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This viewgraph presentation explores how NASA can apply the global shift in demographics, the popularity of collaborative technology and the desire for participation to the future of space exploration. Included in this is a review of the evolution of work, the engagement gap, user contribution systems and a case study concerning the "digital astronaut".
The integration of Large Language Models (LLMs) in energy systems research promises transformative results, as demonstrated in this work, particularly in the realms of information retrieval and legal document analysis. We have developed a chat-based interface, specifically designed to query an extensive corpus of technical reports from the National Renewable Energy Laboratory (NREL). This interface capitalizes on the natural language processing capabilities of LLMs, providing future consumers of NREL research with a user-friendly platform to access and extract valuable information from technical documents, thus enhancing the dissemination of research to the public. In addition to information retrieval, we have employed LLMs to extract renewable energy siting ordinances from a variety of legal documents, a task traditionally driven by significant human labor. This automated extraction not only supports the ongoing development of the high-impact NREL siting ordinance database but also ensures the database's accuracy and comprehensiveness. Crucially, we have augmented the performance of LLMs through the integration of a decision tree framework, resulting in a substantial improvement in extraction accuracy. Comparative analysis with manual efforts has shown that this approach not only rivals but also significantly surpasses human accuracy, heralding increased reliability in legal document analysis for energy systems research. To democratize access to these advancements and foster collaborative research, we introduce the "Energy Language Model" (ELM), an open-source software package. ELM encapsulates the methodologies and tools developed in this work, providing researchers and practitioners with a robust toolkit to conduct similar analyses within their respective domains. Through these contributions, this work underscores the immense potential of LLMs in revolutionizing energy systems research, improving accuracy, efficiency, and accessibility in the field.
Solargraf is a cloud-based 3D design tool by Enphase Energy that allows users to design solar and storage systems with a variety of elements. Through a Cooperative Research and Development Agreement (CRADA), Enphase Energy collaborated with the National Renewable Energy Laboratory (NREL) to validate Solargraf's 3D design simulation against measured PV system performance. This study follows the same methodology of similar validation studies completed at NREL. The predicted performance results from simulations in both Solargraf and NREL's System Advisor Model (SAM) tool were compared with measured data to evaluate performance predictions.
The presentation will overview the flight test capabilities at NASA Armstrong Flight Research Center (AFRC), to open up partnership collaboration opportunities for Wireless Community to conduct flight testing of aerospace wireless technologies. Also, it will brief the current activities on wireless sensor system at AFRC through SBIR (Small Business Innovation Research) proposals, and it will show the current areas of interest on wireless technologies that AFRC would like collaborate with Wireless Community to further and testing.
Traditionally, heliophysics is characterized as the study of the near-Earth space environment, where plasmas and neutral gases originating from the Earth, the Sun, and other solar system bodies interact in ways that are detectable only through in-situ or close-range (usually within ~10 AU) remote sensing. As a result, heliophysics has data from the space environment around a handful of solar system objects, in particular the Sun and Earth. Comparatively, astrophysics has data from an extensive array of objects, but is more limited in temporal, spatial, and wavelength information from any individual object. Thus, our understanding of planetary space environments as a complex, multi-dimensional network of specific interacting systems may in the past have seemed to have little to do with the highly diverse space environments detected through astrophysical methods. Recent technological advances have begun to bridge this divide. Exoplanetary studies are opening up avenues to study planetary environments beyond our solar system, with missions like Kepler, TESS, and JWST, along with increasing capabilities of ground-based observations. At the same time, heliophysics studies are pushing beyond the boundaries of our heliosphere with Voyager, IBEX, and the future IMAP mission. The interdisciplinary field of star-exoplanet interactions is a critical, growing area of study that enriches heliophysics. A multidisciplinary approach to heliophysics enables us to better understand universal processes that operate in diverse environments, as well as the evolution of our solar system and extreme space weather. The expertise, data, theory, and modeling tools developed by heliophysicists are crucial in understanding the space environments of exoplanets, their host stars, and their potential habitability. The mutual benefit that heliophysics and exoplanetary studies offer each other depends on strong, continuing solar system-focused and Earth-focused heliophysics studies. The heliophysics discipline requires new targeted funding to support inter-divisional opportunities, including small multi-disciplinary research projects, large collaborative research teams, and observations targeting the heliophysics of planetary and exoplanet systems. Here we discuss areas of heliophysics-relevant exoplanetary research, observational opportunities and challenges, and ways to promote the inclusion of heliophysics within the wider exoplanetary community.
