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At least 1,387 records · Page 77

Community Coordinated Modeling Center Support of Science Needs for Integrated Data Environment

Space science models are essential component of integrated data environment. Space science models are indispensable tools to facilitate effective use of wide variety of distributed scientific sources and to place multi-point local measurements into global context. The Community Coordinated Modeling Center (CCMC) hosts a set of state-of-the- art space science models ranging from the solar atmosphere to the Earth's upper atmosphere. The majority of models residing at CCMC are comprehensive computationally intensive physics-based models. To allow the models to be driven by data relevant to particular events, the CCMC developed an online data file generation tool that automatically downloads data from data providers and transforms them to required format. CCMC provides a tailored web-based visualization interface for the model output, as well as the capability to download simulations output in portable standard format with comprehensive metadata and user-friendly model output analysis library of routines that can be called from any C supporting language. CCMC is developing data interpolation tools that enable to present model output in the same format as observations. CCMC invite community comments and suggestions to better address science needs for the integrated data environment.

Kuznetsova, M. M.↗

Operational Parameters, Considerations, and Design Decisions for Resource-Constrained Ion Trap Mass Spectrometers

Mass spectrometers are increasingly finding applications in new and unique areas, often in situations where key operational resources (i.e. power, weight and size) are limited. One such example is the Mars Organic Molecule Analyzer (MOMA). This instrument is a joint venture between NASA and the European Space Agency (ESA) to develop an ion trap mass spectrometer for chemical analysis on Mars. The constraints on such an instrument are significant as are the performance requirements. While the ideal operating parameters for an ion trap are generally well characterized, methods to maintain analytical performance with limited power and system weight need to be investigated and tested. Methods Experiments have been performed on two custom ion trap mass spectrometers developed as prototypes for the MOMA instrument. This hardware consists of quadrupole ion trap electrodes that are 70% the size of common commercial instrumentation. The trapping RF voltage is created with a custom tank circuit that can be tuned over a range of RF frequencies and is driven using laboratory supplies and amplifiers. The entire instrument is controlled with custom Lab VIEW software that allows a high degree of flexibility in the definition of the scan function defining the ion trap experiment. Ions are typically generated via an internal electron ionization source, however, a laser desorption source is also in development for analysis of larger intact molecules. Preliminary Data The main goals in this work have been to reduce the power required to generate the radio frequency trapping field used in an ion trap mass spectrometer. Generally minimizing the power will also reduce the volume and mass of the electronics to support the instrument. In order to achieve optimum performance, commercial instruments typically utilize RF frequencies in the 1 MHz range. Without much concern for power usage, they simply generate the voltage required to access the mass range of interest. In order to reduce the required RF voltage (and power), operation of the ion trap at lower RF frequencies has been investigated. Surprisingly, the performance of the instrument has only been slightly degraded at RF frequencies all the way down to 500 kHz. Mass resolution is relatively stable to this point and depending on the resonant ejection point used, the peak intensity is also quite stable. To date only masses up to m/z 200 have been fully investigated, however, additional studies are planned to verify the performance with higher mass ions. The lower frequency and voltage should reduce the pseudo potential well depth, eventually affecting the trapping efficiency of the instrument -- effect that could manifest itself in significantly limiting the mass range of trapped ions. Other methods to reduce the RF power while maintaining analytical performance are also under investigation. This includes ion ejection at lower q(sub z) values to access a given mass with a lower RF voltage. The loss of mass resolution at lower q(sub eject) points has been measured and current work is underway to leverage scan speed and the use of non-linear resonances in order to counter this trend. The overall trap performance under this range of operating conditions will be presented with a goal of identifying what trade-offs are acceptable.

