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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

GradeIT (Road Grade Inference Tool)

The National Renewable Energy Laboratory (NREL) has developed the Road Grade Inference Tool, "GradeIT". This tool is a modular Python package the leverages the United States Geological Survey’s (USGS) 1/3 arc-second Digital Elevation Model (DEM), an open and free public dataset. Roadway gradient (slope) has a strong influence on vehicle energy consumption behavior and longitudinal dynamics. Therefore, any tools, models, or analyses that consider vehicle energy consumption or driving profiles is incomplete without accurate elevation and grade information. Despite the acute need for this data, it is rarely collected alongside GPS (latitude and longitude) data, and tools to post-process GPS data to append elevation and grade are difficult to come by. GradeIT satisfies this significant need in the research community. Utilization of the USGS DEM makes the underlying data available to any potential user and ensures continuous data anywhere in the continental United States. The USGS DEM is a great resource; however, in order to be useful for automotive and traffic engineering applications, significant interpolation and filtering is required to achieve an accurate representation of gradient on the roadway. GradeIT employs a two-dimensional interpolation to approximate elevation at a point on the road from the nearest nodes in the DEM. Then, GradeIT applies multiple filtering techniques to smooth the elevation profile to a realistic road topology. Finally, road grade is derived from the elevation profile and returned as the primary output.

