Coronal Structure at the Solar Eclipse of September 22, 1968 - Prediction and Observation
Prediction and observation compared for coronal structure at solar eclipse of 22 Sept. 1968
Schatten, K. H.↗
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Results for “solar prediction”
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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Posterior Regularized Bayesian Neural Network
Traditional NNs often lack the ability for uncertainty quantification. Bayesian NNs(BNNs) could help measure the confidence level by using distributions in NNs modeling. Besides, knowledge is commonly available and could improve the performance of BNNs if it can be properly incorporated. In this work, we propose a novel Posterior-Regularized BNN(PR-BNN) model by incorporating soft and hard constraints as a posterior regularization term. We also propose an augmented Lagrangian method and stochastic optimization algorithm for efficient updating via Monte Carlo sampling. The simulations and case studies in solar energy prediction have shown the performance improvement of the proposed model over traditional BNNs.
14 SOLAR ENERGY↗
Predictive and Cooperative Voltage Control with Probabilistic Load and Solar Generation Forecasting
This paper proposes predictive cooperative voltage control method in a power system with high penetration of photovoltaic (PV) units. Cooperative distributed control of the reactive power output of PV inverters is coordinated with operation of voltage regulators (VRs) to maintain system voltages within an appropriate bandwidth. Probabilistic forecasting of the solar power generation and the loads is applied to estimate voltage changes which, in turn, are used to set the VR tap positions for preventing large voltage fluctuations with the lowest risk considering the voltage distribution estimation. The fine tuning of voltage adjustment is achieved by cooperative control of PV inverters to maintain a uniform voltage profile across the system. The proposed method is tested on the modified IEEE 123-node test feeder with high PV penetration using real insolation data and with constant loads replaced by several different load profiles. Simulation results demonstrate the effectiveness of the coordinated approach for voltage control with cooperative PV and predictive VR controls taking into account probabilistic load and solar power forecasts.
Cooperative Control↗
EUVAC: A solar EUV flux model for aeronomic calculations
This paper presents a new solar Extreme Ultraviolet (EUV) flux model for aeronomic calulations (EUVAC), which is based on the measured F74113 solar EUV reference spectrum. The model provides fluxes in the 37 wavelength bins that are in widespread use. This paper also presents cross sections to be used with the EUVAC flux model to calculate photoionization rates. The flux scaling for solar activity is accomplished using a proxy-based on the F10.7 index and its 81-day average together with the measured solar flux variation from the EUVS instrument on the Atmosphere Explorer E satellite. This new model produces 50-575 A integrated EUV fluxes in good agreement with rocket observations. The solar cycle variation of the chromospheric fluxes agrees well with the measured variation of the Lyman alpha flux between 1982 and 1988. In addition, the theoretical photoelectron fluxes, calculated using the new EUV flux model, are in good agreement with the solar minimum photoelectron fluxes from the Atmosphere Explorer E satellite and also with the solar maximum photoelectron fluxes from the Dynamics Explorer satellite. Its relative simplicity coupled with its ability to reproduce the 50-575 A solar EUV flux as well as the measured photoelectron spectrum makes the model well suited for aeronomic applications. However, EUVAC is not designed to accurately predict the solar flux variability for numerous individual lines.
Richards, P. G.↗
Cosmic-ray record in solar system matter
The interaction of galactic cosmic rays (GCR) and solar cosmic rays (SCR) with bodies in the solar system is discussed, and what the record of that interaction reveals about the history of the solar system is considered. The influence of the energy, charge, and mass of the particles on the interaction is addressed, showing long-term average fluxes of solar protons, predicted production rates for heavy-nuclei tracks and various radionuclides as a function of depth in lunar rock, and integral fluxes of protons emitted by solar flares. The variation of the earth's magnetic field, the gardening of the lunar surface, and the source of meteorites and cosmic dust are studied using the cosmic ray record. The time variation of GCR, SCR, and VH and VVH nuclei is discussed for both the short and the long term.
