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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Automatic recognition system for document digitization in nuclear power plants

With the increasing number of data-driven models in nuclear applications, large volumes of numerical data are required to accurately model and predict the health status of a plant component. However, many historical operation logs that contain useful information are not fully utilized due to the lack of a systematic approach of digitization. To overcome this issue, this study proposes an automatic pipeline for extracting information from handwritten tabular documents collected from nuclear power plants. In our pipeline, we first denoise scanned documents with morphological operations, and then extract relevant parts from individual pages using both traditional computer vision and neural network methods. Handwriting recognition is applied to obtain text and numbers. As the most challenging step is how to crop only relevant information, the main focus of our paper is to detect tables and cells from scanned handwritten documents. Here we evaluate the efficiency and accuracy of our proposed method on handwritten operational reports obtained from a real-world case study. The results demonstrate the high accuracy and practicality of our proposed method.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1985

Alternatives for Jet Engine Control. Volume 1: Modelling and Control Design with Jet Engine Data

This document compiles a comprehensive list of publications supported by, or related to, National Aeronautics and Space Administration Grant NSG-3048, entitled "Alternatives for Jet Engine Control". Dr. Kurt Seldner was the original Technical Officer for the grant, at Lewis Research Center. Dr. Bruce Lehtinen was the final Technical Officer. At the University of Notre Dame, Drs. Michael K. Sain and R. Jeffrey Leake were the original Project Directors, with Dr. Sain becoming the final Project Director. Publications cover work over a ten-year period. The Final Report is divided into two parts. Volume i, "Modelling and Control Design with Jet Engine Data", follows in this report. Volume 2, "Modelling and Control Design with Tensors", has been bound separately.

Sain, M. K.↗
NASA NTRS2001

Technical Report Series on Global Modeling and Data Assimilation: The Climate of the FVCCM-3 Model - Volume 20

This document describes the climate of version 1 of the NASA-NCAR model developed at the Data Assimilation Office (DAO). The model consists of a new finite-volume dynamical core and an implementation of the NCAR climate community model (CCM-3) physical parameterizations. The version of the model examined here was integrated at a resolution of 2 degrees latitude by 2.5 degrees longitude and 32 levels. The results are based on assimilation that was forced with observed sea surface temperature and sea ice for the period 1979-1995, and are compared with NCEP/NCAR reanalyses and various other observational data sets. The results include an assessment of seasonal means, subseasonal transients including the Madden Julian Oscillation, and interannual variability. The quantities include zonal and meridional winds, temperature, specific humidity, geopotential height, stream function, velocity potential, precipitation, sea level pressure, and cloud radiative forcing.

Suarez, Max J.↗
NASA NTRS1980

A mathematical model for Vertical Attitude Takeoff and Landing (VATOL) aircraft simulation. Volume 2: Model equations and base aircraft data

Equations incorporated in a VATOL six degree of freedom off-line digital simulation program and data for the Vought SF-121 VATOL aircraft concept which served as the baseline for the development of this program are presented. The equations and data are intended to facilitate the development of a piloted VATOL simulation. The equation presentation format is to state the equations which define a particular model segment. Listings of constants required to quantify the model segment, input variables required to exercise the model segment, and output variables required by other model segments are included. In several instances a series of input or output variables are followed by a section number in parentheses which identifies the model segment of origination or termination of those variables.

Fortenbaugh, R. L.↗
NASA NTRS1973

S-2 stage 1/25 scale model base region thermal environment test. Volume 1: Test results, comparison with theory and flight data

A 1/25 scale model S-2 stage base region thermal environment test is presented. Analytical results are included which reflect the effect of engine operating conditions, model scale, turbo-pump exhaust gas injection on base region thermal environment. Comparisons are made between full scale flight data, model test data, and analytical results. The report is prepared in two volumes. The description of analytical predictions and comparisons with flight data are presented. Tabulation of the test data is provided.

