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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Data Driven Model Development for the Supersonic Semispan Transport (S(sup 4)T)

We investigate two common approaches to model development for robust control synthesis in the aerospace community; namely, reduced order aeroservoelastic modelling based on structural finite-element and computational fluid dynamics based aerodynamic models and a data-driven system identification procedure. It is shown via analysis of experimental Super- Sonic SemiSpan Transport (S4T) wind-tunnel data using a system identification approach it is possible to estimate a model at a fixed Mach, which is parsimonious and robust across varying dynamic pressures.

Kukreja, Sunil L.↗
DOE OSTI2025

Enhancing Streamflow Reanalysis Across the Conterminous US Leveraging Multiple Gridded Precipitation Data Sets

Streamflow observations, essential for various water resource applications, are often unavailable at critical locations in need. Although different models have been proposed to enhance streamflow predictability at ungauged locations, the challenge extends beyond model fidelity. Differences in meteorologic forcing data sets, precipitation in particular, can significantly affect the accuracy of hydrologic predictions. This challenge intensifies across regions characterized by diverse hydro-climatological and geographical conditions, such as in the conterminous US (CONUS) where a single precipitation product struggles to consistently replicate observed hydrographs, particularly peak flow dynamics. To enhance streamflow predictions, we utilize a VIC-RAPID hydrologic modeling framework driven by multiple commonly used meteorological forcing data sets, such as Daymet, PRISM, ST4, AORC, and their hybrids and create multiple sets of 40-year (1980–2019) hourly, daily, and monthly streamflow reanalysis, Dayflow Version 2, for 2.7 million river reaches across the CONUS. Most forcings lead to skillful streamflow performance, except for ST4 in the mountainous west, where severe radar blockage adversely affects the accuracy. The evaluation using over 6,000 hourly stream gauges shows that hourly AORC and ST4 lead to improved annual peak flow performance over Daymet—driven streamflow (Dayflow V1), particularly in smaller basins, highlighting the value of high temporal resolution forcings in hydrologic predictions. Compared with other benchmark data sets like National Water Model V3.0, AORC-driven VIC-RAPID exhibits improved regional streamflow performance, with comparable peak flow representation. We envision that multi-forcing streamflow reanalysis data can inform regions in need of forcing data enhancement, diagnose hydrologic model performance, and benefit diverse water resource applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Model data for Flood Frequency Analysis using Stochastic Storm Transposition and an Integrated Surface-Subsurface Hydrological Model

This archived provides scripts and input files used for the implementation of a novel approach to conduct process-based Flood Frequency Analysis using a Stochastic Storm Transposition (SST) and an Integrated Surface-Subsurface Hydrological Model (ISSHM). As a proof-of-concept, this study uses the ISSHM, Advanced Terrestrial Simulator (Amanzi-ATS) model, and the SST model, RainyDay, to conduct flood frequency analysis by simulating the flood response to 5,000 annual synthetic storm events in a ~2000 km2 Southeast Texas watershed.The Watershed Workflow package is implemented in Python3. The Jupyter notebooks can be executed through multiple open-source tools, for example, Anaconda Jupyter Lab, VS Studio Code, etc. Other data files include TXT, CSV, DAT, SBATCH, SHP, TIF, NetCDF, and HDF5 files, which can be read through Python scripts. The input files for the ATS model and RainyDay model have .XML and .SST extensions, respectively, and can be edited in any commonly used text editors.This archive contains:* Scripts and data files essential for generating the ATS model input. It uses the Watershed Workflow package to produce both mesh and ATS input files. * Jupyter notebooks designated for the ATS model evaluation, covering both long-term simulations and 40 rainfall-runoff events.* Input files required to simulate SST storm events using RainyDay.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Energy Prediction under Changed Demand Conditions: Robust Machine Learning Models and Input Feature Combinations

Deciding on a suitable algorithm for energy demand prediction in a building is non-trivial and depends on the availability of data. In this paper we compare four machine learning models, commonly found in the literature, in terms of their generalization performance and in terms of how using different sets of input features affects accuracy. This is tested on a data set where consumption patterns differ significantly between training and evaluation because of the Covid-19 pandemic. We provide a hands-on guide and supply a Python framework for building operators to adapt and use in their applications.

Schranz, Thomas↗
NASA NTRS1976

Textural remanence - A new model of lunar rock magnetism

In reexamining the accumulated magnetic data on lunar rocks, several common patterns of magnetic behavior are recognized. Their joint occurrence strongly suggests a new model of lunar rock magnetism, which is based on partial preferred textural alignment of the spontaneous moments of magnetic grains without requiring the existence of ancient lunar magnetic fields. This magnetic fabric, mimetic to locally oriented petrofabric, gives rise to an apparent 'textural remanent magnetization'. In order to account for the observed intensity of 'stable remanence' in lunar rocks, only a minute fraction (0.001 to 0.00001) of the single-domain iron grains present need be preferentially aligned. Several mechanisms operating on the lunar surface, including shock and diurnal thermal cycling, appear adequate for producing the required type and degree of magnetic alignment in all lunar rock classes. The model is supported by a wide variety of direct and indirect evidence, and its predictions (e.g., regarding anisotropic susceptibility and remanence acquisition) can be experimentally tested.

