Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Topic 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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Calculating Nozzle Side Loads using Acceleration Measurements of Test-Based Models

As part of a NASA/MSFC research program to evaluate the effect of different nozzle contours on the well-known but poorly characterized "side load" phenomena, we attempt to back out the net force on a sub-scale nozzle during cold-flow testing using acceleration measurements. Because modeling the test facility dynamics is problematic, new techniques for creating a "pseudo-model" of the facility and nozzle directly from modal test results are applied. Extensive verification procedures were undertaken, resulting in a loading scale factor necessary for agreement between test and model based frequency response functions. Side loads are then obtained by applying a wide-band random load onto the system model, obtaining nozzle response PSD's, and iterating both the amplitude and frequency of the input until a good comparison of the response with the measured response PSD for a specific time point is obtained. The final calculated loading can be used to compare different nozzle profiles for assessment during rocket engine nozzle development and as a basis for accurate design of the nozzle and engine structure to withstand these loads. The techniques applied within this procedure have extensive applicability to timely and accurate characterization of all test fixtures used for modal test.A viewgraph presentation on a model-test based pseudo-model used to calculate side loads on rocket engine nozzles is included. The topics include: 1) Side Loads in Rocket Nozzles; 2) Present Side Loads Research at NASA/MSFC; 3) Structural Dynamic Model Generation; 4) Pseudo-Model Generation; 5) Implementation; 6) Calibration of Pseudo-Model Response; 7) Pseudo-Model Response Verification; 8) Inverse Force Determination; 9) Results; and 10) Recent Work.

Brown, Andrew M.↗
DOE OSTI2024

Multi-scale modeling of fuel fragmentation and microstructural evolution

An overview of NEAMS program activities to model fuel fragmentation and microstructual evolution to a group of industry attendees at a meeting hosted by EPRI. Topics include atomistic methods to determine grain boundary strength, phase-field fracture modeling to determine critical pressure at grain boundaries, and coupled phase-field-cluster dynamics to model microstructural evolution.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1996

An MHD Study of the Interaction Between the Solar Wind and the Interstellar Medium

The overall objective of this research program is to obtain a better understanding of the interaction between the solar wind and the interstellar medium through the use of numerical solutions of the time-dependent magnetohydrodynamic (MHD) equations. The simulated results have been compared with observations where possible and with the results from previous analytic and numerical studies. The primary accomplishment of this project has been the development of codes for 2-D models in both spherical and cylindrical coordinates and the application of the codes to the solar wind/interstellar medium interaction. Computations have been carried out for both a relatively simple gas-dynamic interaction and a flow-aligned interstellar magnetic field. The results have been shown to compare favorably with models that use more approximations and to modify and extend the previous results as would be expected. The simulations have also been used along with a data analysis study to provide a quantitative estimate of the distance to the termination and bow shocks. Some of the specific topics that have been studied are: (1) gas dynamic models of the solar wind/interstellar medium interaction, (2) termination shock response to large-scale solar wind fluctuations, and (3) distances to the termination shock and heliopause. The main results from each of these studies are summarized. The results were published in three papers which are included as attachments.

Steinolfson, R. S.↗
NASA NTRS2000

Research on the F/A-18E/F Using a 22%-Dynamically-Scaled Drop Model

Research on the F/A-18E/F configuration was conducted using a 22%-dynamically-scaled drop model to study flight dynamics in the subsonic regime. Several topics were investigated including longitudinal response, departure/spin resistance, developed spins and recoveries, and the failing leaf mode. Comparisons to full-scale flight test results were made and show the drop model strongly correlates to the airplane even under very dynamic conditions. The capability to use the drop model to expand on the information gained from full-scale flight testing is also discussed. Finally, a preliminary analysis of an unusual inclined spinning motion, dubbed the "cartwheel", is presented here for the first time.

