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NASA NTRS1994

(abstract) MEASURE-Jupiter: Low Cost Missions to Explore Jupiter in the Post-Galileo Era

MEASURE-Jupiter is a new mission concept for the exploration of giant planets, with initial application to Jupiter. By flying sets of lightweight spacecraft with highly focused measurement objectives, it is designed to break the apparent impass in giant planet exploration beyond Cassini. The MEASURE-Jupiter concept is characterized by: 1) intensive exploration of a giant planet system, 2) multiple small missions flown in focused waves using spacecraft costing $100M to $200M, and 3) mission sets launched every 2 to 3 years. Why Jupiter? Jupiter is the most complex planetary system in the Solar System with many scientifically intriguing bodies and phenomena to explore. The Galileo mission will scratch the surface of the exploration of Jupiter, posing many questions for the MEASURE-Jupiter missions to address. Jupiter is also the easiest planet in the Outer Solar System to reach, making possible flight times of 2 years and total mission durations of 3 years or less. Concept design studies have uncovered a number of scientifically rewarding, simple, low-cost mission options. These options have the additional attraction of being able to launch on 2-year trajectories to Jupiter with low-cost Delta II expendable launch vehicles. A partial list of mission concepts studied to date include: Io Very Close Flyby, Jupiter Close Polar Pass, Mini-Orbiters, and Galilean Satellite Penetrators. Key to the realization of the MEASURE-Jupiter missions is the judicious use of the new low power consuming advanced technology and applicable systems from the Pluto Fast Flyby mission spacecraft design. Foremost of the new technologies planned for inclusion are the elements of hybrid solar array/battery power systems which make it possible to perform the identified missions without the need for Radioactive Thermoelectric Generators (RTGs). This relieves the mission design of the attendant programmatic complexities, cost, and constraints attendant with the use of RTGs.

MEASURE-Jupiter Jupiter Pluto Fast Flyby low cost ↗

NASA NTRS2005

MEMS-Based Micro Instruments for In-Situ Planetary Exploration

NASA's planetary exploration strategy is primarily targeted to the detection of extant or extinct signs of life. Thus, the agency is moving towards more in-situ landed missions as evidenced by the recent, successful demonstration of twin Mars Exploration Rovers. Also, future robotic exploration platforms are expected to evolve towards sophisticated analytical laboratories composed of multi-instrument suites. MEMS technology is very attractive for in-situ planetary exploration because of the promise of a diverse and capable set of advanced, low mass and low-power devices and instruments. At JPL, we are exploiting this diversity of MEMS for the development of a new class of miniaturized instruments for planetary exploration. In particular, two examples of this approach are the development of an Electron Luminescence X-ray Spectrometer (ELXS), and a Force-Detected Nuclear Magnetic Resonance (FDNMR) Spectrometer.

micro instruments↗

NASA NTRS2004

Bioinspired Engineering of Exploration Systems (BEES) - its Impact on Future Missions

