Search NASA⌕ Search

SEARCH · Search NASA

Results for “Requirements Modeling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Secondary Fragmentation of Comet Shoemaker-Levy 9 and the Ramifications for the Progenitor's Breakup in July 1992

Comprehensive analysis of discrete events of secondary fragmentation leads to a conceptually new understanding of the process of disintegration of comet Shoemaker-Levy 9. We submit that the jovian tidal forces inflicted extensive cracks throughout the interior of the original nucleus but did not split it apart. The initial disruption was apparently accomplished by stresses exerted on the cracked object by its fast rotation during the early post-perijove period of time. We argue that this disruption was in fact a rapid sequence of episodes during July 1992 that gave birth to the 12 on-train, or primary, fragments: A, C, D, E, G, H, K, L, Q (later Q(sub 1)), R, S, and W. The discrete events of secondary fragmentation, which gave birth to the off-train fragments, are understood in this scenario as stochastic manifestations of the continuing process of progressive disintegration. Of the 13 off-train fragments considered, nine were secondary--B, F, G(sub 2), M, N, P (later P(sub 2) or P(sub 2a)), Q(sub 2), U, and V--and four tertiary (J, P(sub 1), P(sub 2b), and T). The separation parameters of 11 off-train fragments were determined. The vectorial distribution of separation velocities of these fragments shows a strong concentration toward a great circle, unquestionably an effect of the approximately conserved angular momentum of the progenitor comet since the time of its initial disruption. Also apparent is their clumping (except for P(sub 1)) to a segment along the great circle, implying that the fragments were consistently released from one side of their parents, thus explaining for the first time why the off-train fragments preferentially appeared on one side of the nuclear train. In order to obtain a consistent solution, our model requires that the points of separation be on the antisolar side of the parent fragments, where thermal stresses are likely to enhance the effect of rotation. The episodes of secondary fragmentation are found to have nine months after the close encounter with Jupiter in early July 1992, and the separation velocities ranged between 0.36 and 1.7 m/s. The spin-axis position is determined to have been nearly in the jovicentric orbit plane, which rules out the Asphaug-Benz-Solem strengthless aggregate model as a plausible breakup hypothesis. Since the separation velocities are rotational in nature, they cannot substantially exceed the critical limit for centrifugal breakup and offer an estimate for the original nuclear dimensions. The comet's nucleus is found to have been approximately 10 km in diameter and spinning rapidly. With the exception of P(sub 1) and apparently also P(sub 2) and F, no nongravitational deceleration was detected in the motions of the off-train fragments. Serious doubts are cast on continuing appreciable activity of any of these fragments. Indeed, when it was necessary to introduce a deceleration into the equations of motion, the effect appears to have been due to the action of solar radiation pressure on the centroid of centimeter-sized particulates in the disintegrating condensations.

Sekanina, Z.↗
DOE OSTI2024

Pretraining Billion-Scale Geospatial Foundational Models on Frontier

As AI workloads increase in scope, generalization capability becomes challenging for small task-specific models and their demand for large amounts of labeled training samples increases. On the contrary, Foundation Models (FMs) are trained with internet-scale unlabeled data via self-supervised learning and have been shown to adapt to various tasks with minimal fine-tuning. Although large FMs have demonstrated significant impact in natural language processing and computer vision, efforts toward FMs for geospatial applications have been restricted to smaller size models, as pretraining larger models requires very large computing resources equipped with state-of-the-art hardware accelerators. Current satellite constellations collect 100+TBs of data a day, resulting in images that are billions of pixels and multimodal in nature. Such geospatial data poses unique challenges opening up new opportunities to develop FMs. We investigate billion scale FMs and HPC training profiles for geospatial applications by pretraining on publicly available data. We studied from end-to-end the performance and impact in the solution by scaling the model size. Our larger 3B parameter size model achieves up to 30% improvement in top1 scene classification accuracy when comparing a 100M parameter model. Moreover, we detail performance experiments on the Frontier supercomputer, America's first exascale system, where we study different model and data parallel approaches using PyTorch's Fully Sharded Data Parallel library. Specifically, we study variants of the Vision Transformer architecture (ViT), conducting performance analysis for ViT models with size up to 15B parameters. By discussing throughput and performance bottlenecks under different parallelism configurations, we offer insights on how to leverage such leadership-class HPC resources when developing large models for geospatial imagery applications.