Traditionally, heliophysics is characterized as the study of the near-Earth space environment, where plasmas and neutral gases originating from the Earth, the Sun, and other solar system bodies interact in ways that are detectable only through in-situ or close-range (usually within ∼10 AU) remote sensing. As a result, heliophysics has data from the space environment around a handful of solar system objects, in particular the Sun and Earth. Comparatively, astrophysics has data from an extensive array of objects, but is more limited in temporal, spatial, and wavelength information from any individual object. Thus, our understanding of planetary space environments as a complex, multi-dimensional network of specific interacting systems may in the past have seemed to have little to do with the highly diverse space environments detected through astrophysical methods. Recent technological advances have begun to bridge this divide. Exoplanetary studies are opening up avenues to study planetary environments beyond our solar system, with missions like Kepler, TESS, and JWST, along with increasing capabilities of ground-based observations. At the same time, heliophysics studies are pushing beyond the boundaries of our heliosphere with Voyager, IBEX, and the future IMAP mission. The interdisciplinary field of star-exoplanet interactions is a critical, growing area of study that enriches heliophysics. A multidisciplinary approach to heliophysics enables us to better understand universal processes that operate in diverse environments, as well as the evolution of our solar system and extreme space weather. The expertise, data, theory, and modeling tools developed by heliophysicists are crucial in understanding the space environments of exoplanets, their host stars, and their potential habitability. The mutual benefit that heliophysics and exoplanetary studies offer each other depends on strong, continuing solar system-focused and Earth-focused heliophysics studies. The heliophysics discipline requires new targeted funding to support inter-divisional opportunities, including small multi-disciplinary research projects, large collaborative research teams, and observations targeting the heliophysics of planetary and exoplanet systems. Here we discuss areas of heliophysics-relevant exoplanetary research, observational opportunities and challenges, and ways to promote the inclusion of heliophysics within the wider exoplanetary community.
Superconducting Radio Frequency (SRF) cryomodule assembly is a critical process that demands the highest levels of contamination control in a cleanroom to ensure product quality and reliability. Within the cleanroom environment, human-driven activities remain the major source of uncontrolled particulate. Moreover, the precise manual alignment of components often exceeds expected timeframes, increasing the risk of particulate migration into the critical inner space of the SRF resonant cavity, and causing extended discomfort for workers. Automation comes as a natural solution to address these challenges. The goal of this activity is to set up and integrate a robotic system to support cavity coupler installation in the cleanroom environment. Initially, remote control of a 6-axis collaborative robot arm will be implemented as an introductory step towards automation in the cleanroom. Subsequently, the system will be further enhanced by integrating manipulation capabilities through an appropriate end-effector, and computer vision technology to enable accurate pose estimation. This comprehensive approach aims to achieve a fully automated and adaptable assembly process in the partially structured cleanroom environment, thereby enhancing efficiency and mitigating existing challenges for better product quality and workers safety.
The DUNE Collaboration is conducting an experimental program (named protoDUNE) which involves a beam test of two large-scale prototypes of the DUNE Far Detector at CERN operating in 2018-2019. The volume of data to be collected by the protoDUNE-SP (the single-phase detector) will amount to a few petabytes and the sustained rate of data sent to mass storage is in the range of a few hundred MB per second. After collection the data is committed to storage at CERN and transmitted to Fermi National Accelerator Laboratory in the US for processing, analysis and long-term preservation. The protoDUNE experiment requires substantial Data Quality Monitoring capabilities in order to ascertain the condition of the detector and its various subsystems. We present the design of the protoDUNE Prompt Processing System, its deployment at CERN and its performance during the data challenges and actual data taking.
