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This paper examines modeling and simulation challenges for deployable spacecraft structures with softgood components. Previous studies highlighted the numerical challenges due to the mixture of high stiffness and low stiffness contact in this class of structures. This paper examines the use of the commercial LS-DYNA nonlinear finite element code on a set of relevant benchmark problems.
We describe a software approach for simultaneous demodulation and decoding of multiple frequency- multiplexed spacecraft across multiple ground stations. The approach involves the use of a single ground antenna with wide enough aperture to receive multiple angularly adjacent spacecraft simultaneously. This technique uses a wide-band RF signal digitizer coupled with easily and cheaply duplicated software-receiver modules to independently process the frequency-channelized downlink signals from the spacecraft. This approach relaxes the need for realizable modems at each antenna, for example in the Deep-SpaceNetwork (DSN), and can also function as a delayed data retrieval method for cubesat missions with routine science data return. Thus, we hope that this solution can enable more efficient utilization of DSN assets. We concentrate on a simulation similar to the proposed Exploration Mission 1 (EM-1) mission from a geometric perspective. To that end, the simulated scenario involves ten secondary cubesats deployed and tracked for a span of four days (the modeled motion over the first four days of the mission does not include any Trajectory Correction Maneuvers (TCMs) that may be necessary as the cubesats approach the moon). Transmissions from the cubesats may be received through a combination of DSN ground sites based on visibility. The cubesats are assumed to utilize typical cubesat transmit powers and a waveform similar to that of the Iris radio. One cubesat is chosen as the “target” and is considered tracked by all ground-stations throughout the simulation (i.e., it is consistently at the center of the main lobe of each ground station antenna when the ground station is in view of the cubesat in terms of elevation angle). The simulation effort involves synthesizing a wideband signal that includes the ten cubesats across a large bandwidth due to each cubesat having its own center-frequency in X-band, near 8.4 GHz. Each signal is characterized by its own Doppler-frequency shift and free-space path-loss computed through the underlying geometry of the simulation as well as the cubesat transmit power. Finally, each cubesat signal experiences a unique antenna gain at each ground station due to the underlying antenna pattern and spacecraft-ground station geometry. We establish two interesting findings: First, the link-budget for the EM-1-like scenario is almost completely limited by the angle between the center of the antenna main beam and the cubesat, which means that the signal-to-noise ratio is wholly adequate for demodulation and decoding at the simulated bitrates unless the cubesat exits the main beam. Secondly, and fortunately due to the use of a software radio architecture, we show that it is possible to successfully receive signals from most cubesats for the entire 4-day simulation. Due to the signal-to-noise ratio being sufficient for demodulation even after the side-lobe’s 17dB reduction in SNR, the software radio can still demodulate such cubesats as long as the radio is capable of re-establishing carrier lock as the cubesats leave the main beam and enter the side-lobe. Considering that the target application utilizes offline processing, a loss of lock can be detected and lock can be re-established by iterating over the data. Extensive simulations demonstrate these results.
A deployable one meter mesh reflector compatible with 12U-class CubeSat is introduced for telecommunication. It is compatible with NASA’s deep-space network (DSN) at X-band (i.e., uplink: 7.145-7.19 GHz; downlink: 8.4-8.45 GHz) and Ka-band frequencies (i.e., uplink: 34.2–34.7 GHz; downlink: 31.8–32.3 GHz). Three right-handed circularly polarized (RHCP) antennas, both transmit and receive, are introduced here: X-band only, Ka-band only, and X/Ka-band.
This invited plenary paper summarizes recent significant progress towards development and deployment of manufacturable SiC JFET-R ICs technology for beneficial prolonged use in extreme environmental conditions previously inaccessible to semiconductor electronics.
NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) Excavator is a teleoperated mobile robotic platform with a unique space regolith excavation capability. This research project developed functionality for inferencing regolith mass ingested during RASSOR operation, enhancing RASSOR’s ability to successfully complete ISRU missions. Radio wave propagation time to the Moon and back is ~2.56 seconds. Though teleoperation is possible with this delay, autonomous capability that enables RASSOR to plan and execute excavation missions intelligently and efficiently is preferred. To teleoperate or run autonomously, it is crucial for the quantity of regolith mass ingested by RASSOR to be available as a system state for efficient operation (e.g. knowledge of whether drums are full informs the task of highest priority, whether it be continuing to dig, or returning to a processing plant to offload regolith). A configurable data reduction and analysis pipeline was created to allow for straightforward incorporation of new data, such as that from lunar excavation, to improve model performance in new environments. Four distinct modeling approaches were employed in developing a mass inferencing approach that could work on RASSOR. All four models take in system states and output a mass prediction for each set of the robot’s bucket drums. Initial results from deployment to RASSOR and testing in a simulated lunar environment show that the models have <10% mean error during robot operation. Future work includes refinement of a model that estimates regolith mass in real-time during excavation as well as further testing of the developed models on the hardware.
