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NASA Tech Briefs, August 2012

Topics covered include: Mars Science Laboratory Drill; Ultra-Compact Motor Controller; A Reversible Thermally Driven Pump for Use in a Sub-Kelvin Magnetic Refrigerator; Shape Memory Composite Hybrid Hinge; Binding Causes of Printed Wiring Assemblies with Card-Loks; Coring Sample Acquisition Tool; Joining and Assembly of Bulk Metallic Glass Composites Through Capacitive Discharge; 670-GHz Schottky Diode-Based Subharmonic Mixer with CPW Circuits and 70-GHz IF; Self-Nulling Lock-in Detection Electronics for Capacitance Probe Electrometer; Discontinuous Mode Power Supply; Optimal Dynamic Sub-Threshold Technique for Extreme Low Power Consumption for VLSI; Hardware for Accelerating N-Modular Redundant Systems for High-Reliability Computing; Blocking Filters with Enhanced Throughput for X-Ray Microcalorimetry; High-Thermal-Conductivity Fabrics; Imidazolium-Based Polymeric Materials as Alkaline Anion-Exchange Fuel Cell Membranes; Electrospun Nanofiber Coating of Fiber Materials: A Composite Toughening Approach; Experimental Modeling of Sterilization Effects for Atmospheric Entry Heating on Microorganisms; Saliva Preservative for Diagnostic Purposes; Hands-Free Transcranial Color Doppler Probe; Aerosol and Surface Parameter Retrievals for a Multi-Angle, Multiband Spectrometer LogScope; TraceContract; AIRS Maps from Space Processing Software; POSTMAN: Point of Sail Tacking for Maritime Autonomous Navigation; Space Operations Learning Center; OVERSMART Reporting Tool for Flow Computations Over Large Grid Systems; Large Eddy Simulation (LES) of Particle-Laden Temporal Mixing Layers; Projection of Stabilized Aerial Imagery Onto Digital Elevation Maps for Geo-Rectified and Jitter-Free Viewing; Iterative Transform Phase Diversity: An Image-Based Object and Wavefront Recovery; 3D Drop Size Distribution Extrapolation Algorithm Using a Single Disdrometer; Social Networking Adapted for Distributed Scientific Collaboration; General Methodology for Designing Spacecraft Trajectories; Hemispherical Field-of-View Above-Water Surface Imager for Submarines; and Quantum-Well Infrared Photodetector (QWIP) Focal Plane Assembly.

Source record↗

Nearly hyperuniform, nonhyperuniform, and antihyperuniform density fluctuations in two-dimensional transition metal dichalcogenides with defects

Hyperuniform many-body systems in d-dimensional Euclidean space R d are characterized by completely suppressed (normalized) infinite-wavelength density fluctuations, and appear to be endowed with novel exotic physical properties. Recently, hyperuniform systems of disordered varieties have been observed in the context of various atomic-scale two-dimensional (2D) materials. Here, we analyze the effects of localized defects on the density fluctuations across length scales and on the hyperuniformity property of experimental samples of two-dimensional transition metal dichalcogenides. In particular, we extract atomic coordinates from time series annular dark field-scanning transmission electron microscopy (ADF-STEM) imaging data of 2D tungsten chalcogenides with the 2H structure (Te-doped 2H-WSe 2 ) showing continuous development and evolution of electron-beam induced defects, and construct the corresponding chemical-bonding informed coordination networks between the atoms. We then compute a variety of pair statistics and bond-orientational statistics to characterize the samples. At low defect concentrations, the corresponding materials are nearly hyperuniform, characterized by significantly suppressed scattering at the zero wave-number limit (omitting forward/ballistic scattering). As more defects are introduced, the (approximate) hyperuniformity of the materials is gradually destroyed, and the system becomes non-hyperuniform even when the material still contains a significant amount of crystalline regions. At high defect concentrations, the structures become antihyperuniform with diverging (normalized) large-scale density fluctuations, mimicking those typically observed at the thermal critical points associated with phase transitions. Overall, the defected materials possess varying degrees of orientation order, and there is apparently no intermediate hexatic phase emerging. To understand the observed nearly hyperuniform density fluctuations in the slightly defected materials, we construct a minimalist structural model and demonstrate that the experimental samples can be essentially viewed as perturbed honeycomb crystals with small correlated displacements and double chalcogen vacancies. Moreover, the small correlated displacements alone can significantly degrade hyperuniformity of the perfect honeycomb structure. Therefore, even a small amount of vacancies, when coupled with correlated displacements, can completely destroy hyperuniformity of the system.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Human Exploration Spacecraft Testbed for Integration and Advancement (HESTIA)