Sadunas, J. A.↗
DOE OSTI2025

Intelligent Sampling of Extreme-Scale Turbulence Datasets for Accurate and Efficient Spatiotemporal Model Training

With the end of Moore’s law and Dennard scaling, efficient training increasingly requires rethinking data volume. Can we train better models with significantly less data via intelligent subsampling? To explore this, we develop SICKLE, a sparse intelligent curation framework for efficient learning, featuring a novel maximum entropy (MaxEnt) sampling approach, scalable training, and energy benchmarking. We compare MaxEnt with random and phase-space sampling on large direct numerical simulation (DNS) datasets of turbulence. Evaluating SICKLE at scale on Frontier, we show that subsampling as a preprocessing step can, in many cases, improve model accuracy and substantially lower energy consumption, with observed reductions of up to 38×.

Brewer, Wes [ORNL] (ORCID:0000000236393956)↗
NASA NTRS1976

Wind tunnel test on a 1/4.622 Froude scale, hingeless rotor, tilt rotor model, volume 1

Wing tunnel test data on a 1/4.622 Froude scale, hingeless rotor, tilt rotor mode are reported for all potential flight conditions through hover and a wide envelope of transitions. A mathematical model was used to describe the rotor system in real time simulation by means of regression analyses. Details of the model, test program and data system are provided together with four data files for hover and transition.

Magee, J. P.↗
NASA NTRS2001

Evaluation of Stratospheric Transport in New 3D Models Using the Global Modeling Initiative Grading Criteria

The Global Modeling Initiative (GMI) Team developed objective criteria for model evaluation in order to identify the best representation of the stratosphere. This work created a method to quantitatively and objectively discriminate between different models. In the original GMI study, 3 different meteorological data sets were used to run an offline chemistry and transport model (CTM). Observationally-based grading criteria were derived and applied to these simulations and various aspects of stratospheric transport were evaluated; grades were assigned. Here we report on the application of the GMI evaluation criteria to CTM simulations integrated with a new assimilated wind data set and a new general circulation model (GCM) wind data set. The Finite Volume Community Climate Model (FV-CCM) is a new GCM developed at Goddard which uses the NCAR CCM physics and the Lin and Rood advection scheme. The FV-Data Assimilation System (FV-DAS) is a new data assimilation system which uses the FV-CCM as its core model. One year CTM simulations of 2.5 degrees longitude by 2 degrees latitude resolution were run for each wind data set. We present the evaluation of temperature and annual transport cycles in the lower and middle stratosphere in the two new CTM simulations. We include an evaluation of high latitude transport which was not part of the original GMI criteria. Grades for the new simulations will be compared with those assigned during the original GMT evaluations and areas of improvement will be identified.

Strahan, Susan E.↗
DOE OSTI2023

Differentiable modelling to unify machine learning and physical models for geosciences

Process-based modelling offers interpretability and physical consistency in many domains of geosciences but struggles to leverage large datasets efficiently. Machine-learning methods, especially deep networks, have strong predictive skills yet are unable to answer specific scientific questions. Here, in this Perspective, we explore differentiable modelling as a pathway to dissolve the perceived barrier between process-based modelling and machine learning in the geosciences and demonstrate its potential with examples from hydrological modelling. ‘Differentiable’ refers to accurately and efficiently calculating gradients with respect to model variables or parameters, enabling the discovery of high-dimensional unknown relationships. Differentiable modelling involves connecting (flexible amounts of) prior physical knowledge to neural networks, pushing the boundary of physics-informed machine learning. It offers better interpretability, generalizability, and extrapolation capabilities than purely data-driven machine learning, achieving a similar level of accuracy while requiring less training data. Additionally, the performance and efficiency of differentiable models scale well with increasing data volumes. Under data-scarce scenarios, differentiable models have outperformed machine-learning models in producing short-term dynamics and decadal-scale trends owing to the imposed physical constraints. Differentiable modelling approaches are primed to enable geoscientists to ask questions, test hypotheses, and discover unrecognized physical relationships. Future work should address computational challenges, reduce uncertainty, and verify the physical significance of outputs.

58 GEOSCIENCES↗
NASA NTRS1984

Bearing tester data compilation, analysis and reporting and bearing math modeling, volume 1

Thermal and mechanical models of high speed angular contact ball bearings operating in LOX and LN2 were developed and verified with limited test data in an effort to further understand the parameters that determine or effect the SSME turbopump bearing operational characteristics and service life. The SHABERTH bearing analysis program which was adapted to evaluate shaft bearing systems in cryogenics is not capable of accommodating varying thermal properties and two phase flow. A bearing model with this capability was developed using the SINDA thermal analyzer. Iteration between the SHABERTH and the SINDA models enable the establishment of preliminary bounds for stable operation in LN2. These limits were established in terms of fluid flow, fluid inlet temperature, and axial load for a shaft speed of 30,000 RPM.

