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At least 361 records · Page 20

Artificial Intelligence (AI) Methods for Augmenting the IMPACT Tool Evidence Library

Development of the Evidence Library for use with the IMPACT probability risk assessment tool took several years and involved a staggering amount of effort from a multi-disciplinary team. A very significant amount of the labor effort to collect, assess and finalize the Clinical Finding Form (CliFF) for each of the 119 medical conditions was provided by physician subject matter experts from the Exploration Medical Capability (ExMC) Element Clinical and Science Team. Many AI tools such as ChatGPT are excellent at summarizing large amounts of information and the current project was initiated to determine how such tools might streamline laborious processes, e.g., review and summarization of many scientific research publications, to execute key steps more efficiently in the process of developing CliFFs. The process for collecting the evidence which is found in the CliFFs is well documented in the Evidence Library Methods document (ELM; HRP-48036*). Using ELM and the CliFF development instructions as a guideline, a team of developers is leveraging Microsoft Azure AI tools and services along with open-source frameworks, to construct an AI-assisted automated pipeline. This pipeline is designed to search, retrieve, and process the necessary data sources, and ultimately help generate the final version of a CliFF. Currently, the large language model evaluates the relevance of each source material to spaceflights, either as direct evidence or as an analog. Additionally, the model assists in extracting keywords and generating brief summaries to enhance augmented retrieval and search processes in later stages of CliFF development. Once the data is ready, the model can perform semantic search and retrieval, generating and extracting valuable information for the CliFF. For instance, it can handle epidemiological statistical data, such as incidence rates and the likelihood of best or worst-case scenarios. The steps that required reading and summarizing articles were viewed as providing the greatest return on investment since large language models are very efficient and accurate in summarizing large amounts of text. Since labor effort to complete the original CliFF was not recorded with sufficient granularity, comparisons with an AI tool-generated CliFF will provide merely an approximation of time saved. Upon completion of the process, the CliFF for the medical condition “appendicitis” generated with the support of AI-based methods will serve as a proof-of-concept and will be compared to the original appendicitis CliFF to determine if use of the tools resulted in content and conclusory similarity. Based upon the results from face validation of the two CliFFs, modifications to the process will be made if necessary and additional condition CliFFs will be evaluated. Ultimately, CliFFs for the entire set of medical conditions will be created with the assistance of AI tools. Depending on the cost savings realized, CliFFs for additional medical conditions can be created to expand the Evidence Library. Future direction includes specifying the characteristics of the reviewer (prompting the AI tools to generate output assuming the reviewer is a sub-specialist physician, or nurse or EMT/medic) to determine if the effects on AI-generated output are different based on knowledge, skills and abilities. *Exploration Medical Capability Evidence Library Methods, HRP-48036 Rev A, July 2022.

Ali Al↗

Usage of ChatGPT for Engineering Design and Analysis Tool Development

ChatGPT, a generative AI large language model, has recently captured significant attention in both the computer science community and the broader public domain. It has demonstrated a wide range of capabilities, from answering simple questions to writing fully functional computer code. This study spotlights both the capabilities and limitations of ChatGPT when addressing engineering problems. The model's capacity to generate practical engineering tools is highlighted through an example of a prompt that leads to an interactive plotting tool, enabling the examination of the fluid boundary layer around a fan blade. Subsequently, the paper also uncovers potential pitfalls in ChatGPT’s application, shown through an unsuccessful attempt to use ChatGPT to automate a process in Ansys Workbench through scripting. The research further investigates ChatGPT's proficiency in addressing inquiries and providing explanations about the functionalities of OpenMDAO, an open-source, multidisciplinary design, analysis, and optimization tool developed at NASA Glenn Research Center. Finally, an optimization methodology, developed with ChatGPT’s help, is applied to the structural optimization of a fan blade. The developed optimization method utilizes T-Blade3 for geometry generation, Ansys Mechanical for meshing and finite element analysis, and sci-kit learn’s MLPRegressor method to generate a trained neural network model of the design space. OpenMDAO is then used to find the optimal point within the design space. The outcome is a significant reduction in stress in the optimized model—less than one-fifth of the stress value in the baseline model.

