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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Model America - data and models of every U.S. building

The 5-year goal of the 'Model America' concept was to generate a model of every building in the United States. This data repository delivers on that goal. Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (bit.ly/AutoBEM). There were 125,714,640 buildings detected in the United States and this dataset contains 122,930,327 (97.8%) buildings which resulted in a successful simulation. Future, annual updates have been proposed that may include additional buildings, data improvements, or other algorithmic enhancements. This dataset of 122.9 million buildings includes: Models (state_county.zip) - OpenStudio (v3.1.0) and EnergyPlus (v9.4) building energy models. Please note that the download requires the free Globus Connect Personal (https://www.globus.org/globus-connect-personal); Each model has approximately 3,000 building input descriptors that can be extracted. Please see the EnergyPlus(v9.4) 2,784-page Input/Output Reference Guide (https://energyplus.net/sites/all/modules/custom/nrel_custom/pdfs/pdfs_v9.4.0/InputOutputReference.pdf) for everything that can be retrieved or simulated from these models. These models were derived from the following metadata, which is not included in this dataset: 1. ID - unique building ID 2. County - county name 3. State - state name 4. CZ - ASHRAE Climate Zone designation 5. Clim_Zone - text label of climate zone 6. est_year - estimated year of construction 7. est_commercial - estimated building type (0=residential, 1=commercial) 8. Centroid - building center location in latitude/longitude (from Footprint2D) 9. Footprint2D - building polygon of 2D footprint (lat1/lon1_lat2/lon2_...) 10. Height - building height (meters) 11. Area2D - footprint area (ft2) 12. BuildingType - DOE prototype building designation (IECC=residential) as implemented by OpenStudio-standards 13. WWR_surfaces - percent of each facade (pair of points from Footprint2D) covered by fenestration/windows (average 14.5% for residential, 40% for commercial buildings) 14. NumFloors - number of floors (above-grade) 15. Area - estimate of total conditioned floor area (ft2) 16. Standard - building vintage. These models are made free and openly available in hopes of stimulating any simulation-informed use case. Data is provided as-is with no warranties, express or implied, regarding fitness for a particular purpose. We wish to thank our sponsors which include Oak Ridge National Laboratory (ORNL) Laboratory Directed Research and Development (LDRD), U.S. Dept. of Energy's (DOE) Building Technologies Office (BTO), Office of Electricity (OE), Biological and Environmental Research (BER), and National Nuclear Security Administration (NNSA). This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357. Please cite as: New, Joshua R., Adams, Mark, Bass, Brett, Berres, Anne, and Clinton, Nicholas (2021). 'Model America - data and models of every U.S. building. [Data set].' Constellation, doi.ccs.ornl.gov/ui/doi/339, April 14, 2021