Croom, M.↗
DOE OSTI2019

A nonlinear data-driven reduced order model for computational homogenization with physics/pattern-guided sampling

Developing an accurate nonlinear reduced order model from simulation data has been an outstanding research topic for many years. For many physical systems, data collection is very expensive and the optimal data distribution is not known in advance. Thus, maximizing the information gain remains a grand challenge. In a recent paper, Bhattacharjee and Matouš (2016) proposed a manifold-based nonlinear reduced order model for multiscale problems in mechanics of materials. Expanding this work here, we develop a novel sampling strategy based on the physics/pattern-guided data distribution. Our adaptive sampling strategy relies on enrichment of sub-manifolds based on the principal stretches and rotational sensitivity analysis. This novel sampling strategy substantially decreases the number of snapshots needed for accurate reduced order model construction (i.e., ~5 x reduction of snapshots over Bhattacharjee and Matouš (2016)). Moreover, we build the nonlinear manifold using the displacement rather than deformation gradient data. We provide rigorous verification and error assessment. We demonstrate both localization and homogenization of the multiscale solution on a large particulate composite unit cell.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Monodisperse Single-Material Granular Tribocharging Modeling and Experimental Validation

Charge transfer between insulating grains has been a topic of interest for many years as this phenomenon is extremely important to many areas in industry. Of particular interest to NASA is the behavior of electrically insulative dust grains such as those found on the lunar surface. Whether poured from a scoop during sample collection activities, agitated inside a drum via mining robots, or fluidized by a gas plume, particle-particle interactions between similar granular materials will be widespread on the Moon. Designers hope to have a predictive model for how dust grains are charged, transported, and deposited on flight systems to better understand issues electrostatics may cause in future missions. While difference in work function is often seen as a driver for charge transfer between two materials, this is an incomplete representation for insulative particles. Other asymmetries in the system can also lead to charge being transferred: one such being the difference between static vs dynamic particles. Experiments performed under vacuum in the Electrostatics and Surface Physics Laboratory (ESPL) clearly show that particles having more contacts with other particles tend to charge positively and particles having fewer contacts tend to charge negatively, despite being made from the same material. During these experiments, monodisperse (population of single diameter) spherical particles were held in a reservoir which was then elevated at one end to slope into a Faraday cup used to measure bulk charge of the grains. Care was taken to limit the number of spheres bouncing out of the cup, to isolate the beads from the container itself so that only grain-to-grain interactions occurred, and to assure neutrality of the beads before the experiment began. A discrete element method (DEM) modeling package already incorporating many granular mechanics interactions was augmented to include the electrostatic behaviors seen in experiments. The model can reproduce the experimental results above by tracking the number of contacts between pairs of individual grains and applying a charge transfer condition related to this contact parameter. The experimental results as well as their incorporation into the improved modeling suite will be discussed. Future work includes adding additional asymmetries into the experiments/model such as polydisperse populations of spherical particles and irregularly shaped grains.

granular↗
NASA NTRSDate not supplied

Monodisperse Single-Material Granular Tribocharging Modeling and Experimental Validation

Charge transfer between insulating grains has been a topic of interest for many years as this phenomenon is extremely important to many areas in industry. Of particular interest to NASA is the behavior of electrically insulative dust grains such as those found on the lunar surface. Whether poured from a scoop during sample collection activities, agitated inside a drum via mining robots, or fluidized by a gas plume, particle-particle interactions between similar granular materials will be widespread on the Moon. Designers hope to have a predictive model for how dust grains are charged, transported, and deposited on flight systems to better understand issues electrostatics may cause in future missions. While difference in work function is often seen as a driver for charge transfer between two materials, this is an incomplete representation for insulative particles. Other asymmetries in the system can also lead to charge being transferred: one such being the difference between static vs dynamic particles. Experiments performed under vacuum in the Electrostatics and Surface Physics Laboratory (ESPL) clearly show that particles having more contacts with other particles tend to charge positively and particles having fewer contacts tend to charge negatively, despite being made from the same material. During these experiments, monodisperse (population of single diameter) spherical particles were held in a reservoir which was then elevated at one end to slope into a Faraday cup used to measure bulk charge of the grains. Care was taken to limit the number of spheres bouncing out of the cup, to isolate the beads from the container itself so that only grain-to-grain interactions occurred, and to assure neutrality of the beads before the experiment began. A discrete element method (DEM) modeling package already incorporating many granular mechanics interactions was augmented to include the electrostatic behaviors seen in experiments. The model can reproduce the experimental results above by tracking the number of contacts between pairs of individual grains and applying a charge transfer condition related to this contact parameter. The experimental results as well as their incorporation into the improved modeling suite will be discussed. Future work includes adding additional asymmetries into the experiments/model such as polydisperse populations of spherical particles and irregularly shaped grains.

electrostatics↗
DOE OSTI2023

Tree architecture: A strigolactone-deficient mutant reveals a connection between branching order and auxin gradient along the tree stem