Tsaris, Aristeidis (aris)↗
NASA NTRSDate not supplied

Evaluating the Efficacy of Conditional Variational Autoencoders in Generating Synthetic Single Nuclei RNA-Seq Data for Space Biology Research

Astronauts are subject to unique stressors during spaceflight, leading to changes in their cellular function. However, neither astronauts nor model organisms respond the same to spaceflight, and research implicates a contribution of omics components in differential responses. Understanding how gene expression affects astronaut health is critical for the success of long-term space missions, prompting interest in developing personalized predictive models leveraging artificial intelligence (AI) and machine learning (ML) techniques. Developing such models requires extensive data, which is challenging to obtain and share. This study explores the use of conditional variational autoencoders (CVAEs) to synthetically generate single-nuclei RNA-seq (snRNA-seq) data. CVAEs build on standard variational autoencoders (VAEs) by conditioning data generation on covariates like sample identity and mission parameters, enhancing the relevance of generated data for specific contexts. For our work, we built two CVAEs with varying degrees of sparsity to optimize both interpretability and generative power. We train and validate models on existing snRNA-seq data collected from the brain tissue of mice subjected to spaceflight conditions and their ground control counterparts. We evaluate model performance using statistical tests and visualizations to compare synthetic data to real data. We aim to demonstrate that these prototype CVAE architectures could be used in future space biology work and that this is a method worth further exploring.

Sarah Golts↗
NASA NTRS1989

Primitive bodies - Molecular abundances in Comet Halley as probes of cometary formation environments

The most recent results on abundances of molecules in Halley's comet are examined in the context of various models for the environment in which comets formed. These environments include molecular clouds associated with star-forming regions, the solar nebula, gaseous disks around proto-planets, and combinations of these. Of all constituents in a cometary nucleus, the highly volatile molecules such as methane, ammonia, molecular nitrogen, and carbon monoxide are most sensitive to the final episode of cometary grain formation and incorporation in the comet's nucleus; hence they likely reflect at least some chemical processing in the solar nebula. Proper interpretation requires modeling of a number of physical processes including gas phase chemistry, chemistry on grain surfaces, and fractionation effects resulting from preferential incorporation of certain gases in proto-cometary grains. The abundance of methane in Halley's comet could be a key indicator of where that comet formed, provided the methane abundance on grains in star-forming regions can be observationally constrained.

Lunine, Jonathan I.↗
NASA NTRS1993

Model reduction in integrated controls-structures design

It is the objective of this paper to present a model reduction technique developed for the integrated controls-structures design of flexible structures. Integrated controls-structures design problems are typically posed as nonlinear mathematical programming problems, where the design variables consist of both structural and control parameters. In the solution process, both structural and control design variables are constantly changing; therefore, the dynamic characteristics of the structure are also changing. This presents a problem in obtaining a reduced-order model for active control design and analysis which will be valid for all design points within the design space. In other words, the frequency and number of the significant modes of the structure (modes that should be included) may vary considerably throughout the design process. This is also true as the locations and/or masses of the sensors and actuators change. Moreover, since the number of design evaluations in the integrated design process could easily run into thousands, any feasible order-reduction method should not require model reduction analysis at every design iteration. In this paper a novel and efficient technique for model reduction in the integrated controls-structures design process, which addresses these issues, is presented.