The proposed paper will cover ongoing effort named HESTIA (Human Exploration Spacecraft Testbed for Integration and Advancement), led at the National Aeronautics and Space Administration (NASA) Johnson Space Center (JSC) to promote a cross-subsystem approach to developing Mars-enabling technologies with the ultimate goal of integrated system optimization. HESTIA also aims to develop the infrastructure required to rapidly test these highly integrated systems at a low cost. The initial focus is on the common fluids architecture required to enable human exploration of mars, specifically between life support and in-situ resource utilization (ISRU) subsystems. An overview of the advancements in both integrated technologies, in infrastructure, in simulation, and in modeling capabilities will be presented, as well as the results and findings of integrated testing,. Due to the enormous mass gear-ratio required for human exploration beyond low-earth orbit, (for every 1 kg of payload landed on Mars, 226 kg will be required on Earth), minimization of surface hardware and commodities is paramount. Hardware requirements can be minimized by reduction of equipment performing similar functions though for different subsystems. If hardware could be developed which meets the requirements of both life support and ISRU it could result in the reduction of primary hardware and/or reduction in spares. Minimization of commodities to the surface of mars can be achieved through the creation of higher efficiency systems producing little to no undesired waste, such as a closed-loop life support subsystem. Where complete efficiency is impossible or impractical, makeup commodities could be manufactured via ISRU. Although, utilization of ISRU products (oxygen and water) for crew consumption holds great promise of reducing demands on life support hardware, there exist concerns as to the purity and transportation of commodities. To date, ISRU has been focused on production rates and purities for propulsion needs. The meshing of requirements between all potential users, producers, and cleaners of oxygen and water is crucial to guiding the development of technologies which will be used to perform these functions. Various new capabilities are being developed as part of HESTIA, which will enable the integrated testing of these technologies. This includes the upgrading of a 20' diameter habitat chamber to eventually support long duration (90+ day) human-in-the-loop testing of advanced life support systems. Additionally, a 20' diameter vacuum chamber is being modified to create Mars atmospheric pressures and compositions. This chamber, designated the Mars Environment Chamber (MEC), will eventually be upgraded to include a dusty environment and thermal shroud to simulate conditions on the surface of Mars. In view that individual technologies will be in geographically diverse locations across NASA facilities and elsewhere in the world, schedule and funding constraints will likely limit the frequency of physical integration. When this is the case, absent subsystems can be either digitally or physically simulated. Using the Integrated Power Avionics and Software (iPAS) environment, HESTIA is able to bring together data from various subsystems in simulated surroundings, insert faults, errors, time delays, etc., and feed data into computer models or physical systems capable of reproducing the output of the absent subsystems for the consumption of a local subsystems. Although imperfect, this capability provides opportunities to test subsystem integration and interactions at a fraction of the cost. When a subsystem technology is too immature for integrated testing, models can be produced using the General-Use Nodal Network Solver (GUNNS) capability to simulate the overall system performance. In doing so, even technologies not yet on the drawing board can be integrated and overall system performance estimated. Through the integrated development of technologies, as well as of the infrastructure to rapidly and at a low cost, model, simulate, and test subsystem technologies early in their development, HESTIA is pioneering a new way of developing the future of human space exploration.