This paper will discuss the motivation and details of the implementation of the SEIS tether model and the ways in which the SEIS tether impacted placement accuracy in certain configurations. It will also show results from testing this model on Earth and deploying SEIS to the Martian surface on sol 22 of InSight’s mission.
A compact long-wave infrared (LWIR) channeled spectro-polarimeter (IRCSP) has been developed for integration into the NASA Earth Science Technology Office (ESTO) funded submm-wave and LWIR polarimeters project to measure the microphysical properties of cloud ice. Once deployed, the IRCSP will produce the first linear Stokes measurements ( S0 , S1 , S2 ) of upper-tropospheric cirrus clouds from 8.5 to 12.5 μm. For the first time, a compact, light-weight, and uncooled LWIR polarimeter with off-the-shelf thermal optical components is demonstrated. We report narrowband calibration measurements which quantify metrics of polarimetric system performance. The response of the system to linearly polarized light is shown to agree with both a Mueller matrix model and modulation function for narrowband calibration measurements with an R2 > 0.98 from 8 to 11 μm. The polarimetric efficiency is >0.8 from 8 to 11 μm for narrowband measurements indicating satisfactory performance of the polarization optics. Beyond 11 μm, the agreement is significantly reduced as thermal noise compounds with reduced detector response. Ultimately, the observed system performance is limited by the spectral response of the detector past 11 μm in addition to the thermal noise inherent for the measurements at room temperature.
The Regolith Advanced Surface Systems Operations Robot (RASSOR) Excavator is a teleoperated mobile robotic platform with a unique space regolith excavation capability. The Intelligent Capabilities Enhanced RASSOR research project developed functionality for inferencing regolith mass ingested during RASSOR operation, enhancing RASSOR’s ability to successfully complete ISRU missions. To teleoperate or run autonomously, it is crucial for the quantity of regolith mass ingested by RASSOR to be available as a system state for efficient operation. For example, during autonomous operation, RASSOR should navigate and move to a processing plant to offload the collected regolith when the drums are full; without knowledge of how much mass is in the drums, this type of high-level planning is not possible. Four distinct modeling approaches were employed in developing a mass inferencing approach that could work on RASSOR. All take in system states, such as arm/drum positions, velocities, currents, voltages, and robot pose, and output a mass prediction for each set of the robot’s bucket drums.1) A neural network model that takes a vector of normalized system states; 2) A model that uses the integrated power consumption of an arm-raise (normalized by velocity); 3) A model that uses average drum current over a variable length interval of the drum disengaged from the surface; and 4) A real-time estimation model that aggregates excavation drum current. The developed models run in real time, outputting predictions for the front and rear drums, timestamp of the last prediction, and total mass in RASSOR’s drums. Further testing is required to validate the arm-raise model (2), though initial tests indicate reasonable performance (<10% mean error) on the hardware. The linear fit of average drum-current model (3) had a front value of r^2=0.99 and a rear value of r^2=0.98 on the validation dataset. This model currently has the best performance on unseen data. The real time model (4) is still in development, though initial results on a small subset of the training data show that it has high accuracy in predicting the increase in mass during excavation. Though work remains to be done with deploying a high-fidelity model to the physical system that makes predictions with error below the desired threshold, the modular architecture for model development allows quick adjustment of parameters to increase model fidelity. This architecture can also be adapted to use lunar excavation data to create models that are reflective of RASSOR’s dynamics when operating on the lunar surface. The results are promising as it has been shown that models can be developed that accurately estimate excavated regolith mass.
