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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Optimal Efficiency and Operational Cost Savings: A Framework for Automated Rooftop PV Placement

Residential energy consumers are charged based on a utility rate structure, such as net metering or feed-in tariff. To lower consumers' electricity bills, expensive batteries are deployed to reduce the electricity fed from the grid during peak hours. However, strategic photovoltaic (PV) panel placement enables the reduction of operational energy cost while considering the spatial feasibility and efficiency for hosting rooftop PV. In this paper, we present a framework to automatically identify the optimal location of rooftop PV panels on residential buildings. Our framework integrates multiple workflows, including energy and environmental simulation, parametric modeling, and optimization to identify the ideal location of PV panels to balance the demand and supply at a building and community scale. These workflows are linked using the Grasshopper plug-in for Rhinoceros CAD software. The framework includes two different workflows, each satisfying a target for optimal PV placement: (a) maximizing PV panel efficiency, where users aim to maximize energy generation, and (b) minimizing operational energy cost, where "best'' panels are selected considering utility rates for operational energy cost. Our framework is demonstrated in a residential community in Fort Collins, Colorado, to generate the optimal PV placement for each of the two aforementioned targets. Results from the two workflows are compared to illustrate the effect of PV location and orientation on solar energy production efficiency and operational energy cost. The developed workflows are introduced as tools within the Grasshopper plug-in to investigate the solar potential of rooftop PV panels while taking into account factors such as contextual shading, utility rate structures, and buildings' energy demand profiles.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Introduction to ComStock

This presentation is an introduction to ComStock and the datasets it produces. The goal of this work is to help cities, states, utilities, and other stakeholders have information and resources needed to make informed decisions about their building stock.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

System and method for vehicle coast control

A method for controlling vehicle propulsion includes identifying at least one route characteristic of a portion of a route being traversed by a vehicle. The method further includes determining a profile for a target vehicle speed based on the at least one route characteristic and a vehicle energy consumption profile. The method further includes selectively adjusting a vehicle speed control input based on the target vehicle speed profile. The method further includes communicating the vehicle speed control input to a vehicle propulsion controller to achieve the target vehicle speed profile.

Aggoune, Karim↗
DOE OSTI2021

Field Performance of South-Facing and East-West Facing Bifacial Modules in the Arctic

This paper presents the first systematic comparison between south-facing monofacial and bifacial photovoltaic (PV) modules, as well as between south-facing bifacial and vertical east-west facing bifacial PV modules in Alaska. The state’s solar industry, driven by the high price of energy and dropping equipment costs, is quickly growing. The challenges posed by extreme sun angles in Alaska’s northern regions also present opportunities for unique system designs. Annual bifacial gains of 21% were observed between side by side south-facing monofacial and bifacial modules. Vertical east-west bifacial modules had virtually the same annual production as south-facing latitude tilt bifacial modules, but with different energy production profiles.

14 SOLAR ENERGY↗
NASA NTRS1988

Observations related to the acceleration, injection, and interplanetary propagation of energetic protons during the solar cosmic ray event on February 16, 1984

This paper presents an analysis of data collected by the worldwide network of neutron monitors and from IMP-8 cosmic-ray telescopes, as well as by particle detectors on the GOES 5 and 6 and ICE satellites, on the solar cosmic ray event that took place on February 16, 1984. Using these data, the intensity-time (IT) profiles, the anisotropy-time profiles, the energy spectra, and the pitch angle distributions of the solar protons near earth were deduced. It was found that the solar protons propagated essentially scatter-free from the sun to the earth. The solar protons had easy access to the IMF lines to earth; the time from the onset to maximum intensity and the shape of the IT profiles at earth as a function of energy could be explained by the diffusion of the flare protons near the acceleration region. The energy spectrum of the solar flare protons injected into the undisturbed IMF at the sun was changing with time in both amplitude and shape. The observations suggest a shock acceleration process.

