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Current status, projected goals, and results of 49 research and advanced development programs at the Jet Propulsion Laboratory are reported in abstract form. Areas of investigation include: aerodynamics and fluid mechanics, applied mathematics and computer sciences, environment protection, materials science, propulsion, electric and solar power, guidance and navigation, communication and information sciences, general physics, and chemistry.
Paper describes laboratory spectral and radiometric calibration of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) applied to all AVIRIS science data collected in 1987. Describes instrumentation and procedures used and demonstrates that calibration accuracy achieved exceeds design requirements. Developed for use in remote-sensing studies in such disciplines as botany, geology, hydrology, and oceanography.
Advanced techniques for efficiently representing most forms of data are being implemented in practical hardware and software form through the joint efforts of three NASA centers. These techniques adapt to local statistical variations to continually provide near optimum code efficiency when representing data without error. Demonstrated in several earlier space applications, these techniques are the basis of initial NASA data compression standards specifications. Since the techniques clearly apply to most NASA science data, NASA invested in the development of both hardware and software implementations for general use. This investment includes high-speed single-chip very large scale integration (VLSI) coding and decoding modules as well as machine-transferrable software routines. The hardware chips were tested in the laboratory at data rates as high as 700 Mbits/s. A coding module's definition includes a predictive preprocessing stage and a powerful adaptive coding stage. The function of the preprocessor is to optimally process incoming data into a standard form data source that the second stage can handle.The built-in preprocessor of the VLSI coder chips is ideal for high-speed sampled data applications such as imaging and high-quality audio, but additionally, the second stage adaptive coder can be used separately with any source that can be externally preprocessed into the 'standard form'. This generic functionality assures that the applicability of these techniques and their recent high-speed implementations should be equally broad outside of NASA.
As part of a program to determine the capabilities of Telescience as applied to Microgravity Materials Science the need for a remotely controlled microscope was recognized. For this purpose we equipped a microscope with an X-Y-Z positioning device and motors on the zoom and focus controls. Computer control of these devices allowed remote operation. A standard TV camera was mounted to the computer controlled video board which could compress the image in resolution and grey scale. The operator control console was programmed to display three still video pictures as well as provide command access. A standard data transfer network was used to transmit the video data files and the command interaction was via a high speed phone modem. This system, with the microscope in the Microgravity Materials Science Laboratory (MMSL) at LeRC and the control at RPI, was used to determine the accuracy of setting, time required to achieve setting and the operator ease factor. It was found that the focus setting could be established well within the resolution limit of the TV system and that each motion took about 50 seconds and approximately 12 minutes was required to reach ?best? focus. These times could be reduced significantly with operator experience. The operators were provided with ancillary equipment which provided assistance in making the necessary decisions and they reported satisfaction with the control.
Trajectory design of the orbit phase of the NEAR mission involves a new process that departs significantly from those procedures used in previous missions. In most cases, a precise spacecraft ephemeris is designed well in advance of arrival at the target body. For NEAR, the uncertainty in the dynamic environment around Eros does not allow the luxury of a precise spacecraft trajectory to be defined in advance. The principal cause of this uncertainty is the limited knowledge oi' the gravity field a,-id rotational state of Eros. As a result, the concept for the NEAR trajectory design is to define a number of rules for satisfying spacecraft, mission, and science constraints, and then apply these rules to various assumptions for the model of Eros. Nominal, high, and low Eros mass models are used for testing the trajectory design strategy and to bracket the ranges of parameter variations that are expected upon arrival at the asteroid. The final design is completed after arrival at Eros and determination of the actual gravity field and rotational state. As a result of the unplanned termination of the deep space rendezvous maneuver on December 20, 1998, the NEAR spacecraft passed within 3830 km of Eros on December 23, 1998. This flyby provided a brief glimpse of Eros, and allowed for a more accurate model of the rotational parameters and gravity field uncertainty. Furthermore, after the termination of the deep space rendezvous burn, contact with the spacecraft was lost and the NEAR spacecraft lost attitude control. During the subsequent gyrations of the spacecraft, hydrazine thruster firings were used to regain attitude control. This unplanned thruster activity used Much of the fuel margin allocated for the orbit phase. Consequently, minimizing fuel consumption is now even more important.
