SEARCH · Engineering Papers

Results for “power modeling and estimation”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 631 records · Page 35

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Hourly Electricity Demand Profiles for Each County in the Contiguous United States

This dataset provides estimated hourly electricity demand for each county in the contiguous United States from 2016-2023. The demand profiles represent the sum of two components: (1) Weighted averages of reported hourly demand profiles for North American Electric Reliability Corporation balancing authority (BA) regions and subregions, scaled to match annual estimates of county-level retail sales and direct use of electricity and weighted by the estimated percentage of county load served by each BA region or subregion. (2) Weighted averages of modeled hourly, county- and sector-level distributed photovoltaic (DPV) capacity factor profiles, scaled to match annual estimates of on-site consumption of DPV-generated electricity for each county and weighted by the percentage of consumption attributable to each sector Annual county-level retail sales are estimated by aggregating utility-reported sales to the state level and allocating the results to counties according to each county's share of state population. Annual county-level direct use is calculated by aggregating power plant-reported direct use values. Annual county-level on-site consumption of DPV-generated electricity is estimated by aggregating utility-reported net metering data to determine the amount of DPV-generated electricity sold back to the grid for each state, subtracting those values from modeled state-level DPV generation estimates, and allocating the results to counties according to each county's share of statewide modeled DPV generation. The open-source Python code used to develop this dataset is available at "Historical Load Data Repository" link below.

14 SOLAR ENERGY↗

DOE OSTI2024

Isotope impact on Alfvén eigenmodes and fast ion transport in DIII-D

Abstract Measurements of beam driven Alfvén Eigenmode (AE) activity in matched deuterium (D) and hydrogen (H) DIII-D plasmas show a dramatic difference in unstable mode activity and fast ion transport for a given injected beam power. The dependence of the unstable AE spectrum in reversed magnetic shear plasmas on beam and thermal species is investigated in the current ramp by varying beam power in a sequence of discharges for fixed thermal and beam species at fixed density. In general, a spectrum of Reversed Shear Alfvén Eigenmodes (RSAEs) and Toroidal Alfvén Eigenmodes (TAEs) are driven unstable with sub-Alfvénic D beam injection while primarily only RSAEs are driven unstable for the H beam cases investigated. Further, for a given beam power, the driven AE amplitude is always reduced with H beams relative to D and for H thermal plasma relative to pure D or mixed D/H plasmas. Estimates of the fast ion stored energy combined with modeling using the hybrid kinetic-MHD code MEGA indicate that the dominant mechanism contributing to the difference between H and D beam drive is the faster classical slowing down of H beam ions relative to D and the resultant lower beam ion pressure. Calculations of the AE induced stored energy deficits using the reduced critical gradient model TGLFEP show quantitative agreement with the observed dependencies on injected power, isotope and minimum safety factor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Estimation of High-Altitude Electromagnetic Pulse Signal Leakage into Power Generation Facilities: Simulations and Measurements

The coupling of early-time high-altitude electromagnetic pulse signals into a power generation facility was investigated. This study encompasses both electromagnetic simulation and on-site experimental efforts that are relevant to shielding effectiveness estimation with a passive technique. As an initial step in understanding the attenuation models involved, simulations were carried out as a function of frequency, building properties, and signal incidence angle. Testing was then performed at the US Department of Energy’s Oak Ridge National Laboratory campus to identify the equipment needed for signal collection and to fine-tune the experimental procedure. Finally, as an application of the models and methods presented, measurements were conducted at a power generation plant to derive the field transfer functions and coupled high-altitude electromagnetic pulse waveforms for various locations within the facility.

42 ENGINEERING↗

DOE OSTI2025

CHARGE-MAP: An integrated framework to study the multicriteria EV charging infrastructure expansion problem

The widespread adoption of electric vehicles (EVs) in recent years has necessitated the development of effective charging infrastructures. However, charging infrastructure expansion is a multifaceted problem that requires careful consideration of the existing infrastructure, spatiotemporal distribution of charging demands, power-grid capacity, and budget constraints. Here, to approach this complex problem, we present CHARGE-MAP, a data-driven simulation-optimization framework, focused on ensuring meaningful charging experience for individual EV owners. CHARGE-MAP integrates three modules: an agent-based simulation module that estimates spatiotemporal distribution of charging demands by modeling EV adopter mobility and charging behavior; an optimization module that determines optimal new charging station/charger locations and capacities, while minimizing expected detour distances and wait-times with a limited number of new stations; and a power module that determines how to connect the stations to the power grid while maintaining its stability. Using the state of Virginia (consisting of 95 counties and 38 independent cities) as a case study, our results show that CHARGE-MAP can meet the demand of ~198,600 predicted EVs with 1,305 new public charging stations and 2,164 new chargers. It reduces average detour distances for charging by 66% and wait-times at stations by 72% compared to the existing infrastructure. Furthermore, transformer capacity requirement analysis reveals that only 1.8% of residential transformers require upgrades, while over 80% of commercial charging locations can be supported with modest transformer infrastructure (25 to 50 kVA). This indicates that targeted investments can facilitate cost-effective EV integration. Consequently, CHARGE-MAP provides policymakers and urban planners with crucial data-driven insights for effective EV charging infrastructure expansion. Sign up for PNAS alerts.