Holden, Jacob↗
DOE OSTI2016

A Public-Private-Acadmic Partnership to Advance Solar Power Forecasting

The National Center for Atmospheric Research (NCAR) is pleased to have led a partnership to advance the state-of-the-science of solar power forecasting by designing, developing, building, deploying, testing, and assessing the SunCast™ Solar Power Forecasting System. The project has included cutting edge research, testing in several geographically- and climatologically-diverse high penetration solar utilities and Independent System Operators (ISOs), and wide dissemination of the research results to raise the bar on solar power forecasting technology. The partners include three other national laboratories, six universities, and industry partners. This public-private-academic team has worked in concert to perform use-inspired research to advance solar power forecasting through cutting-edge research to advance both the necessary forecasting technologies and the metrics for evaluating them. The project has culminated in a year-long, full-scale demonstration of provide irradiance and power forecasts to utilities and ISOs to use in their operations. The project focused on providing elements of a value chain, beginning with the weather that causes a deviation from clear sky irradiance and progresses through monitoring and observations, modeling, forecasting, dissemination and communication of the forecasts, interpretation of the forecast, and through decision-making, which produces outcomes that have an economic value. The system has been evaluated using metrics developed specifically for this project, which has provided rich information on model and system performance. Research was accomplished on the very short range (0-6 hours) Nowcasting system as well as on the longer term (6-72 hour) forecasting system. The shortest range forecasts are based on observations in the field. The shortest range system, built by Brookhaven National Laboratory (BNL) and based on Total Sky Imagers (TSIs) is TSICast, which operates on the shortest time scale with a latency of only a few minutes and forecasts that currently go out to about 15 min. This project has facilitated research in improving the hardware and software so that the new high definition cameras deployed at multiple nearby locations allow discernment of the clouds at varying levels and advection according to the winds observed at those levels. Improvements over “smart persistence” are about 29% for even these very short forecasts. StatCast is based on pyranometer data measured at the site as well as concurrent meteorological observations and forecasts. StatCast is based on regime-dependent artificial intelligence forecasting techniques and has been shown to improve on “smart persistence” forecasts by 15-50%. A second category of short-range forecasting systems employ satellite imagery and use that information to discern clouds and their motion, allowing them to project the clouds, and the resulting blockage of irradiance, in time. CIRACast (the system produced by the Cooperative Institute for Atmospheric Research [CIRA] at Colorado State University) was already one of the more advanced cloud motion systems, which is the reason that team was brought to this project. During the project timeframe, the CIRA team was able to advance cloud shadowing, parallax removal, and implementation of better advecting winds at different altitudes. CIRACast shows generally a 25-40% improvement over Smart Persistence between sunrise and approximately 1600 UTC (Coordinated Universal Time) . A second satellite-based system, MADCast (Multi-sensor Advective Diffusive foreCast system), assimilates data from multiple satellite imagers and profilers to assimilate a fully three-dimensional picture of the cloud into the dynamic core of WRF. During 2015, MADCast (provided at least 70% improvement over Smart Persistence, with most of that skill being derived during partly cloudy conditions. That allows advection of the clouds via the Weather Research and Forecasting (WRF) model dynamics directly. After WRF-Solar™ showed initial success, it was also deployed in nowcasting mode with coarser runs out to 6 hours made hourly. It provided improvements on the order of 50-60% over Smart Persistence for forecasts up to 1600 UTC. The advantages of WRF-Solar-Nowcasting and MADCast were then blended to develop the new MAD-WRF model that incorporates the most important features of each of those models, both assimilating satellite cloud fields and using WRF-So far physics to develop and dissipate clouds. MAE improvements for MAD-WRF for forecasts from 3-6 hours are improved over WRF-Solar-Now by 20%. While all the Nowcasting system components by themselves provide improvement over Smart Persistence, the largest benefit is derived when they are smartly blended together by the Nowcasting Integrator to produce an integrated forecast. The development of WRF-Solar™ under this project has provided the first numerical weather prediction (NWP) model specifically designed to meet the needs of irradiance forecasting. The first augmentation improved the solar tracking algorithm to account for deviations associated with the eccentricity of the Earth’s orbit and the obliquity of the Earth. Second, WRF-Solar™ added the direct normal irradiance (DNI) and diffuse (DIF) components from the radiation parameterization to the model output. Third, efficient parameterizations were implemented to either interpolate the irradiance in between calls to the expensive radiative transfer parameterization, or to use a fast radiative transfer code that avoids computing three-dimensional heating rates but provides the surface irradiance. Fourth, a new parameterization was developed to improve the representation of absorption and scattering of radiation by aerosols (aerosol direct effect). A fifth advance is that the aerosols now interact with the cloud microphysics, altering the cloud evolution and radiative properties, an effect that has been traditionally only implemented in atmospheric computationally costly chemistry models. A sixth development accounts for the feedbacks that sub-grid scale clouds produce in shortwave irradiance as implemented in a shallow cumulus parameterization Finally, WRF-Solar™ also allows assimilation of infrared irradiances from satellites to determine the three dimensional cloud field, allowing for an improved initialization of the cloud field that increases the performance of short-range forecasts. We find that WRF-Solar™ can improve clear sky irradiance prediction by 15-80% over a standard version of WRF, depending on location and cloud conditions. In a formal comparison to the NAM baseline, WRF-Solar™ showed improvements in the Day-Ahead forecast of 22-42%. The SunCast™ system requires substantial software engineering to blend all of the new model components as well as existing publically available NWP model runs. To do this we use an expert system for the Nowcasting blender and the Dynamic Integrated foreCast (DICast®) system for the NWP models. These two systems are then blended, we use an empirical power conversion method to convert the irradiance predictions to power, then apply an analog ensemble (AnEn) approach to further tune the forecast as well as to estimate its uncertainty. The AnEn module decreased RMSE (root mean squared error) by 17% over the blended SunCast™ power forecasts and provided skill in the probabilistic forecast with a Brier Skill Score of 0.55. In addition, we have also developed a Gridded Atmospheric Forecast System (GRAFS) in parallel, leveraging cost share funds. An economic evaluation based on Production Cost Modeling in the Public Service Company of Colorado showed that the observed 50% improvement in forecast accuracy will save their customers $819,200 with the projected MW deployment for 2024. Using econometrics, NCAR has scaled this savings to a national level and shown that an annual expected savings for this 50% forecast error reduction ranges from $11M in 2015 to $43M expected in 2040 with increased solar deployment. This amounts to a $455M discounted savings over the 26 year period of analysis.

14 SOLAR ENERGY↗
DOE OSTI2023

Spatially Adaptive Tunable Lighting Control System with Expanded Wellness and Energy Saving Benefits