Banker, Brian F.↗

An Influenced Future

Phobos is a vital precursor and catalyst before our next giant leap to Mars. The principle period of a Phobos' mission could be a series of robotic precursor missions for experimental perception, soil examination, ecological approval and landing site distinguishing proof. For my summer intern position at Johnson Space Center I chipped away at creating a GUNNS (General Use Nodal Network Solver) based power subsystem model for the miniATHLETE hopper, which is a conceptual (idea-based) robotic lander that will operate on Phobos. Keeping in mind the end goal to begin on my venture, I needed to comprehend my undertaking before whatever else, in which I concentrated on C++ to see how to implement the code that GUNNS generates to a Trick S_define file. Prior to coming to this internship at Johnson Space Center Dr. Edwin Zack Crues provided a class on modeling and simulation, which introduced me to the Trick simulation environment. The goal of my project was to develop a GUNNS based power subsystem model for the miniATHLETE hopper. The model needed to incorporate a solar array, battery, hopping legs, and onboard scientific instruments (sensitive measuring/recording devices). The secondary bonus goal after I completed the electrical aspect of my model was to develop a GUNNS based thermal subsystem model for the miniATHLETE hopper. Stringing the two aspects together, I would need to code up a signal aspect to make the system work as one. Accomplishing my goals would not be an easy thing, however I had successfully completed the electrical aspect model with twenty-four servos, six cameras, and multiple sensors. Venturing to complete my project has eluded me to many failures in my design to tune many things like the battery to the proper voltage and the load to the proper wattage. During this time I had touched up on advanced topics in calculus in which I implemented in the converter in my electrical model. I am currently working with my mentor Zu Qun Li to create a signal aspect to control the temperatures inside my electrical aspect model. During my time at JSC I had effectively figured out how to create subsystem models utilizing Trick and GUNNS. I obtain essential knowledge of power and thermal subsystem design for a robotic vehicle. I also learned how to work and communicate in a team effectively to accomplish a goal. Before coming to Johnson Space Center my future career and educational goals included uncertainty, however now I have a completely new look on my path to a prosperous future. My NASA experience has unquestionably impacted me to accomplish and surpass my own particular desires. After my time at Johnson Space Center I plan to apply for a coop position for NASA. This has been a dream come true that I adored each moment being at JSC realizing that I am far fit for doing things most individuals can just long for.

Owens, Christopher↗

Use of a Hybrid Edge Node-Centroid Node Approach to Thermal Modeling

A recent proposal submitted for an ESA mission required that models be delivered in ESARAD/ESATAN formats. ThermalDesktop was the preferable analysis code to be used for model development with a conversion done as the final step before delivery. However, due to some differences between the capabilities of the two codes, a unique approach was developed to take advantage of the edge node capability of ThermalDesktop while maintaining the centroid node approach used by ESARAD. In essence, two separate meshes were used: one for conduction and one for radiation. The conduction calculations were eliminated from the radiation surfaces and the capacitance and radiative calculations were eliminated from the conduction surfaces. The resulting conduction surface nodes were coincident with all nodes of the radiation surface and were subsequently merged, while the nodes along the edges remained free. Merging of nodes on the edges of adjacent surfaces provided the conductive links between surfaces. Lastly, all nodes along edges were placed into the subnetwork and the resulting supernetwork included only the nodes associated with radiation surfaces. This approach had both benefits and disadvantages. The use of centroid, surface based radiation reduces the overall size of the radiation network, which is often the most computationally intensive part of the modeling process. Furthermore, using the conduction surfaces and allowing ThermalDesktop to calculate the conduction network can save significant time by not having to manually generate the couplings. Lastly, the resulting GMM/TMM models can be exported to formats which do not support edge nodes. One drawback, however, is the necessity to maintain two sets of surfaces. This requires additional care on the part of the analyst to ensure communication between the conductive and radiative surfaces in the resulting overall network. However, with more frequent use of this technique, the benefits of this approach can far outweigh the additional effort.

Peabody, Hume L.↗

Use of a Hybrid Edge Node-Centroid Node Approach to Thermal Modeling

A recent proposal submitted for an ESA mission required that models be delivered in ESARAD/ESAT AN formats. ThermalDesktop was the preferable analysis code to be used for model development with a conversion done as the final step before delivery. However, due to some differences between the capabilities of the two codes, a unique approach was developed to take advantage of the edge node capability of ThermalDesktop while maintaining the centroid node approach used by ESARAD. In essence, two separate meshes were used: one for conduction and one for radiation. The conduction calculations were eliminated from the radiation surfaces and the capacitance and radiative calculations were eliminated from the conduction surfaces. The resulting conduction surface nodes were coincident with all nodes of the radiation surface and were subsequently merged, while the nodes along the edges remained free. Merging of nodes on the edges of adjacent surfaces provided the conductive links between surfaces. Lastly, all nodes along edges were placed into the subnetwork and the resulting supernetwork included only the nodes associated with radiation surfaces. This approach had both benefits and disadvantages. The use of centroid, surface based radiation reduces the overall size of the radiation network, which is often the most computationally intensive part of the modeling process. Furthermore, using the conduction surfaces and allowing ThermalDesktop to calculate the conduction network can save significant time by not having to manually generate the couplings. Lastly, the resulting GMM/TMM models can be exported to formats which do not support edge nodes. One drawback, however, is the necessity to maintain two sets of surfaces. This requires additional care on the part of the analyst to ensure communication between the conductive and radiative surfaces in the resulting overall network. However, with more frequent use of this technique, the benefits of this approach can far outweigh the additional effort.

