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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 325 records · Page 18

Addressing Issues with Working Memory in Video Object Segmentation

Contemporary state-of-the-art video object segmentation (VOS) models compare incoming unannotated images to a history of image-mask relations via affinity or cross-attention to predict object masks. We refer to the internal memory state of the initial image-mask pair and past image-masks as a working memory buffer. While the current state of the art models perform very well on clean video data, their reliance on a working memory of previous frames leaves room for error. Affinity-based algorithms include the inductive bias that there is temporal continuity between consecutive frames. To account for inconsistent camera views of the desired object, working memory models need an algorithmic modification that regulates the memory updates and avoid writing irrelevant frames into working memory. A simple algorithmic change is proposed that can be applied to any existing working memory-based VOS model to improve performance on inconsistent views, such as sudden camera cuts, frame interjections, and extreme context changes. The resulting model performances show significant improvement on video data with these frame interjections over the same model without the algorithmic addition. Our contribution is a simple decision function that determines whether working memory should be updated based on the detection of sudden, extreme changes and the assumption that the object is no longer in frame. By implementing algorithmic changes, such as this, we can increase the real-world applicability of current VOS models.

97 MATHEMATICS AND COMPUTING↗

A Compositional Relevance Model for Adaptive Information Retrieval

There is a growing need for rapid and effective access to information in large electronic documentation systems. Access can be facilitated if information relevant in the current problem solving context can be automatically supplied to the user. This includes information relevant to particular user profiles, tasks being performed, and problems being solved. However most of this knowledge on contextual relevance is not found within the contents of documents, and current hypermedia tools do not provide any easy mechanism to let users add this knowledge to their documents. We propose a compositional relevance network to automatically acquire the context in which previous information was found relevant. The model records information on the relevance of references based on user feedback for specific queries and contexts. It also generalizes such information to derive relevant references for similar queries and contexts. This model lets users filter information by context of relevance, build personalized views of documents over time, and share their views with other users. It also applies to any type of multimedia information. Compared to other approaches, it is less costly and doesn't require any a priori statistical computation, nor an extended training period. It is currently being implemented into the Computer Integrated Documentation system which enables integration of various technical documents in a hypertext framework.

Mathe, Nathalie↗

A study of MAPSE extensions

The technical issues of extending the Minimal Ada Programming Support Environment (MAPSE) to support the life cycle of large, complex distributed systems such as the Space Station Program (SSP) are studied. The work has been divided into two phases, Phase one, covered herein, identifies a list of advanced technical tools needed to extend the MAPSE to meet the needs believed to be inherent in the Software Support Environment (SSE). The description of SSE requirements are given, and a list of the tools are identified. An outline is also given of the principle requirements for a MAPSE, along with a description of the life cycle model and a description of the tools in the context of the life cycle model.

Auty, David↗

Model Based Analysis and Test Generation for Flight Software

We describe a framework for model-based analysis and test case generation in the context of a heterogeneous model-based development paradigm that uses and combines Math- Works and UML 2.0 models and the associated code generation tools. This paradigm poses novel challenges to analysis and test case generation that, to the best of our knowledge, have not been addressed before. The framework is based on a common intermediate representation for different modeling formalisms and leverages and extends model checking and symbolic execution tools for model analysis and test case generation, respectively. We discuss the application of our framework to software models for a NASA flight mission.