Lighting design is becoming increasingly complex, including active dimming for energy savings and spectral tuning for human wellbeing. Modern commercial lighting control systems are already difficult to use, and maintain, and even with so-called Smart Lighting, optimizing light settings is rapidly exceeding the capabilities of direct human control, limiting the adoption of lighting control systems. The growing importance of Occupancy Centric Controls (OCC) for advanced building management systems can be applied to the development of autonomous lighting system controls needed to drive the adoption of advanced lighting controls for improved adaptive “sculpted illumination” for both greater energy savings and broader human wellbeing perspectives. This project, led by Rensselaer Polytechnic Institute, entitled “Spatially adaptive tunable lighting control system with expanded wellness and energy saving benefits” will develop and test an entirely new platform for automated optimized lighting design and control that requires little or no human engagement, yet contours lighting profiles automatically to minimize lighting energy use. We call this approach to lighting control “dynamic light sculpting” since the right amount of illumination is automatically delivered to occupants in real time. Since the system uses new, privacy-preserving occupant position and pose detection technologies developed by Rensselaer for broad OCC building applications, the control system will analyze how to deliver the right amount of the right type of illumination only where and when it is needed based these OCC platforms. To create these powerful autonomous lighting control platforms, the project will integrate evolving augmented reality (AR) and virtual reality (VR) tools with sophisticated lighting and interior design toolkits to create interactive lighting design and control simulators. Using the quickly growing paradigm of digital twins, these tools will integrate light fixture properties, occupancy sensor data, interior design data, and lighting specifications to accurately visualize how various design concepts interact with simulated yet realistic human activities that occur in commercial office buildings of various types. These advanced digital twin design and simulation tools will be combined with a new class of digitally-programmable LED lighting fixtures that can dynamically change the spectral content and direction of light emission. When fully integrated, the new autonomous lighting control system will take all of the guesswork out of optimizing light quality while minimizing energy consumption. Digital twin tools will simplify the design, installation, commissioning, operation, and maintenance of future energy-efficient lighting systems. It should be possible to reduce lighting energy costs from 40% to 70% with OCC based dynamic light sculpting systems. The work will be led by the Center for Lighting Enabled Systems and Applications (LESA) and the Center for Architectural Science and Ecology (CASE), both at Renssealer Polytechnic Institute; Lumileds, a global leader in the development of advanced LED systems; and HKS, a leading global architecture design firm. This interdisciplinary project team’s experience includes all of the design simulation tools, VR/AR digital twin visualization technology, advanced occupancy sensing technology, and complex control system design capabilities that will revolutionize lighting design and control technology to autonomously deliver high-quality lighting that improves human health and wellbeing while simultaneously maximizing lighting energy savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Numerical Investigation of a Small Low-Flow Marine Hydrokinetic (MHK) Turbine for Small Autonomous Unmanned Mobile Recharge Stations (CRADA Final Report)

This project will improve the hydrodynamic performance of the undershot waterwheel turbine with a flow concentrator designed by the Participant, using a computational fluid dynamics study. The influence of different result parameters including the number of blades, turbine profile, submerged depth, tip speed ratio, concentrator geometry and wave + current conditions will be assessed to maximize power performance and minimize structural loads.

16 TIDAL AND WAVE POWER↗
DOE OSTI2019

Entropy and Gravitation—From Black Hole Computers to Dark Energy and Dark Matter

We show that the concept of entropy and the dynamics of gravitation provide the linchpin in a unified scheme to understand the physics of black hole computers, spacetime foam, dark energy, dark matter and the phenomenon of turbulence. We use three different methods to estimate the foaminess of spacetime, which, in turn, provides a back-door way to derive the Bekenstein-Hawking formula for black hole entropy and the holographic principle. Generalizing the discussion for a static spacetime region to the cosmos, we find a component of dark energy (resembling an effective positive cosmological constant of the correct magnitude) in the current epoch of the universe. The conjunction of entropy and gravitation is shown to give rise to a phenomenological model of dark matter, revealing the natural emergence, in galactic and cluster dynamics, of a critical acceleration parameter related to the cosmological constant; the resulting mass profiles are consistent with observations. Unlike ordinary matter, the quanta of the dark sector are shown to obey infinite statistics. This property of dark matter may lead to some non-particle phenomenology and may explain why dark matter particles have not been detected in dark matter search experiments. We also show that there are deep similarities between the problem of “quantum gravity” (more specifically, the holographic spacetime foam) and turbulence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Infall/expansion velocities in the low-mass dense cores L492, L694-2, and L1521F: dependence on position and molecular tracer

