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At least 307 records · Page 17

Extraterrestrial Molecular Indicators of Life Investigation (EMILI)

Future missions to Enceladus, Europa, Mars, and beyond may seek the molecular signs of extraterrestrial life through chemical analysis of acquired samples. Particularly on ocean worlds such as Enceladus and Europa, samples may contain trace ocean-borne molecular biosignatures of extant life that may or may not share similarities to those of terrestrial life. In situ analyses must be prepared to detect and characterize a wide range of possible molecular species, structures, and patterns, typically with exquisite sensitivity and within a complex, poorly-characterized planetary environment. The Extraterrestrial Molecular Indicators of Life Investigation (EMILI) is designed to meet or exceed the requirements of such missions for organic molecular analysis through a powerful combination of dual chemical separation and both optical and mass spectrometry detection techniques, realized in an integrated, compact instrument package fully compatible with anticipated flight resources and conditions. The full EMILI instrument combines two sample analysis subsystems to provide wide-ranging and complementary detection of organic compounds and inorganic salts. The Gas Analysis Processing System (GAPS) uses a chemical derivatization protocol with gas chromatography (GC) separation prior to detection in an ion trap mass spectrometer (ITMS) to enable full characterization of lower-polarity, volatile and semi-volatile molecules such as fatty acids and hydrocarbons. The Organic Capillary Electrophoresis ANalysis System (OCEANS) uses a liquid-based extraction protocol with CE separation to enable precise analysis of more water-soluble/polar compounds. OCEANS features a laser-induced fluorescence detection mode to perform ultra-sensitive quantitative analysis of chiral amino acids. In EMILI, OCEANS is additionally coupled to the same ITMS through a novel electrospray ionization interface. The common ITMS allows EMILI to identify and cross-correlate molecular species and patterns, detected through either or both protocols, of molecular weights to over 1000 u, potentially even revealing complex biosignatures such as alien oligopeptides and informational polymers.

Europa↗

Tactical Analysis for Calculating Contextual Risk at Boundaries: Summary of Laboratory Directed Research & Development Effort

The Tactical Analysis for Calculating Contextual Risk at Boundaries (TACCRAB) tool is an innovative digital twin (DT) platform and automated risk algorithm designed to transform operational decision-making in structured screening environments, with an initial focus on Southern Border Land Ports of Entry (POEs). The invention provides integration points for advanced artificial intelligence, predictive modeling, and real-time data analysis to produce a comprehensive risk management tool that enables proactive, data-informed security strategies. The core inventive features of TACCRAB center on its unique risk algorithm, which dynamically calculates contextual risk by synthesizing historical data, near real-time streaming data from the checkpoints themselves, and AI-generated predictions. Unlike traditional risk assessment methods, TACCRAB utilizes a DT to provide comprehensive operational insights, allowing stakeholders to visualize, simulate, and optimize checkpoint configurations with unprecedented speed and contextual awareness. TACCRAB's key innovation lies in its ability to combine multiple complex inputs - including technology detection probabilities, resource availability, screening pathway characteristics, and threat actor behavioral patterns - into a unified risk calculation and update these inputs based on changing operational and environmental conditions. By leveraging a DT that continuously updates and learns from linked data, TACCRAB can suggest adaptive mitigation strategies that minimize risk while maintaining operational efficiency. Particularly novel is the platform's approach to decision support, which goes beyond static risk assessment. The DT provides dynamic metrics such as wait times, resource allocation effectiveness, and potential emerging threat scenarios, enabling users to view sophisticated, relevant what-if simulations and optimize checkpoint operations in near real-time. The system's architecture allows for generalized application across different screening environments, such as secure facilities, ports of entry, and soft targets, making it a versatile tool for security and operational management. The invention distinguishes itself through its comprehensive integration of predictive modeling, AI-driven pattern discovery, and user-friendly interface design. By combining these elements, TACCRAB transforms complex risk data into actionable insights, supporting decision-makers at various organizational levels - from booth agents making split-second screening decisions to checkpoint managers optimizing the day's resource allocation to strategic planners managing long-term investments.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Metamorphic core complexes: Expression of crustal extension by ductile-brittle shearing of the geologic column