Due to their long lifespan, trees and bushes develop higher order of branches in a perennial manner. In contrast to a tall tree, with a clearly defined main stem and branching order, a bush is shorter and has a less apparent main stem and branching pattern. To address the developmental basis of these two forms, we studied several naturally occurring architectural variants in silver birch (Betula pendula). Using a candidate gene approach, we identified a bushy kanttarelli variant with a loss-of-function mutation in the BpMAX1 gene required for strigolactone (SL) biosynthesis. While kanttarelli is shorter than the wild type (WT), it has the same number of primary branches, whereas the number of secondary branches is increased, contributing to its bush-like phenotype. To confirm that the identified mutation was responsible for the phenotype, we phenocopied kanttarelli in transgenic BpMAX1::RNAi birch lines. SL profiling confirmed that both kanttarelli and the transgenic lines produced very limited amounts of SL. Interestingly, the auxin (IAA) distribution along the main stem differed between WT and BpMAX1::RNAi. In the WT, the auxin concentration formed a gradient, being higher in the uppermost internodes and decreasing toward the basal part of the stem, whereas in the transgenic line, this gradient was not observed. Through modeling, we showed that the different IAA distribution patterns may result from the difference in the number of higher-order branches and plant height. Future studies will determine whether the IAA gradient itself regulates aspects of plant architecture.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

CMIP7 data request: Earth system priorities and opportunities

This paper presents a comprehensive overview of the Coupled Model Intercomparison Project Phase 7 (CMIP7) request for data pertaining to Earth systems science, and provides justification for the resources needed to produce this data. Topics within the CMIP7 Earth System (CMIP7-ES) theme centre around tracking of flows of energy, carbon, water and other fluxes across domains, and constraining feedbacks between these cycles and the climate system. These topics are summarized in this paper as scientific “opportunities” describing specific model intercomparison experiments and use cases for next-generation Earth System Model (ESM) output. These opportunities were submitted by modelling groups and scientific consortia following an extended public consultation process. Contained within each opportunity are requests for groups of Climate & Forecasting (CF) variables, which are bundled into variable groups representing all data required to address the opportunities' needs. Novel opportunities in CMIP7 compared with previous phases will include running `emissions-driven' simulations that integrate carbon emissions and removal scenarios with updated representations of the global carbon cycle, expanded variable groups needed to model marine trophic interactions and biogeochemistry, and data needed to understand the risk of global tipping points, among others. The production of these variables will close key gaps and uncertainties identified during previous rounds of CMIP, and support the 7th Intergovernmental Panel on Climate Change Assessment Report (AR7). We argue that CMIP7-ES data will be broadly used by scientific, policy, governmental, industry, and other communities that rely on climate model projections for research and decision making. As an author group we also reflect on the evolution of the CMIP7-ES data request as a part of a deliberative process in support of the global CMIP program.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1987

Aircraft interior noise reduction by alternate resonance tuning

Model problem development and analysis continues with the Alternate Resonance Tuning concept. Various topics are presently at different stages of completion and are described. These topics included optimization of panel mass ratios, panel computer code verification and agreement with experimental data, and flexible frame modeling.

Gottwald, James A.↗
NASA NTRS1990

Helicopter aeroelastic stability and response - Current topics and future trends

This paper presents several current topics in rotary wing aeroelasticity and concludes by attempting to anticipate future trends and developments. These topics are: (1) the role of geometric nonlinearities; (2) structural modeling, and aeroelastic analysis of composite rotor blades; (3) aeroelastic stability and response in forward flight; (4) modeling of coupled rotor/fuselage aeromechanical problems and their active control; and (5) the coupled rotor-fuselage vibration problem and its alleviation by higher harmonic control. Selected results illustrating the fundamental aspects of these topics are presented. Future developments are briefly discussed.

Friedmann, Peretz P.↗
DOE OSTI2025

Second-generation downscaled earth system model data using generative machine learning