Danell, Ryan M.↗

The Interstellar Bullet Engine IRAS 05506+2414

Throughout their life-cycles, high-mass stars inject large amounts of energy and momentum into theirenvironments through stellar winds. Results from a study of the Orion BN/KL region indicate that disruption of a massive young stellar system can lead to an explosive event producing a wide-angle outflow, different from the classical bipolar flows driven by young stellar object (YSO) accretion disks. The discovery of a massive YSO, IRAS 05506+2414, may prove to be the second instance of this uncommon outflow. Prior to this study, data was collected using the Arizona Radio Observatory's 10-meter and 12-meter telescopes. Spectra of 16 different molecular line transitions were organized, reduced, and prepared for further analysis. A variety of molecular transitions were observed, such as 12CO 2-1, HCO+ 3-2, CS 3-2, in order to probe physical conditions of the YSO. From line transitions like HCO+ 3-2, we will determine physical properties like density, temperature, and velocity of our source object. For each molecular transition, the spectra were averaged in subsets, which were then averaged to produce a final spectra with an optimal signal to noise ratio. Future radiative modeling will yield mass and energetics of IRAS05506+2414.

millimeter-wave↗

Synthetic Scientific Image Generation with VAE, GAN, and Diffusion Model Architectures

Generative AI (genAI) has emerged as a powerful tool for synthesizing diverse and complex image data, offering new possibilities for scientific imaging applications. This review presents a comprehensive comparative analysis of leading generative architectures, ranging from Variational Autoencoders (VAEs) to Generative Adversarial Networks (GANs) on through to Diffusion Models, in the context of scientific image synthesis. We examine each model's foundational principles, recent architectural advancements, and practical trade-offs. Our evaluation, conducted on domain-specific datasets including microCT scans of rocks and composite fibers, as well as high-resolution images of plant roots, integrates both quantitative metrics (SSIM, LPIPS, FID, CLIPScore) and expert-driven qualitative assessments. Results show that GANs, particularly StyleGAN, produce images with high perceptual quality and structural coherence. Diffusion-based models for inpainting and image variation, such as DALL-E 2, delivered high realism and semantic alignment but generally struggled in balancing visual fidelity with scientific accuracy. Importantly, our findings reveal limitations of standard quantitative metrics in capturing scientific relevance, underscoring the need for domain-expert validation. We conclude by discussing key challenges such as model interpretability, computational cost, and verification protocols, and discuss future directions where generative AI can drive innovation in data augmentation, simulation, and hypothesis generation in scientific research.

Generative Adversarial Networks↗

Cumulative Spatial Impact Layers: A Novel Multivariate Spatio-Temporal Analytical Summarization Tool

Scientific inquiry often requires analysis of multiple spatio-temporal datasets, ranging in type and size, using complex multi-step processes demanding an understanding of GIS theory and software. Cumulative Spatial Impact Layers (CSIL) is a GIS-based tool that summarizes spatio-temporal datasets based on overlapping features and attributes. Leveraging a recursive quadtree method, and applying multiple additive frameworks, the CSIL tool allows users to analyze raster and vector datasets by calculating data, record, or attribute density. Providing an efficient and robust method for summarizing disparate, multi-format, multi-source geospatial data, CSIL addresses the need for a new integration approach and resulting geospatial product. The built-in flexibility of the CSIL tool allows users to answer a range of spatially-driven questions. Example applications are provided in this paper to illustrate the versatility and variety of uses for this CSIL tool and method. Use cases include addressing regulatory decision-making needs, economic modeling, and resource management. Performance reviews for each use case are also presented, demonstrating how CSILs provides a more efficient and robust approach to assess a range of multivariate spatial data for a variety of uses.

58 GEOSCIENCES↗

A fusion relevant data-driven engineering void swelling model for 9Cr tempered martensitic steels