Reedy, R. C.↗
Asymptotic Giant Branch stars as a source of short-lived radioactive nuclei in the solar nebula
We carried out a theoretical evaluation of the contribution of Asymptotic Giant Branch (AGB) stars to some short-lived (10(exp 6) less than or equal to Tau-bar less than or equal to 2 x 10(exp 7) yr) isotopes in the Interstellar Medium (ISM) and in the early solar system using stellar model calculations for thermally pulsing evolutionary phases of low-mass stars. The yields of s-process nuclei in the convective He-shell for different neutron exposures tau(sub 0) were obtained, and AGB stars were shown to produce several radioactive nuclei (especially Pd-107, Pb-205, Fe-60, Zr-93, Tc-99, Cs-135, and Hf-182) in diferent amounts. Assuming either contamination of the solar nebula from a single AGB star or models for continuous injection and mixing from many stars into the ISM, we calculate the ratios of radioactive to stable nuclei at the epoch of the Sun's formation. The dilution factor between the AGB ejecta and the early solar system matter is obtained by matching the observed Pd-107/Pd-108 and depends on the value of tau(sub 0). It is found that small masses M(sub He) of He-shell material (10(exp -4)-10(exp -7) solar mass) enriched in s-process nuclei are sufficient to contaminate 1 solar mass of the ISM to produce the Pd-107 found in the early solar system. Predictions are made for all of the other radioactive isotopes. The optimal model to explain several observed radioactive species at different states of the proto-solar nebula involves a single AGB star with a low neutron exposure (tau(sub 0) = 0.03 mbarn(sup -1)) which contaminated the cloud with a dilution factor of M(sub He)/solar mass approximately 1.5 x 10(exp -4). This will also contribute newly synthesized stable s-process nuclei in the amount of approximately 10(exp -4) of their abundances already present in the proto-solar cloud. Variations in the degree of homogenization (approximately 30%) of the injected material may account for some of the small general isotopic anomalies found in meteorites. It is also found that Fe-60 is produced in small but significant quantities that may be sufficient to explain the observations if the time elapsed delta from the contamination of the ISM to the formation of protoplanetary bodies is not higher than delta = 5 x 10(exp 6) yr. If delta is longer, up to 10 x 10(exp 6) yr, this would require the single AGB star to experience enhanced neutron densities (n(sub n) approximately 3 x 10(exp 9)n/cu cm) in the s-processing zone in order to compensate for the branching at Fe-59. The alternative model of long-term continuous ejection of matter from many AGB stars does not appear to match the observations. We also estimate the Al-26 production from the H-shell and find that the Al-26 abundance in the early solar system may be readily explained in a self-consistent manner. Moreover, Al-26 from AGB stars may contribute substantially to the galactic Al-26 gamma-source, while no significant gamma-flux from Co-60 (deriving from Fe-60 decay) is to be expected.
Wasserburg, G. J.↗
Improving the prediction of DNI with physics-based representation of all-sky circumsolar radiation
Direct normal irradiance (DNI) is often interpreted differently in ground measurements and forecasts using numerical weather prediction (NWP) models, leading to substantial bias in DNI forecasting especially under cloudy-sky conditions. To mitigate the bias, we use the Fast All-sky Radiation Model for Solar applications with DNI (FARMS-DNI) to conduct physics-based simulations of solar radiation in the circumsolar region. The DNI is quantified using the sum of the radiation along the sun direction and the scattered radiation within the circumsolar region. FARMS-DNI is coupled with the Weather Research and Forecasting model with solar extensions (WRF-Solar) to predict day-ahead DNI in 9-km pixels over an extended domain covering the contiguous United States. The DNI forecasts for the entire year of 2018 are validated using surface-based observations at the Atmospheric Radiation Measurement (ARM) and Surface Radiation Budget Network (SURFRAD) sites and a satellite-based solar radiation product developed by the procedure of the National Solar Radiation Data Base (NSRDB). The results show that the WRF-Solar coupled with the conventional Beer-Bouguer-Lambert law underestimes the overall DNI forecasts by 30%-60%, which is a joint effect of the uncertainties in computing the circumsolar radiation and forecasting cloud properties. This bias is significantly reduced by using FARMS-DNI.
14 SOLAR ENERGY↗
Flat-Plate Solar-Collector Performance Evaluation with a Solar Simulator as a Basis for Collector Selection and Performance Prediction
The use of a solar simulator for performance determination permits collector testing under standard conditions of wind, ambient temperature, flow rate and sun. The performance results determined with the simulator have been found to be in good agreement with outdoor performance results. The measured thermal efficiency and evaluation of 23 collectors are reported which differ according to absorber material (copper, aluminum, steel), absorber coating (nonselective black paint, selective copper oxide, selective black nickel, selective black chrome), type of glazing material (glass, Tedlar, Lexan, antireflection glass), the use of honeycomb material and the use of vacuum to prevent thermal convection losses. The collectors were given performance rankings based on noon-hour solar conditions and all-day solar conditions. The determination with the simulator of an all-day collector performance was made possible by tests at different incident angles. The solar performance rankings were made based on whether the collector is to be used for pool heating, hot water, absorption air conditioning, heating, or for a solar Rankine machine.
