacity and thermal conductivity were the main drivers for the overall uncertainty in peak reconstructed heating and heat load.
The Mars Relay Operational Service (MaROS) comprises a number of tools to coordinate, plan, and visualize various aspects of the Mars Relay network. These levels include a Web-based user interface, a back-end "ReSTlet" built in Java, and databases that store the data as it is received from the network. As part of MaROS, the innovators have developed and implemented a feature set that operates on several levels of the software architecture. This new feature is an advanced querying capability through either the Web-based user interface, or through a back-end REST interface to access all of the data gathered from the network. This software is not meant to replace the REST interface, but to augment and expand the range of available data. The current REST interface provides specific data that is used by the MaROS Web application to display and visualize the information; however, the returned information from the REST interface has typically been pre-processed to return only a subset of the entire information within the repository, particularly only the information that is of interest to the GUI (graphical user interface). The new, advanced query and data mining capabilities allow users to retrieve the raw data and/or to perform their own data processing. The query language used to access the repository is a restricted subset of the structured query language (SQL) that can be built safely from the Web user interface, or entered as freeform SQL by a user. The results are returned in a CSV (Comma Separated Values) format for easy exporting to third party tools and applications that can be used for data mining or user-defined visualization and interpretation. This is the first time that a service is capable of providing access to all cross-project relay data from a single Web resource. Because MaROS contains the data for a variety of missions from the Mars network, which span both NASA and ESA, the software also establishes an access control list (ACL) on each data record in the database repository to enforce user access permissions through a multilayered approach.
Humans have been fascinated with the idea of exploring Mars since the very beginning of the space age. Largely due to the belief that life may have at one time existed in some form, surface exploration has been the ultimate ambition of this exploration. Unfortunately engineers and scientists discovered early on that landing a spacecraft on the surface of Mars was to become one of the most difficult and treacherous challenges of robotic space exploration. At arrival to Mars, a spacecraft will be traveling at velocities between 4 and 7 km/s. 100% of this kinetic energy (KE) must be safely removed for a lander to deliver its payload to the surface. Fortunately Mars has an atmosphere substantial enough to allow the combination of a high drag heatshield and a parachute to remove 99% and 0.98% respectively of this kinetic energy. Unfortunately the atmosphere is not substantial enough to bring a lander to a safe touchdown. This means that an additional landing system is required to remove the remaining kinetic energy. On all previous successful missions the landing system has consisted of 2 major elements, a propulsion subsystem to remove an additional 0.002% (approx.50 - 100 m/s ) of the original KE and a final dedicated touchdown system. The first generation Mars landers used legs to accomplish touchdown. The second generation of Mars lander touchdown systems used airbags to mitigate the last few meters per second of residual velocity. NASA is currently developing a third generation landing system in an effort to reduce cost, mass and risk while simultaneously increasing performance as measured by payload fraction to the surface and accessible terrain roughness.
The international space community has begun to recognize that the established model for management of communications with spacecraft - commanded data transmission over individual pair-wise contacts - is operationally unwieldy and will not scale in support of increasingly complex and sophisticated missions such as NASA's Constellation project. Accordingly, the international Inter-Agency Operations Advisory Group (IOAG) ichartered a Space Internetworking Strategy Group (SISG), which released its initial recommendations in a November 2008 report. The report includes a recommendation that the space flight community adopt Delay-Tolerant Networking (DTN) to address the problem of interoperability and communication scaling, especially in mission environments where there are multiple spacecraft operating in concert. This paper explores some of the issues that must be addressed in implementing, deploying, and operating DTN as part of a multi-mission, multi-agency space internetwork as well as benefits and future operational scenarios afforded by DTN-based space internetworking.
Ancient lake deposits and valley networks on Mars provide strong evidence that its surface was once modified by liquid water, but the extent of that modification is still debated. Ancient lacustrine deposits in Milna Crater provide insight into the timescale and fluid volume required to construct fluvially derived sedimentary deposits near the Noachian-Hesperian boundary. Placing the lacustrine deposits their regional context in Paraná Valles provides a quantitative measurement of the intermittency of large, water-mediated sediment transport events in that region.