For exploration of planetary surfaces, detection of water and ice is of great interest in supporting existence of life on other planets. Therefore, a remote Raman spectroscopy system was demonstrated at NASA Langley Research Center in collaboration with University of Hawaii for detecting ice-water and hydrous minerals on planetary surfaces. In this study, a 532 nm pulsed laser is utilized as an excitation source to allow detection in high background radiation conditions. The Raman scattered signal is collected by a 4-inch telescope positioned in front of a spectrograph. The Raman spectrum is analyzed using a spectrograph equipped with a holographic super notch filter to eliminate Rayleigh scattering, and a holographic transmission grating that simultaneously disperses two spectral tracks onto the detector for higher spectral range. To view the spectrum, the spectrograph is coupled to an intensified charge-coupled device (ICCD), which allows detection of very weak Stokes line. The ICCD is operated in gated mode to further suppress effects from background radiation and long-lived fluorescence. The sample is placed at 5.6 m from the telescope, and the laser is mounted on the telescope in a coaxial geometry to achieve maximum performance. The system was calibrated using the spectral lines of a Neon lamp source. To evaluate the system, Raman standard samples such as calcite, naphthalene, acetone, and isopropyl alcohol were analyzed. The Raman evaluation technique was used to analyze water, ice and other hydrous minerals and results from these species are presented.
Finding the subset of a set of imperfect devices (e.g., nano or micro devices) that results in the best aggregate device is a challenging problem. It is an abstraction of what will likely be a major difficulty in designing and controlling systems of nano or micro-scale components, particularly when a large fraction of those components may be unreliable. Rather than approaching this as a passive search problem, we transform the problem into one of coordination in a complex system by imbuing each device with simple decision making ability. In doing so we face the challenge of determining what each component should attempt to do so that the collective behavior solves the overall problem. Furthermore, in this padicular instance, we face problems of scaling (number of components in the thousands to tens of thousands), observability (components have limited sensing capabilities), and reliability (the components are faulty). We present an approach based on deriving component goals that are aligned with the overall system goal (e.g., forming best aggregate device), and can be computed using information readily (e.g., locally) available to the components. Then, each component in such a collective uses a simple reinforcement learning algorithm to selfishly pursue its own goals. Because those goals are derived in a principled manner, there is no need to use external mechanisms to force collaboration or coordination among the components to ensure that the system reaches a globally desirable solution. The results show that not only this approach provides improvements of over an order of magnitude over both traditional search methods and traditional multi-agent methods, but that the gains increase with the size of the system. This latter result makes this method ideal for domains where the number of components is currently in the thousands and will reach millions in the near future.
In 2001, NASA Goddard Space Flight Center's Laboratory for Terrestrial Physics started the construction of a science Investigator-led Processing System (SIPS) for processing data from the Ozone Monitoring Instrument (OMI) which will launch on the Aura platform in mid 2004. The Ozone Monitoring Instrument (OMI) is a contribution of the Netherlands Agency for Aerospace Programs (NIVR) in collaboration with the Finnish Meteorological Institute (FMI) to the Earth Observing System (EOS) Aura mission. It will continue the Total Ozone Monitoring System (TOMS) record for total ozone and other atmospheric parameters related to ozone chemistry and climate. OMI measurements will be highly synergistic with the other instruments on the EOS Aura platform. The LTP previously developed the Moderate Resolution Imaging Spectrometer (MODIS) Data Processing System (MODAPS), which has been in full operations since the launches of the Terra and Aqua spacecrafts in December, 1999 and May, 2002 respectively. During that time, it has continually evolved to better support the needs of the MODIS team. We now run multiple instances of the system managing faster than real time reprocessings of the data as well as continuing forward processing. The new OMI Data Processing System (OMIDAPS) was adapted from the MODAPS. It will ingest raw data from the satellite ground station and process it to produce calibrated, geolocated higher level data products. These data products will be transmitted to the Goddard Distributed Active Archive Center (GDAAC) instance of the Earth Observing System (EOS) Data and Information System (EOSDIS) for long term archive and distribution to the public. The OMIDAPS will also provide data distribution to the OMI Science Team for quality assessment, algorithm improvement, calibration, etc. We have taken advantage of lessons learned from the MODIS experience and software already developed for MODIS. We made some changes in the hardware system organization, database and software to adapt the system for OMI. We replaced the fundamental database system, Sybase, with an Open Source RDBMS called PostgreSQL, and based the entire OMIDAPS on a cluster of Linux based commodity computers rather than the large SGI servers that MODAPS