Peabody, Hume L.↗

Convolutional Neural Network–Aided Temperature Field Reconstruction: An Innovative Method for Advanced Reactor Monitoring

In this study, the capabilities of a physics-informed convolutional neural network (CNN) for reconstructing the temperature field from a limited set of measurements taken at the boundaries of internal flows are demonstrated. Such an approach enables the development of less invasive monitoring methods for real-time plant diagnostics. As a test case, a Molten Salt Fast Reactor (MSFR) design was selected. This circulating fuel reactor has received interest from both scientific and industrial communities due to its intrinsic safety and sustainability. Molten salt flows in such reactors, however, can present highly localized temperature peaks that can induce significant thermal stresses onto the vessel walls. At these local maxima, the salt temperature may exceed a thousand kelvins, which makes a direct measurement challenging or even unfeasible. The proposed CNN algorithm allows one to detect indirectly such discontinuities through an accurate, albeit indirect, temperature measurement method during reactor operation. The datasets employed to train and test the machine learning models in the present work were generated with Nek5000, a computational fluid dynamics (CFD) code developed at Argonne National Laboratory. The CNN algorithm is trained with CFD results that span a set of MSFR operational power and flow ranges. Here, to demonstrate the efficacy of the algorithm, predictions are made for test cases contained within the training range but for which the CFD data were not used when training. Results demonstrate that the proposed technique properly characterizes temperature peaks and distributions within the domain for a broad range of scenarios.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Liquid Oxygen/Liquid Methane Integrated Power and Propulsion

The proposed paper will cover ongoing work at the National Aeronautics and Space Administration (NASA) Johnson Space Center (JSC) on integrated power and propulsion for advanced human exploration. Specifically, it will present findings of the integrated design, testing, and operational challenges of a liquid oxygen / liquid methane (LOx/LCH4) propulsion brassboard and Solid Oxide Fuel Cell (SOFC) system. Human-Mars architectures point to an oxygen-methane economy utilizing common commodities, scavenged from the planetary atmosphere and soil via In-Situ Resource Utilization (ISRU), and common commodities across sub-systems. Due to the enormous mass gear-ratio required for human exploration beyond low-earth orbit, (for every 1 kg of payload landed on Mars, 226 kg will be required on Earth) increasing commonality between spacecraft subsystems such as power and propulsion can result in tremendous launch mass and volume savings. Historically, propulsion and fuel cell power subsystems have had little interaction outside of the generation (fuel cell) and consumption (propulsion) of electrical power. This was largely due to a mismatch in preferred commodities (hypergolics for propulsion; oxygen & hydrogen for fuel cells). Although this stove-piped approach benefits from simplicity in the design process, it means each subsystem has its own tanks, pressurization system, fluid feed system, etc. increasing overall spacecraft mass and volume. A liquid oxygen / liquid methane commodities architecture across propulsion and power subsystems would enable the use of common tankage and associated pressurization and commodity delivery hardware for both. Furthermore, a spacecraft utilizing integrated power and propulsion could use propellant residuals - propellant which could not be expelled from the tank near depletion due to hydrodynamic considerations caused by large flow demands of a rocket engine - to generate power after all propulsive maneuvers are complete thus utilizing previously wasted mass. Such is the case for human and robotic planetary landers. Although many potential benefits through integrated power & propulsion exist, integrated operations have yet to be successfully demonstrated and many challenges have already been identified the most obvious of which is the large temperature gradient. SOFC chemistry is exothermic with operating temperatures in excess of 1,000 K; however, any shared commodities will be undoubtedly stored at cryogenic temperatures (90-112 K) for mass efficiency reasons. Spacecraft packaging will drive these two subsystems in close proximity thus heat leak into the commodity tankage must be minimized and/or mitigated. Furthermore, commodities must be gasified prior to consumption by the SOFC. Excess heat generated by the SOFC could be used to perform this phase change; however, this has yet to be demonstrated. A further identified challenge is the ability of the SOFC to handle the sudden power spikes created by the propulsion system. A power accumulator (battery) will likely be necessary to handle these sudden demands while the SOFC thermally adjusts. JSC's current SOFC test system consists of a 1 kW fuel cell designed by Delphi. The fuel cell is currently undergoing characterization testing at the NASA JSC Energy Systems Test Area (ESTA) after which a Steam Methane Reformer (SMR) will be integrated and the combined system tested in closed-loop. The propulsion brassboard is approximately the size of what could be flown on a sounding rocket. It consists of one 100 lbf thrust "main" engine developed for NASA by Aerojet and two 10 lbf thrusters to simulate a reaction control system developed at NASA JSC. This system is also under development and initial testing at ESTA. After initial testing, combined testing will occur which will provide data on the fuel cell's ability to sufficiently handle the power spikes created by the propulsion system. These two systems will also be modeled using General-Use Nodal Network Solver (GUNNS) software. Once anchored with test data, this model will be used to extrapolate onto other firing profiles and used to size the power accumulator.

