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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

Multivariant function model generation

The development of computer programs applicable to space vehicle guidance was conducted. The subjects discussed are as follows: (1) determination of optimum reentry trajectories, (2) development of equations for performance of trajectory computation, (3) vehicle control for fuel optimization, (4) development of equations for performance trajectory computations, (5) applications and solution of Hamilton-Jacobi equation, and (6) stresses in dome shaped shells with discontinuities at the apex.

Source record↗
NASA NTRS1979

Status of yield estimation technology: A review of second-generation model development and evaluation

Multiple regression models were studied in order to determine their yield estimation capability for any arbitrary unit area and to obtain greater responsiveness and accuracy through the use of additional data sources applied at smaller spatial and temporal scales. It was concluded that data base inadequacy was the factor limiting performance in the models studied and that each of the models has more yield predicting capability than was reached during LACIE.

Stuff, R. G.↗
NASA NTRS1981

The thermal influence of continents on a model-generated January climate

Two climate simulations were compared. Both climate computations were initialized with the same horizontally uniform state of rest. However, one is carried out on a water planet (without continents), while the second is repeated on a planet with geographically realistic but flat (sea level) continents. The continents in this experiment have a uniform albedo of 0.14, except where snow accumulates, a uniform roughness height of 0.3 m, and zero water storage capacity. Both runs were carried out for a 'perpetual January' with solar declination fixed at January 15.

Spar, J.↗
NASA NTRS1984

Comparison of GLAS retrieved cloud fields with model generated rainfall fields

Monthly mean fractional cloud cover for January and February 1979, retrieved from SOP 1 of FGGE, are compared with the total precipitation field derived diagonally from the GLAS analysis/forecast system for the same time period. The breakdown of cloudiness into day (3 AM) and night (3 PM) is consistent with maps of outgoing long wave and short wave radiation inferred from AVHRR data. Of the many regions of coincidence, there is a particularly striking phenomenon: west of the coast of Peru, at about 20 deg S, there is a distinct small scale maximum in precipitation which coincides precisely with a maximum in the cloudiness field. This maximum in cloudiness and precipitation does not appear in the NOAA/NESS fields of albedo and outgoing long wave radiation which are normally sensitive to cloud fields. These low level clouds with warm tops are a mainly nocturnal phenomenon.

Susskind, J.↗
NASA NTRS1989

Generation models of electron conics

Electron distribution functions (EDFs) with a peak oblique to the magnetic field, adjacent to but distinct from loss-cone features, have been observed by the DE 1, Viking, and S3-3 spacecraft in passes through the nightside auroral zone, polar cap, dayside cusp, and extended dayside auroral oval. Using particle simulations, two types of wave excitation and particle acceleration mechanisms which may contribute to producing these electron conic distributions are investigated. The first involves excitation of upper-hybrid waves by the electron loss cone, and the subsequent perpendicular heating of the background and thermal electrons. The second involves excitation of downward propagating parallel modes by an auroral electron beam which frequently accompanies the upflowing electron conics. These modes provide parallel acceleration, which modifies the GDF. Those electrons which are not lost to the atmosphere and mirror back up the magnetic field line give rise to enhancements in the GDF at the edge of the loss cone.

Roth, I.↗
DOE OSTI2025

Flow matching beyond kinematics: Generating jets with particle identification and trajectory displacement information

We introduce the first generative model trained on the etlass dataset. Our model generates jets at the constituent level, and it is a permutation-equivariant continuous normalizing flow (CNF) trained with the flow matching technique. It is conditioned on the jet type, so that a single model can be used to generate the ten different jet types of etlass. For the first time, we also introduce a generative model that goes beyond the kinematic features of jet constituents. The etlass dataset includes more features, such as particle-ID and track impact parameter, and we demonstrate that our CNF can accurately model all of these additional features as well. Our generative model for etlass expands on the versatility of existing jet generation techniques, enhancing their potential utility in high-energy physics research, and offering a more comprehensive understanding of the generated jets. Published by the American Physical Society 2025

Birk, Joschka (ORCID:0000000219310127)↗
NASA NTRS2016

The Characterization of a DIRSIG Simulation Environment to Support the Inter-Calibration of Spaceborne Sensors

Climate change studies require long-term, continuous records that extend beyond the lifetime, and the temporal resolution, of a single remote sensing satellite sensor. The inter-calibration of spaceborne sensors is therefore desired to provide spatially, spectrally, and temporally homogeneous datasets. The Digital Imaging and Remote Sensing Image Generation (DIRSIG) tool is a first principle-based synthetic image generation model that has the potential to characterize the parameters that impact the accuracy of the inter-calibration of spaceborne sensors. To demonstrate the potential utility of the model, we compare the radiance observed in real image data to the radiance observed in simulated image from DIRSIG. In the present work, a synthetic landscape of the Algodones Sand Dunes System is created. The terrain is facetized using a 2-meter digital elevation model generated from NASA Goddard's LiDAR, Hyperspectral, and Thermal (G-LiHT) imager. The material spectra are assigned using hyperspectral measurements of sand collected from the Algodones Sand Dunes System. Lastly, the bidirectional reflectance distribution function (BRDF) properties are assigned to the modeled terrain using the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF product in conjunction with DIRSIG's Ross-Li capability. The results of this work indicate that DIRSIG is in good agreement with real image data. The potential sources of residual error are identified and the possibilities for future work are discussed..

Ambeau, Brittany L.↗
NASA NTRS1983

Advanced earth observation spacecraft computer-aided design software: Technical, user and programmer guide

The IDEAS computer of NASA is a tool for interactive preliminary design and analysis of LSS (Large Space System). Nine analysis modules were either modified or created. These modules include the capabilities of automatic model generation, model mass properties calculation, model area calculation, nonkinematic deployment modeling, rigid-body controls analysis, RF performance prediction, subsystem properties definition, and EOS science sensor selection. For each module, a section is provided that contains technical information, user instructions, and programmer documentation.