A software program provides a Sensorweb architecture for alert-processing, event detection, asset allocation and planning, and visualization. It automatically tasks and re-tasks various types of assets such as satellites and robotic vehicles in response to alerts (fire, weather) extracted from various data sources, including low-level Webcam data. JPL has adapted cons iderable Sensorweb infrastructure that had been previously applied to NASA Earth Science applications. This NASA Earth Science Sensorweb has been in operational use since 2003, and has proven reliability of the Sensorweb technologies for robust event detection and autonomous response using space and ground assets. Unique features of the software include flexibility to a range of detection and tasking methods including those that require aggregation of data over spatial and temporal ranges, generality of the response structure to represent and implement a range of response campaigns, and the ability to respond rapidly.
HURON solves the problem of how to optimize a plan and schedule for assigning multiple agents to a temporal sequence of actions (e.g., science tasks). Developed as a generic planning and scheduling tool, HURON has been used to optimize space mission surface operations. The tool has also been used to analyze lunar architectures for a variety of surface operational scenarios in order to maximize return on investment and productivity. These scenarios include numerous science activities performed by a diverse set of agents: humans, teleoperated rovers, and autonomous rovers. Once given a set of agents, activities, resources, resource constraints, temporal constraints, and de pendencies, HURON computes an optimal schedule that meets a specified goal (e.g., maximum productivity or minimum time), subject to the constraints. HURON performs planning and scheduling optimization as a graph search in state-space with forward progression. Each node in the graph contains a state instance. Starting with the initial node, a graph is automatically constructed with new successive nodes of each new state to explore. The optimization uses a set of pre-conditions and post-conditions to create the children states. The Python language was adopted to not only enable more agile development, but to also allow the domain experts to easily define their optimization models. A graphical user interface was also developed to facilitate real-time search information feedback and interaction by the operator in the search optimization process. The HURON package has many potential uses in the fields of Operations Research and Management Science where this technology applies to many commercial domains requiring optimization to reduce costs. For example, optimizing a fleet of transportation truck routes, aircraft flight scheduling, and other route-planning scenarios involving multiple agent task optimization would all benefit by using HURON.
An automated cloud tracking algorithm is applied to Cassini Imaging Science Subsystem high-resolution apoapsis images of Saturn from 2005 and 2007 and moderate resolution images from 2011 and 2012 to define the near-global distribution of zonal winds and eddy momentum fluxes at the middle troposphere cloud level and in the upper troposphere haze. Improvements in the tracking algorithm combined with the greater feature contrast in the northern hemisphere during the approach to spring equinox allow for better rejection of erroneous wind vectors, a more objective assessment at any latitude of the quality of the mean zonal wind, and a population of winds comparable in size to that available for the much higher contrast atmosphere of Jupiter. Zonal winds at cloud level changed little between 2005 and 2007 at all latitudes sampled. Upper troposphere zonal winds derived from methane band images are approx. 10 m/s weaker than cloud level winds in the cores of eastward jets and approx. 5 m/s stronger on either side of the jet core, i.e., eastward jets appear to broaden with increasing altitude. In westward jet regions winds are approximately the same at both altitudes. Lateral eddy momentum fluxes are directed into eastward jet cores, including the strong equatorial jet, and away from westward jet cores and weaken with increasing altitude on the flanks of the eastward jets, consistent with the upward broadening of these jets. The conversion rate of eddy to mean zonal kinetic energy at the visible cloud level is larger in eastward jet regions (5.2x10(exp -5) sq m/s) and smaller in westward jet regions (1.6x10(exp -5) sqm/s) than the global mean value (4.1x10(ep -5) sq m/s). Overall the results are consistent with theories that suggest that the jets and the overturning meridional circulation at cloud level on Saturn are maintained at least in part by eddies due to instabilities of the large-scale flow near and/or below the cloud level.