Metamorphic core complexes and detachment fault terranes in the American Southwest are products of stretching of continental crust in the Tertiary. The physical and geometric properties of the structures, fault rocks, and contact relationships that developed as a consequence of the extension are especially well displayed in southeastern Arizona. The structures and fault rocks, as a system, reflect a ductile-through-brittle continuum of deformation, with individual structures and faults rocks showing remarkably coordinated strain and displacement patterns. Careful mapping and analysis of the structural system has led to the realization that strain and displacement were partitioned across a host of structures, through a spectrum of scales, in rocks of progressively changing rheology. By integrating observations made in different parts of the extensional system, especially at different inferred depth levels, it has been possible to construct a descriptive/kinematic model of the progressive deformation that achieved continental crustal extension in general, and the development of metamorphic core complexes in particular.

Davis, G. H.↗

Simons Observatory: characterizing the Large Aperture Telescope Receiver with radio holography

Here, we present near-field radio holography measurements of the Simons Observatory Large Aperture Telescope Receiver optics. These measurements demonstrate that radio holography of complex millimeter-wave optical systems comprising cryogenic lenses, filters, and feed horns can provide detailed characterization of wave propagation before deployment. We used the measured amplitude and phase, at 4 K, of the receiver near-field beam pattern to predict two key performance parameters: 1) the amount of scattered light that will spill past the telescope to 300 K and 2) the beam pattern expected from the receiver when fielded on the telescope. These cryogenic measurements informed the removal of a filter, which led to improved optical efficiency and reduced sidelobes at the exit of the receiver. Holography measurements of this system suggest that the spilled power past the telescope mirrors will be less than 1%, and the main beam with its near sidelobes are consistent with the nominal telescope design. This is the first time such parameters have been confirmed in the lab prior to deployment of a new receiver. This approach is broadly applicable to millimeter and submillimeter instruments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A network approach for multiscale catchment classification using traits

Abstract. The classification of river catchments into groups with similar biophysical characteristics is useful to understand and predict their hydrological behavior. The increasing availability of remote sensing and other large-scale geospatial datasets has enabled the use of advanced data-driven approaches to classify catchments using traits such as topography, geology, climate, land cover, land use, and human influence. Unsupervised clustering algorithms based on the Euclidean distance are commonly used for trait-based classification but are not suitable for highly dimensional data. In this study we present a new network-based method for multi-scale catchment classification, which can be applied to large datasets and used to determine the traits associated with different catchment groups. In this framework, two networks are analyzed in parallel: the first being where the nodes are traits and the second being where the nodes are catchments. In both cases, edges represent pairwise similarity, and a network cluster detection algorithm is used for the classification. The trait network is used to investigate redundancy in the trait data and to condense this information into a small number of interpretable categories. The catchments network is used to classify the catchments into clusters and to identify representative catchments for the different groups using the degree centrality metric. We apply this method to classify 9067 river catchments across the contiguous United States at both regional and continental scales using 274 non-categorical traits. At the continental scale, we identify 25 interpretable trait categories and 34 catchment clusters of sizes greater than 50. We find that catchments with similar trait categories are typically located in the same region, with different spatial patterns emerging among clusters dominated by natural and anthropogenic traits. We also find that the catchment clusters exhibit distinct hydrological behavior based on an analysis of streamflow indices. This network approach provides several advantages over traditional means of classification, including better separation of clusters, the use of alternate similarity metrics that are more suitable for highly dimensional data, and reducing redundancy in the trait information. The paired catchment–trait networks enable analysis of hydrological behavior using the dominant trait categories for each catchment cluster. The approach can be used at multiple spatial scales since the network topologies adjust automatically to reflect the trait patterns at the scale of investigation. Finally, the representative catchments identified as hub nodes in the network can be used to guide transferable observational and modeling strategies. The method is broadly applicable beyond hydrology for classification of other complex systems that utilize different types of trait datasets.