Brecher, A.↗
NASA NTRS1977

A wind tunnel technique for determining stability derivatives from cable mounted aeroelastic models

System identification techniques in common use for extracting stability derivatives from flight test data have been adapted for application to data obtained from aeroelastically-scaled flutter models flown in a wind tunnel on a cable mount system. The concept has been applied with reasonable success to data from rigid models of a Space Shuttle Orbiter and a fighter tested in the NASA Langley transonic dynamics tunnel. Further application of this technique should permit extraction of derivatives that include scaled flexibility effects, thereby obtaining additional information from the testing of expensive flutter models.

Bennett, R. M.↗
DOE OSTI2021

Probabilistic Data Association for Orbital-Element Estimation Using Multistage Expectation–Maximization

Tracking space objects is important for managing space traffic and predicting collisions, but is difficult in part due to data association and orbit model uncertainty. Expectation–maximization (EM) is a commonly used tracking method that has not been widely considered for tracking space objects. The technique consists of iteratively computing data association probabilities with a set of current element estimates, and updating estimates of the elements by solving a nonlinear weighted least-squares regression problem where the weights are the data association probabilities. In this paper, we demonstrate the use of EM for probabilistic data association and orbital-element estimation by applying the technique to simulated data from two angles-only tracking scenarios. In both scenarios, EM provides correct data associations and accurate maximum likelihood estimates of orbital elements. One scenario considers tracking a single object in clutter and quantifies the improvement of the orbital-element estimates and data associations as the detection probability increases. However, standard application of EM requires knowing the number of objects or may fail when a large number of objects are present. To address these issues, this paper employs a multistage version of EM that is applicable when there are a large and possibly unknown number of objects.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Materials data science using CRADLE: A distributed, data-centric approach

Abstract There is a paradigm shift towards data-centric AI, where model efficacy relies on quality, unified data. The common research analytics and data lifecycle environment (CRADLE™) is an infrastructure and framework that supports a data-centric paradigm and materials data science at scale through heterogeneous data management, elastic scaling, and accessible interfaces. We demonstrate CRADLE’s capabilities through five materials science studies: phase identification in X-ray diffraction, defect segmentation in X-ray computed tomography, polymer crystallization analysis in atomic force microscopy, feature extraction from additive manufacturing, and geospatial data fusion. CRADLE catalyzes scalable, reproducible insights to transform how data is captured, stored, and analyzed. Graphical abstract

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Direct Numerical Simulation of Flow Over a Wall-Mounted Cube with the Nek5000 Spectral Element Code: DNS at Re h = 3900

The direct numerical simulation (DNS) of the canonical wall-mounted unit cube subjected to two distinct incident velocity profiles is performed at a Reynolds number where the bulk flow characteristics are known to become relatively Reynolds number insensitive. The aim of this work is to highlight the sensitivity of such bluff-body flows to mean shear and to provide a representative set of data for such flow scenarios where common turbulence modeling techniques often fail. Simple boundary conditions and a small domain are selected to allow for cost-effective and easy comparisons for model development purposes. In addition to mean velocity profiles, select turbulence statistics are presented in detail. Further, the basic efficacy of eddy viscosity models is evaluated and found to be adequate only for the shear stress components for the bluff-body flows examined here. Other failure mechanisms for RANS are proposed.

42 ENGINEERING↗
DOE OSTI2021

A computational study of turbulent separated flow over a wall-mounted cube at two different Reynolds numbers and incoming velocity profiles

Simulations of the canonical wall-mounted unit cube subjected to two distinct incident velocity profiles is performed at Reynolds numbers (Re) where the bulk flow characteristics are known to become relatively Re-insensitive using both direct numerical simulation (DNS) and wall-resolved large eddy simulation (WRLES). The aim of this work is to highlight the sensitivity of such bluff-body flows to mean shear and to provide a representative set of data for such flow scenarios where common turbulence modeling techniques often fail. Simple boundary conditions are selected to allow for easy comparisons for model development purposes and avoid confounding effects from freestream turbulence. In addition to mean velocity profiles, select turbulence statistics are presented in detail. We find that both mean velocity profiles and mean wake turbulence are Re-insensitive over the range examined here.