Although surveys of infall motions in dense cores have been carried out for years, few surveys have focused on mapping infall across cores using multiple spectral-line observations. To fill this gap, we present IRAM 30 m telescope maps of N{sub 2}H{sup +}(1–0), DCO{sup +}(2–1), DCO{sup +}(3–2), and HCO{sup +}(3–2) emission toward two prestellar cores (L492 and L694-2) and one protostellar core (L1521F). We find that the measured infall velocity varies with position across each core and choice of molecular line, likely as a result of radial variations in core chemistry and dynamics. Line-of-sight infall speeds estimated from DCO{sup +}(2–1) line profiles can decrease by 40–50 m s{sup −1} when observing at a radial offset ⩾0.04 pc from the core's dust continuum emission peak. Median infall speeds calculated from all observed positions across a core can also vary by as much as 65 m s{sup −1}, depending on the transition. These results show that while single-pointing, single-transition surveys of core infall velocities may be good indicators of whether a core is either contracting or expanding, the magnitude of the velocities they measure are significantly impacted by the choice of molecular line, proximity to the core center, and core evolutionary state.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Observational evidence of dynamic star formation rate in Milky Way giant molecular clouds

Star formation on galactic scales is known to be a slow process, but whether it is slow on smaller scales is uncertain. We cross-correlate 5469 giant molecular clouds (GMCs) from a new all-sky catalog with 256 star-forming complexes (SFCs) to build a sample of 191 SFC-GMC complexes—collections of multiple clouds each matched to 191 SFCs. The total mass in stars harbored by these clouds is inferred from WMAP free–free fluxes. We measure the GMC mass, the virial parameter, the star formation efficiency ϵ and the star formation rate per freefall time ϵ {sub ff}. Both ϵ and ϵ {sub ff} range over 3–4 orders of magnitude. We find that 68.3% of the clouds fall within σ{sub logϵ}=0.79±0.22 dex and σ{sub logϵ{sub f{sub f}}}=0.91±0.22 dex about the median. Compared to these observed scatters, a simple model with a time-independent ϵ {sub ff} that depends on the host GMC properties predicts σ{sub logϵ{sub f{sub f}}}=0.12--0.24. Allowing for a time-variable ϵ {sub ff}, we can recover the large dispersion in the rate of star formation. This strongly suggests that star formation in the Milky Way is a dynamic process on GMC scales. We also show that the surface star formation rate profile of the Milky Way correlates well with the molecular gas surface density profile.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Gravitational Waves from Merging Intermediate-mass Black Holes. II. Event Rates at Ground-based Detectors

Based on a dynamical formation model of a supermassive black hole (SMBH), we estimate the expected observational profile of gravitational waves at ground-based detectors, such as KAGRA or advanced LIGO/VIRGO. Noting that the second generation of detectors have enough sensitivity from 10 Hz and up (especially with KAGRA owing to its location at less seismic noise), we are able to detect the ring-down gravitational wave of a BH with mass M<2×10{sup 3}M{sub ⊙}. This enables us to check the sequence of BH mergers to SMBHs via intermediate-mass BHs. We estimate the number density of galaxies from the halo formation model and estimate the number of BH mergers from the giant molecular cloud model assuming hierarchical growth of merged cores. At the designed KAGRA (and/or advanced LIGO/VIRGO), we find that the BH merger of its total mass M∼60M{sub ⊙} is at the peak of the expected mass distribution. With its signal-to-noise ratio ρ=10 (30), we estimate the event rate R∼200 (20) per year in the most optimistic case, and we also find that BH mergers in the range M<150M{sub ⊙} are R>1 per year for ρ=10. Thus, if we observe a BH with more than 100M{sub ⊙} in future gravitational-wave observations, our model naturally explains its source.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Imaging a Central Ionized Component, a Narrow Ring, and the CO Snowline in the Multigapped Disk of HD 169142

We report Very Large Array observations at 7 mm, 9 mm, and 3 cm toward the pre-transitional disk of the Herbig Ae star HD 169142. These observations have allowed us to study the millimeter emission of this disk with the highest angular resolution so far (0.″12 × 0.″09, or 14 au × 11 au, at 7 mm). Our 7 and 9 mm images show a narrow ring of emission at a radius of ∼25 au tracing the outer edge of the inner gap. This ring presents an asymmetric morphology that could be produced by dynamical interactions between the disk and forming planets. Additionally, the azimuthally averaged radial intensity profiles of the 7 and 9 mm images confirm the presence of the previously reported gap at ∼45 au and reveal a new gap at ∼85 au. We analyzed archival DCO{sup +}(3–2) and C{sup 18}O(2–1) ALMA observations, showing that the CO snowline is located very close to this third outer gap. This suggests that growth and accumulation of large dust grains close to the CO snowline could be the mechanism responsible for this proposed outer gap. Finally, a compact source of emission is detected at 7 mm, 9 mm, and 3 cm toward the center of the disk. Its flux density and spectral index indicate that it is dominated by free–free emission from ionized gas, which could be associated with the photoionization of the inner disk, an independent object, or an ionized jet.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Dynamical Constraints on the Dark Matter Distribution of the Sculptor Dwarf Spheroidal from Stellar Proper Motions