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

A COMPARISON OF NEAR-INFRARED PHOTOMETRY AND SPECTRA FOR Y DWARFS WITH A NEW GENERATION OF COOL CLOUDY MODELS

We present YJHK photometry, or a subset, for the six Y dwarfs discovered in Wide-field Infrared Survey Explorer (WISE) data by Cushing et al. The data were obtained using the Near-Infrared Imager on the Gemini North telescope; YJHK were obtained for WISEP J041022.71+150248.5, WISEP J173835.52+273258.9, and WISEPC J205628.90+145953.3; YJH for WISEPC J140518.40+553421.5 and WISEP J154151.65225025.2; and YJK for WISEP J182831.08+265037.8. We also present a far-red spectrum obtained using GMOS-North for WISEPC J205628.90+145953.3. We compare the data to Morley et al. models, which include cloud decks of sulfide and chloride condensates. We find that the models with these previously neglected clouds can reproduce the energy distributions of T9 to Y0 dwarfs quite well, other than near 5 {mu}m where the models are too bright. This is thought to be because the models do not include departures from chemical equilibrium caused by vertical mixing, which would enhance the abundance of CO and CO{sub 2}, decreasing the flux at 5 {mu}m. Vertical mixing also decreases the abundance of NH{sub 3}, which would otherwise have strong absorption features at 1.03 {mu}m and 1.52 {mu}m that are not seen in the Y0 WISEPC J205628.90+145953.3. We find that the five Y0 to Y0.5 dwarfs have 300 {approx}< T {sub eff} K {approx}< 450, 4.0 {approx}< log g {approx}< 4.5, and f {sub sed} Almost-Equal-To 3. These temperatures and gravities imply a mass range of 5-15 M {sub Jupiter} and ages around 5 Gyr. We suggest that WISEP J182831.08+265037.8 is a binary system, as this better explains its luminosity and color. We find that the data can be made consistent with observed trends, and generally consistent with the models, if the system is composed of a T {sub eff} Almost-Equal-To 325 K and log g {approx}< 4.5 primary, and a T {sub eff} Almost-Equal-To 300 K and log g {approx}> 4.0 secondary, corresponding to masses of 10 and 7 M {sub Jupiter} and an age around 2 Gyr. If our deconvolution is correct, then the T {sub eff} Almost-Equal-To 300 K cloud-free model fluxes at K and W2 are too faint by 0.5-1.0 mag. We will address this discrepancy in our next generation of models, which will incorporate water clouds and mixing.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Search for vectorlike leptons in multilepton final states in proton-proton collisions at s = 13 TeV

A search for vector-like leptons in multilepton final states is presented. The data sample corresponds to an integrated luminosity of 77.4 fb$^{-1}$ of proton-proton collisions at a center-of-mass energy of 13 TeV collected by the CMS experiment at the LHC in 2016 and 2017. Events are categorized by the multiplicity of electrons, muons, and hadronically decaying $\tau$ leptons. The missing transverse momentum and the scalar sum of the lepton transverse momenta are used to distinguish the signal from background. The observed results are consistent with the expectations from the standard model hypothesis. The existence of a vector-like lepton doublet, coupling to the third generation standard model leptons in the mass range of 120-790 GeV, is excluded at 95% confidence level. These are the most stringent limits yet on the production of a vector-like lepton doublet, coupling to the third generation standard model leptons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Test methodology for validation of multi-frequency models of renewable energy generators using small-signal perturbations

Providing trustworthy and accurate multi-frequency (or harmonic) models for renewable energy generators (REG) is an ongoing challenge for harmonic studies. There have been effective attempts to propose and design a test device to validate the harmonic models, mainly based on shunt current perturbations. However, using additional devices for perturbations is costly for converter-based test sites. This paper provides the test specifications to extend the application of the grid emulators for voltage perturbations and appropriate harmonic model validation. Besides, the effects of the sequence couplings, initial emissions, and power set-points on the test results have been overlooked in the literature. Considering these effects, this paper proposes a generic test methodology to obtain more accurate models in the sequence domain. The experimental verification of the proposed methodology is demonstrated using a 7 MVA grid emulator for testing of a 2 MVA photo-voltaic converter and a 2 MVA Type 3 wind turbine. This way, the test challenges, specifications, and recommendations are presented using the MW-scale experiments on different REGs. Furthermore, the effects of sequence couplings and initial emissions on the calculation results are investigated and compared. The proposed methodology is applicable for harmonic model validation as well as empirical modelling.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Simulation for Wind Turbine Generators: With FAST and MATLAB-Simulink Modules

This report presents the work done to develop generator and gearbox models in the Matrix Laboratory (MATLAB) environment and couple them to the National Renewable Energy Laboratory's Fatigue, Aerodynamics, Structures, and Turbulence (FAST) program. The goal of this project was to interface the superior aerodynamic and mechanical models of FAST to the excellent electrical generator models found in various Simulink libraries and applications. The scope was limited to Type 1, Type 2, and Type 3 generators and fairly basic gear-train models. Future work will include models of Type 4 generators and more-advanced gear-train models with increased degrees of freedom. As described in this study, implementation of the developed drivetrain model enables the software tool to be used in many ways. Several case studies are presented as examples of the many types of studies that can be performed using this tool.