Design↗

Usage of ChatGPT for Engineering Design and Analysis Tool Development

ChatGPT, a generative AI large language model, has recently captured significant attention in both the computer science community and the broader public domain. It has demonstrated a wide range of capabilities, from answering simple questions to writing fully functional computer code. This study spotlights both the capabilities and limitations of ChatGPT when addressing engineering problems. The model's capacity to generate practical engineering tools is highlighted through an example of a prompt that leads to an interactive plotting tool, enabling the examination of the fluid boundary layer around a fan blade. Subsequently, the paper also uncovers potential pitfalls in ChatGPT’s application, shown through an unsuccessful attempt to use ChatGPT to automate a process in Ansys Workbench through scripting. The research further investigates ChatGPT's proficiency in addressing inquiries and providing explanations about the functionalities of OpenMDAO, an open-source, multidisciplinary design, analysis, and optimization tool developed at NASA Glenn Research Center. Finally, an optimization methodology, developed with ChatGPT’s help, is applied to the structural optimization of a fan blade. The developed optimization method utilizes T-Blade3 for geometry generation, Ansys Mechanical for meshing and finite element analysis, and sci-kit learn’s MLPRegressor method to generate a trained neural network model of the design space. OpenMDAO is then used to find the optimal point within the design space. The outcome is a significant reduction in stress in the optimized model—less than one-fifth of the stress value in the baseline model.

Design↗

A Comparative Study of a 1/4-Scale Gulfstream G550 Aircraft Nose Gear Model

A series of fluid dynamic and aeroacoustic wind tunnel experiments are performed at the University of Florida Aeroacoustic Flow Facility and the NASA-Langley Basic Aerodynamic Research Tunnel Facility on a high-fidelity -scale model of Gulfstream G550 aircraft nose gear. The primary objectives of this study are to obtain a comprehensive aeroacoustic dataset for a nose landing gear and to provide a clearer understanding of landing gear contributions to overall airframe noise of commercial aircraft during landing configurations. Data measurement and analysis consist of mean and fluctuating model surface pressure, noise source localization maps using a large-aperture microphone directional array, and the determination of far field noise level spectra using a linear array of free field microphones. A total of 24 test runs are performed, consisting of four model assembly configurations, each of which is subjected to three test section speeds, in two different test section orientations. The different model assembly configurations vary in complexity from a fully-dressed to a partially-dressed geometry. The two model orientations provide flyover and sideline views from the perspective of a phased acoustic array for noise source localization via beamforming. Results show that the torque arm section of the model exhibits the highest rms pressures for all model configurations, which is also evidenced in the sideline view noise source maps for the partially-dressed model geometries. Analysis of acoustic spectra data from the linear array microphones shows a slight decrease in sound pressure levels at mid to high frequencies for the partially-dressed cavity open model configuration. In addition, far field sound pressure level spectra scale approximately with the 6th power of velocity and do not exhibit traditional Strouhal number scaling behavior.

Khorrami, Mehdi R.↗

NASA biological and physical sciences databases: who’s the FAIRest of them all?

Conceptual models are a key part of the foundation of scientific study. Scientific data discovery and retrieval are often inaccurate and incomplete because these models are not sufficiently well-incorporated into data retrieval systems. Systems often don’t provide the necessary tools to those producing scientific data to fully and unambiguously annotate them and the result is consumers of the data cannot find them efficiently. The capability of data archives to provide these tools to link data to underlying conceptual models is one of dimensions of the recently developed “FAIR” principles (https://www.go-fair.org/fair-principles/ ), and is key to many automated processes being able to operate on these data, particularly analytics involving artificial intelligence. We used an open-source web service to measure the FAIR compliance of the three data archives operated by NASA for the biological and physical sciences: the Life Sciences Data Archive, the Physical Sciences Informatics database, and GeneLab. The service ingests references to data sets in these archives, and then executes domain-non-specific examinations of these data and metadata that test compliance to the FAIR principles. Of the 22 metrics tested, GeneLab passed 11 (50%), and PSI and LSDA each passed 7 (32%). These data were gathered using only one representative data set from each archive and we anticipate variability in results as we continue to apply these metrics to other data. A preliminary study of the failure traces for each metric suggests there is a wide range of effort and complexity in the enhancements required for each system to elevate FAIR compliance, and this is the subject of continued investigation. This information has been and will likely continue to be important information in planning these enhancements, with the goal of increased readiness of the data for automated processes.