In this work, we compare the transverse velocity dispersions recently measured within the Sculptor dwarf spheroidal galaxy to the predictions of our previously published dynamical model. This was designed to fit the observed number count and velocity dispersion profiles of both metal-rich and metal-poor stars, both in cored and in cusped potentials. At the projected radius where the proper motions (PMs) were measured, this model (with no change in parameters) predicts transverse dispersions in the range of 6–9.5 km s -1 , with the tangential dispersion about 1 km s -1 larger than the (projected) radial dispersion. Both dispersions are predicted to be about 1 km s -1 larger for metal-poor than for metal-rich stars. At this projected radius, cored and cusped potentials predict almost identical transverse dispersions. The measured tangential dispersion (8.5 ± 3.2 km s -1 ) agrees remarkably well with these predictions, while the measured radial dispersion (11.5 ± 4.3 km s -1 ) differs only at about the 1σ level. Thus, the PM data are in excellent agreement with previous data, but do not help to distinguish between cored and cusped potentials. Lastly, this will require velocity dispersion data (either from PMs or from radial velocities) with uncertainties well below 1 km s -1 over a range of projected radii.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

The Relation between Galaxy ISM and Circumgalactic O vi Gas Kinematics Derived from Observations and ΛCDM Simulations

We introduce the first galaxy–O vi absorption kinematic study for 20 absorption systems (EW > 0.1 Å) associated with isolated galaxies (0.15 ≤ z ≤ 0.55) that have accurate redshifts and rotation curves obtained using Keck/ESI. Our sample is split into two azimuthal angle bins: major axis (Φ < 25°) and minor axis (Φ > 33°). O vi absorption along the galaxy major axis is not correlated with galaxy rotation kinematics, with only 1/10 of systems that could be explained with rotation/accretion models. This is in contrast to corotation commonly observed for Mg ii absorption. O vi along the minor axis could be modeled by accelerating outflows, but only for small opening angles, while the majority of the O vi is decelerating. Along both axes, stacked O vi profiles reside at the galaxy systemic velocity with the absorption kinematics spanning the entire dynamical range of their galaxies. The O vi found in AMR cosmological simulations exists within filaments and in halos of ~50 kpc surrounding galaxies. Simulations show that major-axis O vi gas inflows along filaments and decelerates as it approaches the galaxy, while increasing in its level of corotation. Minor-axis outflows in the simulations are effective within 50–75 kpc; beyond that they decelerate and fall back onto the galaxy. While the simulations show clear O vi kinematic signatures, they are not directly comparable to observations. When we compare kinematic signatures integrated through the entire simulated galaxy halo, we find that these signatures are washed out owing to full velocity distribution of O vi throughout the halo. We illustrate that O vi alone does not serve as a useful kinematic indicator of gas accretion, outflows, or star formation and likely best probes the halo virial temperature.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series: Supporting Data

This dataset consists of soil temperature time series that were used to estimate soil thermal diffusivity and its uncertainty trough the probabilistic modelling approach developed and presented in the article named "Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series" and published in Earth Surface Dynamics. There are two compressed (.zip) files that contains synthetic (Synthetic_soiltemp_Teller.zip) and field (Field_soiltemp_Teller.zip) data. There is one MATLAB file that requires MATLAB to execute but any text editor can open it. The Synthetic_soiltemp_Teller.zip file includes 5 comma-delimited data files (.csv) each of which contains soil temperature time series generated through forward modeling (i.e., heat-conduction process in a heterogeneous medium using an explicit finite difference method) to mimic various types of temperature gradients, trend and fluctuations. These synthetic soil temperatures were used to investigate the impact of different environmental conditions on the uncertainty of thermal diffusivity estimates. The Field_soiltemp_Teller.zip file contains 28 comma-delimited data files (.csv) out of which (a) 27 files includes soil temperature time series recorded from 27 temperature probes located in a site along Teller Road about 40 km northwest of Nome, Alaska (64.72°N, 165.94°W), (b) one includes the name and coordinates of the 27 probes. These field soil temperatures were used to infer soil thermal diffusivity at numerous locations and depths in a discontinuous permafrost environment, and to evaluate the links between the estimated soil thermal diffusivity values and soil physical properties. The comma-delimited data files (.csv) of the synthetic and field soil temperature time series includes date and time (UTC) in the first column and soil temperature from 5 cm below the ground surface to 1.05 m depth (with 5 or 10 cm spacing between sensors) in the other columns. The measurements were acquired every 15 minutes. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Development of Multiresolution Capabilities for the Holistic Energy Resource Optimization Network (HERON) tool A progress update