Simon, F. F.↗
Predicting the arrival times of solar particles
A procedure has been developed to generate a computerized time-intensity profile of the solar proton intensity expected at the earth after the occurrence of a significant solar flare on the sun. This procedure is a combination of many pieces of independent research and theoretical results. Many of the concepts used were first reported by Smart and Shea (1979) and are summarized by Smart and Shea (1985). Extracts from the general procedure that relate to predicting the expected onset time and time of maximum at the earth after the occurrence of a solar flare are presented.
Smart, D. F.↗
Solar Activity Across the Scales: From Small-Scale Quiet-Sun Dynamics to Magnetic Activity Cycles
Observations as well as numerical and theoretical models show that solar dynamics is characterized by complicated interactions and energy exchanges among different temporal and spatial scales. It reveals magnetic self-organization processes from the smallest scale magnetized vortex tubes to the global activity variation known as the solar cycle. To understand these multiscale processes and their relationships, we use a two-fold approach: 1) realistic 3D radiative MHD simulations of local dynamics together with high resolution observations by IRIS, Hinode, and SDO; and 2) modeling of solar activity cycles by using simplified MHD dynamo models and mathematical data assimilation techniques. We present recent results of this approach, including the interpretation of observational results from NASA heliophysics missions and predictive capabilities. In particular, we discuss the links between small-scale dynamo processes in the convection zone and atmospheric dynamics, as well as an early prediction of Solar Cycle 25.
Solar↗
Solar Activity Across the Scales: from Small-Scale Quiet-Sun Dynamics to Magnetic Activity Cycles
Observations as well as numerical and theoretical models show that solar dynamics is characterized by complicated interactions and energy exchanges among different temporal and spatial scales. It reveals magnetic self-‐organization processes from the smallest scale magnetized vortex tubes to the global activity variation known as the solar cycle. To understand these multiscale processes and their relationships, we use a two-fold approach: 1) рealistic 3D radiative MHD simulations of local dynamics together with high-‐resolution observations by IRIS, Hinode, and SDO; and 2) modeling of solar activity cycles by using simplified MHD dynamo models and mathematical data assimilation techniques. We present recent results of this approach, including the interpretation of observational results from NASA heliophysics missions and predictive capabilities. In particular, we discuss the links between small-‐scale dynamo processes in the convection zone and atmospheric dynamics, as well as an early prediction of Solar Cycle 25.
Magneti↗
An empirical polytrope law for solar wind thermal electrons between 0.45 and 4.76 AU: Voyager 2 and Mariner 10
Empirical evidence is presented that solar wind thermal electrons obey a polytrope law with polytrope index gamma = 1.175 plus or minus 0.03. The Voyager 2 and Mariner 10 data used as evidence are compared and discussed. The theoretical predictions that solar wind thermal electrons in the asymptotic solar wind should obey a polytrope law with polytrope index gamma = 1.16 plus or minus. The widespread impressions in the literature that solar wind electrons behave more like an isothermal than adiabatic gas, and the arguments that Coulomb collisions are the dominant stochastic process shaping observed electron distribution functions in the solar wind are reexamined, reviewed and evaluated. The assignment of the interplanetary potential as equal to approximately seven times the temperature of the thermal electrons is discussed.
Sittler, E. C., Jr.↗
Effects of Increasing Drag on Conjunction Assessment
Conjunction Assessment Risk Analysis relies heavily on the computation of the Probability of Collision (Pc) and the understanding of the sensitivity of this calculation to the position errors as defined by the covariance. In Low Earth Orbit (LEO), covariance is predominantly driven by perturbations due to atmospheric drag. This paper describes the effects of increasing atmospheric drag through Solar Cycle 24 on Pc calculations. The process of determining these effects is found through analyzing solar flux predictions on Energy Dissipation Rate (EDR), historical relationship between EDR and covariance, and the sensitivity of Pc to covariance. It is discovered that while all LEO satellites will be affected by the increase in solar activity, the relative effect is more significant in the LEO regime around 700 kilometers in altitude compared to 400 kilometers. Furthermore, it is shown that higher Pc values can be expected at larger close approach miss distances. Understanding these counter-intuitive results is important to setting Owner/Operator expectations concerning conjunctions as solar maximum approaches.