The second-generation Sup3rCC dataset provides high-resolution meteorological data generated through the downscaling of multiple earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). This downscaling is performed through application of a generative machine learning approach called Super-Resolution for Renewable Resource Data (sup3r). This dataset builds on the first-generation Sup3rCC data by applying improved bias correction methods and adding downscaled precipitation to the output variables. As with the first Sup3rCC version, the data still include temperature, wind speed and direction at multiple heights, pressure, three components of downwelling solar radiation, and relative humidity—all at 4-kilometer (km) hourly resolution over the contiguous United States. This is a 25x spatial enhancement and 24x temporal enhancement of the source 100-km daily-average ESM data. This extension of the Sup3rCC dataset includes data from six ESMs from two shared socioeconomic pathways (SSPs) totaling 400 years of data with multiple future projections of changing meteorological conditions. The scenario selection was based on a structured evaluation of historical ESM skill and comprehensive representation of possible trajectories of future climate change in temperature, humidity, precipitation, solar irradiance, and near-surface wind speeds. The inclusion of multiple future projections is intended to enable users to assess key drivers of un 36 certainty and variability. All data are double-bias corrected, resulting in a product that can be used out-of-the-box for energy system analysis with minimal historical bias. The potential applications of Sup3rCC data extend to various topics in renewable energy resource assessment, energy systems modeling, and grid resilience studies. High-resolution future meteorological projections are critical for evaluating the effects of changing meteorological conditions on renewable energy generation, energy demand, and for optimizing energy storage and grid infrastructure. The 4-km hourly resolution of the downscaled data enables understanding of spatial and temporal variability at the scales necessary for energy system operational planning. In addition, the dataset can support risk assessments by providing detailed information on possible future extreme weather events and long-term meteorological variability at scales relevant to energy infrastructure. By offering an enhanced representation of possible future meteorological conditions, the second-generation Sup3rCC dataset enables more precise modeling of energy resilience and adaptation strategies in response to changing meteorological conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Forecasting influenza-like illness dynamics for military populations using neural networks and social media

This work is the first to take advantage of recurrent neural networks to predict influenza-like-illness (ILI) dynamics from various linguistic signals extracted from social media data. Unlike other approaches that rely on timeseries analysis of historical ILI data [1, 2] and the state-of-the-art machine learning models [3, 4], we build and evaluate the predictive power of Long Short Term Memory (LSTMs) architectures capable of nowcasting (predicting in \real-time") and forecasting (predicting the future) ILI dynamics in the 2011 { 2014 influenza seasons. To build our models we integrate information people post in social media e.g., topics, stylistic and syntactic patterns, emotions and opinions, and communication behavior. We then quantitatively evaluate the predictive power of different social media signals and contrast the performance of the-state-of-the-art regression models with neural networks. Finally, we combine ILI and social media signals to build joint neural network models for ILI dynamics prediction. Unlike the majority of the existing work, we specifically focus on developing models for local rather than national ILI surveillance [1], specifically for military rather than general populations [3] in 26 U.S. and six international locations. Our approach demonstrates several advantages: (a) Neural network models learned from social media data yield the best performance compared to previously used regression models. (b) Previously under-explored language and communication behavior features are more predictive of ILI dynamics than syntactic and stylistic signals expressed in social media. (c) Neural network models learned exclusively from social media signals yield comparable or better performance to the models learned from ILI historical data, thus, signals from social media can be potentially used to accurately forecast ILI dynamics for the regions where ILI historical data is not available. (d) Neural network models learned from combined ILI and social media signals significantly outperform models that rely solely on ILI historical data, which adds to a great potential of alternative public sources for ILI dynamics prediction. (e) Location-specific models outperform previously used location-independent models e.g., U.S. only. (f) Prediction results significantly vary across geolocations depending on the amount of social media data available and ILI activity patterns.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Competition between inside-out unfolding and pathogenic aggregation in an amyloid-forming β-propeller

Studies of folded-to-misfolded transitions using model protein systems reveal a range of unfolding needed for exposure of amyloid-prone regions for subsequent fibrillization. Here, we probe the relationship between unfolding and aggregation for glaucoma-associated myocilin. Mutations within the olfactomedin domain of myocilin (OLF) cause a gain-of-function, namely cytotoxic intracellular aggregation, which hastens disease progression. Aggregation by wild-type OLF (OLF WT ) competes with its chemical unfolding, but only below the threshold where OLF loses tertiary structure. Representative moderate (OLF D380A ) and severe (OLF I499F ) disease variants aggregate differently, with rates comparable to OLF WT in initial stages of unfolding, and variants adopt distinct partially folded structures seen along the OLF WT urea-unfolding pathway. Whether initiated with mutation or chemical perturbation, unfolding propagates outward to the propeller surface. In sum, for this large protein prone to amyloid formation, the requirement for a conformational change to promote amyloid fibrillization leads to direct competition between unfolding and aggregation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Understanding Bifacial PV Modeling: Raytracing and View Factor Models