Banker, Brian↗

Machine learning of consistent thermodynamic models using automatic differentiation

In this study, we propose a data-driven method to describe consistent equations of state (EOS) for arbitrary systems. Complex EOS are traditionally obtained by fitting suitable analytical expressions to thermophysical data. A key aspect of EOS is that the relationships between state variables are given by derivatives of the system free energy. In this work, we model the free energy with an artificial neural network and utilize automatic differentiation to directly learn the derivatives of the free energy. We demonstrate this approach on two different systems, the analytic van der Waals EOS and published data for the Lennard-Jones fluid, and we show that it is advantageous over direct learning of thermodynamic properties (i.e., not as derivatives of the free energy but as independent properties), in terms of both accuracy and the exact preservation of the Maxwell relations. Furthermore, the method implicitly provides the free energy of a system without explicit integration.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

PowerModelsGAT-AI: Physics-Informed Graph Attention for Multi-System Power Flow With Continual Learning

Solving the alternating current power flow equations in real time is essential for secure grid operation, yet classical Newton–Raphson solvers can be slow under stressed conditions. Existing graph neural networks for power flow are typically trained on a single system and often degrade on different systems. We present PowerModelsGAT-AI, a physics-informed graph attention network that predicts bus voltages and generator injections. The model uses bus-type-aware masking to handle different bus types and balances multiple loss terms, including a power-mismatch penalty, using learned weights. We evaluate the model on 14 benchmark systems (4 to 6,470 buses) and train a unified model on 13 of these under contingency conditions with up to two branch outages, achieving an average normalized mean absolute error of 0.89% for voltage magnitudes and R 2 >0.99 for voltage angles. We also show continual learning: when adapting a base model to a new 1,354-bus system, standard fine-tuning causes severe forgetting with error increases exceeding 1000% on base systems, while our experience replay and elastic weight consolidation strategy keeps error increases below 2% and in some cases improves base-system performance. Interpretability analysis shows that learned attention weights correlate with physical branch parameters (susceptance: r=0.38 ; thermal limits: r=0.22 ), and feature importance analysis supports that the model captures established power flow relationships.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA Tech Briefs, May 2004