Maghami, Peiman G.↗
NASA NTRS1985

Chemistry in dynamically evolving clouds

A unified model of chemical and dynamical evolution of isolated, initially diffuse and quiescent interstellar clouds is presented. The model uses a semiempirically derived dependence of the observed cloud temperatures on the visual extinction and density. Even low-mass, low-density, diffuse clouds can collapse in this model, because the inward pressure gradient force assists gravitational contraction. In contrast, previous isothermal collapse models required the low-mass diffuse clouds to be unrealistically cold before gravitational contraction could start. Theoretically predicted dependences of the column densities of various atoms and molecules, such as C and CO, on visual extinction in diffuse clouds are in accord with observations. Similarly, the predicted dependences of the fractional abundances of various chemical species (e.g., CO, H2CO, HCN, HCO(+)) on the total hydrogen density in the core of the dense clouds also agree with observations reported to date in the literature. Compared with previous models of interstellar chemistry, the present model has the potential to explain the wide spectrum of chemical and physical properties of both diffuse and dense clouds with a common formalism employing only a few simple initial conditions.

Tarafdar, S. P.↗
NASA NTRS2017

Characterizing DebriSat Fragments: So Many Fragments, So Much Data, and So Little Time

To improve prediction accuracy, the DebriSat project was conceived by NASA and DoD to update existing standard break-up models. Updating standard break-up models require detailed fragment characteristics such as physical size, material properties, bulk density, and ballistic coefficient. For the DebriSat project, a representative modern LEO spacecraft was developed and subjected to a laboratory hypervelocity impact test and all generated fragments with at least one dimension greater than 2 mm are collected, characterized and archived. Since the beginning of the characterization phase of the DebriSat project, over 130,000 fragments have been collected and approximately 250,000 fragments are expected to be collected in total, a three-fold increase over the 85,000 fragments predicted by the current break-up model. The challenge throughout the project has been to ensure the integrity and accuracy of the characteristics of each fragment. To this end, the post hypervelocity-impact test activities, which include fragment collection, extraction, and characterization, have been designed to minimize handling of the fragments. The procedures for fragment collection, extraction, and characterization were painstakingly designed and implemented to maintain the post-impact state of the fragments, thus ensuring the integrity and accuracy of the characterization data. Each process is designed to expedite the accumulation of data, however, the need for speed is restrained by the need to protect the fragments. Methods to expedite the process such as parallel processing have been explored and implemented while continuing to maintain the highest integrity and value of the data. To minimize fragment handling, automated systems have been developed and implemented. Errors due to human inputs are also minimized by the use of these automated systems. This paper discusses the processes and challenges involved in the collection, extraction, and characterization of the fragments as well as the time required to complete the processes. The objective is to provide the orbital debris community an understanding of the scale of the effort required to generate and archive high quality data and metadata for each debris fragment 2 mm or larger generated by the DebriSat project.

Shiotani, B.↗
DOE OSTI2024

High Pressure Melting Curve of Fe‐Si: Implication for the Thermal Properties in Mercury's Core

The motion of liquid iron (Fe) alloy materials in the outer core drives the dynamo, which generates Mercury's magnetic field. The assessment of core models requires laboratory measurements of the melting temperature of Fe alloys at high pressure. Here, we experimentally determined the melting curve of Fe9wt%Si and Fe17wt%Si up to 17 GPa using in situ and ex situ measurements of intermetallic fast diffusion that serves as the melting criterion in a large-volume press. Our determined melting slopes are comparable with previous studies up to about 17 GPa. However, when extrapolated, our melting slopes significantly deviate from previous studies at higher pressures. For Mercury's core with a model composition of Fe9wt%Si, the melting temperature-depth profile determined in our study is lower by ∼150–250 K when compared with theoretical calculations. Using the new melting curve of Fe9wt%Si and the electrical resistivity values from a previous study of Fe8.5wt%Si, we estimate that the electronic thermal conductivity of liquid Fe9wt%Si is 30 Wm −1 K −1 at the Mercury's CMB pressure of 5 GPa and 37 Wm −1 K −1 at an assumed ICB of 21 GPa, corresponding to heat flux values of 23 mWm −2 and 32 mWm −2 , respectively. These values provide new constraints on the core models.