This paper describes an overview of our "Bioinspired Engineering of Exploration Systems for Mars" ( "BEES for Mars") project. The BEES approach distills selected biologically inspired strategies utilizing motion cues/optic flow, bioinspired pattern recognition, biological visual and neural control systems, bioinspired sensing and communication techniques, and birds of prey inspired search and track algorithmic systems. Unique capabilities so enabled, provide potential solutions to future autonomous robotic space and planetary mission applications. With the first series of tests performed in September 2003, August 2004 and September 2004, we have demonstrated the BEES technologies at the El Mirage Dry Lakebed site in the Mojave Desert using Delta Wing experimental prototypes. We call these test flyers the "BEES flyer", since we are developing them as dedicated test platform for the newly developed bioinspired sensors, processors and algorithmic strategies. The Delta Wing offers a robust airframe that can sustain high G launches and offers ease of compact stowability and packaging along with scaling to small size and low ReynOld's number performance for a potential Mars deployment. Our approach to developing light weight, low power autonomous flight systems using concepts distilled from biology promises to enable new applications, of dual use to NASA and DoD needs. Small in size (0.5 -5 Kg) BEES Flyers are demonstrating capabilities for autonomous flight and sensor operability in Mars analog conditions. The BEES project team spans JPL, NASA Ames, Australian National University (ANU), Brigham Young University(BYU), DC Berkeiey, Analogic Computers Inc. and other institutions. The highlights from our recent flight demonstrations exhibiting new Mission enabling capabilities are described. Further, this paper describes two classes of potential new missions for Mars exploration: (1) the long range exploration missions, and (2) observation missions, for real time imaging of critical ephemeral phenomena, that can be enabled by use of BEES flyers. For example, such flyers can serve as a powerful black-box for critical descent and landing data and enablers for improved science missions complementing and supplementing the existing assets like landers and rovers by providing valuable exploration and quick extended low-altitude aerial coverage of the sites of interest by imaging them and distributing instruments to them. Imaging done by orbiters allows broad surface coverage at limited spatial resolution. Low altitude air-borne exploration of Mars offers a means for imaging large areas, perhaps up to several hundred kilometers, quickly and efficiently, providing a close-up birds-eye view of the planetary terrain and close-up approach to constrained difficult areas like canyons and craters. A novel approach to low-mass yet highly capable flyers is enabled by small aircraft equipped using sensors and processors and algorithms developed using BEES technology. This project is focused towards showing the direct impact of blending the best of artificial intelligence attributes and bioinspiration to create a leap beyond existing capability for our future Missions.

navigation↗

NASA NTRS2005

Micro-Inspector Spacecraft for Space Exploration Missions

NASA is seeking to embark on a new set of human and robotic exploration missions back to the Moon, to Mars, and destinations beyond. Key strategic technical challenges will need to be addressed to realize this new vision for space exploration, including improvements in safety and reliability to improve robustness of space operations. Under sponsorship by NASA's Exploration Systems Mission, the Jet Propulsion Laboratory (JPL), together with its partners in government (NASA Johnson Space Center) and industry (Boeing, Vacco Industries, Ashwin-Ushas Inc.) is developing an ultra-low mass (<3.0 kg) free-flying micro-inspector spacecraft in an effort to enhance safety and reduce risk in future human and exploration missions. The micro-inspector will provide remote vehicle inspections to ensure safety and reliability, or to provide monitoring of in-space assembly. The micro-inspector spacecraft represents an inherently modular system addition that can improve safety and support multiple host vehicles in multiple applications. On human missions, it may help extend the reach of human explorers, decreasing human EVA time to reduce mission cost and risk. The micro-inspector development is the continuation of an effort begun under NASA's Office of Aerospace Technology Enabling Concepts and Technology (ECT) program. The micro-inspector uses miniaturized celestial sensors; relies on a combination of solar power and batteries (allowing for unlimited operation in the sun and up to 4 hours in the shade); utilizes a low-pressure, low-leakage liquid butane propellant system for added safety; and includes multi-functional structure for high system-level integration and miniaturization. Versions of this system to be designed and developed under the H&RT program will include additional capabilities for on-board, vision-based navigation, spacecraft inspection, and collision avoidance, and will be demonstrated in a ground-based, space-related environment. These features make the micro-inspector design unique in its ability to serve crewed as well as robotic spacecraft, well beyond Earth-orbit and into arenas such as robotic missions, where human teleoperation capability is not locally available.