42 ENGINEERING↗
NASA NTRS1973

NASIS data base management system: IBM 360 TSS implementation. Volume 4: Program design specifications

The design specifications for the programs and modules within the NASA Aerospace Safety Information System (NASIS) are presented. The purpose of the design specifications is to standardize the preparation of the specifications and to guide the program design. Each major functional module within the system is a separate entity for documentation purposes. The design specifications contain a description of, and specifications for, all detail processing which occurs in the module. Sub-models, reference tables, and data sets which are common to several modules are documented separately.

Source record↗
NASA NTRS1988

Strategies for concurrent processing of complex algorithms in data driven architectures

The purpose is to document research to develop strategies for concurrent processing of complex algorithms in data driven architectures. The problem domain consists of decision-free algorithms having large-grained, computationally complex primitive operations. Such are often found in signal processing and control applications. The anticipated multiprocessor environment is a data flow architecture containing between two and twenty computing elements. Each computing element is a processor having local program memory, and which communicates with a common global data memory. A new graph theoretic model called ATAMM which establishes rules for relating a decomposed algorithm to its execution in a data flow architecture is presented. The ATAMM model is used to determine strategies to achieve optimum time performance and to develop a system diagnostic software tool. In addition, preliminary work on a new multiprocessor operating system based on the ATAMM specifications is described.

Stoughton, John W.↗
NASA NTRS2018

A Qualitative Study on the Effects of Mesh Guideline Modification for Unstructured Mesh Generation of the NASA High Lift Common Research Model (HL-CRM)

As part of the 1st Geometry and Mesh Generation Workshop, unstructured tetrahedral and unstructured hybrid Computational Fluid Dynamics meshes were generated according to the meshing guidelines supplied by the 3rd High Lift Prediction Workshop. During this process, it was noted that application of some meshing guidelines became a bottleneck in the process and negatively impacted the quality of the meshes. A study is performed to compare the FUN3D simulation from the baseline medium-resolution workshop unstructured mesh with those on meshes resulting from guideline variations to the baseline. Recommendations on the elimination or reduction of meshing guidelines for high lift aerodynamic cases like the High Lift Common Research Model are based on the resulting data.

Jones, William T.↗
NASA NTRS1999

Experimental and Analytical Study of Two-Phase Flow in Microgravity

A two-phase test loop has been designed and constructed to generate the necessary data for two-phase pressure drop and Critical Heat Flux (CHF) under reduced gravity conditions. A series of airplane trajectory tests aboard NASA KC-135 were performed and the data was used to evaluate the applicability of the earth gravity models for prediction of the reduced gravity data. Several commonly used correlations for the two-phase friction multiplier and critical heat flux were used to predict the data. It was generally concluded that the two-phase pressure drop can be predicted by the earth gravity correlations. The critical heat flux under reduced gravity conditions did not show a strong dependence on mass flow rate and the measured CHF were generally lower than the equivalent 1g conditions. The earth gravity models need to be modified for application to reduced gravities.

Abdollahian, D.↗
NASA NTRS1998

Design, Evaluation and GCM-Performance of a New Parameterization for Microphysics of Clouds with Relaxed Arakawa-Schubert Scheme (McRas)

A prognostic cloud scheme named McRAS (Microphysics of clouds with Relaxed Arakawa-Schubert Scheme) was developed with the aim of improving cloud-microphysics, and cloud-radiation interactions in GCMs. McRAS distinguishes convective, stratiform, and boundary-layer clouds. The convective clouds merge into stratiform clouds on an hourly time-scale, while the boundary-layer clouds do so instantly. The cloud condensate transforms into precipitation following the auto-conversion relations of Sundqvist that contain a parametric adaptation for the Bergeron-Findeisen process of ice crystal growth and collection of cloud condensate by precipitation. All clouds convect, advect, and diffuse both horizontally and vertically with a fully active cloud-microphysics throughout its life-cycle, while the optical properties of clouds are derived from the statistical distribution of hydrometeors and idealized cloud geometry. An evaluation of McRAS in a single column model (SCM) with the GATE Phase III data has shown that McRAS can simulate the observed temperature, humidity, and precipitation without discernible systematic errors. An evaluation with the ARM-CART SCM data in a cloud model intercomparison exercise shows reasonable but not an outstanding accurate simulation. Such a discrepancy is common to almost all models and is related, in part, to the input data quality. McRAS was implemented in the GEOS II GCM. A 50 month integration that was initialized with the ECMWF analysis of observations for January 1, 1987 and forced with the observed sea-surface temperatures and sea-ice distribution and vegetation properties (biomes, and soils), with prognostic soil moisture, snow-cover, and hydrology showed a very realistic simulation of cloud process, incloud water and ice, and cloud-radiative forcing (CRF). The simulated ITCZ showed a realistic time-mean structure and seasonal cycle, while the simulated CRF showed sensitivity to vertical distribution of cloud water which can be easily altered by the choice of time constant and incloud critical cloud water amount regulators for auto-conversion. The CRF and its feedbacks also have a profound effect on the ITCZ. Even though somewhat weaker than observed, the McRAS-GCM simulation produces robust 30-60 day oscillations in the 200 hPa velocity potential. Two ensembles of 4-summer (July, August, September) simulations, one each for 1987 and 1988 show that the McRAS-GCM simulates realistic and statistically significant precipitation differences over India, Central America, and tropical Africa. Several seasonal simulations were performed with McRAS-GEOS II GCM for the summer (June-July- August) and winter (December-January-February) periods to determine how the simulated clouds and CRFs would be affected by: i) advection of clouds; ii) cloud top entrainment instability, iii) cloud water inhomogeneity correction, and (iv) cloud production and dissipation in different cloud-processes. The results show that each of these processes contributes to the simulated cloud-fraction and CRF.