Pasareanu, Corina S.↗

Current State of Modeling the Photochemistry of Titan's Mutually Dependent Atmosphere and Ionosphere

In the context of recent observations, microphysical models, and laboratory data, a photochemical model of Titan's atmosphere, including updated chemistry focusing on rate coefficients and cross sections measured under appropriate conditions, has been developed to increase understanding of these processes and improve upon previous Titan photochemical models. The model employs a two-stream discrete ordinates method to characterize the transfer of solar radiation, and the effects of electron-impact, cosmic-ray deposition, and aerosol opacities from fractal and Mie particles are analyzed. Sensitivity studies demonstrate that an eddy diffusion profile with a homopause level of 850 km and a methane stratospheric mole fraction of 2.2% provides the best fit of stratospheric and upper atmosphere observations and an improved fit over previous Titan photochemical models. Lack of fits for C3H8, HC3N, and possibly C2H3CN can be resolved with adjustments in aerosol opacity. The model presents a benzene profile consistent with its detection in Titan's stratosphere [Coustenis et al., 2003], which may play an important role in the formation of Titan hazes. An electron peak concentration of 4200 cm(exp -3) is calculated, which exceeds observations by 20%, considerably lower than previous ionosphere models. With adjustments in aerosol opacities and surface fluxes the model illustrates that reasonable fits to existing observations are possible with a single eddy diffusion profile, contrary to the conclusions of previous Titan models. These results will aid in the receipt and interpretation of data from Cassini-Huygens, which will arrive at Titan in 2004 and deploy a probe into Titan's atmosphere in January 2005.

ion chemistry↗

Characterizing Young Giant Planets with the Gemini Planet Imager: An Iterative Approach to Planet Characterization

After discovery, the first task of exoplanet science is characterization. However experience has shown that the limited spectral range and resolution of most directly imaged exoplanet data requires an iterative approach to spectral modeling. Simple, brown dwarf-like models, must first be tested to ascertain if they are both adequate to reproduce the available data and consistent with additional constraints, including the age of the system and available limits on the planet's mass and luminosity, if any. When agreement is lacking, progressively more complex solutions must be considered, including non-solar composition, partial cloudiness, and disequilibrium chemistry. Such additional complexity must be balanced against an understanding of the limitations of the atmospheric models themselves. For example while great strides have been made in improving the opacities of important molecules, particularly NH3 and CH4, at high temperatures, much more work is needed to understand the opacity of atomic Na and K. The highly pressure broadened fundamental band of Na and K in the optical stretches into the near-infrared, strongly influencing the spectral shape of Y and J spectral bands. Discerning gravity and atmospheric composition is difficult, if not impossible, without both good atomic opacities as well as an excellent understanding of the relevant atmospheric chemistry. I will present examples of the iterative process of directly imaged exoplanet characterization as applied to both known and potentially newly discovered exoplanets with a focus on constraints provided by GPI spectra. If a new GPI planet is lacking, as a case study I will discuss HR 8799 c and d will explain why some solutions, such as spatially inhomogeneous cloudiness, introduce their own additional layers of complexity. If spectra of new planets from GPI are available I will explain the modeling process in the context of understanding these new worlds.

exoplanets↗

Surrogate Modeling of Landau Damping with Deep Operator Networks

Kinetic simulations excel at capturing microscale plasma physics phenomena with high accuracy, but their computational demands make them impractical for modeling large-scale space and astrophysical systems. In this context, we build a surrogate model, using Deep Operator Networks (DeepONets), based upon the Vlasov–Poisson simulation data to model the dynamical evolution of plasmas, focusing on the Landau damping process—a fundamental kinetic phenomenon in space and astrophysical plasmas. The trained DeepONets are able to capture the evolution of electric field energy in both linear and nonlinear regimes under various conditions. Extensive validation highlights DeepONets’ robust performance in reproducing complex plasma behaviors with high accuracy, paving the way for large-scale modeling of space and astrophysical plasmas.

plasma astrophysics↗

Robust control of hypersonic vehicles considering propulsive and aeroelastic effects

The influence of propulsion system variations and elastic fuselage behavior on the flight control system of an airbreathing hypersonic vehicle is investigated. Thrust vector magnitude and direction changes due to angle of attack variations affect the pitching moment. Low structural vibration frequencies may occur close to the rigid body modes influencing the angle of attack and lead to possible cross coupling. These effects are modeled as uncertainties in the context of a robust control study of a hypersonic vehicle model accelerating through Mach 8 using H-infinity and mu synthesis techniques. Various levels of uncertainty are introduced into the system. Both individual and simultaneous appearance of uncertainty are considered. The results indicate that the chosen design technique is suitable for this kind of problem provided that a fairly good knowledge of the effects mentioned above is available. The order of the designed controller is reduced but robust performance is lost which shows the need for fixed order design techniques.