charging infrastructure↗

DOE OSTI2021

Estimating carrying capacity for juvenile salmon using quantile random forest models

Abstract Establishing robust methods and metrics to evaluate habitat quality is critical for the recovery of endangered Pacific salmonids ( Oncorhynchus spp.). A variety of modeling approaches are used for status and trend monitoring of anadromous species throughout the Pacific Northwest, USA, but current methods may fail to capture the complex relationship between fish and habitat and are often limited in predictive power beyond specific watersheds. Further, the focus on species distribution and abundance is not easily manipulated to predict carrying capacity and traditional stock‐recruitment analyses are reliant on long‐term data which are not always available. In this study, we developed a quantile random forest model to provide estimates of habitat carrying capacity for Chinook salmon ( O. tshawytscha ) parr during the summer months, at both the site and watershed scale. Quantile random forest models allow for the consideration of noisy data, correlated variables, and non‐linear relationships: common features in fish–habitat datasets. We leveraged Columbia Habitat Monitoring Program data to select habitat co‐variates and predict capacity at those sites. We also identified a set of globally available attributes to extrapolate capacity estimate predictions throughout wadeable streams within the Columbia River basin. Total capacity estimates for watersheds closely matched estimates from alternative fish productivity models. Carrying capacity estimates based on quantile random forest models, like those presented here, provide managers a framework to guide the identification, prioritization, and development of habitat rehabilitation actions to recover salmon populations.

See, Kevin E.↗

DOE OSTI2023

Storm-DEPART (Damage Estimate Prediction and Recovery Tool)

Storm-DEPART (Damage Estimate Prediction and Restoration Tool): Each year hurricanes and tropical storms in the United States damage critical infrastructure assets, disrupt the services they provide, and cause millions to billions of dollars in economic impacts due to extended recovery times. The Storm-DEPART tool and analytical output enable more impactful data-driven decision-making capabilities and strengthen national-level disaster preparedness, response, and recovery. Storm-DEPART, built through multi-month collaboration between Entergy and INL, combines Entergy’s critical infrastructure inventory data with weather forecasts to predict damages to Electric utility’s assets due to natural disasters and the estimated recovery support needed, including time, materials, and resource allocation. In the event of an approaching hurricane, this innovative solution can assess potential damage to power generation capacity, transmission grids, distribution networks, and communications assets from wind bands, storm surge, and flooding. With more effective predictions, Entergy can more efficiently allocate resources to mitigate impacts and optimize recovery for customers. Storm-DEPART also allows Electric utilities the ability to apply a planning scenario and model expected damage to better inform infrastructure restoration needs leading to enhance system resiliency. The technology is fully transferrable to other electric utilities with the same damage estimating challenges. The INL team is working on the evolution of Storm-DEPART to include ice event damage prediction framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Investigating the mixing between two black hole populations in LIGO-Virgo-KAGRA GWTC-3

Here, we introduce a population model to analyze the mixing between hypothesised power-law and ~ 35M ⊙ Gaussian bump black hole populations in the latest gravitational wave catalog, GWTC 3, estimating their co-location and separation. We find a relatively low level of mixing, $3.1^{+5.0}_{-3.1}$%, between the power-law and Gaussian populations, compared to the percentage of mergers containing two Gaussian bump black holes, $5.0^{+3.2}_{-1.7}$%. Our analysis indicates that black holes within the Gaussian bump are generally separate from the power-law population, with only a minor fraction engaging in mixing and contributing to the $\mathcal{M}$ ~ 14M ⊙ peak in the chirp mass. This leads us to identify a distinct population of Binary Gaussian Black Holes (BGBHs) that arise from mergers within the Gaussian bump. We suggest that current theories for the formation of the massive 35M ⊙ Gaussian bump population may need to reevaluate the underlying mechanisms that drive the preference for BGBHs.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Turbulence and Control of Wind Farms

The dynamics of the turbulent atmospheric boundary layer play a fundamental role in wind farm energy production, governing the velocity field that enters the farm as well as the turbulent mixing that regenerates energy for extraction at downstream rows. Understanding the dynamic interactions among turbines, wind farms, and the atmospheric boundary layer can therefore be beneficial in improving the efficiency of wind farm control approaches. Anticipated increases in the sizes of new wind farms to meet renewable energy targets will increase the importance of exploiting this understanding to advance wind farm control capabilities. This review discusses approaches for modeling and estimation of the wind farm flow field that have exploited such knowledge in closed-loop control, to varying degrees. We focus on power tracking as an example application that will be of critical importance as wind farms transition into their anticipated role as major suppliers of electricity. The discussion highlights the benefits of including the dynamics of the flow field in control and points to critical shortcomings of the current approaches.