Topics include: Embedded Heaters for Joining or Separating Plastic Parts; Curing Composite Materials Using Lower-Energy Electron Beams; Aluminum-Alloy-Matrix/Alumina-Reinforcement Composites; Fibrous-Ceramic/Aerogel Composite Insulating Tiles; Urethane/Silicone Adhesives for Bonding Flexing Metal Parts; Scalable Architecture for Multihop Wireless ad Hoc Networks; Improved Thermoplastic/Iron-Particle Transformer Cores; Cooperative Lander-Surface/Aerial Microflyer Missions for Mars Exploration Dual-Frequency Airborne Scanning Rain Radar Antenna System Eight-Channel Continuous Timer Reduction of Phase Ambiguity in an Offset-QPSK Receiver Ambient-Light-Canceling Camera Using Subtraction of Frames Lightweight, Flexible, Thin, Integrated Solar-Power Packs Windows(Registered Trademark)-Based Software Models Cyclic Oxidation Behavior Software for Analyzing Sequences of Flow-Related Images Improved Ball-and-Socket Docking Mechanism Two-Stage Solenoid Ordered Nanostructures Made Using Chaperonin Polypeptides Low-Temperature Plasma Functionalization of Carbon Nanotubes Improved Cryostat for Cooling a Wide Panel Current Pulses Momentarily Enhance Thermoelectric Cooling Hand-Held Color Meters Based on Interference Filters Calculating Mass Diffusion in High-Pressure Binary Fluids Fresnel Lenses for Wide-Aperture Optical Receivers Increasing Accuracy in Computed Inviscid Boundary Conditions Higher-Order Finite Elements for Computing Thermal Radiation Radar for Monitoring Hurricanes from Geostationary Orbit Time-Transfer System for Two Orbiting Spacecraft

Source record↗

Anomalously strong viscosity behavior in mixed oxy-sulfide Na 4 P 2 S 7-x O x invert glasses

In this paper, the first observations have been made of anomalously strong viscosity behavior and correspondingly strong bulk glass formation and resistance to crystallization in a melt quenched (MQ) prepared series of invert, modifier content greater than the glass former content, mixed oxy-sulfide Na 4 P 2 S 7-x O x , 0 ≤ x ≤ 5, (NaPSO) glasses. We find that these glasses even with 67 mole % modifier, Na 2 S, and only 33 mole% glass former P 2 S 5-x O x , exhibit a calorimetric fragility index, m cal , as small as 29 compared to typical values of ~ 60 to 80 for alkali silicate glasses with > 50 mole% SiO 2 and the theoretical minimum m cal of ~ 15. The m cal values were converted to kinetic viscosity fragility, m vis , values and used with the measured glass transition temperatures, T g s, to produce viscosity curves for the glasses using the Mauro-Yue-Ellison-Gupta-Allan (MYEGA) model. The viscosity of the glass with a minimum m cal value of x = 2.5 was then shown to exhibit a viscosity that was as strong as, and for some compositions stronger than, the viscosity of alkali aluminosilicate glasses which have three dimensional network structures compared to the one dimensional chain structures observed in these MOS invert glasses. Consistent with these small values of fragility indices and therefore predicted higher viscosity above the glass transition temperature, T g , in the supercooled liquid regime, these glasses are also particularly resistant to crystallization. For example, the x = 2.5 glass composition exhibits a crystallization temperature, T C , more than 150K above its T g . We find that the calorimetric fragility of these glasses varies systematically with the extent of network forming bridging oxygens (BOs) in the glasses. The structural change caused by incrementally replacing sulfur with oxygen has been found to have consistent, large effects on the thermal properties.

36 MATERIALS SCIENCE↗

Precipitation from Space: Advancing Earth System Science

Of the three primary sources of spatially contiguous precipitation observations (surface networks, ground-based radar, and satellite-based radar/radiometers), only the last is a viable source over ocean and much of the Earth's land. As recently as 15 years ago, users needing quantitative detail of precipitation on anything under a monthly time scale relied upon products derived from geostationary satellite thermal infrared (IR) indices. The Special Sensor Microwave Imager (SSMI) passive microwave (PMW) imagers originated in 1987 and continue today with the SSMI sounder (SSMIS) sensor. The fortunate longevity of the joint National Aeronautics and Space Administration (NASA) and Japan Aerospace Exploration Agency (JAXA) Tropical Rainfall Measuring Mission (TRMM) is providing the environmental science community a nearly unbroken data record (as of April 2012, over 14 years) of tropical and sub-tropical precipitation processes. TRMM was originally conceived in the mid-1980s as a climate mission with relatively modest goals, including monthly averaged precipitation. TRMM data were quickly exploited for model data assimilation and, beginning in 1999 with the availability of near real time data, for tropical cyclone warnings. To overcome the intermittently spaced revisit from these and other low Earth-orbiting satellites, many methods to merge PMW-based precipitation data and geostationary satellite observations have been developed, such as the TRMM Multisatellite Precipitation Product and the Climate Prediction Center (CPC) morphing method (CMORPH. The purpose of this article is not to provide a survey or assessment of these and other satellite-based precipitation datasets, which are well summarized in several recent articles. Rather, the intent is to demonstrate how the availability and continuity of satellite-based precipitation data records is transforming the ways that scientific and societal issues related to precipitation are addressed, in ways that would not be otherwise possible. These developments have taken place in parallel with the growth of an increasingly interconnected scientific environment. Scientists from different disciplines can easily interact with each other via information and materials they encounter online, and collaborate remotely without ever meeting each other in person. Likewise, these precipitation datasets are quickly and easily available via various data portals and are widely used. Within the framework of the NASA/JAXA Global Precipitation Measurement (GPM mission, these applications will become increasingly interconnected. We emphasize that precipitation observations by themselves provide an incomplete picture of the state of the atmosphere. For example, it is unlikely that a richer understanding of the global water cycle will be possible by standalone missions and algorithms, but must also involve some component of data, where model analyses of the physical state are constrained alongside multiple observations (e.g., precipitation, evaporation, radiation). The next section provides examples extracted from the many applications that use various high-resolution precipitation products. The final section summarizes the future system for global precipitation processing.

