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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

Computer Programs (Turbomachinery)

NASA computer programs are extensively used in design of industrial equipment. Available from the Computer Software Management and Information Center (COSMIC) at the University of Georgia, these programs are employed as analysis tools in design, test and development processes, providing savings in time and money. For example, two NASA computer programs are used daily in the design of turbomachinery by Delaval Turbine Division, Trenton, New Jersey. The company uses the NASA splint interpolation routine for analysis of turbine blade vibration and the performance of compressors and condensers. A second program, the NASA print plot routine, analyzes turbine rotor response and produces graphs for project reports. The photos show examples of Delaval test operations in which the computer programs play a part. In the large photo below, a 24-inch turbine blade is undergoing test; in the smaller photo, a steam turbine rotor is being prepared for stress measurements under actual operating conditions; the "spaghetti" is wiring for test instrumentation

Source record↗
NASA NTRS1990

Predicting performance of parallel computations

An accurate and computationally efficient method for predicting the performance of a class of parallel computations running on concurrent systems is described. A parallel computation is modeled as a task system with precedence relationships expressed as a series-parallel directed acyclic graph. Resources in a concurrent system are modeled as service centers in a queuing network model. Using these two models as inputs, the method outputs predictions of expected execution time of the parallel computation and the concurrent system utilization. The method is validated against both detailed simulation and actual execution on a commercial multiprocessor. Using 100 test cases, the average error of the prediction when compared to simulation statistics is 1.7 percent, with a standard deviation of 1.5 percent; the maximum error is about 10 percent.

Mak, Victor W.↗
DOE OSTI2024

Development of message passing-based graph convolutional networks for classifying cancer pathology reports

Abstract Background Applying graph convolutional networks (GCN) to the classification of free-form natural language texts leveraged by graph-of-words features (TextGCN) was studied and confirmed to be an effective means of describing complex natural language texts. However, the text classification models based on the TextGCN possess weaknesses in terms of memory consumption and model dissemination and distribution. In this paper, we present a fast message passing network (FastMPN), implementing a GCN with message passing architecture that provides versatility and flexibility by allowing trainable node embedding and edge weights, helping the GCN model find the better solution. We applied the FastMPN model to the task of clinical information extraction from cancer pathology reports, extracting the following six properties: main site, subsite, laterality, histology, behavior, and grade. Results We evaluated the clinical task performance of the FastMPN models in terms of micro- and macro-averaged F1 scores. A comparison was performed with the multi-task convolutional neural network (MT-CNN) model. Results show that the FastMPN model is equivalent to or better than the MT-CNN. Conclusions Our implementation revealed that our FastMPN model, which is based on the PyTorch platform, can train a large corpus (667,290 training samples) with 202,373 unique words in less than 3 minutes per epoch using one NVIDIA V100 hardware accelerator. Our experiments demonstrated that using this implementation, the clinical task performance scores of information extraction related to tumors from cancer pathology reports were highly competitive.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1997

Sequential Testing Algorithms for Multiple Fault Diagnosis

In this paper, we consider the problem of constructing optimal and near-optimal test sequencing algorithms for multiple fault diagnosis. The computational complexity of solving the optimal multiple-fault isolation problem is super-exponential, that is, it is much more difficult than the single-fault isolation problem, which, by itself, is NP-hard. By employing concepts from information theory and AND/OR graph search, we present several test sequencing algorithms for the multiple fault isolation problem. These algorithms provide a trade-off between the degree of suboptimality and computational complexity. Furthermore, we present novel diagnostic strategies that generate a diagnostic directed graph (digraph), instead of a diagnostic tree, for multiple fault diagnosis. Using this approach, the storage complexity of the overall diagnostic strategy reduces substantially. The algorithms developed herein have been successfully applied to several real-world systems. Computational results indicate that the size of a multiple fault strategy is strictly related to the structure of the system.