A reduced complexity investigation for blunt-leading-edge vortical separation has been undertaken. The overall approach is to design the fundamental work in such a way so that it relates to the aerodynamics of a more complex Uninhabited Combat Air Vehicle (UCAV) concept known as SACCON. Some of the challenges associated with both the vehicle-class aerodynamics and the fundamental vortical flows are reviewed, and principles from a hierarchical complexity approach are used to relate flow fundamentals to system-level interests. The work is part of roughly 6-year research program on blunt-leading-edge separation pertinent to UCAVs, and was conducted under the NATO Science and Technology Organization, Applied Vehicle Technology panel.
A diamond-wing configuration has been developed to isolate and study blunt-leading edge vortex separation with both computations and experiments. The wing has been designed so that the results are relevant to a more complex Uninhabited Combat Air Vehicle concept known as SACCON. The numerical and theoretical development process for this diamond wing is presented, including a view toward planned wind tunnel experiments. This work was conducted under the NATO Science and Technology Organization, Applied Vehicle Technology panel. All information is in the public domain.
BIRCHES is the compact broadband IR spectrometer of the Lunar Ice Cube mission. Lunar Ice Cube is one of 13 6U cubesats that will be deployed by EM1 in cislunar space, qualifying as lunarcubes. The LunarCube paradigm is a proposed approach for extending the affordable CubeSat standard to support access to deep space via cis-lunar/lunar missions. Because the lunar environment contains analogs of most solar system environments, the Moon is an ideal target for both testing critical deep space capabilities and understanding solar system formation and processes. Effectively, as developments are occurring in parallel, 13 prototype deep space cubesats are being flown for EM1. One useful outcome of this 'experiment' will be to determine to what extent it is possible to develop a lunarcube 'bus' with standardized interfaces to all subsystems using reasonable protocols for a variety of payloads. The lunar ice cube mission was developed as the test case in a GSFC R&D study to determine whether the cubesat paradigm could be applied to deep space, science requirements driven missions, and BIRCHES was its payload. JPL's Lunar Flashlight, and Arizona State University's LunaH-Map, both also EM1 lunar orbiters, will also be deployed from EM1 and provide complimentary observations to be used in understanding volatile dynamics in the same time frame.
In the realm of aerospace engineering and the physical sciences, we have developed laws of physics based on empirical and research evidence that reliably guide design, research, and development efforts. For instance, an engineer designs a system based on data and experience that can be consistently and repeatedly verified. This reproducibility depends on the consistency and dependability of the materials on which the engineer works and is subject to physics, geometry and convention. In life sciences and medicine, these apply as well, but individuality introduces a host of variables into the mix, resulting in characteristics and outcomes that can be quite broad within a population of individuals. This individuality ranges from differences at the genetic and cellular level to differences in an individuals personality and abilities due to sex and gender, environment, education, etc.
There is more useful information in the time series of satellite-derived column-averaged carbon dioxide (XCO2) than is typically characterized. Often, the entire time series is treated at once without considering detailed features at shorter timescales, such as nonstationary changes in signal characteristics – amplitude, period and phase. In many instances, signals are visually and analytically differentiable from other portions in a time series. Each rise (increasing) and fall (decreasing) segment in the seasonal cycle is visually discernable in a graph of the time series. The rise and fall segments largely result from seasonal differences in terrestrial ecosystem production, which means that the segment's signal characteristics can be used to establish observational benchmarks because the signal characteristics are driven by similar underlying processes. We developed an analytical segmentation algorithm to characterize the rise and fall segments in XCO2 seasonal cycles. We present the algorithm for general application of the segmentation analysis and emphasize here that the segmentation analysis is more generally applicable to cyclic time series. We demonstrate the utility of the algorithm with specific results related to the comparison between satellite- and model-derived XCO2 seasonal cycles (2009–2012) for large bioregions across the globe. We found a seasonal amplitude gradient of 0.74–0.77 ppm for every 10∘ of latitude in the satellite data, with similar gradients for rise and fall segments. This translates to a south–north seasonal amplitude gradient of 8 ppm for XCO2, about half the gradient in seasonal amplitude based on surface site in situ CO2 data (∼19 ppm). The latitudinal gradients in the period of the satellite-derived seasonal cycles were of opposing sign and magnitude (−9 d per 10∘ latitude for fall segments and 10 d per 10∘ latitude for rise segments) and suggest that a specific latitude (∼2∘ N) exists that defines an inversion point for the period asymmetry. Before (after) the point of asymmetry inversion, the periods of rise segments are lesser (greater) than the periods of fall segments; only a single model could reproduce this emergent pattern. The asymmetry in amplitude and the period between rise and fall segments introduces a novel pattern in seasonal cycle analyses, but, while we show these emergent patterns exist in the data, we are still breaking ground in applying the information for science applications. Maybe the most useful application is that the segmentation analysis allowed us to decompose the model biases into their correlated parts of biases in amplitude, period and phase independently for rise and fall segments. We offer an extended discussion on how such information about model biases and the emergent patterns in satellite-derived seasonal cycles can be used to guide future inquiry and model development.