uses. Rather than relying on a central I/O server host, the new system distributes its data archive among multiple server hosts in the cluster. OMI is also customizing the graphical user interfaces and reporting structure to more closely meet the needs of the OMI Science Team. Prior to 2003, simulated OMI data and the science algorithms were not ready for production testing. We initially constructed a prototype system and tested using a 25 year dataset of Total Ozone Mapping Spectrometer (TOMS) and Solar Backscatter Ultraviolet Instrument (SBUV) data. This prototype system provided a platform to support the adaptation of the algorithms for OMI, and provided reprocessing of the historical data aiding in its analysis. In a recent reanalysis of the TOMS data, the OMIDAPS processed 108,000 full orbits of data through 4 processing steps per orbit, producing about 800,000 files (400 GiB) of level 2 and greater data files. More recently we have installed two instances of the OMIDAPS for integration and testing of OM1 science processes as they get delivered from the Science Team. A Test instance of the OMIDAPS has also supported a series of "Interface Confidence Tests" (ICTs) and End-to-End Ground System tests to ensure the launch readiness of the system. This paper will discuss the high-level hardware, software, and database organization of the OMIDAPS and how it builds on the MODAPS heritage system. It will also provide an overview of the testing and implementation of the production OMIDAPS.
New technologies and operational concept changes have been proposed for implementation in the National Airspace System (NAS). These changes include improved datalink (CPDLC) technologies for providing improved weather, traffic, Flight Object (FO) and navigation information to the pilot and controller, and new forms of automation for both the flight deck and air traffic management system. In addition, the way business is conducted in the NAS is under consideration. Increases in the discretion provided to pilots (and dispatchers in commercial airlines) are being contemplated in an effort to increase system capacity and flexibility. New concepts of operation (e.g., Collaborative Decision Making and Free Flight) allow for more control to be given to the cockpit or airline with correspondingly greater monitoring responsibilities on the ground. In addition, new technologies and displays make possible much greater information flow between the ground and the cockpit and also dramatic changes in the type of information provided. Designing to support these changes suggests two integrally linked questions: (1) What display technologies and information are needed to support desired changes responsibilities? (2) How will the changes in information availability influence the negotiation process between the cockpit and the ground? Each of these proposed changes (both in technology and operational concept) will have a marked impact on the performance, workload, and Situation Awareness (SA) of both pilots and controllers. Typically such changes are evaluated independently in terms of the effects of the proposed change on either pilot performance or ATC performance. It is proposed here, however, that in order to fully understand the effects of such changes, the joint pilot/controller system must be considered.
Autonomous decision-making is crucial for enhancing mission effectiveness in Distributed Space Systems (DSS), particularly in multi-spacecraft operations where communication constraints and mission complexity pose challenges. The Distributed Spacecraft Autonomy (DSA) team at NASA’s Ames Research Center is advancing autonomy in DSS through five key technical areas: distributed resource and task management, reactive operations, system modeling and simulation, human-swarm interaction, and ad hoc network communications. The DSA experiment onboard the Starling 1.0 Mission showcases collaborative resource allocation for multi-point science data collection with four small spacecraft. Autonomy in decision-making is highlighted as a crucial factor for multi-spacecraft missions, enabling spacecraft to operate independently, reducing reliance on ground control. This capability is particularly significant for future deep-space missions, where communication delays and limited data transmission capacity make traditional command and control approaches impractical. This demonstration focuses on a GPS Channel Selection Experiment, leveraging emergent capabilities like "shared sampling" and "simultaneous sampling" to optimize channel selection across the spacecraft swarm. The experiment aims to capture ionospheric phenomena such as the Equatorial Ionization Anomaly and Polar Patches. The DSA system's autonomous reconfiguration ability is showcased, emphasizing its adaptability to natural phenomena without significant integration efforts. The GPS Channel Selection Experiment utilizes a dual-band GPS receiver to estimate plasma density in the ionosphere. Explorative and exploitative channel selections are employed based on the nature of observed phenomena. The performance of DSA algorithms is evaluated in terms of optimal channel allocations and responsiveness to changes in observed features. The DSA Flight Software utilizes the Core Flight System (cFS) framework, ensuring compatibility with the Starling 1.0 flight mission software. DSA showcases results from RTI’s Connext DDS Micro communication middleware, enabling message routing over the Ad-Hoc Network of Starling 1.0. This paper provides a comprehensive overview of the DSA experiment's initial results, emphasizing the advancements in autonomy for Distributed Space Systems and the successful collaboration with the Starling 1.0 mission.