Marshall, D. D.↗
DOE OSTI2024

OPER: Optimality-Guided Embedding Table Parallelization for Large-scale Recommendation Model

With the sharp increasing volume of user data, Deep Learning Recommendation Model (DLRM) becomes an indispensable infrastructure in large technology companies. However, large-scale DLRM on the multi-GPU platform is still inefficient due to unbalanced workload partitioning and intensive inter-GPU communication. To this end, we propose OPER, an OPtimality guided Embedding table placement for large-scale Recommendation model training and inference. OPER explores the potential of mitigating remote memory access latency in DLRM through fine-grained embedding table placement. Specifically, OPER proposes a theoretical modeling that builds up the relationship between EMT placement and the embedding communication latency in both training and inference. OPER proves the NP hardness of finding the optimal embedding table placement and proposes a heuristic algorithm that yields near optimal placement. OPER implements a SHMEM-based embedding table training system and a unified embedding index mapping to support fine-grained embedding table sharding and placement. Comprehensive experiments reveal that OPER achieves on average 3.4× and 5.1× speedup on training and inference respectively over state-of-the-art DLRM frameworks.

Wang, Zheng↗
NASA NTRS1979

Propellant injection for MPD thrusters

The propellant gas for a pulsed self-field MPD thruster must be supplied by a valve which will necessarily be separated from the thruster injectors by some ullage volume. A model and experimental data are presented showing the effect of the ullage volume on the propellant pulse shape, along with a discussion of the proper location for the propellant flow choke point(s). Prospective MPD pulse valves are surveyed and the performance of two solenoid valves, one with a pulse length less than 2 milliseconds, is included. Pulse shape data is presented for a thruster specially modified to reduce the ullage volume.

Jones, R. M.↗
DOE OSTI2020

Development of limited-view tomography for measurement of Spray G plume direction and liquid volume fraction

Abstract The method for direct injection of fuel in the cylinder of an IC engines is important to high-efficiency and low-emission performance. Optical spray diagnostics plays an important role in understanding plume movement and interaction for multi-hole injectors, and providing baseline understanding used for computational optimization of fuel delivery. Traditional planar or line-of-sight diagnostics fail to capture the liquid distribution because of optical thickness concerns. This work proposes a high-speed (67 kHz) extinction imaging technique at various injector rotations coupled to computed tomography (CT) for time-resolved reconstruction of liquid volume fraction in three dimensions. The number of views selected and processing were based on synthetic (modeled) liquid volume fraction data where extinction and CT adequately reconstructed each plume. The exercise showed that for an 8-hole, symmetric-design injector (ECN Spray G), only three different views are enough to reproduce the direction of each plume, and particularly the mean plume direction. Therefore, the number of views was minimized for experiments to save expense. Measurements applying this limited-view technique confirm plume–plume variations also detected with mechanical patternation, while providing better spatial and temporal resolution than achieved previously. Uncertainties due to the limited view within pressurized spray chambers, the droplet size, and optically thick regions are discussed. Graphic abstract

42 ENGINEERING↗
NASA NTRS1987

Low speed wind tunnel test of a propulsive wing/canard concept in the STOL configuration. Volume 2: Test data

A propulsive wind/canard model was tested at STOL operating conditions in the NASA Langley Research Center 4 x 7 meter wind tunnel. Longitudinal and lateral/directional aerodynamic characteristics were measured for various flap deflections, angles of attack and sideslip, and blowing coefficients. Testing was conducted for several model heights to determine ground proximity effects on the aerodynamic characteristics. Flow field surveys of local flow angles and velocities were performed behind both the canard and the wing. This is volume 2 of a 2 volume report. All of the test data in three appendices are presented. Appendix A presented tabulated six component force and moment data, Appendix B presents tabulated wing pressure coefficients, and Appendix C presents the flow field data.

Stewart, V. R.↗