Frigm, Ryan Clayton↗
Solar-induced variations of environment affecting manned space flight and spacecraft operations
Estimates of short and long term solar activity are required for calculating variations in the environment with regard to spacecraft charging, radiation effects, and orbital lifetime. Correlations appear to exist between the time of solar activity and the time of operational anomalies due to electrical discharges when the dielectric surfaces of geosynchronous spacecraft are charged by interaction with the ambient plasma to levels above breakdown voltage. An ability to predict the solar induced variation variability of the plasmas could permit refinement of design criteria. The influence of the radiation on spacecraft materials, systems, and manned operations is summarized. Solar radition effects on the orbital altitude atmospheric density environment and spacecraft lifetimes are also considered.
Johnson, W. G.↗
Screening of solar cells
Because solar cells in a production batch are not identical, screening is performed to obtain similar cells for aggregation into arrays. A common technique for screening is based on a single operating point of the I-V characteristic of the cell, usually the maximum power point. As a result, inferior cell matching may occur at the actual operating points. Screening solar cells based on the entire I-V characteristic will inherently result in more similar cells in the array. An array consisting of more similar cells is likely to have better overall characteristics and more predictable performance. Solar cell screening methods and cell ranking are discussed. The concept of a mean cell is defined as a cell 'best' representing all the cells in the production batch. The screening and ranking of all cells are performed with respect to the mean cell. The comparative results of different screening methods are illustrated on a batch of 50 silicon cells of the Space Station Freedom.
Appelbaum, J.↗
A Hybrid Reinforcement Learning-MPC Approach for Distribution System Critical Load Restoration
This paper proposes a hybrid control approach for distribution system critical load restoration, combining deep reinforcement learning (RL) and model predictive control (MPC) aiming at maximizing total restored load following an extreme event. RL determines a policy for quantifying operating reserve requirements, thereby hedging against uncertainty, while MPC models grid operations incorporating RL policy actions (i.e., reserve requirements), renewable (wind and solar) power predictions, and load demand forecasts. We formulate the reserve requirement determination problem as a sequential decision-making problem based on the Markov Decision Process (MDP) and design an RL learning environment based on the OpenAI Gym framework and MPC simulation. The RL agent reward and MPC objective function aim to maximize and monotonically increase total restored load and minimize load shedding and renewable power curtailment. The RL algorithm is trained offline using a historical forecast of renewable generation and load demand. The method is tested using a modified IEEE 13-bus distribution test feeder containing wind turbine, photovoltaic, microturbine, and battery. Case studies demonstrated that the proposed method outperforms other policies with static operating reserves.
distribution system↗
Inclusion of Radiation Environment Variability for Reliability Estimates for SiC Power MOSFETs
Variability of the solar energetic particle environment is investigated for single-event-burnout reliability of silicon-carbide power metal-oxide-semiconductor field effect transistors. A probabilistic assessment of failure evaluates the benefits of de-rating voltage, shielding, and mission length. The Prediction of Solar particle Yields for Characterizing Integrating Circuits code is used to calculate a cumulative density function for the fluence of the environment. The lethal ion method is then used to determine what proportion of the environment will cause single-event-burnout. The operating voltage determines the lowest linear-energy-transfer particle that will cause single-event-burnout and that should be included in the environment distribution. The shielding and mission length also determine the final environment distribution of the mission fluence. Through calculating the reliability for different operating voltages, shielding, and mission length for a specific device, it is shown that shielding thickness and operating voltage have a large effect on reliability and can be traded off during the design.
Heavy ion↗
A Hybrid Reinforcement Learning-MPC Approach for Distribution System Critical Load Restoration: Preprint
This paper proposes a hybrid control approach for distribution system critical load restoration, combining deep reinforcement learning (RL) and model predictive control (MPC) aiming at maximizing total restored load following an extreme event. RL determines a policy for quantifying operating reserve requirements, thereby hedging against uncertainty, while MPC models grid operations incorporating RL policy actions, i.e., the reserve requirement, renewable (wind and solar) power predictions, and load demand forecasts. We formulate the reserve requirement determination problem as a sequential decision making problem based on the Markov Decision Process (MDP) and design an RL learning environment based on the OpenAI Gym framework and MPC. The RL agent reward and MPC objective function aim to maximize and monotonically increase total restored load and minimize load shedding and renewable power curtailment. The RL algorithm is trained off-line using historical forecast of renewable generation and load demand. The method is tested using a modified IEEE 13-bus distribution test feeder containing wind turbine, photovoltaic, microturbine and battery. Case studies demonstrated that the proposed method outperforms other operating reserve determination methods.
distribution system↗