microspacecraft↗

NASA NTRS2012

PHOBOS Exploration using Two Small Solar Electric Propulsion Spacecraft

Primitive bodies are exciting targets for exploration as they provide clues to the early Solar system conditions and dynamical evolution. The two moons of Mars are particularly interesting because of their proximity to an astrobiological target. However, after four decades of Mars exploration, their origin and nature remain enigmatic. In addition, when considering the long-term objectives of the flexible path for the potential human exploration to Mars, Phobos and Deimos present exciting intermediate opportunities without the complication and expense of landing and ascending from the surface. As interest in these targets for the next frontier of human exploration grows, characterization missions designed specifically to examine surface properties, landing environments, and surface mapping prior to human exploration are becoming increasingly important. A precursor mission concept of this sort has been developed using two identical spacecraft designed from low cost, flight proven and certified off-the-shelf component and utilizing Solar Electric Propulsion (SEP) to orbit both targets as secondary payloads launched aboard any NASA or GTO launch. This precursor mission has the potential to address both precursor measurements that are strategic knowledge gaps and decadal science, including soil physical properties at the global and local (human) scale and the search for in situ resources.

Phobos↗

NASA NTRS2017

Lunar Exploration Missions Since 2006

The announcement of the Vision for Space Exploration in 2004 sparked a resurgence in lunar missions worldwide. Since the publication of the first "New Views of the Moon" volume, as of 2017 there have been 11 science-focused missions to the Moon. Each of these missions explored different aspects of the Moon's geology, environment, and resource potential. The results from this flotilla of missions have revolutionized lunar science, and resulted in a profoundly new emerging understanding of the Moon. The New Views of the Moon II initiative itself, which is designed to engage the large and vibrant lunar science community to integrate the results of these missions into new consensus viewpoints, is a direct outcome of this impressive array of missions. The "Lunar Exploration Missions Since 2006" chapter will "set the stage" for the rest of the volume, introducing the planetary community at large to the diverse array of missions that have explored the Moon in the last decade. Content: This chapter will encompass the following missions: Kaguya; ARTEMIS (Acceleration, Reconnection, Turbulence, and Electrodynamics of the Moon’s Interaction with the Sun); Chang’e-1; Chandrayaan-1; Moon Impact Probe; Lunar Reconnaissance Orbiter (LRO); Lunar Crater Observation Sensing Satellite (LCROSS); Chang’e-2; Gravity Recovery and Interior Laboratory (GRAIL); Lunar Atmosphere and Dust Environment Explorer (LADEE); Chang’e-3.

LUNAR EXPLORATION MISSIONS 200↗

NASA NTRS2014

Scientific Rationale for Saturn's in Situ Exploration

Remote sensing observations meet some limitations when used to study the bulk atmospheric composition of the giant planets of our solar system. A remarkable example of the superiority of in situ probe measurements is illustrated by the exploration of Jupiter, where key measurements such as the determination of the noble gases׳ abundances and the precise measurement of the helium mixing ratio have only been made available through in situ measurements by the Galileo probe. This paper describes the main scientific goals to be addressed by the future in situ exploration of Saturn placing the Galileo probe exploration of Jupiter in a broader context and before the future probe exploration of the more remote ice giants. In situ exploration of Saturn's atmosphere addresses two broad themes that are discussed throughout this paper: first, the formation history of our solar system and second, the processes at play in planetary atmospheres. In this context, we detail the reasons why measurements of Saturn's bulk elemental and isotopic composition would place important constraints on the volatile reservoirs in the protosolar nebula. We also show that the in situ measurement of CO (or any other disequilibrium species that is depleted by reaction with water) in Saturn's upper troposphere may help constraining its bulk O/H ratio. We compare predictions of Jupiter and Saturn's bulk compositions from different formation scenarios, and highlight the key measurements required to distinguish competing theories to shed light on giant planet formation as a common process in planetary systems with potential applications to most extrasolar systems. In situ measurements of Saturn's stratospheric and tropospheric dynamics, chemistry and cloud-forming processes will provide access to phenomena unreachable to remote sensing studies. Different mission architectures are envisaged, which would benefit from strong international collaborations, all based on an entry probe that would descend through Saturn's stratosphere and troposphere under parachute down to a minimum of 10 bar of atmospheric pressure. We finally discuss the science payload required on a Saturn probe to match the measurement requirements.