Kucera, Paul A.↗

Inferring the Thermal History of the Intergalactic Medium from the Properties of the Hydrogen and Helium Lyα Forest

The filamentary network of intergalactic medium (IGM) gas that gives origin to the Lyα forest in the spectra of distant quasars encodes information on the physics of structure formation and the early thermodynamics of diffuse baryonic material. Here we use a massive suite of more than 400 high-resolution cosmological hydrodynamical simulations run with the Graphics Processing Unit–accelerated code Cholla to study the IGM at high spatial resolution maintained over the entire computational volume. The simulations capture a wide range of possible IGM thermal histories by varying the photoheating and photoionizing background produced by star-forming galaxies and active galactic nuclei. A statistical comparison of synthetic spectra with the observed 1D flux power spectra of hydrogen at redshifts 2.2 ≤ z ≤ 5.0 and with the helium Lyα opacity at redshifts 2.4 < z < 2.9 tightly constrains the photoionization and photoheating history of the IGM. By leveraging the constraining power of the available Lyα forest data to break model degeneracies, we find that the IGM experienced two main reheating events over 1.2 Gyr of cosmic time. For our best-fit model, hydrogen reionization completes by z R ≈ 6.0 with a first IGM temperature peak of T 0 ≃ 1.3 × 10 4 K and is followed by the reionization of He ii that completes by z R ≈ 3.0 and yields a second temperature peak of T 0 ≃ 1.4 × 10 4 K. We discuss how our results can be used to obtain information on the timing and the sources of hydrogen and helium reionization.

79 ASTRONOMY AND ASTROPHYSICS↗

Machine-learning modeling of magnetization dynamics in quasi-equilibrium and driven metallic spin systems

Here, we present a perspective on recent progress in machine-learning (ML) force-field approaches for large-scale Landau–Lifshitz–Gilbert (LLG) simulations of metallic spin systems. Building on a generalization of the Behler–Parrinello (BP) architecture originally developed for quantum molecular dynamics, we develop scalable and transferable ML models that faithfully capture the complex, environment-dependent electron-mediated exchange fields characteristic of itinerant magnets. A central ingredient of this framework is the implementation of symmetry-aware magnetic descriptors based on group-theoretical bispectrum formalisms. Leveraging these ML force fields, LLG simulations faithfully reproduce hallmark non-collinear magnetic orders—such as the 120° and tetrahedral states—on the triangular lattice, and successfully capture the complex spin textures emerging in the mixed-phase states of a square-lattice double-exchange model under thermal quench. We further discuss a generalized potential theory that extends the BP formalism to incorporate both conservative and nonconservative electronic torques, thereby enabling ML models to learn nonequilibrium exchange fields from computationally demanding microscopic approaches such as nonequilibrium Green’s-function techniques. This extension yields quantitatively accurate predictions of voltage-driven domain-wall motion and establishes a foundation for quantum-accurate, multiscale modeling of nonequilibrium spin dynamics and spintronic functionalities.