The Broadband InfraRed Compact High-resolution Exploration Spectrometer (BIRCHES), which will be described in detail here, is the compact broadband IR spectrometer of the Lunar Ice Cube mission. Lunar Ice Cube is one of 13 6U cubesats that will be deployed by EM1 in cislunar space, qualifying as lunarcubes. The LunarCube paradigm is a proposed approach for extending the affordable CubeSat standard to support access to deep space via cis-lunar/lunar missions. Because the lunar environment contains analogs of most solar system environments, the Moon is an ideal target for both testing critical deep space capabilities and understanding solar system formation and processes. Effectively, as developments are occurring in parallel, 13 prototype deep space cubesats are being flown for EM1. One useful outcome of this ‘experiment’ will be to determine to what extent it is possible to develop a lunarcube ‘bus’ with standardized interfaces to all subsystems using reasonable protocols for a variety of payloads. The lunar ice cube mission was developed as the test case in a GSFC R&D study to determine whether the cubesat paradigm could be applied to deep space, science requirements driven missions, and BIRCHES was its payload. Here, we present the design and describe the ongoing development, and testing, in the context of the challenges of using the cubesat paradigm to fly a broadband IR spectrometer in a 6U platform, including minimal funding and extensive need for leveraging existing assets and relationships on development, the foreshortened schedule for payload delivery on testing, and minimum bandwidth translating into simplified or canned operation.
There is more useful information in the time series of satellite-derived column-averaged carbon dioxide (XCO2) than is typically characterized. Often, the entire time series is treated at once without considering detailed features at shorter timescales, such as nonstationary changes in signal characteristics – amplitude, period and phase. In many instances, signals are visually and analytically differentiable from other portions in a time series. Each rise (increasing) and fall (decreasing) segment in the seasonal cycle is visually discernable in a graph of the time series. The rise and fall segments largely result from seasonal differences in terrestrial ecosystem production, which means that the segment's signal characteristics can be used to establish observational benchmarks because the signal characteristics are driven by similar underlying processes. We developed an analytical segmentation algorithm to characterize the rise and fall segments in XCO2 seasonal cycles. We present the algorithm for general application of the segmentation analysis and emphasize here that the segmentation analysis is more generally applicable to cyclic time series. We demonstrate the utility of the algorithm with specific results related to the comparison between satellite- and model-derived XCO2 seasonal cycles (2009–2012) for large bioregions across the globe. We found a seasonal amplitude gradient of 0.74–0.77 ppm for every 10∘ of latitude in the satellite data, with similar gradients for rise and fall segments. This translates to a south–north seasonal amplitude gradient of 8 ppm for XCO2, about half the gradient in seasonal amplitude based on surface site in situ CO2 data (∼19 ppm). The latitudinal gradients in the period of the satellite-derived seasonal cycles were of opposing sign and magnitude (−9 d per 10∘ latitude for fall segments and 10 d per 10∘ latitude for rise segments) and suggest that a specific latitude (∼2∘ N) exists that defines an inversion point for the period asymmetry. Before (after) the point of asymmetry inversion, the periods of rise segments are lesser (greater) than the periods of fall segments; only a single model could reproduce this emergent pattern. The asymmetry in amplitude and the period between rise and fall segments introduces a novel pattern in seasonal cycle analyses, but, while we show these emergent patterns exist in the data, we are still breaking ground in applying the information for science applications. Maybe the most useful application is that the segmentation analysis allowed us to decompose the model biases into their correlated parts of biases in amplitude, period and phase independently for rise and fall segments. We offer an extended discussion on how such information about model biases and the emergent patterns in satellite-derived seasonal cycles can be used to guide future inquiry and model development.