The Spacecraft Water Impurity Monitor (SWIM) is a joint collaboration to develop an instrument platform that will perform in-flight measurements and deliver a more complete picture of water quality to decision makers. For exploration missions, returned water samples will not be an option, so spacecraft and habitats will need to be equipped with advanced water monitoring capabilities. Eventually, missions to the moon, Mars, and beyond should be equipped with analytical capabilities roughly analogous to those found in terrestrial labs. Based on what we know about current and future spacecraft environments, SWIM will seek to provide enhanced analytical capability that enables NASA to confidently send astronauts on distant missions without the possibility of returned water samples. The SWIM architecture can be broken down in an Organic Water Module (OWM) and an Inorganic Water Module (IWM), independent of each other but can be flown together if desired; an integrated system may share some commonality, e.g., single sample injection, sampling consumables, waste, etc. Each of these main modules can be broken down further into separation (if required) and detection modules. And, each separation module can be paired with one or more detection module depending on mission, spacecraft, customer needs, and size/mass/power constraints. This paper discusses the research and development progress toward the goal of a total water analysis system. For OWM, one of the analysis technologies that the SWIM team have been developing is a liquid-injection gas chromatograph mass spectrometer system; these systems are the workhorses of analytical chemistry laboratories world-wide. For IWM, the team is exploring a number of technologies ranging from traditional liquid chromatography technologies (e.g. ion chromatography, capillary electrophoresis) to flight-heritage technology such as ion-specific electrodes.
The Spacecraft Water Impurity Monitor (SWIM) is a joint collaboration to develop an instrument platform that will perform in-flight measurements and deliver a more complete picture of water quality to decision makers. For exploration missions, returned water samples will not be an option, so spacecraft and habitats will need to be equipped with advanced water monitoring capabilities. Eventually, missions to the moon, Mars, and beyond should be equipped with analytical capabilities roughly analogous to those found in terrestrial labs. Based on what we know about current and future spacecraft environments, SWIM will seek to provide enhanced analytical capability that enables NASA to confidently send astronauts on distant missions without the possibility of returned water samples. The SWIM architecture can be broken down in an Organic Water Module (OWM) and an Inorganic Water Module (IWM), independent of each other but can be flown together if desired; an integrated system may share some commonality, e.g., single sample injection, sampling consumables, waste, etc. Each of these main modules can be broken down further into separation (if required) and detection modules. And, each separation module can be paired with one or more detection module depending on mission, spacecraft, customer needs, and size/mass/power constraints. This paper discusses the research and development progress toward the goal of a total water analysis system. For OWM, one of the analysis technologies that the SWIM team have been developing is a liquid-injection gas chromatograph mass spectrometer system; these systems are the workhorses of analytical chemistry laboratories world-wide. For IWM, the team is exploring a number of technologies ranging from traditional liquid chromatography technologies (e.g. ion chromatography, capillary electrophoresis) to flight-heritage technology such as ion-specific electrodes.