Buschek, Harald↗

AI Benchmark Democratization and Carpentry

Benchmarks are a cornerstone of modern machine learning, enabling reproducibility, comparison, and scientific progress. However, AI benchmarks are increasingly complex, requiring dynamic, AI-focused workflows. Rapid evolution in model architectures, scale, datasets, and deployment contexts makes evaluation a moving target. Large language models often memorize static benchmarks, causing a gap between benchmark results and real-world performance. Beyond traditional static benchmarks, continuous adaptive benchmarking frameworks are needed to align scientific assessment with deployment risks. This calls for skills and education in AI Benchmark Carpentry. From our experience with MLCommons, educational initiatives, and programs like the DOE's Trillion Parameter Consortium, key barriers include high resource demands, limited access to specialized hardware, lack of benchmark design expertise, and uncertainty in relating results to application domains. Current benchmarks often emphasize peak performance on top-tier hardware, offering limited guidance for diverse, real-world scenarios. Benchmarking must become dynamic, incorporating evolving models, updated data, and heterogeneous platforms while maintaining transparency, reproducibility, and interpretability. Democratization requires both technical innovation and systematic education across levels, building sustained expertise in benchmark design and use. Benchmarks should support application-relevant comparisons, enabling informed, context-sensitive decisions. Dynamic, inclusive benchmarking will ensure evaluation keeps pace with AI evolution and supports responsible, reproducible, and accessible AI deployment. Community efforts can provide a foundation for AI Benchmark Carpentry.

von Laszewski, Gregor [Virginia U.]↗

A Damage Model for the Simulation of Delamination in Advanced Composites under Variable-Mode Loading

A thermodynamically consistent damage model is proposed for the simulation of progressive delamination in composite materials under variable-mode ratio. The model is formulated in the context of Damage Mechanics. A novel constitutive equation is developed to model the initiation and propagation of delamination. A delamination initiation criterion is proposed to assure that the formulation can account for changes in the loading mode in a thermodynamically consistent way. The formulation accounts for crack closure effects to avoid interfacial penetration of two adjacent layers after complete decohesion. The model is implemented in a finite element formulation, and the numerical predictions are compared with experimental results obtained in both composite test specimens and structural components.

Turon, A.↗

Risk-Informed Safety Assurance and Probabilistic Assessment of Mission-Critical Software-Intensive Systems

This report validates and documents the detailed features and practical application of the framework for software intensive digital systems risk assessment and risk-informed safety assurance presented in the NASA PRA Procedures Guide for Managers and Practitioner. This framework, called herein the "Context-based Software Risk Model" (CSRM), enables the assessment of the contribution of software and software-intensive digital systems to overall system risk, in a manner which is entirely compatible and integrated with the format of a "standard" Probabilistic Risk Assessment (PRA), as currently documented and applied for NASA missions and applications. The CSRM also provides a risk-informed path and criteria for conducting organized and systematic digital system and software testing so that, within this risk-informed paradigm, the achievement of a quantitatively defined level of safety and mission success assurance may be targeted and demonstrated. The framework is based on the concept of context-dependent software risk scenarios and on the modeling of such scenarios via the use of traditional PRA techniques - i.e., event trees and fault trees - in combination with more advanced modeling devices such as the Dynamic Flowgraph Methodology (DFM) or other dynamic logic-modeling representations. The scenarios can be synthesized and quantified in a conditional logic and probabilistic formulation. The application of the CSRM method documented in this report refers to the MiniAERCam system designed and developed by the NASA Johnson Space Center.