database↗

Modeling Ionizing Radiation for Spaceflight Dynamic Radioisotope Power Systems

This paper presents methods, simulations, and analyses for spaceflight ionizing radiation exposures to three dynamic radioisotope power systems(DRPSs). The specific systems being investigated are part of an open solicitation by the National Aeronautics and Space Administration (NASA) and the US Department of Energy (DOE)to develop DRPS convertor technologies. The analyses include ionizing radiation sources from PuO2andgalactic cosmic rays (GCRs) over notional 20-year mission architectures with optional 10-year exposures from Jovian radiation environments. Total integrated doses to various components are calculated and compared to known material degradation thresholds in the open literature. Based on the findings, certain material trades are recommended for Jovian and non-Jovian mission architectures based solely on ionizing radiation. However, consideration is given to known and unknown synergistic degradation effects(i.e., radiation in combination with heat, pressure, or outgassing)that may be relevant to these systems and are not captured in these analyses.

Models↗

Global Network of Slow Solar Wind

The streamer belt region surrounding the heliospheric current sheet (HCS) is generally treated as the primary or sole source of the slow solar wind. Synoptic maps of solar wind speed predicted by the Wang-Sheeley-Arge model during selected periods of solar cycle 23, however, show many areas of slow wind displaced from the streamer belt. These areas commonly have the form of an arc that is connected to the streamer belt at both ends. The arcs mark the boundaries between fields emanating from different coronal holes of the same polarity and thus trace the paths of belts of pseudostreamers, i.e., unipolar streamers that form over double arcades and lack current sheets. The arc pattern is consistent with the predicted topological mapping of the narrow open corridor or singular separator line that must connect the holes and, thus, consistent with the separatrix-web model of the slow solar wind. Near solar maximum, pseudostreamer belts stray far from the HCS-associated streamer belt and, together with it, form a global-wide web of slow wind. Recognition of pseudostreamer belts as prominent sources of slow wind provides a new template for understanding solar wind stream structure, especially near solar maximum.

solar wind↗

Evidence for a Broad Relativistic Iron Line from the Neutron Star LMXB Ser X-1

We report on an analysis of XMM-Newton data from the neutron star low mass X-ray binary (LMXB) Serpens X-1 (Ser X-1). Spectral analysis of EPIC PN data indicates that the previously known broad iron Ka emission line in this source has a significantly skewed structure with a moderately extended red wing. The asymmetric shape of the line is well described with the laor and diskline models in XSPEC, which strongly supports an inner accretion disk origin of the line. To our knowledge this is the first strong evidence for a relativistic line in a neutron star LMXB. This finding suggests that the broad lines seen in other neutron star LMXBs likely originate from the inner disk as well. Detailed study of such lines opens up a new way to probe neutron star parameters and their strong gravitational fields. The laor model describes the line from Ser X-1 somewhat better than diskline, and suggests that the inner accretion disk radius is less than 6GM/c(exp 2). This is consistent with the weak magnetic fields of LMXBs, and may point towards a high compactness and rapid spin of the neutron star. Finally, the inferred source inclination angle in the approximate range 50-60 deg is consistent with the lack of dipping from Ser X-1.