The UCSB database on cavity evolution in 9-12Cr tempered martensitic steels (TMS), includes the results for both dual heavy and helium ion (DII), and High Flux Isotope Reactor (HFIR) in situ helium injection (ISHI) neutron irradiations at 500°C. These results were combined with literature single ion and fission neutron irradiation data to derive a model for the void volume fraction, f v , as a function of displacements per atom (dpa) and transmutant helium concentrations in atomic parts per million (appm). The scientific foundation for the paper is described in a companion paper entitled “Cavity Evolution and Void Swelling in Dual Ion Irradiated Tempered Martensitic Steels”. Here, in this study, we show that f v (dpa, He/dpa) is described by the incubation dose, dpa i , for the onset of void growth, and the post-incubation growth rate, f v ’(%/dpa). Both dpa i and f v ’ decrease with increasing He/dpa at > ~ 5. The dpa i is also lower for the ISHI neutron irradiations at the same He/dpa. Single heavy ion and fission reactor neutron irradiations, with low He/dpa ratios, have a much larger dpa i . Based on a combined analysis of DII, single ion, ISHI and fission neutron data, we further show that the post-incubation f v data analyzed here have a common empirical curve shape, with f v ’ reaching up to ~ 0.2%/dpa at very high dpa. We also show that f v ’ can be predicted based on a physical model of defect partitioning between evolving sinks. At 500°C and fusion relevant He/dpa ≈ 10, the best-fit model predicts nominal swelling, S = f v /(1-f v ), of ~ 1.1, 4.9 and 16% at 50, 100 and 200 dpa, respectively. The physically motivated, data-driven model includes estimated uncertainties for both dpa i and f v ’.

36 MATERIALS SCIENCE↗

A simulation-based model for understanding the time dependent x-ray drive asymmetries and error bars in indirectly driven implosions on the National Ignition Facility

Time-dependent low-mode asymmetries are believed to play a leading role in limiting the performance of current inertial confinement fusion implosions on the National Ignition Facility (NIF) [E. I. Moses et al., Phys. Plasmas 16, 041006 (2009)]. These long wavelength modes are initiated and driven by asymmetries in the x-ray flux from the hohlraum; however, the underlying hydrodynamics of the implosion also act to modify and amplify these asymmetries. Here we present here a simulation-based model connecting the time-dependent drive asymmetry seen by the capsule to the measured inflight and hot spot symmetries. This approach is based on a Green's function analysis for which we evaluate the response of the capsule to impulses of drive asymmetry at a series of times. Our model sheds new light on the sensitivity to the drive asymmetry of an imploded capsule, giving a new tool for design. Inverting the problem and finding the drive asymmetry needed to match the experimental data allow us to tightly constrain the drive asymmetry seen by the capsule, providing an error estimate on the result. Doing so, we are able to point out when and how the complex hohlraum simulations start to deviate from what they should obtain to match the experimental data. Ultimately, we project to use this model to make some experimental recommendations to fix the time-dependent low-mode asymmetry of indirectly driven implosions and identify additional measurements to further constrain the asymmetries with a view to improving target design on the NIF.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Interpretation of the BRITE oscillation data of the hybrid pulsator ν Eridani: a call for the modification of stellar opacities

The analysis of the BRIght Target Explorer (BRITE) oscillation spectrum of the main-sequence early B-type star ν Eridani is presented in this paper. Only models with the modified mean opacity profile can account for the observed frequency ranges as well as for the values of some individual frequencies. The number of the κ-modified seismic models is constrained by the non-adiabatic parameter f, which is very sensitive to the opacity changes in the subphotospheric layers, where the pulsations are driven. We present an example of the model that satisfies all the above conditions. It seems that the OPLIB opacities are preferred over those from the OPAL and OP projects. Finally and moreover, we discuss additional consequences of the opacity modification, namely, an enhancement of the efficiency of convection in the Z bump as well as an occurrence of close radial modes which is a kind of avoided-crossing phenomenon common for non-radial modes in standard main-sequence models.

79 ASTRONOMY AND ASTROPHYSICS↗

Observation and analysis of emergent coherent structures in a high-energy-density shock-driven planar mixing layer experiment

Coherent emergent structures have been observed in a high-energy-density supersonic mixing layer experiment. A millimeter-scale shock tube uses lasers to drive Mbar shocks into the tube volume. The shocks are driven into initially solid foam (60 mg/cm 3 ) hemicylinders separated by an Al or Ti metal tracer strip; the components are vaporized by the drive. Before the experiment disassembles, the shocks cross at the tube center, creating a very fast (ΔU > 200 km/s) shear-unstable zone. After several nanoseconds, an expanding mixing layer is measured, and after 10+ ns we observe the appearance of streamwise-periodic, spanwise-aligned rollers associated with the primary Kelvin-Helmholtz instability of mixing layers. We additionally image roller pairing and spanwise-periodic streamwise-aligned filaments associated with secondary instabilities. New closures are derived to connect length scales of these structures to estimates of fluctuating velocity data otherwise unobtainable in the high-energy-density environment. Finally, this analysis indicates shear-induced specific turbulent energies 10 3 – 10 4 times higher than the nearest conventional experiments. Because of difficulties in continuously driving systems under these conditions and the harshness of the experimental environment limiting the usable diagnostics, clear evidence of these developing structures has never before been observed in this regime.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A TCN-Based Hybrid Forecasting Framework for Hours-Ahead Utility-Scale PV Forecasting