54 ENVIRONMENTAL SCIENCES↗

Dynamics and X-ray emission of a galactic superwind interacting with disk and halo gas

There is a general agreement that the conspicuous extranuclear X-ray, optical-line, and radio-contiuum emission of starbursts is associated with powerful galactic superwinds blowing from their centers. However, despite the significant advances in observational studies of superwinds, there is no consensus on the nature of the emitting material and even on the emission mechanisms themselves. This is to a great extent a consequence of a poor understanding of dynamical processes in the starburst superwind regions. To address this issue, we have conducted two-dimensional hydrodynamical simulations of galactic superwinds. While previous similar studies have used a single (disk) component to represent the ISM of the starburst galaxy, we analyze the interaction of the wind with a two-component disk-halo ambient interstellar medium and argue that this two-component representation is crucial for adequate modeling of starbursts. The emphasis of this study is on the geometry and structure of the wind region and the X-ray emission arising in the wind material and the shocked gas in the disk and the halo of the galaxy. The simulation results have shown that a clear-cut bipolar wind can easily develop under a range of very different conditions. On the other hand, a complex 'filamentary' structure associated with the entrained dense disk material is found to arise within the hot bubble blown out by the wind. The flow pattern within the bubble is dominated equally by the central biconic outflow and a system of whirling motions r elated to the origin and development of the 'filaments'. The filament parameters make them a good candidate for optical-emission-line filamentary gas observed in starburst halos. We find that the history of mass and energy deposition in the starburst region of the galaxy is crucial for wind dynamics. A 'mild' early wind, which arises as a result of the cumulative effect of stellar winds from massive stars, produces a bipolar vertical cavity in the disk and halo gas without strongly affecting the gaseous disk, thus creating conditions for virtually free vertical escape of the hot gas at the later, much more violent supernova-dominated phases of the starburst. We calculate the luminosity, mass, and effective temperature of the X-ray emitting gas in the 'soft' (0.1 to 0.7 keV, 0.7 to 2.2 keV, and 0.1 to 2.2 keV) and 'hard' (1.6 to 8.3 keV) energy bands and estimate the contribution of different gaseous components to the X-ray flux in these bands. Analysis of these parameters enables us to make conclusions regarding the nature of the X-ray-emitting material. We have inferred that the bulk of the soft thermal X-ray emission from starbursts arises in the wind-shocked material of the disk and halo gas rather than in the wind material itself. This enables us to predict that the integrated soft X-ray spectra of starbursts need not show an overabundance of heavy elements which are believed to be produced copiously in the centers of starbursts. Unlike soft X-ray emission, the hard component of thermal X-ray emission is found to originate in the wind material ejected from the starburst region. However, the derived ratio of hard-to-soft X-ray luminosities is too small compared to that observed in starbursts. We conclude therefore that the observed hard X-ray emission of starbursts is probably not associated with the thermal emission of hot wind or ambient shocked gas. Typical temperatures of the bulk of the soft X-ray-emitting material in our very different models have been found to agree well with the ones estimated on the basis of the ROSAT data for the soft component of X-ray emission of nearby starbursts. We predict that temperatures of the extranuclear soft X-ray-emitting gas in starburst galaxies with heavy element abundances near solar should be close to T(sub Xs = 2 to 5 x 10(exp 6)K.