Sustainable missions, beyond low Earth orbit, will require autonomous capabilities in order to achieve NASA’s Artemis program objectives. Correspondingly, the crew must have a means to efficiently interact with these autonomous systems; this can be facilitated via voice and speech communications. Voice-based controls enable the user to access autonomous systems hands-free/eyes-free, allowing the user to better focus on critical tasks. The goal of this project was to explore the knowledge and technology needed to successfully design effective voice interfaces for autonomous systems. The main objective was to understand how a crew member, through voice interaction, could most efficiently and intuitively communicate with a notional autonomous vehicle system manager. This project leveraged prior research conducted by the University of Michigan’s Bioastronautics and Life Support System (BLiSS) team as part of a NASA Moon to Mars eXploration Systems and Habitation (M2M X-Hab) 2020 Academic Innovation Challenge. The X-Hab 2020 work from the BliSS Team resulted in an intuitive graphical user interface/user experience that was built on an Internet of Things (IOT) platform. The Voice User Interface (VUI) design for the M2M X-Hab 2021 project leveraged this technology and incorporated a voice-based assistant and NASA’s Platform for Autonomous Systems (NPAS) software. This required technologies to convert voice to text, conduct semantic interpretations, and convert responses from the autonomous system to text and to speech; additionally, the background noise environment of spacecraft was assessed, and a relatable personality for the autonomous system to facilitate human-like conversations was created. This work’s success was largely due to the diverse team that included expertise in Space Systems Engineering, Human Computer Interaction, Aerospace Engineering, Computer Science, Biomedical Engineering, and Applied Physics. The differing perspectives fostered elaborate discussions, resulting in the conception of three main interactions: (1) User-System, (2) NPAS-System, and (3) Environment-System. The system developed, i.e. the VUI, had to be unique, efficient, and intuitive; thus, the team crafted a personality for the system to enable human-like conversation. User surveys sent to students and young professionals were used to help determine these personality traits by capturing perspectives and expectations of the “Artemis Generation Astronauts”. To further simulate human-like conversations, the system had to be able to quickly interpret user speech and be able to integrate with NASA’s NPAS system for quick and reliable information transfer. Results of this research include (1) a working prototype user interface, that is compatible with NASA’s NPAS system; (2) software that demonstrates the ability to interpret user requests and respond appropriately; (3) the capability to implement fully expanded conversations between user and system using intuitive communication in four request categories; and (4) software and hardware recommendations that optimize the system’s ability to operate, i.e. be heard, in a noisy environment. The technologies chosen for this project’s demonstrations included the following: Raspberry Pi, RASA, Mozilla Deep Speech, Coqui, RTX Voice and Adobe XD. This work has laid the foundation for the development of VUI’s used for autonomy, and is intended to provide guidance for future VUI development.