17 WIND ENERGY↗
DOE OSTI2021

Advanced Performance Metrics and their Application to the Sensitivity Analysis for Model Validation and Calibration

High-quality generator dynamic models are critical to reliable and accurate power systems studies and planning. With the availability of PMUs, measurement-based approach for model validation has gained significant prominence. In this approach, the quality of a model is analyzed by visually comparing measured generator response with the model-based simulated response for large system disturbances. This paper proposes a new set of performance metrics to assess the model validation results to facilitate automation of the model validation process. In the proposed methodology, first, the slow governor response and comparatively faster oscillatory response are separated, and then a separate set of performance metrics is calculated for each of these two components. These proposed metrics quantify the mismatch between the actual and model-based response in a comprehensive manner without missing any information enabling automation of the process. Furthermore, in this paper, we are also proposing that the sensitivity analysis for model calibration be performed with respect to the proposed metrics for the systematic identification of key parameters. In this work, results obtained using both simulated and real-world case-studies validate the effectiveness of the proposed performance metrics for model validation and their application to the sensitivity analysis for model calibration.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Assessing the nature of large language models: A caution against anthropocentrism.

Generative AI models garnered a large amount of public attention and speculation with the release of OpenAI’s chatbot, ChatGPT in November of 2022. At least two opinion camps exist – one that is excited about the possibilities these models offer for fundamental changes to human tasks, and another that is highly concerned about the power these models seem to have – especially since the release of GPT-4, which was trained on multimodal data and has ~1.7 trillion (T) parameters. We evaluated some concerns regarding these models’ power by assessing GPT-3.5 using standard, normed, and validated cognitive and personality measures. These measures come from the tradition of psychometrics in experimental psychology and have a long history of providing valuable insights and predictive distinctions in humans. For this seedling project, we developed a battery of tests that allowed us to estimate the boundaries of some of these models’ capabilities, how stable those capabilities are over a short period of time, and how they compare to humans.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Assessing the nature of large language models: A caution against anthropocentrism

Generative AI models garnered a large amount of public attention and speculation with the release of OpenAI’s chatbot, ChatGPT in November of 2022. At least two opinion camps exist – one that is excited about the possibilities these models offer for fundamental changes to human tasks, and another that is highly concerned about the power these models seem to have – especially since the release of GPT-4, which was trained on multimodal data and has ~1.7 trillion (T) parameters. We evaluated some concerns regarding these models’ power by assessing GPT 3.5 using standard, normed, and validated cognitive and personality measures. These measures come from the tradition of psychometrics in experimental psychology and have a long history of providing valuable insights and predictive distinctions in humans. For this seedling project, we developed a battery of tests that allowed us to estimate the boundaries of some of these models’ capabilities, how stable those capabilities are over a short period of time, and how they compare to humans.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

WE-D-303-02: Applications of Volumetric Images Generated with a Respiratory Motion Model Based On An External Surrogate Signal

Purpose: Respiratory motion can vary significantly over the course of simulation and treatment. Our goal is to use volumetric images generated with a respiratory motion model to improve the definition of the internal target volume (ITV) and the estimate of delivered dose. Methods: Ten irregular patient breathing patterns spanning 35 seconds each were incorporated into a digital phantom. Ten images over the first five seconds of breathing were used to emulate a 4DCT scan, build the ITV, and generate a patient-specific respiratory motion model which correlated the measured trajectories of markers placed on the patients’ chests with the motion of the internal anatomy. This model was used to generate volumetric images over the subsequent thirty seconds of breathing. The increase in the ITV taking into account the full 35 seconds of breathing was assessed with ground-truth and model-generated images. For one patient, a treatment plan based on the initial ITV was created and the delivered dose was estimated using images from the first five seconds as well as ground-truth and model-generated images from the next 30 seconds. Results: The increase in the ITV ranged from 0.2 cc to 6.9 cc for the ten patients based on ground-truth information. The model predicted this increase in the ITV with an average error of 0.8 cc. The delivered dose to the tumor (D95) changed significantly from 57 Gy to 41 Gy when estimated using 5 seconds and 30 seconds, respectively. The model captured this effect, giving an estimated D95 of 44 Gy. Conclusion: A respiratory motion model generating volumetric images of the internal patient anatomy could be useful in estimating the increase in the ITV due to irregular breathing during simulation and in assessing delivered dose during treatment. This project was supported, in part, through a Master Research Agreement with Varian Medical Systems, Inc. and Radiological Society of North America Research Scholar Grant #RSCH1206.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Investigating Short Circuit Models for Wind Turbine Generators