The Spacecraft Water Impurity Monitor (SWIM) is a joint collaboration to develop an instrument platform that will perform in-flight measurements and deliver a more complete picture of water quality to decision makers. For exploration missions, returned water samples will not be an option, so spacecraft and habitats will need to be equipped with advanced water monitoring capabilities. Eventually, missions to the moon, Mars, and beyond should be equipped with analytical capabilities roughly analogous to those found in terrestrial labs. Based on what we know about current and future spacecraft environments, SWIM will seek to provide enhanced analytical capability that enables NASA to confidently send astronauts on distant missions without the possibility of returned water samples. The SWIM architecture can be broken down in an Organic Water Module (OWM) and an Inorganic Water Module (IWM), independent of each other but can be flown together if desired; an integrated system may share some commonality, e.g., single sample injection, sampling consumables, waste, etc. Each of these main modules can be broken down further into separation (if required) and detection modules. And, each separation module can be paired with one or more detection module depending on mission, spacecraft, customer needs, and size/mass/power constraints. This paper discusses the research and development progress toward the goal of a total water analysis system. For OWM, one of the analysis technologies that the SWIM team have been developing is a liquid-injection gas chromatograph mass spectrometer system; these systems are the workhorses of analytical chemistry laboratories world-wide. For IWM, the team is exploring a number of technologies ranging from traditional liquid chromatography technologies (e.g. ion chromatography, capillary electrophoresis) to flight-heritage technology such as ion-specific electrodes.
The Spacecraft Water Impurity Monitor (SWIM) is a joint collaboration to develop an instrument platform that will perform in-flight measurements and deliver a more complete picture of water quality to decision makers. For exploration missions, returned water samples will not be an option, so spacecraft and habitats will need to be equipped with advanced water monitoring capabilities. Eventually, missions to the moon, Mars, and beyond should be equipped with analytical capabilities roughly analogous to those found in terrestrial labs. Based on what we know about current and future spacecraft environments, SWIM will seek to provide enhanced analytical capability that enables NASA to confidently send astronauts on distant missions without the possibility of returned water samples. The SWIM architecture can be broken down in an Organic Water Module (OWM) and an Inorganic Water Module (IWM), independent of each other but can be flown together if desired; an integrated system may share some commonality, e.g., single sample injection, sampling consumables, waste, etc. Each of these main modules can be broken down further into separation (if required) and detection modules. And, each separation module can be paired with one or more detection module depending on mission, spacecraft, customer needs, and size/mass/power constraints. This paper discusses the research and development progress toward the goal of a total water analysis system. For OWM, one of the analysis technologies that the SWIM team have been developing is a liquid-injection gas chromatograph mass spectrometer system; these systems are the workhorses of analytical chemistry laboratories world-wide. For IWM, the team is exploring a number of technologies ranging from traditional liquid chromatography technologies (e.g. ion chromatography, capillary electrophoresis) to flight-heritage technology such as ion-specific electrodes.
The National Wildlife Federation (NWF) and its Eco-Schools USA program is focused providing an engaging educational experience to help students better understand the essential principles of Earth's systems and the impact of climate change on them. The program is aimed to provide those students with the ability to communicate about climate change and apply knowledge in decision making. To achieve these objectives, the NWF partnered with NASA scientists and developed the Eco-Schools USA Climate Change Connections (CCC) is a 9th-12th grade curriculum. CCC is designed to build upon and utilize the many NASA mission resources, programs, and associated interfaces to enhance authentic learning experiences for both educators and students. It seeks to develop an integrated systems-thinking approach to understanding and acting upon the issue of climate change. In collaboration with mission specialists from ICESat, LandSat, Terra, AQUA, AURA, a cross programmatic curriculum was developed to provide a unified or systems-thinking approach to addressing realworld Earth systems problems (see NWF web page below). In this presentation, we provide an overview of the Climate Change Connections lesson curriculum but focus specifically on a couple of example exercises where NASA data sets are used to teach basic lessons about aspects of the climate system as it pertains to the built environment. In particular, we show how data adapted from NASA’s GEWEX Surface Energy Budget are applied to a lesson in solar energy. These data sets are made available directly through NASA web portals entitled “My NASA Data” and the Prediction of Worldwide Renewable Energy Resource. At the POWER web portal there is a link to the Surface meteorology and Solar Energy web portal providing data sets tailored specifically to the assessment of solar energy resource at any location on the globe. Here, we depict the sources of these data and their subsequent usage in the Eco-Schools USA CCC Lessons.