The Regolith Advanced Surface Systems Operations Robot (RASSOR) Excavator is a mobile robotic bucket-drum excavator platform with a unique space regolith excavation capability. The Intelligent Capabilities Enhanced RASSOR research project developed functionality for estimating the quantity of regolith mass ingested during RASSOR operation, enhancing RASSOR’s ability to successfully complete In-Situ Resource Utilization (ISRU) missions. To teleoperate or run autonomously, it is crucial for the amount of regolith mass ingested to be available as a system state for efficient operation. For example, during autonomous operation, RASSOR should navigate and move to a processing plant to offload the collected regolith when the drums are full; without knowledge of the total mass in the drums, this type of high-level planning is not possible. Three distinct modeling approaches were employed in developing a mass inferencing approach that could work on RASSOR, none of which require modification to the hardware. All take in system states, such as arm/drum motor positions, velocities, currents, voltages, and robot pose, and output a mass prediction for each set of the robot’s bucket drums. The developed models run in real-time, outputting predictions for the front drum mass, rear drum mass, timestamp of the last prediction, and total drum mass (sum of front and rear) in RASSOR’s drums. Models deployed to the hardware have low error (<7.5% mean error over the mass range, and <2.6% mean error when drums are more than half full) when making predictions in real-time. Our modeling approach can be adapted to use lunar excavation data to create models that are reflective of RASSOR’s dynamics when operating on the lunar surface. The results of this work are promising and show that models can be developed to accurately estimate excavated regolith mass.
The Regolith Advanced Surface Systems Operations Robot (RASSOR) Excavator is a mobile robotic bucket-drum excavator platform with a unique space regolith excavation capability. The Intelligent Capabilities Enhanced RASSOR research project developed functionality for estimating the quantity of regolith mass ingested during RASSOR operation, enhancing RASSOR’s ability to successfully complete In-Situ Resource Utilization (ISRU) missions. To teleoperate or run autonomously, it is crucial for the amount of regolith mass ingested to be available as a system state for efficient operation. For example, during autonomous operation, RASSOR should navigate and move to a processing plant to offload the collected regolith when the drums are full; without knowledge of the total mass in the drums, this type of high-level planning is not possible. Three distinct modeling approaches were employed in developing a mass inferencing approach that could work on RASSOR, none of which require modification to the hardware. All take in system states, such as arm/drum motor positions, velocities, currents, voltages, and robot pose, and output a mass prediction for each set of the robot’s bucket drums. The developed models run in real-time, outputting predictions for the front drum mass, rear drum mass, timestamp of the last prediction, and total drum mass (sum of front and rear) in RASSOR’s drums. Models deployed to the hardware have low error (<7.5% mean error over the mass range, and <2.6% mean error when drums are more than half full) when making predictions in real-time. Our modeling approach can be adapted to use lunar excavation data to create models that are reflective of RASSOR’s dynamics when operating on the lunar surface. The results of this work are promising and show that models can be developed to accurately estimate excavated regolith mass.
The Adaptive Deployable Entry and Placement Technology (ADEPT) offers a delivery capability for Small Sat or CubeSat orbiter(s), in-situ elements, or landers. ADEPT can deliver the same science payload to a destination with a stowed diameter a factor of 3-4 times smaller than an equivalent rigid aeroshell, alleviating volumetric constraints on the secondary payload accommodation or primary carrier spacecraft bus. The ADEPT system can support payload over a range of mass and geometries to offer a delivery capability for a single or constellation of spacecraft supporting the goals and objectives of “Low Cost Mars Science Missions.”
This paper will discuss the motivation and details of the implementation of the SEIS tether model and the ways in which the SEIS tether impacted placement accuracy in certain configurations. It will also show results from testing this model on Earth and deploying SEIS to the Martian surface on sol 22 of InSight’s mission.
The Center Differential Pivot Restraint (CDPR) for the Mars 2020 mission is designed to constrain motion of the rover differential and to dampen out the load response of during rover’s mobility deployment event in Entry, Descent, and Landing (EDL) phase of the mission. For Mars 2020, it was required to redesign the mechanism to save minimum 33% of the mass from the previous Mars Science Laboratory (MSL) design. The new mechanism architecture used a monolithic spring-like flexure to act as the system compliance, resulting in 50% mass savings from the MSL design. Along the design and prototype testing process, several mechanism design principles were re-affirmed as well as lessons learned about potential race conditions.