Bhattacharyya, Sudip↗

Prediction of the interplanetary magnetic field strength

A new model of the coronal and interplanetary magnetic field can predict both the interplanetary magnetic field strength and its polarity from measurements of the photospheric magnetic field. The model includes the effects of the large-scale horizontal electric currents flowing in the inner corona, of the warped heliospheric current sheet in the upper corona, and of volume currents flowing in the region where the solar wind plasma totally controls the magnetic field. The model matches the MHD solution for a simple dipole test case better than earlier source surface and current sheet models. The strength and polarity of the radial interplanetary magnetic field component predicted for quiet time samples in each year from 1977 to 1986 agree with observations made near the Earth's orbit better than the hybrid MHD-source surface model (Wang and Sheeley, 1988). The results raise the question of whether coronal holes are the only solar source of the interplantary magnetic field in the solar wind. If some interplanetary flux originates outside coronal holes, the model can match the observed field using the accepted 1.8 saturation correction factor for lambda 5250 A magnetograph observations. Requiring open flux to come exclusively from coronal holes requires and additional factor of two.

Zhao, Xuepu↗

Enabling Model Organism and Commercial Astronaut Data Access Through the NASA Open Science Data Repository

NASA’s Open Science Data Repository (OSDR) brings together omics data from NASA’s GeneLab project and non-omics data, including physiological, phenotypic, imaging, and behavioral data from NASA’s Ames Life Sciences Data Archive (ALSDA) collected from decades of space biology research, providing open and FAIR (findable, accessible, interoperable, and reusable) access of these precious data to scientists world-wide. This rich source of meticulously curated metadata and data from spaceflight and analog studies has been mined by the scientific community resulting in dozens of high impact scientific publications that reveals a complex network of molecular and physiological effects of spaceflight across living systems, from microbes to plants, to mammals. Understanding how these effects translate to the human condition is critical as we move deeper into the era of commercial space travel. However, the integration of data, specifically omics data, from astronauts is particularly challenging due to their sensitive nature. OSDR has risen to this challenge by developing a mechanism to control access to identifiable levels of omics data, such as raw sequence data, while enabling public access to processed, unidentifiable, data and associated metadata that will allow the scientific community to interrogate human astronaut data alongside data from model organisms to begin answering these critical questions. The 2021 SpaceX Inspiration4 (I4) mission collected a comprehensive atlas of biological measurements from four civilian astronauts, providing a wealth of data to characterize the effects of spaceflight on the human body. These data include both non-omics and omics assays such as direct RNA sequencing (RNA-seq), single nuclei ATAC-seq and RNA-seq, metagenomics, proteomics, and comprehensive metabolic and cytokine panels, all of which have been integrated into the OSDR system across no less than 9 studies. Each study has been carefully curated using community-backed OSDR standards for sample and assay level metadata ensuring these data are findable and accessible. In addition to hosting both raw and processed data from the principal investigator team for each assay type, the GeneLab team plans to re-process the I4 omics data using GeneLab’s standard processing pipelines. The GeneLab processed data outputs will allow for comparisons across studies on OSDR and enable visualization of these data through the OSDR data visualization platform thereby enabling data reusability and interoperability. Here we describe the robust privacy and security protocols implemented by OSDR to safeguard sensitive health data from astronauts while facilitating metadata and processed data sharing for research purposes. We further provide a road map for navigating the vast amount of data provided for each I4 study on the OSDR, including experimental design, associated experiments, payloads, and missions, data generation and analysis protocols, and associated scientific articles. Additionally, we illustrate how to interrogate the standardized metadata provided in the sample and assay tables as well as various means to download and access the data including programmatically through the GeneLab Open API (GLOpenAPI). The open access of datasets in NASA’s OSDR provides a unique opportunity for the scientific community, as well as citizen scientists and students, to continue using OSDR resources to further unlock profound insights into the consequences of space travel on the human body. Through implementation of security measures to protect sensitive human data, the OSDR seeks to strengthen the science exchange between the Biological and Physical Sciences Program and the Human Research Program, per recommendation 4-1 of the 2023-2032 Decadal Survey, and encourage further sharing and dissemination of astronaut data to provide the scientific community with the resources needed to lay the groundwork for developing targeted mitigation strategies to help withstand the rigors of long-duration spaceflight.