Debrunner, H.↗
DOE OSTI2024

Large-scale simulation-based parametric analysis of an optimal precooling strategy for demand flexibility in a commercial office building

Achieving success with grid-interactive efficient buildings (GEBs) is closely tied to the utilization of flexible loads. A valuable strategy involves the implementation of precooling techniques before high-demand events, such as peak hours, by adjusting zone air temperature setpoints. This leads to a reduction in thermal loads and peak electricity demand during these times, as the building’s thermal mass stores and subsequently releases thermal energy. However, the effectiveness of the pre-cooling optimization is highly contingent on specific conditions such as building thermal properties, weather conditions, utility rate structure, HVAC equipment sizing, etc. Therefore, investigating the impacts of these condition-specific factors is crucial, especially when considering precooling strategies that utilize thermal mass in commercial buildings. In this paper, we first devised a novel heuristic control approach that incorporates parameterized optimal precooling thermostat schedules to enhance demand flexibility in a commercial office building. Subsequently, we conducted a thorough performance evaluation of this control strategy. Here, the optimal thermostat schedule was parameterized using three optimization variables: the precooling start time, the precooling end time, and the precooling temperature setpoint. Utilizing the DOE medium-sized office building as the virtual testbed, we showed that the parameterized schedule effectively approximates model predictive control and requires drastically reduced computational overhead. In addition, we investigated the impact of different influencing factors on the optimal precooling strategy. These factors include building thermal mass, outdoor air conditions, and energy price profiles. Using high-performance computing, we simulated a total of 225 scenarios, consisting of three levels of thermal mass, five typical outdoor air temperature profiles, and fifteen time-of-use price plans. The results demonstrate that optimal thermostat scheduling could save substantial energy cost in medium-sized office buildings with heavy thermal mass but with some energy penalty. Although the potential for cost savings is lower in buildings with low and medium thermal mass, the energy penalty remains consistent in all three thermal mass scenarios. The study also highlights the need to account for zone diversity and recognize that a one-size-fits-all-zone setpoint schedule may not be suitable for all zones and can lead to unnecessary energy wastage. Furthermore, the results highlight that while outdoor air conditions play a role in cost and energy performance, the cooling load exerts a more immediate and substantial influence on cost savings in precooling strategies. Although cost savings are comparable under certain conditions with the same cooling load, observed deviations in energy penalty indicate potential disparities in the efficiency of the HVAC system during the load-shifting process. In addition, the duration of peak pricing and the ratio between peak and off-peak times exhibit clear correlations with cost savings and energy consumption, aligning with intuitive expectations. These findings offer valuable insights for optimizing precooling strategies in office buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1986

Ion composition of the bulk ring current during a magnetic storm - Observations with the CHEM-instrument on AMPTE-CCE

Ion composition measurements in the entire energy range of the ring current population, obtained with the Charge-, Energy-, Mass-spectrometer instrument on the Charge Composition Explorer in September 1984, are reported. From the energy spectra obtained for all major constituents during the main phase of a magnetic storm, the number densities, energy densities, and mean energies are calculated and displayed as radial profiles. The mean energies of He(2+) are found to be about twice that of H(+) and He(+) throughout this storm, and the time profiles for the mean energies of all major ions are seen to bunch together (when normalizing mean energies by the ionic charge), with the largest variations of the energy densities and mean energies occurring for O(+) ions.

Stuedemann, W.↗
DOE OSTI2021

Direct Measurements of DT Fuel Preheat from Hot Electrons in Direct-Drive Inertial Confinement Fusion

Hot electrons generated by laser-plasma instabilities degrade the performance of laser-fusion implosions by preheating the DT fuel and reducing core compression. The hot-electron energy deposition in the DT fuel has been directly measured for the first time by comparing the hard x-ray signals between DT-layered and mass-equivalent ablator-only implosions. The electron energy deposition profile in the fuel is inferred through dedicated experiments using Cu-doped payloads of varying thickness. The measured preheat energy accurately explains the areal-density degradation observed in many OMEGA implosions. Furthermore, this technique can be used to assess the viability of the direct-drive approach to laser fusion with respect to the scaling of hot-electron preheat with laser energy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