Water is a critical resource need for future human exploration and habitation of Mars and other planetary environments. An integral scientific question in the search for life outside of Earth is: What are the constraints on life in planetary environments? One of the most critical features of habitable environments is the availability of water - both as an environment for prebiotic chemistry, abiogenesis, and life; and as a vehicle for generating geo- and electro- chemical systems that can support metabolism. Seeking evidence of life prior to human arrival is important both to preserve signs of any existing or past evidence of Martian life, reducing the risks of unintentional forward contamination of Martian environments, and to potentially protect the health of any human crews. Looking forward towards Mars, future human exploration will require a rapid, but thorough, initial survey of any local “area of operations” on Mars to determine the spatial distribution, quantity, and quality (e.g., salt/mineral/organic content) of any local water, as well as to evaluate any signs of current or extinct life. We will discuss several candidate field survey methodologies, involving humans, a teamed instrument platform and a surveying/sampling rover. These are proposed to be validated in a given terrestrial Mars analog environment exhibiting varying distributions of water (ice, permafrost, rock-bound) to evaluate the constraints on life. Commercial space exploration brings the future possibility of unprecedented mass, power and in situ instrument capability, potentially enabling thorough exploration of the geology, hydrology and astrobiology of a km-radius study-zone around a future Mars human/commercial space landing site. We propose to study several representative planetary surface precursor-survey architectures and mission concepts (that are commercial-Mars-compatible), and to test and compare them in field application. We will examine some of the performance issues, using given metrics and controls, of spacesuited humans using handheld and standalone instruments, vs. a robotic human-tended rover/drill, robot arm and instruments. The latter rover-based architecture can in turn be viewed in terms of returned-to-base sample in-situ analyses vs sample analysis performed on a standalone instrument platform deployed away from the primary area of operations.
Deployable Entry Vehicle (DEV) technology has made significant advances over the last decade with ground test development campaigns and flight test demonstrations. DEVs offer benefits over traditional rigid entry vehicles including lower volume and mass, while enabling larger payload delivery and greater landing access. A crucial mission benefit is the DEV capability to transform from a compactly stowed launch configuration to a high drag area entry system for delivery of landers, rovers, aerial platforms, and orbiters (via aerocapture). These benefits span the range of mission classes from Small Satellite to human-class exploration systems. This presentation will describe DEV technology development status, highlight mission concepts, and recommend future investments.
Wireless sensors, especially if battery powered, have a number of advantages over wired sensors for flexible or temporary diagnostic deployment in a field or lab setting. Recent advances in wireless technology and microprocessor boards have produced a variety of inexpensive off-the shelf chips which can communicate wirelessly with simple protocols. This paper describes the design and implementation of a highly customizable wireless sensor network (called WiSe Net) using inexpensive open-source hardware components as wireless nodes. These wireless sensor nodes can transmit data at a rate <250 Hz, can be battery powered, and have a small footprint (2x5 cm). In addition, a preliminary over-the-air programming system was developed to allow for simple wireless configuration when active. The network performance was demonstrated by taking distributed and electrically isolated temperature measurements on a high-voltage lab apparatus. Although this test case is in a laboratory setting, this network architecture could be easily repurposed for various other forms of monitoring
This paper summarizes a recent numerical analysis of water vapor and volatile condensible material deposition on the James Webb Space Telescope from the initial orbit insertion up to 180 days post launch. The analysis utilized 17 distinct geometry files capturing observatory configuration changes during the deployment. Surface temperature was set from a time-dependent thermal analysis solution. A vapor pressure model was used to calculate the net water ice adsorption. Molecular contamination included a contribution from UV photopolymerization. The analysis predicted levels of ice and molecular accumulation were found to be within the allowable limits specified by the observatory contamination control plan.
A set of procedures was developed to enable rapid flight control law deployment and testing on subscale vertical takeoff and landing (VTOL) aircraft. Low-cost, subscale flight vehicles have become well-suited testbeds for rapid flight dynamics and controls research progression; however, integration of custom flight control laws onto flight hardware has historically been an arduous task. The toolchain described in this report leverages Simulink with the UAV Toolbox, a Pixhawk flight computer running PX4 firmware, and QGroundControl to efficiently design and flight test custom control algorithms. A subscale CL-84 VTOL aircraft was used as a testbed in this investigation to exercise the hardware integration process on a physical model. Implementation of custom attitude stabilization control laws and programmed test input excitations for aircraft system identification were demonstrated using the expeditious hardware integration process. The detailed procedures given in this report are expected to be used in future flight test efforts.