Suchkov, Anatoly A.↗

Fossil Signatures Using Elemental Abundance Distributions and Bayesian Probabilistic Classification

Elemental abundances (C6, N7, O8, Na11, Mg12, Al3, P15, S16, Cl17, K19, Ca20, Ti22, Mn25, Fe26, and Ni28) were obtained for a set of terrestrial fossils and the rock matrix surrounding them. Principal Component Analysis extracted five factors accounting for the 92.5% of the data variance, i.e. information content, of the elemental abundance data. Hierarchical Cluster Analysis provided unsupervised sample classification distinguishing fossil from matrix samples on the basis of either raw abundances or PCA input that agreed strongly with visual classification. A stochastic, non-linear Artificial Neural Network produced a Bayesian probability of correct sample classification. The results provide a quantitative probabilistic methodology for discriminating terrestrial fossils from the surrounding rock matrix using chemical information. To demonstrate the applicability of these techniques to the assessment of meteoritic samples or in situ extraterrestrial exploration, we present preliminary data on samples of the Orgueil meteorite. In both systems an elemental signature produces target classification decisions remarkably consistent with morphological classification by a human expert using only structural (visual) information. We discuss the possibility of implementing a complexity analysis metric capable of automating certain image analysis and pattern recognition abilities of the human eye using low magnification optical microscopy images and discuss the extension of this technique across multiple scales.

Hoover, Richard B.↗

Simons Observatory: Characterizing the Large Aperture Telescope Receiver with Radio Holography

We present near-field radio holography measurements of the Simons Observatory Large Aperture Telescope Receiver optics. These measurements demonstrate that radio holography of complex millimeter-wave optical systems comprising cryogenic lenses, filters, and feed horns can provide detailed characterization of wave propagation before deployment. We used the measured amplitude and phase, at 4 K, of the receiver near-field beam pattern to predict two key performance parameters: 1) the amount of scattered light that will spill past the telescope to 300 K and 2) the beam pattern expected from the receiver when fielded on the telescope. These cryogenic measurements informed the removal of a filter, which led to improved optical efficiency and reduced sidelobes at the exit of the receiver. Holography measurements of this system suggest that the spilled power past the telescope mirrors will be less than 1%, and the main beam with its near sidelobes are consistent with the nominal telescope design. This is the first time such parameters have been confirmed in the lab prior to deployment of a new receiver. This approach is broadly applicable to millimeter and submillimeter instruments.

Grace. E. Chesmore↗

Characterizing Signatures of Geothermal Exploration Data with Machine Learning Techniques: An Application to the Nevada Play Fairway Analysis

We are introducing machine learning methods to the play fairway analysis to generate geothermal potential maps to support the evaluation of geothermal resource potential and the exploration for undiscovered blind geothermal systems in the Nevada Great Basin region. Our project aims to identify new ways to combine the play fairway data and empirically organize relationships between feature weights and labels in an improved workflow. As a means of doing this, we introduce machine learning methods to evaluate the influence of certain geological and geophysical features/feature sets in predicting geothermal favorability. This report highlights promising approaches based on supervised and unsupervised learning methods. First, we demonstrate a filter method applied to supervised classification modeling. The supervised filter method is based on permutation analysis to evaluate every possible feature combination/drop out scenario and rank feature influence based on the performance variance of supervised classification models. Additionally, we present an unsupervised factor analysis based on principal component analysis coupled with a semi-supervised kmeans clustering algorithm. This analysis allows us to identify the optimal number of groups/clusters for training sites and structural settings to identify feature patterns including correlation, variance, and latent and dominant feature relationships. The results from these methods offer a promising avenue for identifying favorable sources of predictive information to identify the locations of blind geothermal systems and furthering our understanding of complex geothermal feature and label relationships in the Great Basin region and beyond.

15 GEOTHERMAL ENERGY↗

The Urban Observatory: A Multi-Modal Imaging Platform for the Study of Dynamics in Complex Urban Systems

We describe an “Urban Observatory” facility designed for the study of complex urban systems via persistent, synoptic, and granular imaging of dynamical processes in cities. An initial deployment of the facility has been demonstrated in New York City and consists of a suite of imaging systems—both broadband and hyperspectral—sensitive to wavelengths from the visible (∼400 nm) to the infrared (∼13 micron) operating at cadences of ∼0.01–30 Hz (characteristically ∼0.1 Hz). Much like an astronomical survey, the facility generates a large imaging catalog from which we have extracted observables (e.g., time-dependent brightnesses, spectra, temperatures, chemical species, etc.), collecting them in a parallel source catalog. We have demonstrated that, in addition to the urban science of cities as systems, these data are applicable to a myriad of domain-specific scientific inquiries related to urban functioning including energy consumption and end use, environmental impacts of cities, and patterns of life and public health. We show that an Urban Observatory facility of this type has the potential to improve both a city’s operations and the quality of life of its inhabitants.