End-Use Savings Shapes: Public Dataset Release for Residential Round 1 [Slides]

The End-Use Load Profiles project created a public database of 900,000 individual building end-use load profiles. Load profiles were modeled to represent the U.S. building stock as it was in 2018, as nearly as possible based on the best available data. The End-Use Savings Shapes follow-on project adds measure impact profiles for energy efficiency and electrification packages to the public dataset. This presentation details the public dataset release on September 20, 2022.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Direct Measurements of DT Fuel Preheat from Hot Electrons in Direct-Drive Inertial Confinement Fusion

Hot electrons generated by laser-plasma instabilities degrade the performance of laser-fusion implosions by preheating the DT fuel and reducing core compression. The hot-electron energy deposition in the DT fuel has been directly measured for the first time by comparing the hard x-ray signals between DT-layered and mass-equivalent ablator-only implosions. The electron energy deposition profile in the fuel is inferred through dedicated experiments using Cu-doped payloads of varying thickness. The measured preheat energy accurately explains the areal-density degradation observed in many OMEGA implosions. This technique can be used to assess the viability of the direct-drive approach to laser fusion with respect to the scaling of hot-electron preheat with laser energy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1996

Efficient Low-Speed Flight in a Wind Field

A new software tool was needed for flight planning of a high altitude, low speed unmanned aerial vehicle which would be flying in winds close to the actual airspeed of the vehicle. An energy modeled NLP (non-linear programming) formulation was used to obtain results for a variety of missions and wind profiles. The energy constraint derived included terms due to the wind field and the performance index was a weighted combination of the amount of fuel used and the final time. With no emphasis on time and with no winds the vehicle was found to fly at maximum lift to drag velocity, V(sub md). When flying in tail winds the velocity was less than V(sub md), while flying in head winds the velocity was higher than V(sub md). A family of solutions was found with varying times of flight and varying fuel amounts consumed which will aid the operator in choosing a flight plan depending on a desired landing time. At certain parts of the flight, the turning terms in the energy constraint equation were found to be significant. An analysis of a simpler vertical plane cruise optimal control problem was used to explain some of the characteristics of the vertical plane NLP results.

Feldman, Michael A.↗
NASA NTRS2019

Evaluation of Full Reynolds Stress Turbulence Models in FUN3D for Axisymmetric Jet Flow

Two full seven-equation turbulence models available in the FUN3D code are evaluated for their ability to improve the computation of challenging mixing flows encountered in aerospace propulsion. These models are the SSG/LRR and Wilcox full second-moment Reynolds stress models. They solve equations for the six components of the Reynolds stress and a seventh equation for the turbulent length scale. Two standard eddy viscosity models are also evaluated for comparison, the Spalart-Allmaras (SA) one-equation model and the Menter Shear Stress Transport (SST-V) two-equation turbulence model. Flow through an axisymmetric reference nozzle is examined at three flow conditions: subsonic unheated, subsonic heated, and near sonic unheated. Centerline profiles of velocity and turbulent kinetic energy and radial profiles of velocity, turbulent kinetic energy and turbulent stresses are examined. Results showed that the SA model did well at predicting the jet potential core length, but over-mixed the downstream flow, whereas the SST-V model over-predicted the potential core length. The Wilcox-model significantly over-predicted the potential core length and under-predicted the mixing and was not well-suited for the jet flows evaluated, however the SSG/LRR Reynolds stress model did well at predicting the mixing rate and mean velocity for all cases examined.

mixing layers↗
NASA NTRS2019

Evaluation of Full Reynolds Stress Turbulence Models in FUN3D for Axisymmetric Jet Flow