Galileo↗

NASA NTRSDate not supplied

Future Homes in Space: Development of Concepts for Exploration Space Habitats

NASA’s Artemis campaign seeks to return humans to the moon and establish a sustained presence on the lunar surface. This session will emphasize how habitation capabilities on the moon and in cislunar space can potentially contribute to the sustainability objectives of Artemis. Habitable elements represent opportunities to enable longer duration stays, increase the number of crew members present, enhance science and utilization activities, drive technology development for future Mars exploration, perform analog missions, and fuel economic opportunities for US industry. Panelists include Paul Kessler (NASA Marshall Space Flight Center, deputy lead for lunar surface habitation); Andrew Choate (NASA Marshall Space Flight Center, Mars habitation lead); Krystofer Dudzinski (NASA Marshall Space Flight Center, a space architect within the MSFC Advanced Concepts Office); and Larry Toups (retired from NASA Johnson Space Center, currently an adjunct professor at University of Houston in space architecture). The panel is moderated by Tracie Prater (NASA Marshall Space Flight Center, Habitation Systems Development Office). The panel will begin with an overview of the history of habitation concepts and an academic perspective on general considerations in space habitat design (Larry Toups). Paul Kessler and Andrew Choate will introduce NASA’s principle of “architecting from the right” to help define objectives for Artemis missions, needs/characteristics, use cases, and functions (as published in the agency’s Architecture Definition Document) and provide perspective on how this principle informs habitation concept development work. NASA panelists will discuss key engineering challenges identified for developing, deploying, and operating habitable assets on the lunar surface and/or in deep space. These may include dust mitigation, outfitting of inflatable softgoods (for concepts which may use softgoods as a primary structural material), survival in lunar darkness, human health and performance considerations, maintenance/repair/sparing, and autonomy. These identified challenges represent risks for habitation systems development and relate closely to capability gaps identified by the agency. While the work of NASA Marshall Space Flight Center’s habitation development office is primarily focused on habitats which are launched from earth pre-integrated (referred to as Class I in the framework previously developed by NASA space architects Kennedy/Cohen) or launched from earth and deployed at the point of use (Class II), there is also extensive work in NASA, academia, and companies on constructed habitats, which would be built on a planetary surface using indigenous resources (Class III habitats). Panelist Krystopher Dudzinski will discuss potential evolutionary pathways from Class I and Class II habitats to Class III habitats, unique and common architectural challenges within each habitat class, and key gaps in implementing Class III habitats from an architectural perspective. NASA panelists and the moderator will also provide an overview of partnership opportunities and avenues for further engagement to advance habitation systems for the SpaceCom audience. NASA is currently developing notional concepts for a lunar surface habitat and Mars transit habitat, which will be discussed during this panel session and used as examples. These concepts represent options for habitation system design and are a point of departure. They do not represent a final plan or formal recommendation on the part of the agency. Based on the most recent analysis cycle, NASA’s lunar surface habitat (SH) concept nominally supports two crew members for 30 days, with the capacity to support four crew during a surge period where crew will swap between the SH and another surface asset, such as a pressurized rover. This example design has a metallic airlock for ingress/egress and the upper portion is an inflatable material system which serves as the habitation module. The notional interior of the habitat is a three-deck layout/configuration which supports all crew mission functions, including exercise, stowage, extravehicular activity (EVA), sleep, hygiene waste collection, maintenance and repair, and meal preparation. Under analysis assumptions for habitation, the Mars Transit Habitat (TH) concept would support four crew on an up to 1,200 day Mars mission. One option for the concept is to initially dock Transit Habitat at Gateway, where it can be used to increase the duration of crew stays in cislunar space and perform shakedown and analog missions prior to a Mars departure. One challenge in longer duration missions which involve both surface exploration and transit is understanding crew adaptation when transitioning between partial gravity and microgravity environments. TH at Gateway offers an opportunity to study this transition and in doing so reduce risks associated with future Mars exploration. Like lunar SH, the most recent analysis cycle concept of a Mars TH is a hybrid structure design, with a metallic section supporting EVAs, axial/radial docking, and Safe Haven capabilities, and an inflatable softgoods structure for the primary habitation function. Interior layouts to optimize crew usability and livability are currently under trade. The panel will include presentation material, but also seeks to engage the audience in a highly interactive conversation regarding the potential role for habitation in future exploration initiatives. Potential topics for discussion include the influence of the crew experience on habitation systems design and livability/usability considerations, the benefits of space habitation development in terrestrial applications, and challenges and opportunities in “feeding forward” lunar surface habitation systems development to Mars exploration.