54 ENVIRONMENTAL SCIENCES↗

Coherence in Chemistry: Foundations and Frontiers

Coherence refers to correlations in waves. Because matter has a wave-particle nature, it is unsurprising that coherence has deep connections with the most contemporary issues in chemistry research (e.g., energy harvesting, femtosecond spectroscopy, molecular qubits and more). But what does the word "coherence" really mean in the context of molecules and other quantum systems? We provide a review of key concepts, definitions, and methodologies, surrounding coherence phenomena in chemistry, and we describe how the terms "coherence" and "quantum coherence" refer to many different phenomena in chemistry. Moreover, we show how these notions are related to the concept of an interference pattern. Coherence phenomena are indeed complex, and ambiguous definitions may spawn confusion. By describing the many definitions and contexts for coherence in the molecular sciences, we aim to enhance understanding and communication in this broad and active area of chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

3D Localization of Defects in Facility Inspection

Wind tunnels are crucial facilities that support the aerospace industry. However, these facilities are large, complex, and pose unique maintenance and inspection requirements. Manual inspections to identify defects such as cracks, missing fasteners, leaks, and foreign objects are important but labor and schedule intensive. Our goal is to utilize small Unmanned Aircraft Systems (sUAS) and computer vision-based analysis to automate the inspection of the interior and exterior of NASA’s critical wind tunnel facilities. We detect missing fasteners as our defect class, and detect existing fasteners to provide potential future missing fastener sites for preventative maintenance. These detections are done on both 2D raw images and in 3D space to provide a visual reference and real world location to facilitate repairs. A dataset was created consisting of images taken along a grid-like pattern of an interior tunnel section in the AEDC National Full-Scale Aerodynamics Complex (NFAC) at NASA Ames Research Center. Our method uses object detection to create image level bounding boxes of the fasteners and missing fasteners, then uses photogrammetry to create a mapping from 2D image locations to 3D real world locations. The image level bounding boxes and the 2D to 3D mapping are then combined to determine the 3D location of the defects. We describe the data collection, photogrammetry, and computer vision techniques used for object detection as well as a quantitative analysis of the method.

Small Unmanned Aircraft Systems (sUAS)↗

Lineament and polygon patterns on Europa

A classification scheme is presented for the lineaments and associated polygonal patterns observed on the surface of Europa, and the frequency distribution of the polygons is discussed in terms of the stress-relief fracturing of the surface. The lineaments are divided on the basis of albedo, morphology, orientation and characteristic geometry into eight groups based on Voyager 2 images taken at a best resolution of 4 km. The lineaments in turn define a system of polygons varying in size from small reticulate patterns the limit of resolution to 1,000,000 sq km individuals. Preliminary analysis of polygon side frequency distributions reveals a class of polygons with statistics similar to those found in complex terrestrial terrains, particularly in areas of well-oriented stresses, a class with similar statistics around the antijovian point, and a class with a distribution similar to those seen in terrestrial tensional fracture patterns. Speculations concerning the processes giving rise to the lineament patterns are presented.