Two full seven-equation turbulence models have been implemented into the FUN3D code to evaluate their ability to improve the computation of challenging flows encountered in aerospace propulsion, including mixing flows. These models are the SSG/LRR and Wilcox full second-moment Reynolds stress models. They solve equations for the six components of the Reynolds stress and a seventh equation for the mixing length. Two standard eddy viscosity models are also evaluated for comparison, the Spalart-Allmaras (SA) one-equation model and the Menter Shear Stress Transport (SST-V) two-equation turbulence model. Flow through an axisymmetric reference nozzle is examined at three flow conditions: subsonic unheated, subsonic heated, and near sonic unheated. Centerline profiles of velocity and turbulent kinetic energy and radial profiles of velocity, turbulent kinetic energy and turbulent stresses are examined. characteristics, no significant changes in the downstream flow behavior compared to the baseline case are observed. Furthermore, the total power consumed by the fans for different incoming flow conditions also remain marginally the same. It is hoped that the results, albeit obtained at very low speeds. would serve as a database for this technologically interesting flow field that has not been explored adequately before.

computational fluid dynamics↗
NASA NTRS2019

Using Deep Learning to Automate Inference of Meteoroid Pre-Entry Properties

Properly assessing the asteroid threat depends on the knowledge of asteroid pre-entry parameters, such as size, velocity, mass, density, and strength. Although a vast number of possible bodies to study exist, such characterization of asteroid populations is currently limited by substantial costs associated with space rendezvous missions and rare meteorite findings. As asteroids fragment, ablate, and decelerate in the atmosphere, they emit light detectable by ground-based and space-borne instruments. Earth’s atmosphere, thus, becomes an accessible laboratory that enables impactor risk assessments by facilitating inference of the pre-entry parameters. These asteroid pre-entry conditions are typically deduced by modeling the entry and breakup physics that best reproduce the observed light or energy deposition curve. However, this process requires extensive manual trial-and-error of uncertain modeling parameters. Automating meteor modeling and inference would improve property distributions used in risk assessments and enable population characterization as more light curves become more readily available through the presence of space assets and ground-based camera networks. We previously developed a genetic algorithm to automate meteor modeling by using the fragment-cloud model (FCM) to search for the values of the FCM input parameters (e.g., diameter) that generate energy deposition profiles that match the observed one. Now, we apply deep learning to infer asteroid diameter, velocity, and density from observed energy deposition curves. We trained and tested our neural network models with synthetic energy deposition curves modeled using the FCM rubble pile implementation. We present an application of a 1D convolutional neural network and compare its performance to other attempted regressors and machine learning techniques, such as a fully connected neural network and Random Forest regression, to demonstrate its capabilities. We validate our model weights and approach using the Chelyabinsk, Tagish Lake, Benešov, Košice, and Lost City meteors.

Tarano, Ana Maria↗
DOE OSTI2021

Residential Demand Side Aggregation of Privacy-Conscious Consumers

The increasing adoption of smart meters has led to growing concerns regarding privacy risks stemming from the high resolution measurements. This has given rise to privacy protection techniques that physically alter the consumer's energy load profile, masking private information by using localised devices, e.g. batteries or flexible loads. Meanwhile, there has also been increasing interest in aggregating the distributed energy resources (DERs) of residential consumers to provide services to the grid. In this paper, we propose an online distributed algorithm to aggregate the DERs of privacy-conscious consumers to provide services to the grid, whilst preserving their privacy. Results show that the optimisation solution from the distributed method converges to one close to the optimum computed using an ideal centralised solution method, balancing between grid service provision, consumer preferences and privacy protection. More importantly, the distributed method preserves consumer privacy, and does not require high-bandwidth two-way communications infrastructure.

ancillary services↗
DOE OSTI2025

Density Functional Tight Binding Insights into Plasmonic Silver–Platinum Nanoparticles and Alloys for Enhanced Photocatalysis