As part of the PV Magazine Webinar 'View-factor vs. ray tracing - which bifacial modelling techniques should you use?,' the second part lead by NREL will explore the different rear-irradiance calculation software, which fall into two categories: view-factor and ray-tracing models. View factor models assume isotropic scattering of reflected rays, allowing for calculation of irradiance by integration. Due-diligence software such as PVSyst or SAM use the view-factor model. Ray-tracing models simulate multipath reflection and absorption of individual rays entering a scene. Raytracing software such as bifacial_radiance, which is the only available open-source toolkit, offers the possibility of reproducing complex scenes, including shading or finite-system edge effects. This can be useful to evaluate specific system geometries, shading and obstructions, areas of different albedo and electrical mismatch, all topics of interest to the prediction of bifacial performance. Model agreement for view factors and bifacial_radiance software is improving and has been shown to be between 2% (absolute) when compared with measured results.

14 SOLAR ENERGY↗
DOE OSTI2019

Modeling fuel assembly distortion in light water reactors using BISON

Individual fuel rods in a light water reactor fuel assembly (FA) often have different power profiles that result in a spatial temperature gradient in the FA. This temperature gradient causes some rods to elongate more than others which could in turn distort the entire FA. Such FA distortion has been known to cause operational difficulties with refueling and with the insertion of control rods [1]. Numerical modeling of FA distortion due to differential elongation of fuel rods requires: (i) modeling the thermal elongation as well as the creep and irradiation induced elongation of the fuel rods, and (ii) modeling the bending response of the FA due to the differential elongation of the fuel rods. Past studies on this topic have been focused on the mechanical deformation of the FA with simplistic modeling of fuel rod elongation. In this paper, a simulation approach is presented that directly couples 2D axisymmetric fuel performance models of the individual fuel rods in a FA with structural beam models of the fuel rods in a FA using the Bison code [2]. This allows all of the mechanisms internal to the fuel rod leading to cladding elongation to be accounted for in the FA distortion model. To demonstrate this capability, the bowing of a simplified and idealized 6x6 FA (Fig. 1a), modeled using beam elements, is analyzed under different spatially varying power profiles. For this study, the guide tubes are rigidly connected to the spacer grid. Also, the fuel rods are rigidly connected to the spacer grid in all directions except the vertical direction (Y) along which slipping can occur between the fuel rods and spacer grids, depending on the friction coefficient between them. Coupling the thermo-mechanical response of individual fuel rods to the global mechanical behavior of the FA can shed light on the mechanisms that cause distortion of the FA and potential solutions to address this issue.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Outage Forecast-Based Preventative Scheduling Model for Distribution System Resilience Enhancement

Distribution system resilience enhancement is an important topic to ensure customers have access to power supply during extreme events. In fact, certain weather-related extreme events can be predicted ahead of time. Therefore, it is important to investigate how to predict grid outages using extreme weather forecasts, and how outage predictions can be incorporated into distribution system resilience enhancement. In this paper, a preventative scheduling model for distribution systems is proposed. The model targets at allocating resources, especially mobile responsive resources such as mobile backup generators and mobile energy storage systems, to prepare for an extreme event in the day-ahead context. To achieve efficient resource allocation and scheduling, a machine learning-based outage prediction module is developed to predict vulnerable or risky segments of the distribution system based on historical operating records and extreme weather event forecast. By integrating the outage prediction results into the scheduling model, optimal resource allocation can be derived to help distribution systems prepare for an upcoming event and improve resilience performance. A real distribution feeder in North Carolina, U.S. is used in the case study to validate the proposed approach.

distributed energy resources↗
NASA NTRS1988

Modeling magnetospheric plasma; Proceedings of the First Huntsville Workshop on Magnetosphere/Ionosphere Plasma Models, Guntersville, AL, Oct. 14-16, 1987

The conference presents papers on the global modeling of magnetospheric plasma processes, the modeling of the midlatitude ionosphere and plasmasphere, the modeling of the auroral zone and boundary layer, the modeling of the polar magnetosphere and ionosphere, and the modeling of the plasma sheet and ring current. Particular attention is given to the kinetic approach in magnetospheric plasma transport modeling, self-consistent neutral point current and fields from single particle dynamics, preliminary statistical survey of plasmaspheric ion properties from observations by DE 1/RIMS, and a model of auroral potential structures based on dynamics explorer plasma data. Other topics include internal shear layers in auroral dynamics, quantitative parameterization of energetic ionospheric ion outflow, and open flux merging in an expanding polarcap model.

Moore, T. E.↗