Short circuit study needs to be performed at the planning stage before connecting large gen erators with the electric grid. This study will reveal the impact of new generation on the fault levels of the grid. The fault levels will determine the rating of nearby equipment and setting of relays. However, a short circuit model of the new generation is required for this study. This report investigates and quantifies the short circuit models of different wind turbine generators (WTGs) and of wind farms, and using these models, explores the effects of the wind farms on the nearby switchgear. WTGs, commonly classified as Type 1, Type 2, Type 3, and Type 4, exhibit different short circuit behavior depending upon their architecture and controls. The short circuit model (synonymous to Thevenin model) of Type 1 WTG is well known; it comprises of a voltage source behind a transient reactance, X'. The transient reactance X' is derived using the reactance of stator, rotor and the magnetizing reactance. In case of Type 2 WTG, an external rotor resistance is used to increase the range of operating slips. The value of the external rotor resistance increases at higher operating slips. The effect of the external rotor resistance on the fault current response is analyzed by simulating a validated model of Type 2 WTG. The validation is performed using the field data from an actual 67-machine Type 2 wind farm located in Wyoming, USA. The results shows that the external rotor resistance should be considered in its Thevenin impedance for better accuracy. A wind farm contains a large number of WTGs, pad mounted transformers, and cables typically connected in a ‘daisy chain” configuration. The effect of these cable impedances on the short circuit model of Type 2 wind farm is examined using the validated models. It is found that the collector circuit cables inside the farm do not have a significant effect on the short circuit model of the farm. Based on this finding, a simple equivalencing procedure for the wind farm is proposed and validated. Faults inside and outside the wind farm are analyzed and recommendations to select main circuit breakers and generator circuit breakers are made. Type 3 WTG, also known as Doubly Fed Asynchronous Generator (DFAG), uses back to back converters in the rotor circuit to inject slip frequency voltage into the rotor circuit. Until recently, these machines used crowbar to short the rotor circuit during faults to protect the converter com ponents form high rotor currents resulting from faults. This type of WTG is simulated and the model is validated using field data from a 66-machine Type 3 wind farm in Wyoming, USA. The simulation study reveals that the crowbar feature is activated almost immediately after the fault takes place, and remains activated throughout the fault-period. This confirms that the short circuit model for Type 3 WTG with crowbar is similar to the model for Type 2 WTG. In the past, wind farms were allowed to disconnect during faults. However, recent grid codes around the world and in the United States demand that the wind farms be kept connected to the grid during faults, and provide certain reactive power quantified based on the voltage dip at the point of interconnection. This requirement, also called low voltage ride through (LVRT), can be accomplished by using Type 4 WTGs that employ full back to back converter interface between generators (permanent magnet synchronous generators are typically used) and the grid. However, the controls are proprietary, and hence the short circuit models are not well defined. This report proposes controls that enable the WTG to comply with the strictest grid codes, and based on this model, proposes a short circuit model of the Type 4 WTG. This model is not validated due to lack of validation data, but the use of grid code requirements as control objectives lends good credibility to the model. PSCAD/EMTDC ® , a powerful and time-tested time-domain simulation software is used to implement all models. This software is capable of modeling in detail all components of wind farms, and all components and controls of converters in time domain.