Developing accurate and efficient Slater-Koster (SK) tight-binding parameter sets is essential for quantum plasmonic studies of alloyed metal nanoparticles, as conventional time dependent density functional theory (TD-DFT) calculations are computationally prohibitive for larger clusters. In this work, we develop and validate density functional tight binding (DFTB) parameter sets for both ground state (GS-SK) and excited state (ES-SK) calculations to study the structural, electronic, and optical properties of silver (Ag), platinum (Pt), and Ag–Pt nanoalloys. Our investigation of the ground state properties demonstrates that the GS-SK parameters enable DFTB to closely reproduce the electronic structures of platinum clusters with diverse sizes and geometries – showing qualitative agreement with DFT for density of states (DOS) profiles and energy levels. The ES-SK parameters accurately describe excited-state properties compared to TD-DFT reference calculations, including the broad, featureless absorption profiles of Pt that are dominated by interband transitions. Using the ES-SK parameters within a real-time TD-DFTB framework, we compute size-dependent optical absorption spectra of Ag, Pt and Ag-Pt nanocubes containing up to 1099 atoms (size ∼4.18 nm). A detailed study of Ag–Pt and Pt-Ag core–shell nanoparticles shows quenching of the Ag plasmon resonance even at monolayer coverage for Ag-Pt, but not for Pt-Ag. We also show how to define submonolayer Ag-core Pt-shell cubic structures that have similar optical properties to those generated experimentally for much larger particles, which offers potential for describing plasmon-enhanced photocatalysis. Collectively, the GS-SK and ES-SK parameter sets provide an accurate, computationally efficient approach for modeling the complex optical and electronic behavior of noble–transition metal nanostructures and their alloys.

SPR↗
DOE OSTI2022

Developing occupant archetypes within urban low-income housing: A case study in Mumbai, India

Rapid urbanization pressure and poverty have created a push for affordable housing within the global south. The design of affordable housing can have consequences on the thermal (dis)comfort and behaviour of the occupants, hence requiring an occupant-centric approach to ensure sustainability. This paper investigates occupant behaviour within the urban poor households of Mumbai, India and its impact on their thermal comfort and energy use. This study is a first-of-its-kind attempt to explore the socio-demographic characteristics and energy-related behaviour of low-income occupants within Indian context. Three occupant archetypes, Indifferent Consumers; Considerate Savers; and Conscious Conventionals, were identified from the behavioural and psychographic characteristics gathered through a transverse field survey. A two-step clustering approach was adopted for occupant segmentation that highlighted considerable diversity in occupants’ adaptation measures, energy knowledge, energy habits, and their pro-environmental behaviour within similar socio-economic group. Building energy simulation of the representative archetype behaviour estimated up to 37% variations for air-conditioned and up to 8% variation for fan-assisted naturally ventilated housing units during peak summer months. The results from this study establish the significance of occupant factors in shaping energy demand and thermal comfort within low-income housing and pave way for developing occupant-centric building design strategies to serve this marginalized population. The developed low-income occupant archetypes would be useful for architects and energy modelers to generate realistic energy use profiles and improve building performance simulation results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

A New MCNP6 Electron-Photon Transport Validation Test: The Lockwood Energy Deposition Experiment (V.1.0)

This memo announces the availability of a new validation test for quantifying the accuracy of the MCNP6 electron-photon transport algorithm for use in energy-deposition calculations. Specifically, energy-deposition results are compared with the Lockwood energy-deposition experiment. The comparison includes energy-deposition profiles in a variety of different single-element materials including beryllium, aluminum, carbon, copper, iron, molybdenum, tantalum, and uranium for pencil beam electron sources with energies including 0.05-, 0.1-, 0.3-, 0.5, and 1-MeV and angles of incidence including normal, 30°, and 60° off-normal. The purpose of this memo is to discuss the contents of the Lockwood validation directory and to outline the procedure for generating the input files, running the tests, processing the results, and comparing results to the experimental and numerical benchmark. Each step is mostly automated by a makefile that executes the necessary perl script.

74 ATOMIC AND MOLECULAR PHYSICS↗