Descriptors↗

The International Space Station and the Space Debris Environment: 10 Years On

For just over a decade the International Space Station (ISS), the most heavily protected vehicle in Earth orbit, has weathered the space debris environment well. Numerous hypervelocity impact features on the surface of ISS caused by small orbital debris and meteoroids have been observed. In addition to typical impacts seen on the large solar arrays, craters have been discovered on windows, hand rails, thermal blankets, radiators, and even a visiting logistics module. None of these impacts have resulted in any degradation of the operation or mission of the ISS. Validating the rate of small particle impacts on the ISS as predicted by space debris environment models is extremely complex. First, the ISS has been an evolving structure, from its original 20 metric tons to nearly 300 metric tons (excluding logistics vehicles) ten years later. Hence, the anticipated space debris impact rate has grown with the increasing size of ISS. Secondly, a comprehensive visual or photographic examination of the complete exterior of ISS has never been accomplished. In fact, most impact features have been discovered serendipitously. Further complications include the estimation of the size of an impacting particle without knowing its mass, velocity, and angle of impact and the effect of shadowing by some ISS components. Inadvertently and deliberately, the ISS has also been the source of space debris. The U.S. Space Surveillance Network officially cataloged 65 debris from ISS from November 1998 to November 2008: from lost cameras, sockets, and tool bags to intentionally discarded equipment and an old space suit. Fortunately, the majority of these objects fall back to Earth quickly with an average orbital lifetime of less than two months and a maximum orbital lifetime of a little more than 15 months. The cumulative total number of debris object-years is almost exactly 10, the equivalent of one piece of debris remaining in orbit for 10 years. An unknown number of debris too small to be tracked and cataloged have also been generated, but normally with even shorter orbital lifetimes. Finally, eight collision avoidance maneuvers have been performed to avoid potential collisions between ISS and large, tracked space debris. The most recent such maneuver was accomplished by ESA's Automated Transfer Vehicle, the Jules Verne, just three months before the 10th anniversary of the launch of ISS's first element.

Johnson, Nicholas↗

Exact representations of many-body interactions with restricted-Boltzmann-machine neural networks

Restricted Boltzmann machines (RBMs) are simple statistical models defined on a bipartite graph which have been successfully used in studying more complicated many-body systems, both classical and quantum. In this work, we exploit the representation power of RBMs to provide an exact decomposition of many-body contact interactions into one-body operators coupled to discrete auxiliary fields. This construction generalizes the well known Hirsch's transform used for the Hubbard model to more complicated theories such as pionless effective field theory in nuclear physics, which we analyze in detail. Finally, we also discuss possible applications of our mapping for quantum annealing applications and conclude with some implications for RBM parameter optimization through machine learning.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Novel Approach for Modeling Chemical Reaction in Generalized Fluid System Simulation Program

The Generalized Fluid System Simulation Program (GFSSP) is a computer code developed at NASA Marshall Space Flight Center for analyzing steady state and transient flow rates, pressures, temperatures, and concentrations in a complex flow network. The code, which performs system level simulation, can handle compressible and incompressible flows as well as phase change and mixture thermodynamics. Thermodynamic and thermophysical property programs, GASP, WASP and GASPAK provide the necessary data for fluids such as helium, methane, neon, nitrogen, carbon monoxide, oxygen, argon, carbon dioxide, fluorine, hydrogen, water, a hydrogen, isobutane, butane, deuterium, ethane, ethylene, hydrogen sulfide, krypton, propane, xenon, several refrigerants, nitrogen trifluoride and ammonia. The program which was developed out of need for an easy to use system level simulation tool for complex flow networks, has been used for the following purposes to name a few: Space Shuttle Main Engine (SSME) High Pressure Oxidizer Turbopump Secondary Flow Circuits, Axial Thrust Balance of the Fastrac Engine Turbopump, Pressurized Propellant Feed System for the Propulsion Test Article at Stennis Space Center, X-34 Main Propulsion System, X-33 Reaction Control System and Thermal Protection System, and International Space Station Environmental Control and Life Support System design. There has been an increasing demand for implementing a combustion simulation capability into GFSSP in order to increase its system level simulation capability of a liquid rocket propulsion system starting from the propellant tanks up to the thruster nozzle for spacecraft as well as launch vehicles. The present work was undertaken for addressing this need. The chemical equilibrium equations derived from the second law of thermodynamics and the energy conservation equation derived from the first law of thermodynamics are solved simultaneously by a Newton-Raphson method. The numerical scheme was implemented as a User Subroutine in GFSSP.

Sozen, Mehmet↗