Amanda Marie Saravia-butler↗

Opening of the magnetic field lines in a fast rotating magnetosphere, with an application to Jupiter

A simple model of a magnetosphere rotating around a rotating Jupiter-like object with a spin-aligned dipolar moment mu is considered. A low-energy plasma is released by inner sources located beyond the corotation radius and is diffused outward through closed lines. The lines form a closed thin equatorial disk, maintaining a quasi-static balance between the centrifugal force and the magnetic tension. Solutions are obtained for the analytical equations characterizing the plasma in the closed region; the structure of the magnetic field outside the disk; and the self-consistent value of the critical radius r sub zero. The analytical solutions are compared to the observed properties of the Jovian magnetosphere, and the results are discussed in detail.

Aly, J. J.↗

High-Energy Emission From Millisecond Pulsars

The X-ray and gamma-ray spectrum of rotation-powered millisecond pulsars is investigated in a model for acceleration and pair cascades on open field lines above the polar caps. Although these pulsars have low surface magnetic fields, their short periods allow them to have large magnetospheric potential drops, but the majority do not produce sufficient pairs to completely screen the accelerating electric field. In these sources, the primary and secondary electrons continue to accelerate to high altitude and their Lorentz factors are limited by curvature and synchrotron radiation reaction. The accelerating particles maintain high Lorentz factors and undergo cyclotron resonant absorption of radio emission, that produces and maintains a large pitch angle, resulting in a strong synchrotron component. The resulting spectra consist of several distinct components: curvature radiation from primary electrons dominating from 1 - 100 GeV, synchrotron radiation from primary and secondary electrons dominating up to about 100 MeV, and much weaker inverse-Compton radiation from primary electrons a t 0.1 - 1 TeV. We find that the relative size of these components depends on pulsar period, period derivative, and neutron star mass and radius with the level of the synchrotron component also depending sensitively on the radio emission properties. This model is successful in describing the observed X-ray and gamma-ray spectrum of PSR J0218+4232 as synchrotron radiation, peaking around 100 MeV and extending up to a turnover around several GeV. The predicted curvature radiation components from a number of millisecond pulsars, as well as the collective emission from the millisecond pulsars in globular clusters, should be detectable with AGILE and GLAST. We also discuss a hidden population of X-ray-quiet and radio-quiet millisecond pulsars which have evolved below the pair death line, some of which may be detectable by telescopes sensitive above 1 GeV. Subject headings: pulsars: general - radiation mechanisms: nonthermal - stars: neutron - gamma rays: theory

Harding, Alice K.↗

GLDAS-2 Land Surface Model Data and Data Services at NASA GES DISC

The goal of the NASA Global Land Data Assimilation System (GLDAS, https://ldas.gsfc.nasa.gov/gldas(https://ldas.gsfc.nasa.gov/gldas)) is to generate optimal fields of land surface states and fluxes by ingesting satellite- and ground-based observational data products, using advanced land surface modeling and data assimilation techniques (Rodell et al., 2004).The GLDAS dataset currently archived at and distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC, https://disc.gsfc.nasa.gov/ (https://disc.gsfc.nasa.gov/)) is GLDAS Version 2 (GLDAS-2). It contains a series of output fields from the upgraded Noah-3.6, Catchment-F2.5, and VIC-4.1.2 Land Surface Models (LSMs) in the Land Information System (LIS-V7, https://lis.gsfc.nasa.gov/ (https://lis.gsfc.nasa.gov/)). GLDAS-2 has three components:GLDAS-2.0, GLDAS-2.1, and GLDAS-2.2. GLDAS-2.0 is forced entirely with the upgraded Princeton Meteorological ForcingV2.2 Dataset and provides a temporally consistent series from 1948 through 2014. GLDAS-2.1 is forced with a combination of model and observation data, with data spanning from 2000 to the present. The GLDAS-2.2 product suite uses data assimilation(DA), whereas the GLDAS-2.0 and GLDAS-2.1 products are "open-loop" (i.e., no data assimilation). The choice of forcing data, as well as DA observation source, variable, and scheme, varies for different GLDAS-2.2 products. The currently availableGLDAS-2.2 data contain a daily 0.25-degree output from the Catchment-F2.5 LSM in LIS-V7. The data are forced with the meteorological analysis fields from the operational European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (ECMWF-IFS) and assimilated with GRACE and GRACE-FO data, ranging from February 1, 2003 to the present. The current GLDAS-2.0 and 2.1 Noah LSM data were reprocessed in November 2019 and January 2020 respectively and their data from Catchment and VIC LSMs are new to the GLDAS-2 collection. This presentation provides a summary of theGLDAS-2 data products, their land surface fields, and their related data services at the GES DISC; and a description of the majorGLDAS-2 climatological characteristics as well as the intercomparison with the data of the previous version.