Sud, Y. C.↗
DOE OSTI2022

Improving Solar and Solar+Storage Screening Techniques to Reduce Utility Interconnection Time and Costs (Final Technical Report)

Residential PV installations have increased rapidly over the last decade, and the increased application volume has caused permitting delays and lower overall adoption rates. In this project, we developed and evaluated whether data-driven secondary modeling and screening techniques can help utilities assess customer applications more accurately than traditional screening shortcuts. Secondary topologies are predicted using decision trees and commonly available information, such as service transformer, customer, and street locations. Conductors were predicted using a logistic regression method based on real world object (RWO) types, service transformer ratings, conductor length, and distance to transformer. After developing the combined primary and secondary distribution network model, hosting capacity results were used to train a random forest model to predict the pass/fail likelihood of a customer application. Powerflow based models with predicted secondaries and data-driven methods both increased the screening success rate, relative to common utility heuristics, by as much as 55 percentage points. Data-driven screening techniques were described by one utility as a "right-sized" approach for residential customers given the low-risk of small errors and the high-cost of accurate modeling.

14 SOLAR ENERGY↗
NASA NTRS2014

The Parallel System for Integrating Impact Models and Sectors (pSIMS)

We present a framework for massively parallel climate impact simulations: the parallel System for Integrating Impact Models and Sectors (pSIMS). This framework comprises a) tools for ingesting and converting large amounts of data to a versatile datatype based on a common geospatial grid; b) tools for translating this datatype into custom formats for site-based models; c) a scalable parallel framework for performing large ensemble simulations, using any one of a number of different impacts models, on clusters, supercomputers, distributed grids, or clouds; d) tools and data standards for reformatting outputs to common datatypes for analysis and visualization; and e) methodologies for aggregating these datatypes to arbitrary spatial scales such as administrative and environmental demarcations. By automating many time-consuming and error-prone aspects of large-scale climate impacts studies, pSIMS accelerates computational research, encourages model intercomparison, and enhances reproducibility of simulation results. We present the pSIMS design and use example assessments to demonstrate its multi-model, multi-scale, and multi-sector versatility.

crop modeling↗
DOE OSTI2020

Chromatographic Modeling of 1-Foot Detritiation Test Column Results for the Optimization of Regeneration Time

This report documents the methods and results of a modeling study on a series of data generated by 1-foot test columns for the Water Detritiation project. In order to compliment modeling work already in progress on this project, a purely empirical curve-fitting approach is used in this study to determine chromatographic performance indicators such as retention time, curve width, and the number of chromatographic stages. The data used in this study comes from four sets of chromatographic test separations performed in March through May of 2017 using 1-foot columns. All are using the same flow rates and temperature (room temperature, nominally 25 C°). The first set of data (referred to in this report as the Column 1 data) is a series of twelve breakthrough curve measurements. Prior to each of these twelve runs, the column was regenerated by flowing hydrogen gas through the column, for increasing amounts of time, ranging from 2 hours to 25 hours. The second set of data (referred to as the Column 2 data) is comprised of five measurements of breakthrough curves measured in similar fashion as the Column 1 data, across a range of regeneration times from 2 to 21 hours. The third set of data (referred to as the Purge data) is of three breakthrough curves, measured after a regeneration time of 8 hours, which takes place after a nitrogen purge of 15, 30, or 45 minutes. The fourth data set is a series of five breakthrough curve measurements using a 2 nd batch of stationary phase, taken after regeneration times ranging from 2 to 20 hours. The overall modeling approach is as follows. First, the data is pre-processed for formatting, artifact removal, and is normalized. The data is then fit by integrated versions of four common chromatographic models. The best model is chosen based on the predictive performance of the model, and chromatographic performance values are calculated based on the best model’s fit parameters. Each of these processes are detailed below.

42 ENGINEERING↗