17 WIND ENERGY↗
DOE OSTI2024

A Spectacular Viscoelastic Model Calibration for 828/D230/Alox Generated from Legacy Sandia Data

The nonlinear viscoelastic Spectacular model is calibrated to the thermo-mechanical behavior of 828/D230/Alox with an alox volume fraction of 20 %. Legacy experimental data from Sandia’s polymer properties database (PPD) is used to calibrate the model. Based on known densities of the epoxy 828/D230 and the alox filler, the alox volume fractions listed on the PPD were likely reported incorrectly. The alox volume fractions are recalculated here. Using the recalculated alox volume fractions, the PPD contains experimental data for 828/D230/Alox with alox volume fractions of 16 %, 24 %, and 33 %, so the thermo-mechanical behavior at 20 % alox volume fraction is estimated by interpolating between the bounding cases of of 16 % and 24 %. Because the Spectacularmodel can be fairly challenging to calibrate, the calibration procedure is described in detail. Several of the calibration steps involve inverse parameter identification, where an experiment is simulated and parameters are iteratively updated until the model response matches the experimental data. As the PPD does not fully describe all experimental procedures, the experimental simulations use assumed thermal and mechanical loading rates that are typical for the viscoelastic characterization of epoxies. Spectacular uses four independent relaxation functions related to volumetric (ƒ 1 ), shear (ƒ 2 ), thermal strain (ƒ 3 ), and thermal relaxations (ƒ 4 ). The previous SPEC model form, also known as the universal_polymer model, uses two independent relaxation functions related to volumetric and thermal relaxation (ƒ ν = ƒ 1 = ƒ 3 = ƒ 4 ) and shear relaxation (ƒ s = ƒ 2 ). The two constitutive choices are briefly evaluated here, where it is found that the four relaxation function approach of Spectacular was better suited for fitting the coefficient of thermal expansion during both heating and cooling.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Influence of Vegetation Canopy Architecture on Dynamics of Spatiotemporal Light Distribution and its Effect on Land-Biosphere-Atmosphere Fluxes of Energy, Carbon, and Water

The dynamic spatiotemporal distribution of light and micro climatic variables (wind speed, atmospheric CO 2 concentration, humidity, pressure, and air temperature) within the plant canopy as determined by the canopy architecture play a critical role in land-biosphere-atmosphere (LBA) photosynthetic carbon uptake, transpiratory water loss and energy partitioning. Vegetation models that include effects of sun and shade flecks, leaf temperature and energy balance partitioning between sensible and latent heat fluxes, and reduced turbulent mixing in dense vegetation canopies can accurately predict canopy performance, particularly its shaded leaves, which can constitute 80% of leaf area and contribute up to 50% of carbon update and 65% of water loss. However, current vegetation models with their bulk characterization of shaded leaves poorly represent the complex three dimensional (3D) canopy architecture are insufficient to capture the spatiotemporal dynamics of shaded leaves. Here, we propose to employ an x-ray computed tomography (XCT) imaging technique in combination with an automated, high throughput, image processing pipeline (3DArch, to be developed) to obtain an explicit 3D triangulated surface mesh of a plant canopy (Fig 1). 3DArch would provide a much needed technological jump in 3D LBA modeling where computer generated artificial 3D models suffer from lack of high resolution detailed canopy architecture parameters. The 3D canopy surface mesh output from 3DArch is coupled with an explicit 3D forward ray tracing model (fastTracer) to obtain a high resolution representation of the dynamic spatiotemporal light environment within the canopy over the course of a day (Fig 1). The results from the light attenuation model are then coupled with a process based multi-scale bio-physical canopy and leaf model of photosynthesis (PlantGro) to get fluxes of carbon, water and energy at the leaf and canopy scale, in addition to estimating whole plant carbon uptake, and water loss. Our proposed model framework would be the first of its kind to provide a breakthrough capability in the field of process-based plant modeling that bridges the key technological gap in shaded leaf modeling through explicit representation of 3D canopy architecture. Computer generated artificial 3D model canopy simulations on grasses show that the canopy light distribution does not follow an exponential behavior as assumed in most 1D vegetation models, but rather exhibits a heterogeneous behavior, with a small but significant portion of interior canopy leaves experiencing peak light levels due to sun flecks while the rest of the canopy receives substantially lower light levels. These results indicate a bias in traditional models that overestimates shaded leaf contribution towards whole canopy photosynthesis by up to 15% and underestimate transpiration by up to 12% with an associated increase in sensible heat fluxes since photosynthesis, transpiration and energy partitioning are tightly coupled processes. However, these test results need to be validated using the 3D architecture obtained from a real plant imaged in 3D using 3DArch, rather than an artificial model plant. Our proposed model framework would allow us to identify inefficiencies in canopy light distribution and prescribe optimal canopy architectures (leaf optical properties, leaf area, leaf angles, row spacing, planting density, etc.) to traditional and genetic engineering based crop breeders, for maximizing target functions such as light use efficiency, water use efficiency, drought tolerance, crop yield, crop resilience etc., with important applications in biofuel crops such as sorghum, and switchgrass. Our model can also be applied for designing optimal canopy architecture that increase surface albedo as a mitigation strategy for global warming and projections of crop yield for future food and water security under climate change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Structural features of ISG borosilicate nuclear waste glasses revealed from high-energy X-ray diffraction and molecular dynamics simulations