Hydrology↗

A Partitioned -Task Parallel Implementation of the NASA Multiscale Analysis Tool for High Performance Computing

The NASA Multiscale Analysis Tool (NASMAT) is a “plug and play” software package that allows users to conduct massively multiscale modeling of hierarchical and nonlinear materials. This work extends the scalability and improves the High Performance Computing friendliness of NASMAT by adopting a Partitioned Task-Parallel approach. Interoperability of NASMAT with external software is enhanced through preCICE, a open source library for multiphysics coupling in a partitioned manner. Enhancement through preCICE allows for easy integration of NASMAT to other macro solvers and dissociates the parallelization strategy adopted within NASMAT from the macro solver. The task-parallel framework based on Master-Worker approach is implemented as the parallelization scheme. The scheme accounts for hierarchy of multiple scales (task-dependence) and heterogeneous nature (dynamic load balancing) of computations. The applicability and scalability of the framework will be evaluated by analyzing large scale engineering problems through massively multiscale methods.

NASMAT↗

Coupling the Solar-Wind/IMF to the Ionosphere through the High Latitude Cusps

Magnetic merging is a primary means for coupling energy from the solar wind into the magnetosphere-ionosphere system. The location and nature of the process remain as open questions. By correlating measurements form diverse locations and using large-scale MHD models to put the measurements in context, it is possible to constrain out interpretations of the global and meso-scale dynamics of magnetic merging. Recent evidence demonstrates that merging often occurs at high latitudes in the vicinity of the cusps. The location is in part controlled by the clock angle in the interplanetary magnetic field (IMF) Y-Z plane. In fact, B(sub Y) bifurcated the cusp relative to source regions. The newly opened field lines may couple to the ionosphere at MLT locations of as much as 3 hr away from local noon. On the other side of noon the cusp may be connected to merging sites in the opposite hemisphere. In face, the small convection cell is generally driven by opposite hemisphere merging. B(sub X) controls the timing of the interaction and merging sites in each hemisphere, which may respond to planar features in the IMF at different times. Correlation times are variable and are controlled by the dynamics of the tilt of the interplanetary electric field phase plane. The orientation of the phase plane may change significantly on time scales of tens of minutes. Merging is temporally variable and may be occurring at multiple sites simultaneously. Accelerated electrons from the merging process excite optical signatures at the foot of the newly opened field lines. All-sky photometer observations of 557.7 nm emissions in the cusp region provide a "television picture" of the merging process and may be used to infer the temporal and spatial variability of merging, tied to variations in the IMF.

Maynard, Nelson C.↗

Parabolic harmonics in magnetospheric modeling - The main dipole and the ring current

A new representation is developed for that portion of the magnetospheric magnetic field which is produced by currents on the magnetopause or outside it. For a magnetopause which is a paraboloid of rotation and which confines all field lines of magnetospheric sources, the fields due to magnetopause currents are derived for two sources, a dipole and a two-parameter model of the ring current, each arbitrarily inclined to the earth-sun line. Methods are also developed for accomodating changes in the size of the magnetospheric cavity and for using nonparaboloidal boundaries, open at the nightside. Neutral points and polar cusps are derived, and in agreement with observations it is found that a growth of the ring current shifts them equatorward. By extrapolation from these results, it is argued that the observation of such shifts during magnetic storms may help resolve the relative importance of two processes proposed for magnetic storms.