The sustainable missions beyond Low Earth Orbit (LEO) envisioned for NASA’s Artemis program will require autonomous capabilities. Moreover, Artemis mission crews will need a means to efficiently interact with a spacecraft’s autonomous systems. This interaction can be facilitated by voice and speech communications because voice-based controls enable users to interact hands- and eyes-free, allowing the user to better focus on critical tasks. The goal of our project was to explore the knowledge and technology needed to successfully design effective Voice User Interfaces (VUIs) for autonomous systems utilizing Human Centered Design (HCD) principles. The focus of the human factors’ aspect of engineering, pays close attention to psychological and physiological principles in the development of autonomous crew operation systems. A main objective was to understand how a crew member, through voice interaction, could efficiently and intuitively communicate with a notional autonomous vehicle system manager. This project was a part of the NASA Moon to Mars eXploration Systems and Habitation (M2M X-Hab) 2020 Academic Innovation Challenge. The work from the BLiSS Team, at the University of Michigan, resulted in the design of a system persona, Diego, to which an astronaut may quickly build trust with autonomous systems, to alleviate known stressors on mental health expected during long duration space missions. Optimal software to facilitate integration of the system persona into a reference Lunar orbiting Gateway station was defined. Additionally, a Speech to Text (STT) system and a Graphical User Interface (GUI) that could be implemented in future missions was developed on an Internet of Things (IOT) platform. The Voice User Interface (VUI) design for the M2M X-Hab 2020 project leveraged previous technology developed by the BLiSS team to incorporate a voice-based interface into NASA’s Platform for Autonomous Systems (NPAS) software. This required technologies to convert voice to text, conduct semantic interpretations, and convert responses from the autonomous system to text and to speech; additionally, the spacecraft background noise environment was assessed, a noise mitigation technique was developed, and a relatable personality for the autonomous system was developed in order to facilitate human-like conversations. The success of our effort was largely due to the diversity of the team that included expertise in Space Systems Engineering, Human Computer Interaction, Aerospace Engineering, Computer Science, Biomedical Engineering, and Applied Physics. The diverse perspectives fostered elaborate discussions, resulting in the conception of three main subsystems: (1) User-System, (2) NPAS-System, and (3) Environment-System. The VUI was unique and had to be efficient and intuitive. For this project, 5 subteams were formed, each with a separate objective, Voice Design team, Background Noise Mitigation team, Software Integration team and Graphical User Interface team. The BLiSS team crafted a personality for the VUI to enable human-like conversation and drive user adoption and trust. User surveys were completed and used to help determine the required VUI system personality traits by capturing perspectives and expectations of prospective “Artemis Generation Astronauts”. To further simulate human-like conversations, the system had to be able to quickly interpret user speech and be able to integrate with NASA’s NPAS platform for quick and reliable information transfer. The outcomes of our research were: (1) a working prototype user interface, that is compatible with NASA’s NPAS platform; (2) software that demonstrates the ability of the VUI system to interpret user requests and respond appropriately; (3) the capability to implement fully expanded conversations between user and system using intuitive communication in four request categories; and (4) software and hardware recommendations that optimize the system’s ability to operate in a noisy environment. Our research has laid the foundation for the development of VUI’s for autonomy, and provides a baseline for future VUI developments.
This research proposal aims to investigate the unique molecular adaptations exhibited by Arabidopsis Thaliana, specifically focusing on the Cape Verde Islands (Cvi-0) ecotype, in response to microgravity conditions. The study examines data from NASA’s Open Science Data Repository and applies a multifaceted RNAseq analysis pipeline using tools in the UseGalaxy.org open platform. Through transcriptomic analysis, differential gene expression patterns were identified in Cvi-0, revealing an absence of heat shock protein (HSP) upregulation and an upregulation of Rubisco Activase (RCA) and chloroplast-related pathways. To test the hypothesis that these adaptations may contribute to Cvi-0’s increased adaptability in microgravity, a three-fold experimental design is proposed. Four experimental groups will be cultivated under simulated microgravity and ground control conditions, including Cvi-0, Col-0, and genetically modified Col-0 with silenced HSP genes, and genetically modified Col-0 with upregulated RCA gene. Growth parameters will be measured to assess plant resilience, and RNA sequencing will provide transcriptomic data for pathway analysis. Anticipated outcomes include improved markers of plant health (mass, growth, etc.) of Cvi-0 in simulated microgravity and enhanced resilience in genetically altered Col-0 variants, providing insights into potential mechanisms of adaptation. This research would bear significance for space agriculture, nutrition for extended space missions, and sustainable terrestrial crop enhancement. Moreover, the insights gained could reshape crop engineering on Earth, enhancing robustness to climate induced stresses and bolstering global food security. The proposal’s trajectory blends scientific curiosity with practical applicability, forging a path towards sustainable food production and improving human exploration beyond our planet.