INL researchers work on technoeconomic analyses for integrated energy systems (IES) using the Framework for Optimization of ResourCes and Economics (FORCE). Within FORCE, researchers use the Holistic Energy Resource Optimization Network (HERON) tool to conduct optimization of grid portfolios under uncertain market conditions. These optimizations determine optimal capacities for all IES components and strategies for resource dispatch which maximize some economic metric (e.g., net present value). Resource dispatch occurs on finer timescales (typically hours) and thus are asked to respond to a given time series (e.g. hourly load demand profiles for a grid, or pre-determined electricity prices). Volatile and complex bidding dynamics as well as poorly forecasted weather events within deregulated markets add uncertainty to the time series; FORCE can address this uncertainty by training a reduced order model on historical time series and generate unique synthetic time series which represent individual scenarios or realizations of the market. The IES configuration can be simulated under these different sampled realizations and a stochastic optimization is conducted which optimizes the expected value of the desired economic metric. The training of a synthetic time series generator is limited by the chosen time resolution; dynamics can occur on different time scales. Seasonal demand trends can dominate faster dynamical events (such as power outages from certain sectors or severe weather events) which might not get captured correctly by the trained model. In this report, we investigate different ways of addressing the training and generation of time series on multiple time scales using three main algorithms: wavelet decomposition, dynamic mode decomposition, and generative adversarial networks for time series. We demonstrate a time series analysis that yields information on not just the frequency space but also temporal space: where a fast Fourier transform can provide what frequencies dominate, the new algorithms can provide when the frequencies dominate as well. These analyses can help improve IES optimization by allowing researchers to couple simulations at different timescales when it is most needed - seasonal, day-ahead, and real time optimization - with greater computational efficiency. Future work will include implementation of a subset of the proposed algorithms into the FORCE toolset and application of these analyses into multiple timescale optimization.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

2D modeling of electromagnetic waves in cold plasmas

The consequences of sheath (rectified) electric fields, resulting from the different mobility of electrons and ions as a response to radio frequency (RF) fields, are a concern for RF antenna design as it can cause damage to antenna parts, limiters and other in-vessel components. As a first step to a more complete description, the usual cold plasma dielectric description has been adopted, and the density profile was assumed to be known as input. Ultimately, the relevant equations describing the wave-particle interaction both on the fast and slow timescale will need to be tackled but prior to doing so was felt as a necessity to get a feeling of the wave dynamics involved. Maxwell's equations are solved for a cold plasma in a 2D antenna box with strongly varying density profiles crossing also lower hybrid and ion-ion hybrid resonance layers. Numerical modelling quickly becomes demanding on computer power, since a fine grid spacing is required to capture the small wavelengths effects of strongly evanescent modes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Harnessing Ocean Thermal Gradients Using Thermoelectric Based Submersibles for Ocean Power Applications

The urgent need for energy solutions in marine environments has accelerated the development of innovative technologies capable of leveraging natural resources for power generation. This study introduces a buoyancy-driven submersible system designed to harness ocean thermal gradients using thermoelectric generators (TEGs) and phase change materials (PCMs). The technology aims to provide autonomous power to offshore aquaculture farms, unmanned underwater vehicles (UUVs), offshore platform illumination, and ocean sensors, significantly reducing dependence on fossil fuels. Ocean thermal gradients, especially prevalent in mid-latitude regions, exhibit temperature differences between surface and deep waters ranging from 7 degrees Celsius to 30 degrees Celsius depending on seasonal variations. The proposed submersible technology utilizes TEGs to convert thermal energy from these gradients into electrical power, generating between 0.2 and 0.5 watts, while PCMs are employed to store and regulate this energy, ensuring a stable and continuous power supply. The buoyancy-driven mechanism of the submersible enhances its capability to navigate through varying depths, optimizing its exposure to different thermal gradients and maximizing energy harvesting. The performance of this submersible system is analyzed through detailed thermodynamic assessments and computational fluid dynamics (CFD) modeling focused on heat transfer. These analyzes consider real-world ocean temperature profiles and seek to refine the interaction between TEGs and PCMs to optimize energy extraction. The evaluation encompasses several key performance metrics, including power output and energy efficiency. Results confirm the potential of this innovative technology to provide a continuous and reliable power source for marine applications. By demonstrating the feasibility of using ocean thermal gradients for energy generation, this study contributes to the broader efforts of innovation in energy technologies for harsh, remote marine environments. The implementation of such promises is significant advancements in the autonomy of marine operations. The ongoing research will further investigate scalability ensuring that the system can be effectively adapted to various marine settings and operational demands.