space habitats↗

DOE OSTI2014

Geothermal Exploration Case Studies on OpenEI (Presentation)

The U.S. Geological Survey (USGS) resource assessment (Williams et al., 2008) outlined a mean 30 GWe of undiscovered hydrothermal resource in the western United States. One goal of the U.S. Department of Energy's (DOE) Geothermal Technology Office (GTO) is to accelerate the development of this undiscovered resource. DOE has focused efforts on helping industry identify hidden geothermal resources to increase geothermal capacity in the near term. Increased exploration activity will produce more prospects, more discoveries, and more readily developable resources. Detailed exploration case studies akin to those found in oil and gas (e.g. Beaumont and Foster, 1990-1992) will give developers central location for information gives models for identifying new geothermal areas, and guide efficient exploration and development of these areas. To support this effort, the National Renewable Energy Laboratory (NREL) has been working with GTO to develop a template for geothermal case studies on the Geothermal Gateway on OpenEI. In 2012, the template was developed and tested with two case studies: Raft River Geothermal Area (http://en.openei.org/wiki/Raft_River_Geothermal_Area) and Coso Geothermal Area (http://en.openei.org/wiki/Coso_Geothermal_Area). In 2013, ten additional case studies were completed, and Semantic MediaWiki features were developed to allow for more data and the direct citations of these data. These case studies are now in the process of external peer review. In 2014, NREL is working with universities and industry partners to populate additional case studies on OpenEI. The goal is to provide a large enough data set to start conducting analyses of exploration programs to identify correlations between successful exploration plans for areas with similar geologic occurrence models.

15 GEOTHERMAL ENERGY↗

DOE OSTI2013

Analysis of Gaps in Geothermal Exploration Data in the Western United States

The USGS Resource Assessment (Williams et al. 2008) outlined a mean 30 GW, of Undiscovered Hydrothermal Resource in the western U.S. One goal of the Geothermal Technology Office (GTO) is to accelerate the development of this undiscovered resource. To help guide its future data collection efforts, GTO funded a data gap analysis in FY2012 to identify high potential hydrothermal areas where critical data are needed. For the gap analysis, information was collected about existing data and data coverage maps were created with this information. Next, these maps were compared with the USGS resource potential maps to identify priority sites for exploration data collection. Though there are many types of data that can be used for hydrothermal exploration, five types of exploration data were targeted for this analysis. These data types were elected for their regional reconnaissance potential, and include many of the primary exploration echniques currently used by the geothermal industry. The data types include: 1) well data; 2) geologic maps; 3) fault maps; 4) geochemistry data; and 5) geophysical data. To determine data coverage, metadata for exploration data (including data type, data status, and coverage information) were collected and catalogued. Many industry, university, laboratory, and agency personnel were contacted in order to collect metadata for this effort. Data and metadata provided by the contributors to the National Geothermal Data System (NGDS) were also incorporated in the gap analysis. An online tool was developed to allow all geothermal data providers to directly add metadata themselves and view the results of the analys is via maps of data coverage in Geothermal Prospector (http://maps.nrel.gov/gt_prospector). A grid of the contiguous U.S. was created with 88,000 10-km by 10-km grid cells, and each cell was populated with the status of data availability corresponding to the five data types. Using these five data coverage maps and the USGS Resource Potential Map, sites were identified for future data collection efforts. These sites signify both that the USGS has indicated high favorability of occurrence of geothermal resources and that data gaps exist.