Shakeri, Mojdeh↗
NASA NTRS2006

Distributed Computing Architecture for Image-Based Wavefront Sensing and 2 D FFTs

Image-based wavefront sensing (WFS) provides significant advantages over interferometric-based wavefi-ont sensors such as optical design simplicity and stability. However, the image-based approach is computational intensive, and therefore, specialized high-performance computing architectures are required in applications utilizing the image-based approach. The development and testing of these high-performance computing architectures are essential to such missions as James Webb Space Telescope (JWST), Terrestial Planet Finder-Coronagraph (TPF-C and CorSpec), and Spherical Primary Optical Telescope (SPOT). The development of these specialized computing architectures require numerous two-dimensional Fourier Transforms, which necessitate an all-to-all communication when applied on a distributed computational architecture. Several solutions for distributed computing are presented with an emphasis on a 64 Node cluster of DSPs, multiple DSP FPGAs, and an application of low-diameter graph theory. Timing results and performance analysis will be presented. The solutions offered could be applied to other all-to-all communication and scientifically computationally complex problems.

Smith, Jeffrey S.↗
DOE OSTI2026

HydraGNN_OPF_GFM_2026 - Ensemble of predictive graph foundation models for power grid applications

This dataset supports research on graph foundation models for optimal power flow (OPF) on electric grids using HydraGNN. It contains heterogeneous graph representations of PGLib-OPF cases spanning systems from 14 to 13,659 buses, together with packed HDF5 datasets for pretraining, feasibility classification, and N-1 contingency analysis. The release includes OPF solution data, downstream fine-tuning datasets, pretrained HeteroSAGE and HeteroHEAT model checkpoints, hyperparameter-optimization summaries across multiple heterogeneous GNN architectures, and aggregated fine-tuning results for sample-efficiency studies. The dataset is designed to enable scalable training, evaluation, and transfer-learning studies for OPF surrogate modeling, including node-level AC-OPF solution prediction, graph-level prediction, feasibility classification, operating-condition generalization, and contingency-response tasks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1977

Coherent wave induced particle precipitation into the upper atmosphere

A description is presented of the results of a computer simulation involving a study of the particle precipitation induced by coherent VLF waves in the magnetosphere. The results of a computation for a 10 picoweber/sq m wave amplitude are shown in a graph. The precipitated flux for three different energies is given in a table. For 1.5 keV the energy deposition rate is about 0.8 erg/sq cm-sec, almost as intense as a moderate aurora. It is concluded that significant energy is deposited by a wave of 10 picoweber/sq m intensity. Such a wave amplitude is representative of highly coherent VLF wave types that are found in the magnetosphere. On the basis of the considered results it appears that controlled VLF wave injection in the magnetosphere could be an important and useful tool to study the coupling processes between the atmosphere and magnetosphere.

Inan, U. S.↗
NASA NTRS1979

GEOS 3 STDN S band Doppler tracking investigation

GEOS 3S Doppler band and laser ranging data, acquired from August 1975 to March 1976 in the spacecraft altimeter calibration area, are examined. An evaluation of two-way and three-way Doppler data, for the positioning of Spaceflight Tracking and Data Network S band stations is presented, as well as the Goddard Space Flight Center laser system that is used to reference the exact position of the Doppler stations. The two-way and three-way Doppler tracking devices, situated at Rosman and Bermuda, have yielded data for the recovery of GEOS 3 arc height with an uncertainty of only 1 m. Attention is given to the effects of beacon signal frequency instability, controlled by a temperature sensitive auxiliary crystal oscillator on board the spacecraft, and to the one-way range rate tracking noise that was found to be within a range of 2 to 10 cm/s. 1- and 2-way passes and their different arc meters are graphed, showing the Doppler tracking interval. It was concluded that other accurate computations and recovery of station coordinates could be performed employing tracking data from S band stations.

Rosenbaum, B.↗
NASA NTRS1986

On the free vibrations of spinning paraboloids

The dynamic behavior of a spinning linear-elastic paraboloid subject to nonaxisymmetric deformation is investigated analytically, applying the Rayleigh-Ritz procedure described by Utku et al. (1983). Energy-density, strain-displacement, and velocity-displacement expressions are generated; expressions for the generalized strain and position vector are derived; and the discretized dynamic equations are obtained. Numerical results obtained with a computer-program implementation of the method are presented in extensive tables and graphs. The effects of spin rate and bending rigidity and results for the special case of a spinning disk are included.