58 GEOSCIENCES↗
NASA NTRS2013

Testing the Empirical Shock Arrival Model Using Quadrature Observations

The empirical shock arrival (ESA) model was developed based on quadrature data from Helios (in situ) and P-78 (remote sensing) to predict the Sun-Earth travel time of coronal mass ejections (CMEs). The ESA model requires earthward CME speed as input, which is not directly measurable from coronagraphs along the Sun-Earth line. The Solar Terrestrial Relations Observatory (STEREO) and the Solar and Heliospheric Observatory (SOHO) were in quadrature during 20102012, so the speeds of Earth-directed CMEs were observed with minimal projection effects. We identified a set of 20 full halo CMEs in the field of view of SOHO that were also observed in quadrature by STEREO. We used the earthward speed from STEREO measurements as input to the ESA model and compared the resulting travel times with the observed ones from L1 monitors. We find that the model predicts the CME travel time within about 7.3 h, which is similar to the predictions by the ENLIL model. We also find that CME-CME and CME-coronal hole interaction can lead to large deviations from model predictions.

CMEs↗
DOE OSTI2025

Concurrent two-way coupling of global and local models across internal boundaries with non-matching discretizations

Coupling local and global models enables efficient simulation of multiscale systems, where global models capture large-scale behavior and local models, with enhanced physics, resolve finer details over a smaller region. Here, this paper presents a mathematically consistent method for coupling physics-based models of varying fidelity across adjacent, non-overlapping subdomains, even when discretizations do not match at the immersed interdomain interfaces. Incompressible Navier-Stokes equations (NSE) constitute the global model while residual-based turbulence model serves as the local high-fidelity model. In addition, a scalar advection-diffusion equation that models the convection of an active scalar field is appended to the turbulence model in the local domain. This scalar field does not have its complement in the global model, giving rise to unequal number of equations at the immersed boundary between local and global models. Interdomain coupling terms are derived via the Variational Multiscale Discontinuous Galerkin (VMDG) method with new developments in scale representation and efficient fine-scale estimation. While transient laminar flows modeled with NSE in the global domain can be resolved with relatively coarse mesh, turbulent flow calculations in the local model require much finer spatial discretizations as well as smaller time-step for appropriately resolving the turbulent flow physics. The proposed framework also accommodates non-matching meshes at the immersed boundaries. Test problems in 2D and 3D numerically showcase the concurrent two-way coupling of unknown fields across the immersed boundaries. The 3D test presents a case with an unequal number of equations, where the scalar field represents the convection of contaminant concentration. This provides more detailed physics in the local region and highlights its application in climate modeling and atmospheric sciences.

Variational Multiscale Discontinuous Galerkin (VMD↗
DOE OSTI2024

AI-Enhanced Co-Design for Next-Generation Microelectronics: Innovating Innovation (Workshop Report)

The Artificial Intelligence Enhanced Co-Design for Next Generation Microelectronics virtual workshop was held April 4-5, 2023, and attended by subject matter experts from universities, industry, and national laboratories. This was the third in a series of workshops to motivate the research community to identify and address major challenges facing microelectronics research and production. The 2023 workshop focused on a set of topics from materials to computing algorithms, and included discussions on relevant federal legislation and such as the Creating Helpful Incentives to Produce Semiconductors and Science Act (CHIPS Act) which was signed into law in the summer of 2022. Talks at the workshop included edge computing in radiation environments, new materials for neuromorphic computing, advanced packaging for microelectronics, and new AI techniques. We also received project updates from several of the Department of Energy (DOE) microelectronics co-design projects funded in the fall of 2021, and from three of the Energy Frontier Research Centers (EFRCs) that had been funded in the fall of 2022. The workshop also conducted a set of breakout discussions around the five principal research directions (PRDs) from the 2018 Department of Energy workshop report: 1) define innovative material, device, and architecture requirements driven by applications, algorithms, and software; 2) revolutionize memory and data storage; 3) re-imagine information flow unconstrained by interconnects; 4) redefine computing by leveraging unexploited physical phenomena; 5) reinvent the electricity grid through new materials, devices, and architectures. We tasked each breakout group to consider one primary PRD (and other PRDs as relevant topics arose during discussions) and to address questions such as whether the research community has embraced co-design as a methodology and whether new developments at any level of innovation from materials to programming models requires the research community to reevaluate the PRDs developed back in 2018.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