Automation & Control Systems↗

DOE OSTI2024

Controlling radioisotope proportions when randomly sampling from Dirichlet distributions in PyRIID

As machine learning models for radioisotope quantification become more powerful, likewise the need for high-quality synthetic training data grows as well. For problem spaces that involve estimating the relative isotopic proportions of various sources in gamma spectra it is necessary to generate training data that accurately represents the variance of proportions encountered. In this report, we aim to provide guidance on how to target a desired variance of proportions which are randomly when using the PyRIID Seed Mixer, which samples from a Dirichlet distribution. We provide a method for properly parameterizing the Dirichlet distribution in order to maintain a constant variance across an arbitrary number of dimensions, where each dimension represents a distinct source template being mixed. We demonstrate that our method successfully parameterizes the Dirichlet distribution to target a specific variance of proportions, provided that several conditions are met. This allows us to follow a principled technique for controlling how random mixture proportions are generated which are then used downstream in the synthesis process to produce the final, noisy gamma spectra.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1979

The critical satellite technical issues of future pervasive broadband low-cost communication networks

The critical technical issues of signal waveform design, projected spacecraft technology, satellite launch options, and satellite cost are discussed for future pervasive broadband communication networks. With DPCM video signal encoding, 32 Mb/s user-to-user data rate per channel, 10% overhead, two orthogonal polarizations, and crosstalk loss limited to 1 dB, TFM permits about 75 channels/GHz of frequency allocation. The BOM (beginning of mission) weight and power of a baseline 400-channel multibeam satellite is about 1800 kg and 5000 W. Each 35 Mb/s channel can support 1 to 10 video channels. The weight and power estimates assume hardened digital logic, composite materials for a multibeam antenna structure, high-efficiency solar cells, batteries, and amplifiers. Based on a cost model for large communication satellites, the total space segment cost of two active satellites and one spare would be about $485 M.

Harvey, R. L.↗

NASA NTRS1980

Satellite power system (SPS) magnetron tube assessment study

Taks performed to extend the data base and to define a technology development program for the magnetron directional amplifier for the SPS are reviewed. These include: (1) demonstrating the tracking of phase and amplitude of the microwave output to phase and amplitude references; (2) expanding the range of power over which the directional amplifier will operate; (3)recognizing the importance of amplitude control in overall system design and in simplifying power conditioning; (4) developing a preliminary design for the overall architecture of the power module; (5) demonstrating magnetron starting using the amplitude control system; (6) mathematically modelling and performing a computerized study of the pyrolytic graphite radiating fin; (7) defining the mass of the magnetic circuit for the SPS tube; (8) noise measurement; (9) achieving harmonic suppression by notch reflection filters; (10) estimating the mass of the transmitting antenna; (11) developing a magnetron package with power generation, phase control, and power condition functions; and (12) projecting magnetron package characteristics.

Source record↗

NASA NTRS1982

Advanced reliability modeling of fault-tolerant computer-based systems

Two methodologies for the reliability assessment of fault tolerant digital computer based systems are discussed. The computer-aided reliability estimation 3 (CARE 3) and gate logic software simulation (GLOSS) are assessment technologies that were developed to mitigate a serious weakness in the design and evaluation process of ultrareliable digital systems. The weak link is based on the unavailability of a sufficiently powerful modeling technique for comparing the stochastic attributes of one system against others. Some of the more interesting attributes are reliability, system survival, safety, and mission success.

Bavuso, S. J.↗

NASA NTRS1987

High temperature electrolyzer/fuel cell power cycle: Preliminary design considerations

A model of a high temperature electrolyzer/fuel cell, hydrogen/oxygen, thermally regenerative power cycle is developed and used to simulate system performance for varying system parameters. Initial estimates of system efficiency, weight, and volume are provided for a one KWe module assuming specific electrolyzer and fuel cell characteristics, both current and future. Specific interest is placed on examining the system responses to changes in device voltage versus current density operating curves, and the associated optimum operating ranges. The performance of a solar-powered, space based system in low earth orbit is examined in terms of the light-dark periods requiring storage. The storage design tradeoffs between thermal energy, electrical energy, and hydrogen/oxygen mass storage are examined. The current technology module is based on the 1000 C solid oxide electrolyzer cell and the alkaline fuel cell. The Future Technology system examines benefits involved with developing a 1800K electrolyzer operating with an advanced fuel cell.