Pieri, D. C.↗

Vortex-Body Interactions: A Critical Assessment. Coupled Gap-Wake Instabilities/Turbulence: A Source of Noise

This program has involved, first of all, a critical state-of-the-art assessment of vortex-body interactions. Then, efforts were focused on experimental investigation on coupled-wake instabilities and turbulence occurring in a two-cylinder system. An extensive review was undertaken on the effect of incident vortices on various types of bodies. These incident vortices have a length scale of the same order of magnitude as the scale of the body. The body can take on various forms, including, for example, a circular cylinder, a blade or a wing. The classes of vortex-body interaction that were critically assessed include: (1) Periodic distortion of the incident (primary) vortex and shedding of secondary vorticity from the surface of the body. (2) Modulated vortex distortion and shedding at a leading-edge or surface due to incidence of a complex system of vortices. (3) Vortex distortion and shedding in presence of body oscillation. (4) Three-dimensional vortex interaction and shedding. For all of these classes of vortex-body interaction, quantitative topologies of the vorticity distributions and streamline patterns were found to be central to a unified description of mechanisms of vortex distortion and shedding. In most cases, it was possible to define relationships between vortex interactions and unsteady loading at the body surface. This phase of the program was an experimental investigation of a two-cylinder system, which simulated a central aspect of a four-wheel bogie on a large-scale commercial aircraft. The overall aim of this experimental research program was to determine the crucial elements of the unsteadiness in the gap and near-wake regions as a function of time using cinema-based techniques. During the research program, various image evaluation techniques were employed. They involved assessment of instantaneous velocity fields, streamline topology and patterns of vorticity. Experiments were performed in a large-scale water channel using a high-resolution version of digital particle image velocimetry. The program has focused on acquisition of images of velocity and vorticity for varying gap widths between the two-cylinder system. As a result of analysis of a relatively large number of images, it is demonstrated that low frequency instabilities can occur in the gap region between the cylinder. These low frequency instabilities are hypothesized to influence the near-wake structure of the entire two-cylinder system. The nature of the unstable shear layers in the gap region involves generation of small-scale Kelvin-Helmholtz instabilities. These unsteady shear layers then impinge upon the upper and lower surfaces of the cylinders, thereby influencing both the unsteady structure and the time-averaged patterns of the near-wake. Initial efforts have focused on characterization of the patterns of instantaneous and averaged streamlines using topological concepts. The end result of this investigation is a series of documented instantaneous images. They will serve as a basis for various types of post-processing, which will lead to a fuller understanding of the instantaneous and time-averaged unstable-turbulent fields in the gap region and downstream of the two-cylinder system. This further assessment is the focus of a subsequent program.

Rockwell, Donald↗

Development of Numerical Codes for Modeling Electromagnetic Behavior at High Frequencies Near Large Objects

A study into the problem of determining electromagnetic solutions at high frequencies for problems involving complex geometries, large sizes and multiple sources (e.g. antennas) has been initiated. Typical applications include the behavior of antennas (and radiators) installed on complex conducting structures (e.g. ships, aircrafts, etc..) with strong interactions between antennas, the radiation patterns, and electromagnetic signals is of great interest for electromagnetic compatibility control. This includes the overall performance evaluation and control of all on-board radiating systems, electromagnetic interference, and personnel radiation hazards. Electromagnetic computational capability exists at NASA LaRC, and many of the codes developed are based on the Moment Method (MM). However, the MM is computationally intensive, and this places a limit on the size of objects and structures that can be modeled. Here, two approaches are proposed: (i) a current-based hybrid scheme that combines the MM with Physical optics, and (ii) an Alternating Direction Implicit-Finite Difference Time Domain (ADI-FDTD) method. The essence of a hybrid technique is to split the overall scattering surface(s) into two regions: (a) a MM zone (MMZ) which can be used over any part of the given geometry, but is most essential over irregular and "non-smooth" geometries, and (b) a PO sub-region (POSR). Currents induced on the scattering and reflecting surfaces can then be computed in two ways depending on whether the region belonged to the MMZ or was part of the POSR. For the MMZ, the current calculations proceed in terms of basis functions with undetermined coefficients (as in the usual MM method), and the answer obtained by solving a system of linear equations. Over the POSR, conduction is obtained as a superposition of two contributions: (i) currents due to the incident magnetic field, and (ii) currents produced by the mutual induction from conduction within the MMZ. This effectively leads to a reduction in the size of linear equations from N to N - Npo with N being the total number of segments for the entire surface and Npo the number of segments over the POSR. The scheme would be appropriate for relatively large, flat surfaces, and at high frequencies. The ADI-FDTD scheme provides for both transient and steady state analyses. The restrictive Courant-Friedrich-Levy (CFL) condition on the time-step is removed, and so large time steps can be chosen even though the spatial grids are small. This report includes the problem definition, a detailed discussion of both the numerical techniques, and numerical implementations for simple surface geometries. Numerical solutions have been derived for a few simple situations.