Guarro, Sergio B.↗

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.↗

Physics and evolution of constant opening angle jets using a quasi-one-dimensional magnetohydrodynamic model

We discuss the significance of the assumptions of infinite conductivity and time independence in the context of an ideal MHD model for constant opening angle jets. The model is developed by projecting the MHD equations onto the jet axis. We find that for initially sub-Alfvenic flows (i.e., flows emanating from active galactic nuclei and neutron stars) wind-type solutions exist only when the field lines at the origin are wound up in a direction opposite to the direction of rotation of the compact source. We discuss the possibility that the time evolution of these outflows may be a cycle between breeze- and wind-type solutions as a result of continuous changes in the boundary conditions at the origin due to accretion. We propose that such cycles may explain the apparent one-sideness of some jets, especially the ones for which we cannot use arguments of relativistic beaming. We examine the dependence of the wind-type solutions on the following parameters describing the outflow at the origin: the degree of winding of the field lines, the value of the gas pressure, the polytropic index, the strength of the magnetic field, the value of the rotational velocity, the gravitational potential of the compact object, and the injection velocity. We compare results with results obtained previously, and discuss briefly the qualitative features and physical interpretation of the solutions for outflows emanating from neutron stars and protostars.

Koupelis, Theodoros↗

RingX: Scalable Parallel Attention for Long-Context Learning on HPC

The attention mechanism has become foundational for remarkable AI breakthroughs since the introduction of the Transformer, driving the demand for increasingly longer context to power frontier models such as large-scale reasoning language models and high-resolution image/video generators. However, its quadratic computational and memory complexities present substantial challenges. Current state-of-the-art parallel attention methods, such as ring attention, are widely adopted for long-context training but utilize a point-to-point communication strategy that fails to fully exploit the capabilities of modern HPC network architectures. In this work, we propose ringX, a scalable family of parallel attention methods optimized explicitly for HPC systems. By enhancing workload partitioning, refining communication patterns, and improving load balancing, ringX achieves up to 3.4 × speedup compared to conventional ring attention on the Frontier supercomputer. Optimized for both bi-directional and causal attention mechanisms, ringX demonstrates its effectiveness through training benchmarks of a Vision Transformer (ViT) on a climate dataset and a Generative Pre-Trained Transformer (GPT) model, Llama3 8B. Our method attains an end-to-end training speedup of approximately 1.5 × in both scenarios. To our knowledge, the achieved 38% model FLOPs utilization (MFU) for training Llama3 8B with a 1M-token sequence length on 4,096 GPUs represents one of the highest training efficiencies reported for long-context learning on HPC systems. Our code implementation is available at https://github.com/jqyin/ringX-attention.

Yin, Junqi [ORNL] (ORCID:0000000338435520)↗

Advanced data assimilation in strongly nonlinear dynamical systems

Advanced data assimilation methods are applied to simple but highly nonlinear problems. The dynamical systems studied here are the stochastically forced double well and the Lorenz model. In both systems, linear approximation of the dynamics about the critical points near which regime transitions occur is not always sufficient to track their occurrence or nonoccurrence. Straightforward application of the extended Kalman filter yields mixed results. The ability of the extended Kalman filter to track transitions of the double-well system from one stable critical point to the other depends on the frequency and accuracy of the observations relative to the mean-square amplitude of the stochastic forcing. The ability of the filter to track the chaotic trajectories of the Lorenz model is limited to short times, as is the ability of strong-constraint variational methods. Examples are given to illustrate the difficulties involved, and qualitative explanations for these difficulties are provided. Three generalizations of the extended Kalman filter are described. The first is based on inspection of the innovation sequence, that is, the successive differences between observations and forecasts; it works very well for the double-well problem. The second, an extension to fourth-order moments, yields excellent results for the Lorenz model but will be unwieldy when applied to models with high-dimensional state spaces. A third, more practical method--based on an empirical statistical model derived from a Monte Carlo simulation--is formulated, and shown to work very well. Weak-constraint methods can be made to perform satisfactorily in the context of these simple models, but such methods do not seem to generalize easily to practical models of the atmosphere and ocean. In particular, it is shown that the equations derived in the weak variational formulation are difficult to solve conveniently for large systems.