This paper presents a Temporal Convolutional Network (TCN) based hybrid PV forecasting framework for enhancing hours-ahead utility-scale PV forecasting. The hybrid framework consists of two forecasting models: a physics-based trend forecasting (TF) model and a data-driven fluctuation forecasting (FF) model. Three TCNs are integrated in the framework for: i) blending the inputs from different Numerical Weather Prediction sources for the TF model to achieve superior performance on forecasting hourly PV profiles, ii) capturing spatial-temporal correlations between detector sites and the target site in the FF model to achieve more accurate forecast of intra- hour PV power drops, and iii) reconciling TF and FF results to obtain coherent hours-ahead PV forecast with both hourly trends and intra-hour fluctuations well preserved. To automatically identify the most contributive neighboring sites for forming a detector network, a scenario-based correlation analysis method is developed, which significantly improves the capability of the FF model on capturing large power fluctuations caused by cloud movements. Here, the framework is developed, tested, and validated using actual PV data collected from 95 PV farms in North Carolina. Simulation results show that the performance of 6 hours ahead PV power forecasting is improved by 20% - 30% compared with state-of-the-art methods.

42 ENGINEERING↗

Systematics in the XENON1T data: The 15-keV anti-axion

The XENON1T collaboration Aprile et al. [2020] has found an excess of electron recoil events in their Science Run 1 data below ~7 keV with a spectral shape consistent with that expected from a solar-axion-induced signal. The claimed statistical significance of the solar-axion model over the null hypothesis is 3.5σ. In this work we provide suggestive evidence for mismodeling in the electron recoil data that may decrease the local significance of the axion model. To reach this conclusion, we search for a signal with the spectral template of the solar axion model, but shifted to higher (unphysical) energies above ~7 keV. We find that the distribution of significances found from this side-band analysis does not follow the expected chi-square distribution. For example, we find a high-significance feature in the data, with a global $p$-value $p≈0.026$, when the solar axion model is shifted upwards in energy by ~15 keV and allowed to have a negative normalization. We argue that such statistical tests, if performed a priori, provide a data-driven way to test and potentially account for systematic uncertainties on the background model in low-threshold dark matter experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

Accurate Modeling of Bromide and Iodide Hydration with Data-Driven Many-Body Potentials

Ion–water interactions play a central role in determining the properties of aqueous systems in a wide range of environments. However, a quantitative understanding of how the hydration properties of ions evolve from small aqueous clusters to bulk solutions and interfaces remains elusive. Here, we introduce the second generation of data-driven many-body energy (MBnrg) potential energy functions (PEFs) representing bromide–water and iodide–water interactions. The MB-nrg PEFs use permutationally invariant polynomials to reproduce two-body and three-body energies calculated at the coupled cluster level of theory, and implicitly represent all higher-body energies using classical many-body polarization. Further, a systematic analysis of the hydration structure of small Br - (H 2 O) n and I - (H 2 O) n clusters demonstrates that the MBnrg PEFs predict interaction energies in quantitative agreement with “gold standard” coupled cluster reference values. Importantly, when used in molecular dynamics simulations carried out in the isothermal-isobaric ensemble for single bromide and iodide ions in liquid water, the MB-nrg PEFs predict extended X-ray absorption fine structure (EXAFS) spectra that accurately reproduce the experimental spectra, which thus allows for characterizing the hydration structure of the two ions with high level of confidence.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Experimental study of linear and nonlinear regimes of density-driven instabilities induced by CO{sub 2} dissolution in water