Estimation of geopotential differences over intercontinental locations using satellite and terrestrial measurements

An error analysis study was conducted in order to assess the current accuracies and the future anticipated improvements in the estimation of geopotential differences over intercontinental locations. An observation/estimation scheme was proposed and studied, whereby gravity disturbance measurements on the Earth's surface, in caps surrounding the estimation points, are combined with corresponding data in caps directly over these points at the altitude of a low orbiting satellite, for the estimation of the geopotential difference between the terrestrial stations. The mathematical modeling required to relate the primary observables to the parameters to be estimated, was studied for the terrestrial data and the data at altitude. Emphasis was placed on the examination of systematic effects and on the corresponding reductions that need to be applied to the measurements to avoid systematic errors. The error estimation for the geopotential differences was performed using both truncation theory and least squares collocation with ring averages, in case observations on the Earth's surface only are used. The error analysis indicated that with the currently available global geopotential model OSU89B and with gravity disturbance data in 2 deg caps surrounding the estimation points, the error of the geopotential difference arising from errors in the reference model and the cap data is about 23 kgal cm, for 30 deg station separation.

Pavlis, Nikolaos K.↗
NASA NTRS2016

Preparation for Cassini Grand Finale - Validation of Saturn Ring Heating in TSS

Thermal analysis of spacecraft at Saturn have previously been restricted to three environmental heat fluxes: solar, Saturn planet IR, and Saturn planet albedo. Heat flux from Saturn’s rings were not available in any commercially available thermal analysis tools. While preparing for the Cassini Grand Finale, during which Cassini will travel extremely close to the rings of Saturn, it was determined the existing thermal model required updating to accurately predict heat fluxes from the rings. This is particularly important for Cassini’s Visual and Infrared Mapping Spectrometer infrared spectrometer (VIMS-IR), as it is cooled by a passive radiator which operates below the temperature of Saturn’s rings. This paper discusses the validation of the heat flux from solar, Saturn, and Saturn’s rings in Spacedesign’s Thermal Synthesizer System (TSS). The incorporation of heating from Saturn’s rings also led to the use of SPICE geometry to ensure accurate spacecraft positioning and pointing. Thermal model results are compared against historical heating events as well as predictive Grand Finale sequences.

Swanson, Kirsten S.↗
NASA NTRS2005

MRI-Based Computational Fluid Dynamics in Experimental Vascular Models: Toward the Development of an Approach for Prediction of Cardiovascular Changes During Prolonged Space Missions

A priority of NASA is to identify and study possible risks to astronauts health during prolonged space missions [l]. The goal is to develop a procedure for a preflight evaluation of the cardiovascular system of an astronaut and to forecast how it will be affected during the mission. To predict these changes, a computational cardiovascular model must be constructed. Although physiology data can be used to make a general model, a more desirable subject-specific model requires anatomical, functional, and flow data from the specific astronaut. MRI has the unique advantage of providing images with all of the above information, including three-directional velocity data which can be used as boundary conditions in a computational fluid dynamics (CFD) program [2,3]. MRI-based CFD is very promising for reproduction of the flow patterns of a specific subject and prediction of changes in the absence of gravity. The aim of this study was to test the feasibility of this approach by reconstructing the geometry of MRI-scanned arterial models and reproducing the MRI-measured velocities using CFD simulations on these geometries.

Spirka, T. A.↗
NASA NTRS2002

Cellular and Network Mechanisms Underlying Information Processing in a Simple Sensory System

Realistic, biophysically-based compartmental models were constructed of several primary sensory interneurons in the cricket cercal sensory system. A dynamic atlas of the afferent input to these cells was used to set spatio-temporal parameters for the simulated stimulus-dependent synaptic inputs. We examined the roles of dendritic morphology, passive membrane properties, and active conductances on the frequency tuning of the neurons. The sensitivity of narrow-band low pass interneurons could be explained entirely by the electronic structure of the dendritic arbors and the dynamic sensitivity of the SIZ. The dynamic characteristics of interneurons with higher frequency sensitivity required models with voltage-dependent dendritic conductances.