Morehouse, Jeffrey H.↗

NASA NTRS1997

Fault Detection of Rotating Machinery using the Spectral Distribution Function

The spectral distribution function is introduced to characterize the process leading to faults in rotating machinery. It is shown to be a more robust indicator than conventional power spectral density estimates, but requires only slightly more computational effort. The method is illustrated with examples from seeded gearbox transmission faults and an analytical model of a defective bearing. Procedures are suggested for implementation in realistic environments.

Davis, Sanford S.↗

NASA NTRS2016

Photon Counting Detector Array Algorithms for Deep Space Optical Communications

For deep-space optical communications systems utilizing an uplink optical beacon, a single-photon-counting detector array on the flight terminal can be used to simultaneously perform uplink tracking and communications as well as accurate downlink pointing at photon-starved (pW/sq. m) power levels. In this paper, we discuss concepts and algorithms for uplink signal acquisition, tracking, and parameter estimation using a photon-counting camera. Statistical models of detector output data and signal processing algorithms are presented, incorporating realistic effects such as Earth background and detector/readout blocking. Analysis and simulation results are validated against measured laboratory data using state-of-the-art commercial photon-counting detector arrays, demonstrating sub-microradian tracking errors under channel conditions representative of deep space optical links.

beacon tracking↗

NASA NTRS2020

ZTF Early Observations of Type Ia Supernovae. II. First Light, the Initial Rise, and Time to Reach Maximum Brightness

While it is clear that Type Ia supernovae (SNe) are the result of thermonuclear explosions in C/O white dwarfs (WDs), a great deal remains uncertain about the binary companion that facilitates the explosive disruption of the WD. Here, we present a comprehensive analysis of a large, unique data set of 127 SNe Ia with exquisite coverage by the Zwicky Transient Facility (ZTF). High-cadence (six observations per night) ZTF observations allow us to measure the SN rise time and examine its initial evolution. We develop a Bayesian framework to model the early rise as a power law in time, which enables the inclusion of priors in our model. For a volume-limited subset of normal SNe Ia, we find that the mean power-law index is consistent with 2 in the r(ZTF)-band (a(r) = 2.01 ± 0.02), as expected in the expanding fireball model. There are, however, individual SNe that are clearly inconsistent with a(r) = 2. We estimate a mean rise time of 18.9 days (with a range extending from ∼15 to 22 days), though this is subject to the adopted prior. We identify an important, previously unknown, bias whereby the rise times for higher redshift SNe within a flux-limited survey are systematically underestimated. This effect can be partially alleviated if the power-law index is fixed to α = 2, in which case we estimate a mean rise time of 21.7 days (with a range from ∼18 to 23 days). The sample includes a handful of rare and peculiar SNe Ia. Finally, we conclude with a discussion of lessons learned from the ZTF sample that can eventually be applied to observations from the Vera C. Rubin Observatory.

A. A. Miller↗

DOE OSTI2020

System and method for modeling and forecasting cyclical demand systems with dynamic controls and dynamic incentives

Systems and methods for modeling and forecasting cyclical demand systems in the presence of dynamic control or dynamic incentives. A method for modeling a cyclical demand system comprises obtaining historical data on one or more demand measurements over a plurality of demand cycles, obtaining historical data on incentive signals over the plurality of demand cycles, constructing a model using the obtained historical data on the one or more demand measurements and the incentive signals, wherein constructing the model comprises specifying a state-space model, specifying variance parameters in the model, and estimating unknown variance parameters.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2015

Architecture, Voltage, and Components for a Turboelectric Distributed Propulsion Electric Grid (AVC-TeDP)

The purpose of this effort was to advance the selection, characterization, and modeling of a propulsion electric grid for a Turboelectric Distributed Propulsion (TeDP) system for transport aircraft. The TeDP aircraft would constitute a miniature electric grid with 50 MW or more of total power, two or more generators, redundant transmission lines, and multiple electric motors driving propulsion fans. The study proposed power system architectures, investigated electromechanical and solid state circuit breakers, estimated the impact of the system voltage on system mass, and recommended DC bus voltage range. The study assumed an all cryogenic power system. Detailed assumptions within the study include hybrid circuit breakers, a two cryogen system, and supercritical cyrogens. A dynamic model was developed to investigate control and parameter selection.

power↗