Joshi, R. P.↗

A Tutor That's Up to the Task

With assistance from NASA s Marshall Space Flight Center, a new breed of ITS for technical training and complex problem-solving has hit the market to provide students and trainees with the decision-making skills necessary to succeed to the next level. The Task Tutor Toolkit (T3), developed by Stottler Henke Associates, Inc., of San Mateo, California, is a generic tutoring system shell and scenario authoring tool that emulates expert instructors and lowers the cost and difficulty of creating scenario-based ITS for technical training. The functionality of Stottler Henke Associates T3 far exceeds that of traditional computer-based training systems, which test factual recall and narrow skills by prompting students to answer multiple-choice or fill-inthe- blank questions. The T3, on the contrary, lets students assess situations, generate solutions, make decisions, and carry out actions in realistically complex scenarios.At the beginning of each scenario, the T3 tutoring system presents a briefing that describes the situation and the goals the students should pursue. Each scenario contains a solution template that specifies a partially-ordered sequence of action patterns that match correct sequences of student actions. During each scenario, the built-in simulator notifies the tutoring system of each student action. The T3 uses this information to evaluate the student action by comparing it with the scenario s solution template and with error rules that detect incorrect actions.

Source record↗

Solar-power for Deep Space Science Missions

Solar power systems have enabled dazzling planetary science missions to much of the Solar System. This chapter outlines the types of solar array structures that have been used on U.S.-led robotic planetary science missions since the beginning of the space age, including several in development for future launch. The first solar-powered spacecraft employed body-mounted solar cells but designs quickly moved to extended panels to generate more electrical power. Early “paddle” designs were replaced by deployable twin rectangular “wings” which are still common in science missions and nearly ubiquitous in commercial telecommunications satellites. The increasing complexity of science missions investigating the nature of the space environment drove the development of the solar-powered satellites from the very beginning, and unique mission requirements to explore ever more distant and harsher regions of our solar system continue to drive innovations in spacecraft design, including solar arrays. This general progression to ever larger solar arrays to power ever more sophisticated spacecraft in ever harsher environments, punctuated by missions that emphasize lower cost and complexity, is a pattern that began in the 1960s and continues to this day. This chapter describes the solar array configurations used on deep space missions, with an emphasis on NASA’s planetary science missions, including specific design requirements that led to individual design selections. Future trends are also described.

Carolyn R Mercer↗

Semi-automated Design of Artificial Intelligence Earth Science Models

Prediction and observation of water cycles involve not only patterns isolated in space and time, but rather modeling complex spatio-temporal relationships across multiple sources of data and domains. For instance, Evapotranspiration (ET) and Leaf Area Indexes (LAI) are two critical components in DOE’s Energy Exascale Earth System Model (E3SM). Accurate assessments of ET and LAI are critical for understanding hydrological processes, deforestation, crop yield, and irrigation impacts. However, current ET estimates for global simulations are available at very coarse spatial resolution. They are usually derived from satellite data based on broad plant functional types (PFT), which fail to capture the fine-scale variations due to change in vegetation type across the globe. Within this context and in light of the data-model integration challenges highlighted in the EESSD Strategic Plan, the new era of AI model development for geosciences calls for data-driven methods that provide domain scientists with estimations of parameters such as PFT and LAI in an efficient, interpretable, and easy-to-operate manner.

Ambrozio Dias, Philipe↗