Vitrification is a widely accepted method to immobilize nuclear waste. Detailed structural information is critical to understand the physical and chemical behaviors, including the long-term chemical durability of these glasses that are to be stored in geological storage sites. High-energy X-ray diffraction studies are used to obtain accurate structural information of the International Simple Glass (ISG), a six-component borosilicate model nuclear waste glass with a composition (mol%) of 60.2SiO 2 -16.0B 2 O 3 -12.6Na 2 O-3.8Al 2 O 3 -5.7CaO-1.7ZrO 2 . Classical molecular dynamics (MD) simulations with recently developed effective potentials are utilized to generate structural models of the ISG glasses to provide interpretation of the high-energy X-ray structural data and additional short and medium range structural details. The atomic structure model generated from MD simulations shows an excellent agreement with high-energy X-ray diffraction, measured for the first time for ISG, with an R x value of 5.5%. Systematic investigations of the medium-range structural features of ISG are performed, built upon recent study of the short-range structure. In particular, the glass former cation oxygen polyhedral analysis show that [SiO 4 ]-[SiO 4 ] and [BO 4 ]-[SiO 4 ] connections are the most abundant while [ZrO 6 ] octohedra having higher probability to connect to another [SiO 4 ], [BO 4 ] and [BO 3 ]. Moreover, we have studied the ISG surface structure using MD simulations. Noticeable differences in terms of both chemical compositions and structural features between the bulk and surface are observed. There exist increased small-sized rings, under coordinated Si species, high 3-coordinated boron content (86.5%) on the surface. Very importantly, sodium ions are found to be enriched on the glass surface, consistent with recent experimental results. Furthermore, both bulk and surface structural information are discussed in terms of the dissolution and corrosion mechanisms of ISG and related nuclear waste glasses.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Generation of Data-Driven Expected Energy Models for Photovoltaic Systems

Although unique expected energy models can be generated for a given photovoltaic (PV) site, a standardized model is also needed to facilitate performance comparisons across fleets. Current standardized expected energy models for PV work well with sparse data, but they have demonstrated significant over-estimations, which impacts accurate diagnoses of field operations and maintenance issues. This research addresses this issue by using machine learning to develop a data-driven expected energy model that can more accurately generate inferences for energy production of PV systems. Irradiance and system capacity information was used from 172 sites across the United States to train a series of models using Lasso linear regression. The trained models generally perform better than the commonly used expected energy model from international standard (IEC 61724-1), with the two highest performing models ranging in model complexity from a third-order polynomial with 10 parameters (Radj2 = 0.994) to a simpler, second-order polynomial with 4 parameters (Radj2=0.993), the latter of which is subject to further evaluation. Subsequently, the trained models provide a more robust basis for identifying potential energy anomalies for operations and maintenance activities as well as informing planning-related financial assessments. We conclude with directions for future research, such as using splines to improve model continuity and better capture systems with low (≤1000 kW DC) capacity.

14 SOLAR ENERGY↗