Density driven instabilities produced by CO{sub 2} (gas) dissolution in water containing a color indicator were studied in a Hele Shaw cell. The images were analyzed and instability patterns were characterized by mixing zone temporal evolution, dispersion curves, and the growth rate for different CO{sub 2} pressures and different color indicator concentrations. The results obtained from an exhaustive analysis of experimental data show that this system has a different behaviour in the linear regime of the instabilities (when the growth rate has a linear dependence with time), from the nonlinear regime at longer times. At short times using a color indicator to see the evolution of the pattern, the images show that the effects of both the color indicator and CO{sub 2} pressure are of the same order of magnitude: The growth rates are similar and the wave numbers are in the same range (0–30 cm{sup −1}) when the system is unstable. Although in the linear regime the dynamics is affected similarly by the presence of the indicator and CO{sub 2} pressure, in the nonlinear regime, the influence of the latter is clearly more pronounced than the effects of the color indicator.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Integral Experiment Request 523 CED-2 Report

This report documents the final design phase of the Critical Experiment Design (CED-2) conducted as part of integral experiment request (IER) 523. The purpose of IER 523 is to determine critical configurations of 35 weight percent (wt%) enriched uranium dioxide beryllium oxide (UO 2 -BeO) material driven by an annular ring of Seven Percent Critical Experiment (7uPCX) fuel rods at Sandia National Laboratories (Sandia). The experiments will provide benchmark data on water moderated, intermediately enriched UO2 systems as well as Be nuclear data. The experiment will also provide partial validation for the beryllium oxide (BeO) thermal neutron scattering law (TSL) in the thermal energy range. Experiment design concepts, neutronic analysis results, and proposed paths for continuing the CED process are presented. This report builds on the feasibility and justification of experimental need report (CED-0) and preliminary experiment design report (CED-1) completed in December 2021 and September 2023, respectively [1, 2].

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Voyager 2 plasma ion observations in the magnetosphere of Uranus

Positive ion measurements in the magnetosphere of Uranus have been made by the Voyager 2 plasma science experiment. The paper presents an overview of the entire data set and a detailed analysis of the observations from the inner magnetosphere which complements and extends results reported elsewhere. Densities and temperatures are obtained from an analysis which incorporates details of the instrumental response. These results are then used to calculate flux tube particle and energy content to support the hypothesis that the plasma transport is controlled by a solar wind-driven magnetospheric convection system. Variations in the flux tube content suggest both a local source of plasma, produced from the neutral hydrogen corona of Uranus, and a nonlocal source, convected inwared and heated by adiabatic compression. In each case a proton composition is inferred. Sharp boundaries in the high-energy (approximately 1 keV) plasma population are interpreted in terms of the spatial extent of the magnetospheric convection, with significant shielding of the convection electric field. The convection theory is also used in a simulation of the low-energy (approximately 10 eV) ion component using the neutral hydrogen source, resulting in distribution functions which qualitatively agree with the observations.

Selesnick, Richard S.↗

Using XML and Java Technologies for Astronomical Instrument Control

Traditionally, instrument command and control systems have been highly specialized, consisting mostly of custom code that is difficult to develop, maintain, and extend. Such solutions are initially very costly and are inflexible to subsequent engineering change requests, increasing software maintenance costs. Instrument description is too tightly coupled with details of implementation. NASA Goddard Space Flight Center, under the Instrument Remote Control (IRC) project, is developing a general and highly extensible framework that applies to any kind of instrument that can be controlled by a computer. The software architecture combines the platform independent processing capabilities of Java with the power of the Extensible Markup Language (XML), a human readable and machine understandable way to describe structured data. A key aspect of the object-oriented architecture is that the software is driven by an instrument description, written using the Instrument Markup Language (IML), a dialect of XML. IML is used to describe the command sets and command formats of the instrument, communication mechanisms, format of the data coming from the instrument, and characteristics of the graphical user interface to control and monitor the instrument. The IRC framework allows the users to define a data analysis pipeline which converts data coming out of the instrument. The data can be used in visualizations in order for the user to assess the data in real-time, if necessary. The data analysis pipeline algorithms can be supplied by the user in a variety of forms or programming languages. Although the current integration effort is targeted for the High-resolution Airborne Wideband Camera (HAWC) and the Submillimeter and Far Infrared Experiment (SAFIRE), first-light instruments of the Stratospheric Observatory for Infrared Astronomy (SOFIA), the framework is designed to be generic and extensible so that it can be applied to any instrument. Plans are underway to test the framework with other types of instruments, such as remote sensing earth science instruments.