Stern, D. P.↗

Hydrological Modeling of the Jezero Crater Outlet-Forming Flood

Abundant evidence exists for lakes on Mars both from orbital observations [e.g., 1-3] and in situ exploration [e.g., 4-5]. These lakes can be divided into two classes: those that were hydrologically closed, so their source valley(s) terminated at the basin [3], and those that were hydrologically open, where there was sufficient flow from inlet valley(s) to cause the lake to breach and form an outlet valley [2]. It is easier to be confident from orbital data alone that a standing body of water must have existed in open basins, because there is no other way for their perched outlet valleys to form. The majority of basins fed by valley networks, rather than by isolated inlet valleys, are open [6], with some important exceptions (e.g., Gale Crater). Jezero crater (Fig. 1) is one of the most well-studied open basin paleolakes on Mars, with a breach that re-mains well above the lowest part of the crater floor, and two sedimentary fans at its northwestern margin that are likely deltaic in origin [7-9]. CRISM observations of these sediments indicate they host a variety of alteration minerals [9-11], including smectite and carbonate, and both the mineralogy of the sediments and their settings suggest they have a strong potential for preserving organic materials [10]. As a result, Jezero is a strong candidate landing site for the Mars 2020 rover. Approximate formative discharges have been estimated for its well-preserved western fan (Q approximately 500m3/s) [7], but to our knowledge, no estimates for the dis-charges associated with formation and incision of its outlet valley have been presented. Indeed, only a few studies [e.g., 12-14] have attempted to reconstruct the formation of outlet breaches broadly similar to Jezero anywhere on Mars, despite the apparent commonality of basins with large outlets [e.g., 2]. The outlet valley formed as a dam breach when the lake overflowed. In such an event, the growth and incision of the breach is directly coupled to flood discharge. In the case of Jezero, the discharge through the breach eventually lacked the energy needed to erode through the dam further, preventing complete drainage of the lake. After the initial flood, further incision can take place if additional water flows into, and thus out of, the hydrologically open lake, though the rate of this erosion occurs under more typical fluvial conditions. Despite this qualitative understanding of the process, it is useful to explore numerically what range of model parameters are potentially consistent with obser-vations of the outlet. We ultimately seek to address questions that include: (1) What was the flood hydro-graph?, (2) What sediment transport processes were involved and what can we infer about the erosion process? (3) Can most or all of the Jezero outlet's morphology be explained as a consequence of catastrophic formation, or is additional longer-term erosion required?

geology↗

Deep Learning Models for Planetary Seismicity Detection

Research in planetary seismology is fundamentally constrained by a lack of data. Seismo-logical science products of future missions can typically only be informed by theoretical signal/noise characteristics of the environment or likely Earth-analogues. Although objectives can be re-assessed after some initial data-collection upon lander arrival, transfer of high-resolution data back to Earth is costly on lander power usage. Over the last several years, development of GPU computing techniques and open-source high-level APIs have led to rapid advances in deep learning within the fields of computer vision, natural language processing, and collaborative filtering. These techniques are actively being adapted in seismology for a variety of tasks, including: earthquake detection, seismic phase discrimination, and ground-motion prediction. Until the recent detection of mars quakes during the Mars InSight mission, the only other measurements of seismicity recorded outside of Earth was on the Moon during the Apollo missions between 1969 to 1977. These unique data sets have been periodically revisited using new seismological methods, including ambient noise interferometry and Hidden Markov Models. Our objective is to develop a deep learning seismic detector and use it to catalog moonquakes from the Apollo 17 Lunar Seismic Profiling Experiment (LSPE) and compare the results with those obtained by other methods. Additionally, we will assess the accuracy tradeoff between using a training set of lunar data and one composed of Earth seismicity. In this document, we present preliminary results using a prototype classifier trained on a small set of earthquakes that was able to obtain detections for LSPE moonquakes with a greater accuracy than a recent study using Hidden Markov Models.

Civilini, F.↗