Jacobs, Gwen↗
NASA NTRS1986

Evaluation of reliability modeling tools for advanced fault tolerant systems

The Computer Aided Reliability Estimation (CARE III) and Automated Reliability Interactice Estimation System (ARIES 82) reliability tools for application to advanced fault tolerance aerospace systems were evaluated. To determine reliability modeling requirements, the evaluation focused on the Draper Laboratories' Advanced Information Processing System (AIPS) architecture as an example architecture for fault tolerance aerospace systems. Advantages and limitations were identified for each reliability evaluation tool. The CARE III program was designed primarily for analyzing ultrareliable flight control systems. The ARIES 82 program's primary use was to support university research and teaching. Both CARE III and ARIES 82 were not suited for determining the reliability of complex nodal networks of the type used to interconnect processing sites in the AIPS architecture. It was concluded that ARIES was not suitable for modeling advanced fault tolerant systems. It was further concluded that subject to some limitations (the difficulty in modeling systems with unpowered spare modules, systems where equipment maintenance must be considered, systems where failure depends on the sequence in which faults occurred, and systems where multiple faults greater than a double near coincident faults must be considered), CARE III is best suited for evaluating the reliability of advanced tolerant systems for air transport.

Baker, Robert↗
NASA NTRS1997

Bounds on Lithospheric Thickness on Venus from Magellan Gravity and Topography Data

The primary objective of the work executed under NAGW-4784 is to provide constraints on the thermal and tectonic evolution of Venus. Establishing thermal and tectonic evolution models requires not only geological, but geophysical constraints, in particular the nature of temporal and spatial variations in crustal and lithospheric thickness. The major topics of study completed under NAGW-4784 (described more fully below) are: (1) detailed analyses of the resolution of Magellan Line-Of-Site (LOS) Doppler data to establish the minimum resolvable wavelength in the gravity data; (2) calculations of the global strain field in the venusian lithosphere and comparisons with global strain patterns from geological mapping; (3) study of the geological history of coronae at E. Eistla Regio; (4) estimation of crustal and lithospheric thickness by modeling of topography at asymmetric and symmetric rift-like chasmata; (5) preliminary investigations of spatial versus temporal variations in lithospheric thickness. Both the PI and Co-I have presented papers based on these topics at national and international meetings (American Geophysical Union Meetings, Lunar and Planetary Science Conferences, Chapman Conference on the Geodynamics of Venus).

Johnson, Catherine L.↗
NASA NTRS1993

Efficient partitioning and assignment on programs for multiprocessor execution

The general problem studied is that of segmenting or partitioning programs for distribution across a multiprocessor system. Efficient partitioning and the assignment of program elements are of great importance since the time consumed in this overhead activity may easily dominate the computation, effectively eliminating any gains made by the use of the parallelism. In this study, the partitioning of sequentially structured programs (written in FORTRAN) is evaluated. Heuristics, developed for similar applications are examined. Finally, a model for queueing networks with finite queues is developed which may be used to analyze multiprocessor system architectures with a shared memory approach to the problem of partitioning. The properties of sequentially written programs form obstacles to large scale (at the procedure or subroutine level) parallelization. Data dependencies of even the minutest nature, reflecting the sequential development of the program, severely limit parallelism. The design of heuristic algorithms is tied to the experience gained in the parallel splitting. Parallelism obtained through the physical separation of data has seen some success, especially at the data element level. Data parallelism on a grander scale requires models that accurately reflect the effects of blocking caused by finite queues. A model for the approximation of the performance of finite queueing networks is developed. This model makes use of the decomposition approach combined with the efficiency of product form solutions.

Standley, Hilda M.↗