Ames, Troy↗

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Reproducible, data-driven thermal protection system (TPS) research requires that experimental records from high-enthalpy testing be consistently structured, traceable, and accessible across campaigns and institutions. In practice, however, arcjet and plasma facilities data remain largely fragmented: raw diagnostics are stored in ad hoc formats, material sample histories are disconnected from test conditions, and metadata standards are absent, precluding systematic cross-campaign analysis and long-term reuse. BEAST (Backend for Experiment Analysis, Storage, and Traceability) is an open-source, web-based platform that addresses these limitations by providing a unified, queryable infrastructure for high-enthalpy ground-test data [1]. First presented at the 15th Ablation Workshop [2], BEAST has since undergone significant development. The platform ingests and structures multi-channel time-series diagnostics, facility configurations, and material property records within a common provenance model, ensuring end-to-end traceability from raw sensor acquisition to reduced experimental quantities. A versioned material library links specimen identity and processing history to the specific runs in which each sample was tested. An integrated modeling workbench enables training and evaluation of regression models directly on archived experimental data, supporting condition interpolation and the construction of empirical material response databases. Beyond its original deployment at NASA Ames Research Center, BEAST has been designed to be facility-agnostic, with ongoing efforts to extend its adoption to other facilities. Its modular architecture accommodates heterogeneous diagnostic setups and facility types, and its future open-source distribution allows institutions to build on a common data standard rather than maintaining isolated, bespoke solutions. BEAST is further integrated within a broader ecosystem of companion tools: arcjetCV [3] extracts recession rates and shock standoff distances from high-speed video using computer vision, and miniSTARscan [4] provides sub-minute, portable photogrammetric surface reconstruction of test articles before and after exposure. All tools share a common data schema, enabling seamless ingestion of surface geometry, imagery, and time-series data into a single, coherent experimental record.

Database↗

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Reproducible, data-driven thermal protection system (TPS) research requires that experimental records from high-enthalpy testing be consistently structured, traceable, and accessible across campaigns and institutions. In practice, however, arcjet and plasma facilities data remain largely fragmented: raw diagnostics are stored in ad hoc formats, material sample histories are disconnected from test conditions, and metadata standards are absent, precluding systematic cross-campaign analysis and long-term reuse. BEAST (Backend for Experiment Analysis, Storage, and Traceability) is an open-source, web-based platform that addresses these limitations by providing a unified, queryable infrastructure for high-enthalpy ground-test data [1]. First presented at the 15th Ablation Workshop [2], BEAST has since undergone significant development. The platform ingests and structures multi-channel time-series diagnostics, facility configurations, and material property records within a common provenance model, ensuring end-to-end traceability from raw sensor acquisition to reduced experimental quantities. A versioned material library links specimen identity and processing history to the specific runs in which each sample was tested. An integrated modeling workbench enables training and evaluation of regression models directly on archived experimental data, supporting condition interpolation and the construction of empirical material response databases. Beyond its original deployment at NASA Ames Research Center, BEAST has been designed to be facility-agnostic, with ongoing efforts to extend its adoption to other facilities. Its modular architecture accommodates heterogeneous diagnostic setups and facility types, and its future open-source distribution allows institutions to build on a common data standard rather than maintaining isolated, bespoke solutions. BEAST is further integrated within a broader ecosystem of companion tools: arcjetCV [3] extracts recession rates and shock standoff distances from high-speed video using computer vision, and miniSTARscan [4] provides sub-minute, portable photogrammetric surface reconstruction of test articles before and after exposure. All tools share a common data schema, enabling seamless ingestion of surface geometry, imagery, and time-series data into a single, coherent experimental record.

Database↗