Shoemaker, W. L.↗
NASA NTRS1987

Methods for design and evaluation of integrated hardware/software systems for concurrent computation

Two testbed programming environments to support the evaluation of a large range of parallel architectures have been implemented under the program Parallel Implementation of Scientific Computing Environments (PISCES). The PISCES 1 environment was applied to two areas of aerospace interest: a sparse matrix iterative equation solver and a dynamic scene analysis system. Currently, the NICE/SPAR testbed system for structural analysis is being modified for parallel operation under PISCES 2; the PISCES 1 applications are also being adapted for PISCES 2. A new formal model of concurrent computation has been developed, based on the mathematical system known as H graph semantics together with a timed Petri net model of the parallel aspects of a system.

Pratt, Terrence W.↗
NASA NTRS1988

Modeling and optimum time performance for concurrent processing

The development of a new graph theoretic model for describing the relation between a decomposed algorithm and its execution in a data flow environment is presented. Called ATAMM, the model consists of a set of Petri net marked graphs useful for representing decision-free algorithms having large-grained, computationally complex primitive operations. Performance time measures which determine computing speed and throughput capacity are defined, and the ATAMM model is used to develop lower bounds for these times. A concurrent processing operating strategy for achieving optimum time performance is presented and illustrated by example.

Mielke, Roland R.↗
NASA NTRS1989

Theoretical characterization of the minimum energy path for hydrogen atom addition to N2 - Implications for the unimolecular lifetime of HN2

Results are reported from CASSCF externally contracted CI ab initio computations of the minimum-energy path for the addition of H to N2. The theoretical basis and numerical implementation of the computations are outlined, and the results are presented in extensive tables and graphs and characterized in detail. The zero-point-corrected barrier for HN2 dissociation is estimated as 8.5 kcal/mol, and the lifetime of the lowest-lying quasi-bound vibrational state of HN2 is found to be between 88 psec and 5.8 nsec (making experimental observation of this species very difficult).

Walch, Stephen P.↗
NASA NTRS1991

Comparison of straight and 15 degree vectored nozzles using a six component thrust stand

This project compared the forces and moments produced by straight and 15 degree vectored nozzles. Using the six component thrust stand in the engines laboratory at California Polytechnic State University, several trials were performed. This data was then reduced using first a computer program and then later an electronic spreadsheet. This reduced data was graphed and compared. As a result of these comparisons some unexpected forces were discovered. Several more tests were run including a zero thrust test and a statistical comparison were done to discover the source of these discrepancies. As a direct result several nozzle changes were made and significant revisions to the thrust stand are being made.

Carpenter, Thomas W.↗
DOE OSTI2024

Evaluating the Use of Foundational Chemical Language Models in Multimodal Graph Fusion

Rapid and accurate prediction of the physicochemical properties of molecules given their structures remains a key challenge in cheminformatics. Machine learning approaches offer high-throughput options, but the optimality of inductive biases and data representations are up for debate. For example, BERT-based masked language models (MLMs) can be trained in a self-supervised way on hundreds of millions to billions of readily available SMILES strings. Another option is graph neural networks (GNNs), which can operate directly on molecular structures. Yet, generating accurate molecular geometry is computationally expensive, leading to a relative scarcity in data compared to SMILES strings. It is attractive to combine these two paradigms by pre-training an LM on a large corpus of SMILES strings and embedding these representation into a geometric graph neural network. Despite the promise of such an approach, and contrary to previous studies, we find mixed results with the combination of the LMs and GNNs on several molecule datasets. In particular, we found evidence for improvement on the FreeSolv and QM7 benchmarks, but degraded performance on the ESOL, LIPO and QM9 datasets compared to a GNN baseline.

Francel, Collin [University of Alabama]↗
NASA NTRS2017

Applying Graph Theory to Problems in Air Traffic Management

Graph theory is used to investigate three different problems arising in air traffic management. First, using a polynomial reduction from a graph partitioning problem, it isshown that both the airspace sectorization problem and its incremental counterpart, the sector combination problem are NP-hard, in general, under several simple workload models. Second, using a polynomial time reduction from maximum independent set in graphs, it is shown that for any fixed e, the problem of finding a solution to the minimum delay scheduling problem in traffic flow management that is guaranteed to be within n1-e of the optimal, where n is the number of aircraft in the problem instance, is NP-hard. Finally, a problem arising in precision arrival scheduling is formulated and solved using graph reachability. These results demonstrate that graph theory provides a powerful framework for modeling, reasoning about, and devising algorithmic solutions to diverse problems arising in air traffic management.

computational complexity↗