15 GEOTHERMAL ENERGY↗

DOE OSTI2021

RhizoVision Explorer: open-source software for root image analysis and measurement standardization

Abstract Roots are central to the function of natural and agricultural ecosystems by driving plant acquisition of soil resources and influencing the carbon cycle. Root characteristics like length, diameter and volume are critical to measure to understand plant and soil functions. RhizoVision Explorer is an open-source software designed to enable researchers interested in roots by providing an easy-to-use interface, fast image processing and reliable measurements. The default broken roots mode is intended for roots sampled from pots and soil cores, washed and typically scanned on a flatbed scanner, and provides measurements like length, diameter and volume. The optional whole root mode for complete root systems or root crowns provides additional measurements such as angles, root depth and convex hull. Both modes support providing measurements grouped by defined diameter ranges, the inclusion of multiple regions of interest and batch analysis. RhizoVision Explorer was successfully validated against ground truth data using a new copper wire image set. In comparison, the current reference software, the commercial WinRhizo™, drastically underestimated volume when wires of different diameters were in the same image. Additionally, measurements were compared with WinRhizo™ and IJ_Rhizo using a simulated root image set, showing general agreement in software measurements, except for root volume. Finally, scanned root image sets acquired in different labs for the crop, herbaceous and tree species were used to compare results from RhizoVision Explorer with WinRhizo™. The two software showed general agreement, except that WinRhizo™ substantially underestimated root volume relative to RhizoVision Explorer. In the current context of rapidly growing interest in root science, RhizoVision Explorer intends to become a reference software, improve the overall accuracy and replicability of root trait measurements and provide a foundation for collaborative improvement and reliable access to all.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

Automated Design Space Exploration with Aspen

Architects and applications scientists often use performance models to explore a multidimensional design space of architectural characteristics, algorithm designs, and application parameters. With traditional performance modeling tools, these explorations forced users to first develop a performance model and then repeatedly evaluate and analyze the model manually. These manual investigations proved laborious and error prone. More importantly, the complexity of this traditional process often forced users to simplify their investigations. To address this challenge of design space exploration, we extend our Aspen (Abstract Scalable Performance Engineering Notation) language with three new language constructs: user-defined resources, parameter ranges, and a collection of costs in the abstract machine model. Then, we use these constructs to enable automated design space exploration via a nonlinear optimization solver. We show how four interesting classes of design space exploration scenarios can be derived from Aspen models and formulated as pure nonlinear programs. The analysis tools are demonstrated using examples based on Aspen models for a three-dimensional Fast Fourier Transform, the CoMD molecular dynamics proxy application, and the DARPA Streaming Sensor Challenge Problem. Our results show that this approach can compose and solve arbitrary performance modeling questions quickly and rigorously when compared to the traditional manual approach.

Spafford, Kyle L.↗

DOE OSTI2021

Exploration ToolKit (ExTK)

The Exploration Toolkit (ExTK) is a reusable Extended Reality (XR) system developed for incorporating and exploring 3-Dimensional (3-D) computer aided design (CAD) models in XR, with a primary focus on Augmented Reality (AR). The ExTK consists of a Developer Mode and a User Mode. In Developer Mode, ExTK provides developers with the ability to easily import 3-D CAD models and activate desired exploration functionality and layout. Multiple models can be added to a single instantiation of the ExTK using Unity's Scene capability. Exploration functions include scaling, rotating, explode/contract, animations, hiding parts, submodules, and measurement functions. In User Mode, ExTK provides a menu system that allows users to select models and initiate exploration functions. ExTK is architected for reusability and developers can customize the ExTK layout and functions according to application needs. ExTK is designed to be hardware agnostic, although initial development focused on the Microsoft HoloLens as the primary deployment platform. The ExTK is developed using the Unity Game Engine Development Platform. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-1506 O