Miller, Robert N.↗

LLM-Based Adaptive Distribution Voltage Regulation Under Frequent Topology Changes: An In-Context MPC Framework

This paper proposes a large language model (LLM) based adaptive inverter control for distribution voltage regulation under frequent topology changes. We leverage the ability of the LLM to perform in-context learning and create a topology-adaptive surrogate model for power flow calculation. The surrogate model is then integrated with a long short-term memory-based load forecaster and a model predictive control (MPC) scheme to achieve the optimal inverter control that adapts to frequent topology changes. Unlike many existing works that assume fixed-topology grids or require the knowledge of all possible topologies when training a model, the proposed in-context MPC method tackles the distribution voltage control problem under various topologies and adapts to unknown topologies with limited data requirement for fine-tuning. The effectiveness of our method is demonstrated on a modified IEEE 123-bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Mass loss in Alpha Cygni - Synthetic H-Alpha profiles

Alpha Cygni (A2 Ia) is the brightest and best-studied A type supergiant. The star's position in the H-R diagram makes the determination of its mass loss rate extremely important. The present investigation is concerned with a semiempirical modeling of the H-alpha profile in Alpha Cyg in connection with the objective of estimating the mass loss rate and further constraining the physical state of the stellar wind. The synthetic H-alpha profiles considered are compared with the observed profiles in Alpha Cyg. It is concluded that a spherically symmetric, steady-state model, with the network of hydrogen transitions treated in detail, can fit the deeper observed profiles but not the shallower ones. The obtained results indicate that, within the context of the turbulent models, the mass loss rate of Alpha Cyg is (1.7 + or - 0.4) x 10 to the -7th solar mass per year.

Kunasz, P. B.↗

The X-ray halo of an extremely luminous LSB disk galaxy

We are continuing to refine our upper limit on emission from halo gas in Malin 2. The upper limit is, of course, below the detected flux, but is made more difficult to quantify by the disk and possible AGN sources. We are also exploring spectral and spatial-size constraints to help separate the sources of emission. On the theory side, more recent work on the X-ray halo luminosity from halo gas leftover from galaxy formation has lowered the prediction for disk galaxies (e.g. Toft et al. 2002, MNRAS, 335, 799). While our upper limit is well below the original prediction, refinements in model have moved the theoretical goalposts, so that the observation may be consistent with newer models. A recent theoretical development, which our observations of Malin 2 appear to support, is that a substantial amount of mass can be accreted onto galaxies without being heated at a virial shock. The previous standard theory was that gas accreting into a halo hits a virial shock and is heated to high temperatures, which could produce X-ray halos in massive galaxies. Recent models show that "smooth accretion" of matter bypasses the virial shocking (Murali e t al. 2002, ApJ, 571, 1; Birnboim & Dekel 2003, MNRAS, 345, 349). Additionally, new hydrodynamical simulations of galaxy mergers by UCSC graduate student T. J. Cox show that hot gas halos can be created by gas blown out from the merger, taking up orbital energy of the merging galaxies (Cox et al. 2004, ApJ, 607, L87). If mergers rather than virial shocking are the origin of hot gas halos, the existence of an X-ray halo should depend more on past merger activity than halo mass. Then it makes sense that elliptical galaxies and poor groups with ellipticals, which are probably formed in mergers, have X-ray gas halos; while a giant, quiescent LSB disk galaxy like Malin 2, which has never suffered a major merger, does not have an X-ray halo. While both the observational expectations and theoretical models have changed since we began this project, which has forced us to re-evaluate the goals, we are pressing forward to firm up the observations and put them in context of the current models for X-ray halos of massive galaxies.

Weiner, Benjamin J.↗