16 TIDAL AND WAVE POWER↗
DOE OSTI2017

Influence of chemistry, interfacial width, and non-isothermal conditions on spatially heterogeneous activated relaxation and elasticity in glass-forming free standing films

Here, we employ the Elastically Collective Nonlinear Langevin Equation (ECNLE) theory of activated relaxation to study several questions in free standing thin films of glass-forming molecular and polymer liquids. The influence of non-universal chemical aspects on dynamical confinement effects is found to be relatively weak, but with the caveat that for the systems examined, the bulk ECNLE polymer theory does not predict widely varying fragilities. Allowing the film model to have a realistic vapor interfacial width significantly enhances the reduction of the film-averaged glass transition temperature, T g , in a manner that depends on whether a dynamic or pseudo-thermodynamic averaging of the spatial mobility gradient is adopted. The nature of film thickness effects on the spatial profiles of the alpha relaxation time and elastic modulus is studied under non-isothermal conditions and contrasted with the corresponding isothermal behavior. Modest differences are found if a film-thickness dependent T g is defined in a dynamical manner. But, adopting a pseudo-thermodynamic measure of T g leads to a qualitatively new form of the alpha relaxation time gradient where highly mobile layers near the film surface coexist with strongly vitrified regions in the film interior. Consequently, the film-averaged shear modulus can increase with decreasing film thickness, despite the T g reduction and presence of a mobile surface layer. Such a behavior stands in qualitative contrast to the predicted mechanical softening under isothermal conditions. Spatial gradients of the elastic modulus are studied as a function of temperature, film thickness, probing frequency, and experimental protocol, and a rich behavior is found.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Integrated Framework of Vehicle Dynamics, Instabilities, Energy Models, and Sparse Flow Smoothing Controllers

This work presents an integrated framework of: vehicle dynamics models, with a particular attention to instabilities and traffic waves; vehicle energy models, with particular attention to accurate energy values for strongly unsteady driving profiles; and sparse Lagrangian controls via automated vehicles, with a focus on controls that can be executed via existing technology such as adaptive cruise control systems. This framework serves as a key building block in developing control strategies for human-in-the-loop traffic flow smoothing on real highways. In this contribution, we outline the fundamental merits of integrating vehicle dynamics and energy modeling into a single framework, and we demonstrate the energy impact of sparse flow smoothing controllers via simulation results.

Lee, Jonathan W.↗
DOE OSTI2016

Dynamics of intrinsic axial flows in unsheared, uniform magnetic fields

A simple model for the generation and amplification of intrinsic axial flow in a linear device, controlled shear decorrelation experiment, is proposed. This model proposes and builds upon a novel dynamical symmetry breaking mechanism, using a simple theory of drift wave turbulence in the presence of axial flow shear. This mechanism does not require complex magnetic field structure, such as shear, and thus is also applicable to intrinsic rotation generation in tokamaks at weak or zero magnetic shear, as well as to linear devices. This mechanism is essentially the self-amplification of the mean axial flow profile, i.e., a modulational instability. Hence, the flow development is a form of negative viscosity phenomenon. Unlike conventional mechanisms where the residual stress produces an intrinsic torque, in this dynamical symmetry breaking scheme, the residual stress induces a negative increment to the ambient turbulent viscosity. The axial flow shear is then amplified by this negative viscosity increment. The resulting mean axial flow profile is calculated and discussed by analogy with the problem of turbulent pipe flow. For tokamaks, the negative viscosity is not needed to generate intrinsic rotation. However, toroidal rotation profile gradient is enhanced by the negative increment in turbulent viscosity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