Farrell, C. E.↗
NASA NTRS1990

COMGEN: A computer program for generating finite element models of composite materials at the micro level

COMGEN (Composite Model Generator) is an interactive FORTRAN program which can be used to create a wide variety of finite element models of continuous fiber composite materials at the micro level. It quickly generates batch or session files to be submitted to the finite element pre- and postprocessor PATRAN based on a few simple user inputs such as fiber diameter and percent fiber volume fraction of the composite to be analyzed. In addition, various mesh densities, boundary conditions, and loads can be assigned easily to the models within COMGEN. PATRAN uses a session file to generate finite element models and their associated loads which can then be translated to virtually any finite element analysis code such as NASTRAN or MARC.

Melis, Matthew E.↗
NASA NTRS2005

Generating Solid Models from Topographical Data

A method of generating solid models of terrain involves the conversion of topographical data into a form useable by a rapid-prototyping (RP) machine. The method was developed to enable the use of the RP machine to make solid models of Martian terrain from Mars Orbiter laser-altimeter topographical data. The method is equally applicable to the generation of models of the terrains of other astronomical bodies, including other planets, asteroids, and Earth. Topographical data describe a terrain in terms of a set of three-dimensional coordinates [e.g., Cartesian (x,y,z) or polar (latitude, longitude, radius) coordinates] of points or nodes on the terrain surface. The input data for the RP machines are required to provide a three-dimensional description, not of a single surface, but of a volume in this case, a ground volume that underlies the terrain surface. The description is required to be in the form of triangular elements that connect the nodes of all the surfaces and that completely bound the volume, with no open areas, no overlap of triangles, and no extraneous geometric elements. The software used in the present model-generation method was written in IDL - an advanced programming language that affords a number of tools, including subroutines that triangularize surfaces. The software creates a volume from the topographical surface data by adding sides to the edges of the terrain surface and joining the sides with a bottom surface. Each of the sides is triangularized by use of IDL subroutines, and then the software searches for extraneous elements and removes them. Topographical data are usually presented in a grid corresponding to polar coordinates, so that a model generated from such data is equivalent to a topographical map in Mercator projection. However an RP machine is fully capable of including the curvature of a planetary body in a model that it makes. Therefore, the software also offers a capability to transform the topographical data to a projection onto a surface having a curvature corresponding to that of the surface of the modeled planet.

Keller, John W.↗
NASA NTRS1984

The Solid Model Geometry Generator (SMGG)

The Solid Model Geometry Generator (SMGG) system provides the capacity to model complex solid objects through the composition of primitive parts. The parts are specified through input of dimension and orientation parameters. The parts may later be edited, the model may be displayed (through a variety of display options), and the resulting geometry formatted for subsequent analysis. The SMGG system was originally constructed for use in the preliminary stages of space station and other spacecraft design. Because the system models a design through the use of basic shapes common to many solid objects and provides limited capabilities for producing irregularly shaped parts, it can be used for a variety of applications. Currently, seven primitive parts may be specified and produced through SMGG. These include boxes, spheres, cones, paraboloids, tori, and translationally or rotationally swept parts. Each part may be specified by the user through input of basic part dimensions and a local orientation. For example, a box is specified by its length, width, height and orientation in space (rotation, translation, and scaling).

Jones, K. H.↗
NASA NTRS1995

Integrated performance and reliability specification for digital avionics systems

This paper describes an automated tool for performance and reliability assessment of digital avionics systems, called the Automated Design Tool Set (ADTS). ADTS is based on an integrated approach to design assessment that unifies traditional performance and reliability views of system designs, and that addresses interdependencies between performance and reliability behavior via exchange of parameters and result between mathematical models of each type. A multi-layer tool set architecture has been developed for ADTS that separates the concerns of system specification, model generation, and model solution. Performance and reliability models are generated automatically as a function of candidate system designs, and model results are expressed within the system specification. The layered approach helps deal with the inherent complexity of the design assessment process, and preserves long-term flexibility to accommodate a wide range of models and solution techniques within the tool set structure. ADTS research and development to date has focused on development of a language for specification of system designs as a basis for performance and reliability evaluation. A model generation and solution framework has also been developed for ADTS, that will ultimately encompass an integrated set of analytic and simulated based techniques for performance, reliability, and combined design assessment.

Brehm, Eric W.↗
DOE OSTI2025

Generative AI models for learning flow maps of stochastic dynamical systems in bounded domains

Simulating stochastic differential equations (SDEs) in bounded domains, presents significant computational challenges due to particle exit phenomena, which requires accurate modeling of interior stochastic dynamics and boundary interactions. Despite the success of machine learning-based methods in learning SDEs, existing learning methods are not applicable to SDEs in bounded domains because they cannot accurately capture the particle exit dynamics. We present a unified hybrid data-driven approach that combines a conditional diffusion model with an exit prediction neural network to capture both interior stochastic dynamics and boundary exit phenomena. Our ML model consists of two major components: a neural network that learns exit probabilities using binary cross-entropy loss with rigorous convergence guarantees, and a training-free diffusion model that generates state transitions for non-exiting particles using closed-form score functions. The two components are integrated through a probabilistic sampling algorithm that determines particle exit at each time step and generates appropriate state transitions. Here, the performance of the proposed approach is demonstrated via three test cases: a one-dimensional simplified problem for theoretical verification, a two-dimensional advection-diffusion problem in a bounded domain, and a three-dimensional problem of interest to magnetically confined fusion plasmas.

Bounded domains↗