Klein, BrandonThorin↗

DOE OSTI2020

GBCGE Subsurface Database Explorer and APIs

This submission defines a DOI for the Great Basin Center for Geothermal Energy's (GBCGE) Subsurface Database Explorer web application and underlying data services, and acknowledges the INGENIOUS project as a major source of funding for data compilation and quality assurance. The GBCGE Subsurface Database Explorer is an interactive web mapping application that provides public access to the GBCGE Subsurface Database, and its collection of datasets pertinent to geothermal exploration, oil and gas exploration, critical mineral exploration, and other subsurface characterization for the Great Basin Region, western US. This is a living database, and will be continuously updated with new data and datasets as funding and motivations allow. The underlying database views that populate the web application are on an automated refresh schedule. Data sources and acknowledgements: We thank our partners with the Nevada Division of Minerals (NDOM), the Southern Methodist University (SMU), and Great Basin State Geological Surveys for their active efforts in data curation, schema design, and quality assurance. We also thank contributors among the USGS, Oregon Institute of Technology, State Divisions of Water Resources, State Divisions of Oil, Gas, and Minerals, and State Geological Surveys for open data availability and direct contributions made under the National Geothermal Data System (NGDS).

15 GEOTHERMAL ENERGY↗

DOE OSTI2022

GeoThermalCloud: Machine Learning for Geothermal Resource Exploration

Geothermal is a renewable energy source that can provide reliable and flexible electricity generation for the world. In the past decade, the U.S. Geological Survey's resource assessments, Play Fairway Analyses (PFA), and GeoVision report by the U.S. Department of Energy's Geothermal Technologies Office provided insights on enormous untapped potential for geothermal energy to contribute to the U.S. domestic energy needs. The past studies identified that geothermal resources without surface expression (e.g., blind/hidden hydrothermal systems) comprise a huge potential. These blind systems can significantly increase power generation. But a primary challenge is locating and quantifying these hidden resources, which do not have any thermal manifestations on the surface. PFA has successfully identified some blind systems in the western USA (e.g., specific locations in the Great Basin region within Nevada). However, a comprehensive search for these blind systems can be time-consuming, expensive, and resource-intensive with a low probability of success. Accelerated discovery of these blind resources is needed with growing energy needs and higher chances of exploration success. Recent advances in machine learning (ML) have shown promise in shortening the timeline for this discovery. This paper presents a novel ML-based methodology for geothermal exploration towards PFA applications. Our methodology is provided through our open-source ML framework called GeoThermalCloud \url{https://github.com/SmartTensors/GeoThermalCloud.jl}. GeoThermalCloud uses a series of unsupervised, supervised, and physics-informed ML methods available in SmartTensors AI platform \url{https://github.com/SmartTensors}. Here, the presented analyses are performed using our unsupervised ML algorithm called NMF$k$, which is available in the SmartTensors AI platform. Our ML algorithm facilitates the discovery of new phenomena, hidden patterns, and mechanisms that helps us to make informed decisions. Moreover, the GeoThermalCloud enhances the collected PFA data and discovers signatures representative of geothermal resources. Through GeoThermalCloud, we were able to identify hidden patterns in the geothermal field data needed for the efficient discovery of blind systems. Crucial geothermal signatures often overlooked in traditional PFA are extracted using GeoThermalCloud and analyzed by the subject matter experts to provide ML-enhanced PFA, which is informative for efficient exploration. We applied our ML methodology on various open-source geothermal datasets within the U.S. (some of these are collected by past PFA work), and the results provide valuable insights on resource types within those explored regions. This ML-enhanced workflow makes GeoThermalCloud attractive for the geothermal community to improve existing datasets and extract valuable information often unnoticed during geothermal exploration.

machine learning (ML), geothermal energy↗

DOE OSTI2021

Geo Thermal Cloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The project is motivated by the challenges, risks, and costs associated with geothermal exploration and production. Many processes and parameters impacting geothermal conditions are poorly understood. Diverse datasets are available to help characterize subsurface geothermal conditions (public and proprietary; satellite, airborne surveys, vegetation/water sampling, geological, geophysical, etc.). Yet, it is not clear how to properly leverage these datasets for geothermal exploration due to an incomplete understanding of how physical processes impacting subsurface geothermal conditions are represented in these observations. Recent advancements in machine learning (ML) provide great promise to resolve these issues. The tremendous challenges and risks of geothermal exploration and production bring the demand for novel ML methods and tools that can (1) analyze large field datasets, (2) assimilate model simulations (large inputs and outputs), (3) process sparse datasets, (4) perform transfer learning (between sites with different exploratory levels), (5) extract hidden geothermal signatures in the field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. Our goals and work under Phases 1 and 2 (as proposed) of this project address all these needs.

15 GEOTHERMAL ENERGY↗

DOE OSTI2024

Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The primary goals of this project are identifying hidden geothermal resources in the USA and designing profitable enhanced geothermal systems (EGS). Many non-obvious processes and parameters could characterize geothermal resources and could control the ultimate energy potential of geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize geothermal resources, but this data is sparse and multi-scale. This has hindered attempts to leverage the datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) give promise to overcome these issues. Modern ML methods and tools can (1) analyze large datasets, (2) assimilate model ensembles that include a multitude of inputs and outputs, (3) process sparse datasets, (4) perform transfer learning between sites with different data quality, (5) extract hidden geothermal signatures from field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. In this work, we implement ML-based geothermal exploration and an enhanced geothermal systems (EGS) design tool to achieve the above goals. Our exploration tool is GeoThermalCloud (GTC) EGS design tool is GeoDT-ML. GTC (github.com/SmartTensors/GeoThermalCloud.jl) utilizes a LANL unsupervised ML platform called SmartTensors (https://tensors.lanl.gov/) to automate data analyses and interpretations by extracting hidden signatures to identify geothermal prospects. It enables the identification of critical measurements needed to identify geothermal resource signatures. GeoDT-ML (github.com/SmartTensors/GeoThermalCloud.jl/tree/master/) adds coupling to GeoDT (https://github.com/GeoDesignTool/GeoDT.git) for stochastic EGS design optimization and performance prediction. GeoDT-ML leverages recent advances in deep learning and high-performance computing. Contributors to this effort include LANL, PNNL, Google, Stanford, and Julia Computing.

15 GEOTHERMAL ENERGY↗

DOE OSTI2017

Theoretical Models of Optical Transients. I. A Broad Exploration of the Duration–Luminosity Phase Space

The duration–luminosity phase space (DLPS) of optical transients is used, mostly heuristically, to compare various classes of transient events, to explore the origin of new transients, and to influence optical survey observing strategies. For example, several observational searches have been guided by intriguing voids and gaps in this phase space. However, we should ask, do we expect to find transients in these voids given our understanding of the various heating sources operating in astrophysical transients? In this work, we explore a broad range of theoretical models and empirical relations to generate optical light curves and to populate the DLPS. We explore transients powered by adiabatic expansion, radioactive decay, magnetar spin-down, and circumstellar interaction. For each heating source, we provide a concise summary of the basic physical processes, a physically motivated choice of model parameter ranges, an overall summary of the resulting light curves and their occupied range in the DLPS, and how the various model input parameters affect the light curves. We specifically explore the key voids discussed in the literature: the intermediate-luminosity gap between classical novae and supernovae, and short-duration transients (≲10 days). We find that few physical models lead to transients that occupy these voids. Moreover, we find that only relativistic expansion can produce fast and luminous transients, while for all other heating sources events with durations ≲10 days are dim (M{sub R}≳−15 mag). Finally, we explore the detection potential of optical surveys (e.g., Large Synoptic Survey Telescope) in the DLPS and quantify the notion that short-duration and dim transients are exponentially more difficult to discover in untargeted surveys.

79 ASTRONOMY AND ASTROPHYSICS↗